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Lur Epelde Sierra
EVALUATION OF THE EFFICIENCY OF METALPHYTOREMEDIATION PROCESSES WITH
MICROBIOLOGICAL INDICATORSOF SOIL HEALTH
Vitoria-Gasteiz, 2010
TESIS DOCTORALESN.º 71
Evaluation of thE EfficiEncy of mEtalphytorEmEdiation procEssEs
with microbiological indicatorsof soil hEalth
Lur Epelde Sierra
Universidad del País vasco
First published: 1st november 2010
Edition: 55 copies
© Administration of the Autonomous Community of the Basque Country Environment, Territorial Planning, Agriculture and Fishing Department
Internet: www.euskadi.net
Published: Eusko Jaurlaritzaren Argitalpen Zerbitzu Nagusia Servicio Central de Publicaciones del Gobierno Vasco Donostia-San Sebastián, 1 - 01010 Vitoria-Gasteiz
Printed by: Eusko Printing Service, S.L. www.eps-grupo.com
ISBN: 978-84-457-3092-8
Legal record: VI 479-2010
A catalogue record of this book is available in the catalogue of the General Library of the Basque Governement: <http://www.euskadi.net/ejgvbiblioteka>.
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LABURPENA
Gure gizartearen biziraupen eta ongizatea, nahitaez, lurzoru ekosistemaren osasunari lotuta
daude. Zoritxarrez, lurzoruaren kutsaduraren arazoa maila kezkagarrira iritsi da azken
hamarkadetan, baliabide honen funtzionaltasun eta iraunkortasuna kolokan jarriaz.
Fitoerremediazioa kostu ekonomiko baxua, ingurugiroarekiko begirunea eta gizartearen
aldetik harrera ona dituen teknologia izateaz gain, lurzoru kutsatuen erremediaziorako
potentzial handikoa da. Nabarmendu beharra dago edozein prozesu fitoerremediatzaileren
gorengo helburua ez dela izan behar kutsatzailea ezabatzea soilik, baizik eta batez ere
lurzoruaren osasuna berreskuratzea; baliabide honek bere funtzioak modu iraunkorrean
burutzeko duen ahalmena berreskuratzea, alegia, ikuspegi antropozentriko zein
ekozentrikotik begiratuta. Lurzoruaren propietate biologikoek - komunitate mikrobianoen
biomasa, aktibitate eta biodibertsitatearekin zerikusia dutenek, batez ere - potentzial handia
dute lurzoru ekosistemaren osasunaren bioadierazle gisa. Lan honen helburua metalekin
kutsaturiko lurzoruak fitoerremediatzeko estrategia desberdinen ebaluazioa burutzea da,
horretarako lurzoru ekosistemaren osasunaren adierazle gisa potentzial handia duten
lurzoruaren hainbat propietate mikrobiologiko baliatuz.
Gure emaitzek adierazten dutenez, metalek sorturiko kutsadurak lurzoru
ekosistemaren osasunean eragin negatiboa izaten du sarritan eta eragin negatibo hau
praktika fitoerremediatzaileak erabiliz hein handi batean edota guztiz lehengoratu daiteke.
Meatze-inguruneetan aurkitzen diren landareak lurzoruko metal-kontzentrazio altuak
jasateko gai dira, eta fitoerauzketa zein fitoegonkortze prozesuetarako hautagai ezin hobeak
dira. Hain zuzen: (i) Zn eta Cd-aren fitoerauzketa jarraiturako, Thlaspi caerulescens
landarearen “Lanestosa” ekotipoaren izaera hipermetatzailea baieztatu da, eta hortaz,
fitoerauzketarako duen ahalmena (era berean, metalen fitoerauzketarako basartoa bezalako
biomasa altuko laboreak erabiltzea ere baliozko izan daiteke); (ii) kelatzaile bidezko
fitoerauzketari dagokionez, EDDSak EDTAk baino ahalmen txikiagoa du karduan Pb-aren
metaketa eragiteko (bestalde, EDDSak toxikotasun baxuagoa du lurzoruko komunitate
mikrobianoentzako); metalen kimiofitoegonkortzeari buruz, medeapen sintetiko eta
organikoen erabilerak Zn, Pb eta Cd-aren toxikotasuna murrizten du, Lolium perenne-aren
hazkuntza osasuntsua ahalbidetuz; eta (iv), metalak jasateko estrategia desberdinak dituzten
landare pseudometalofitoen konbinazioen erabilerak etorkizun handiko aukera dirudi
metalekin kutsaturiko lurzoruen birlandatze/fitoerremediaziorako. Azkenik, lurzoruko
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propietate mikrobiologikoen sentsibilitate, asalduren aurrean azkar erantzuteko ahalmen eta
izaera bateratzaileari esker, tresna hobezinak dira prozesu fitoerremediatzaileen efizientzia
ebaluatzeko.
RESUMEN
La supervivencia y el bienestar de nuestra sociedad están inextricablemente ligados a
la salud del ecosistema edáfico. Por desgracia, en las últimas décadas, el problema de la
contaminación del suelo ha alcanzado una magnitud alarmante, afectando sin duda
gravemente a la funcionalidad y sostenibilidad de este recurso. La fitorremediación es una
fitotecnología barata, medioambientalmente respetuosa, socialmente aceptada, y de gran
potencial para la remediación de suelos contaminados. Es preciso enfatizar que el objetivo
último de cualquier proceso fitorremediador no debe ser exclusivamente eliminar el
contaminante, sino sobre todo recuperar la salud del suelo, entendida ésta como la
capacidad de este recurso para realizar sus funciones, desde una doble perspectiva
antropocéntrica-ecocéntrica, de forma sostenible. Las propiedades biológicas del suelo, en
especial aquellas relacionadas con la biomasa, actividad y biodiversidad de las comunidades
microbianas edáficas, presentan un gran potencial como herramientas bioindicadoras de la
salud del ecosistema edáfico. El objetivo de este trabajo fue evaluar la eficacia de distintas
estrategias fitorremediadoras de suelos contaminados con metales mediante la utilización
de una gama diversa de propiedades microbiológicas del suelo con potencial indicador de la
salud del ecosistema edáfico.
Nuestros resultados indican que frecuentemente la contaminación por metales tiene
un impacto negativo considerable sobre la salud del ecosistema edáfico, la cual puede ser
parcial o totalmente restablecida mediante prácticas fitorremediadoras. Las plantas
presentes en entornos mineros se caracterizan por su tolerancia a niveles elevados de
metales en el suelo y son candidatas ideales para procesos fitoextractores y
fitoestabilizadores. Concretamente: (i) para la fitoextración en continuo de Zn y Cd, el
ecotipo “Lanestosa” de Thlaspi caerulescens ha confirmado su carácter hiperacumulador y,
por ende, su capacidad fitoextractora (si bien la utilización de cultivares de elevada biomasa
como el sorgo puede ser una estrategia igualmente válida para fitoextraer metales); (ii) en lo
concerniente a la fitoextracción inducida por quelantes, el EDDS tiene menor capacidad
que el EDTA para inducir la acumulación de Pb en cardo (por otra parte, el EDDS es
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menos tóxico para las comunidades microbianas edáficas); (iii) en relación con la
quimiofitoestabilización de metales, la adición de enmiendas sintéticas y orgánicas reduce la
toxicidad del Zn, Pb y Cd, permitiendo el establecimiento de una cubierta sana de Lolium
perenne; y (iv) la opción de utilizar combinaciones de plantas pesudometalofitas con distintas
estrategias de tolerancia a metales para la revegetación/fitorremediación de suelos
contaminados con metales parece altamente prometedora. Por último, la sensibilidad,
rapidez de respuesta frente a perturbaciones y carácter integrador de las propiedades
microbiológicas del suelo hacen de ellas herramientas bioindicadoras óptimas para la
evaluación de la eficiencia de procesos fitorremediadores.
ABSTRACT
The survival and well-being of our society are inextricably linked to the health of the
soil ecosystem. Unfortunately, in the last decades, soil pollution has become a huge
environmental problem that is at the moment seriously affecting the health and
sustainability of our soils. Phytoremediation is considered a cost-effective, environmentally-
friendly, socially accepted phytotechnology of great potential for the remediation of
polluted soils. It must be highlighted that the ultimate goal of any phytoremediation
process must be not only to remove the pollutant from the soil but, most importantly, to
recover soil health, i.e. the capacity of the soil to sustainably carry out its functions from an
anthropocentric and ecocentric point of view. The soil biological properties, particularly
those related to the biomass, activity and diversity of the soil microbial communities, have
great potential as bioindicators of soil health. The main objective of the current work was
to assess the efficiency of different phytoremediation strategies of metal polluted soils
through the determination of a variety of soil microbiological properties with potential as
bioindicators of soil health.
Our results indicate that metal pollution frequently has a considerable adverse impact
on soil health; such health can be partially or totally recovered through phytoremediation
practices. Plants growing in mining sites are characterized by their tolerance to high levels
of soil metals and are, consequently, ideal candidates for phytoextraction and
phytostabilization processes. In particular: (i) for continuous Zn and Cd phytoextraction,
the local Lanestosa ecotype of Thlaspi caerulescens has confirmed its hyperaccumulator
condition as well as its capacity for phytoextraction (nonetheless, the utilization of high
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biomass cultivars such as sorghum can be an equally valid strategy to phytoextract metals);
(ii) regarding chelate-induced phytoextraction, EDDS has a lower capacity than EDTA to
induce Pb accumulation in cardoon (on the other hand, EDDS is less toxic for the soil
microbial communities); (iii) concerning chemophytostabilization, the addition of synthetic
and organic amendments reduces the toxicity caused by Zn, Pb and Cd, thus allowing the
establishment of a healthy Lolium perenne cover; and (iv) the possibility of using
combinations of pseudometallophytes with different strategies of metal tolerance for the
revegetation/phytoremediation of metal polluted soils appears highly promising. Finally,
the sensitivity, rapid response and integrative character of the soil microbiological
properties make them invaluable bioindicators for the assessment of the efficiency of
phytoremediation processes.
Índice
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1. GENERALINTRODUCCTION/INTRODUCCIÓNGENERAL....................................... 1.1. Heavy metal phytoremediation: microbial indicatos of soil health for the
assessmentofremediationefficiency............................................................................. . 1.1.1... Microbial.indicators.of.soil.health....................................................................... . 1.1.2... Heavy.metal.phytoremediation............................................................................ . . 1.1.2.1... Continuous.metal.phytoextraction....................................................... . . 1.1.2.2... Chelate.induced.phytoextraction........................................................ .. . . 1.1.2.3... Phytostabilization................................................................................ . 1.1.3... Conclusions......................................................................................................... 1.2. Contextoyplanteamientodeltrabajodelatesis......................................................... . 1.2.1... Tradición.minera.en.la.CAPV............................................................................. . 1.2.2... Contaminación.del.suelo.en.la.CAPV................................................................. . 1.2.3... Aspectos.legales.de.la.contaminación.del.suelo.................................................. . 1.2.4... Recuperación.de.emplazamientos.contaminados.en.la.CAPV............................ . 1.2.5... Situación.de.la.fitorremediación.a.nivel.global..................................................
2. HIPOTESIAETAHELBURUAK........................................................................................... 2.1. Hipotesia.......................................................................................................................... 2.2. Helburuorokorra........................................................................................................... 2.3. Helburuespezifikoak.....................................................................................................2. HIPÓTESISYOBJETIVOS.................................................................................................... 2.1. Hipótesis.......................................................................................................................... 2.2. Objetivogeneral.............................................................................................................. 2.3. Objetivosespecificos......................................................................................................2. HYPOTHESISANDOBJECTIVES....................................................................................... 2.1. Hypothesis....................................................................................................................... 2.2. Mainobjective................................................................................................................. 2.3. Specificobjectives..........................................................................................................
3. ESCENARIOYPROCEDIMIENTOSGENERALES.......................................................... 3.1. Escenariodeestudioycondicionesdecultivo.............................................................. . 3.1.1... Escenario............................................................................................................. . 3.1.2.. Condiciones.de.cultivo........................................................................................ 3.2. Parámetrosanalíticos..................................................................................................... . 3.2.1... Propiedades.físico-químicas.y.microbiológicas.con.potencial.indicador.de.la.
salud.del.ecosistema.edáfico................................................................................ . . 3.2.1.1. Propiedades microbiológicas con potencial indicador de la salud
del ecosistema edáfico ....................................................................... 3.2.1.2. Propiedades físico-químicas con potencial indicador de la salud del
ecosistema edáfico............................................................................... . 3.2.2... Parámetros.fisiológicos.de.plantas....................................................................... . 3.2.3... Concentración.de.metales.en.suelo.y.planta.......................................................
4. INTERACTIONS BETWEEN PLANT AND RHIZOSPHERE MICROBIALCOMMUNITIESINAMETALLIFEROUSSOIL...............................................................
. 4.1. Abstract..........................................................................................................................
. 4.2. Introduction...................................................................................................................
. 4.3. Materialsandmethods..................................................................................................
. . 4.3.1... Field.characterization.........................................................................................
. . 4.3.2... Plant.parameters.................................................................................................
. . 4.3.3... Soil.microbial.and.physicochemical.parameters................................................
. . 4.3.4... Statistical.analysis...............................................................................................
. 4.4. Results.............................................................................................................................
. . 4.4.1... Soil.microbial.and.physicochemical.properties..................................................
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. . 4.4.2... Interactions.between.plants.and.soil.microbial.and.physicochemical.properties
. . 4.4.3... Plant.parameters.................................................................................................
. 4.5. Discussion.......................................................................................................................
. 4.6. Conclusions....................................................................................................................
5. FUNCTIONAL DIVERSITY AS INDICATOR OF THE RECOVERY OF SOILHEALTH DERIVED FROM Thlaspi caerulescens GROWTH AND METALPHYTOEXTRACTION...........................................................................................................
. 5.1. Abstract..........................................................................................................................
. 5.2. Introduction...................................................................................................................
. 5.3. Materialsandmethods..................................................................................................
. . 5.3.1... Soil.characterization.and.contamination.............................................................
. . 5.3.2... Experimental.design.and.plant.growth...............................................................
. . 5.3.3... Soil.physicochemical.parameters.and.metal.determination...............................
. . 5.3.4... Soil.biological.parameters..................................................................................
. . 5.3.5... Plant.physiological.parameters.and.metal.accumulation....................................
. . 5.3.6... Statistical.analysis...............................................................................................
. 5.4. Results.............................................................................................................................
. . 5.4.1... Thlaspi.caerulescens.growth.and.physiological.parameters...............................
. . 5.4.2... Thlaspi.caerulescens.metal.uptake.....................................................................
. . 5.4.3... Soil.physicochemical.parameters.......................................................................
. . 5.4.4... Soil.enzyme.activities.........................................................................................
. . 5.4.5... Community-level.physiological.profiles............................................................
. 5.5. Discussion.......................................................................................................................
. . 5.5.1... Metal.phytoextraction.........................................................................................
. . 5.5.2... Impact.of.metal.pollution.on.biological.indicators.of.soil.health.......................
. . 5.5.3... Effect. of. T.. caerulescens. growth. and. metal. phytoextraction. on. biological.indicators.of.soil.health.......................................................................................
. 5.6. Conclusions....................................................................................................................
6. IMPACTOFMETALPOLLUTIONANDThlaspi caerulescensPHYTOEXTRACTIONONSOILMICROBIALCOMMUNITIES............................................................................
. 6.1. Abstract..........................................................................................................................
. 6.2. Introduction...................................................................................................................
. 6.3. Materialsandmethods..................................................................................................
. . 6.3.1... Experimental.design...........................................................................................
. . 6.3.2... Soil.metal.concentrations....................................................................................
. . 6.3.3... Soil.microbial.parameters...................................................................................
. . 6.3.4... Plant.parameters.................................................................................................
. . 6.3.5... Statistical.analysis...............................................................................................
. 6.4. Results.............................................................................................................................
. . 6.4.1... Plant.physiological.parameters.and.metal.concentrations..................................
. . 6.4.2... Soil.physicochemical.and.microbial.parameters................................................
. 6.5. Discussion.......................................................................................................................
. . 6.5.1... Metal.phytoextraction.........................................................................................
. . 6.5.2... Impact.of.metal.pollution.on.soil.properties.......................................................
. . 6.5.3... Effect.of.T..caerulescens.growth.and.metal.phytoextraction.on.soil.properties.
. 6.6. Conclusions....................................................................................................................
7. SOILMICROBIALCOMMUNITYASBIOINDICATOROFTHERECOVERYOFSOIL FUNCTIONING DERIVED FROM METAL PHYTOEXTRACTION WITHSORGHUM...............................................................................................................................
. 7.1. Abstract..........................................................................................................................
. 7.2. Introduction...................................................................................................................
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. 7.3. Materialsandmethods..................................................................................................
. . 7.3.1... Soil.characterization.and.experimental.design...................................................
. . 7.3.2... Plant.parameters.................................................................................................
. . 7.3.3... Soil.parameters...................................................................................................
. . 7.3.4... Statistical.analysis...............................................................................................
. 7.4. Results.............................................................................................................................
. . 7.4.1... Metal.phytoextraction.by.sorghum.plants..........................................................
. . 7.4.2... Effect.of.metal.pollution.and.phytoextraction.on.soil.parameters......................
. 7.5. Discussion.......................................................................................................................
. . 7.5.1... Metal.phytoextraction.by.sorghum.plants..........................................................
. . 7.5.2... Effect.of.metal.pollution.and.phytoextraction.on.soil.parameters......................
. 7.6. Conclusions....................................................................................................................
8. EFFECTSOFCHELATESONPLANTSANDSOILMICROBIALCOMMUNITY:COMPARISONOFEDTAANDEDDSFORLEADPHYTOEXTRACTION..................
. 8.1. Abstract..........................................................................................................................
. 8.2. Introduction...................................................................................................................
. 8.3. Materialsandmethods..................................................................................................
. . 8.3.1... Greenhouse.experiment......................................................................................
. . 8.3.2... Plant.metal.accumulation....................................................................................
. . 8.3.3... Soil.solution.analysis..........................................................................................
. . 8.3.4... Soil.biological.indicators....................................................................................
. . 8.3.5... Statistical.analysis...............................................................................................
. 8.4. Results.............................................................................................................................
. . 8.4.1... Chelate.effects.on.soil.Pb.mobilization..............................................................
. . 8.4.2... Pb.accumulation.in.cardoon.plants.....................................................................
. . 8.4.3... Plant.biomass......................................................................................................
. . 8.4.4... Soil.biological.indicators....................................................................................
. 8.5. Discussion.......................................................................................................................
. . 8.5.1... Chelate.effects.on.soil.Pb.mobilization..............................................................
. . 8.5.2... Pb.accumulation.in.cardoon.plants.....................................................................
. . 8.5.3... Plant.biomass......................................................................................................
. . 8.5.4... Soil.biological.indicators....................................................................................
. 8.6. Conclusions....................................................................................................................
9. EVALUATIONOFTHEEFFICIENCYOFAPHYTOSTABILIZATIONPROCESSWITHBIOLOGICALINDICATORSOFSOILHEALTH.................................................
. 9.1. Abstract..........................................................................................................................
. 9.2. Introduction...................................................................................................................
. 9.3. Materialsandmethods..................................................................................................
. . 9.3.1... Experimental.design...........................................................................................
. . 9.3.2... Soil.physicochemical.and.biological.characterization........................................
. . 9.3.3... Statistical.analysis...............................................................................................
. 9.4. Results.............................................................................................................................
. . 9.4.1... CaCl2-extractable.metal.concentrations.in.soil...................................................
. . 9.4.2... Plant.parameters.................................................................................................
. . 9.4.3... Soil.physicochemical.and.biological.parameters................................................
. 9.5. Discussion.......................................................................................................................
. 9.6. Conclusions....................................................................................................................
10.LINKS BETWEEN PSEUDOMETALLOPHYTESAND RHIZOSPHERE MICRO-BIALCOMMUNITIESINAMETALLIFEROUSSOIL....................................................
. 10.1. Abstract..........................................................................................................................
. 10.2. Introduction...................................................................................................................
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. 10.3. Materialsandmethods..................................................................................................
. . 10.3.1...Soil.characterization.and.experimental.design...................................................
. . 10.3.2...Plant.parameters.................................................................................................
. . 10.3.3...Soil.physicochemical.and.microbial.properties..................................................
. . 10.3.4...Soil.ecosystem.health.........................................................................................
. . 10.3.5...Statistical.analysis...............................................................................................
. 10.4. Results.............................................................................................................................
. . 10.4.1...Plant.parameters.and.soil.properties...................................................................
. . 10.4.2...Soil.ecosystem.health.........................................................................................
. . . 10.4.2.1. Sorghum productivity essay ............................................................... 10.4.2.2. Soil stability ....................................................................................... 10.4.2.3. Attributes of ecosystem health and overall ecosystem health............. 10.5. Discussion........................................................................................................................ . 10.5.1...Soil.and.plant.parameters.................................................................................... . 10.5.2...Soil.ecosystem.health.......................................................................................... 10.6. Conclusions....................................................................................................................
11. SÍNTESIS..................................................................................................................................
12.ONDORIOANAGUSIAKETATESIA................................................................................... 12.1. Ondorioak....................................................................................................................... 12.2. Tesia................................................................................................................................12.CONCLUSIONESPRINCIPALESYTESIS......................................................................... 12.1. Conclusiones.................................................................................................................... 12.2. Tesis.................................................................................................................................12.MAINCONCLUSIONSANDTHESIS................................................................................... 12.1. Conclusions..................................................................................................................... 12.2. Thesis..............................................................................................................................
BIBLIOGRAFIA/BIBLIOGRAFÍA/REFERENCES..................................................................
AGRADECIMIENTOS/ACKNOWLEDGEMENTS/ESKERRAK...........................................
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1. General introduction / introducción General
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1. GENERAL INTRODUCTION/INTRODUCCIÓN GENERAL
NOTA INTRODUCTORIA: el capítulo “1. Introducción General” se divide en dos apartados: (1.1) una breve introducción (en inglés) a los indicadores microbianos de la salud del suelo y a la fitorremediación de suelos contaminados con metales (Epelde et al., publicada en el libro Advances in Applied Bioremediation; Springer, en prensa, doi: 10.1007/978-3-540-89621-0_16) en la que se incluyen asimismo, al objeto de ilustrar algunos conceptos, resultados de experimentos; (1.2) una segunda parte (en castellano) en la que se contextualiza el marco en el que se encuadra este trabajo dentro de la problemática particular de los suelos contaminados en la CAPV y la situación de la fitorremediación a nivel global.
1.1 Heavy metal phytoremediation: microbial indicators of soil health for the assessment of remediation efficiency
1.1.1 Microbial indicators of soil health
In the last few years, there has been a growing interest in the definition and
evaluation of soil health, in part stimulated by an increasing awareness that soil is a
critical component of the Earth´s biosphere, functioning not only in the production
of food and fiber but also in the maintenance of local, regional, and worldwide
environmental quality (Doran and Parkin, 1994; Alkorta et al., 2003a). Although its
definition is currently a topic of much debate and confusion, a commonly used
definition of soil quality/health that appears in many bibliographic references reads
as follows: “the continued capacity of a specific kind of soil to function as a vital
living system, within natural or managed ecosystem boundaries, to sustain plant and
animal productivity, to maintain and enhance the quality of air and water
environments, and to support human health and habitation” (Doran and Parkin,
1996; Doran and Safley, 1997). The terms “soil quality” and “soil health” are often
used interchangeably, but the former focuses more on the capacity of the soil to
meet defined human needs, such as the growth of a particular crop, while, by
contrast, the latter (i) relates more to the soil´s continued capacity to sustain plant
growth and maintain its functions (Coleman et al., 1998) and (ii) captures the
ecological attributes of the soil, mainly, those associated with its biota, such as
evaluation of the efficiency of metal phytoremediation processes with microbioloGical indicators of soil health
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biodiversity, food web structure, activity, range of function, etc. (Pankhurst et al.,
1997). Furthermore, the term “soil health” conveys the idea of soil as a living
system, a concept of the utmost importance since, after all, the soil contains vast
assemblages of organisms that are responsible for many of its vital functions, such
as decomposition and recycling of nutrients from dead plant and animal tissues,
nitrogen fixation, maintenance of soil structure, detoxification of pollutants, and so
on (Alkorta et al., 2003b).
Unfortunately, our soils are presently being degraded through salinization,
erosion, sealing, pollution, loss of organic matter and biodiversity, etc., leading to
the deterioration of the soil´s physical, chemical and biological properties
worldwide. Actually, the quantity and quality of the soil´s ecosystem services and
functions are nowadays being diminished at an alarming rate, making soil
degradation an environmental issue that demands immediate attention and response.
In this respect, history has repeatedly shown that mismanagement of the soil
resource base can lead to poverty, malnutrition and economic disaster (Bezdicek et
al., 1996). Within a community, a strong link can be found between soil
quality/health, food quantity and quality, and the health, well-being, and prosperity
of its citizens (Janke and Papendick, 1994). Indeed, the quality of life on Earth is
inextricably linked to the health of our soils.
In particular, the release of contaminants into our soils by human activities has
increased enormously over the past several decades, overwhelming the self-cleaning
capacity of the soil ecosystem and, as a consequence, resulting in the accumulation
of dangerous toxic substances. Accordingly, in our time, soil pollution attracts
considerable public attention since the magnitude of the problem calls for
immediate action (Garbisu and Alkorta, 2003).
In this context, it is urgently imperative to have reliable indicators for the
assessment and monitoring of soil health. To date, emphasis has mostly been placed
on physical and chemical soil properties as indicators of soil health, but biological
parameters are becoming increasingly used due to their being more sensitive to
changes in the soil as well as to their capacity to provide information that integrates
many environmental factors (Alkorta et al., 2003b; Hernández-Allica et al., 2006a;
Mijangos et al., 2006). Many biological parameters have been proposed as
1. General introduction / introducción General
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17
bioindicators of soil health, such as microbial biomass, basal and substrate-induced
respiration, mineralizable nitrogen, soil enzyme activities, abundance of soil
microflora and fauna, root pathogens, structural and functional biodiversity, food
web structure, plant growth and diversity, and so on (Pankhurst et al., 1997).
Microbial parameters, particularly those related to the size, activity and biodiversity
of the soil microbial communities, are most relevant as indicators of soil health.
After all, microbially mediated processes are central to the functions that soil
performs and, what´s more, microorganisms are responsible for 70-85% of the soil
biological activity (Reichle, 1977).
In any event, and because the pedosphere, hydrosphere, atmosphere and
biosphere are overlapping, intimately associated in the ecosystem, environmental
compartments, whatever occurs in the soil has a profound effect not only on soil
health but also on ecosystem health (Huang et al., 1998). The concept of ecosystem
health has been elaborated as a comprehensive, multiscale, dynamic, hierarchical
measure of system (i) vigor, which may be quantified in terms of productivity,
throughput of material and energy in the system, etc.; (ii) resilience, which may be
determined in terms of the system´s ability to maintain its structure and pattern of
behaviour in the presence of stress; and (ii) organization, which may be assessed in
terms of both the diversity of components and their degree of mutual dependence
(Mageau et al., 1995; Costanza et al., 1998; Rapport, 1998; Alkorta et al., 2004a).
Moreover, a healthy ecosystem must have the following attributes: (i) it should be
free of the “ecosystem distress syndrome”, that comprises a group of signs (e.g.,
leaching of soil nutrients, reduced species diversity, shifts in species composition to
opportunistic species, reduced productivity, increased pest and disease loads) by
which ecosystem breakdown is recognized; (ii) it should be self-sustaining; (iii) it
should not adversely affect or degrade surrounding systems (Costanza et al., 1992;
Hildén and Rapport, 1993; Rapport et al., 1997; Alkorta et al., 2004a). Although soil
health must not be equated with ecosystem health, the application of the ecosystem
health approach to studies of soil status and condition can indeed provide useful
information to, for instance, assess the impact of pollution on soil functioning and
to establish the efficiency of a certain remediation procedure.
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As abovementioned, vigor can be measured in terms of productivity,
throughput of material and energy in the system, etc. In the soil, these processes
might be investigated by methods that focus either on broad physiological
properties, such as soil respiration or nitrogen mineralization, or on specific enzyme
reactions carried out by soil microorganisms (Kandeler, 2007). Soil respiration is
related to ecosystem productivity, soil fertility, and regional and global carbon cycles
(Luo and Zhou, 2006). Soil enzyme activities, which control the rates of soil nutrient
cycling, provide a unique integrative biological assessment of soil function,
especially those catalyzing a wide range of soil biological processes, such as
dehydrogenase, urease, phosphatase, etc. (Nannipieri et al., 2002).
Resilience is included in the concept of stability, which comprises both resilience, the property of the system to recover after disturbance, and resistance, the inherent
capacity of the system to withstand disturbance. This concept can be applied to
those studies dealing with the impact of pollution on soil health. Interestingly, two
theories diverge with respect to the stability of ecological processes: (i) according to
the first theory, non-stressed systems are more stable, thanks to the large resources
they dispose to maintain function in case of stress (Loreau, 2000); (ii) the second
theory predicts that stressed systems are more stable because, due to first stress,
they have gained abilities to cope with stress and thus maintain function (Odum,
1981).
Finally, organization refers to ecosystem complexity and is affected by both the
diversity of species and the number of pathways of material exchange between each
component (Costanza et al., 1998). From an ecological perspective, in the soil
ecosystem, functional diversity, as opposed to structural diversity, provides more
relevant information (Torsvik and Øvreås, 2007). There are different methods to
determine the functional diversity of soil microbial communities such as, for
instance, community level physiological profiles (Preston-Mafham et al., 2002), soil
enzyme activities (Larson et al., 2002), and a variety of culture-independent
molecular techniques (Malik et al., 2008).
In this Chapter, the possibility of using microbial indicators of soil health to
assess the efficiency of metal phytoremediation processes is discussed.
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1.1.2 Heavy metal phytoremediation
Heavy metals are present in soil as natural components or as a result of human
activity, with the primary sources of metal pollution being the burning of fossil
fuels, mining and smelting of metalliferous ores, electroplating, downwash from
power lines, municipal wastes, fertilizers, pesticides and sewage (Garbisu and
Alkorta, 2001; Alkorta et al., 2004b). Actually, metal pollution has become one of
the most serious environmental problems today (Alkorta et al., 2004b). For instance,
arsenic, a nonessential metalloid, is an environmental pollutant of prime concern
which is causing a global epidemic of poisoning, with tens of thousands of people
having developed skin lesions, cancers and other symptoms (Pearce, 2003; Alkorta
et al., 2004c; Rozas et al., 2006).
Some metals are essential for life (e.g., they provide essential cofactors for
metalloproteins and enzymes) but, at high concentrations, metals are toxic for both
higher organisms and microorganisms (Garbisu and Alkorta, 1997). Indeed, at high
concentrations, metals can act in a deleterious manner by blocking essential
functional groups, displacing other metal ions, or modifying the active conformation
of biological molecules (Collins and Stotzky, 1989). Besides, due to their immutable
nature (metals are unique in that they do not undergo either chemically or
biologically induced degradation that could reduce their toxicity but rather
transform from one oxidation state or organic complex to another) (Alkorta et al.,
2006) and persistence in soil (with residence times in the order of thousands of
years) (McGrath, 1987), metals are a group of pollutants of much concern (Garbisu
and Alkorta, 1997; 2003). In soil, rather than total metal concentration, a major
factor governing metal toxicity is biovailability (Alkorta et al., 2006).
evaluation of the efficiency of metal phytoremediation processes with microbioloGical indicators of soil health
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Figure 1.1 is included as an example of the impact of metal pollution on soil
microbial communities (in particular, on the cultivable portion of the soil
heterotrophic microbial community). In this Figure 1.1, the average well colour
development (AWCD) curves, obtained from the carbon substrates utilization
patterns (i.e., community level physiological profiles - CLPP) of the Biolog
EcoPlatesTM, are presented. The data correspond to a soil artificially polluted with
250, 500, 100, 2000 and 4000 mg Zn kg-1 DW soil as ZnCl2, and show that 250 and
500 mg Zn kg-1 did not cause a negative impact on the soil functional microbial
diversity. On the contrary, 1000 mg Zn kg-1 and especially 2000 and 4000 mg Zn kg-
1 clearly affected the capacity of the cultivable portion of the soil heterotrophic
microbial community to utilize carbon substrates.
Figure 1.1: Effect of Zn pollution on average well colour development (AWCD) curves obtained with Biolog EcoPlatesTM. Soils were polluted with 250, 500, 100, 2000 and 4000 mg Zn kg-1 DW
soil as ZnCl2.
Traditional physicochemical methods for the remediation of metal polluted
soils are, in general, very expensive, which has stimulated the development of
innovative biological technologies to economically remediate these soils
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21
(Hernández-Allica et al., 2006a). Bioremediation, “a managed treatment process that
uses microorganisms to degrade and transform chemicals in contaminated soil,
aquifer material, sludges and residues” (Dasappa and Loehr, 1991), offers an
effective, non-destructive, economical clean-up technique for the remediation of
polluted sites, that must be considered an important tool in our attempts to mitigate
environmental contamination (Garbisu and Alkorta, 1997, 1999, 2003). But
although many studies have been carried out to investigate the possibility of using
microorganisms to aid in the remediation of metal polluted environments,
microorganisms do not solve the critical problem of the removal of metals from the
polluted soil. As a matter of fact, bacteria can only transform metals from one
oxidation state or organic complex to another, but not extract them from the
polluted soil (Garbisu et al., 2002).
Luckily, to overcome this limitation of bacterial metal soil remediation, the
possibility of using plants that can literally extract the metals from the polluted soil
was raised. In this respect, phytoremediation, “the use of green plants to remove
pollutants from the environment or to render them harmless” (Cunningham and
Berti, 1993; Raskin et al., 1994), is currently viewed as the ecologically responsible
alternative to the environmentally destructive physicochemical remediation methods
(Meagher, 2000). This phytotechnology has been reported as an effective, non-
intrusive, inexpensive, aesthetically pleasing, socially accepted remediation process
(Garbisu et al., 2002). The technical aspects of phytoremediation, together with the
advantages and limitations of this technology, have been extensively reviewed
elsewhere (Chaney et al., 1997; Raskin et al., 1997; Salt et al., 1998; Alkorta and
Garbisu, 2001; Garbisu and Alkorta, 2001; Garbisu et al., 2002; McGrath et al.,
2002; Alkorta et al. 2004b, 2004d; Pilon-Smits, 2005).
Within the field of phytoremediation, several categories have been defined:
phytoextraction, phytofiltration, phytostabilization, phytovolatilization,
phytodegradation, phytotransformation, etc. (Garbisu et al., 2002). Regarding soil
metal remediation, two of these categories are most relevant: phytoextraction and
phytostabilization.
evaluation of the efficiency of metal phytoremediation processes with microbioloGical indicators of soil health
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Figure 1.2: Strategies for metal phytoremediation.
Finally, it is most important to emphasize that, from an ecocentric point of
view, the ultimate goal of any soil remediation process must be not only to remove
the pollutant(s) from the soil but to restore soil health (Hernández-Allica et al.,
2006a; Epelde et al., 2008a).
1.1.2.1 Continuous metal phytoextraction
The term “phytoextraction” refers to the utilization of plants to remove
pollutants (mostly, metals) from soils. In particular, “continuous phytoextraction” is
based on the utilization of metal hyperaccumulating plants (hyperaccumulators) that
have the capacity to accumulate, translocate and tolerate high amounts of metals
over the complete growth cycle (Figure 1.3; Salt et al., 1995; Baker et al., 2000). In
this respect, Thlaspi caerulescens (i.e., alpine pennycress or alpine pennygrass), a
hyperaccumulating plant extensively studied due to its remarkable capacity to
phytoextract Zn and Cd from polluted soils (Hernández-Allica et al., 2006a, b;
Epelde et al., 2008a), has been suggested as model species for research on metal
phytoextraction (Assunção et al., 2003).
Phytoextraction Phytostabilization
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23
Figure 1.3: Continuous phytoextraction with Thlaspi caerulescens.
With a local ecotype of T. caerulescens, termed “Lanestosa”, from the Basque
Country (northern Spain), we carried out a microcosms study to (i) evaluate the
potential of such ecotype for Zn phytoextraction and (ii) assess the effect of the
phytoextraction process, which includes both plant growth and metal
phytoextraction, on microbial indicators of soil health. To this aim, T. caerulescens seedlings were transplanted to 2.5 kg pots that had been artificially polluted with
1000 mg Zn kg-1 DW soil and fertilized with 120 mg kg-1 DW soil of N, P and K.
After three months of growth, on average, T. caerulescens plants accumulated 5,654
mg Zn kg-1 DW shoot and extracted 28.9 mg of Zn pot-1. In addition, CLPPs were
obtained from Biolog EcoPlatesTM at the end of the experiment. Table 1.1 shows
the values of AWCD, richness (S) and Shannon´s diversity (H’) calculated from
Biolog EcoPlatesTM data at an incubation time of 52 h. As observed in this Table
1.1, in the absence of plants, Zn pollution led to lower values of all these
parameters, as compared to values of control non-polluted soils. Nevertheless, as a
result of T. caerulescens growth and metal phytoextraction, all these values were
recovered, indicating that the cultivable portion of the soil heterotrophic microbial
community had recovered its capacity to use carbon substrates (its functional
diversity). For all parameters of microbial functional diversity, the presence of plants
proved more important than the amount of metal phytoextracted from the soil
(actually, in this experiment, such amount was very low). As compared to bare soil,
vegetated soils are commonly described as having higher rates of microbial activity,
due to the presence of additional surfaces for microbial colonization and organic
compounds released by the plant roots (Tate, 1995; Grayston et al., 1997; Delorme
Met
al u
ptak
e
Harvest Growth Phase
Plant biomass
evaluation of the efficiency of metal phytoremediation processes with microbioloGical indicators of soil health
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et al., 2001). In similar phytoextraction experiments with T. caerulescens plants, higher
values of biological activity were found in rhizosphere versus non-rhizosphere soil
(Gremion et al., 2004; Keller and Hammer, 2004; Hernández-Allica et al., 2006a;
Wang et al., 2006; Epelde et al., 2008a). Finally, regarding the recovery of soil health
derived from a phytoextraction process, as reflected by the values of soil microbial
parameters, an ideal target should be to return to the conditions of a valid control
soil, i.e. a vegetated, unpolluted soil of similar physicochemical properties and
subjected to the same edaphoclimatic conditions.
Table 1.1: Values of average well colour development (AWCD) and diversity indexes calculated from Biolog EcoPlatesTM absorbance data at 52 h incubation time, in soils from a Zn
phytoextraction experiment with Thlaspi caerulescens Lanestosa plants. S = richness; H’ = Shannon´s diversity. Mean values (n = 3) ± standard errors. Values followed with different letters are
significantly different (P<0.05 or lower) according to Fisher´s PLSD-test.
AWCD S H’
Control, non-polluted 0.91 ± 0.01ab 24 ± 1a 3.0 ± 0.1a
Metal polluted, unplanted 0.78 ± 0.03a 18 ± 0b 2.8 ± 0.0a
Metal polluted, planted 1.01 ± 0.05b 24 ± 2a 3.1 ± 0.1a
From a remediation point of view, phytoextraction demands a sufficient
harvestable biomass. Unfortunately, most metal hyperaccumulators (e.g., T. caerulescens) are, in general, relatively small, have slow rates of biomass production
and lack any established cultivation, pest management or harvesting practices
(Wenzel et al., 1999). Consequently, nowadays, fast-growing, high biomass crop
plant species that accumulate moderate levels of metals in their shoots are actively
being tested for phytoextraction (Hernández-Allica et al., 2008). After all, in some
cases, a greater shoot biomass has been reported to more than compensate for a
lower shoot metal concentration (Ebbs and Kochian, 1997).
1.1.2.2 Chelate induced phytoextraction
The discovery that the application of chelating agents to the soil increases
plant metal uptake and translocation (Figure 1.4) opened a wide range of
possibilities for phytoextraction (Blaylock et al., 1997), most importantly, that of
1. General introduction / introducción General
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using high biomass plants for the remediation of metal polluted soils, particularly
with low bioavailable metals such as Pb (Hernández-Allica et al., 2007). However,
side-effects related to the addition of chelating agents to the soil, such as metal
leaching and toxic effects on soil microbial communities, have usually been
neglected (Römkens, 2002). In this respect, most studies on chelate-induced
phytoextraction have focused on EDTA (ethylenediaminetetracetic acid)-mediated
Pb phytoextraction (McGrath et al., 2002). Nevertheless, EDTA and the formed
EDTA-Pb complexes present low biodegradability and a high solubility, resulting in
an elevated risk of adverse environmental effects due to metal mobilization and long
persistence (Alkorta et al., 2004d). EDDS (ethylenediaminedisuccinate) has been
proposed as an alternative for chelate-induced metal phytoextraction (Grčman et al.,
2003; Santos et al., 2006). EDDS has been shown to be easily biodegradable
(Jaworska et al., 1999), to form strong complexes with transition metals and
radionuclides (Jones and Williams, 2001), to cause a much lower leaching of Pb
down the soil profile than EDTA (Grčman et al., 2003), and to be less toxic to soil
microorganisms (Grčman et al., 2003). In any case, environmentally safe methods of
chelate-induced phytoextraction must clearly be developed before steps towards
further development and commercialization of this remediation technology are
taken (Alkorta et al., 2004d).
Figure 1.4: Chelate-induced phytoextraction with Cynara cardunculus.
As an example, Figure 1.5 shows the response of several soil microbial
parameters to EDTA and EDDS addition (1 g kg-1 DW soil) in a microcosm
chelate-induced phytoextraction experiment, with Cynara cardunculus plants, carried
out in a soil artificially polluted with 1000 mg Pb kg-1 DW soil. EDTA was much
more effective (428.4 mg Pb kg-1 DW shoot) than EDDS (20.8 mg Pb kg-1 DW
Met
alup
take
Plantbiomass
Harvest Growth Phase
evaluation of the efficiency of metal phytoremediation processes with microbioloGical indicators of soil health
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shoot) for the induction of Pb shoot accumulation (6.3 mg Pb kg-1 DW shoot in
control pots). However, soil microbial parameters, especially dehydrogenase activity
(which, on average, was halved) and basal respiration, were more negatively affected
by EDTA than EDDS (Figure 1.5). Dehydrogenase activity, which occurs in every
viable microbial cell, and basal respiration are both used as indicators of overall
microbiological activity in the soil (Nannipieri et al., 2002).
Figure 1.5: Effect of chelating agents (EDTA, EDDS) on soil biological parameters in a chelate-induced Pb phytoextraction experiment with Cynara cardunculus plants. Controls: no chelating agents added. Values of control soils are used as reference points (values found at these control
soils = 100%). Resp: basal respiration (indicator of soil microbial activity); SIR: substrate-induced respiration (indicator of potentially active microbial biomass); Min N: potentially mineralizable N
(indicator of potential rate of N mineralization); DH: dehydrogenase (indicator of overall microbiological activity of soil); Glu: β-Glucosidase (an enzyme that plays a central role in the hydrolysis of polymers of plant residues, i.e. cellobiose); Aryl-S: arylsulfatase (an enzyme that
catalyses the hydrolysis of organic sulphate ester releasing sulphate); Acid-P: acid phosphatase (an enzyme that releases phosphate from organic phosphorus).
Then, apart from being effective for the induction of metal phytoextraction,
chelating agents for enhanced phytoextraction must be as innocuous as possible for
the soil biota. After all, the addition of chelating agents to the soil may increase, for
0
20
40
60
80
100
Resp
SIR
Min N
Acid-PDH
Glu
Aryl-S
Control
EDTA
EDDS
1. General introduction / introducción General
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instance, metal availability for soil microorganisms (Welp and Brümmer, 1997) and,
since soil microorganisms depend directly or indirectly on the soil solution for
uptake of food and water, elevated metal concentrations in the soil solution might
lead to toxic effects on the soil microbiota (Römkens et al., 2002).
1.1.2.3 Phytostabilization
The remediation of metal polluted soils, particularly those presenting high
levels of metal pollution, using phytoextraction procedures usually takes many years,
most probably, decades. In fact, to overcome this often considered Achilles heel of
phytoextraction, i.e. the long time needed for effective remediation, it has been
suggested that this phytotechnology should be combined with a profit making
operation such as forestry or bioenergy production (Robinson et al., 2003). In any
case, an alternative phytotechnology for the remediation of metal polluted soils is
phytostabilization or the use of plants to reduce the biovailability of pollutants in
the environment. More specifically, phytostabilization refers to the immobilization
of a contaminant in the rhizosphere through absorption and accumulation by roots,
adsorption onto roots, or precipitation within the root zone of plants, so that
contaminant migration via wind and water erosion, leaching and soil dispersion are
prevented (EPA, 2000). Thus, although metals are not removed from the soil, their
adverse environmental effects are reduced. The choice of metal phytoremediation
strategy (phytoextraction versus phytostabilization) will depend on a variety of
factors: type of metal(s) present in the soil, level of metal pollution, future use of the
site, etc. Interestingly, the combination of both strategies, so that the limitations of
one strategy might be overcomed by the advantages of the other strategy, appears a
most promising approach.
Chemophytostabilization, the combination of a chemical method (such as the
addition of organic or inorganic amendments to the soil) with phytostabilization
(Knox et al., 2000), is most promising for the remediation of metal polluted soils.
Amendments, such as different sources of organic matter, are added to the soil in an
attempt to reduce metal bioavailability by formation of insoluble metal organic
complexes with humic acids, thereby lessening the risk of metal toxicity to plants
and microbes (Stevenson et al., 1972; Kirkham, 1977). The combination of both
evaluation of the efficiency of metal phytoremediation processes with microbioloGical indicators of soil health
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approaches is very interesting as the chemicals bind the excess of metals, control pH
and provide plant nutrients, and the plants prevent wind erosion, reduce leaching,
and accumulate metals in their roots.
We have previously reported the phytostimulatory effect of plants on soil
microbial communities within the context of the phytoremediation of metal
polluted soils (Hernández-Allica et al., 2006a; Epelde et al., 2008a). However, for a
chemophytostabilization procedure, it is essential to also take into account the
effects of amendments on the soil microbial community. In this respect, we carried
out a microcosm study with a moderately polluted mine soil (1000 mg Zn kg-1 DW
soil, 340 mg Pb kg-1 DW soil, 2.6 mg Cd kg-1 DW soil) amended with cow slurry
[i.e., cow slurry, having 12% dry matter (DM), 3.25% DM nitrogen, 0.9% DM
phosphorus, and 3% DM potassium, was applied at a dose of 0.1 L kg-1 DW soil] or
a chemical fertilizer (i.e., urea plus PK14% fertilizer at similar nutrient doses than
those applied as cow slurry). Twenty weeks after amendment addition, bioavailable
(CaCl2 extractable) soil metal concentrations had decreased considerably: a 45, 62
and 38% reduction in biovailable Zn, Pb and Cd, respectively, was observed for the
chemically fertilized soils; a 34, 50 and 33 reduction in bioavailable Zn, Pb and Cd,
respectively, was found in those soils fertilized with cow slurry. At the same time,
values of dehydrogenase activity increased in both amended soils (i.e., control, no
amendment added, soil: 0.2 mg INTF kg-1 DW soil 20 h-1; soil with chemical
fertilizer: 12.0 mg INTF kg-1 DW soil 20 h-1; soil with cow slurry: 77.4 mg INTF kg-
1 DW soil 20 h-1), indicating the stimulatory effect of both amendments on soil
microbiological activity.
1. General introduction / introducción General
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Figure 1.6: Metabolic fingerprints of substrate utilization patterns obtained with the Biolog EcoPlatesTM at an incubation time of 44 hours, from control (no amendment), chemical fertilizer-amended (NPK = urea plus PK14%) and cow slurry-amended mine soil. For clarity purposes, only
those substrates showing significant differences (P<0.05) among treatments, according to ANOVA, are presented.
Since soil microbial biodiversity has a key role in the maintenance of soil
fertility, functioning and resilience, in the same chemophytostabilization study, we
also determined the microbial functional diversity, through CLPPs obtained with
the Biolog EcoPlatesTM, of control and amended soils. Figure 1.6 shows the
metabolic fingerprints of the CLPPs displayed by control and amended (cow slurry
or chemical fertilizer) soils. In this Figure 1.6, for clarity purposes, only those
substrates showing significant differences among treatments are presented. As
observed in this Figure 1.6, the addition of urea plus PK14% led to a different
pattern of carbon substrates utilization by the cultivable portion of the soil
heterotrophic microbial community. The addition of cow slurry resulted in higher
values of functional diversity in the polluted mine soil (Fig. 1.6). In this case, the
easily mineralizable organic matter might have favoured the soil microbial functional
evaluation of the efficiency of metal phytoremediation processes with microbioloGical indicators of soil health
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30
diversity. The addition of manure and compost to the soil has previously been
reported to significantly increase values of microbial functional diversity according
to BiologTM data (Gómez et al., 2006; Toyota and Kuninaga, 2006).
1.1.3 Conclusions
Despite the logical interest in improving the metal extraction capacity of metal
phytoremediating plants (phytoextraction) or reducing metal bioavailability, leaching
and dispersion using plants (phytostabilization), it should never be forgotten that
the ultimate goal of any soil remediation process must be not only to remove the
contaminant(s) from the polluted soil but, most importantly, to restore the
continued capacity of the soil to perform or function according to its potential (i.e.,
to recover soil health). In fact, in some cases, it might be possible to recover soil
health without decreasing soil metal concentrations to levels indicated in the
different regulations (most current regulations governing metal toxicity in soils are
still based on the total metal concentration in the soil, whose validity as a basis for
metal limits in soil is certainly questionable).
In this respect, although to date, emphasis has been placed on physical and
chemical soil properties as indicators of soil health, biological parameters are
becoming increasingly used due to their being more sensitive to changes in the soil
as well as to their capacity to provide information that integrates many
environmental factors. In particular, those biological indicators related to the size,
activity and diversity of the soil microbial communities are most promising since
microorganisms are, to a large extent, responsible for soil functioning. Microbial
indicators of soil health are valid tools to evaluate the success of phytoextraction
and phytostabilization processes.
Finally, it is important to point out that metal polluted and phytoremediated
soils are interesting scenarios to deepen into the still poorly understood plant-
microbe interactions that occur belowground and which fulfil vital roles in the
functioning of terrestrial ecosystems. After all, disturbed environments usually
provide a better insight into the workings of the system.
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31
1.2 Contextualización
1.2.1 Tradición minera en la CAPV
La contaminación del suelo de origen minero, en torno a la que se desarrolla
gran parte de este trabajo, adquiere una especial relevancia en la CAPV como se
deriva de la enorme importancia que históricamente ha tenido la actividad minera en
nuestra Comunidad. Ciertamente, a lo largo de la historia, se han explotado en la
CAPV yacimientos minerales en muy diversas zonas de nuestra geografía: los
Montes de Triano (municipios de Gallarta, Ortuella, Muskiz, Sopuerta y Galdames),
la zona de Ollargan (Bilbao), Legazpi, Oñati, Zerain, Irún, etc. En la Figura 1.7, se
puede observar la distribución de los emplazamientos mineros en la CAPV
recogidos en el Sistema de Cartografía Ambiental del Gobierno Vasco (Gesplan). La
mayoría de ellos son de hierro (Fe), aunque también son abundantes los de zinc
(Zn) y plomo (Pb), como pueden ser las minas de Arditurri (Oiartzun), Mina Troya
(Mutiloa) y Mina Legorreta (Legorreta) en Gipuzkoa, o la zona de Carranza y
Lanestosa en Bizkaia.
Figura 1.7: Explotaciones mineras en la CAPV. Fuente: Gesplan, Gobierno Vasco.
En estos yacimientos, a medida que se iban agotando los minerales de mayor
pureza, cuya extracción no requería grandes infraestructuras, se pasó a utilizar
evaluation of the efficiency of metal phytoremediation processes with microbioloGical indicators of soil health
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minerales con menor porcentaje metálico utilizando técnicas más innovadoras. El
proceso de extracción del mineral comenzaba con las perforaciones que realizaban
los barrenadores en la roca, para luego introducir los explosivos y así fragmentarla
mediante voladuras controladas. Posteriormente, se procedía al troceado de la roca
desprendida y se llenaban los cestos en los que se cargaba el mineral. Luego, para el
lavado del mineral, se utilizaban trómeles, grandes cilindros de chapa terminados en
un cono y colocados con una ligera inclinación. El mineral a lavar se introducía por
el extremo superior y el agua en dirección contraria, arrastrando así la arcilla.
Finalmente, el mineral debía transportarse desde el monte donde se encontraban los
criaderos hasta la costa, lugar donde generalmente se embarcaba rumbo a las
siderurgias inglesas. Para el transporte del mineral se utilizaban “planos inclinados”
(vagonetas unidas entre sí que se deslizaban sobre unos raíles en un plano de
pronunciado desnivel y que funcionaban por contrapeso) y líneas de baldes (tranvías
aéreos movidos por un motor). La construcción de una red de trenes mineros fue
posiblemente la mayor inversión que tuvieron que hacer las compañías mineras. Los
cargaderos, estructuras de madera sobre las que las vagonetas podían desplazarse y
descargar directamente a las bodegas del barco, suponían el punto final de la cadena
productiva.
Los cotos de Bizkaia siempre fueron los más productivos. En los Montes de
Triano la actividad minera se inició con los romanos. Hasta el siglo XIX, la
explotación de los minerales se realizaba artesanalmente por los vecinos de los
pueblos cercanos, sin ninguna ley que regulara esta extracción. A partir de mediados
del siglo XIX se empezaron a utilizar sistemas mecanizados que permitieron la
extracción industrial de mineral. Esto fue posible gracias a la privatización de los
yacimientos mineros y la implantación de nuevos sistemas de explotación de
carácter capitalista con financiación, maquinaria e ingeniería extranjera.
La extracción y elaboración de mineral en el siglo XX tuvo muchos altibajos.
Durante la primera guerra mundial (1914-1918), se orientó la siderurgia a la
producción de munición para los aliados. Acabada esta guerra, la demanda de
mineral de hierro se desplomó. En la Segunda Guerra Mundial (1939-1945) las
exportaciones de mineral se dirigieron hacia la Alemania de Hitler. De nuevo, pocos
años después de que acabara la Segunda Guerra Mundial, la exportación de hierro
1. General introduction / introducción General
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cesó, esta vez definitivamente, y las pocas minas que aún quedaban activas se
dedicaron a abastecer únicamente a la siderurgia local.
El sector siderometalúrgico vasco cubría una amplia gama de productos (aceros
especiales, tubos sin soldadura, aceros moldeados, tubos soldados, etc.). En 1979 se
censaron 10.979 empresas dedicadas a estas actividades, de las cuales casi la mitad se
localizaban en Bizkaia (destacando la margen izquierda de la Ría del Nervión, donde
esta industria cubría grandes extensiones) y un tercio en Gipuzkoa. En 1975 el sector
daba empleo a 243.294 personas, cifra que suponía el 46.7% de la población activa
vasca. A partir de entonces, un lento declive culminó a principios de los 90 con el
cierre de la última mina y de la empresa siderúrgica más emblemática de la zona:
Altos Hornos de Vizcaya.
Figura 1.8: (a) Extracción de mineral y (b) fundición de acero. Fuente:
http://www.museominero.net/.
Indiscutiblemente, la actividad minera de hierro, así como de metales no
férricos, ha constituido un componente trascendental del desarrollo industrial-
económico de la CAPV. Los beneficios económicos, sociales y culturales de esta
actividad han sido inmensos. Sin embargo, tras su caída, la atención se cierne
inevitablemente sobre las “heridas medioambientales abiertas” resultado de dicha
actividad.
Hoy en día, algunos emplazamientos mineros y zonas anteriormente ocupadas
por la industria siderúrgica han sido rehabilitadas. Por ejemplo, en la zona minera de
La Arboleda (Bizkaia), se ha emprendido una mejora sustancial del terreno,
acondicionándolo y plantando numerosas especies de arbustos y árboles autóctonos.
Este paisaje caótico de belleza singular, tiene ahora un uso recreativo. En lo referente
b) a)
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a emplazamientos industriales rehabilitados, sirvan de ejemplo los desarrollos
urbanísticos en el eje de la Ría del Nervión (e.g., las exitosas construcciones del
“Palacio Euskalduna” y el “Museo Guggenheim Bilbao” donde antes se alzaban los
“Astilleros del Nervión” y los “tinglados” de las navieras bilbaínas, respectivamente).
Sin embargo, la mayoría de los emplazamientos fueron abandonados después
de la acción devoradora de la minería, dejando tras de sí focos importantes de
contaminación. Además del evidente impacto visual que estos emplazamientos
producen en el paisaje, los residuos mineros aportan al entorno una cantidad
significativa de elementos contaminantes, bien presentes de forma natural en los
mismos emplazamientos o procedentes de los productos auxiliares empleados
durante la actividad minera. Este tipo de contaminación, aunque también se
presenta en forma difusa, está sobre todo localizada en vertederos no siempre
suficientemente controlados. En general, este tipo de enclaves mineros presentan
una fuerte pendiente, carecen de una cobertura vegetal estabilizada y son
especialmente proclives a la erosión y lixiviación, acrecentando así el riesgo de
dispersión de los metales a otros suelos y ecosistemas. Como ejemplo encontramos
los emplazamientos anexos a la zona recreativa de La Arboleda o las minas
abandonadas de Carranza.
Nota: Parte de la información incluida en este apartado ha sido extraída de Castilla y Asensio, 2007 y de la página web http://www.hiru.com/historia/ondarea, 2009.
1.2.2 Contaminación del suelo en la CAPV
En la CAPV, la escasez de suelo útil y la elevada densidad de población han
producido una ocupación masiva del suelo. Además, esta ocupación ha estado ligada
a un rápido desarrollo industrial basado en la transformación del metal, madera e
industria química, que se realizó sin ninguna planificación urbanística, en una época
en la que la preocupación por los problemas medioambientales simplemente no
existía. El vertido incontrolado de los residuos que estas actividades industriales han
generado y generan en nuestra Comunidad ha originado graves consecuencias
medioambientales. Entre ellas, cabe destacar la preocupante contaminación de los
suelos con un conjunto muy variado de compuestos tóxicos orgánicos (PAHs,
PCBs, etc.) e inorgánicos (metales).
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Según el Inventario de Emplazamientos con Actividades Potencialmente Contaminantes del Suelo elaborado por el Gobierno Vasco (2008), en la CAPV hay identificados un
total de 12.964 emplazamientos (7.898 hectáreas; 1.1% de la superficie total de la
CAPV; 16.5% de la superficie de suelo útil) susceptibles de estar alterados en su
calidad. Entre los diferentes tipos de emplazamientos inventariados se distinguen: (i)
los emplazamientos industriales activos (suponen un 75% de los emplazamientos
inventariados); (ii) vertederos (muy extensos en superficie); (iii) emplazamientos
industriales sin actividad en el momento presente (de los cuales el 79% corresponde
a antiguas zonas mineras); y (iv) emplazamientos modificados (parcelas en las que en
el pasado se han desarrollado actividades potencialmente contaminantes del suelo,
pero que en la actualidad albergan otros usos diferentes). Estos emplazamientos se
encuentran muy concentrados en núcleos urbanos y zonas adyacentes. De hecho, las
áreas funcionales del Bilbao Metropolitano, Donostia-San Sebastián y Álava Central
acaparan aproximadamente el 75% de la superficie potencialmente contaminada
inventariada de la CAPV.
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Figura 1.9: Distribución de los suelos potencialmente contaminados en la CAPV. Fuente: IHOBE.
A partir de muestreos llevados a cabo en estos emplazamientos
potencialmente contaminantes, se estimó que la superficie total realmente alterada
y/o contaminada de la CAPV se encuentra entre 1.279 y 3.120 hectáreas. Los
metales están entre los contaminantes más comunes en suelos y aguas subterráneas
de la CAPV (presentes en el 34% de casos en los que el suelo se encontraba alterado
y/o contaminado), aunque también es habitual la presencia de aceite mineral,
hidrocarburos aromáticos policíclicos y compuestos orgánicos aromáticos volátiles.
No se dispone de estudios que aporten datos cuantitativos objetivos en relación con
las presiones ejercidas por las fuentes de contaminación difusa.
1.2.3 Aspectos legales de la contaminación del suelo
La aparición a principios de los años 90 de los primeros casos de
contaminación de suelos en la CAPV puso en evidencia la necesidad de adoptar
medidas en el ámbito de la protección del medio ambiente. Así, la propuesta del Plan
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37
Director para la Protección del Suelo de 1994 fue de gran ayuda como directriz clave en la
implantación de la política de protección del suelo frente a la contaminación.
Hoy en día, la protección del suelo frente a la contaminación en la CAPV se
regula fundamentalmente a través de la Ley 1/2005, de 4 de febrero, de prevención y corrección de la contaminación del suelo, aunque los conceptos básicos relativos a esta
materia ya se habían incluido en la Ley 3/1998, de 27 de febrero, general de protección del medio ambiente del País Vasco. A nivel estatal, la regulación específica en materia de
protección de suelo frente a la contaminación se condensa en dos normas: la Ley 10/1998, de 21 de abril, de residuos y el Real Decreto 9/2005, de 14 de enero, por el que se aprueba la relación de actividades potencialmente contaminantes del suelo y los estándares y criterios para la declaración de suelos contaminados. Por último, la Comisión Europea ha publicado
recientemente una propuesta de directiva marco para la protección del suelo que va
acompañada de una estrategia temática y una evaluación de impacto.
La Ley 1/2005 concedió al suelo un marco de protección comparable a aquél
que ya gozaban otros medios como el aire o el agua y pretende remediar la herencia
de suelos contaminados, así como asegurar la protección de la salud humana y del
medio ambiente, evitando en el futuro que el escaso suelo de la CAPV sufra más
agresiones por contaminación. En dicha Ley 1/2005 se establecen límites para una
gran cantidad de compuestos contaminantes. Para poder afirmar si un suelo está o
no contaminado, se establecen unos estándares que se corresponden con los límites
superiores del intervalo de concentraciones en que una determinada sustancia se
encuentra de forma natural en los suelos de la CAPV (valores indicativos de
evaluación VIE-A). En dicha Ley 1/2005 también se establecen los estándares que
indican la concentración de una sustancia en el suelo por encima de la cual el suelo
está alterado y puede estar contaminado, pudiendo suponer un riesgo para la salud
humana (valores VIE-B). En este último caso se requerirá la realización de un
análisis de riesgos para confirmar si el suelo está contaminado. Los estándares VIE-
B se especifican dependiendo del uso al que se destina el suelo (industrial, parque
público, urbano, área de juego, otros). Por último, a las concentraciones por encima
de los valores VIE-C el suelo puede declararse contaminado sin necesidad de
realizar un análisis de riesgos.
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En cumplimiento de los mandatos de la Ley 1/2005 y las metas y objetivos
marcados en la Estrategia Vasca de Desarrollo Sostenible (2002-2020) y el Programa Marco Ambiental (2002-2006), se diseñó el Plan de Suelos Contaminados del País Vasco 2007-2012. El Plan de Suelos Contaminados tiene como meta la protección del suelo contra la
contaminación (la incorporación de sustancias químicas de origen antrópico) y
consta de cuatro objetivos estratégicos: prevenir (dotando a los agentes de
información y motivación para que lleven a cabo pautas más sostenibles), recuperar
(teniendo en cuenta el futuro uso de los suelos), reutilizar (dando nuevos usos a
suelos contaminados desocupados) y valorizar (asignando usos no contaminantes y
de alto valor añadido a los suelos). Además, desarrolla instrumentos tendentes a
reducir el sellado o artificialización del suelo. Para cumplir esos objetivos, el Plan de Suelos plantea tres programas: (i) EZAGUTU, para la obtención, actualización y
gestión de la información sobre la calidad de los suelos, para la generación de
conocimiento científico y técnico, y para la comunicación de este conocimiento a
través de programas de sensibilización, información y formación; (ii) ERAGIN, para
la búsqueda de mejoras en el diseño y la aplicación normativa junto a una mayor
integración de políticas; (iii) EKIN, que incorpora las acciones que contribuyen de
una manera más práctica y directa a la consecución de los cuatro objetivos
estratégicos.
Los avances en la política de suelos contaminados en la CAPV se resumen a
continuación: (i) la gestión de la información relativa a la calidad del suelo
(inventario de emplazamientos con actividades potencialmente contaminantes del
suelo; desarrollo de un sistema de información de la calidad del suelo); (ii) la
generación de conocimiento (elaboración de guías metodológicas y técnicas para la
investigación y recuperación de suelos contaminados; incorporación de líneas de
investigación prioritarias relacionadas con la protección del suelo contra la
contaminación); (iii) la información y formación de agentes implicados en la
protección del suelo; (iv) la elaboración, desarrollo y aplicación del marco legal; (v)
la integración del criterio “calidad del suelo” en otras políticas y coordinación con
otras administraciones; (vi) la prevención de la contaminación del suelo; (vii) la
construcción de infraestructuras (estudio de viabilidad y prediseño de un centro de
gestión de suelos contaminados); (viii) el diseño y puesta en marcha de instrumentos
económicos; y (ix) la reutilización y valorización de suelos alterados en su calidad.
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1.2.4 Recuperación de emplazamientos contaminados en la CAPV
Si bien la legislación desarrollada ha permitido poner los cimientos para la
prevención y corrección de la contaminación del suelo, pretender acabar con dicha
contaminación a corto plazo es un objetivo al cual han renunciado en la actualidad
todos aquellos países que se encuentran a la vanguardia de las políticas de
protección del suelo. En cualquier caso, en la mayor parte de los casos, la prioridad
de actuación se establece sobre los suelos que en el pasado han soportado
actividades susceptibles de contaminar el suelo. Se trata en general de solares e
instalaciones industriales (ruinas en numerosas ocasiones) en el momento del cese,
cuando son sometidas a un proceso de modificación del uso, o al ser objeto de
reutilización; por lo tanto, al requerirse una nueva licencia de actividad debe iniciarse
el citado procedimiento. En este sentido, las intervenciones urbanísticas han
resultado ser el motor de las investigaciones llevadas a cabo en los suelos. De hecho,
en aproximadamente el 50% de emplazamientos inventariados como
potencialmente contaminantes se prevén intervenciones urbanísticas en los
próximos años. Por otro lado, también hay terrenos potencialmente contaminados
fuera del circuito urbanístico, que se localizan en zonas rurales y naturales en las que
los efectos sobre los ecosistemas pueden ser relevantes. Aun así, abordar el
saneamiento de todas las parcelas en las cuales tras una investigación se demuestre la
existencia de un riesgo inaceptable requerirá de una estrategia bien planificada que permita una solución progresiva.
La Ley 1/2005 determina el procedimiento a llevar a cabo para conocer la
calidad del suelo: el proceso comienza con una fase exploratoria, donde se incluye
una investigación histórica sobre las actividades desarrolladas sobre el suelo y se
obtienen datos de las características relevantes del medio físico. Al mismo tiempo, se
realiza una campaña de muestreo y análisis que permita acotar la lista de sustancias
contaminantes presentes en la totalidad del suelo objeto de investigación y su
posible distribución espacial, indicando asimismo su concentración. Si del resultado
de la investigación exploratoria se dedujera la superación de los valores VIE-B para
el uso al que esté destinado el suelo, se dará comienzo a la fase detallada. La
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investigación detallada deberá permitir la correcta delimitación del tipo,
concentración y distribución de las sustancias contaminantes en el suelo y en el resto
de los medios que puedan haberse visto afectados por la contaminación, así como la
cuantificación de los riesgos para la salud de las personas y el medio ambiente
derivados de su presencia. Cuando un suelo fuese declarado contaminado, el órgano
ambiental de la Comunidad Autónoma ordenará la adopción de las medidas de
recuperación necesarias atendiendo a los resultados de las investigaciones y análisis
de riesgos que se hayan realizado.
Por otra parte, la construcción de Celdas de Seguridad para el confinamiento
de tierras contaminadas con residuos de la producción del pesticida Lindane resultó
ser un hito en la breve historia de la remediación de suelos contaminados en la
CAPV. El hexaclorociclohexano (HCH) es el residuo de la fabricación del pesticida
Lindane. Este residuo tóxico presenta serios riesgos para la salud humana y el medio
ambiente. Durante varias décadas, dos empresas ubicadas en la CAPV, Bilbao
Chemicals en Barakaldo y Nexana en Erandio, estuvieron fabricando dicho
pesticida, efectuando una serie de vertidos incontrolados del residuo en más de 37
puntos de la geografía vasca, principalmente en municipios de las márgenes
izquierda y derecha de la Ría del Nervión. La producción total de residuos se estimó
en 95.900 toneladas, de las cuales 18.900 se destinaron a procesos de
aprovechamiento, mientras que el resto fue vertido incontroladamente. Las
soluciones posibles no resultaban viables técnica o económicamente, por lo que se
determinó almacenar las tierras contaminadas en Celdas de Seguridad. Dichas celdas
se construyeron en Argalario (Barakaldo, siendo está la que mayor cantidad de
tierras confinó, 412.000 m3; Figura 1.10a) y en el aeropuerto de Loiu (con 110.000
m3 de tierras contaminadas). Otro elemento clave del proyecto fue la eliminación del
HCH en su estado puro. A tal efecto, se utilizó el proceso de decloración catalizada
por base, propiedad de la Agencia Americana de Medio ambiente. Este proceso
consiste en destruir el HCH a una temperatura de 150°C mediante una reacción
química que lo convierte en cloruro de sodio (sal), triclorobenzeno (TCB) y agua.
Así, durante los dos años de funcionamiento de la estación, se eliminaron 3.200
toneladas de Lindane. Finalmente, 1.074 toneladas de TCB fueron comercializados
como materia prima para la industria química, mientras que la sal sirvió para la
producción de agua salobre.
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En los últimos años, la cantidad de materiales/suelos excavados y gestionados
como residuos peligrosos y el número de emplazamientos contaminados
recuperados en la CAPV está aumentando de forma considerable. Un ejemplo típico
del tipo de actuaciones llevadas a cabo en la CAPV es la desarrollada en el término
municipal de Pasaia (Gipuzkoa) entre 2002 y 2008, en el sitio en el que se ubicaban
las empresas Funpasaia, S.A. (dedicada a la fundición de hierro, talleres mecánicos y
calderería), Laffort y Cía, S.A. (productos enológicos y aromas para la alimentación)
y Campsa (depósito y distribución de combustible), ocupando una superficie de
36.797 m2. Tras realizar las pertinentes investigaciones y análisis de riesgos, se
determinó que el suelo estaba contaminado con TPHs, PCBs, PAHs y metales,
suponiendo un riesgo inaceptable para la salud humana considerando el uso
residencial previsto. El proyecto de recuperación incluyó la excavación y gestión de
los residuos derivados: 16.755.880 kg de residuos no peligrosos, 125.000 kg de
residuos peligrosos y 376.900 kg de agua con hidrocarburos (ver Figura 1.10b).
Figura 1.10: (a) Celda de seguridad de Argalario y (b) gestión de depósitos enterrados durante el saneamiento de Pasaia. Fuente: (a) http://ec.europa.eu/, (b) TERRANOVA S.L.
En la actualidad, la práctica habitual en la CAPV en lo que a recuperación de
suelos contaminados se refiere consiste en su excavación y traslado a vertedero
controlado. No obstante, existen algunas experiencias (por desgracia, todavía un
número insuficiente) de tratamiento de suelos contaminados propiamente dicho en
la CAPV. A este respecto, uno de los tratamientos aplicados on site más comunes es
el “lavado de suelo”, aplicado recientemente, por ejemplo, por la empresa Hera AG
Ambiental en terrenos contaminados por hidrocarburos que previamente habían
estado ocupados por instalaciones de la empresa CHL en Muskiz (Bizkaia). El
a) b)
b)
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lavado de suelo consiste en separar y, a continuación, limpiar (con agua, detergentes,
etc.) exclusivamente aquellas fracciones del suelo que estén más contaminadas (las
fracciones de grano fino como el limo o la arcilla absorben más compuestos
químicos contaminantes que las fracciones de grano grueso como la arena o la
grava). El proceso se realiza en una “unidad de lavado” y permite reducir el volumen
de suelo que requiere una limpieza en profundidad. No obstante, técnicas físico-
químicas como ésta tienen un fuerte efecto adverso en la estructura y funcionalidad
del suelo. Por ello, el uso de tecnologías avanzadas para el tratamiento de suelo
contaminado (en especial in situ) y el desarrollo del concepto de “mejores
tecnologías disponibles” a un coste asumible, constituyen en la actualidad uno de los
retos de mayor importancia de la política de protección del suelo en la CAPV. Sin
duda, el futuro inmediato en este campo se dirige hacia la minimización de riesgos
mediante tecnologías de bajo coste, mucho más que hacia sistemas de
descontaminación en profundidad.
1.2.5 Situación de la fitorremediación a nivel global
Si bien hasta el momento no ha sido utilizada a escala comercial en la CAPV,
la fitorremediación, como técnica de remediación de suelos contaminados, es una
alternativa medioambientalmente respetuosa (utiliza energía solar), estéticamente
agradable, que genera pocos residuos y se puede aplicar in situ en extensiones
amplias. Una vez que las plantas han extraído del suelo las sustancias químicas
contaminantes, éstas pueden tener distintos destinos dentro de la planta:
almacenarse en las raíces, los tallos y las hojas; transformarse en sustancias menos
perjudiciales en el interior de la planta; o bien transformarse en gases que se liberan
al aire cuando la planta transpira. El término fitorremediación se utilizó por primera
vez en los años 80 para describir el uso de plantas para remediar suelos
contaminados o degradados, pero hubo que esperar hasta mediados de los 90 para
observar un rápido desarrollo metodológico en este campo. En la actualidad, la
investigación en fitorremediación implica a cientos de científicos y decenas de
instituciones de investigación y empresas privadas.
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La investigación en fitorremediación discurre por diferentes caminos en
Europa y Estados Unidos. De hecho, aunque los investigadores europeos se han
puesto al mismo nivel que los estadounidenses en lo referente a los fundamentos e
investigación básica en fitorremediación, Estados Unidos tiene una trayectoria
mucho más amplia en cuanto a su aplicación. Asimismo, es importante reseñar que
países emergentes con crecientes problemas de contaminación, como pueden ser
China o India, están prestando cada vez más atención a este tipo de fitotecnologías
(Tang, 2007; Prasad, 2007).
En concreto, hay muy pocas demostraciones prácticas de fitoextracción de
metales más allá de ensayos a pequeña escala y a corto plazo. Las dos
aproximaciones más utilizadas han sido el empleo de (i) especies hiperacumuladoras
como Thlaspi caerulescens (Zn, Cd), Alyssum spp. (Ni, Co; Figura 1.11) y Pteris vittata
(As), y (ii) plantas de alto crecimiento (árboles) como Salix y Populus spp.
Figura 1.11: Fitoextracción de suelos contaminados con Ni (Oregon, EEUU) mediante Alyssum
murale. Fuente: Chaney y cols., 1998.
Una alternativa más realista actualmente para la recuperación de suelos
contaminados con altos niveles de metales es la fitoestabilización, empleando
especies de plantas tolerantes que, a su vez, no transloquen grandes concentraciones
de metales a las partes aéreas (comestibles) al objeto de minimizar su incorporación
a la cadena trófica. Uno de los ejemplos más significativos en Europa es el caso del
proyecto de rehabilitación de la zona minera de La Combe du Saut, en el sur de
Francia (Figura 1.12). En esta mina se extrajo principalmente oro y arsénico. Al
clausurarse la mina en 2004, la cantidad de residuos dejados tras de sí en una
extensión de 120 hectáreas se estimó en 15 millones de toneladas. Las plumas más
contaminadas se trataron mediante métodos de excavación y confinamiento. Por
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otro lado, la contaminación residual y difusa remanente se trató con la
implementación de la tecnología de la fitoestabilización. Para ello, se seleccionaron
especies de plantas presentes en la zona (tratando de incluir plantas de distintos
grupos: gramíneas, leguminosas, etc.). Asimismo, se añadieron granallas de acero
como enmienda, pues presentan un gran potencial para la inmovilización de
arsénico.
Figura 1.12: Remediación de la Combe du Saut (Francia), (a) antes y (b) después. Fuente: www.difpolmine.org.
En Estados Unidos, la fitorremediación se ha aplicado al tratamiento de varios
emplazamientos Superfund, denominados así por incluirse en la lista de una ley
federal diseñada para remediar una serie de emplazamientos sin control o
abandonados con residuos peligrosos para las personas o los ecosistemas. El XII Informe Anual de Tecnologías de Tratamiento para la Remediación de Emplazamientos Contaminados (EPA, 2007) indica que, entre 1982 y 2005, se ha observado una
tendencia creciente hacia los tratamientos in situ. Además, los tratamientos de
incineración van disminuyendo (un 6% entre 2002 y 2005 frente a un 29% entre
1982 y 2002), mientras que los tratamientos denominados innovadores (entre los
que se encuentra la fitorremediación) van en aumento, llegando al 48% en 2005 (la
fitorremediación se utilizó en el 3% de los tratamientos innovadores entre 1982 y
2005).
b)
a)
1. General introduction / introducción General
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D. Glass Associates Inc. estimó (1999) el mercado estadounidense de la
fitorremediación en 3-7 millones de dólares, de los cuales 2-3 millones se atribuían a
la eliminación de contaminantes orgánicos de aguas subterráneas y 1-2 millones a la
eliminación de metales del suelo. Asimismo, auguraba perspectivas de rápido
crecimiento al mercado de las fitotecnologías tanto en Estados Unidos como en
Europa y Canadá. Desgraciadamente, que nosotros sepamos, en la última década, no
se ha realizado ningún análisis de mercado en profundidad sobre las perspectivas
futuras de la fitorremediación. Lo cierto es que, hasta el momento, se han realizado
pocos proyectos de fitorremediación de suelos contaminados a nivel comercial. De
hecho, aunque existen una serie de compañías (e.g., Phytotech Inc., Ecolotree Inc.,
Edenspace Inc.) que ofertan técnicas de fitorremediación como parte de su actividad
comercial (suelen especializarse en unos contaminantes y tecnologías específicos), la
realidad es que todavía hay muchos aspectos de esta incipiente tecnología que deben
ser estudiados/desarrollados.
La búsqueda de plantas tolerantes y acumuladoras/estabilizadoras de metales
sigue siendo, hoy en día, un aspecto fundamental en el desarrollo de la
fitorremediación de metales. Según Peer y cols. (2005), en este momento, la
fitoextracción parece factible para el arsénico y el níquel, mientras que para el resto
de metales la tecnología está lejos de ser aplicable a nivel comercial. De hecho, la
gran mayoría de las especies hiperacumuladoras descubiertas hasta ahora son
hiperacumuladoras de Ni (do Nascimento y Xing, 2006). Mientras tanto, las especies
de plantas capaces de acumular niveles altos de Zn, Pb, Cd, Co, Cu, etc. son mucho
menos numerosas (McGrath y cols., 2001a). Muchos grupos de investigación están
trabajando activamente para esclarecer los mecanismos genéticos y celulares de la
acumulación, transporte y tolerancia a metales de plantas diversas. Por desgracia, la
mayoría de especies hiperacumuladoras son de crecimiento lento y de pequeña
biomasa; por ello, la transferencia de sus genes de tolerancia y acumulación a plantas
de crecimiento rápido y gran biomasa parece a priori una estrategia prometedora
para mejorar la eficacia de los procesos fitoextractores (Chaney y cols. 2007). Sin
embargo, en este punto, es inevitable tener en consideración los conocidos
problemas, de índole diversa, asociados a la utilización de plantas transgénicas.
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En cuanto a la fitoextracción inducida por quelantes se refiere, se debe
investigar en la búsqueda y diseño de agentes quelantes medioambientalmente
respetuosos, de baja toxicidad, que sean a su vez fácilmente biodegradables (Hauser
y cols., 2007). Es innegable que la tasa de degradación de los agentes quelantes es un
aspecto crucial para el futuro de la fitoextracción inducida por quelantes, como se
deriva de los problemas actuales de lixiviación asociados a esta fitotecnología. Entre
otros factores, una prevención efectiva de esta lixiviación es de suma importancia
para la aceptación y posterior aplicación comercial de la fitoextracción inducida; no
obstante, hasta el momento, no se ha hallado ninguna solución satisfactoria a esta
cuestión (Alkorta et al., 2004d).
Para mejorar el rendimiento económico de los procesos fitoextractores de
metales es deseable que el metal a extraer tenga un buen precio en el mercado
(como es el caso del talio, oro, manganeso, cobalto, níquel) que incentive su
recuperación. Otra alternativa de futuro es la utilización de plantas
fitorremediadoras con capacidad para realísticamente generar productos que puedan
tener un valor económico como, por ejemplo, suplemento alimenticio,
acondicionador de suelo, aditivo energético, etc. (Bañuelos, 2006).
Indudablemente, la eficacia y utilidad de este tipo de fitotecnologías está
determinada por el contexto socioeconómico y ecológico en donde se enmarca la
problemática del suelo contaminado en cuestión. En cualquier caso, parece probable
que la fitorremediación continúe siendo en el futuro una tecnología (i) que requiere
periodos de tiempo relativamente largos; (ii) que esté limitada a la parte más
superficial del suelo (a la profundidad a la que penetren las raíces); y (iii) donde la
viabilidad de las plantas y, por ende, del éxito del proceso, dependa estrechamente
de las condiciones edafoclimáticas.
En cualquier, la fitorremediación resulta adecuada para una
sorprendentemente amplia variedad de contextos (e.g., para su aplicación en
extensiones rurales o urbanas amplias que no precisen de una remediación
inmediata, como algunos emplazamientos mineros; para emplazamientos en zonas
protegidas o de alto valor ecológico; para países en vías de desarrollo que necesiten
de una tecnología barata; como tecnología de prevención en zonas circundantes a
un foco de contaminación; etc.), por lo que es esperable y deseable que tenga un
desarrollo considerable durante el siglo XXI.
2. hipotesia eta helburuak / hipótesis y objetivos / hypothesis and objetives
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2. HIPOTESIA ETA HELBURUAK
2.1 Hipotesia
2.2 Helburu orokorra
Lan honen helburu orokorra metalekin kutsaturiko lurzoruetan prozesu
fitoerremediatzaileen efizientzia ebaluatzea izan zen, lurzoru ekosistemaren
osasunaren bioadierazle izateko potentziala duten lurzoruaren hainbat propietate
mikrobiologiko baliatuz.
2.3 Helburu espezifikoak
• Meatze-inguruneetako landare pseudometalofitoak: landare
pseudometalofitoek metalen aurrean duten erantzun fisiologikoaren
kuantifikazioa eta beraien potentzial fitoerremediatzailearen azterketa.
Landare pseudometalofitoen eta errizosferako mikrobio-komunitateen arteko
elkarrekintzen azterketa (4. Kapitulua).
• Fitoerauzketa jarraitua landare hipermetatzaileen bidez: metalek lurzoru
ekosistemaren osasunean duten eraginaren eta Thlaspi caerulescens espezie
hipermetatzailearen bidez egindako fitoerauzketa jarraituaren
eraginkortasunaren neurketa, horretarako lurzoru ekosistemaren osasunaren
Lurzoruko propietate mikrobiologikoek informazio erabakigarria ematen dutelurzoruaren egitura eta prozesuei buruz. Beraz, balio nabarmena dute lurzoruekosistemaren osasunaren bioadierazle gisa, kutsadurak lurzoruaren osasuneanduen eragina aztertzeko bereziki. Horregatik hain zuzen, uste dugu lurzorukopropietate mikrobiologikoak erabilgarritasun handiko eta garrantzi ekologikogoreneko tresnak izan daitezkeela metalekin kutsaturiko lurzoruen prozesufitoerremediatzaileen efizientzia ebaluatzeko.
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bioadierazle izateko potentziala duten lurzoruaren propietate mikrobiologikoak
baliatuz (5. eta 6. Kapituluak).
• Fitoerauzketa jarraitua biomasa altuko laboreen bidez: Basartoak (Sorghum bicolor x sudanense) Zn eta Cd-aren fitoerauzketa jarraiturako duen
potentzialaren azterketa. Lurzoruaren propietate mikrobiologikoen erabilera
(i) metalek lurzoru ekosistemaren osasunean duten eragina eta (ii) prozesu
fitoerauzlearen eraginkortasuna ebaluatzeko (7. Kapitulua).
• Kelatzaileek eragindako fitoerauzketa biomasa altuko laboreen bidez: EDTA
versus EDDSren ahalmenaren ebaluazioa Pb-arekin artifizialki kutsaturiko
lurzoru batean metala solubilizatu eta kardu landareetan (Cynara cardunculus) honen metaketa eragiteko. Bi kelatzaile hauek karduan eta lurzoruko
mikroorganismoengan eragiten duten toxikotasunaren azterketa (8.
Kapitulua).
• Kimiofitoegonkortzea labore belarkaren bidez: lurzoruko propietate
mikrobiologikoen erabilera prozesu kimiofitoegonkortzaile baten
eraginkortasunaren bioadierazle gisa, Lolium perenne eta medeapen sintetiko
versus organiko batekin, Zn, Pb eta Cd-arekin kutsatutako lurzoru bat
erremediatzeko (9. Kapitulua).
• Meatze-lurren fitoerremediazioa metalak jasateko estrategia desberdinak dituzten
landare pseudometalofitoen konbinazioen erabileraren bidez: meatze-lurren
fitoerremediaziorako (fitoerauzketa eta fitoegonkortzea) metalak jasateko estrategia
desberdinak dituzten landare pseudometalofitoen (Thlaspi caerulescens, Rumex acetosa, Festuca rubra) konbinazioak erabiltzeko aukeraren ebaluazioa, lurzoru
ekosistemaren osasunaren bioadierazle izateko potentziala duten lurzoruaren
propietate mikrobiologikoak erabiliz (10. Kapitulua).
• Lurzoruaren osasuna eta ekosistemaren osasuna kontzeptuak uztartzea
ahalbidetuko duen metodologia baten diseinua (10. Kapitulua).
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2. HIPÓTESIS Y OBJETIVOS
2.1 Hipótesis
2.2 Objetivo general
El objetivo general de este trabajo fue evaluar la eficacia de distintas estrategias
de fitorremediación de suelos contaminados con metales mediante la determinación
de un conjunto de propiedades microbiológicas del suelo con potencial bioindicador
de la salud del ecosistema edáfico.
2.3 Objetivos específicos
• Plantas pseudometalofitas en entornos mineros: cuantificación de la
respuesta fisiológica de plantas pseudometalofitas a la presencia de metales y
análisis de su potencial fitorremediador. Estudio de las interacciones entre
plantas pseudometalofitas y sus correspondientes comunidades microbianas
rizosféricas (Capítulo 4).
• Fitoextracción en continuo con plantas hiperacumuladoras: evaluación del
impacto de metales sobre la salud del ecosistema edáfico y de la eficacia de
un proceso de fitoextracción en continuo con la especie hiperacumuladora
Thlaspi caerulescens, mediante el empleo de propiedades microbiológicas del
Las propiedades microbiológicas del suelo aportan información crucial sobre la estructura y los procesos del suelo, por lo que tienen un notable valor como bioindicadores de la salud del ecosistema edáfico y, en particular, del impacto de la contaminación sobre dicha salud. Es por ello que consideramos que las propiedades microbiológicas del suelo pueden ser herramientas metodológicas de gran utilidad y máxima relevancia ecológica a la hora de evaluar la eficacia de procesos fitorremediadores de suelos contaminados con metales.
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suelo con potencial bioindicador de la salud del ecosistema edáfico
(Capítulos 5 y 6).
• Fitoextracción en continuo con cultivares de alta biomasa: estudio del
potencial del sorgo (Sorghum bicolor x sudanense) para la fitoextracción en
continuo de Zn y Cd. Evaluación mediante el empleo de propiedades
microbiológicas del suelo del (i) efecto de los metales sobre la salud del
ecosistema edáfico y (ii) la eficacia del proceso fitoextractor (Capítulo 7).
• Fitoextracción inducida por quelantes con cultivares de alta biomasa:
evaluación de la capacidad del EDTA versus EDDS para solubilizar Pb de un
suelo artificialmente contaminado con este metal e inducir su acumulación en
plantas de cardo (Cynara cardunculus). Estudio de la toxicidad de estos dos
quelantes sobre el cardo y los microorganismos del suelo (Capítulo 8).
• Quimiofitoestabilización con cultivares herbáceos: utilización de propiedades
microbiológicas del suelo como herramienta monitorizadora de la eficacia de
un proceso quimiofitoestabilizador, con Lolium perenne y enmienda sintética
versus orgánica, para remediar un suelo minero contaminado con Zn, Pb y Cd
(Capítulo 9).
• Fitorremediación de suelos mineros mediante el empleo de combinaciones
de plantas pseudometalofitas con distintas estrategias de tolerancia a metales:
evaluación de la posibilidad de utilizar combinaciones de plantas
pseudometalofitas con distintas estrategias de tolerancia a metales (Thlaspi caerulescens, Rumex acetosa, Festuca rubra) para la fitorremediación
(fitoextracción y/o fitoestabilización) de suelos mineros, mediante el empleo
de propiedades microbiológicas del suelo con potencial bioindicador de la
salud del ecosistema edáfico (Capítulo 10).
• Diseño de una metodología que permita vincular los conceptos de salud del
suelo y salud del ecosistema (Capítulo 10).
2. hipotesia eta helburuak / hipótesis y objetivos / hypothesis and objetives
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2. HYPOTHESIS AND OBJECTIVES
2.1 Hypothesis
2.2 Main objective
The main objective of the current work was to assess the efficiency of different
phytoremediation strategies of metal polluted soils through the determination of a
variety of soil microbiological properties with potencial as bioindicators of soil
health.
2.3 Specific objectives
• Pseudometallophytes in mining sites: evaluation of the physiological
response of pseudometallophytes in the presence of metals and analysis of
their phytoremediation potential. Study of the interactions between
pseudometallophytes and their corresponding rhizosphere microbial
communities (Chapter 4).
• Continuous phytoextraction with hyperaccumulators: assessment of the
impact of metals on soil health as well as of the efficiency of a continuous
phytoextraction process with the hyperaccumulator Thlaspi caerulescens through the determination of a variety of soil microbiological properties with
potential as bioindicators of soil health (Chapters 5 and 6).
• Continuous phytoextraction with high biomass cultivars: study of the
potential of sorghum (Sorghum bicolor x sudanense) for continuous
phytoextraction of Zn and Cd. Assessment, through the determination of
Soil microbiological properties provide invaluable information on soil structureand processes, and consequently are most useful as bioindicators of soil health and,in particular, of the impact of pollutants on such health. Therefore, we consider thatsoil microbiological properties can be valid, ecologically-relevant methodological toolsto assess the efficiency of phytoremediation processes of soils polluted with metals.
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soil microbiological properties, of (i) the effect of metals on soil health and
(ii) the efficiency of the phytoextraction process (Chapter 7).
• Chelate-induced phytoextraction with high biomass cultivars: assessment of
the capacity of EDTA versus EDDS to solubilize Pb from an artificially
polluted soil and to induce Pb accumulation in cardoon (Cynara cardunculus) plants. Study of the toxicity of both chelating agents on cardoon plants and
soil microorganisms (Chapter 8).
• Chemophytostabilization with herbaceous cultivars: utilization of soil
microbiological properties as monitoring tools of the efficiency of a
chemophytostabilization process, with Lolium perenne and synthetic versus organic amendment, to remediate a mine soil polluted with Zn, Pb and Cd
(Chapter 9).
• Phytoremediation of mine soils using combinations of pseudometallophytes
with different strategies of metal tolerance: assessment of the possibility of
using combinations of pseudometallophytes with different strategies of metal
tolerance (Thlaspi caerulescens, Rumex acetosa, Festuca rubra) for the
phytoremediation (phytoextraction and/or phytostabilization) of mine soils,
through the determination of soil microbiological properties with potential as
bioindicators of soil health (Chapter 10).
• Design of a methodology to link the concepts of soil health and ecosystem
health (Chapter 10).
3. escenario y procedimientos Generales
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3. ESCENARIO Y PROCEDIMIENTOS GENERALES
NOTA INTRODUCTORIA: en el presente capítulo se describe el emplazamiento minero en el cual hemos realizado estudios en campo y muestreado suelo crónicamente contaminado con metales para posteriores experimentos en invernadero. Asimismo, se detallan las condiciones de cultivo de los diversos ensayos llevados a cabo en invernadero en este trabajo. Parte de estos experimentos han sido realizados con muestras de suelo de praderas localizadas en Derio y Larrauri (Bizkaia) que posteriormente han sido contaminadas de forma artificial. Por otro lado, en este capítulo, se incluye una breve descripción de las propiedades microbiológicas del suelo con potencial bioindicador de la salud del ecosistema edáfico empleadas en este trabajo. Los materiales y métodos particulares de cada experimento se describen con mayor detalle en los capítulos correspondientes. Finalmente, las referencias bibliográficas de los métodos aquí descritos se mencionan en los artículos correspondientes.
3.1 Escenario de estudio y condiciones de cultivo
3.1.1 Escenario
El emplazamiento minero en torno al cual se ha desarrollado parte de este
trabajo (Capítulos 4, 9 y 10) pertenece a una antigua explotación de Pb, conocida
localmente como “mina Txomin” (Figura 3.1), que está localizada en el municipio
vizcaíno de Lanestosa (latitud 43°13´; longitud 3°26´). Al parecer, esta mina,
actualmente abandonada, estuvo operativa desde las primeras décadas del siglo XX
hasta finales de los años 70; no obstante, se carece de documentos que den
constancia del periodo exacto de actividad minera así como de su magnitud e
intensidad. Dentro de la mina, la zona de estudio está situada en una zona
montañosa, con pendientes de entre 30 y 50%, a unos 440 metros sobre el nivel del
mar, en las laderas de orientación oeste que drenan sobre el río Kalera. En el área de
explotación, se encuentran diseminados distintos emplazamientos de extracción y
procesado del mineral como cortas de extracción a cielo abierto, galerías
subterráneas de extracción, balsas de lavado de mineral y decantación de lodo,
escombreras de deposición de escoria y lodo, etc. La dispersión de estos
emplazamientos potencialmente contaminantes, junto con la orografía de la zona
expuesta a vientos frecuentemente moderados, ha dado como resultado varias
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hectáreas de suelo con distinto grado de contaminación por metales (especialmente
Zn, Pb y Cd).
Figura 3.1: Emplazamiento minero de Lanestosa. Fuente: NEIKER-Tecnalia.
Esta gran superficie de suelo contaminado, unida al hecho de que el uso del
suelo en esa zona es casi exclusivamente de tipo rural, ofrece una excelente
oportunidad para la aplicación de la fitorremediación como tecnología de bajo coste
y medioambientalmente respetuosa para recuperar emplazamientos contaminados
con metales. Asimismo, es importante enfatizar que la mina actúa como preciado
banco de germoplasma de especies de plantas de gran potencial para su utilización
en fitotecnologías diversas y para investigaciones sobre los mecanismos de
adaptación y tolerancia a metales en plantas. En efecto, dentro de la mina, las zonas
con mayor concentración de metales en suelo se encuentran colonizadas por un tipo
de vegetación (dominada por la especie Festuca rubra) que presenta un alto grado de
tolerancia a metales. Estas especies altamente tolerantes, en combinación con
diferentes prácticas agrícolas, pueden ser por ejemplo empleadas para la
revegetación de suelos desnudos en los que la alta concentración de metal, unida a la
escasez de nutrientes, haya impedido el establecimiento de una cubierta vegetal
estable. Por otro lado, en las zonas de la mina contaminadas con niveles moderados
de metales, la comunidad vegetal es mucho más diversa, siendo las especies más
abundantes en términos de individuos Festuca rubra, Agrostis capilaris, Thlaspi caerulescens, Jasione montana, Ulex europaeus, Rumex acetosa, Pteridium aquilinum y Plantago lanceolata (Barrutia, 2008). Algunas de las especies que se encuentran en estos
emplazamientos mineros, amén de un alto grado de tolerancia a metales, presentan
3. escenario y procedimientos Generales
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la rara habilidad de concentrar concentraciones elevadas de metal en sus partes
aéreas, lo que les convierte en potenciales candidatas para su empleo en procesos
fitoextractores (e.g., Thlaspi caerulescens, Rumex acetosa; Figura 3.2).
Figura 3.2: Rumex acetosa – acumuladora (panel izquierdo), (b) Thlaspi caerulescens – hiperacumuladora (panel derecho). Fuente: NEIKER-Tecnalia.
Por otro lado, como se ha mencionado anteriormente, parte de los
experimentos de fitorremediación en este trabajo (Capítulos 5-8) han sido realizados
con suelo artificialmente contaminado con metales. En estos casos, el suelo se
muestreó (capa superficial: 0-30 cm) en una pradera natural localizada en el
municipio vizcaíno de Derio (latitud 43°17´; longitud 2°52´; 65 m por encima del
nivel del mar). Excepcionalmente, el suelo utilizado en el ensayo descrito en el
Capítulo 8 fue muestrado en una pradera de similares características localizada en
Larrauri (Bizkaia; latitud 43°22´; longitud 2°48´; 85 m por encima del nivel del mar).
La Figura 3.3 muestra de forma esquemática el procedimiento empleado para
muestrear suelo (las imágenes corresponden a la pradera de Derio): (a) se seleccionó
una zona de la pradera, homogénea visualmente y de acuerdo a caracterización
físico-química previa; (b) posteriormente, se excavó la tierra a una profundidad de
30 cm; (c) se tamizó por un tamiz de 4 cm de diámetro; y finalmente (d) se
contaminó artificialmente con metales, utilizando una hormigonera para facilitar su
homogeneización. Después de un periodo de estabilización en oscuridad y a
temperatura y humedad constantes, variable en su duración según el ensayo, el suelo
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se trasladó al invernadero, distribuyó en tiestos y, finalmente, se establecieron los
tratamientos correspondientes en cada experimento.
Figura 3.1: Emplazamiento minero de Lanestosa
Figura 3.3: Muestreo de suelo para su utilización en ensayos a escala microcosmos: (a) detalle de la
pradera de Derio, (b) cava, (c) tamizado y (d) contaminación artificial con hormigonera. Fuente: NEIKER-Tecnalia.
3.1.2 Condiciones de cultivo
Las semillas de las especies de gramíneas utilizadas en los distintos estudios
(i.e., Sorghum bicolor, Lolium perenne, Festuca rubra) se sembraron directamente en los
tiestos de ensayo. Sin embargo, las semillas del resto de especies estudiadas (i.e., Thlaspi caerulescens, Rumex acetosa, Cynara cardunculus) fueron germinadas en una
cámara de germinación en bandejas (en mezcla de perlita:vermiculita 2:3 v/v o en
compost John Innes Nº 2 autoclavado) previamente a su transplante a los tiestos de
ensayo. Las condiciones de la cámara de germinación fueron las siguientes:
temperatura de 20/16 ºC día/noche, humedad relativa de 70%, y una intensidad de
b)
c) d)
a)
3. escenario y procedimientos Generales
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PAR (radiación fotosintéticamente activa) de 300 μmol fotón m-2 s-1 obtenida con
lámparas frías blancas.
Figura 3.4: Invernaderos de NEIKER-Tecnalia, Derio. Fuente: NEIKER-Tecnalia.
Los ensayos a escala microcosmos se realizaron en los invernaderos de
NEIKER-Tecnalia en Derio, Bizkaia (Figura 3.4). Estos invernaderos disponen de
un sistema automático de ventilación y calefacción, así como de un sistema
electrónico de monitorización de ambos parámetros localizado en el interior de la
nave. La temperatura mínima establecida fue de 14ºC/18ºC noche/día, y la máxima
de 16ºC/20ºC noche/día. La temperatura para la apertura de las compuertas fue de
20ºC/25ºC noche/día. Excepcionalmente, el ensayo presentado en el Capítulo 5 de
este trabajo se realizó en el invernadero de la Facultad de Ciencia y Tecnología de la
Universidad del País Vasco (EHU/UPV), acondicionado a una temperatura entre
18-25 ºC durante el día y 17-24 ºC por la noche, con un fotoperiodo de 14 horas de
luz. La iluminación natural fue suplementada con lámparas frías blancas para
alcanzar una intensidad de PAR mínima de 400 μmol fotón m-2 s-1.
3.2 Parámetros analíticos
3.2.1 Propiedades físico-químicas y microbiológicas con potencial indicador de la salud del ecosistema edáfico
Una vez finalizada la fase de crecimiento en los ensayos, el material vegetal se
cosechó, lavó y secó, previamente a la determinación de su peso seco. Por otro lado,
el suelo muestreado en los ensayos se separó en dos partes: (i) una porción destinada
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a los análisis de parámetros físico-químicos, la cual se secó al aire y tamizó por un
tamiz de 2 mm de diámetro; (ii) una segunda parte destinada a los análisis de
parámetros microbiológicos, que fue tamizada en fresco por un tamiz de 2 mm de
diámetro. Las muestras destinadas a la determinación de parámetros
microbiológicos se almacenaron a 4ºC hasta su posterior análisis.
En relación con los indicadores de la salud del suelo, tradicionalmente, la
calidad/salud* del suelo se ha venido determinando en base a la cuantificación de
parámetros físico-químicos con potencial indicador. Sin embargo, los suelos son
sistemas vivos que contienen, por ejemplo, una enorme cantidad de microorganismos
responsables en último término del 80-90% de la actividad biológica y los procesos
edáficos. Estos procesos biológicos no sólo están íntimamente unidos al
mantenimiento de la estructura y fertilidad del suelo sino que, además, son
potencialmente más sensibles y responden con mayor rapidez frente a los
cambios/perturbaciones introducidos en el ecosistema suelo. Asimismo, una de las
más importantes ventajas de los procesos y parámetros (micro)biológicos para su
utilización como bioindicadores** es su carácter integrador, que agrupa la totalidad de
los parámetros físicos, químicos y biológicos que definen un ecosistema. Los
principales indicadores biológicos de la salud del suelo son (Alkorta y cols., 2003b):
biomasa microbiana; respiración del suelo; nitrógeno potencialmente mineralizable;
actividades enzimáticas; abundancia de microflora; abundancia de fauna del suelo
(macro-, meso-, microfauna); enfermedades de raíces (patógenos de plantas);
biodiversidad del suelo (estructural y funcional); estructura de la red trófica;
biodiversidad de plantas y composición florística; y crecimiento de plantas.
*Calidad/salud: “calidad del suelo” se define como el grado de aptitud de un determinado suelo para desempeñar una función específica (e.g., producir una cosecha); por el contrario, el término “salud del suelo” engloba las características o atributos ecológicos de un suelo que tienen implicaciones más allá de su calidad o capacidad para desempeñar una función específica y que son responsables de su funcionamiento, sostenibilidad e integridad ecológica. El término “calidad” es más utilizado desde una perspectiva antropocéntrica, mientras que el término “salud” se contempla habitualmente desde una perspectiva biocéntrica-ecocéntrica.
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**Un bioindicador (o, más correctamente, indicador biológico) se define como “un organismo, parte de un organismo, producto de un organismo, grupo de organismos o procesos biológicos que pueden ser utilizados para obtener información sobre todo o parte del medio ambiente”.
3.2.1.1Propiedades microbiológicas con potencial indicador de la salud del ecosistema edáfico
Actividades enzimáticas
Los enzimas del suelo son los mediadores y catalizadores de la mayoría de los
procesos del suelo y, por lo tanto, presentan un gran potencial para suministrar una
evaluación integradora de la salud del ecosistema edáfico. La mayor parte de los
enzimas encontrados en los suelos son hidrolasas, pero también se han encontrado
oxidorreductasas, transferasas y liasas. Aunque es bien cierto que algunos enzimas
existen únicamente como parte de células viables, suministrando así información
sobre la actividad del componente biológico presente en ese momento en el suelo
(e.g., deshidrogenasa), la mayoría de los enzimas se encuentran tanto en células
viables como en forma extracelular (componente abiótico) en la solución del suelo o
complejadas a la matriz edáfica. Gracias a esta última característica es posible
incorporar un componente “histórico” a los ensayos enzimáticos, de forma que se
reflejen los cambios acumulados en el tiempo sobre la salud del ecosistema edáfico.
La mayoría de los métodos de determinación de actividad enzimática se basan
en la determinación colorimétrica del producto liberado por la actividad cuando el
suelo tamponado es incubado a una temperatura óptima, en condiciones de
substrato saturantes (Figura 3.5a). Existe un amplio grupo de enzimas que pueden
ser utilizados como bioindicadores de la salud del ecosistema edáfico: hidrolasas
(fosfatasas, sulfatasas, ureasa, proteasas, peptidasas, deaminasas, celulasas),
oxidorreductasas (deshidrogenasas, fenol oxidasas, peroxidasas, catalasas), liasas y
transferasas (Burns y Dick, 2002).
En este trabajo se han determinado las siguientes actividades enzimáticas:
• Actividad deshidrogenasa (Capítulos 4, 7, 8, 9 y 10; método descrito en detalle en
los Capítulos 4 y 9), la cual forma parte integral de las células intactas y refleja
la totalidad de las actividades oxidativas de la microflora edáfica, de
importancia crucial para la oxidación de la materia orgánica del suelo. En otras
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palabras, representa la actividad metabólica oxidativa in situ de los organismos
del suelo.
• Actividad fostatasa ácida (Capítulos 4, 5, 8, 9 y 10; método descrito en detalle en
los Capítulos 5 y 9) y alcalina (método descrito en detalle en el Capítulo 5),
implicadas en la liberación de fosfato disponible para las plantas a partir de la
materia orgánica del suelo.
• Actividad β-glucosidasa (Capítulos 4, 5, 8, 9 y 10; método descrito en detalle en
los Capítulos 5 y 9), implicada en la liberación de glucosa. Este enzima
hidroliza polímeros de los residuos vegetales (i.e., celobiosa y maltosa)
aportando los esqueletos de carbono y energía esenciales para el crecimiento
de los organismos heterótrofos del suelo. Asimismo, este enzima inicia los
procesos que conducen a la mineralización y/o estabilización del carbono
residual vegetal.
• Actividad ureasa (Capítulos 4, 5 y 10; método descrito en detalle en el Capítulo
5), enzima importante en el ciclo del nitrógeno que cataliza la hidrólisis de urea
en CO2 y NH3.
• Actividad arilsulfatasa (Capítulos 4, 5, 8, 9 y 10; método descrito en detalle en los
Capítulos 5 y 9), responsable de la mineralización de ésteres orgánicos de
azufre para producir sulfato inorgánico. Los ésteres de sulfato microbianos son
propios de hongos y no de bacterias, por lo que una elevada actividad
arilsulfatasa puede relacionarse con la presencia de hongos.
Nitrógeno potencialmente mineralizable
El proceso de mineralización de nitrógeno se puede definir como la
conversión de nitrógeno orgánico a formas minerales disponibles para las plantas. El
primer paso de esta transformación consiste en pasar del nitrógeno orgánico a
amonio, y es realizado exclusivamente por microorganismos heterótrofos, siendo
posible tanto en condiciones aeróbicas como en anaeróbicas. El nitrógeno
potencialmente mineralizable es un parámetro con gran valor indicador de la
fertilidad del suelo. El método utilizado en los Capítulos 8 y 9 contempla la
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mineralización de nitrógeno orgánico ocurrida durante una semana en condiciones
de anaerobiosis.
Respiración (basal e inducida por substrato)
La respiración del suelo es un parámetro bien establecido para monitorizar la
descomposición de la materia orgánica. No obstante, la interpretación de los datos
de respiración en términos de salud del ecosistema edáfico es ciertamente
problemática pues, en ocasiones, además de que su aumento puede indicar
condiciones de estrés, la descomposición de la materia orgánica puede no ser
deseable, mientras que en otras la liberación de nutrientes producida por dicha
descomposición en el tiempo preciso en que las plantas los demandan es, sin duda,
una característica deseable. En el método de determinación utilizado en este trabajo,
el suelo se introduce en un tarro de vidrio de cierre hermético junto con un vasito
con una solución de sosa, donde se atrapa el CO2 producido durante la respiración.
Transcurrido el tiempo correspondiente se valora la sosa remanente con ácido
clorhídrico (Figura 3.5b). La respiración basal del suelo se ha medido en los
Capítulos 6, 7 y 8, estando descrita en detalle en este último.
La respiración inducida por substrato se basa en proveer a la biomasa
microbiana con una concentración saturante de un substrato fácilmente
mineralizable (generalmente, glucosa) y el posterior seguimiento de la respiración
durante un periodo relativamente corto. La tasa de respiración en presencia de una
concentración saturante de substrato representa la velocidad de reacción máxima y
es, por ende, proporcional a la biomasa microbiana potencialmente activa. La
respiración inducida se ha medido en este trabajo utilizando por un lado glucosa
como substrato (Capítulos 6, 7 y 8; método descrito en detalle en el Capítulo 8) y
por otro empleando una solución modelo de rizodepósito (Capítulo 7). Esta
solución de rizodepósito (que contiene 50 mM fructosa, 50 mM glucosa, 50 mM
sucrosa, 25 mM ácido succínico, 25 mM ácido málico, 12.5 mM arginina, 12.5 mM
serina y 12.5 mM cisteína) aporta a priori datos de mayor relevancia ecológica que la
glucosa para el estudio de las comunidades microbianas rizosféricas.
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Carbono de la biomasa microbiana
La biomasa microbiana se refiere al componente vivo de la materia orgánica
del suelo. La biomasa microbiana del suelo responde rápidamente a condiciones
cambiantes en el suelo, tales como la adición de substratos o el aumento del
contenido en metales. Así, la biomasa microbiana parece ser una medida más
sensible frente a los cambios producidos en la salud del ecosistema edáfico que la
proporcionada por el contenido en materia orgánica total.
En el método de fumigación/extracción aquí empleado, el suelo se fumiga con
cloroformo, al objeto de permeabilizar las membranas celulares. El aumento en el
carbono orgánico extraíble, comparado con un control sin fumigar, es la medida de
la biomasa microbiana total. Este método se ha utilizado en los Capítulos 4, 9 y 10
(se describe en detalle en el Capítulo 4).
Figura 3.5: Equipamientos para (a) actividades enzimáticas, (b) respiración y (c) perfiles fisiológicos a nivel de comunidad microbiana obtenidos con placas EcoBiologTM. Fuente:
NEIKER-Tecnalia.
Abundancia de genes por PCR a tiempo-real
La técnica de PCR a tiempo-real se puede utilizar para cuantificar la
abundancia de genes taxonómicos y funcionales en el suelo. Este análisis combina la
detección a tiempo final de la PCR tradicional con tecnologías de detección por
fluorescencia, para así medir la acumulación de copias “a tiempo-real” en cada ciclo
b) c) a)
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de amplificación de la PCR. El número de copias detectado en la fase exponencial
temprana es proporcional a la concentración presente en la muestra inicial. La
información cuantitativa que se genera es de gran ayuda para entender los roles y las
contribuciones de grupos microbianos y funcionales particulares al funcionamiento
del ecosistema edáfico.
El grupo de Ecología Microbiana Terrestre del Prof. George A. Kowalchuk
(Centro de Ecología Terrestre del Instituto de Ecología de Holanda, Heteren) tiene
gran experiencia en ésta y similares técnicas moleculares aplicadas a muestras de
suelo. Con su colaboración, se utilizó este método en los Capítulos 6 y 10, donde se
cuantificaron genes para bacterias totales, oxidadores de amonio y degradadores de
quitina, así como para hongos totales.
Perfiles fisiológicos a nivel de comunidad (Biolog EcoPlatesTM)
Los perfiles fisiológicos de utilización de fuentes de carbono son ampliamente
utilizados a modo de huella digital catabólica en estudios sobre el efecto de
diferentes variables en la salud del ecosistema edáfico. Las Biolog EcoplatesTM,
comercialmente disponibles, constan de 31 pocillos (por triplicado) que contienen
distintos substratos de carbono (aminas/amidas, aminoácidos, carbohidratos, ácidos
carboxílicos, polímeros), más un pocillo como blanco para cada réplica. El tetrazolio
presente en las Biolog EcoplatesTM se reduce con NADH para formar una
coloración morada. La tasa y la extensión de formación de color morado en cada
pocillo indican la tasa y la extensión a la que ocurre la respiración microbiana
utilizando el substrato presente en el citado pocillo (Figura 3.5c). Este método se ha
utilizado en los Capítulos 4, 5, 7, 8, 9 y 10, estando descrito con más detalle en los
Capítulos 5 y 8.
Microarray de genes funcionales (Geochip)
Los microarrays son una tecnología revolucionaria innovadora basada en la
síntesis o fijación de sondas que representan los genes sobre un substrato sólido,
que posteriormente son expuestas a las moléculas diana. El nivel de hibridación
entre la sonda específica y la molécula diana se indica mediante fluorescencia y se
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mide por análisis de imagen (Figura 3.6a). Recientemente, el grupo de investigación
del Dr. Jizhong Zhou del Instituto de Genómica Ambiental de la Universidad de
Oklahoma ha diseñado, construido y evaluado un microarray de genes funcionales,
denominado Geochip, que contiene más de 24.000 sondas de genes implicados en
diversos procesos biogeoquímicos, ecológicos y medioambientales (ciclos del
carbono, nitrógeno y azufre; utilización de fósforo; degradación de contaminantes
orgánicos; reducción y resistencia a metales; etc.). El Geochip es de suma utilidad a
la hora de estudiar las relaciones entre la diversidad microbiana (más concretamente,
la diversidad de genes) y los procesos y funciones del ecosistema suelo. Este
microarray de genes funcionales se ha utilizado en el Capítulo 6.
Figura 3.6: (a) Microarray Geochip, (b) cubeta de DGGE y (c) gel de DGGE. Fuente: NEIKER-Tecnalia.
Huella genética de las comunidades microbianas (DGGE)
La electroforesis en gel de gradiente desnaturalizante es un método molecular
que separa productos de DNA de la misma extensión pero de distinta secuencia
(pertenecientes a distintas especies) generados por PCR (Figura 3.6b, c). Los
cebadores utilizados pueden amplificar tanto secuencias de genes de RNA
ribosómico como de genes funcionales, sirviendo de descriptores de la diversidad
b) c)
a)
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estructural o funcional, respectivamente. La separación se basa en la movilidad
disminuida de moléculas de DNA en un gradiente de compuestos desnaturalizantes.
Así, se visualizan una serie de bandas con las que se obtiene una huella de la
comunidad microbiana objeto de estudio. Con la colaboración del grupo del Prof.
George A. Kowalchuk, se ha aplicado la técnica del DGGE en la caracterización de
las comunidades de bacterias (cebadores F968-GC/R1378; Capítulos 6 y 10) y
hongos edáficos (cebadores FR1_GC/FF390; Capítulo 10) del suelo.
Ensayos de estabilidad (resiliencia-resistencia) del ecosistema suelo
La estabilidad de un suelo se define como la habilidad para mantener su
estructura y funcionamiento en presencia de una perturbación. El concepto de
estabilidad incluye tanto el de resiliencia, la capacidad del sistema para recuperarse tras
una perturbación, como el de resistencia, la capacidad innata del sistema para soportar
la perturbación. Se puede medir tras la aplicación de un estrés (por ejemplo, un
calentamiento transitorio a 40 ºC o una adición de un metal tóxico) para
posteriormente ver la evolución de parámetros como, por ejemplo, la respiración
basal o la tasa potencial de nitrificación (esta última se calcula cuantificando la
oxidación de amonio por acumulación de nitrito durante un tiempo de incubación
determinado). A partir de estos datos se pueden calcular diversos índices de
resistencia y resiliencia del suelo. Este ensayo se ha utilizado en el Capítulo 10 como
parte de una evaluación integrada de la salud del ecosistema edáfico, junto con otros
atributos, léase, vigor y organización.
Bioensayos de productividad y toxicidad con plantas
La capacidad de un suelo para mantener el crecimiento de plantas es un
indicador de gran utilidad para evaluar su salud. De hecho, en los sistemas agrícolas,
se considera que la evolución de la productividad de los cultivos es uno de los
indicadores biológicos de más valor a la hora de monitorizar la calidad del suelo. En
este trabajo, la productividad del suelo se ha medido utilizando alfalfa como especie
modelo en el Capítulo 6 y sorgo en el Capítulo 10.
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Por otro lado, los índices de germinación pueden aportar información valiosa
sobre la fitotoxicidad de un determinado suelo derivada de, por ejemplo,
contaminación por metales. El ensayo de germinación con la especie Lepidium sativum (en el que se cuantifica tanto la germinación como el crecimiento radicular
después de la exposición a un extracto del suelo) se ha utilizado como medida de
fitotoxicidad en el Capítulo 7.
3.2.1.2 Propiedades físico-químicas con potencial indicador de la salud del ecosistema edáfico
Los parámetros físico-químicos, siendo los más estudiados tradicionalmente
(por ello, y por ser los indicadores microbiológicos el objeto principal de este
trabajo, no se describen en detalle en este apartado) siguen aportando información
de gran valor a la hora de evaluar la salud del ecosistema edáfico. Así, al finalizar los
ensayos, y siguiendo métodos oficiales de análisis, se midieron diversos parámetros
físico-químicos en las muestras de suelo: pH, variable fundamental que establece los
límites para el desarrollo de las plantas y los microorganismos del suelo; contenido en materia orgánica y carbono orgánico soluble en agua, componentes del suelo determinantes
de su fertilidad; nutrientes como nitrógeno total, nitratos, fósforo y potasio extraíble; capacidad de intercambio catiónico, relacionada con la disponibilidad de nutrientes;
conductividad eléctrica, que define los límites de actividad vegetal y microbiana; textura,
de importancia para la retención y transporte de agua, nutrientes y compuestos
químicos; capacidad de retención hídrica, determinante para conocer la cantidad de agua
disponible, etc. Análogamente, todos los suelos objeto de estudio fueron
caracterizados físico-químicamente antes del comienzo de los ensayos.
3.2.2 Parámetros fisiológicos de plantas
La fitotoxicidad causada por los metales sobre las plantas se puede estudiar en
base a medidas de fluorescencia y contenido en pigmentos. Asimismo, es posible
evaluar la tolerancia y fitotoxicidad causada por metales en plantas monitorizando la
evolución de compuestos antioxidantes. En colaboración con el grupo del Prof. José
María Becerril del Departamento de Biología Vegetal y Ecología, Universidad del
País Vasco, en diversos ensayos, se realizaron medidas de fluorescencia (Capítulos 5
y 6) y se cuantificó la presencia de una serie de pigmentos fotosintéticos (clorofilas a
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y b, carotenoides, violaxantina, anteraxantina, zeaxantina, γ- y α-tocoferol) y
antioxidantes lipofílicos (carotenoides y tocoferol) (Capítulos 4, 5, 6 y 9; en los
Capítulos 5 y 9 se midieron solamente clorofilas y carotenoides). Las medidas de
fluorescencia se realizaron con un fluorímetro portátil. La toma de muestras para los
análisis fisiológicos se realizó en tejido adaptado a la oscuridad durante 12 h a
temperatura ambiente. Las muestras vegetales (0.02 g de hoja) se congelaron en
nitrógeno liquido y almacenaron a -80ºC hasta su análisis por HPLC de fase reversa.
Figura 3.7: (a) Rhizons tipo MOM, (b) espectrómetro de absorción atómica de llama. Fuente: NEIKER-Tecnalia.
3.2.3 Concentración de metales en suelo y planta
Al final de cada ensayo, se midió la concentración total (digeridas bien con
“aqua regia” o bien con una mezcla de HNO3/HClO4) y extraíble en CaCl2 de los
diferentes metales en el suelo, para así poder evaluar su variación tras la aplicación
de las distintas técnicas fitorremediadoras. Además, en el Capítulo 8 se utilizaron
Rhizons tipo MOM (Figura 3.7a) para medir la concentración de metal en la
solución del suelo. Asimismo, en el Capítulo 10 se incluye un procedimiento de
extracción secuencial de los metales del suelo (i.e., fracción soluble/intercambiable;
fracción unida a carbonatos; fracción unida a óxidos de Fe y Mn; fracción unida a
materia orgánica; fracción residual). Por otro lado, los tallos y raíces cosechados en
los ensayos fueron digeridos con una mezcla de HNO3/HClO4.
Posteriormente, la concentración de metales en las digestiones y extracciones
se determinó mediante Espectrometría de Absorción Atómica de Llama (FAAS,
Varian Spectra AA-250 plus; Figura 3.7b) y Espectrometría de Emisión Atómica por
plasma (ICP-AES, Varian VISTA-MPX).
b) a)
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4. INTERACTIONS BETWEEN PLANT AND RHIZOSPHERE MICROBIAL COMMUNITIES IN A METALLIFEROUS SOIL
Epelde et al., submitted to Journal of Soils and Sediments
4.1 Abstract
The main objective was to study the relationships between
pseudometallophytes and their rhizosphere microbial communities in a mine soil
chronically polluted with high levels of Cd, Pb and Zn. Physiological response (as
reflected by the content of lipophilic antioxidants and photosynthetic pigments) and
phytoremediation potential of the studied pseudometallophytes were also
investigated.
Several plant consortia consisting of 1-4 metallicolous pseudometallophytes
with different metal-tolerance strategies (Thlaspi caerulescens: hyperaccumulator; Jasione montana: accumulator; Rumex acetosa: indicator; and Festuca rubra: excluder), together
with their corresponding rhizosphere microbial communities, were collected from a
severely polluted mine area. Plant biomass, as well as lipophilic antioxidants
(carotenoids and tocopherols) and photosynthetic pigments were measured. The
following physicochemical and microbial properties were determined in rhizosphere
soil to study the relationships between aboveground plant and belowground
microbial communities: pH, water soluble organic C, microbial biomass C, enzyme
activities (dehydrogenase, β-glucosidase, arylsulphatase, acid phosphatase, urease)
and community-level physiological profiles with Biolog EcoplatesTM. Soil and plant
(shoot) metal concentrations (total and bioavailable) were also determined.
No correlation was found between number of plant species present in the
plant consortia and soil properties. However, most belowground biological
parameters were correlated with plant biomass. It was found that the higher the
values of most soil microbial parameters, the lower the biomass of T. caerulescens. Anyway, soil microbial properties had a stronger effect on plant biomass rather than
the other way around (35.2% versus 14.9%). Biomass values for R. acetosa were
positively linked to enzyme activities and S and AWCD values calculated from
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Biolog EcoPlatesTM. Jasione montana biomass was positively influenced by biomass C,
while F. rubra biomass increased towards sites with higher-than average values of
acid phosphatase, arylsulphatase and dehydrogenase. On the contrary, biomass
values for T. caerulescens increased towards sites with lower-than-average values of
soil microbial properties. Likewise, soil microbial and physicochemical properties
were highly related. T. caerulescens confirmed its ability to hyperaccumulate Zn in
shoots, reaching a maximum concentration of up to 2.7% on a DW basis. J. montana
and R. acetosa also accumulated considerable amounts of Pb and Zn. Thlaspi caerulescens showed some features related to stress tolerance, such as elevated levels
of A+Z/VAZ ratio and tocopherol per chlorophyll content.
The studied metallicolous populations are tolerant to metal pollution and offer
potential for the development of phytoextraction and phytostabilization
technologies. T. caerulescens appears very tolerant to metal stress and most suitable
for metal phytoextraction; the other three species enhance soil functionality. The
rhizosphere microbial communities adapted to survive in highly polluted mine soils
are determinant for the growth of pseudometallophytes. An ecological
understanding of how contaminants, ecosystem functions and biological
communities interact in the long-term is needed for proper management of these
fragile metalliferous ecosystems.
4.2 Introduction
In mining sites, toxic heavy metals are known to adversely affect the number,
activity and diversity of soil organisms, as well as to restrict the growth of all but the
most tolerant plants (Wong, 2003). Interestingly, the endemic biodiversity present in
many metalliferous sites offers huge potential for the development of environmental
technologies such as, for instance, the phytoremediation of metal-polluted soils.
Unfortunately, sound decisions regarding the future management of fragile
metalliferous ecosystems are impeded by a lack of ecological understanding of how
contaminants, ecosystem functions and biological communities interact in the long-
term (Ramsey et al., 2005).
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Metallophytes are plant species with the capacity to grow in metalliferous soils,
as they have evolved a complex array of mechanisms to avoid the detrimental
effects of excessively high internal metal concentrations via exclusion or uptake and
detoxification (Clemens, 2001). On the other hand, most of the plant species from
metalliferous soils are pseudometallophytes (plants that colonize both metalliferous
and non-metalliferous environments). These tolerant pseudometallophyte
populations are nowadays showing high rates of population decline, making actions
towards their conservation imperative (Whiting et al., 2004). On the other hand, soil
microorganisms are also able to develop tolerance against heavy metals: the
mechanisms of resistance are generally efflux “pumping” and enzymatic
detoxification to convert toxic to less toxic or less available metal-ion species (Silver
and Phung, 1996).
Aboveground plant and belowground microbial communities of terrestrial
ecosystems are closely related. Plants provide a source of carbon (C) and other
nutrients for the soil decomposer community in the form of plant litter and root
exudates; changes in aboveground plant diversity can alter belowground soil
microbial diversity (Bartelt-Ryser, 2005; Rodríguez-Loinaz et al., 2008). In turn,
belowground microbial communities decompose soil organic matter (OM), stabilize
soil structure and, through its essential role in the cycling of elements, release
nutrients for plant growth (Porazinska et al., 2003), thus affecting vegetation
structure. Regrettably, so far, only a few studies have addressed the interactions
between aboveground and belowground communities in polluted environments
(Phillips et al., 2008; Yang et al., 2007).
The main objective of the current work was to study the relationships between
several metallicolous populations and their rhizosphere microbial communities (in
terms of activity, abundance and functional diversity) in a Zn-Pb mine soil
chronically polluted with high levels of Cd, Pb and Zn. We focused on the
rhizosphere microbial communities of a few plant consortia, naturally found in a
metal-polluted mine, consisting of 1 to 4 metallicolous pseudometallophytes with
different metal-tolerance strategies, i.e. Thlaspi caerulescens: hyperaccumulator; Jasione montana: accumulator; Rumex acetosa: indicator; and Festuca rubra: excluder. In
addition, physiological response (as reflected by the content of lipophilic
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antioxidants and photosynthetic pigments) and phytoremediation potential of these
four metallicolous pseudometallophytes were also investigated. To our knowledge,
this is the first report on the interactions between plant and rhizosphere microbial
communities in a metal-polluted mine soil under field conditions.
4.3 Materials and methods
4.3.1 Field characterization
The study was carried out in a spontaneously revegetated abandoned mine,
heavily polluted with Cd, Pb and Zn, located in Lanestosa, Biscay, northern Spain
(latitude 43°13´; longitude 3°26´). Within the mine, an experimental area of
approximately 300 m2 was chosen for this study based on the richness of plant
species observed in that area. Initially, a systematic soil sampling (upper 0-10 cm)
was carried out by means of dividing the experimental area into four quadrants and
then, within each of them, 10 soil cores (diameter: 2.5 cm) were collected at random
and mixed together to form a composite sample (i.e., 4 composite samples: one per
quadrant). Immediately after collection, soil samples were sieved to <2 mm, air-
dried at 30 ºC, and subjected to physicochemical characterization according to
standard methods (MAPA, 1994). The soil was sandy loam, with the following
physicochemical properties (mean value ± SE; n = 4): pH = 6.6 ± 0.0, OM content
= 4.77 ± 0.27%, total nitrogen (N) content = 0.19 ± 0.02%, C/N ratio = 15 ± 1,
phosphorus (P) content = 1.49 ± 0.32 mg kg-1 DW soil, and potassium (K+)
content = 28.50 ± 2.66 mg kg-1 DW soil. Total concentrations of heavy metals in
soil samples were determined using flame atomic absorption spectrometry (AAS,
Varian) following digestion with a mixture of HNO3/HClO4 (Zhao et al., 1994).
The following values (mean value ± SE; n = 4) of total metal concentration were
found (mg kg-1 DW soil): 48 ± 14, 26,328 ± 6,165, and 113,620 ± 14,514 for Cd, Pb
and Zn, respectively.
4.3.2 Plant parameters
For this study, as abovementioned, four metallicolous species with different
metal-tolerance strategies were chosen: Thlaspi caerulescens J. & C. Presl. (Brassicaceae;
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metal hyperaccumulator); Jasione montana L. (Campanulaceae; metal accumulator);
Rumex acetosa L. (Polygonaceae; metal indicator); and Festuca rubra L. (Poaceae; metal
excluder). Thirty-three (33) points were selected to study native consortia (Figure
4.1) consisting of 1-4 of these plant species, taking into account that sampling points
had to be at least 1 m apart from each other. For each of the following
combinations, 1-5 samples were taken: T, J, R, F, TR, TF, JR, RF, TJR, TJF, TRF,
JRF and TJRF (T = T. caerulescens; J = J. montana; R = R. acetosa; F = F. rubra). Blocks
containing both aboveground plant consortia and belowground rhizosphere soil
were carefully sampled and taken to the laboratory.
Figure 4.1: Examples of plant consortia present in the experimental area: (a) Rumex acetosa; (b) Thlaspi caerulescens; (c) Rumex acetosa and Festuca rubra; (d) Thlaspi caerulescens, Jasione montana and Rumex
acetosa.
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Shoots from each plant species were harvested, washed thoroughly with
deionized water and gently dried with paper towels. Fresh weights (FW) were
recorded and, subsequently, shoots were oven-dried at 70 ºC for 48 h to calculate
dry weights (DW). Subsamples (0.4 g) of dried shoot tissue were digested with a
mixture of HNO3/HClO4 (Zhao et al., 1994) and, finally, Cd, Pb and Zn were
determined using AAS. Leaf samples were collected and kept in the dark for 12 h at
room temperature (20–22ºC) to reduce the effects of diurnal variations in
antioxidants and pigments composition and to provide comparable “artificial
predawn conditions” (García-Plazaola et al., 2000; Tausz et al., 2003). Then,
approximately 0.02 g FW leaf was collected, frozen in liquid nitrogen and stored at -
80º C until analysis. Lipophilic antioxidants (carotenoids and tocopherols) and
photosynthetic pigments [a and b chlorophylls (Chl), carotenoids (Carot),
violaxanthin (V), antheraxanthin (A), zeaxanthin (Z), γ- and α-tocopherols (Toc)]
were extracted and measured by reverse-phase HPLC following the method of
García-Plazaola and Becerril (1999), with the modifications described in García-
Plazaola and Becerril (2001).
4.3.3 Soil microbial and physicochemical parameters
Rhizosphere soil was carefully sampled by collecting all the soil adhering to
roots after gentle shaking. For the analysis of microbial parameters, soils were sieved
to <2 mm and stored fresh at 4 ºC until analysis. Microbial biomass C, an indicator
of soil microbial biomass, was measured by the fumigation-extraction method
(Vance et al. 1987): a moist sample, equivalent to 5 g DW soil, was fumigated for 24
h with amylene stabilized CHCl3 and extracted with 20 ml of 0.5 M K2SO4. Then,
3.5 ml of chromium reagent [i.e., chromium (VI) oxide (0.06% w/v); sulfuric acid
(65% v/v)] were added to 2 ml of extract and incubated at 150 ºC for 60 min.
Finally, organic C concentration was determined colorimetrically at 445 nm.
Microbial biomass C was calculated as the difference between C concentration of
the fumigated and unfumigated extracts (an extractability of 0.38 was assumed) (Wu
et al. 1990).
Regarding soil enzyme activities (soil enzymes can be used as indicators of the
functional status or condition of the soil environment; see Naseby and Lynch,
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2002), dehydrogenase activity (EC 1.1) was determined according to Taylor et al.
(2002): a moist sample, corresponding to 1 g DW soil, was mixed with 0.4 ml of
buffer (100 mM THAM, pH 7) and 0.4 ml of substrate [iodonitrotetrazolium
chloride (0.5% w/v)]. The mixture was incubated at 25 ºC for 3 h and the reaction
stopped with 8 ml of methanol. After centrifugation (3500 x g, 3 min), the
absorbance value of the samples was read at 490 nm. β-glucosidase (EC 3.2.1.21),
arylsulphatase (EC 3.1.6.1) and acid phosphatase (EC 3.1.3.2) activities were
determined according to Dick et al. (1996) and Taylor et al. (2002), as described in
Epelde et al. (2008a). Urease (EC 3.5.1.5) activity was determined according to
Kandeler and Gerber (1988), as described in Rodríguez-Loinaz et al. (2008).
It has been reported that measurements of functional diversity (such as
community level physiological profiles, CLPPs) are likely to provide information
more relevant to the functioning of the soil ecosystem than species diversity (Zak et
al. 1994). In this respect, substrate utilization patterns determined with the
commercially available Biolog EcoPlatesTM look at the ability of microbial
populations to aerobically degrade a multitude of carbon sources (Dobler et al.
2001). For the analysis of CLPPs, Biolog EcoPlatesTM were used following Epelde
et al. (2008a). Average well colour development (AWCD) and species richness (S =
number of substrates with an absorbance value >0.25; this value marked the
beginning of the exponential phase in the Biolog EcoPlatesTM) were calculated at a
44 h incubation time (at approximately this incubation time, the highest rate of
microbial growth was observed in the Biolog EcoPlatesTM).
For the analysis of soil physicochemical parameters, soils were air-dried at 30
ºC for 48 h, sieved to <2 mm and stored at 4 ºC until analysis. Soil pH (1:2.5 w/v,
soil:water) was measured following standard methods (MAPA 1994). Water-soluble
organic carbon (WSOC) was extracted by shaking soil (horizontal shaker at 175
rpm) with distilled water (1:5 w/v) for 1 h and then measured as described above
for microbial biomass C. Total concentrations of heavy metals in soil were
determined as above. For the estimation of metal bioavailability, CaCl2-extractable
(0.01 M) metal fractions in soil were determined as described by Houba et al. (2000)
and then analyzed by AAS.
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4.3.4 Statistical analysis
To study the influence of soil characteristics on biomass of each plant species
(influence of belowground on aboveground), multivariate relationships between
physicochemical and microbial soil properties and plant biomass were explored. As
the beta-diversity along ordination axes was short, a redundancy analysis (RDA) was
chosen (ter Braak, 1994). The statistical significance of all canonical axes combined
by means of non-parametric Monte Carlo permutation test (Leps and Šmilauer,
2003) was also tested. To explore the individual and shared effects of soil
physicochemical and microbial properties to the revealed patterns in plant biomass
data, we employed variation partitioning procedures (Pereira et al., 2008). In the
same way, we quantified how much of the variability in the values of soil
physicochemical properties could be attributed to the individual or joint effect of
both soil microbial properties and plant biomass data (influence belowground on
belowground and influence aboveground on belowground). Finally, we measured
how much of the variation in values of soil microbial properties could be attributed
to the individual or joint effect of both soil physicochemical parameters and plant
biomass data (influence belowground on belowground and influence aboveground
on belowground). Likewise, in order to study physiological response of each
particular pseudometallophyte, we explored the relationships between the content
values of all lipophilic antioxidants and photosynthetic pigments here determined
and shoot metal concentrations for each of the 4 pseudometallophytes, considering
all 33 samples as a whole, by means of a principal component analysis (PCA)
applied on the correlation matrix of these variables. All multivariate analyses were
done by running Canoco for Windows 4.5 (ter Braak and Šmilauer, 2002).
Differences in shoot metal concentration, lipophilic antioxidants and
photosynthetic pigments among species were analyzed by one-way ANOVA using
Microsoft Stat View Software (SAS Institute). Fisher´s PLSD-test was used to
establish the significance of the differences among means. Pearson’s correlations
were calculated using SPSS Programme (Inso Corporation).
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4.4 Results
4.4.1 Soil microbial and physicochemical properties
Regarding total metal concentrations in the rhizosphere soil of the 33 studied
sampling points, the observed values varied considerably, i.e. from 13.4 to 57.0 mg
Cd kg-1 DW; from 5,959 to 58,928 mg Pb kg-1 DW; and from 27,150 to 203,110 mg
Zn kg-1 DW. Similarly, regarding metal bioavailability, CaCl2-extractable metal
concentrations in rhizosphere soil were also highly variable among the 33 sampling
points: from 1.33 to 6.94 mg Cd kg-1 DW; from 9.8 to 33.5 mg Pb kg-1 DW; from
412 to 1,102 mg Zn kg-1 DW. On average, 20.7, 0.3 and 2.9% of total Cd, Pb and
Zn, respectively, appeared in a bioavailable (CaCl2-extractable) form (Table 4.1).
Values of soil pH ranged between 6.04 and 6.99, while WSOC values ranged from
33 to 285 mg C kg-1 DW soil. Likewise, values of microbial biomass C, enzyme
activities, and CLPPs showed great variability among the 33 rhizosphere soils (Table
4.1). Table 4.1: Physicochemical and microbial properties of the 33 studied rhizosphere soils.
Mean ± SE Interval
Total Cd (mg kg-1 DW soil) 33.0 ± 2.0 13.4 - 57.0
CaCl2 extractable Cd (mg kg-1 DW soil) 3.04 ± 0.23 1.33 - 6.94
Total Pb (mg kg-1 DW soil) 24,175 ± 2,241 5,959 - 58,928
CaCl2 extractable Pb (mg kg-1 DW soil) 21.4 ± 1.0 9.8 - 33.5
Total Zn (mg kg-1 DW soil) 97,735 ± 6,594 27,150 - 203,110
CaCl2 extractable Zn (mg kg-1 DW soil) 761 ± 25 412 - 1,102
pH 6.47 ± 0.04 6.04 – 6.99
WSOC (mg C kg-1 DW soil) 101 ± 10 33 - 285
Microbial biomass C (mg C kg-1 DW soil) 312 ± 24 87 - 590
Dehydrogenase (mg INTF kg-1 20 h-1) 436 ± 40 65 - 916
β-glucosidase (mg ρ-nitrophenol kg-1 h-1) 169 ± 21 29 - 569
Arylsulphatase (mg ρ-nitrophenol kg-1 h-1) 146 ± 17 57 - 448
Acid phosphatase (mg ρ-nitrophenol kg-1 h-1) 274 ± 26 76 - 726
Urease (mg N-NH4+ kg-1 h-1) 14.7 ± 1.7 2.7 - 42.5
AWCD (Biolog EcoPlatesTM) 0.26 ± 0.03 0.04 - 0.59
S (Biolog EcoPlatesTM) 11 ± 1 1 - 21
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4.4.2 Interactions between plants and soil microbial and physicochemical properties
No correlation was found between number of plant species present in the
different plant consortia (richness) and soil properties (neither physicochemical nor
microbial). However, total plant biomass was positively correlated with microbial
biomass C (R = 0.575, P < 0.001), dehydrogenase activity (R = 0.605, P < 0.001),
acid phosphatase activity (R = 0.553, P < 0.001), urease activity (R = 0.362, P <
0.038), AWCD (R = 0.447, P < 0.009), S-BiologTM (R = 0.390, P < 0.025), CaCl2
extractable Zn (R = 0.355, P < 0.042) and WSOC (R = 0.441, P < 0.010). The
correlation was negative for soil pH (R = -0.596, P < 0.001).
After partialling out the influence of selected sets of co-variables, most of the
explained variation in plant biomass data was attributable to changes in soil
microbial properties (which, per se, explained 35.2% of the total inertia) (Figure 4.2).
However, most of the explained variation in soil microbial properties was due to
changes in soil physicochemical variables (49.0%), with values of plant biomass
exerting only a minor influence (14.9%). In turn, physicochemical properties were
also influenced by microbial properties (38.5%; Figure 4.2).
Figure 4.2: Results of the variation partitioning, RDA analyses. Explained (Exp) percentages indicate the explained variation of the response variable by the RDA. For each set of response
variables (plant biomass; soil microbial properties; soil physicochemical properties), the remaining sets were considered as co-variables in successive RDAs. When P < 0.05, numbers shown in arrows
quantify the effects of each set of explaining factors, after partialling out the effect of the other variables, expressed as percent contribution to the total inertia in the response variable.
Physico-chemical propertie
s
Microbial propertie
s
Plant biomass
49.0% (P = 0.002) 35.2% (P = 0.032)
14.9% (P = 0.010)
Exp. = 67.7% P = 0.002
Exp. = 62.1% P = 0.046
P = 0.266 P = 0.626
Non-significant effects
Exp. = 48.2% P = 0.024
38.5% (P = 0.008)
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Figure 4.3 shows the influence of soil microbial properties on the biomass of
the different pseudometallophytes (influence of belowground on aboveground).
Biomass values for R. acetosa increased towards the positive region of RDA-1 axis,
being positively linked to enzyme activities and S and AWCD values calculated from
Biolog EcoPlatesTM. On the contrary, biomass values for T. caerulescens increased
towards sites with lower-than-average values of soil microbial properties. Along
RDA-2, J. montana biomass was positively influenced by microbial biomass C.
Finally, F. rubra biomass increased towards sites with higher-than average values of
acid phosphatase, arylsulphatase and dehydrogenase.
Figure 4.3: Triplot of the redundancy analysis performed on plant biomass data as response variable, soil microbial properties as explanatory variables, and soil physicochemical properties as
covariables. Closed symbols represent the 33 samples, whereas thick vectors represent plant biomass and thin arrows represent soil microbial properties. AWCD: average well colour development; S: richness from Biolog EcoPlatesTM; Glu: β-glucosidase; Ure: urease; Sul:
arylsulphatase; Pho: phosphatase; DH: dehydrogenase; MBC: microbial biomass C.
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Although the percentage of explained variability is considerably lower, the
influence of plant biomass on soil microbial properties is shown in Figure 4.4
(influence of aboveground on belowground). R. acetosa biomass positively influenced
most enzyme activities (except for β-glucosidase) and S and AWCD values
calculated from Biolog EcoPlatesTM. Meanwhile, microbial biomass C and β-
glucosidase activity increased towards sites with higher values of F. rubra and J. montana biomass. Lastly, T. caerulescens biomass negatively influenced most of the
microbial parameters here measured.
Figure 4.4: Triplot of the redundancy analysis performed on soil microbial properties as response variable, plant biomass data as explanatory variables, and soil physicochemical properties as covariables. Closed symbols represent the 33 samples, whereas thick vectors represent soil microbial properties and thin arrows represent plant biomass. AWCD: average well colour development; S: richness from Biolog EcoPlatesTM; Glu: β-glucosidase; Ure: urease; Sul:
arylsulphatase; Pho: phosphatase; DH: dehydrogenase; MBC: microbial biomass C.
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Soil microbial and physicochemical properties were interrelated. When
performing RDAs (data not shown), soil microbial parameters were negatively
influenced by most of the soil metal contents (except for CaCl2-extractable Zn
concentration) and soil pH, and positively by WSOC. Soil physicochemical
parameters (apart from CaCl2-extractable Zn and WSOC) were negatively
influenced by soil microbial parameters.
4.4.3 Plant parameters
Shoot metal concentrations for the four pseudometallophytes are shown in
Figure 4.5. Highest Cd shoot concentrations were found in T. caerulescens with a
mean value of 30 ± 4 mg kg-1 DW. The other three species had Cd concentrations
below 5 mg kg-1 DW shoot. T. caerulescens also showed the highest shoot Zn
concentrations with a mean value of 19,339 ± 756 mg kg-1 DW. On the contrary,
lowest values of Zn shoot concentrations were found in F. rubra (1,021 ± 116 mg
kg-1 DW). Regarding shoot Pb concentrations, highest values were found in T. caerulescens and J. montana (lowest values again corresponded to F. rubra).
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Figure 4.5: Shoot metal concentrations [mean values ± SE; T. caerulescens (n=18), J. montana (n=16), R. acetosa (n=21), F. rubra (n=20)]. Bars followed with different letters are significantly different
according to Fisher´s PLSD-test.
Figure 4.6 shows multivariate relationships between shoot metal
concentration, photosynthetic pigments and lipophilic antioxidant indexes. Many of
these indexes [i.e., Zea/Chl (a+b), A+Z/VAZ, and both γ- and α-Toc/Chl (a+b)] increased towards the positive region of PCA-1, which accounted for 41% of the
variance, and were positively correlated with shoot metal concentrations (by
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contrast, shoot chlorophyll contents were negatively correlated). At the same time,
the indexes V/Chl (a+b), VAZ/Chl (a+b), A/Chl (a+b) and Carot tot/Chl (a+b) extended along the positive region of PCA-2, which accounted for 30% of the
variance. The different plant species separated from each other along PCA-1, which
could simply be due to differences in shoot metal concentration. However, this
separation among species was still observed when removing data of shoot metal
concentration from the PCA (data not shown), implying that differences among
species regarding contents of photosynthetic pigments and antioxidant metabolites
did occur.
Figure 4.6: Biplot of PCA performed on shoot metal concentrations (thick vectors) and content of lipophilic antioxidants and photosynthetic pigments indexes (thin vectors). Chl: chlorophyll a+b;
Carot: carotenoids; V: violaxanthin; A: antheraxanthin; Z: zeaxanthin; A-Toc: α-tocopherol; G-Toc: γ -tocopherol.
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In fact, it can be seen in Table 4.2 that T. caerulescens showed significantly lower
values of VAZ/Chl and V/Chl and higher values of Z/Chl, A+Z/VAZ, γ-Toc/Chl
and α-Toc/Chl than the rest of the species (in the case of Zea/Chl, the difference
with J. montana was not statistically significant). Remarkably, total tocopherol values
in T. caerulescens were 118, 57 and 79% higher than in J. montana, R. acetosa and F. rubra, respectively. T. caerulescens and J. montana showed significantly lower values of
chlorophylls than R. acetosa and F. rubra (Table 4.2). Also, R. acetosa showed the
highest and lowest values of Ant/Chl and Carot tot/Chl, respectively (Table 4.2).
Table 4.2: Content of lipophilic antioxidants and photosynthetic pigments in the four
pseudometallophytes [mean values ± SE; T. caerulescens (n=18), J. montana (n=16), R. acetosa (n=21), F. rubra (n=20)]. Values followed with different letters are significantly different according to
Fisher´s PLSD-test. Chl (a+b): chlorophyll a+b; Carot: carotenoids; V: violaxanthin; A: antheraxanthin; Z: zeaxanthin; VAZ: violaxanthin + antheraxanthin + zeaxanthin; Toc: tocopherol.
T. caerulescens R. acetosa J. montana F. rubra
Chl (a+b)a 1165 ± 66a 2132 ± 54b 1363 ± 85a 1913 ± 122b
Carot/Chl (a+b)b 381 ± 9a 360 ± 4b 362 ± 6ab 378 ± 5a
V/Chl (a+b)b 66.5 ± 3.2a 81.3 ± 2.5b 79.5 ± 3.3b 83.3 ± 2.5b
A/Chl (a+b)b 2.57 ± 0.28a 3.44 ± 0.29b 2.42 ± 0.20a 2.55 ± 0.15a
Z/Chl (a+b)b 4.11 ± 0.77a 2.20 ± 0.22b 2.94 ± 0.30ab 2.14 ± 0.15b
VAZ/Chl (a+b)b 73.2 ± 3.8a 86.9 ± 2.7b 84.9 ± 3.6b 87.9 ± 2.6b
A+Z/VAZ (a+b)b 87.4 ± 11.2a 64.4 ± 4.8b 62.0 ± 4.5b 53.0 ± 2.4b
γ-Toc/Chl (a+b)b 15.61 ± 1.97a 3.11 ± 0.38b 4.77 ± 0.86b 3.46 ± 0.51b
α-Toc/Chl (a+b)b 382 ± 45a 128 ± 8b 162 ± 25b 126 ± 9b apmol mg-1 FW leaf bmmol mol-1
4.5 Discussion
The studied mine field was severely polluted with Cd, Pb and Zn, surpassing
by far, as expected, the maximum Cd, Pb and Zn concentrations usually found in
non-polluted soils of the Basque Country (0.8 mg Cd kg-1 soil, 16+0.7L+2.1H mg
Pb kg-1 soil, 50+2L mg Zn kg-1 soil; L and H refer to clay and OM content,
respectively) (IHOBE, 1998). A considerable portion of the metals was found in the
non CaCl2-extractable fraction, an unavailable form for plants. It is well-known that
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Pb usually appears in soil non-bioavailable fractions, but Cd and Zn frequently
appear in more bioavailable fractions (Sun et al., 2001). In the studied soil a
considerable amount of Zn seems to be present in a hypogene assemblage
consisting of sphalerite, galena, pyrite, dolomite, calcite, and quartz (Grandia et al.,
2003).
On the other hand, the high metal concentrations found in the mine soil could
well be responsible for its relatively high values of OM content (4.77 ± 0.27%) and
very low values of N, P and K+ content, as heavy metals might affect biological
mineralization cycles (Chander and Brookes, 1991).
Previous studies (Bardgett et al., 1998; Kowalchuk et al., 2002; Wardle et al.,
1999) have shown that the composition of belowground soil microbial communities
may depend on aboveground plant species composition, mainly through the
development of rhizobacteria induced by the release of specific sugars and amino
acids into the rhizosphere. Besides, plant composition, plant richness and
abundance may also affect soil microbial communities. In our study, plant richness
did not have any effect on soil microbial properties (or physicochemical properties),
probably due to the low number of species present in the plant consortia (1-4) as
well as the limited number of replicates per plant consortia found in the
experimental area. However, plant biomass was positively correlated with most
microbial parameters measured (also with WSOC and negatively with soil pH). The
redundancy analysis suggested that the biomass of each plant species influenced in a
different way soil microbial parameters. Particularly, the higher the biomass of T. caerulescens the lower the values of microbial biomass C, β-glucosidase, urease and
microbial functional diversity (AWCD and S-BiologTM). Being an endemic ecotype
of T. caerulescens, it might well be that microbial communities associated with its
rhizosphere are very specific and low in functional diversity. These results are of use
for the selection of phytoremediation strategies. For instance, T. caerulescens appears
as a metal hyperacumulator most suitable for phytoextraction (see below). Instead,
from the point of view of a biologically active and healthy soil, revegetation with R. acetosa would be the best choice. It must always be remembered that the objective of
any soil remediation process must be not only to remove the contaminant(s) from
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the soil but, most importantly, to restore the continued capacity of the soil to
perform or function according to its potential (Epelde et al. 2009a).
Most importantly, soil microbial parameters had a stronger effect on plant
biomass rather than the other way round (35.2% versus 14.9%). This could be due
to the extremely harsh conditions present in the mine soil, making microbial activity
of vital importance for plant development. Indeed, positive effects of microbes on
plant productivity are most common in nutrient poor ecosystems where they
enhance the supply of growth limiting nutrients such as N and P to plants (van der
Heijden et al. 2008). Under such limiting conditions, up to 90% of the P and N for
plant growth might be provided by soil microbes, emphasizing their importance for
plant productivity in those areas (van der Heijden et al. 2008). In our case, this
appears to be the case except for T. caerulescens, as higher biomass values of this
species were found with lower values of soil microbial properties. This might
indicate that T. caerulescens is more adapted to survive in these metal polluted
environments, without the need of much support from soil microbes. In any case,
links among plant communities, microbial communities, nutrient availability and
ecosystem processes are never unidirectional and rarely simple (Hooper et al. 2000,
Naeem et al. 2000).
The influence of soil physicochemical properties (including metal
concentrations) on soil microbial properties and viceversa is worth-mentioning. An
increasing body of evidence suggests that heavy metals have a strong impact on
both bacterial and fungal communities (Kozdroj and van Elsas 2001). Nonetheless,
soil microorganisms have developed highly efficient systems for metal detoxification
which, in bacteria, can be grouped into five categories: intracellular sequestration,
export, reduced permeability, extracellular sequestration, and extracellular
detoxification (Rough et al. 1995). Heavy metal contamination provides a strong
pressure that selects for the recruitment of multiple resistance phenotypes that
encode resistance to the predominant metals in the site (Ryan et al. 2005). In our
study, CaCl2-extractable Zn positively influenced soil microbial parameters. Unlike
Cd and Pb, Zn is an essential trace element; however, it has been reported to be
highly toxic at elevated concentrations (Tang et al., 2009). Microorganisms are
intimately involved in metal biogeochemistry with a variety of processes determining
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mobility and bioavailability (Gadd 2004). Microorganisms can affect metal
speciation thanks to their ability to effect and/or mediate mobilization or
immobilization processes (the balance between mobilization and immobilization
varies depending on the organisms involved, their environment and
physicochemical conditions) that influence the balance of metal species between
soluble and insoluble phases (Gadd 2004).
Also, except for metal concentrations themselves, both soil pH and WSOC
had a negative and positive influence on soil microbial properties, respectively. In a
study by Wang et al. (2006), a relationship between soil biological activities (alkaline
phosphatase activity, arylsulphatase activity, nitrification potential, respiration) and
soil pH was well characterized by linear or quadratic regression models with R
values ranging from 0.57 to 0.99. Certainly, the labile fraction of soil OM included
in WSOC provides nutrients for the soil microbial community (Bol et al., 2003).
Apart from that, despite the elevated levels of soil metal pollution present in
the mine soil, the four pseudometallophytes were able to spontaneously grow under
such metalliferous conditions. T. caerulescens confirmed its ability to hyperaccumulate
Zn in shoots, reaching a maximum concentration of up to 2.7% on a DW basis.
Indeed, T. caerulescens exceeded the threshold value for hyperaccumulation indicated
by Baker et al. (2000) for Zn (10,000 mg Zn kg-1 DW shoot) in all cases, and for Pb
(1,000 mg Pb kg-1 DW shoot) when present alone (in the absence of the other three
species). Regrettably, hyperaccumulating plants such as T. caerulescens are, in general,
relatively small, have slow rates of biomass production, and lack any established
cultivation, pest management or harvesting practices (Wenzel et al., 1999), making
their application for metal phytoextraction complicated.
Both J. montana and R. acetosa accumulated considerable amounts of Pb and
Zn. R. acetosa is an species that usually behaves as a Zn indicator, but in the current
study, due to the extremely high levels of metals present in the experimental area, no
correlation between soil Zn concentration and shoot Zn concentration was
observed. This population of R. acetosa has previously been reported to have great
potential for Zn phytoextraction (Barrutia et al., 2009).
The grass F. rubra, a metal excluder, was able to tolerate the high levels of
metal pollution by physiologically restricting the entry of heavy metals, thus making
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it a good candidate for phytostabilization of soils heavily polluted with metals such
as those from mining areas (phytostabilization is a phytoremediation method that
converts soil metal pollutants into inert, immobile forms using metal excluder
plants) (Salt et al., 1995).
None of the studied plants showed severe phytotoxic symptoms according to
the values of photosynthetic pigments and antioxidant metabolites, confirming their
adaptation to the harsh environmental conditions present in the mine. However, as
reflected by the values of photosynthetic pigments and antioxidant metabolites,
some differences were observed: sorrel, R. acetosa, stood out among the other
species because of its elevated content of antheraxanthin per chlorophyll (A/Chl).
Anteraxanthin, together with zeaxanthin, is related to membrane stabilization
(Havaux, 1998) and antioxidant activity (Havaux and Niyougi, 1999) as well as to
chlorophyll quenching (Yamamoto and Bassi, 1996; Goss et al., 2006). Zeaxanthin
per chlorophyll ratio (Z/Chl) was high in T. caerulescens. Moreover, this species
showed some other noteworthy features such as elevated levels of A+Z/VAZ ratio
and tocopherol per chlorophyll content. Interestingly, these two parameters have
been related to stress tolerance. The deepoxidation index (A+Z/VAZ ratio) is
frequently used as an estimation of excess energy dissipation (García-Plazaola et al.,
2007) and was higher in T. caerulescens mainly due to the low V/Chl and high Z/Chl
ratios found in its leaves. Energy dissipation in the antenna mediated by the
xanthophyll cycle is one of the main mechanisms to prevent photooxidative damage
in plants; the other main mechanism is the induction of antioxidant response
(several enzymes and low molecular weight scavengers such as tocopherol). The
elevated total Toc/Chl ratio observed in T. caerulescens was the result of high values
of both γ-tocopherol and α-tocopherol. Tocopherol, vitamin E, might play a
protective role to membrane systems in plant cells (Collin et al., 2008; Havaux et al.,
2005) and also to PSII reaction centre against photoinhibition (Krieger-Liszkay and
Trebst; 2006). Indeed, tocopherol is an important part of the plants machinery to
maintain integrity and normal function of photosynthetic apparatus (Liu et al.;
2008). Then, high levels of tocopherol might provide protection against
environmental stresses, e.g. metal pollution. In fact, tocopherol content has been
positively correlated with tolerance to low temperature, water deficit or salt stress in
different plant species (Guo et al., 2006; Munné-Bosch et al., 1999; Yamaguchi-
4. interactions between plant and rhizosphere microbial communities in a metalliferous soil
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Shinozaki and Shinozaki, 1994) and recently suggested to be involved in Cd
tolerance of Arabidopsis thaliana (Collin et al., 2008). These particular features
observed in T. caerulescens suggest that this species is probably better protected
against environmental stress than the others. This is the first time that antioxidant
metabolites are studied in T. caerulescens under field conditions and the interesting
results obtained should encourage the scientific community to further study the
physiology of this plant in order to better understand its peculiar behaviour.
4.6 Conclusions
The study of metalliferous environments is of great relevance since it can
provide invaluable information on ecological impact of heavy metals on ecosystem
function, physiological strategies used by metal-tolerant organisms, and novel tools
for remediation of metal polluted sites. The studied pseudometallophytes are
tolerant to metal pollution and offer potential for the development of
phytoextraction and phytostabilization technologies. The suitability of each species
for phytoremediation is also different regarding the recovery of soil health. Soil
microbial parameters are related to plant biomass, but not to plant richness.
Rhizosphere microbial communities influence more the growth of plants, instead
of the other way round. Soil microbial and physicochemical properties are
interrelated. An ecological understanding of how contaminants, ecosystem
functions and biological communities interact in the long-term is needed for
proper management of these fragile metalliferous ecosystems.
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5. FUNCTIONAL DIVERSITY AS INDICATOR OF THE RECOVERY OF SOIL HEALTH DERIVED FROM Thlaspi
caerulescens GROWTH AND METAL PHYTOEXTRACTION
Epelde et al. (2008), published in Applied Soil Ecology 39, 299-310
5.1 Abstract
Continuous phytoextraction has lately drawn a lot of attention due to its
potential for the remediation of metal polluted soils. Although when assessing the
success of a phytoextraction process, up till now, emphasis has mostly been placed
on metal removal, it is important to highlight that the ultimate objective of a
phytoextraction process must be to restore soil health. Consequently, a short-term
microcosm study was carried out to evaluate the capacity of an actively growing
ecotype of the Zn and Cd hyperaccumulator Thlaspi caerulescens (Lanestosa ecotype)
to phytoextract metals from soil and, above all, to assess the potential of soil
functional diversity (through the determination of soil enzyme activities and
community level physiological profiles) to both determine the toxic effect of metals
on soil condition and to monitor the efficiency of a metal phytoextraction process.
T. caerulescens plants grown in metal polluted soils showed a shoot metal
concentration of 337 mg of Cd, 5670 mg of Zn and 76.6 mg of Pb per kg of dry
weight tissue. Apart from confirming its great potential for Zn and Cd
phytoextraction, the presence of T. caerulescens, as compared to the metal
phytoextraction itself, had the major effect on soil biological parameters. Actually, in
metal polluted soils, the presence of T. caerulescens led to a 154, 115, 140, 37 and
164% increase in the activity of β-glucosidase, arylsulphatase, acid phosphatase,
alkaline phosphatase and urease, respectively. Metal pollution did not cause a clear
inhibition of soil enzyme activities. Contrasting results were obtained with
EcoPlatesTM versus soil enzyme activities. Actually, the presence of metals led to
significantly lower values of Shannon´s index calculated from enzyme activities and
non-significant higher values of this same index when calculated from EcoPlatesTM
evaluation of the efficiency of metal phytoremediation processes with microbioloGical indicators of soil health
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data. It was concluded that biological indicators of soil health are valid tools to
evaluate the success of a metal phytoextraction process.
5.2 Introduction
Continuous phytoextraction (a technology based on the utilization of metal
hyperaccumulating plants that have the capacity to accumulate, translocate and
tolerate high amounts of metals over the complete growth cycle) appears a cost-
effective, non-intrusive, socially accepted, aesthetically pleasing phytotechnology
with great potential for the remediation of metal polluted soils. Thlaspi caerulescens, a
hyperaccumulating plant extensively studied due to its remarkable capacity to
phytoextract zinc and cadmium from polluted soils, has been suggested as a model
species for research on metal phytoextraction (Assunção et al., 2003) and much
screened in the search for new ecotypes with greater capacities to phytoextract
metals (McGrath et al., 2001b; Lombi et al., 2002).
Up to now, when assessing the success of a phytoextraction process,
emphasis has mostly been placed on metal removal. However, the ultimate objective
of a phytoextraction process must be not only to remove the metal from the soil
but, most importantly, to restore soil health, i.e. the continued capacity of soil to
function as a vital living system, within ecosystem and land-use boundaries, to
sustain biological productivity, promote the quality of air and water environments,
and maintain plant, animal, and human health (Doran and Safley, 1997). Hence,
indicators of soil health are needed to properly assess the efficiency of a
phytoextraction process. Biological indicators of soil health, especially those related
to the activity, size and diversity of soil microbial communities, are becoming
increasingly used due to their sensitivity and capacity to provide information that
integrates many environmental factors (Alkorta et al., 2003b).
In this respect, soil enzyme activities have been reported to provide a unique
integrative biochemical assessment of soil function and condition (Dick et al., 1997;
Naseby and Lynch, 2002) and to be useful as indicators of soil functional diversity
(Bending et al., 2002, 2004; Sowerby et al., 2005). In addition, soil microbial
functional diversity can be determined through the utilization of community level
5. functional diversity as indicator of the recovery of soil health derived from Thlaspi caerulescens Growth and metal phytoextraction
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physiological profiles (CLPPs) which reflect the potential of the culturable portion
of the microbial community to respond to carbon substrates (Bending et al., 2004).
The so-called Biolog EcoPlatesTM were developed for CLPP of terrestrial
communities (Insam, 1997) and contain 31 useful carbon sources for soil
community analysis. Regarding the degradative capabilities of soil bacterial
communities, it has been reported that, in heavy-metal-affected bacterial
communities, relatively rare degradative capabilities are even rarer than in unaffected
communities, while the reverse is true for more common capabilities (Burkhardt et
al., 1993).
The main objective of the current work was to evaluate the potential of soil
functional diversity (through the determination of soil enzyme activities and CLPPs)
in order to determine the toxic effect of metals on soil condition and, above all, to
monitor the efficiency of a metal phytoextraction process, i.e. its capacity to restore
soil health.
5.3 Materials and methods
5.3.1 Soil characterization and contamination
A short-term (5 months) microcosm phytoextraction study was carried out
with soil collected from the top layer (0-30 cm) of a natural polyphita grassland
located in Derio (Basque Country, northern Spain). Immediately after collection, the
soil was sieved to <4 mm, air-dried at 30 ºC for 48 h, and subjected to
physicochemical characterization according to standard methods (MAPA, 1994).
The soil was a clay loam, with a pH of 5.2, an organic matter (OM) content of
4.12%, a total nitrogen (N) content of 0.23%, a C/N ratio of 10.4, a phosphorus (P)
content of 26.4 mg kg-1 and an electrical conductivity of 0.08 dS m-1.
Subsequently, the soil was artificially contaminated with a mixture of zinc
(Zn), lead (Pb) and cadmium (Cd) as follows: 1,000 mg Zn kg-1 dry weight (DW)
soil as Zn(NO3)2 + 500 mg Pb kg-1 DW soil as Pb(NO3)2 + 100 mg Cd kg-1 DW
soil as Cd(NO3)2. Control non-polluted (both planted and unplanted) soil was
amended with 100 mg Zn kg-1 DW soil as Zn(NO3)2 (to support the growth of T. caerulescens) and 3.45 g KNO3 kg-1 DW soil (to compensate for the amount of nitrate
evaluation of the efficiency of metal phytoremediation processes with microbioloGical indicators of soil health
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added to the artificially polluted soil). Metal polluted and control (non-polluted)
soils were then stored at room temperature for 1 week.
5.3.2 Experimental design and plant growth
T. caerulescens J. & C. Presl. seeds of a local ecotype, named Lanestosa, collected
from an area formerly occupied by a nowadays abandoned Zn/Pb smelter in the
province of Biscay, Basque Country, northern Spain, were germinated for two
weeks (on a mixture of perlite and vermiculite, 2:3 v/v, moistened with deionized
water) in a greenhouse under the following controlled conditions: temperature
25/18 ºC day/night, relative humidity 60/80% day/night, and a photosynthetic
photon flux density of 400 µmol photon m-2 s-1 by supplementing natural
illumination with white cold lamps (Philips SON-T AGRO 400, Belgium). Then,
seedlings were transplanted to John Innes No. 2 compost and allowed to grow for 1
month. Finally, three T. caerulescens plants were transferred to study pots containing
1.5 kg (DW) of metal polluted or control (non-polluted) soil and allowed to grow
for five months. Unplanted pots were also included in the experiment as additional
controls. Four different treatments (i.e., NM-UP: no metal, unplanted; NM-P: no
metal, planted; M-UP: metal, unplanted; M-P: metal, planted) were conducted in
triplicate. The experiment was carried out for five months under the
abovementioned greenhouse controlled conditions. Throughout the experimental
period, plants were bottom watered periodically as needed.
5.3.3 Soil physicochemical parameters and metal determination
Soil was sampled at the end of the phytoextraction experiment, i.e. 5 months
after transplanting. Immediately after sampling, soils were air-dried at 30 ºC for 48
h, sieved to <2 mm and stored at 4 ºC until analysis.
Soil pH, OM content, total N, cation exchange capacity (CEC), electrical
conductivity (EC), Olsen P, and extractable potassium (K+), calcium (Ca2+) and
magnesium (Mg2+) were measured following standard methods (Watanabe and
Olsen, 1965; MAPA, 1994).
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Total concentrations of heavy metals in soil were determined using inductively
coupled plasma atomic emission spectrometry (ICP-AES, Varian) following aqua
regia digestion (McGrath and Cunliffe, 1985). For the determination of the
phytoavailable fraction of metals, pore water metal content was extracted using 0.01
M CaCl2 as described by Houba et al. (2000) and analyzed by ICP-AES.
5.3.4 Soil biological parameters
Regarding soil enzyme activities, β-glucosidase (EC 3.2.1.21), arylsulphatase
(EC 3.1.6.1) and alkaline and acid phosphatase (EC 3.1.3.1 and EC 3.1.3.2) were
determined according to Dick et al. (1996) and Taylor et al. (2002). Urease (EC
3.2.1.21) activity was determined according to Kandeler and Gerber (1988). All
enzyme activities were determined at optimum conditions of pH, temperature and
substrate concentration in order to get an assessment of their maximum potential
activity in the soil.
For β-glucosidase, arylsulphatase and acid and alkaline phosphatase, 1 g DW
soil was mixed with 1.6 ml of buffer (i.e., 20 mM modified universal buffer-MUB,
pH 6.0, for β-glucosidase; 500 mM acetate buffer, pH 5.8, for arylsulphatase; 20
mM MUB, pH 6.5, for acid phosphatase; 20 mM MUB, pH 11, for alkaline
phosphatase) and 0.4 ml of substrate [i.e., 4-nitrophenyl-β-D-glucopyranoside (1.5%
w/v) for β-glucosidase; potassium 4-nitrophenyl sulphate (1.3% w/v) for
arylsulphatase; 4-nitrophenyl phosphate disodium salt (1.85% w/v) for acid and
alkaline phosphatase]. The mixture was incubated at 37 °C for 45 min and the
reaction stopped with 0.4 ml of 500 mM CaCl2 and 1.6 ml of 500 mM NaOH. After
centrifugation (3500 x g, 3 min), the absorbance value of the samples was read at
410 nm.
For urease activity, 1 g DW soil was mixed with 1.75 ml of 100 mM borate
buffer (pH 10.0) and 0.25 ml of 820 mM urea. The mixture was then incubated at
37 °C for 1 h and the reaction stopped with 6 ml of acidified 2 M KCl. After
centrifugation (3500 x g, 3 min), 0.25 ml of the supernatant fraction was mixed with
3.75 ml of distilled water and 2 ml of a reagent composed of a sodium
salicylate/sodium nitroprusiate mixture (17% w/v and 0.12% w/v, respectively), 0.3
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M NaOH and distilled water (1:1:1 v/v/v). Finally, 0.8 ml of sodium
dichloroisocyanurate was added to the reaction mixture. After 30 min, the
absorbance value of the samples was read at 670 nm.
From the values of these five enzyme activities, soil functional diversity was
determined using the Shannon´s diversity index (H’=-∑pilog2pi) (Magurran, 2004) as
indicated by Bending et al. (2004), where pi = the ratio of the activity of a particular
enzyme to the sum of activities of all enzymes. Since the five enzymes here tested
did show activity in all the analyzed samples, then, in this work, Shannon´s diversity
index reflects the “evenness” or distribution of the enzyme activities (Bending et al.,
2004). The order of magnitude of the values obtained for the different enzyme
activities varies considerably depending on the specific activity being determined,
thus leading to some enzyme activities having more weight than others. To resolve
this problem, the percentage of the mean value found for that specific enzyme
activity in the NM-P soil was used for the calculation of the Shannon´s diversity
index. This NM-P soil was taken as the 100% reference since it can be considered a
suitable target where the polluted soils should return after the phytoextraction
procedure (i.e., a vegetated, unpolluted soil of similar physicochemical properties
and subjected to the same edaphoclimatic conditions). Consequently, in this study,
H’ values for enzyme activities indicate how far the remaining soils are from the
target NM-P soil regarding soil enzymes distribution.
For the analysis of CLPPs, Biolog EcoPlatesTM were used. Soil samples were
extracted by agitating in an orbital shaker (125 rev min-1) 1 g DW soil with 10 ml of
autoclaved Mili-Q ultra pure water for 1 h. After shaking, samples were left to settle
down and then a 1:100 dilution (1 ml soil suspension:100 ml autoclaved Mili-Q ultra
pure water) was inoculated onto the Biolog EcoPlatesTM. The plates were incubated
at 30 ºC and colour development was read at 595 nm using a micro plate reader
(Anthos Zenyth 3100). For each reading time, raw absorbance data were corrected
by subtracting the zero hour reading point and the absorbance value given by the
control well. Average well colour development (AWCD) was determined by
calculating the mean of every well’s absorbance value at each reading time. The
plates corresponding to an incubation time of 48 h were chosen for further
calculations (at approximately this incubation time, the highest rate of microbial
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growth was observed in the Biolog EcoPlatesTM). The number of utilized substrates
(i.e., the number of substrates with an absorbance value > 0.1; this value marked the
beginning of the exponential phase in the Biolog EcoPlatesTM), equivalent to species
richness, S, was calculated at this 48 h incubation time. Similarly, Shannon´s
diversity (H’) and evenness (J’=H’/Hmax=H’/log2S) indexes were calculated,
considering absorbance values at each well as equivalent to species abundance.
Additionally, kinetic parameters were estimated by fitting the curve of
“corrected absorbance versus time” at 48 h incubation time to a density-dependent
logistic growth equation (Lindstrom et al., 1998):
where K = asymptote that the “corrected absorbance versus time” curve
approaches, r = exponential rate of absorbance changes (slope), t = time following
inoculation of the microplates, and s = time to reach the midpoint of the
exponential portion of the curve (i.e., when y = K/2). Substrates with a corrected
absorbance < 0.1 at 48 h incubation time were omitted from the data set.
Parameters were estimated using the data analysis Origin Program (Microcal
Software, Inc., Northampton, MA). Curve parameters with standard errors greater
than the parameter values or χ2 (goodness of fit) values > 0.01 were omitted from
further analysis. These kinetic parameters were calculated for both the AWCD curve
and for the absorbance curves of each individual substrate present in the Biolog-
EcoPlatesTM.
5.3.5 Plant physiological parameters and metal accumulation
Plants were harvested at the end of the experiment, i.e. 5 months after
transplanting. Shoots and roots were harvested separately and their fresh weights
(FW) recorded. Leaf samples were collected and kept in the dark for 12 h at room
temperature (20-22 ºC) to reduce the effects of diurnal variations in pigments and
provide comparable conditions, “artificial predawn conditions”, as described in
García-Plazaola et al. (2000) and Tausz et al. (2003). Then, leaf discs (diameter: 3
mm) were collected, frozen in liquid N, and stored at -80 ºC until pigment analysis.
⎟⎠⎞⎜
⎝⎛ −−+
==)(1
595 stre
K nmODy
evaluation of the efficiency of metal phytoremediation processes with microbioloGical indicators of soil health
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Fluorescence measurements were done in dark-adapted leaves after 12 h at room
temperature. Maximal photochemical efficiency of PSII (Fv/Fm) was determined
using a portable modulated fluorimeter (OS 5-FL, Optisciences, Tyngsboro, USA).
Initial (F0) and maximal (Fm) fluorescence were measured with a saturating pulse of
0.8 s. This measurement represents the maximal photochemical efficiency of PSII
after a period of dark recovery and thus it can be considered as proportional to the
degree of “chronic photoinhibition” (Werner et al., 2002). Pigments (chlorophylls
a+b) were extracted in acetone and analysed by reverse phase HPLC following the
method of García-Plazaola and Becerril (1999), with the modifications of García-
Plazaola and Becerril (2001).
For plant metal analysis, shoots and roots were washed thoroughly with
deionized water to remove soil particles. Roots were also washed with 1 mM H-
EDTA (pH 4.5-5.0) at 4 ºC for 30 min to remove metals from the root apoplast
(Jarvis et al., 2001). Subsequently, shoots and roots were oven-dried at 70 ºC for 48
h and their dry weights recorded. Subsamples (0.2 g) of dried plant tissue were
digested with a mixture of HNO3/HClO4 (Zhao et al., 1994) and, subsequently, Cd,
Zn, and Pb in the digest were determined using ICP-AES.
5.3.6 Statistical analysis
Differences among treatments (i.e., NM-UP, NM-P, M-UP and M-P) were
analyzed by one-way ANOVA (Microsoft Stat View Software, SAS Institute)
followed by Fischer´s PLSD-test to establish the significance of the differences
among means (the results of this Fischer´s PLSD-test are shown in Tables, as letter
superscripts). Data from enzyme activities and Biolog EcoPlatesTM (at 48 h
incubation time) were used to perform principal component analysis (PCA). One-
way ANOVAs and Fischer´s PLSD-tests were applied to PCA data in order to
determine the significance of the differences among treatments.
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5.4 Results
5.4.1 Thlaspi caerulescens growth and physiological parameters
T. caerulescens plants showed significantly (P<0.05) higher values of shoot and
root biomass in metal polluted than in control pots (Table 5.1). Actually, mean
values of plant biomass (g DW pot-1) were 2.2 and 1.9 times higher for shoots and
roots, respectively, in metal polluted than in control pots.
Table 5.1. Shoot and root biomass (g DW pot-1; 3 plants pot-1) of T. caerulescens plants in control non-polluted and metal polluted pots at the end of the phytoextraction experiment. Values followed with different letters are significantly different (P<0.05 or lower) according to Fischer´s PLSD-test. Mean values (n = 3) ± standard errors.
Shoot
(g DW pot-1) Root
(g DW pot-1)
NM-P 6.09 ± 1.33a 1.35 ± 0.19a
M-P 13.2 ± 1.16b 2.56 ± 0.53b
Nonetheless, fluorescence (Fv/Fm) values for plants growing in both metal
polluted and control pots were normal and identical (i.e., 0.80 ± 0.01), indicating
that plants had an optimal physiological status and showed no symptoms of
phytotoxicity. In turn, at the end of the experiment, chlorophyll a+b values were
higher in metal polluted than in control pots (i.e., 1012.50 ± 2.50 and 708.64 ± 9.12
μmol m-2 for metal polluted and control pots, respectively).
5.4.2 Thlaspi caerulescens metal uptake T. caerulescens plants grown in metal polluted soils showed a shoot metal
concentration of 337 mg of Cd, 5670 mg of Zn and 76.6 mg of Pb per kg of dry
weight tissue (Table 5.2). Cadmium and Zn were efficiently translocated from roots
to shoots, i.e. the translocation factor (TF = shoot metal concentration/root metal
concentration) was 1.6 and 4.1 for Cd and Zn, respectively. On the contrary, most
of the Pb was retained in the roots, as indicated by a TF value of 0.16. Finally, 4.45
mg of Cd, 74.8 mg of Zn, and 1.01 mg of Pb were accumulated in T. caerulescens shoots per pot. The bioconcentration factor (BF = shoot metal concentration/soil
metal concentration) achieved by the T. caerulescens plants was 4.9, 8.4 and 0.2 for
Cd, Zn and Pb, respectively.
evaluation of the efficiency of metal phytoremediation processes with microbioloGical indicators of soil health
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Table 5.2. Shoot and root metal concentrations (mg kg-1 DW tissue) of T. caerulescens plants in metal polluted and control pots at the end of the phytoextraction experiment. NM-P: no metal, planted; M-P: metal, planted. Values followed with different letters are significantly different (P<0.05 or lower) according to Fischer´s PLSD-test. Mean values (n = 3) ± standard errors.
Shoots (mg kg-1 DW tissue)
Roots
(mg kg-1 DW tissue) Cd Zn Pb Cd Zn Pb
NM-P 0.3 ± 0.0a 1550 ± 133a 0.6 ± 0.2a 1.1 ± 0.2a 417 ± 31.8a 4.7 ± 0.9a
M-P 337 ± 54.6b 5670 ± 537b 76.6 ± 8.8b 209 ± 5.4b 1400 ± 132b 479 ± 25.4b
5.4.3 Soil physicochemical parameters
In the presence of metals, significantly lower values of extractable K+ were
observed in both planted and unplanted pots (Table 5.3), as compared to control
non-polluted pots, most likely due to the addition of KNO3 to these control pots
(see Materials and Methods). Planted pots showed significantly higher and lower
values of soil pH and Olsen P, respectively, than unplanted pots in both control and
metal polluted soils (Table 5.3). In metal polluted pots, T. caerulescens growth resulted
in significantly lower values of CEC.
At the end of the experiment, in the metal polluted soils, a 32, 37, and 42 %
reduction in total Cd, Zn and Pb, respectively, was observed in planted pots, as
compared to unplanted ones (Table 5.4). On the contrary, in these metal polluted
soils, the concentration of phytoavailable (CaCl2 extractable) Cd was not
significantly different between planted and unplanted pots (Table 5.4). Instead,
phytoavailable Zn and Pb concentrations were 14 and 27% lower, respectively, in
planted versus unplanted pots.
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10
1
Tab
le 5
.3. S
oil p
H, o
rgan
ic m
atte
r (O
M) c
onte
nt, t
otal
nitro
gen
(N),
catio
n ex
chan
ge c
apac
ity (C
EC)
, elec
trica
l con
duct
ivity
(EC)
, and
ext
ract
able
phos
phor
us (P
), po
tass
ium
(K+),
calci
um (C
a2+) a
nd m
agne
sium
(Mg2
+) m
easu
red
at th
e en
d of
the
phyt
oext
ract
ion
expe
rimen
t. N
M-U
P: n
o m
etal,
unp
lante
d; N
M-P
: no
met
al,
plan
ted;
M-U
P: m
etal,
unp
lante
d; M
-P: m
etal,
plan
ted.
Valu
es f
ollo
wed
with
diff
eren
t let
ters
are
sig
nific
antly
diff
eren
t (P<
0.05
or
low
er) a
ccor
ding
to F
ische
r´s
PLSD
-test
. Mea
n va
lues
(n =
3) ±
stan
dard
err
ors.
pH
O
M
Tot
al N
C
EC
E
C
P K
+
Ca2
+
Mg2
+
(%)
(%)
(meq
100
ml-1
) (µ
S cm
-1)
(mg
kg-1)
(mg
kg-1)
(mg
kg-1)
(mg
kg-1)
NM
-UP
4.40
± 0
.09a
b 5.
37 ±
0.3
6a
0.26
± 0
.01a
10
.5 ±
0.3
3a
3260
± 1
56a
19.7
± 0
.54a
73
2 ±
15.
3a
1230
± 6
8.4a
14
0 ±
7.3
6ab
NM
-P
4.77
± 0
.05c
5.
31 ±
0.3
6a
0.24
± 0
.00a
9.
92 ±
0.4
0a
2870
± 4
2.2a
b 14
.0 ±
0.9
4b
610
± 4
5.5b
12
20 ±
39.
4a
165
± 6
.84a
M-U
P 4.
30 ±
0.0
5a
5.44
± 0
.17a
0.
26 ±
0.0
1a
9.61
± 0
.08a
28
80 ±
120
ab
18.0
± 0
.47a
13
1 ±
6.4
8c
1200
± 1
3.2a
13
1 ±
4.6
4b
M-P
4.
63 ±
0.0
7bc
5.66
± 0
.15a
0.
25 ±
0.0
0a
8.15
± 0
.31b
25
70 ±
32.
5b
12.0
± 0
.47b
66
.0 ±
4.3
2c
1100
± 4
4.9a
15
4 ±
7.7
9ab
Tab
le 5
.4.
Tota
l (a
qua
regi
a di
gest
ed)
and
phyt
oava
ilabl
e (C
aCl 2
extra
ctab
le) m
etal
conc
entra
tions
(m
g kg
-1 D
W s
oil)
in s
oil
sam
ples
at
the
end
of t
he
phyt
oext
ract
ion
expe
rimen
t. A
t the
beg
inni
ng o
f the
exp
erim
ent,
soils
wer
e ar
tifici
ally
cont
amin
ated
with
a m
ixtu
re o
f met
als c
onta
inin
g 1,
000
mg
Zn
kg-1 D
W so
il,
500
mg
Pb k
g-1 D
W s
oil,
and
100
mg
Cd k
g-1 D
W s
oil.
NM
-UP:
no
met
al, u
nplan
ted;
NM
-P: n
o m
etal,
plan
ted;
M-U
P: m
etal,
unp
lante
d; M
-P: m
etal,
plan
ted.
V
alues
follo
wed
with
diff
eren
t let
ters
are
sign
ifica
ntly
diffe
rent
(P<
0.05
or l
ower
) acc
ordi
ng to
Fisc
her´
s PLS
D-te
st. M
ean
valu
es (n
= 3
) ± st
anda
rd e
rror
s.
T
otal
(m
g kg
-1 D
W so
il)
Ph
ytoa
vaila
ble
(mg
kg-1 D
W so
il)
C
d Zn
Pb
Cd
Zn
Pb
NM
-UP
0.80
± 0
.01a
77
.0 ±
29.
1a
46.8
± 2
5.4a
0.27
± 0
.01a
62
.8 ±
5.4
0a
2.81
± 0
.09a
NM
-P
0.80
± 0
.01a
11
9 ±
14.
6a
25.5
± 3
.27a
0.39
± 0
.07a
44
.2 ±
1.5
1a
2.90
± 0
.10a
M-U
P 10
1 ±
6.4
2b
1060
± 6
3.4b
59
1 ±
18.
6b
77
.6 ±
1.9
3b
572
± 2
4.1b
47
.1 ±
1.0
9b
M-P
68
.3 ±
10.
3c
672
± 1
31c
344
± 5
7.3c
79.9
± 1
.44b
49
5 ±
22.
8c
34.2
± 3
.29c
evaluation of the efficiency of metal phytoremediation processes with microbioloGical indicators of soil health
100
101
5.4.4 Soil enzyme activities
T. caerulescens growth led to significantly higher values of arylsulphatase, and
acid and alkaline phosphatase activities in both metal polluted and control soils
(Table 5.5), and also significantly higher values of β-glucosidase activity in metal
polluted soils (Table 5.5). Table 5.5. Soil enzyme activities at the end of the phytoextraction experiment. NM-UP: no metal, unplanted; NM-P: no metal, planted; M-UP: metal, unplanted; M-P: metal, planted. Values followed with different letters are significantly different (P<0.05 or lower) according to Fischer´s PLSD-test. Mean values (n = 3) ± standard errors.
β-Glucosidase Arylsulphatase Acid phosphatase Alkaline phosphatase Urease
(mg ρ-Nitrophenol kg-1 h-1) (mg N-NH4+ kg-1
h-1)
NM-UP 81.0 ± 10.6a 67.3 ± 15.7ab 348 ± 48.0a 167 ± 10.5a 31.0 ± 5.8ab
NM-P 133 ± 12.8ab 120 ± 11.8c 743 ± 81.3b 241 ± 20.2b 45.3 ± 10.8a
M-UP 87.3 ± 3.3a 44.6 ± 1.3a 311 ± 24.9a 182 ± 6.4a 9.6 ± 1.8b
M-P 222 ± 52.2b 96.0 ± 8.2bc 745 ± 30.7b 250 ± 22.6b 25.3 ± 6.6ab
In metal polluted soils, the presence of T. caerulescens led to a 154, 115, 140,
37 and 164% increase in the activity of β-glucosidase, arylsulphatase, acid
phosphatase, alkaline phosphatase and urease, respectively. In control soils, T. caerulescens growth led to a 64, 78, 114, 44 and 46% increase in the activity of β-
glucosidase, arylsulphatase, acid phosphatase, alkaline phosphatase and urease,
respectively.
In order to provide a visual illustration of the overall soil biochemical
functionality, together with an integrated fingerprint of the effect of treatments on
soil functional diversity, a sun ray plot is presented in Figure 1 using the target NM-
P soil as 100% reference. The presence of T. caerulescens plants led to higher values of
all enzyme activities here tested in both metal polluted and control soils (Fig. 5.1).
The shape of the sun-ray plot was different in metal polluted soils, as compared to
control soils, indicating a distinct pattern of soil enzyme activity.
5. functional diversity as indicator of the recovery of soil health derived from Thlaspi caerulescens Growth and metal phytoextraction
101
103
Figure 5.1. Sun ray plot of soil enzyme activities at the end of the phytoextraction experiment. NM-UP: no metal, unplanted; NM-P: no metal, planted; M-UP: metal, unplanted; M-P: metal, planted. A value of 100 corresponds to the mean value obtained for each specific enzyme activity in the target NM-P soil.
The application of PCA to enzyme data (data not shown) significantly
(P<0.05) separated M-P from all the other treatments along PC1 (PC1 accounted
for 73% of the variance). Also, along PC1, the PCA significantly separated NM-P
from NM-UP pots. In turn, the PCA significantly separated M-UP pots from
control non-polluted pots along PC2 (but PC2 accounted for only 16% of the
variance). Finally, along PC2, NM-P pots were significantly separated from metal
polluted pots.
5.4.5 Community-level physiological profiles
Figure 5.2 shows the AWCD curves obtained with the Biolog EcoPlatesTM. In
this Figure, it can be observed that, at approximately an incubation time of 48 h, the
highest rate of microbial growth was achieved in the Biolog EcoPlatesTM. In
unplanted pots, the AWCD value at 48 h for metal polluted soils was slightly higher
(the difference was not statistically significant) than that obtained for control soils.
evaluation of the efficiency of metal phytoremediation processes with microbioloGical indicators of soil health
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104
In planted pots, the AWCD value at 48 h for metal polluted soils was very similar to
that obtained for control soils. T. caerulescens growth resulted in significantly higher
absorbance values, in both metal polluted and control soils, than those observed in
unplanted pots (Fig. 5.2).
Figure 5.2. Average well colour development (AWCD) curves at the end of the phytoextraction experiment. NM-UP: no metal, unplanted; NM-P: no metal, planted; M-UP: metal, unplanted; M-P: metal, planted. Values followed with different letters are significantly different (P<0.05 or lower) at an incubation time of 48 h according to Fischer´s PLSD-test.
Figure 5.3 shows the metabolic fingerprint of the CLPPs displayed by planted
and unplanted pots at the end of the experiment (only those substrates showing
significant differences among treatments are presented). In relation to the pattern of
individual substrates´ utilization, D-cellobiose, ketobutyric acid, D-malic acid and
glucose-1-phosphate were utilized to a significantly greater extent (P<0.05) by the
culturable portion of the soil microbial community in M-P pots than in all the other
treatments (according to Fisher´s PLSD test).
5. functional diversity as indicator of the recovery of soil health derived from Thlaspi caerulescens Growth and metal phytoextraction
103
105
Figure 3. Metabolic fingerprints of substrate utilization patterns obtained with the EcoPlatesTM at an incubation time of 48 h [only those substrates showing significant differences (P<0.05) among treatments, according to ANOVA, are presented]. NM-UP: no metal, unplanted; NM-P: no metal, planted; M-UP: metal, unplanted; M-P: metal, planted.
The kinetic parameters obtained from fitting the “AWCD versus time” curve to
the density-dependent logistic growth equation indicated above are presented in
Table 5.6. In control non-polluted soils, K values were found to be significantly
higher in planted versus unplanted pots. The presence of T. caerulescens led to
significantly lower values of s in metal polluted soils.
evaluation of the efficiency of metal phytoremediation processes with microbioloGical indicators of soil health
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106
Table 5.6. Kinetic parameters K, r and s obtained from fitting the “AWCD versus time” curve to the density-dependent logistic growth equation. NM-UP: no metal, unplanted; NM-P: no metal, planted; M-UP: metal, unplanted; M-P: metal, planted. Values followed with different letters are significantly different (P<0.05 or lower) according to Fischer´s PLSD-test. Mean values (n = 3) ± standard errors.
K r s
NM-UP 0.90 ± 0.15a 0.12 ± 0.01a 51.5 ± 1.88ab
NM-P 1.20 ± 0.01b 0.13 ± 0.00a 48.5 ± 0.82a
M-UP 0.99 ± 0.07ab 0.12 ± 0.01a 53.6 ± 1.89b
M-P 1.20 ± 0.01b 0.13 ± 0.00a 48.5 ± 0.67a
The application of PCA to the absorbance data obtained with the Biolog
EcoPlatesTM at 48 h incubation time (Fig. 5.4a) significantly (P<0.05) separated M-P
pots from all the other treatments along PC1 (PC1 accounted for 68% of the
variance). Furthermore, along PC2, NM-P pots were significantly separated from all
the other pots (but PC2 accounted for only 21% of the variance).
The value of the kinetic parameter r provides information on how rapidly a
carbon source can be metabolised by a community once the density has reached the
level at which colour production begins. Therefore, r may be the most useful
parameter for comparing the relative functional responses of different communities
(Preston-Mafham et al., 2002). In consequence, another PCA was carried out using
the values of r (Fig. 5.4b), finding out that NM-UP pots were significantly (P<0.05)
separated from all the other treatments along PC1.
5. functional diversity as indicator of the recovery of soil health derived from Thlaspi caerulescens Growth and metal phytoextraction
105
107
Figure 5.4. Principal component analysis from (A) absorbance values obtained with the EcoPlatesTM at an incubation time of 48 h and (B) the values of the kinetic parameter r. NM-UP: no metal, unplanted; NM-P: no metal, planted; M-UP: metal, unplanted; M-P: metal, planted. In (A): PC1 and PC2 account for 68 and 21% of the variance, respectively. In (B): PC1 and PC2 account for 48 and 18% of the variance, respectively.
evaluation of the efficiency of metal phytoremediation processes with microbioloGical indicators of soil health
106
108
Finally, Table 5.7 shows the diversity indexes calculated from both soil enzyme
activities and Biolog EcoPlatesTM. At the end of the experiment, it was observed
that the presence of metals had led to significantly lower values of the H’ index
obtained from soil enzyme activities in both planted and unplanted pots (Table 5.7).
Table 5.7. Diversity indexes calculated from EcoPlatesTM absorbance data at 48 h incubation time and from soil enzyme activities. S = richness; H’ = Shannon´s diversity; J’ = Shannon´s evenness. NM-UP: no metal, unplanted; NM-P: no metal, planted; M-UP: metal, unplanted; M-P: metal, planted. Values followed with different letters are significantly different (P<0.05 or lower) according to Fischer´s PLSD-test. Mean values (n = 3) ± standard errors.
S - Biolog H’ - Biolog J’ - Biolog H’ - Enzymes
NM-UP 13.3 ± 1.76a 3.47 ± 0.25a 0.93 ± 0.02a 2.31 ± 0.01a
NM-P 17.3 ± 0.88ab 3.83 ± 0.08a 0.93 ± 0.00a 2.30 ± 0.01a
M-UP 18.3 ± 1.33ab 3.88 ± 0.09a 0.93 ± 0.01a 2.18 ± 0.02b
M-P 27.7 ± 2.33b 4.23 ± 0.14a 0.93 ± 0.00a 2.19 ± 0.02b
5.5 Discussion
5.5.1 Metal phytoextraction
T. caerulescens (Lanestosa ecotype) plants proved a high metal tolerance and
capacity to grow at an optimum rate at elevated soil metal concentrations. Indeed, in
the presence of metals, T. caerulescens plants achieved a considerable biomass and
showed no reduction of photochemical efficiency together with higher values of
photosynthetic pigments than those observed in control soils. Furthermore, they
had a very prolific root system, covering with fine roots the whole area of the pot.
Most importantly, our local ecotype Lanestosa showed a high capacity to
accumulate Zn and Cd, particularly the latter. Actually, the threshold value of 100
mg Cd kg-1 DW shoot indicated by Baker et al. (2000) for Cd hyperaccumulators
was exceeded. For both metals, the shoot-to-root metal concentration ratio was well
over 1 as it is usually the case with hyperaccumulating plants (McGrath and Zhao,
2003). However, for all metals here studied, the bioconcentration factor was <10,
the threshold value considered for a phytoextraction process to be feasible
(McGrath et al., 2006). These results contrast with those previously reported by us
5. functional diversity as indicator of the recovery of soil health derived from Thlaspi caerulescens Growth and metal phytoextraction
107
109
for this very same ecotype (Hernández-Allica et al. 2006a). In that study, Lanestosa
plants appeared as Zn hyperaccumulators (with a zinc BF of 16.7) but not of Cd.
This disagreement is most likely due to different experimental designs (e.g., a
chronically polluted mine soil versus an artificially polluted, recently spiked grassland
soil) and metal concentrations.
Regarding soil metal concentrations in planted pots, at the end of the
experiment, total metal values had suffered a more pronounced decrease than values
of phytoavailable metal fractions. Although T. caerulescens plants do not seem to
access specific metal pools in the soil (Gerard et al., 2000; Hutchinson et al., 2000;
Schwartz et al., 2003), in our study, due to a considerable metal uptake, the kinetics
of replenishment of the depleted phytoavailable metal pool may have led to
depletion of pools thought to be otherwise poorly available to plants, as previously
suggested (Whiting et al., 2001; Hammer and Keller, 2002). In addition, soil pH
increased in planted pots, thus resulting in lower metal bioavailability. Consequently,
in agreement with other works (Luo et al., 2000; Wang et al., 2006), in our study,
metal hyperaccumulation was not achieved through soil acidification.
5.5.2 Impact of metal pollution on biological indicators of soil health
In this study, metal pollution did not cause a clear inhibition of soil enzyme
activities (i.e., in both planted and unplanted pots, values of enzyme activity were
lower in metal polluted versus control soils only for arylsulphatase and urease; in any
case, the differences were not statistically significant) (Table 5.5). Metals are toxic to
living organisms primarily due to their protein-binding capacity and hence ability to
inhibit enzymes (Dick et al., 1997). But the nature and degree of inhibition of soil
enzymes by metals is strongly related to soil type. Actually, metals have a varying
impact on soil enzyme activity depending not only on their total concentration in
the soil but rather on their capacity to interact with enzyme protein. Therefore, their
impact depends on soil pH, OM levels, and interaction with other soil minerals and
OM (Tate, 2002). Usually, inhibition of enzyme activity in metal polluted soils
reflects the “bioavailability” of the metals, because the mechanisms that protect soil
enzymes from inhibition by metals are likely to be the same mechanisms limiting
metal uptake by plants and soil organisms (Speir and Ross, 2002). As a consequence,
evaluation of the efficiency of metal phytoremediation processes with microbioloGical indicators of soil health
108
110
soil enzyme activities are surrogate measurements of the impact of metals on soil
biota as a whole or of their uptake by, and their toxicity to, plants (Speir and Ross,
2002).
Then, since the impact of metals on soil enzymes is strongly dependent on soil
type, it is not surprising that the sensitivity of specific soil enzymes to metal
pollution varies considerably depending on the study. Kandeler et al. (1996) found
that C-acquiring enzymes (cellulase, xylanase, β-glucosidase) were the least affected
by soil pollution, phosphatase and sulfatase the most affected, and, finally, N-
acquiring enzymes (urease) had an intermediate response. In a study on metal
polluted grassland soil (Kuperman and Carreiro, 1997), β-glucosidase was the most
depressed, while phosphatase and endocellulase activities were the least.
Nonetheless, in general, arylsulphatase appears most sensitive to metal pollution,
while acid phosphatase and urease are less affected (Dick et al., 1997).
Regarding soil functional diversity, contrasting results were obtained with
EcoPlatesTM versus soil enzyme activities (Table 5.7). Indeed, it was observed that the
presence of metals led to significantly lower values of H’ obtained from enzyme
activities and non-significant higher values of S and H’ obtained from EcoPlatesTM.
This is not an unexpected result because EcoPlatesTM reflect the potential of only
the culturable portion of the microbial community to respond to substrates, while
enzyme analyses reflect the status of the whole microbial community. Interestingly,
Burkhardt et al. (1993) reported that in heavy-metal-affected bacterial communities,
relatively rare degradative capabilities, irrespective of their nature, are even rarer
than in unaffected communities, while the reverse is true for more common
capabilities. But although EcoPlatesTM data are not necessarily related to the
functional potential of the most abundant soil bacteria (Smalla et al., 1998), they
provide a useful assessment of biological responses to metal pollution. In turn,
enzymes are one of the more reactive components of the soil ecosystem and
potentially excellent indicators of the soil’s microbial functional status and diversity
(Sowerby et al., 2005). It must be remembered that values of soil enzyme activities
come from laboratory measurements of sieved soil samples under optimal
conditions of temperature, pH, substrate concentration, etc. and then do not
5. functional diversity as indicator of the recovery of soil health derived from Thlaspi caerulescens Growth and metal phytoextraction
109
111
provide data on actual enzyme activities in the soil, but an assessment of their
maximum potential activity (Vaughan and Malcolm, 1984).
5.5.3 Effect of T. caerulescens growth and metal phytoextraction on biological indicators of soil health
In metal polluted soils, T. caerulescens growth and metal phytoextraction (M-P
pots) led to significantly higher values of β-glucosidase, arylsulphatase, and acid and
alkaline phosphatase than those found in M-UP pots (Table 5.5). Likewise, values of
urease activity were higher (although in this case the differences were not statistically
significant) in M-P than M-UP pots. By contrast, the H’ index obtained from soil
enzyme activities did not differentiate between M-P and M-UP pots, most likely due
to the fact that, in our study, such index only reflects the evenness or distribution of
the enzyme activities. Then, as a consequence of the phytoextraction process (which
involves both T. caerulescens growth and metal phytoextraction), the activity of five
soil enzymes which have a key function in the cycling of C, N, P and S in the soil
increased, as compared to the activity of those same enzymes in the metal polluted
unplanted soil. Since urease, acid and alkaline phosphatase, and arylsulphatase are
involved in the release of bioavailable forms of N, P and S, respectively, then it was
concluded that, as a result of our phytoextraction process, soil fertility, an important
attribute of a healthy soil, was probably improved in our phytoremediated soils.
Interestingly, D-cellobiose, ketobutyric acid, D-malic acid and glucose-1-
phosphate were utilized to a greater extent by the culturable portion of the soil
microbial community in M-P pots than in all the other treatments (Fig. 5.3). In this
respect, in hyperaccumulators, levels of citric, malic, malonic and oxalic acids have
been correlated with elevated concentrations of Ni or Zn in the biomass (Lee et al.,
1978; Tolrá et al., 1996). Nonetheless, T. caerulescens plants appear to have
constitutively high concentrations of malic acid/malate in their tissues (Shen et al.,
1997; Boominathan and Doran, 2003).
As observed in Figures 5.1 and 5.2, the presence of T. caerulescens plants, as
compared to the metal phytoextraction itself, had the major effect on soil biological
parameters. As compared to bare soil, vegetated soils have frequently been reported
evaluation of the efficiency of metal phytoremediation processes with microbioloGical indicators of soil health
110
112
to have higher rates of microbial activity due to the presence of additional surfaces
for microbial colonization and organic compounds released by the plant roots (Tate,
1995; Delorme et al., 2001). In our study, the establishment of a vegetation cover by
the fifth month of growth led to significantly higher values of many of the biological
indicators of soil health here measured, as compared to unvegetated soils. The H’
index obtained from soil enzyme activities did not differentiate between planted and
unplanted pots, again most likely due to its reflecting only the distribution of the
enzyme activities. Gremion et al. (2004) and Wang et al. (2006) also observed that
rhizosphere soil had higher biological activities than non-rhizosphere soil in similar
phytoextraction experiments. In our study, the increase in soil pH found in planted
pots may also partly explain why they had higher biological activities than unplanted
pots, as suggested by Wang et al. (2006).
Finally, since colour development typically follows a sigmoidal trend with time,
Lindstrom et al. (1998) developed a sigmoidal growth model and used the
parameters of the model for statistical analyses. Being independent of incubation
time, kinetic analysis removes the need for a decision on the optimum incubation
time for analysis (Garland, 1996; Verschuere, 1997) and has been suggested to give a
more effective description of the whole-community substrate utilization patterns
(Haack et al., 1995; Garland, 1997). Then, in theory, with the kinetic approach, a
more detailed understanding of the nature of the colour response may be feasible.
However, this concept should be approached with caution given the general lack of
understanding concerning the physiological or ecological basis for differences in the
kinetic parameters and the known selective bias due to growth in the plates (Smalla
et al., 1998). In our study, the PCA carried out using the values of r was not able to
clearly discriminate between treatments (Fig. 5.4b). On the contrary, when a PCA
was applied to the absorbance data obtained with the Biolog EcoPlatesTM, clear
differences between treatments were found. This supports the findings of Garland
et al. (2001) that, despite the potential utility of the kinetic approach for the analysis
of CLPP results, kinetic analysis does not appear to be the best approach for rapid
classification of samples. Our data indicate that the utilization of single point plate
readings at a set point in the AWCD curve is a better tool for classification.
5. functional diversity as indicator of the recovery of soil health derived from Thlaspi caerulescens Growth and metal phytoextraction
111
113
5. 6 Conclusions
T. caerulescens (Lanestosa ecotype) plants proved a high metal tolerance and
capacity to grow at an optimum rate at elevated soil metal concentrations. Most
importantly, our ecotype Lanestosa showed a high capacity to accumulate Zn and
Cd, particularly the latter.
In our study, metal pollution did not cause a clear inhibition of soil enzyme
activities. Contrasting results were obtained with EcoPlatesTM versus soil enzyme
activities. Actually, the presence of metals led to significantly lower values of H’
obtained from enzyme activities and non-significant higher values of S and H’
obtained from EcoPlatesTM. Interestingly, D-cellobiose, ketobutyric acid, D-malic
acid and glucose-1-phosphate were utilized to a greater extent by the culturable
portion of the soil microbial community in M-P pots than in all the other
treatments.
As a consequence of the phytoextraction process (which involves both T. caerulescens growth and metal phytoextraction), the activity of five soil enzymes which
have a key function in the cycling of C, N, P and S in the soil increased. In any
event, the presence of T. caerulescens plants, as compared to the metal
phytoextraction itself, had the major effect on soil biological parameters. Actually, in
metal polluted soils, the presence of T. caerulescens led to a 154, 115, 140, 37 and
164% increase in the activity of β-glucosidase, arylsulphatase, acid phosphatase,
alkaline phosphatase and urease, respectively. In control soils, T. caerulescens growth
led to a 64, 78, 114, 44 and 46% increase in the activity of β-glucosidase,
arylsulphatase, acid phosphatase, alkaline phosphatase and urease, respectively.
Biological indicators of soil health, such as soil enzymes and community level
physiological profiles, are valid tools to evaluate the success of a continuous metal
phytoextraction process.
6. impact of metal pollution and Thlaspi caerulescens phytoextraction on soil microbial communities
113
114
6. IMPACT OF METAL POLLUTION AND Thlaspi caerulescens PHYTOEXTRACTION ON SOIL MICROBIAL COMMUNITIES
Epelde et al., in preparation for publication
6.1 Abstract
Metal phytoextraction using hyperaccumulating plants has great potential for
the remediation of metal polluted soils. When assessing the success of a
phytoextraction process, emphasis must be placed on the recovery of soil health. In
this respect, soil microbial parameters can be used as valuable bioindicators of the
effects of pollutants on soil health. Consequently, a short-term microcosm
experiment was carried out to study the impact of Zn and/or Cd pollution and T. caerulescens phytoextraction on soil health through the determination of soil microbial
properties: basal respiration; substrate-induced respiration (SIR); respiration
quotient (QR); structural genetic diversity of soil bacteria with PCR-DGGE; gene
abundance from real-time PCR for total bacteria, ammonia-oxidizing bacteria and
chitin-degrading bacteria; and Geochip functional gene array. T. caerulescens confirmed its great potential for Zn and Cd phytoextraction: shoots accumulated up
to 8,211 and 1,763 mg kg-1 DW of Zn and Cd, respectively (besides, plants showed
most promising bioconcentration factors: up to 17.4 for Zn and 8.0 for Cd). Zn
pollution led to decreased levels of both basal respiration and SIR. T. caerulescens growth and metal phytoextraction increased the values of these two parameters. In
soils polluted with 1,000 mg Zn kg-1 and 250 mg Cd kg-1 DW, both metals had a
clear effect on structural genetic diversity of soil bacteria. Functional diversity
(number of genes detected) and redundancy, regardless of gene category, increased
as a result of metal pollution. The abundance of Zn and/or Cd resistance genes
detected was higher in T. caerulescens planted versus unplanted soils, even in the
absence of metals.
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6.2 Introduction
Soil metal pollution is an environmental problem of worldwide concern. Due
to their immutable nature and toxicity, heavy metals persist in the soil environment
for very long periods of time and adversely affect the growth and survival of
(micro)organisms, with concomitant negative effects on soil fertility and functioning
(Epelde et al., 2009a).
Phytoremediation, the use of green plants to remove pollutants from the
environment or to render them harmless (Cunningham and Berti, 1993), has great
potential for the remediation of polluted soils. Within the phytoremediation field,
the term “phytoextraction” refers to the utilization of plants to transport and
concentrate pollutants, mainly metals, from the soil into the above-ground shoots
(Salt et al., 1995). Thlaspi caerulescens, a hyperaccumulating plant extensively studied
due to its remarkable capacity to phytoextract zinc (Zn) and cadmium (Cd) from
polluted soils (Hernández-Allica et al., 2006a, b; Epelde et al., 2008a), has been
suggested as a model species for research on metal phytoextraction (Assunção et al.,
2003).
Traditionally, when evaluating the success of a phytoextraction process,
emphasis has mostly been placed on metal removal from soil. However, most
importantly, the ultimate goal of any phytoextraction process must be not only to
remove the metal(s) from the soil but to restore soil health (i.e., the soil´s continued
capacity to sustain plant growth and maintain its functions) (Coleman et al., 1998).
Soil microbial properties, particularly those reflecting the biomass, activity and
diversity of the soil microbial communities, have great potential as bioindicators of
the effects of disturbances (e.g., metal pollution) on soil health. Likewise, DNA
microarray technologies are rapidly becoming important tools for the analysis of
complex microbial communities inhabiting various environments (Wilson et al.,
2002; Zhou, 2003). A recently developed functional gene array, termed GeoChip
(He et al., 2007), appears most promising for the assessment of the impact of
pollutants on soil health (as well as for the assessment of the efficiency of
remediation methods) since it contains probes from genes with known biological
functions (e.g., nitrogen, carbon, sulfur and phosphorus cycling; metal reduction and
resistance; degradation of organic contaminants) and has been reported as a high-
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throughput, powerful genomic technology for research on biogeochemical,
ecological and environmental processes (Rhee et al., 2004; Li et al., 2005; He et al.,
2007; Yergeau et al., 2007b; Wu et al., 2008; Zhou et al., 2008).
The main objective of the current work was to determine the impact of metal
(Cd and Zn) pollution and T. caerulescens phytoextraction on soil health through the
determination of a variety of soil microbial properties with potential as bioindicators
of soil functioning (i.e., soil respiration; substrate-induced respiration; microbial
respiration quotient; structural genetic diversity of soil bacteria with PCR-DGGE;
gene copy abundance from real-time PCR for total bacteria, ammonia-oxidizing
bacteria and chitin-degrading bacteria; and Geochip functional gene array). The
capacity of T. caerulescens to phytoextract Zn and Cd from polluted soil was also
studied.
6.3 Materials and methods
6.3.1 Experimental design
A short-term (4 months) microcosm phytoextraction experiment was carried
out with soil collected from the top layer (0-30 cm) of a natural grassland located in
Derio (Basque Country, northern Spain). Immediately after collection, the soil was
sieved to <4 mm, air-dried at 30 ºC for 48 h, and subjected to physicochemical
characterization according to standard methods (MAPA, 1994). The soil was a clay
loam, with a pH of 5.2, an organic matter (OM) content of 4.12%, a total nitrogen
(N) content of 0.23%, a C/N ratio of 10.4, a phosphorus (P) content of 26.4 mg kg-
1, and an electrical conductivity of 0.08 dS m-1. Subsequently, the soil was artificially
polluted with combinations of different concentrations of Zn (250, 500 and 1,000
mg kg-1 DW) as ZnCl2 and Cd (0, 50, 250 mg kg-1 DW) as CdCl2. Thus, the
following 9 combinations were studied (in mg kg-1 DW): (1) 250 Zn + 0 Cd
(control-unpolluted; a small concentration of Zn was added to support T. caerulescens growth); (2) 250 Zn + 50 Cd; (3) 250 Zn + 250 Cd; (4) 500 Zn + 0 Cd; (5) 500 Zn
+ 50 Cd; (6) 500 Zn + 250 Cd; (7) 1,000 Zn + 0 Cd; (8) 1,000 Zn + 50 Cd; and (9)
1,000 Zn + 250 Cd. Then, metal polluted soils were stored at a constant room
temperature and 15% relative humidity for 6 months. Study pots (17 cm diameter x
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13 cm height) were filled with 1.5 kg (DW) of each of these polluted soils, which
were then fertilized with 120 mg kg-1 of N, P, and K+, and subsequently allowed to
precondition, under the greenhouse conditions described below, for one week.
On the other hand, T. caerulescens J. & C. Presl. seeds of a local ecotype, named
Lanestosa, were germinated for two weeks (on a mixture of perlite and vermiculite,
2:3 v/v, moistened with deionized water) in a growth chamber under the following
controlled conditions: 20/16 ºC day/night temperature, 70% relative humidity, and
a photosynthetic photon flux density of 300 µmol photon m-2 s-1 by supplementing
natural illumination with white cold lamps. Then, half of the study pots were
planted with five of these T. caerulescens seedlings per pot while the other half were
kept unplanted as controls. Then, 18 treatments were studied (in quadruplicate) in
this experiment: 9 metal combinations (see above) for planted pots and 9 metal
combinations for unplanted pots. Plants were then allowed to grow for 4 months in
a soft polyethylene-covered greenhouse (Venlo-type) located in Derio (Basque
Country) at a latitude of 43º 17’ N, a longitude of 2º 52’ W, and an altitude of 65 m
above sea-level. The climate in this region is Atlantic temperate. Minimal
temperature set points controlling air-heating were 14/18 ºC night/day, and
maximal temperature set points were 18/20 ºC night/day. Vent opening
temperatures were 20/25 ºC night/day. During the experiment, average temperature
was 15/24 ºC night/day, average relative humidity 60%, and average
photosynthetically active radiation 459 µmol photon m-2 s-1.
After these 4 months, shoot and roots were harvested by cutting the shoots
exactly at the swelling formed in the root to shoot junction. Then, plant
physiological parameters and shoot and root metal contents were determined (see
below). Half of the soil present in the study pots was sampled and soil
physicochemical and microbial properties determined (see below). The remaining
half was used to grow alfalfa (Medicago sativa L.) in order to assess the capacity of
that phytoremediated soil to support plant growth at the end of the phytoextraction
experiment: 1 g (approximately, 100 seeds) of alfalfa seeds was sown in each study
pot. Alfalfa plants were then allowed to grow under the same greenhouse conditions
described above for two months (plants were bottom watered periodically as
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needed). Finally, shoots were harvested (as above), washed thoroughly with
deionized water, oven-dried at 70 ºC for 48 h and their dry weights recorded.
6.3.2 Soil metal concentrations
Soil was sampled at the end of the phytoextraction experiment, i.e. 4 months
after T. caerulescens plant transplant. For soil physicochemical analysis, soils were air-
dried at 30 ºC, sieved to <2 mm, and stored at 4 ºC until analysis. Soil pH, OM
content, total N, nitrates content, extractable P and potassium (K+) were measured
following standard methods (MAPA, 1994).
Total concentrations of heavy metals in soil were determined using flame
atomic absorption spectrometry (AAS, Varian) following digestion with a mixture of
HNO3/HClO4 (Zhao et al., 1994). Likewise, the CaCl2-extractable (0.01 M CaCl2)
fraction of metals was determined according to Houba et al. (2000) and analyzed by
AAS.
6.3.3 Soil microbial parameters
For analysis of microbial parameters, soils were sieved to <2 mm and stored
fresh at 4 ºC until analysis. Soil basal respiration was determined according to ISO
16072 Norm at 30 ºC and a water holding capacity (WHC) of 60%. Substrate-
induced respiration (SIR) was determined, with glucose as substrate, following ISO
17155 Norm. Microbial respiration quotient (QR) was calculated as the ratio
between values of soil basal respiration and SIR.
Soil samples for DNA analysis were sieved to < 2 mm and stored fresh at -20
ºC. DNA was extracted from soil samples (0.25 g soil) using Power SoilTM DNA
Isolation Kit (MO BIO Laboratories, California, USA) according to the
manufacturer’s specifications. Prior to DNA extraction, soil samples were washed
twice in 120 mM K2HPO4 (pH 8.0) to wash away extracellular DNA from soil
without loss of intact cells (Kowalchuk et al., 1997). In this way, most of the
extracted DNA comes from live bacterial cells (nonetheless, a small fraction of the
extracted DNA might be associated with unlysed dead cells or extracellular DNA
not completely washed from the soil samples) (Kowalchuk et al., 1997).
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For real-time PCR measurements of gene copy abundance, the primers and
amplification regimes used to assess (i) 16S rRNA gene fragments for total bacteria,
(ii) ammonia monooxygenase gene (amoA) for ammonia-oxidizing bacteria and (iii)
group A bacterial chitinases for chitin-degrading bacteria are summarized in Table
6.1. Each 25 μl reaction contained 5 μl of template, 12.5 μl of ABsolute QPCR
SYBR green 2x reaction mix (AbGene, Epsom, UK), 2.5 μl of each primer at a
concentration of 10 μM (0.25 μl at 30 μM in the case of total bacteria), 2.5 μl bovine
serum albumin (BSA; 40 mg ml-1), and 4.5 μl of water in the case of total bacteria.
Known template standards were made from whole genomes extracted from pure
bacterial isolates as described in Yergeau et al. (2007a). All mixes were made using a
CAS-1200 pipetting robot (Corbett Research, Sydney, Australia) to reduce variation
caused by pipetting errors. PCR conditions were as follows: 95 ºC for 15 min; 94 ºC
for 60 s (30 s in the case of total bacteria); specified annealing (Table 1); 72 ºC for
60 s; optional reading (Table 1; 40 cycles); and melt curve from 55 ºC (65 ºC in the
case of total bacteria) to 98 ºC. PCR amplification and product quantification were
performed using the Rotor-Gene 3000 (Corbett Research). Gene copies were
quantified against the standard curve using ROTOR-GENE 6 software (Corbett
Research, Sydney, Australia).
Table 6.1: Primers and amplification regimes used in the real-time PCR.
Primer 1 Primer 2 Annealing Reading Reference Total bacteria Ba519F Ba907R 52 ºC/30 s - (Lueders et al.,
2004a,b)
AmoA AmoA-1F AmoA-2R-TC 52 ºC/60 s 81 ºC/15 s (Nicolaisen and Ramsing, 2002)
Chitinase group A GA1F GA1R 63 ºC/30 s - (Williamson et al.,
2000)
DGGE (denaturing gradient gel electrophoresis) and Geochip analysis were
done only with four of the studied soils (those representing the most extreme cases):
250 Zn + 0 Cd planted; 250 Zn + 0 Cd unplanted; 1,000 Zn + 250 Cd planted;
1,000 Zn + 250 Cd unplanted. For DGGE, bacterial 16S rRNA was amplified by
using the primer pair F968-GC/R1378 (Heuer et al., 1997). PCRs were carried out
in 25 μl volumes containing 2.5 μl of 10x PCR buffer, 0.5 μl of each primer (30
μM), 2.5 μl of dNTPs mix (2 mM), and 3.5 U μl-1 of Expand high fidelity
polymerase (Roche, Mannheim, Germany). Amplifications were carried out on a
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PTC-200 thermal cycler (MJ-Research, Waltham, MA). PCR conditions were as
follows: initial denaturation at 94 ºC for 2 min; 92 ºC for 30 s; 55 ºC for 1 min; 68
ºC for 45 sec (+1 sec cycle-1; 35 cycles) and extension at 68 ºC for 5 min. A D-Code
Universal Mutation Detection System (Bio-Rad, Hercules, CA) was used. The
denaturating gradient was from 45 to 65% of the denaturant (100% denaturant is
defined as 7 M urea and 40%, v/v, formamide). DGGE was performed using 20 µl
of the PCR product in 0.5x TAE buffer at 60 ºC (1x TAE = 40 mM tri-acetate, 20
mM sodium acetate, 1 mM EDTA, pH 8.0). Gradient gels were topped with 10 ml
of acrylamide containing no denaturant. Electrophoresis was performed at 200 V
for 15 min followed by 70 V for an additional 16 h. Electrophoresis gels were
stained with ethidium bromide and digital images captured using an ImaGo
apparatus (Gentaur, Brussels, Belgium) upon UV transillumination. Banding
patterns were analyzed using the Imagemaster elite program (version 4.20)
(Amersham Bioscience, Rosendaal, The Netherlands). The resulting binary
(presence-absence) matrices were used to calculate Jaccard similarity indexes (CJ =
a/a+b+c; where a, the total number of bands present in both treatments; b, the
number of bands present only in the first treatment; and c, the number of bands
present only in the second treatment) among treatments.
Before GeoChip analysis (see below), a desalting protocol was applied to the
DNA in order to remove contaminants and improve 260/230 ratios. The sample
was precipitated with 2.5x volume of 100% ice cold ethanol and 1:10 volume of
NaOAc (3 M, pH 5.2). After 3 hours of incubation, the DNA was centrifuged
(13,000 x g, 30 min) and the pellet washed with 70% ethanol. Samples were then
centrifuged (13,000 x g, 10 min), decanted, dried at room temperature, and finally
resuspended in 0.1 ml of nuclease-free water.
The rest of the protocol for the Geochip analysis is a modification of the one
described by Yergeau et al. (2007b). As the amount of DNA was small (prior to
Geochip analysis, the amount of DNA in our samples was determined on a ND-
1000 spectrophotometer; data not shown), rolling circle amplification was carried
using the TempliPhi kit (Amersham, Piscataway, NJ) according to the
manufacturer’s specifications. Spermidine (0.1 μg μL-1) and single-stranded DNA
binding protein (~260 ηg μl-1) were added to the reaction mix to facilitate
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amplification. The reactions were incubated at 30 ºC for 6 h and the enzyme was
then inactivated by incubation at 65 ºC for 10 min.
For Geochip analysis, these rolling circle amplification products were used for
DNA labeling with Cystidine-5 (Cy-5) dye: amplification products were denatured
for 5 min at 100 ºC in a solution containing 1x random octamer mix (Invitrogen,
Carlsbad, CA) and immediately chilled on ice. Following denaturation, the following
components were added: 5 mM dATP, dGTP and dCTP, 2.5 mM dTTP, 25 ηM Cy-
5 dye and 80 U of the large Klenow fragment (large fragment of DNA polymerase I;
Invitrogen). Reaction mixtures were then incubated at 37 ºC for 6 h. Labeled target
DNA was purified with a QIAquick PCR kit (Qiagen, Valencia, CA) according to
the manufacturer´s instructions, measured on a ND-1000 spectrophotometer, and
dried in a speed-vac at 45ºC for 45 min. Prior to hybridization, dried labeled DNA
was re-suspended in a solution containing 50% formamide, 3x SSC, 0.3% SDS, 0.7
μg μL-1 herring sperm DNA and 0.8 ηM dithiothreitol (DTT). This solution was
incubated at 98 ºC for 3 min and kept at 65 ºC until hybridization. Hybridizations
were performed using a HS4800 Hybridization Station (TECAN US, Durham, NC)
at 42 ºC for 10 h.
Microarrays were scanned using a ProScanArray microarray scanner (Perkin
Elmer, Boston, MA). The emitted fluorescent signal was detected by a
photomultiplier tube (PMT) at 633 ηm using a laser power of 95% and a PMT gain
of 64%. Images were then transferred to ImaGene 6.0 (BioDiscovery, El Segundo,
CA) where a grid of individual circles defining the location of each DNA spot on
the array was superimposed on the image, in order to designate each fluorescent
spot to be quantified. Hybridization spots with a signal-noise ratio SNR < 2 (He and
Zhou, 2008) were removed for further analysis. Normalization among slides was
done based on all spots mean signals (Wu et al., 2008). Replicate outliers (>2
standard deviation) were removed, and gene detection considered positive when a
positive hybridization signal was obtained from 33% of spots targeting the gene of
all replicates.
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6.3.4 Plant parameters
T. caerulescens plants were harvested at the end of the experiment, i.e. 4 months
after transplant. Fluorescence measurements were done in dark-adapted leaves after
12 h at room temperature to reduce the effects of diurnal variations in pigments and
provide comparable conditions, “artificial predawn conditions”, as described in
García-Plazaola et al. (2000) and Tausz et al. (2003). Maximal photochemical
efficiency of PSII (Fv/Fm) was determined using a portable modulated fluorimeter
(OS 5-FL, Optisciences, Tyngsboro, USA). Initial (F0) and maximal (Fm)
fluorescence were measured with a saturating pulse of 0.8 s. This measurement
represents the maximal photochemical efficiency of PSII after a period of dark
recovery and thus it can be considered as proportional to the degree of “chronic
photoinhibition” (Werner et al., 2002). Then, approximately 0.02 g FW leaf was
collected, frozen in liquid nitrogen and stored at -80º C until biochemical analysis.
Lipophilic antioxidants (carotenoids and tocopherols) and photosynthetic pigments
[a and b chlorophylls (Chl), carotenoids (Carot), violaxanthin (V), antheraxanthin
(A), zeaxanthin (Z), γ- and α-tocopherols (Toc)] were extracted and measured by
reverse-phase HPLC following the method of García-Plazaola and Becerril (1999),
with the modifications described in García-Plazaola and Becerril (2001). Shoots and
roots were then harvested separately and their fresh weights (FW) recorded.
For metal analysis, shoots and roots were washed thoroughly with deionized
water to remove soil particles. For metal desorption, roots were also washed with
1% HNO3. Subsequently, shoots and roots were oven-dried at 70 ºC for 48 h and
their dry weights recorded. Subsamples of dried plant tissue were digested with a
mixture of HNO3/HClO4 (Zhao et al., 1994) and, subsequently, Zn and Cd in the
digest were determined using AAS.
6.3.5 Statistical analysis
Significant differences (P<0.05) between treatments were analyzed by two-way
ANOVAs using Microsoft Stat View software (SAS Institute). Tukey Kramer-test
was used to establish the significance (P<0.05) of the differences among means for:
(i) treatments grouped according to their soil Zn (250 versus 500 versus 1,000) or Cd
(0 versus 50 versus 250) concentration (when, according to two-way ANOVA, no
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interaction was found between soil Zn and Cd); and (ii) all 9 metal combinations,
(when, according to two-way ANOVA, an interaction was found between soil Zn
and Cd). Relationships between soil microbial and physicochemical parameters were
explored by means of principal component analysis (PCA) applied on the
correlation matrix of these variables. In this way, PCA not only revealed the
multivariate relationships between data, but was also used as a dimension reduction
technique.
To choose between linear and unimodal models of response in DGGE binary
matrices and Geochip data, a detrended correspondence analysis (DCA) was
applied: the length of the first and the remaining axes of this DCA were short (λ <
2.5 SD), what evidenced a short beta diversity in our data along ordination axes;
therefore, a linear response model was selected. Then, a redundancy analysis (RDA)
was applied to explain DGGE and GeoChip data as a function of linear
combinations of two variables: T. caerulescens shoot biomass and soil metal
concentration (ter Braak, 1994). To explore the individual and shared effects of
shoot biomass versus soil metal concentration to the revealed patterns in DGGE and
GeoChip data, variation partitioning procedures were employed (Leps and Šmilauer,
2003). RDAs were also performed to identify the physicochemical and microbial soil
parameters with the most significant influence on DGGE and Geochip data. All
multivariate analyses were done by running Canoco for Windows 4.5 (ter Braak and
Šmilauer 2002). Pearson’s correlations were calculated between real-time PCR and
Geochip results using SPSS Programme (SPSS).
6.4 Results
6.4.1 Plant physiological parameters and metal concentrations Table 6.2 shows the values of shoot biomass achieved by T. caerulescens plants
at the end of the phytoextraction experiment. A two-way ANOVA indicated a
significant interaction between both soil metals (Cd, Zn) for shoot biomass values.
Values of shoot biomass were significantly higher in treatment 250-250 than in
treatments 250-0, 500-250 and 1,000-50 (Table 6.2).
Regarding plant physiological parameters, a significant interaction was found
between both soil metals for values of all physiological parameters determined here.
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No significant differences were observed between treatments (data not shown). The
following values (mean ± SE) were found: 0.78 ± 0.00 Fv/Fm; 402 ± 10 μmol Chl
(a+b) m2; 329 ± 2 mmol Carot mol-1 Chl (a+b); 51 ± 1 mmol VAZ mol-1 Chl (a+b); 119 ± 8 mmol A+Z mol-1 VAZ; and 109 ± 7 mmol Toc mol-1 Chl (a+b).
Concerning shoot and root metal concentrations, no interaction was found
between both soil metals for values of (i) Zn root concentration and (ii) Cd shoot
and root concentrations: in these three cases, increasing soil metal concentrations
led to significantly higher values of their respective metal tissue concentrations
(Figure 6.1). However, according to two-way ANOVA, there was a significant
interaction between both soil metals for values of shoot Zn concentration. In soils
polluted with 250 and 500 mg Zn kg-1 DW, shoot Zn concentration was
significantly highest in the presence of 250 mg Cd kg-1 DW (Figure 6.1). Highest
values of shoot Zn and Cd concentration were obtained in treatment 500-250 (i.e., 8,211 and 1,763 mg kg-1 DW shoot for Zn and Cd, respectively). Finally, metal
concentrations were much higher in shoots than in roots (Figure 6.1).
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Figure 6.1: Shoot and root metal concentrations in T. caerulescens plants, subjected to different Zn (first value) and Cd (second value) soil concentrations (mg kg-1 DW), at the end of the
phytoextraction experiment. Bars with different letters are significantly different (P<0.05 or lower) according to Tukey Kramer-test (statistics are shown only when, according to two-way ANOVA, a significant interaction was found between both soil metals). Mean values (n = 4) ± standard errors.
Regarding translocation factors (TF = shoot metal concentration/root metal
concentration) (Table 6.2), a significant interaction was observed between both soil
metals. Highest TF values for Zn were found in treatment 250-250 (TF = 11.1). By
contrast, highest TF values for Cd were found in treatment 1,000-250 (TF = 3.8).
As far as total amount of metal phytoextracted from soil is concerned (shoot
biomass x shoot metal concentration) (Table 6.2), a significant interaction was
found between both soil metals for values of phytoextracted Zn and Cd. Highest
values of Zn phytoextracted from soil were observed in treatment 1,000-250 (43.4
mg). Highest values of Cd phytoextracted from soil were found in treatment 250-
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250 (10.6 mg). This treatment 250-250 achieved highest values of T. caerulescens shoot biomass.
Table 6.2: Shoot biomass (g DW tissue), translocation factors (TF), amount of metal
phytoextracted from soil (μg), and bioconcentration factors (BF) in T. caerulescens plants, subjected to different Zn (first value) and Cd (second value) soil concentrations (mg kg-1 DW) at the end of the phytoextraction experiment. Values followed with different letters are significantly different
(P<0.05 or lower) according to Tukey Kramer-test. Mean values (n = 4) ± standard errors.
TF Metal phytoextracted BF
Shoot biomass Zn Cd Zn Cd Zn Cd
250-0 3.61 ± 0.21a 4.2 ± 0.3a - 9310 ± 705a 4 ± 0a 8.4 ± 0.6abc -
250-50 5.59 ± 0.42ab 5.1 ± 1.0abc 0.9 ± 0.1a 16204 ± 2610ab 1236 ± 148a 9.8 ± 0.9ab 5.5 ± 0.4a
250-250 7.62 ± 0.88b 11.1 ± 0.6d 1.6 ± 0.1ab 38972 ± 5774cd 10572 ± 1456b 17.4 ± 0.8d 8.0 ± 0.4a
500-0 5.89 ± 0.95ab 3.5 ± 0.2a - 18281 ± 2964ab 13 ± 3a 6 ± 0.5ac -
500-50 5.69 ± 0.54ab 7.4 ± 0.9bc 2.4 ± 0.2ab 27011 ± 2895bcd 1610 ± 114ac 10.1 ± 1.1b 7.2 ± 0.3a
500-250 3.63 ± 0.23a 7.9 ± 0.4b 1.9 ± 0.2ab 28030 ± 2531bcd 4935 ± 734cd 15.2 ± 0.7d 7.1 ± 0.8a
1,000-0 4.83 ± 0.28ab 3.5 ± 0.2a - 25903 ± 1031abc 6 ± 1a 5.4 ± 0.3c -
1,000-50 4.57 ± 0.18a 4.9 ± 0.5abc 1.3 ± 0.1ab 31777 ± 3422bcd 1368 ± 109ac 7.8 ± 0.8abc 7.5 ± 0.6a
1,000-250 6.35 ± 0.48ab 4.5 ± 0.6ac 3.8 ± 1.3b 43387 ± 3197d 8560 ± 1133bd 8.3 ± 0.2abc 8.0 ± 0.9a
CaCl2-extractable metal concentrations in soil are shown in Table 6.3. A
significant interaction between both soil metals was observed for values of CaCl2-
extractable Zn and Cd soil concentration. CaCl2-extractable Zn concentrations
tended to decrease in treatment 1000-250, as compared to treatments 1000-0 and
1000-50 (Table 6.3). Instead, CaCl2-extractable Cd concentrations were significantly
higher in the presence of 500 or 1,000 mg Zn kg-1 DW soil (in planted pots, only
with 500 mg Zn kg-1 DW soil). In many treatments, planted soils showed
significantly lower values of CaCl2-extractable metal concentrations than
corresponding unplanted soils (Table 6.3): a 18 and 24% reduction (planted versus unplanted) in CaCl2-extractable Cd was observed in the presence of 50 and 250 mg
Cd kg-1 DW soil, respectively; a 9, 22 and 17% reduction (planted versus unplanted)
in CaCl2-extractable Zn was observed in the presence of 250, 500 and 1,000 mg Zn
kg-1 DW soil, respectively. A reduction, though less pronounced, between planted
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and unplanted pots was also observed regarding total soil metal concentrations at
the end of the phytoextraction experiment (data not shown): a 3 and 18% reduction
(planted versus unplanted) in total Cd was observed in the presence of 50 and 250
mg Cd kg-1 DW soil, respectively; a 4, 9 and 14% reduction (planted versus unplanted) in total Zn was observed in the presence of 250, 500 and 1,000 mg Zn
kg-1 DW soil, respectively.
Table 6.3: CaCl2-extractable metal (Zn and Cd) concentrations in soils polluted with different Zn (first value) and Cd (second value) concentrations (mg kg-1 DW) at the end of the phytoextraction
experiment. Values followed with different letters are significantly different (P<0.05 or lower) according to Tukey Kramer-test (lower case letters: among unplanted treatments; upper case letters: among planted treatments). Asterisks represent significant differences (P<0.05 or lower) between
planted and unplanted soils. Mean values (n = 4) ± standard errors.
Zn Cd
(mg kg-1 DW soil)
250-0 116 ± 2a* 0 ± 0a
250-50 111 ± 2a* 19 ± 0ab*
250-250 99 ± 4a* 77 ± 3c*
500-0 201 ± 1b* 0 ± 0a*
500-50 212 ± 8b* 20 ± 0b*
500-250 189 ± 1b 106 ± 1d
1,000-0 395 ± 3c 1 ± 0a*
1,000-50 405 ± 9c* 22 ± 0b*
Unp
lant
ed
1,000-250 353 ± 17d* 122 ± 10d*
250-0 95 ± 2AB 0 ± 0A
250-50 79 ± 2A 16 ± 0B
250-250 79 ± 3A 61 ± 1C
500-0 167 ± 3BC 0 ± 0A
500-50 162 ± 4ABC 17 ± 0B
500-250 224 ± 43C 96 ± 5D
1,000-0 390 ± 11D 0 ± 0A
1,000-50 329 ± 10D 17 ± 1B
Plan
ted
1,000-250 232 ± 10C 76 ± 6C
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With regard to bioconcentration factors (BF = shoot metal concentration/soil
metal concentration) (Table 6.2), there was a significant interaction between both
soil metals for BF values of Zn and Cd. BF values for Zn tended to decrease with
increasing soil Zn concentrations and decreasing soil Cd concentrations (Table 6.2).
Highest BF values for Zn were found in treatment 250-250 (BF = 17.4). No
significant differences between treatments were found concerning BF values for Cd
(Table 6.2).
6.4.2 Soil physicochemical and microbial parameters
Table 6.4 shows the values of soil basal respiration, SIR and QR at the end of
the phytoextraction experiment. For both planted and unplanted pots, a two-way
ANOVA indicated a significant interaction between both soil metals for values of
basal respiration, SIR and QR, except for basal respiration in unplanted pots. In
these unplanted pots, basal respiration decreased significantly with increasing soil
Zn concentrations (mean values ± SE were: 1.26 ± 0.05, 0.90 ± 0.01 and 0.50 ±
0.03 μg C g-1 h-1 for soils with 250, 500 and 1,000 mg Zn kg-1 DW, respectively),
while soil Cd concentrations did not have any effect on such parameter. In planted
pots, in general, values of basal respiration tended to decrease with increasing soil
metal concentrations. Values of basal respiration were, in general, higher in planted
than unplanted soils.
In unplanted pots, treatments 250-50 and 250-250 showed highest values of
SIR (Table 6.4). On the contrary, in planted pots, no significant differences were
found between treatments regarding SIR. Values of SIR were always higher in
planted than unplanted soils, though differences were rarely statistically significant.
In respect to QR (Table 6.4), highest values were found in unplanted pots
under treatment 250-0 (lowest values were found in unplanted pots under
treatments 1,000-0 and 1,000-250). In planted pots, values of QR were significantly
highest under treatment 250-0.
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Table 6.4: Soil basal respiration, substrate-induced respiration (SIR) and microbial respiration quotient (QR) in soils polluted with different Zn (first value) and Cd (second value) concentrations (mg kg-1 DW) at the end of the phytoextraction experiment. Values followed with different letters are significantly different (P<0.05 or lower) according to Tukey Kramer-test (statistics are shown only when, according to two-way ANOVA, a significant interaction was found between both soil
metals). Lower case letters: among unplanted treatments; upper case letters: among planted treatments. Asterisks represent significant differences (P<0.05 or lower) between planted and
unplanted soils. Mean values (n = 4) ± standard errors.
Basal respiration SIR QR (μg C g-1 DW soil h-1)
250-0 1.33 ± 0.07 3.38 ± 0.31a 0.41 ± 0.06a
250-50 1.19 ± 0.08 6.78 ± 0.17b* 0.18 ± 0.01bc
250-250 1.27 ± 0.11 6.03 ± 0.32bc* 0.21 ± 0.01bc*
500-0 0.88 ± 0.03 2.96 ± 0.49a 0.34 ± 0.07ab
500-50 0.87 ± 0.01* 3.78 ± 0.68ac 0.26 ± 0.05abc
500-250 0.95 ± 0.01 4.93 ± 0.26abc 0.19 ± 0.01bc
1,000-0 0.55 ± 0.07* 4.79 ± 0.08abc 0.12 ± 0.01c
1,000-50 0.55 ± 0.04* 4.32 ± 0.76ac 0.14 ± 0.02bc
Unp
lant
ed
1,000-250 0.40 ± 0.02* 3.75 ± 0.39ac* 0.11 ± 0.02c
250-0 1.51 ± 0.08A 4.18 ± 0.44A 0.39 ± 0.07A
250-50 1.21 ± 0.03B 8.46 ± 0.47A 0.15 ± 0.01B
250-250 0.97 ± 0.01CD 8.08 ± 0.08A 0.12 ± 0.00B
500-0 0.95 ± 0.02CD 6.85 ± 1.40A 0.16 ± 0.03B
500-50 1.23 ± 0.03B 6.55 ± 1.22A 0.21 ± 0.03B
500-250 0.81 ± 0.06DE 5.94 ± 0.67A 0.14 ± 0.02B
1,000-0 1.06 ± 0.03BC 5.92 ± 0.68A 0.19 ± 0.03B
1,000-50 0.85 ± 0.02CE 5.47 ± 0.17A 0.16 ± 0.01B
Plan
ted
1,000-250 0.69 ± 0.05E 7.62 ± 0.92A 0.10 ± 0.01B
With regard to gene copy quantification from real-time PCR (Table 6.5), a
significant interaction was observed between both soil metals in unplanted pots. In
unplanted pots, abundance of total bacteria gene fragments was highest under
treatment 250-50 and lowest under treatment 500-0. In planted pots, soil Zn
concentration did not have any significant effect on gene abundance of total
bacteria. On the contrary, in these planted pots, the presence of 50 and 250 mg Cd
kg-1 DW soil led to significantly lower values of total bacteria gene abundance as
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compared to soils lacking Cd: 132,514 ± 24,641 x 103 copies g-1 for soils non-
polluted with Cd versus 71,370 ± 8,031 copies g-1 for soils polluted with Cd (mean
value of soils polluted with 50 and 250 mg kg-1 DW). For chitin-degrading bacteria,
in unplanted pots, treatment 250-50 showed highest values of gene copies
(treatments 500-0 and 1,000-0 showed lowest values). In planted pots, no significant
differences were observed regarding abundance of chitin-degrading gene copies
between metal treatments. Finally, concerning abundance of ammonia-oxidizing
gene copies, in unplanted pots, again treatment 250-50 showed highest values
(treatment 1,000-250 showed lowest values). In planted pots, at 1,000 mg Zn kg-1
DW soil, ammonia-oxidizing gene copies decreased compared to that observed at
250 mg Zn kg-1 DW (8.9 ± 2.4 versus 17.2 ± 2.1 x 103 copies g-1). Similarly, in these
planted pots, at 250 mg Cd kg-1 DW soil, ammonia-oxidizing gene fragment
abundance decreased compared to that observed in the absence of Cd (10.8 ± 1.7
versus 18.8 ± 2.5 x 103 copies g-1). In respect to differences between planted and
unplanted soils regarding bacterial gene abundances, no clear patterns were
observed (Table 6.5). However, as a whole, planted soils showed a 58% higher total
bacterial gene abundance than unplanted soils.
Concerning the experiment on the capacity of the phytoremediated soil to
support M. sativa growth at the end of the phytoextraction study, it was found that
alfalfa growth was highly inhibited by the presence of both heavy metals: actually,
M. sativa growth was only observed in treatments 250-0, 250-50 and 500-0. In
previously unplanted soils, the following values of alfalfa shoot biomass were found
for treatment 250-0, 250-50 and 500-0, respectively: 1.80 ± 0.33, 0.14 ± 0.04 and
0.16 ± 0.05 g DW shoot. Instead, in previously planted (with T. caerulescens) soils, the
following values of alfalfa shoot biomass were found for treatments 250-0, 250-50
and 500-0, respectively: 0.88 ± 0.21, 0.18 ± 0.06 and 0.21 ± 0.10 g DW shoot.
Under treatment 250-0, values of alfalfa shoot biomass were 49% lower in soils
previously planted with T. caerulescens versus previously unplanted pots (on the
contrary, under treatment 250-50 and 500-0, values of alfalfa shoot biomass were 26
and 34% higher, respectively, in previously planted versus unplanted).
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Table 6.5: Total bacteria, group A bacterial chitinases and ammonia monooxygenase gene abundance in soils polluted with different Zn (first value) and Cd (second value) concentrations
(mg kg-1 DW) at the end of the phytoextraction experiment. Values followed with different letters are significantly different (P<0.05 or lower) according to Tukey Kramer-test (statistics are shown only when, according to two-way ANOVA, a significant interaction was found between both soil
metals). Asterisks represent significant differences (P<0.05 or lower) between planted and unplanted soils. Mean values (n = 4) ± standard errors.
Total bacteria Chitinase group A AmoA (103 copies g-1 DW soil)
250-0 124360 ± 33241ab 135 ± 23a 19.0 ± 0.8ab
250-50 137622 ± 54455a 253 ± 7b* 36.9 ± 1.3c*
250-250 22795 ± 6225ab 157 ± 26ab 16.7 ± 2.4ab
500-0 10247 ± 448b* 112 ± 25a 13.6 ± 0.8abd
500-50 64639 ± 18855ab 147 ± 20ab 16.9 ± 1.8ab
500-250 38897 ± 6734ab 156 ± 19ab 19.1 ± 1.1ab
1,000-0 31138 ± 5089ab* 110 ± 9a* 23.3 ± 4.8a
1,000-50 33488 ± 564ab 160 ± 22ab 8.2 ± 1.5bd
Unp
lant
ed
1,000-250 59259 ± 9644ab 212 ± 12ab* 3.1 ± 0.8d
250-0 205862 ± 49911 179 ± 14 19.4 ± 4.4
250-50 63122 ± 7632 118 ± 29 18.4 ± 3.3
250-250 66442 ± 20075 161 ± 24 13.7 ± 2.1
500-0 102297 ± 29487 151 ± 30 23.8 ± 4.5
500-50 49229 ± 6125 180 ± 13 13.3 ± 1.3
500-250 44446 ± 13238 102 ± 27 11.6 ± 3.9
1,000-0 89383 ± 8123 158 ± 8 15.6 ± 5.5
1,000-50 102339 ± 25350 166 ± 32 4.1 ± 0.5
Plan
ted
1,000-250 102643 ± 13926 156 ± 11 7.0 ± 1.2
The application of PCA to all soil physicochemical and microbial parameters
determined here (Figure 6.2) separated soils subjected to different levels of Zn
pollution along axis 1, which accounted for 29% of the variance. Soils treated with
250 mg Zn kg-1 DW showed higher values of nitrates content, alfalfa growth,
ammonia monooxygenase gene abundance, extractable P content and basal
respiration. These five parameters were positively correlated with each other, and
negatively with values of soil pH. No clear pattern was observed regarding the
possible correlation between soil Cd concentration and physicochemical or
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microbial parameters. On the other hand, planted and unplanted pots also appeared
separated (Figure 6.2). Planted pots showed higher values of SIR and total bacterial
gene fragments and group A bacterial chitinase gene abundances, and lower values
of total N and K+ content.
Figure 6.2: Principal component analysis of soil physicochemical and microbial properties in planted (P) and unplanted (UP) soils, polluted with different Zn (first value) and Cd (second value) concentrations, at the end of the phytoextraction experiment. Axis 1 and Axis 2 account for 29 and
17% of the variance, respectively. SIR: substrate-induced respiration; Chit: group a bacterial chitinase gene abundance; Bac: total bacteria gene abundance; OM: organic matter content; BR:
basal respiration; P: extractable phosphorus content; Amo: ammonia monooxygenase gene abundance; Ms: Medicago sativa growth; NO3: nitrates content; N: total N content; K: potassium
content.
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Regarding DGGE results, out of all treatment pairs, the pairs 250-0-
unplanted/250-0-planted and 1,000-250-unplanted/1,000-250-planted showed the
highest values of the Jaccard index (CJ = 0.64 and CJ = 0.66, respectively). The
remaining values of the Jaccard index ranged between 0.40 and 0.46. According to
the RDA, soil heavy metal concentration and T. caerulescens shoot biomass explained
41% of the total inertia present in the DGGE data. After partialling out the
influence of selected sets of co-variables, most of the explained variation in DGGE
data was attributable to changes in soil metal concentration (31.7%), and just 7.0%
could be attributed to changes in T. caerulescens shoot biomass. In addition, another
RDA was performed to identify the soil physicochemical and microbial properties
that had the most significant influence on bacterial community structure. The soil
properties that yielded P<0.05 after forward selection were: basal respiration
(P<0.001) and pH (P<0.008), which positively influenced non-polluted (250-0) and
metal polluted (1,000-250) soils, respectively.
Table 6.6: Genes detected in the Geochip functional genes array, together with the variation partitioning obtained by RDA, in planted (P) and unplanted (UP) soils polluted with different Zn (first value) and Cd (second value) concentrations, at the end of the phytoextraction experiment.
Numbers shown below ‘Explaining factors’ quantify the effects of each set of explaining factors (T. caerulescens shoot biomass and soil metal concentration), after partialling out the effect of the other
variables, expressed as a percent contribution to the total inertia in the response variable.
N-cycle C-cycle Sulphate Heavy metals
Organic compounds TOTAL
250-0-UP 19 18 5 22 44 108
250-0-P 31 41 9 54 75 210
1,000-250-UP 63 74 17 94 160 408
1,000-250-P 85 105 26 118 198 532
% Explained 54.6 63.3 55.8 60.9 59.3
% Unexplained 45.4 36.7 44.2 39.1 40.7
Explaining factors
Shoot biomass 15.4 15.4 16.1 14.7 14.7 Soil metal
concentration 39.9 44.0 35.2 46.7 41.6
Interaction 0.0 3.9 4.5 0.0 3.0
Finally, Table 6.6 shows a summary of the genes detected in the Geochip for
each treatment. In every gene category, more genes were detected in polluted
(1,000-250) than non-polluted (250-0) soils. Besides, gene detection was higher in
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planted versus unplanted soils. The RDA explained a high percentage (above 54%) of
the total inertia present in the Geochip data. After partialling out the influence of
selected covariables (i.e., T. caerulescens shoot biomass and metal concentration), most
of the explained variation was due to changes in soil metal concentration. Indeed,
for every gene category, soil metal concentration explained from 35.2 to 46.7% of
data variation, while T. caerulescens shoot biomass explained from 14.7 to 16.1%.
Out of the twelve Zn and/or Cd resistance genes detected, three belonged to
Staphylococcus sp. All of them were present in metal-polluted (1,000-250) planted soils,
while only seven of them were found in metal-polluted (1,000-250) unplanted soils
(five of them were present in 250-0 planted soils, and just one in these non-polluted
unplanted soils).
Using binary presence-absence data, the number of different gene variants
detected were studied to gain insight into possible functional redundancy. The gene
families that were well-represented (with a minimum of 5 gene variants) and that
showed a significant (P<0.05) difference between treatments according to ANOVA
are shown in Figure 6.3. As a general pattern, both metal polluted (1,000-250) and
planted soils showed a larger number of gene variants than non-polluted and
unplanted soils, respectively.
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Figure 6.3: Number of gene variants detected in the Geochip functional gene array in planted (P) and unplanted (UP) soils, polluted with different Zn (first value) and Cd (second value)
concentrations, at the end of the phytoextraction experiment. Only those gene variants well-represented (with a minimum of 5 gene variants) and showing significant differences (P <0.05)
among treatments, according to ANOVA, are presented.
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RDAs were performed for each gene category in order to identify the soil
physicochemical and microbial properties that had the most significant influence on
functional genes. The soil properties that yielded P<0.05 after forward selection
were SIR and K+ content for the C-cycle, sulphate reduction and organic
contaminant degradation gene categories, which positively influenced 1,000-250
planted and unplanted soils, respectively. On the other hand, SIR and nitrates
content yielded P< 0.05 after forward selection for the N-cycle and metal reduction
and resistance gene categories, and positively influenced 1,000-250 planted and 250-
0 planted/unplanted soils, respectively. Finally, no significant correlations were
found between abundandes of ammonia monooxygenase gene and group A
bacterial chitinases estimated through real-time PCR and their respective
abundances obtained in the Geochip microarray.
6.5 Discussion
6.5.1 Metal phytoextraction
Our T. caerulescens Lanestosa ecotype proved to have a great capacity for Zn
and Cd hyperaccumulation. In fact, shoot Cd concentrations reached values above
the hyperacumulation threshold of 100 mg Cd kg-1 DW (Baker et al., 2000). These
results are in accordance with those previously reported by us for this very same
ecotype (Epelde et al., 2008a). Besides, as reflected by the values of the plant
physiological parameters studied here, T. caerulescens plants did not show any
phytoxicity symptoms in the presence of high levels of metals. Indeed, our results
indicate that T. caerulescens Lanestosa ecotype has an elevated tolerance to Cd, a
heavy metal for which few hyperaccumulator species are known (Baker et al., 2000).
Interestingly, at a soil Zn concentration of 250 and 500 mg kg-1 DW, the presence
of 250 mg Cd kg-1 DW soil significantly stimulated Zn shoot accumulation (and also
Zn translocation at 250 mg Zn kg-1 DW).
Translocation factors for both metals were >1, as it is usually the case with
hyperaccumulators (McGrath et al., 2002). On the other hand, according to Zhao et
al. (2003), for metal phytoextraction, bioconcentration factors are more important
than shoot metal concentrations. In the present study, T. caerulescens plants showed
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most promising bioconcentration factors for Cd (up to 8.0) and Zn (up to 17.4),
taking into account that 10 is the threshold value reported for a phytoextraction
process to be considered feasible (McGrath et al., 2006).
6.5.2 Impact of metal pollution on soil properties
In this study, it was found that the lower the soil Zn concentration, the higher
the values of alfalfa growth (i.e., capacity of the phytoremediated soil to support
plant growth), soil basal respiration and abundance of ammonia-oxidizer genes
(Figure 6.2). On the other hand, these three parameters were negatively correlated
with soil pH. By contrast, in a study by Wang et al. (2006), a positive correlation
between soil biological activities and pH was found. Likewise, in our study, the
abundance of ammonia-oxidizer genes was positively correlated with soil nitrates
content. The amoA gene codes the α subunit of ammonia monooxygenase (AMO),
the key enzyme of all aerobic ammonia-oxidizing bacteria: this enzyme catalyzes the
rate limiting process of nitrification, i.e. the oxidation of ammonia to hydroxylamine
(Yuan et al., 2005).
Biological parameters, especially those related to the activity, size and diversity
of soil microbial communities, are becoming increasingly used to assess the impact
of pollutants on soil functioning due to their sensitivity, rapid response and capacity
to provide information that integrates many environmental factors (Hernández-
Allica et al., 2006a; Epelde et al., 2008a, b). Soil basal respiration, an indicator of the
overall activity of microorganisms involved in OM decomposition (Anderson,
1982), has been shown to be negatively affected by the presence of heavy metals
(Duxbury, 1985; Kandeler et al., 1996). In our study, Zn pollution led to decreased
levels of both soil basal respiration and SIR values (an indicator of potentially active
microbial biomass). Also, under some treatments, a metal-induced reduction in total
bacterial gene abundance was also observed: Cd pollution (50 and 250 mg Cd kg-1
DW soil) negatively affected the abundance of total bacterial genes in planted pots;
highest levels of metal pollution (1,000 mg Zn kg-1 DW and 250 mg Cd kg-1 DW)
led to lower values of abundance of ammonia-oxidizer genes. Similarly, Mertens et
al. (2006) reported that ammonia-oxidizer populations were sensitive to increasing
Zn concentrations in artificially contaminated soils. This metal-induced inhibition is
6. impact of metal pollution and Thlaspi caerulescens phytoextraction on soil microbial communities
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also reflected in the values of QR, a parameter frequently used to assess the effect of
disturbances on the soil ecosystem (Anderson and Domsch, 1985; Insam and
Domsh, 1988).
In soils polluted with high levels of metals (treatment 1,000-250), both Cd
and Zn had a clear effect on the structural genetic diversity of soil bacteria. This is in
accordance with other studies which also detected metal-induced shifts in the soil
bacterial community using DGGE and other molecular techniques (Gremion et al.,
2004; Sandaa et al., 1999a).
Functional diversity, as determined by the GeoChip, was also most affected by
the presence of heavy metals. Unlike soil properties related to microbial activity or
biomass, functional diversity (number of genes detected), regardless of gene
category, increased as a result of metal pollution. Similarly, functional redundancy
appeared higher as a response to metal pollution.
No correlations were found between real-time PCR data and the respective
values of gene abundance detected by the Geochip. This could be due to the rolling
circle amplification carried out before labeling and hybridization steps. Most
important, any quantitative interpretation of microarray studies requiring an
intermediate PCR amplification should be treated with caution, as results are
susceptible to the same biases associated with any end-point PCR protocol
(Reysenbach et al., 1992; Smith and Osborn, 2009). In addition, in our study, real-
time PCR assays rely on different priming sites than those used for probing on the
array. Furthermore, probe signals were a summation of signals derived from
multiple specific signals within a gene family, whereas real-time PCR results were
generated by gene-family specific primers. Another explanation is that both
methods rely on extant sequence data for primer and probe design and may either
miss some members of the target gene families or overlap with related gene families
(Yergeau et al., 2007b).
Finally, regarding the M. sativa productivity experiment carried out to
determine the capacity of the phytoremediated soil to support plant growth at the
end of the phytoextraction experiment, it was found that Zn and Cd levels were still
very toxic for this plant species (alfalfa growth was only observed under treatments
250-0, 250-50 and 500-0; much higher growth was found under 250-0 as compared
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to the other two treatments). Though plant bioassays are certainly a most useful tool
to assess soil toxicity, its response depends on a variety of factors such as the
species used, type and levels of contamination, edaphic and environmental factors
of the assay, etc.
6.5.3 Effect of T. caerulescens growth and metal phytoextraction on soil properties
T. caerulescens growth and metal phytoextraction increased the values of soil
basal respiration, SIR and total bacterial gene abundance. As compared to bare soil,
vegetated soils commonly have higher rates of microbial biomass and activity as a
result of the improvement in soil conditions due to the presence of greater
quantities of organic compounds and surfaces for microbial colonization (Grayston
et al., 1997). In similar phytoextraction experiments with T. caerulescens plants, we
previoulsy found higher values of microbial activity in rhizosphere versus non-
rhizosphere soil (Hernández-Allica et al., 2006a; Epelde et al., 2008a).
Regarding the M. sativa productivity experiment, under treatment 250-0, M. sativa growth was lower in previously planted soils, probably due to the reduction in
soil nutrient levels caused by T. caerulescens growth. However, under treatments 250-
50 and 500-0, M. sativa growth was higher in previously planted soils, most likely
owing to a positive effect derived from the reduction in soil metal concentrations
caused by T. caerulescens metal uptake, which compensates the negative effect
produced from decreased nutrient levels.
Interestingly, the PCA separated planted and unplanted treatments: planted
treatments showed higher values of microbial biomass data which were all positively
correlated among each other despite targeting different portions of the soil
microbial community (e.g., SIR, an indicator of potentially active microbial biomass,
was positively correlated with total bacteria gene abundance calculated by real-time
PCR). The lower values of total N and extractable K+ observed in planted versus unplanted soils are most likely due to plant uptake.
As far as structural genetic bacterial diversity, no major differences were found
between planted and unplanted soils. Similarly, in a phytoremediation experiment
6. impact of metal pollution and Thlaspi caerulescens phytoextraction on soil microbial communities
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with poplars, Frey et al. (2008) reported that DGGE patterns of Pseudomonas populations of unplanted and planted treatments were similar. On the contrary,
Wang et al. (2008) found differences in bacterial community composition (measured
also with DGGE) between Elsholtzia splendens and Trifolium repens planted and
unplanted Cu polluted soils. On the other hand, although the presence of plants
explained a low percentage of the variability of the Geochip data, the number of
genes detected and the functional redundancy in planted soils were higher for every
gene category, as compared to unplanted soils.
The abundance of Zn and/or Cd resistance genes detected was higher in T. caerulescens planted versus unplanted soils, even in the absence of metals. There are
quite a few reports on the effects of metals on microbial communities in bulk soils
(Brim et al., 1999; Sandaa et al., 1999b), but the information on the microbial
community present in the rhizosphere of heavy metal-accumulating plants is still
scarce. In particular, it is unclear if heavy metal-accumulating plants selectively affect
bacterial community composition in heavy metal-contaminated soils, showing
communities in the root-zone (Kozdrój and van Elsas, 2001) that may not be
dominant or active in unplanted bulk soil. In this respect, Gremion et al. (2003)
studied a T. caerulescens rhizosphere soil library derived from rRNA, finding out that
Actinobacteria (and more specifically Rubrobacteria) might be a dominating part of the
metabolically active bacteria in the rhizosphere of this hyperaccumulator.
6.6 Conclusions
The Lanestosa ecotype of T. caerulescens confirmed its great potential for Zn
and Cd phytoextraction: highest values of Zn (43.4 mg) and Cd (10.6 mg)
phytoextracted from soil were observed under treatment 1,000-250 and 250-250,
respectively. Translocation factors for both metals were >1. T. caerulescens plants
showed most promising bioconcentration factors: up to 17.4 for Zn and 8.0 for Cd.
Zn pollution led to decreased levels of both soil basal respiration and SIR.
Also, under some treatments, a metal-induced reduction in total bacterial gene
abundance was observed. In soils polluted with high levels of metals, both Cd and
Zn had a clear effect on the structural genetic diversity of soil bacteria. Functional
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diversity (number of genes detected) and redundancy, regardless of gene category,
increased as a result of metal pollution. T. caerulescens growth and metal
phytoextraction increased the values of soil basal respiration, SIR and total bacterial
gene abundance. As far as structural genetic diversity of soil bacteria is concerned,
no major differences were found between planted and unplanted soils. On the other
hand, although the presence of plants explained a low percentage of the variability
of the Geochip data, the number of genes detected and the functional redundancy
in planted soils were higher for every gene category, as compared to unplanted soils.
The abundance of Zn and/or Cd resistance genes detected was higher in T. caerulescens planted versus unplanted soils, even in the absence of metals. Certainly,
more efforts are needed to deepen into the still poorly understood plant-microbe
interactions that occur in metal polluted soils.
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7. SOIL MICROBIAL COMMUNITY AS BIOINDICATOR OF THE RECOVERY OF SOIL FUNCTIONING DERIVED FROM METAL
PHYTOEXTRACTION WITH SORGHUM
Epelde et al., published in Soil Biology and Biochemistry (in press, doi:10.1016/j.soilbio.2008.04.001)
7.1 Abstract
A three-month microcosm study was carried out in order to evaluate: (i) the
capacity of sorghum plants to phytoextract Cd (50 mg kg-1) and Zn (1000 mg kg-1)
from artificially polluted soil; and (ii) the possibility of biomonitoring the efficiency
of phytoremediation using parameters related to the size, activity and functional
diversity of the soil microbial community. Apart from plant and soil (total and
bioavailable) metal concentrations, the following parameters were determined: soil
physicochemical properties (pH, OM content, electrical conductivity, total N,
extractable P and K+), dehydrogenase activity, basal and substrate-induced
respiration (with glucose and a model rhizodeposit solution, both adjusted to 800
mg C kg-1 DW soil and 45.2 mg N kg-1 DW soil), microbial respiration quotient,
functional diversity through community level physiological profiles and, finally, seed
germination toxicity tests with Lepidium sativum. Sorghum plants were highly tolerant
to metal pollution and capable of reaching high biomass values in the presence of
metals. In the first two harvests, values of shoot Cd concentrations were higher
than 100 mg Cd kg-1 DW, the threshold value for hyperaccumulators. Nonetheless,
in the third harvest, the bioconcentration factor was 1.34 and 0.35 for Cd and Zn,
respectively, well below the threshold value of 10 considered for a phytoextraction
process to be feasible. In general, microbial parameters showed lower values in
metal polluted than in control non-polluted soils, and higher values in planted than
in control unplanted pots. As a result of the phytoextraction process, which includes
both plant growth and metal phytoextraction, the functioning of the
phytoremediated soil, as reflected by the values of the different microbial
parameters here determined, was restored. Most importantly, although the
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phytoextracted soil recovered its functionally, it was still more phytotoxic than the
control non-polluted soil.
7.2 Introduction
Phytoextraction, or the utilization of plants to transport and concentrate
metals from the soil into the harvestable parts of roots and above-ground shoots
(Kumar et al., 1995), appears a promising, cost-effective technology for the
remediation of metal polluted soils. Although hyperaccumulators (i.e., plants that
have the capacity to accumulate in their aerial tissues large quantities of metals from
the surrounding soil) have been extensively studied for metal phytoextraction, their
deployment for the phytoremediation of metal polluted soils presents certain
constraints, namely that hyperaccumulating plants are, in general, relatively small,
have slow rates of biomass production, and lack any established cultivation, pest
management or harvesting practices (Wenzel et al., 1999). Consequently, nowadays,
fast-growing, high biomass crop plant species that accumulate moderate levels of
metals in their shoots are actively being tested for phytoextraction (Hernández-
Allica et al., 2007). After all, in some cases, a greater shoot biomass has been
reported to more than compensate for a lower shoot metal concentration (Ebbs and
Kochian, 1997, 1998).
To avoid the inconvenience of having to sow again the phytoextracting plant
after each harvest, an interesting approach is to use perennial plant species, such as
sorghum, able to regrow in the polluted soil after harvesting, thus allowing for
repeated cuttings. Sorghum plants have been reported to accumulate high amounts
of metals in their shoots when grown hydroponically (Hernández-Allica et al., 2007).
Interestingly, cropping of sorghum has been predicted to increase under climate
change due to its drought and heat tolerance (Tuck et al., 2006). In addition,
sorghum plants are multipurpose cereals of potential interests for several non-food
uses, especially as energy crops for the production of bioethanol (Barbanti et al.,
2006). In order to circumvent the recent food versus biofuel debate, it would be
practical to use polluted soils, not suitable for food crops, for energy biomass
production. Furthermore, obtaining products with economic value from plants used
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in the cleanup of polluted soils would be an additional benefit to phytoremediation,
which could indeed help sustain its long-term use (Bañuelos, 2006).
The ultimate goal of any soil remediation process must be not only to remove
the contaminant(s) from the polluted site but, most importantly, to restore the
capacity of the soil to perform or function according to its potential (i.e., its health)
(Hernández-Allica et al., 2006a). Regarding the recovery of soil health/functioning
derived from the phytoextraction process, an ideal target should be to return to the
conditions of a valid control soil (i.e., a vegetated, unpolluted soil of similar
physicochemical properties and subjected to the same edaphoclimatic conditions).
Hence, indicators of soil health are needed to properly assess the efficiency of
a phytoextraction process. Biological indicators of soil health, especially those
related to the size, activity and diversity of soil microbial communities, are becoming
increasingly used due to their sensitivity and capacity to provide information that
integrates many environmental factors (Alkorta et al., 2003b).
Dehydrogenase activity, an intracellular process that occurs in every viable
microbial cell, is used to determine overall microbiological activity of soil
(Nannipieri et al., 2002). Soil microbial activity can also be measured through the
determination of soil basal respiration (ISO 16072 Norm). In turn, soil microbial
functional diversity can be determined through the utilization of community level
physiological profiles (CLPPs) which reflect the potential of the cultivable portion
of the heterotrophic microbial community to respond to carbon substrates (Bending
et al., 2004). Substrate (glucose)-induced respiration (SIR) is a suitable indicator of
potentially active microbial biomass (ISO 17155 Norm). The addition of carbon
sources, other than glucose, commonly reported as constituents of root exudates
might convert SIR into an ecologically more relevant parameter for testing
rhizospheric microbial communities (Dedourge et al., 2004). The microbial
respiration quotient (QR = basal soil respiration to SIR ratio) has been used to assess
the effects of various perturbations in soil ecosystems (Insam and Domsh, 1988).
The aim of the current work was to evaluate the feasibility of using sorghum
plants for Cd and Zn phytoextraction. We hypothesized that bioindicators of soil
health might be valid monitoring tools to assess (i) the effect of metals on soil
functioning and (ii) the efficiency of the phytoextraction process (i.e., its capacity to
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restore soil functioning as a result of the phytoextraction process, which includes
both plant growth and metal phytoextraction).
7.3 Materials and methods
7.3.1 Soil characterization and experimental design
A three-month microcosm study was carried out with soil collected from the
top layer (0-30 cm) of a natural polyphita grassland located in Derio (Basque
Country, northern Spain). Immediately after collection, the soil was sieved to <4
mm, air-dried at 30 ºC, and subjected to physicochemical characterization according
to standard methods (MAPA, 1994). The soil was a clay loam, with a pH of 7.2, an
organic matter (OM) content of 4.92 %, a total nitrogen (N) content of 0.26 %, a
C/N ratio of 11, a phosphorus (P) content of 57.1 mg kg-1, and an electrical
conductivity (EC) of 0.18 dS m-1.
Subsequently, the soil was artificially contaminated with 50 mg Cd kg-1 dry
weight (DW) soil as CdCl2 and 1000 mg Zn kg-1 DW soil as ZnCl2. Metal polluted
and control non-polluted soils were stored in the dark for 1 month at 20 %
humidity and 20 ºC.
Afterwards, 10 kg of soil (on a DW basis) were placed in pots and fertilized
with 120 mg kg-1 of N, P and K+ before planting. For both metal polluted and
control soils, half of the pots were planted with 200 seeds of Sorghum bicolor x sudanense. Four different treatments (i.e., NM-UP: no metal, unplanted; NM-P: no
metal, planted; M-UP: metal, unplanted; M-P: metal, planted) were conducted in
quadruplicate. The plants were then allowed to grow for three months in a soft
polyethylene-covered greenhouse (Venlo-type) located in Derio at a latitude of 43º
17’ N, a longitude of 2º 52’ W, and an altitude of 65 m above sea-level. The climate
in this region is Atlantic temperate. Minimal temperature set points controlling air-
heating were 14/18 ºC night/day, and maximal temperature set points were 18/20
ºC night/day. Vent opening temperatures were 20/25 ºC night/day. During the
experiment, average temperature was 19/31 ºC night/day, average relative humidity
41/76 % night/day, and average photosynthetically active radiation 476 μmol
photon m-2 s-1. At the end of each month, sorghum plants were harvested by means
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of cutting at 2-3 cm of the soil surface. Throughout the experimental period, plants
were bottom watered periodically as needed.
7.3.2 Plant parameters
Shoots were harvested three times (at the end of each month). In turn, roots
were harvested only once, i.e. at the end of the experiment. After harvesting, fresh
weights (FW) of shoots and roots were recorded. Shoot and roots were washed
thoroughly with deionized water to remove soil particles. Subsequently, shoots and
roots were oven-dried at 70 ºC for 48 h and their dry weights recorded. Subsamples
(0.4 g) of dried plant tissue were digested with a mixture of HNO3/HClO4 (Zhao et
al., 1994) and Cd and Zn in the digest were determined using inductively coupled
plasma atomic emission spectrometry (ICP-AES, Varian).
7.3.3 Soil parameters
Soil was also sampled at the end of each month. For the first two harvests, a
soil core sampler (1 cm diameter; 20 cm height; 4 cores per pot which were then
pooled) was used. In the first two harvests, only three parameters were determined
in the soil samples: bioavailable metal fraction, dehydrogenase activity and CLPPs.
In the third harvest, all parameters described below were analysed. The selection of
the microbial parameters here determined was carried out following the
recommendations by Bloem et al. (2006).
For analysis of biological parameters, soils were sieved to <2 mm, and stored
at 4 ºC until analysis. Dehydrogenase activity was determined according to Taylor et
al. (2002). The analysis of CLPPs was carried out following Rodríguez-Loinaz et al.
(2007). The plates corresponding to an incubation time of 40 h were chosen for
calculations (at approximately this time, the highest rate of microbial growth was
observed in the Biolog EcoPlatesTM). Jaccard similarity index (CJ = a/a+b+c; where
a, the total number of substrates used in both treatments; b, the number of
substrates used only in the first treatment; and c, the number of substrates used only
in the second treatment) was calculated for each pair of treatments.
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Soil basal microbiological respiration was determined according to ISO 16072
Norm. SIR was determined with glucose following ISO 17155 Norm. Likewise, SIR
was measured using a model rhizodeposit solution as substrate (Griffiths et al.,
1999). For this model rhizodeposit solution, a stock solution of 50 mM fructose, 50
mM glucose, 50 mM sucrose, 25 mM succinic acid, 25 mM malic acid, 12.5 mM
arginine, 12.5 mM serine and 12.5 mM cysteine was prepared. The working solution
was obtained by diluting the stock solution with distilled water to give a rate of 800
mg C kg-1 DW soil and 45.2 mg N kg-1 DW soil. Equivalent rates of C and N were
added in the form of glucose and diammonium sulphate in the glucose-induced
respiration. The addition of these solutions to the soil brought the final soil
moisture content up to 80 % WHC. QR was calculated as the ratio between soil
basal respiration and glucose-induced respiration. For the calculation of QR, the
values of soil basal respiration obtained after 35 days of incubation were chosen to
avoid the priming effect due to sieving, humidification and incubation of soil
samples, processes that frequently speed up the mineralization of the most labile C
fractions. The values of SIR observed after 6 h of incubation were chosen so that a
valid estimate of the potentially active microbial biomass was obtained (i.e., a short
incubation time is used to register the respiration reaction of the initial microbial
population without invoking microbial growth) (Lin and Brookes, 1999).
Soil collected at the third harvest was used to carry out a germination test (to
assess soil phytotoxicity) with Lepidium sativum seeds following Zucconi et al. (1985).
Seed germination and root length in each plate were measured after 48 h. The
germination index (GI) after exposure to the soil extracts was calculated as follows
(Hoekstra et al., 2002):
GI (%) = 100 (SD/SB) (LD/LB)
where SD, SB = number of germinated seeds for sample and blank,
respectively, and LD, LB = average root length of seeds for sample and blank,
respectively.
For analysis of chemical parameters, soils were air-dried at 30 ºC for 48 h,
sieved to <2 mm, and stored at 4 ºC until analysis. Soil pH, OM content, total N,
electrical conductivity, and extractable P and K+ were measured according to
MAPA (1994). Total metal concentrations were determined using ICP-AES
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following aqua regia digestion (McGrath and Cunliffe, 1985). For the determination
of the bioavailable fraction of metals, pore water metal was extracted using 0.01 M
CaCl2 (Houba et al., 2000) and analyzed by ICP-AES.
7.3.4 Statistical analysis
Differences between treatments were analyzed (i.e., one-way ANOVAs) using
Microsoft Stat View Software (SAS Institute). Fisher´s PLSD-test was used to
establish the significance of the differences among means. Simple regression
analyses were performed to study the relationship between soil metal concentrations
and plant metal accumulation or soil biological parameters. Biolog EcoPlatesTM data
were used to perform a principal component analysis (PCA) treating each of the
substrates as a variable.
7.4 Results
7.4.1 Metal phytoextraction by sorghum plants
In the first two harvests, values of shoot biomass remained practically
constant for both metal polluted and control pots (Table 7.1). However, in the third
harvest, values of shoot biomass decreased by ca. 18 and 24 % in metal polluted and
control pots, respectively. Values of shoot biomass were always lower (on average,
ca. 22 % lower) in metal polluted than in control pots. In turn, root biomass was
halved as a result of metal pollution (Table 7.1). Nonetheless, plants did not show
any visual toxicity symptoms throughout the experiment.
In the first two harvests, values of shoot Cd concentration in metal polluted
pots were higher than 100 mg Cd kg-1 DW (Table 7.1). Shoot Zn concentrations
were 729.2 ± 111.5 and 635.8 ± 87.9 mg kg-1 DW in the first and second harvest,
respectively. In the third harvest, shoot metal concentrations in metal polluted pots
were significantly lower (as compared to the first two harvests) for both metals, with
low translocation factors (TF = shoot metal concentration/root metal
concentration) for both Cd (0.29) and Zn (0.06). At the end of the experiment,
considering the three harvests, sorghum plants had extracted, and subsequently
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traslocated, 12.9 mg of Cd and 74.4 mg of Zn from the soil to the aboveground
tissues.
Table 7.1: Shoot and root biomass (g DW tissue) and metal concentrations (mg kg-1 DW tissue) of sorghum plants in metal polluted and control non-polluted soils. For each metal and biomass value, numbers followed with different letters are significantly different (P <0.05 or lower) according to Fisher´s PLSD-test (lower case letters: among harvests; upper case letters: among polluted and non-polluted pots). Mean values (n = 4) ± standard errors.
Shoot
1st harvest Shoot
2nd harvest Shoot
3rd harvest
Root 3rd harvest
Polluted 46.7 ± 2.8aA 45.7 ± 4.2aA 37.9 ± 3.3aA 6.8 ± 1.7A Biomass
Non-polluted 61.1 ± 2.0aB 61.1 ± 0.7aB 46.2 ± 2.4bA 13.7 ± 0.4B
Polluted 122.4 ± 8.5aA 113.7 ± 5.0aA 52.5 ± 3.3bA 183.5 ± 6.2A Cd concentration Non-polluted 6.5 ± 0.5aB 10.9 ± 1.0aB 7.6 ± 0.6aB
10.7 ± 1.0B
Polluted 729.2 ± 111.5aA 635.8 ± 87.9aA 299.3 ± 53.1bA 4659.4 ± 605.3A Zn concentration
Non-polluted 49.7 ± 2.1aB 73.0 ± 2.4aB 44.5 ± 1.0aB
161.2 ± 13.0B
In metal polluted pots, a 6.6 and 6.8 % reduction in total Cd and Zn,
respectively, was observed in planted versus unplanted pots (Table 7.2). In these
metal polluted pots, concentrations of bioavailable Cd and Zn were significantly
lower in planted versus unplanted pots (a 46.7 and 50.7 % reduction in bioavailable
Cd and Zn, respectively). In control non-polluted soils, no significant differences in
total or bioavailable metal concentrations were found between planted and
unplanted pots. In metal polluted soils, shoot Cd and Zn concentrations were
correlated to soil metal bioavailable fractions (R2 = 0.52 for Cd and 0.77 for Zn; P =
0.008 and <0.001 for Cd and Zn, respectively) but not to soil total concentrations
(R2 = 0.07 for Cd and 0.10 for Zn; P = 0.736 and 0.684 for Cd and Zn,
respectively).
In the third harvest, the bioconcentration factor in metal polluted pots (BF =
shoot metal concentration/soil metal concentration) was 1.34 and 0.35 for Cd and
Zn, respectively.
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Table 7.2: Total (aqua regia digested) and bioavailable (CaCl2 extractable) metal concentrations (mg kg-1 DW soil) in soil samples at the end of the phytoextraction experiment. NM-UP: no metal, unplanted; NM-P: no metal, planted; M-UP: metal, unplanted; M-P: metal, planted. Values followed with different letters are significantly different (P <0.05 or lower) according to Fisher´s PLSD-test (letters refer to differences among treatments). Mean values (n = 4) ± standard errors.
Cd Zn Total Bioavailable Total Bioavailable
NM-UP 0.90 ± 0.06a 0.04 ± 0.01a 84.08 ± 3.44a 0.38 ± 0.19a
NM-P 0.83 ± 0.02a 0.06 ± 0.00a 66.05 ± 1.77a 0.68 ± 0.07a
M-UP 42.08 ± 2.19b 8.31 ± 0.50b 923.00 ± 36.53b 149.92 ± 11.11b
M-P 39.30 ± 1.70b 4.43 ± 0.94c 860.50 ± 32.32b 73.88 ± 19.82c
7.4.2 Effect of metal pollution and phytoextraction on soil parameters
In metal polluted pots, in the third harvest, the presence of sorghum led to a
statistically significant 412.4 % increase in dehydrogenase activity (Table 7.3). In
metal polluted soils, dehydrogenase activity was correlated to soil metal bioavailable
fractions (R2 = 0.45 for Cd and 0.52 for Zn; P <0.001 for both Cd and Zn) but not
to soil total metal concentrations (R2 = 0.02 for Cd and 0.06 for Zn; P = 0.713 and
0.577 for Cd and Zn, respectively). Table 7.3: Values of dehydrogenase activity (mg INTF kg-1 20 h-1). NM-UP: no metal, unplanted; NM-P: no metal, planted; M-UP: metal, unplanted; M-P: metal, planted. Values followed with different letters are significantly different (P <0.05 or lower) according to Fisher´s PLSD-test (lower case letters: among harvests; upper case letters: among treatments). Mean values (n = 4) ± standard errors.
NM-UP NM-P M-UP M-P
1st harvest 165.4 ± 59.9aA 168.8 ± 15.5aA 97.9 ± 4.3aA 146.2 ± 22.1aA
2nd harvest 144.9 ± 48.9aA 183.5 ± 6.5aA 100.4 ± 10.6aA 160.8 ± 6.5aA
3rd harvest 116.6 ± 38.8aAB 124.7 ± 6.4aAB 45.0 ± 16.8aA 185.6 ± 27.6aB
Figure 7.1 shows the average well colour development (AWCD) values
corresponding to the third harvest. In both the absence and presence of metals,
planted pots showed significantly higher values of AWCD than unplanted pots.
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Figure 7.1: Average well colour development (AWCD) curves in the third harvest. NM-UP: no metal, unplanted; NM-P: no metal, planted; M-UP: metal, unplanted; M-P: metal, planted. Lower case letters refer to significant differences (P <0.05 or lower) among treatments, according to Fisher´s PLSD-test, at 40 h of incubation.
In the third harvest, a PCA revealed clear differences among treatments
(Figure 7.2). Along PC1, the PCA significantly (P <0.05) separated planted from
unplanted pots. The substrates responsible to a greater extent for this separation
were L-asparagine, L-phenylalanine, L-serine, D-cellobiose, D-xylose, N-acetyl-D-
glucosamine, D-galactonic acid lactone, 4-hydroxy benzoic acid and glucose-1-
phosphate. The PCA significantly (P <0.05) separated metal polluted from control
pots along PC2 (but PC2 accounted for only 12 % of the variance). The main
substrate responsible for this separation was γ-hydroxybutyric acid.
Out of all treatment pairs, the pair NM-P/M-P showed the highest value of
the Jaccard index (CJ = 0.82). The lowest values of the Jaccard index were found for
the pairs M-UP/NM-P (CJ = 0.43) and M-UP/NM-UP (CJ = 0.48).
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Figure 7.2: Principal component analysis from absorbance values obtained in the third harvest with the Biolog EcoPlatesTM at an incubation time of 40 h. NM-UP: no metal, unplanted; NM-P: no metal, planted; M-UP: metal, unplanted; M-P: metal, planted. PC1 and PC2 account for 76 and 12 % of the variance, respectively.
Cumulative respiration curves corresponding to the third harvest (Figure 7.3)
show that, in both control and metal polluted soils, the presence of sorghum led to
significantly higher values of soil basal respiration. In unplanted pots, metal addition
resulted in significantly lower values of soil basal respiration.
With regard to SIR with glucose (data not shown), after 6 h of incubation, M-
UP pots showed significantly (P <0.05) lower values (mean SIR = 59.8 μg CO2-C g-
1 DW soil) than all the other pots [mean SIR ranged from 80.1 (NM-UP) to 92.8
(M-P) μg CO2-C g-1 DW soil]. After 48 h of incubation (by this time, cell division
has most likely occurred), metal polluted planted and unplanted pots showed
significantly higher values of SIR-glucose (755.3 and 690.9 μg CO2-C g-1 DW soil,
respectively) than their corresponding non-metal polluted planted and unplanted
controls (726.4 and 634.9 μg CO2-C g-1 DW soil, respectively). In addition, SIR-
glucose for planted pots (both metal and non-metal polluted) was significantly
higher than in their corresponding unplanted controls.
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Figure 7.3: Values of cumulative basal respiration at different incubation times obtained in the third harvest. NM-UP: no metal, unplanted; NM-P: no metal, planted; M-UP: metal, unplanted; M-P: metal, planted. Lower case letters refer to significant differences (P <0.05 or lower) among treatments, according to Fisher´s PLSD-test, at 35 days of incubation.
In relation to SIR with the model rhizodeposit solution (data not shown), after
6 h of incubation, planted and unplanted metal polluted soils showed significantly
lower values (17.7 and 10.5 μg CO2-C g-1 DW soil, respectively) than corresponding
planted and unplanted non-polluted controls (21.6 and 17.5 μg CO2-C g-1 DW soil,
respectively), and metal and non-metal planted pots showed significantly higher
values than the respective unplanted controls. Similar results were observed after 48
h of incubation. Thus, unlike SIR-glucose, lower values of SIR-rhizodeposit were
always found in metal polluted than control non-polluted pots.
When comparing SIR values between both substrates (glucose versus rhizodeposit), after 6 h of incubation, values of SIR-glucose were significantly
higher than SIR-rhizodeposit values. By contrast, after 48 h, SIR-rhizodeposit values
were always higher than those obtained with glucose (in some cases the differences
were not statistically significant).
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Although the differences were not statistically significant, values of QR were
higher in planted than unplanted pots and lower in metal polluted than control soils
(QR for NM-UP, NM-P, M-UP and M-P were 19.7 ± 3.0, 23.2 ± 1.0, 15.2 ± 1.7 and
20.8 ± 2.3, respectively).
Values of extractable K+ were significantly lower in planted than unplanted
pots and significantly higher in metal polluted than control soils (values for NM-UP,
NM-P, M-UP and M-P were 280.8, 111.3, 328.5 and 178.3 mg kg-1, respectively).
Values of extractable P were significantly lower in planted than unplanted pots and
in metal polluted than control soils (values for NM-UP, NM-P, M-UP and M-P pots
were 98.0, 80.8, 75.5 and 67.3 mg kg-1, respectively). Values of EC were significantly
higher in planted than unplanted pots (on average, values of EC for planted and
unplanted pots were 2566 and 2308 µS cm-1, respectively). No differences among
treatments were found for the remaining soil physicochemical parameters here
determined (pH, OM, total N, C/N).
At the end of the experiment, the phytoremediated soils were still significantly
more phytotoxic than control non-polluted soils (values of GI for NM-UP, NM-P,
M-UP and M-P pots were 96.8 ± 4.3, 95.3 ± 5.4, 78.5 ± 3.8 and 78.1 ± 1.5,
respectively). Indeed, metal polluted soils were significantly (P <0.005) more
phytotoxic than control non-polluted soils (no significant differences were found
between planted and unplanted pots).
7.5 Discussion
7.5.1 Metal phytoextraction by sorghum plants
Our sorghum plants proved to be highly tolerant to metal pollution and
capable of reaching high biomass values in the presence of metals. In the first two
harvests, values of shoot Cd concentrations in metal polluted pots were higher than
100 mg Cd kg-1 DW, the threshold value for hyperaccumulators indicated by Baker
et al. (2000). However, in the third harvest, the bioconcentration factors in metal
polluted pots were well below the threshold value of 10 considered for a
phytoextraction process to be feasible (McGrath et al., 2006). For both metals, the
shoot-to-root metal concentration ratio was well below 1 (by contrast,
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hyperaccumulator plants are characterized by a shoot-to-root metal concentration
ratio >1) (Baker, 1981). In the literature, there are not many reports on the metal
tolerance and phytoextraction potential of sorghum. In a previous study, we found
sorghum plants to accumulate high amounts of metals in their shoots when grown
hydroponically (Hernández-Allica et al., 2008). By contrast, in a field trial, Marchiol
et al. (2007) found sorghum plants to have a poor capacity for metal
phytoextraction.
If one assumes that metal pollution is restricted to the active rooting zone of
sorghum (i.e., top 90-cm soil layer) (Mbuya et al., 2001), which would give a total
soil mass to remediate of 11,700 t ha-1 (considering a soil bulk density of 1.3 t m-3),
some theoretical calculations can be performed. Thus, if we consider that in, for
instance, Spain, sorghum plants have been reported to reach a mean biomass yield
of 29 t ha-1 (Fernández, 1998), according to our metal concentration data, 0.61% of
the total amount of Cd present in a soil polluted with 50 mg Cd kg-1 DW soil would
be removed in the first harvest. If we hypothesize that sorghum plants are able to
extract the same amount of Cd in consecutive crops, independently of the soil Cd
concentration, then it would take 154 consecutive crops to reduce the initial soil Cd
concentration used in our experiment to 3 mg kg-1 (the target end-point
concentration used by Lombi et al., 2001). In our region, an average of 3 cuttings of
sorghum per year might be feasible, leading to an estimated remediation time of 51
years. As Cd concentration in shoots might decrease with decreasing Cd content in
soil, this calculation represents only a theoretical abstraction and a clear
overestimate of the reality. Indeed, as metals are removed from the soil by
successful croppings, the available metal concentration is expected to decrease (Van
Nevel et al., 2007). Although this change may occasionally be linear, in most cases a
logarithmic decay upon succesive croppings could occur (Robinson et al., 1999).
Eriksson and Ledin (1999) reported a 30-40 % decrease in plant-available Cd as a
result of long-term cropping of Salix. In any case, this reduction of the bioavailable
metal pool is still a matter of debate since other authors (Keller and Hammer, 2004;
Fischerová et al., 2006) have described a replenishment of the bioavailable pool. In
our experiment, the bioavailable CaCl2-extractable metal pool appears to be the
phytoavailable fraction of metals. Most likely, the lower shoot metal concentrations
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found in the third harvest, as compared to the first two harvests (Table 7.1), are due
to the decrease in the bioavailable pool of Cd and Zn observed in M-P pots.
7.5.2 Effect of metal pollution and phytoextraction on soil parameters
In general, microbial parameters (i.e., dehydrogenase activity, AWCD, basal
respiration, SIR-glucose, SIR-rhizodeposits, QR) show lower values in metal
polluted than control non-polluted soils. Actually, one of the lowest values of the
Jaccard index corresponded to the pair M-UP/NM-UP, indicating that, in the
absence of plants, metal pollution had a strong impact on the soil functional
diversity. Metals have frequently been reported to have a negative effect on soil
functioning and soil biological parameters (Giller et al., 1998; Kelly and Tate, 1998).
After all, metals are known to affect growth, morphology and metabolism of soil
microorganisms through functional disturbance, protein denaturation and
destruction of cell membrane integrity (Leita et al., 1995). Interestingly,
dehydrogenase activity was correlated to soil metal bioavailable fractions but not to
soil total metal concentrations, suggesting that the inhibitory effect of metals on
dehydrogenase activity was dependent on the bioavailable metal pool. Similar results
were reported by Hattori (1992) in sewage sludge amended soils. Inhibition of
enzyme activities in metal polluted soils reflects metal bioavailability because the
mechanisms that protect soil enzymes from inhibition by metals are likely to be the
same mechanisms limiting metal uptake by plants and soil organisms (Speir and
Ross, 2002). Then, the increase in dehydrogenase activity observed for M-P pots, as
compared to M-UP pots, in the third harvest (Table 7.3), may well be due to the
decrease in bioavailable metal concentration found in such pots (Table 7.2), together
with the stimulatory effect of plants on soil microbes (see below). Except for a few
enzymes like dehydrogenase, most soil enzymes have a significant portion of the
enzymatic activity associated with abiontic enzymes (Dick, 1997; Nannipieri et al.,
2002). By contrast, dehydrogenase requires the organization of the living
intracellular environment to express its activity and then it is a measure of the
activity of physiologically active microorganisms (Speir and Ross, 2002). That is why
the most widely studied enzyme indicator of soil biological activity is dehydrogenase
(because it exists only in viable cells) (Dick, 1997). Nonetheless, measured
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dehydrogenase activity does not correlate consistently with other parameters of
microbial activity such as respiration, due to, for instance, extracellular phenol
oxidases and some common anions in soil, such as nitrate, acting as alternative
hydrogen acceptors (Dick, 1997; Speir and Ross, 2002). Another problem with the
dehydrogenase enzyme assay is that copper (Cu) can interfere with the analytical
procedure so that soils high in soil solution Cu show artificially low dehydrogenase
activity levels (Chander and Brookes, 1991). In our case, in metal polluted soils,
dehydrogenase, basal respiration, SIR-glucose and SIR-rhizodeposit showed similar
trends with higher values in planted than unplanted pots (see below).
Although further research is still needed to explain the higher values of SIR-
glucose found in metal polluted pots after 48 h of incubation, soil microorganisms
under stress have been reported to divert energy from growth to cell maintenance
function, leading to higher values of CO2 evolution (Killham, 1985). Unlike SIR-
glucose, lower values of SIR-rhizodeposit were always found in metal polluted than
control non-polluted pots and, in this respect, it is important to point out that SIR-
rhizodeposit is an ecologically more relevant parameter for testing rhizospheric
microbial communities than SIR-glucose (Dedourge et al., 2004). After 6 h of
incubation, values of SIR-glucose were significantly higher than SIR-rhizodeposit
values. It has been previously reported that soil microorganisms utilize glucose
rapidly and efficiently because of its being a simple, soluble, low molecular weight
substrate which diffuses quite readily within the soil matrix (Chowdhury et al.,
2000). In any case, an understanding of the mechanisms by which rhizodeposits
affect soil community structure is beyond the intention of this study.
Likewise, it has been observed that all microbial parameters measured (i.e.,
dehydrogenase activity, AWCD, basal respiration, SIR-glucose, SIR-rhizodeposits,
QR) show higher values in planted than unplanted pots. As compared to bare soil,
vegetated soils are commonly described as having higher rates of microbial activity
and biomass, due to the presence of easily metabolizable root exudates (e.g., sugars,
amino compounds, organic acids, fatty acids, growth factors, nucleotides) and
surfaces for microbial colonization (Curl and Truelove, 1986; Grayston et al., 1997).
In similar phytoextraction experiments with T. caerulescens plants, higher values of
7. soil microbial community as bioindicator of the recovery of soil functioninG derived from metal phytoextraction with sorGhum
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biological activity were also found in rhizosphere versus non-rhizosphere soil
(Hernández-Allica et al., 2006a; Wang et al., 2006).
The values of AWCD, basal respiration and SIR-glucose obtained in M-P soils
at the end of the experiment were similar to those found in NM-P pots.
Furthermore, out of all treatment pairs, when applied to Biolog EcoPlatesTM data,
the highest value of the Jaccard index corresponded to the pair NM-P/M-P. Then,
it can be concluded that, as a result of the phytoextraction process, which includes
both plant growth and metal phytoextraction, the functioning of the
phytoremediated soil has been restored. Indeed, as abovementioned, regarding the
recovery of soil functioning derived from a phytoextraction process, an ideal target
should be to return to the conditions of a valid control soil (i.e., a vegetated,
unpolluted soil of similar physicochemical properties and subjected to the same
edaphoclimatic conditions). However, at the end of the experiment, according to
the germination test, the phytoremediated soils were still significantly more
phytotoxic than control non-polluted soils. This discrepancy between data obtained
with the germination test versus those obtained through the determination of soil
microbial parameters is not surprising because the former reflect only the effect of
metal pollution on the germination of a specific plant species while the latter reflect
the status of the soil microbial community, not necessarily behaving in a similar way.
Although CLPPs analysis by Biolog EcoPlatesTM has been criticised because of
its being prone to the biases inherent to methods measuring diversity under culture
conditions (Preston-Mafham et al., 2002), here it proved to be a very useful tool,
capable of clearly differentiating between treatments. Differences between
treatments were observed for substrates that belonged to different classes (e.g.,
amino acid, organic acid), but not regarding patterns of substrate class utilization.
Interestingly, five of the substrates that defined the plant treatment (L-asparagine, L-
phenylalanine, L-serine, D-xylose and 4-hydroxy benzoic acid) corresponded to C
sources reported as constituents of root exudates (Campbell et al., 1997).
Finally, regarding physicochemical parameters, it was concluded that they are
not as sensitive as biological indicators for the assessment of the effect of metal
pollution on soil functioning, as previously suggested by Mijangos et al. (2006).
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7.6 Conclusions
To avoid the inconvenience of having to sow again the phytoextracting plant
after each harvest, an interesting approach, worthy of in-depth study, is to use
perennial plant species able to regrow in the polluted soil after harvesting. In this
work, sorghum plants were able to accumulate high levels of Cd in their shoots
while maintaining a high biomass yield.
In terms of the values obtained for many of the soil microbial parameters here
determined, phytoremediated and control (vegetated) soils were very similar at the
end of the experiment and, then, it was concluded that, as a result of the
phytoextraction process, which includes both plant growth and metal
phytoextraction, the functioning of the phytoremediated soil was restored.
However, most importantly, although the phytoextracted soil recovered its
functionally, it was still more phytotoxic than the control non-polluted soil.
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8. EFFECTS OF CHELATES ON PLANTS AND SOIL MICROBIAL COMMUNITY: COMPARISON OF EDTA AND EDDS FOR LEAD
PHYTOEXTRACTION
Epelde et al. (2008), published in Science of the Total Environment 401, 21-28
8.1 Abstract
Most studies on chelate-induced phytoextraction have focused on EDTA-
mediated Pb phytoextraction. But EDTA and the formed EDTA-Pb complexes
have low biodegradability and high solubility in soil, resulting in an elevated risk of
adverse environmental effects. EDDS is an easily biodegradable chelating agent that
has recently been proposed as an environmentally sound alternative to EDTA.
Consequently, a greenhouse experiment, using a completely randomized factorial
design with four replications, was carried out to compare the potential of EDTA
and EDDS for chelate-induced Pb phytoextraction with Cynara cardunculus, as well as
to investigate the toxicity of these two chelates to both cardoon plants and soil
microorganisms. The effects of chelate addition on soil microbial communities were
studied through the determination of a variety of biological indicators of soil quality
such as soil enzyme activities, basal and substrate-induced respiration, potentially
mineralizable nitrogen, and community level physiological profiles. EDTA was
much more efficient than EDDS for the enhancement of root Pb uptake and root-
to-shoot Pb translocation. In a soil polluted with 5000 mg Pb kg-1, as a result of the
addition of 1 g EDTA kg-1 soil, a value of 1332 mg Pb kg-1 DW shoot was obtained.
EDDS application resulted in a shoot Pb accumulation of only 310 mg kg-1 DW.
Plants treated with EDDS showed lower values of biomass than those treated with
EDTA. EDDS proved to be rapidly degraded, and less toxic to the soil microbial
community in control non-polluted soils. Pb-polluted EDDS-treated soils showed
significantly higher values of basal and substrate-induced respiration than those
treated with EDTA. Although EDDS had a lower capacity to enhance Pb
phytoextraction than EDTA, it has the advantage of rapid biodegradation.
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8.2 Introduction
The application of chelating agents to the soil has been reported to increase
plant metal uptake and translocation, thus opening a wide range of possibilities for
metal phytoextraction (Blaylock et al., 1997; Garbisu and Alkorta, 2001; Garbisu et
al., 2002; Alkorta et al., 2004d). For chelate-induced phytoextraction, plants should
be fast-growing, tolerant to grow in polluted soils, easily cultivated using well-known
agricultural practices, and produce a large biomass (McGrath et al., 2002). Cardoon
(Cynara cardunculus L.) plants fulfil most of these requirements and, in addition, are
well adapted to a wide range of soils and tolerant to adverse climatic conditions,
making them interesting candidates for chelate-induced phytoextraction
(Hernández-Allica et al., 2007).
Most studies on chelate-induced phytoextraction have focused on EDTA
(ethylene diamine tetracetic acid)-mediated lead (Pb) phytoextraction (McGrath et
al., 2002). Nevertheless, EDTA and the formed EDTA-Pb complexes have low
biodegradability and high solubility in soil, resulting in an elevated risk of adverse
environmental effects due to metal mobilization and long persistence (Alkorta et al.,
2004b, d). In this respect, the amount of Pb taken up by plants has been reported to
be much smaller than the amount of Pb mobilized from the soil during EDTA-
induced Pb phytoextraction (Chen et al., 2004). EDDS (ethylene diamine
disuccinate) was proposed as an alternative for chelate-induced metal
phytoextraction (Grčman et al., 2003). EDDS has been shown to be easily
biodegradable (Jaworska et al., 1999), to form strong complexes with transition
metals and radionuclides (Jones and Williams, 2001), to cause a much smaller
leaching of Pb down the soil profile than EDTA (Grčman et al., 2003), and to be
less toxic to soil microorganisms (Grčman et al., 2003).
Contradictory results can be found in the literature regarding the capacity of
EDTA and EDDS to induce plant Pb accumulation. Grčman et al. (2003) found
that EDDS and EDTA were equally efficient for the induction of Pb accumulation
in Chinese cabbage shoots. By contrast, under similar experimental conditions, Kos
and Leštan (2003) reported that EDTA was almost twice as efficient as EDDS for
the induction of Pb accumulation in Chinese cabbage shoots. Likewise, conflicting
data can be found in the literature regarding the phytotoxicity of these chelates and
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the formed metal-chelate complexes. Grčman et al. (2003) observed a significant
phytotoxic effect with EDTA but not with EDDS on Brassica rapa. Conversely, Luo
et al. (2005) observed a greater plant growth inhibition in EDDS-treated plants, as
compared to those treated with EDTA. Meers et al. (2005) did not observe any
visual toxicity symptoms or growth inhibition in plants treated with EDDS or
EDTA.
Finally, the ultimate goal of any soil (phyto)remediation process must be not
only to remove the contaminant(s) from the polluted site but to restore soil quality,
i.e. the continued capacity of soil to perform or function according to its potential
(Hernández-Allica et al., 2006a). Although to date much more emphasis has been
placed on physicochemical indicators of soil quality (Mijangos et al., 2006),
biological indicators (e.g., enzyme activities, microbial biomass, basal and substrate-
induced respiration, mineralizable N, structural and functional biodiversity, and so
on) are becoming increasingly used due to their being more sensitive to changes in
the soil as well as to their capacity to provide information that integrates many
environmental factors (Alkorta et al., 2003a, b). We hypothesized that biological
indicators of soil quality are useful monitoring tools (i) to assess the efficiency of a
chelate-induced phytoextraction process and (ii) to determine the chelate-induced
toxic effect on the soil microbial community.
The objectives of this study were (i) to compare the capacity of EDTA and
EDDS to solubilize Pb from an artificially polluted soil and induce Pb accumulation
in cardoon plants, and (ii) to investigate the toxicity of these two chelates to both
cardoon plants and soil microorganisms [in this latter case, through the
determination of a variety of biological indicators of soil quality, such as enzyme
activities, basal and substrate induced respiration, mineralizable N, and community
level physiological profiles (CLPPs)].
8.3 Materials and methods
8.3.1 Greenhouse experiment
Soil was collected from the upper 20 cm of a natural grassland located in
Larrauri (Basque Country, northern Spain). The physicochemical properties of this
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soil (Table 8.1) were determined according to standard methods (MAPA, 1994).
Immediately after collection, the soil was air-dried for 24 h to allow sieving through
a 5 mm mesh and then stored at 4 ºC.
Table 8.1: Selected physicochemical parameters of the soil used in this study.
Parameter Value
pH 6.9
Organic matter (%) 14.4
C/N 13
WHC* (%) 35.5
Coarse sand (%) 15.7
Fine sand (%) 36.3
Loam (%) 24.4
Clay (%) 23.7
Pb (mg kg-1) 46.5
*WHC: water holding capacity at 33 kPa
Soil portions equivalent to 250 g of dried soil were individually contaminated
(by mechanical mixing in plastic bags) with two different concentrations of Pb (2500
and 5000 mg Pb kg-1 DW soil) as Pb(NO3)2 dissolved in water, and then placed in
350 cm3 plastic pots. Control, non-polluted soil portions were similarly amended
with KNO3 to compensate for the amount of nitrate added to the polluted soil.
Control and polluted soil portions were allowed to settle for 2 weeks (at 25 ºC and
70% water holding capacity-WHC) in the plastic pots.
The experiment was carried out in a greenhouse under controlled conditions
with pots arranged in a completely randomized factorial design with four
replications. Temperature (15-30 ºC) and humidity (50-95% relative humidity) were
electronically monitored and controlled by means of an automatic ventilating and
heating system. Initially, seeds of cardoon plants were germinated in trays on John
Innes No. 2 compost. One week later, cardoon seedlings (one emerging seedling per
pot) were transplanted to the pots and left to grow for four months. Throughout
the experimental period, plants were bottom-watered using deionized water, so that
soils were kept at 60-70% of their WHC at 33 kPa. Four months after transplanting,
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the following chelate treatments were applied: (i) a single dose of 1 g EDTA kg-1
DW soil (as reported by Lombi et al., 2001) and (ii) a single dose of 1 g EDDS kg-1
DW soil. Four control, untreated pots were also included in the experiment.
8.3.2 Plant metal accumulation
Seven days after chelate treatment, cardoon plants were harvested by cutting
the shoots exactly at the swelling formed in the root to shoot junction. Roots and
shoots were washed thoroughly with deionized water to remove soil particles,
blotted with tissue paper, and their fresh weights recorded. Plant material was dried
in an oven at 70 ºC for 48 h and dry weights recorded. Then, shoots and roots were
prepared for acid digestion by milling in a ball-mill (Restch) (2 mm mesh).
Subsamples (0.2 g) of dried plant tissue were digested with a mixture of
HNO3/HClO4 (Zhao et al., 1994) and Pb in the digest was determined using an
atomic absorption spectrometer (Spectra AA-250 plus, Varian, Australia) equipped
with an automatic sampler (Sps-5, Varian, Australia). The reliability of the digestion
and analytical procedure was tested including blanks and standards of plant leaves
(IPE 150 and IPE 160, 2nd semester 2004, Wageningen University, Holland) with
every batch of sample digest. Percentage recoveries were between 95 and 105%.
8.3.3 Soil solution analysis
In order to study the effect of chelates on Pb concentration in the soil
solution, 2500 mg kg-1 Pb-polluted pots were fitted with MOM-type Rhizons
(Eijkelkamp Agrisearch Equipment, The Netherlands). MOM-type Rhizons are
porous plastic samplers frequently used for the extraction of soil solution free of
microbial and colloidal contamination (Knight et al., 1998). One and 7 days after
chelate addition, soil solution was extracted from the pots and analyzed for Pb using
an atomic absorption spectrometer. Reagent blanks and at least two replicates of all
samples were used to ensure accuracy and precision in the analysis. The rate of
EDDS degradation was assessed, for three weeks, in the 2500 mg kg-1 Pb-polluted
pots according to Vandevivere et al. (2001). In this assay, filtered water extracts were
diluted to less than 2 mM EDDS and acidified to pH 2.1 with HNO3. Following
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addition of CuSO4 to 3 mM and 30 min incubation, absorbance was measured at
670 nm. In the current study, the rate of EDTA degradation in soil was not
determined. However, EDTA has previously been reported to degrade very slowly
in soil, i.e. 5 months after EDTA application, EDTA-metal complexes were still
present in the soil pore water (Lombi et al., 2001).
8.3.4 Soil biological indicators
Biological parameters were determined in control (non-polluted) and 2500 mg
kg-1 Pb-polluted soils. Soils were sieved to <2 mm and stored in fresh at 4 ºC.
Enzyme activities (i.e., dehydrogenase, acid phosphatase, β-glucosidase, and
arylsulphatase) were determined according to Dick et al. (1996) and Taylor et al.
(2002). Dehydrogenase (EC 1.1) activity is an intracellular process that occurs in
every viable microbial cell and is measured to determine overall microbiological
activity of soil (Nannipieri et al., 2002). Acid phosphatase (EC 3.1.3.2) is an
important enzyme in the P cycle because it provides P for plant uptake by releasing
phosphate from organic P (Eivazi and Tabatabai, 1977). β-glucosidase (EC 3.2.1.21),
a glycosidase important in the C cycle, hydrolyses carbohydrates with a β-D-
glycoside bond by splitting off the terminal β-D-glucose (Schinner et al., 1996) and
then plays a central role in the hydrolysis of polymers of plant residues, such as the
disaccharide cellobiose, releasing glucose as an important energy source for soil
heterotrophic organisms. Arylsulphatase (EC 3.1.6.1) is the enzyme that catalyses
the hydrolysis of organic sulphate ester releasing sulphate, the plant available form
of S (Rodríguez-Loinaz et al., 2008).
Potentially mineralizable N, an indicator of biologically active soil N, was
measured as described by Powers (1980). For soil basal microbiological respiration
(an indicator of overall microbiological activity), soil samples were placed in airtight
jars and moistened to 60 % WHC. The soils were incubated for three days at 30ºC
together with vials containing 0.2 M NaOH. The CO2 evolved during the incubation
period was determined by titration with 0.1 N HCl (ISO 16072 Norm). Substrate-
induced respiration, a measure of potentially active microbial biomass, was
determined by adding 10000 mg C kg-1 DW soil as glucose and then measuring the
respiration rate after 6 hours of incubation (ISO 17155 Norm). Finally, metabolic
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quotients (qCO2) were calculated as the ratio between values of basal respiration and
substrate-induced respiration.
For the analysis of CLPPs, Biolog EcoPlatesTM were used. Soil samples were
extracted by agitating in an orbital shaker (125 rev min-1) 1 g DW soil with 10 mL of
autoclaved Mili-Q ultra pure water for 1 h. After shaking, samples were left to settle
down and then a 1:100 dilution (1 mL soil suspension:100 mL autoclaved Mili-Q
ultra pure water) was inoculated onto the Biolog EcoPlatesTM. The plates were
incubated at 30 ºC and colour development was read at 595 nm using a micro plate
reader (Anthos Zenyth 3100). For each reading time, raw absorbance data were
corrected by subtracting the zero hour reading point and the absorbance value given
by the control well. Average well colour development (AWCD) was determined by
calculating the mean of every well’s absorbance value at each reading time. The
plates corresponding to an incubation time of 48 h were chosen for further
calculations (at approximately this incubation time, the highest rate of microbial
growth was observed in the Biolog EcoPlatesTM). The number of utilized substrates
(i.e., the number of substrates with an absorbance value > 0.25; this value marked
the beginning of the exponential phase in the Biolog EcoPlatesTM), equivalent to
species richness, S, was calculated at this 48 h incubation time. Similarly, Shannon´s
diversity (H’=-∑pilog2pi) and evenness (J’=H’/Hmax=H’/log2S) indexes (Magurran,
2004) were calculated, considering absorbance values at each well as equivalent to
species abundance.
8.3.5 Statistical analysis
Statistical analyses were performed using StatView software (SAS Institute
Inc.). Differences among treatments were analyzed by analyses of variance
(ANOVA) using Stat View software. Fisher´s PLSD-test was used to establish the
significance of the differences among means.
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8.4 Results
8.4.1 Chelate effects on soil Pb mobilization Much higher values of Pb concentration in soil solution were found in EDTA-
treated pots than in those treated with EDDS. Twenty-four hours after chelate
addition, values of Pb concentration in soil solution were 2.5-fold higher in EDTA-
treated pots (340 mg Pb L-1), as compared to EDDS-treated pots (139 mg Pb L-1).
At harvest (7 days after chelate addition), values of Pb concentration in soil solution
were 29.8-fold higher in EDTA-treated pots (264 mg Pb L-1), as compared to
EDDS-treated pots (9 mg Pb L-1).
Figure 8.1 shows the rate of EDDS degradation in the 2500 mg kg-1 Pb-
polluted soil, fitted with an exponential decay equation. As seen in this Figure 8.1,
EDDS showed a half-life in this polluted soil of 24 h.
Figure 8.1: Rate of EDDS degradation in the 2500 mg kg-1 Pb-polluted soil, fitted with an exponential decay equation.
8.4.2 Pb accumulation in cardoon plants
For all treatments, increasing values of soil Pb concentration led to increasing
values of root and shoot Pb concentration (Table 8.2). In control pots (no chelate
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added), root Pb concentrations were much higher than shoot Pb concentrations.
The root-to-shoot translocation (shoot metal concentration/root metal
concentration) induced by EDTA (and not EDDS; Table 8.2) resulted in relatively
high values of shoot Pb concentration (1332 mg Pb kg-1 DW tissue) in the 5000 mg
kg-1 Pb-polluted pots.
As expected, chelate addition (both EDTA and EDDS) led to higher values of
root and shoot Pb concentration, as compared to control pots. EDTA was much
more effective than EDDS for the enhancement of both root Pb uptake and root-
to-shoot Pb translocation (Table 8.2). Higher values of shoot Pb concentration were
observed in EDTA-treated pots than in those treated with EDDS (i.e., 8.6- and 4.3-
fold higher for the 2500 and 5000 mg kg-1 Pb-polluted pots, respectively). This
effect was less apparent in roots, i.e. in the 5000 mg kg-1 Pb-polluted soils, the
addition of EDTA led to 1.6-fold higher values of root Pb concentration than the
addition of EDDS.
Table 8.2: Effect of EDTA and EDDS on plant Pb accumulation (mg Pb kg-1 DW tissue) and translocation factor (TF) in cardoon plants subjected to different levels of Pb pollution in soil. Values followed with different letters are significantly different (P<0.05 or lower) according to Fisher´s PLSD-test (lower case: among chelate treatments for shoots, roots or TF; upper case:
among Pb concentrations for shoots, roots or TF). Mean values (n = 4) ± standard errors.
46.5 2500 5000
mg Pb kg-1 DW soil
Control 0.1 ± 0.1aA 14.9 ± 2.3aA 43.2 ± 3.1aA
EDTA 46.2 ± 20.3aA 666.8 ± 229.9bB 1332.0 ± 244.3bC Shoot
EDDS 0.9 ± 0.0aA 77.2 ± 17.9aA 310.2 ± 100.7aA
Control 8.3 ± 1.5aA 675.6 ± 16.8aA 1961.1 ± 96.8aB
EDTA 91.1 ± 44.3bA 1450.7 ± 67.3bB 6695.2 ± 711.2bC Root
EDDS 12.2 ± 2.9aA 1412.2 ± 132.1bB 4165.8 ± 607.9cC
Control 0.015 ± 0.011aA 0.022 ± 0.003aA 0.022 ± 0.002aA
EDTA 0.518 ± 0.100bA 0.461 ± 0.138bA 0.203 ± 0.036aB TF
EDDS 0.086 ± 0.018aA 0.053 ± 0.008aA 0.076 ± 0.024aA
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Furthermore, in EDDS-treated pots, the bioconcentration factor (BF = shoot
metal concentration/soil metal concentration) was 0.03 and 0.06 for the 2500 and
5000 mg kg-1 Pb-polluted pots, respectively. In EDTA-treated pots, the BF was 0.27
for both the 2500 and 5000 mg kg-1 Pb-polluted pots.
8.4.3 Plant biomass Table 8.3: Effect of EDTA and EDDS on shoot, root and total (shoot + root) dry weight (in
grams) of cardoon plants subjected to different levels of Pb pollution in soil. Values followed with different letters are significantly different (P<0.05 or lower) according to Fisher´s PLSD-test (lower case: among chelate treatments for shoots, roots or total; upper case: among Pb concentrations for
shoots, roots or total). Mean values (n = 4) ± standard errors.
46.5 2500 5000
mg Pb kg-1 DW soil
Control 3.5 ± 0.1aA 4.1 ± 0.4aA 2.7 ± 0.1aB
EDTA 2.6 ± 0.2bA 3.3 ± 0.3abB 2.1 ± 0.1bA Shoot
EDDS 2.6 ± 0.2bA 2.6 ± 0.2bA 2.0 ± 0.3bA
Control 2.2 ± 0.1aA 2.0 ± 0.1aA 1.4 ± 0.2aB
EDTA 1.6 ± 0.2bA 1.5 ± 0.1bAB 1.1 ± 0.1abB Root
EDDS 1.3 ± 0.2bA 0.9 ± 0.1cAB 0.8 ± 0.1bB
Control 5.7 ± 0.1aA 6.1 ± 0.3aA 4.0 ± 0.3aB
EDTA 4.1 ± 0.2bA 4.8 ± 0.3bA 3.2 ± 0.1abB Total
EDDS 3.8 ± 0.2bA 3.5 ± 0.2cAB 2.8 ± 0.3bB
For all treatments, lower values of shoot, root and total (shoot + root)
biomass were obtained at 5000 mg kg-1 Pb-polluted pots, as compared to 2500 mg
kg-1 Pb-polluted pots (Table 8.3). In non-polluted pots, chelate addition led to lower
values of shoot, root and total biomass, as compared to control plants (no chelate
added). In Pb-polluted soils, EDDS induced a greater reduction in shoot, root and
total biomass than EDTA. As compared to control plants, EDTA treatment
resulted in 20 and 22% lower values of shoot biomass in the 2500 and 5000 mg kg-1
Pb-polluted pots, respectively. On the other hand, as compared to control plants,
EDDS treatment resulted in 37 and 26% lower values of shoot biomass in the 2500
and 5000 mg kg-1 Pb-polluted pots, respectively. This effect was more marked for
root biomass: as compared to control plants, EDTA-treatment led to 25 and 21%
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lower values in the 2500 and 5000 mg kg-1 Pb-polluted pots, respectively; EDDS-
treatment led to 55 and 43% lower values in the 2500 and 5000 mg kg-1 Pb-polluted
pots, respectively. Finally, regarding total biomass, EDTA-treatment led to 21 and
20% lower values in the 2500 and 5000 mg kg-1 Pb-polluted pots, respectively;
EDDS-treatment led to 43 and 30% lower values in the 2500 and 5000 mg kg-1 Pb-
polluted pots, respectively.
8.4.4 Soil biological indicators The effect of chelate addition on soil biological properties was determined for
non-polluted and 2500 mg kg-1 Pb-polluted pots. In non-polluted pots, the addition
of EDTA, but not of EDDS, significantly inhibited dehydrogenase activity (Table
8.4). In 2500 mg kg-1 Pb-polluted pots, the addition of EDDS, but not of EDTA,
led to significantly higher values of β-glucosidase (Table 8.4). In both non-polluted
and 2500 mg kg-1 Pb-polluted pots, no significant differences were found for
arylsulphatase, acid phosphatase and potentially mineralizable N between controls
(no chelate added) and chelate-treated pots. Finally, in the absence of chelates, the
presence of 2500 mg Pb kg-1 did not have any inhibitory effect on soil enzymes and
potentially mineralizable N (as compared to those values obtained in non-polluted
pots) (Table 8.4). Table 8.4: Effect of EDTA and EDDS on soil enzyme activities and potentially mineralizable nitrogen in non-polluted and 2500 mg kg-1 Pb-polluted soils. Values followed with different letters are significantly different (P<0.05 or lower) according to Fisher´s PLSD-test. Mean values (n = 4) ± standard errors.
Dehydrogenase Arylsulphatase β-glucosidase Acid phosphatase Potentially mineralizable N
mg INTF kg-1
DW soil h-1 mg PN kg-1 DW soil h-1 mg N-NH4 kg-1 DW soil
Control 448.3 ± 20.1a 202.3 ± 16.8ab 227.8 ± 6.0a 1070.0 ± 52.6a 8.1 ± 0.3a
EDTA 294.5 ± 15.2b 182.2 ± 10.8a 241.4 ± 5.2ab 1159.4 ± 58.5a 9.3 ± 1.1a 46.5
EDDS 420.1 ± 56.8ab 204.5 ± 11.7ab 242.1 ± 3.5ab 1168.8 ± 64.1a 9.0 ± 1.2a
Control 440.4 ± 36.9a 233.7 ± 4.4b 233.4 ± 5.3a 1038.3 ± 116.1a 10.0 ± 0.8a
EDTA 325.9 ± 22.0ab 211.2 ± 6.5ab 245.1 ± 5.7ab 1233.6 ± 39.2a 8.5 ± 0.6a 2500
mg
Pb k
g-1 D
W so
il
EDDS 441.9 ± 69.9a 219.1 ± 8.3b 252.5 ± 4.9b 1236.5 ± 45.6a 7.8 ± 0.1a
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Figure 8.2: Effect of EDTA and EDDS on (a) soil basal respiration, (b) substrate-induced respiration and (c) microbial metabolic quotient (qCO2) in control non-polluted and 2500 mg kg-1 Pb-polluted pots. Bars with different letters are significantly different (P<0.05 or lower) according to Fisher´s PLSD-test. Mean values (n = 4) ± standard errors.
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Concerning soil respiration parameters (Fig. 8.2), EDTA addition led to
significantly lower values of basal respiration in both non-polluted and 2500 mg kg-1
Pb-polluted soil (Fig. 8.2a). The addition of EDDS also resulted in a significant but
lower inhibition of soil basal respiration in the non-polluted soil. With regard to
SIR, it was observed that EDTA treatment caused a significant reduction in this
parameter only in the 2500 mg kg-1 Pb-polluted pots (Fig. 8.2b). By contrast, EDDS
addition had no significant effect on SIR. Finally, the microbial metabolic quotient
(i.e., qCO2 = basal respiration/SIR) significantly decreased as a result of both
EDTA and EDDS treatment (Fig. 8.2c). In any case, EDTA addition resulted in
significantly lower values of qCO2, as compared to EDDS. In the absence of
chelates (control plants), similar values of these three respiratory parameters were
found in both non-polluted and 2500 mg kg-1 Pb-polluted pots (Fig. 8.2).
Data on soil microbial functional diversity obtained from the CLPPs are
summarized in Table 8.5. EDDS, but not EDTA, caused a significant increase in
species richness (S) and Shannon´s diversity (H’) in both non-polluted and 2500 mg
kg-1 Pb-polluted pots (Table 8.5). By contrast, no significant differences were
observed among treatments regarding AWCD and Shannon´s evenness (J’). In the
absence of chelates, the presence of 2500 mg Pb kg-1 led to significantly higher
values of S and H’.
Table 8.5: Effect of EDTA and EDDS on the AWCD and diversity indexes calculated from Biolog EcoPlatesTM absorbance data at an incubation time of 48 h. Values followed with different letters are significantly different (P<0.05 or lower) according to Fisher´s PLSD-test. Mean values (n = 4) ± standard errors. AWCD: average well colour development; S = richness; H’ = Shannon´s diversity index; J’ = Shannon´s evenness index.
AWCD S H’ J’
Control 0.49 ± 0.08a 15.67 ± 1.20a 2.64 ± 0.07a 0.67 ± 0.00a
EDTA 0.55 ± 0.10a 15.33 ± 0.88a 2.59 ± 0.05a 0.66 ± 0.00a 46.5
EDDS 0.62 ± 0.08a 19.67 ± 1.20bc 2.85 ± 0.06bc 0.66 ± 0.00a
Control 0.51 ± 0.03a 18.33 ± 0.33b 2.77 ± 0.01b 0.66 ± 0.00a
EDTA 0.57 ± 0.03a 18.67 ± 0.33b 2.80 ± 0.01b 0.66 ± 0.00a 2500
m
g Pb
kg-
1 DW
soil
EDDS 0.80 ± 0.06b 21.33 ± 0.33c 2.93 ± 0.02c 0.66 ± 0.00a
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8.5 Discussion
8.5.1 Chelate effects on soil Pb mobilization
In the current study, we investigated the potential of EDTA and EDDS for
chelate-induced Pb phytoextraction using cardoon plants and taking into account,
most importantly, the possible detrimental effect of chelate addition on soil
microbial communities. After all, microorganisms depend directly on the soil
solution for uptake of nutrients and water, and thus chelate-elevated metal
concentrations could lead to toxic effects for soil microorganisms which are
critically important for soil functioning (Kos and Leštan, 2004).
In our study, EDDS was less effective than EDTA for the enhancement of
soil Pb solubilization. This is not an unexpected result because EDTA has been
reported to have a stronger affinity for Pb (log Ks = 17.88) than EDDS (log Ks =
12.70) (Luo et al., 2005). The fast rate of EDDS biodegradation might also be an
important factor determining the differences in Pb solubilization efficiency. In our
soil, we obtained a degradation half-life of 24 h for EDDS. Jaworska et al. (1999)
reported a calculated half-life of 2.5 d for EDDS in sludge amended soil. Although
we did not determine the rate of EDTA degradation in soil, this chelate has
previously been reported to degrade very slowly, i.e. 5 months after EDTA
application; EDTA-metal complexes were still present in the soil pore water (Lombi
et al., 2001). Twenty-four hours after chelate addition, in the presence of 2500 mg
Pb kg-1, the concentration of Pb in the soil solution of our EDDS-treated pots was
approximately 40% of that found in EDTA-treated pots. Then, if we consider that,
at that time, approximately 50% of the EDDS was already degraded in our soil, it
could be speculated that, while present, EDDS showed a similar capacity to
solubilise Pb than EDTA. Most likely, the differences between EDTA and EDDS
regarding their capacity to solubilize Pb would be smaller at lower Pb
concentrations with a Pb:chelate ratio close to 1. In this case, the capacity of
chelates to solubilize Pb is strongly dependent on soil pH and the presence of other
ions such as Ca2+ and Fe2+. Tandy et al. (2006) indicated that at a soil pH of 7 and a
Pb:chelate ratio of 1, EDDS was as efficient as EDTA for metal solubilization.
Finally, in a previous study with a natural soil polluted with Cd, Zn and Pb (Santos
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et al., 2006), we also found EDTA to be much more effective in soil Pb
solubilization than EDDS.
8.5.2 Pb accumulation in cardoon plants
Regarding shoot Pb accumulation, EDTA appeared much more efficient than
EDDS (Table 8.2). Although shoot Pb concentrations observed as a result of
EDTA addition did not reach the 10000 mg kg-1 threshold proposed by several
authors (Blaylock et al., 1997; Salt et al., 1998) for a feasible phytoextraction in the
field, they were relatively high (1332 mg kg-1 in the 5000 mg kg-1 Pb-polluted soil).
In agreement with our results, Luo et al. (2005) found that Pb translocation from
roots to shoots of corn and bean plants was higher in the presence of EDTA than
EDDS, and concluded that it was due to the stronger chemical affinity of EDTA
for Pb. Apart from EDDS´s weaker affinity for Pb and its lower capacity to
solubilize Pb, due to its high degradation rate, EDDS-mediated uptake was probably
restricted to the first 2-3 days after treatment which could explain, at least partly, the
observed lower efficiency of EDDS to induce Pb accumulation under our
experimental conditions. Conversely, in a previous study with Brachiaria decumbens plants growing in a natural polluted soil (Santos et al., 2006), we found EDDS to be
more efficient inducing Pb accumulation in shoots than EDTA (and also more
efficient than EDTA in stimulating the translocation of Pb from roots to shoots).
Differences in experimental conditions (e.g., plant species, presence of other metals,
type of soil, time of exposure and harvest, etc.) can explain some of the conflicting
results among chelate-induced Pb phytoextraction experiments. Finally, it has been
reported that both chelates are taken up and translocated to the shoots through the
same apoplastic and non-selective absorption pathways (Tandy et al., 2006;
Hernández-Allica et al., 2007).
8.5.3 Plant biomass
The phytotoxicity of both chelates was similar in control non-polluted pots (a
reduction in shoot biomass of around 25% was observed for both chelates) (Table
8.3). However, the lower values of Pb accumulation induced by EDDS, as
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compared to EDTA, could also be due to the higher phytotoxicity caused by this
chelate when applied to the Pb-polluted soil (Tables 8.3). In agreement with our
data, Luo et al. (2005) found a significant reduction in shoot DW as a result of
EDDS addition. On the contrary, in a biotest with red clover (Trifolium pratense L.),
Grčman et al. (2003) found a greater phytotoxic effect with EDTA than EDDS. In
all treatments where 10 mmol kg-1 EDTA or EDDS was applied, Kos and Leštan
(2003) observed visual symptoms (necrotic lesions on the leaves of Chinese
cabbage) of chelator toxicity (the effect was much less pronounced at lower chelate
concentrations). In a previous study with cardoon plants grown hydroponically
(Hernandez-Allica et al., 2007), we found EDTA to negatively affect plant
physiological parameters related to plant water transpiration. Both in the absence
and presence of metals, Tandy et al. (2006) did not find a significant EDDS-induced
(500 μM) phytotoxicity in hydroponically grown sunflower plants. This EDDS-
imposed phytotoxicity is an important factor to be considered for the practical
aspects of chelate application in the field. Since EDDS degrades quite fast, it should
be possible to schedule several gradual applications of small doses of this chelate
during the growing period, in an attempt to maximize shoot metal uptake and
reduce the risk of metal movement into groundwater (Alkorta et al., 2004d).
Unfortunately, this strategy would be impeded if the chelate had a high
phytotoxicity.
8.5.4 Soil biological indicators
The adverse effects of heavy metal contamination on soil microbial
communities have been widely demonstrated in numerous field and laboratory
studies (Giller et al., 1998; Kelly et al., 1999). However, Pb is a poorly bioavailable
metal and consequently might not have such a strong negative impact on soil
microbes. As a matter of fact, in our work, Pb pollution did not have a significant
effect on some bioindicators known to reflect the activity of soil microbial
communities (i.e., dehydrogenase activity, potentially mineralizable N, basal
respiration, and SIR) (Table 8.4, Fig. 8.2). By contrast, the presence of Pb did have a
positive impact on the capacity of the culturable portion of the microbial
community to respond to substrates, as indicated by the significantly higher values
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of S and H’ obtained in the 2500 mg kg-1 Pb-polluted soils, as compared to non-
polluted pots (Table 8.5). Then, we could speculate that the presence of Pb might
have induced the appearance of Pb-tolerant, culturable, fast growing, r-selected
microbial populations.
On the contrary, the effects of chelate addition on soil microbes in metal
contaminated soils have rarely been investigated (Grčman et al., 2003; Bouwman et
al., 2005; Ultra et al., 2005). Particularly, very little is known about the effects of
chelator amendment on soil microbial activity and community composition during
metal chelate-assisted phytoremediation (Chen et al., 2006). In non-polluted soils,
EDTA had a strong negative impact on the activity of the soil microbial population,
as indicated by its effects on soil respiration and dehydrogenase activity (Fig. 8.2,
Table 8.4). In non-polluted soils, EDDS also caused a significant inhibition of soil
basal respiration, but less pronounced than that observed with EDTA (Fig. 8.2).
Interestingly, in non-polluted pots, SIR, an indicator of potentially active microbial
biomass, was not significantly affected by any of these chelates (Fig. 8.2). Kos and
Leštan (2004) observed that 5 mmol kg-1 of EDDS increased SIR perhaps because it
increased the bioavailability of trace metals essential for microbial growth (in their
study, higher EDDS concentrations caused no increase in SIR). In a previous study,
they found lower values of SIR in soils treated with EDTA, as compared to those
treated with EDDS (Kos and Leštan, 2003). The lower values of qCO2 here
obtained in the presence of chelates, as compared to control soils (Fig. 2), could
indicate an increased metabolic efficiency in the conversion of substrates into
biomass, as suggested by Pirt (1975). EDDS is a naturally occurring substance in soil
where it is readily decomposed into benign degradation products (Grčman et al.,
2003), which could explain its lower toxicity for soil microbes, as compared to
EDTA. In fact, EDDS has previously been reported to cause less stress to soil
microorganisms, as indicated by the trans to cis phospholipid fatty acid ratio
(Grčman et al., 2003).
The higher values of AWCD, S and H’ found in Pb-polluted EDDS-treated
pots, as compared to Pb-polluted EDTA-treated pots, could also confirm the lower
toxicity of EDDS to soil microorganisms. However, in the case of these Pb-polluted
soils, the lower values of AWCD, S and H’ found in EDTA-treated versus EDDS-
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treated pots are most likely also due to the higher concentrations of Pb in soil
solution found in EDTA-treated pots.
Finally, it is important to emphasize that, since many chelates are toxic for
both plants and soil microorganisms and pose a considerable environmental
problem due to their leaching towards groundwater, environmentally safe methods
of chelate-induced phytoextraction must clearly be developed before steps towards
further development and commercialization of this phytoremediation technology
are taken (Alkorta et al., 2004d).
8.6 Conclusions
EDTA was much more efficient than EDDS for Pb phytoextraction with C. cardunculus. EDDS had a half-life in soil of 24 h and, when applied to a Pb-polluted
soil, caused more toxicity to cardoon plants than EDTA. On the other hand, in
control non-polluted soils, EDDS proved to be less toxic to the soil microbial
community than EDTA. Then, it was concluded that although EDDS had a lower
capacity to enhance Pb phytoextraction in cardoon plants than EDTA, it has the
advantage of rapid biodegradation.
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9. EVALUATION OF THE EFFICIENCY OF A PHYTOSTABILIZATION PROCESS WITH BIOLOGICAL
INDICATORS OF SOIL HEALTH
Epelde et al., published in Journal of Environmental Quality (accepted)
9.1 Abstract A phytostabilization process which combined the addition of a synthetic
(CalcinitTM + urea + PK14% + calcium carbonate) or organic (cow slurry)
amendment with Lolium perenne L. growth was used to remediate a mine soil
moderately contaminated with Zn, Pb and Cd. The reduced toxicity caused by both
amendments allowed the establishment of a healthy L. perenne vegetation cover
which had a positive influence on soil properties, increasing the biomass, activity
and functional diversity of the soil microbial community. Beneficial effects of
phytostabilization on soil properties were more accentuated in organically amended
than in synthetically amended soils. Root-to-shoot translocation factors were smaller
in amended versus control plants indicating a reduction in the risk of metals entering
the food chain through phytostabilization. The sensitivity, rapid response, and
integrative character of biological indicators of soil health make them valuable tools
for the assessment of the efficiency of metal phytostabilization processes.
9.2 Introduction
The enormous costs associated with the remediation of contaminated soils by
means of traditional physicochemical methods have stimulated the development of
innovative biological technologies which could economically clean-up these soils
(Hernández-Allica et al., 2007). Phytoremediation, the use of green plants to remove
pollutants from the environment or to render them harmless (Cunningham et al.,
1995), has great potential for the remediation of contaminated soils. Within the
phytoremediation field, “phytostabilization”, a process wherein plants are
established and function primarily to accumulate metals into root tissue or aid in
their precipitation in the root zone (Cunningham et al., 1995; Salt et al., 1995), is
being encouraged for the revegetation and remediation of soils contaminated with
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high levels of metals, e.g. mine soils. Ideally, plants for phytostabilization should
develop an extensive root system and produce a large amount of biomass in the
presence of high concentrations of metals, while keeping root-to-shoot metal
translocation as small as possible (Wong, 2003). Nevertheless, mine soils are
frequently unfavourable environments for plants due to the presence of many
growth limiting factors, such as high levels of available metals, soil acidity, lack of
organic matter (OM) and its associated nutrients, and poor substrate structure
(Tordoff et al., 2000; Wong, 2003). Then, the use of organic amendments is a
common practice in phytostabilization procedures as organic residues are able to
improve soil properties by raising pH, increasing OM content, adding essential
nutrients for plant growth, increasing water holding capacity, and
modifying/reducing metal bioavailability (Alvarenga et al., 2009a, b). If revegetation
is performed in combination with amendments, it can then be termed as “aided
phytostabilization” (Alvarenga et al., 2009a, b) or “chemophytostabilization” (Knox
et al., 2000). The utilization of amendments, in the absence of plants, for the
remediation of mine soils has a number of limitations such as the need for regular
inspections, a lack of proven durability, and its failure to enhance the sometimes
unsightly nature of abandoned mine sites (Tordoff et al., 2000). On the contrary,
revegetation is an aesthetically pleasing technology which prevents water and wind
erosion as well as runoff and leaching of metals by rhizosphere-induced adsorption
and precipitation processes (Arienzo et al., 2004).
In any case, the ultimate goal of any soil metal remediation process must be
not only to remove the metals from the contaminated site or to render them
harmless (immobile, non-bioavailable) but to restore soil health/functioning. To
date, considerable emphasis has been placed on soil physicochemical properties as
indicators of soil health. However, soil biological properties, particularly those
related to the size, activity and diversity of soil microbial communities, are becoming
increasingly used as bioindicators of soil health owing to, among other advantages,
their rapid response, sensitive and capacity to provide information that integrates
many environmental factors (Mijangos et al., 2006).
The objective of this work was to evaluate the suitability of soil
microbiological indicators for the short-term assessment of the efficiency of
phytostabilization processes. For that purpose, a short-term phytostabilization
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microcosm study was carried out using Lolium perenne, combined with the addition
of a synthetic versus an organic amendment, to remediate a mine soil moderately
contaminated with Zn, Pb and Cd.
9.3 Materials and methods 9.3.1 Experimental design
A soil moderately contaminated with metals (total Zn, Pb and Cd in mg kg-1:
1000, 340 and 2.6, respectively; CaCl2-extractable Zn, Pb and Cd in mg kg-1: 417, 4.0
and 1.1, respectively) was collected with a shovel (upper 0-20 cm) from an
abandoned mine located in Lanestosa, Bizkaia, northern Spain (latitude 43°13´,
longitude 3°26´). This metal contaminated site occupies several hectares in the
middle of an area of predominantly rural use, providing an excellent opportunity for
the application of phytoremediation procedures. In previous studies (Barrutia et al.,
2009; Hernández-Allica et al., 2006a, 2008; Santos et al., 2006), we observed that
metal distribution in the Lanestosa mine was highly heterogeneous. For the current
study, soil was collected from an area known to contain moderate total
concentrations of metals. Immediately after collection, the soil was sieved to <4
mm, taken to the laboratory and subjected to characterization (see methods below).
The soil was a sandy-loam with the following physicochemical properties: pH = 4.8;
OM (%) = 4.75; total N (%) = 0.18; C/N = 15.3; extractable P (mg kg-1) = 6;
extractable K+ (mg kg-1) = 30; electrical conductivity (μS cm-1) = 2,400; and cation
exchange capacity (mEq 100 mL-1) = 2.89.
After characterization, one third of the soil was treated with cow slurry (pH =
8.2; OM (%) = 57.3; total N (%) = 0.36; total P (%) = 0.59; total K+ (%) = 3.03; all
values on a fresh weight basis) to reach a final concentration of major
macronutrients of: 0.39 mg N kg-1 dry weight (DW) soil, 0.25 mg P2O5 kg-1 DW
soil, 0.43 mg K2O kg-1 DW soil and 0.20 mg Ca2+ kg-1 DW soil. Another third was
treated with a mixture of synthetic amendments (CalcinitTM + urea + PK14% +
calcium carbonate) to reach the same macronutrient (N, P, K+ and Ca2+)
concentrations. In both cases, the amount of amendment added to the soil was <
1.5% the amount of soil (on a DW basis). A cement mixer was used to properly
homogenize the amendment-soil mixtures. The last third corresponded to non-
amended control soil (control soil samples were also homogenized in the cement
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mixer). All soils were allowed to stabilize in the dark for 6 months at 30% humidity
and 20 ºC. After this stabilization period, composite soil samples from each
treatment (SA: synthetic amendment; OA: organic amendment with cow slurry; C:
controls) were taken for the phytostabilization experiment.
Prior to the study, a two-week experiment (data not shown) was carried out
with four gramineous plant species, i.e. Agrostis tenuis Sibth (cv. Highland), Festuca arundinacea Schreber (cv. Villageoise), Lolium perenne L. (cv. Concerto) and Festuca rubra L. (cv. Pernille), to find out the most suitable species in terms of growth and
tolerance in the studied mine contaminated soil. L. perenne showed the best
germination rate and growth in the mine soil and, consequently, we selected this
species for our study. L. perenne has been reported (Alvarenga et al., 2008; Arienzo et
al., 2004) as a suitable species for revegetation of metalliferous sites, producing high
dry matter yields and accumulating moderate to high levels of metals in its biomass.
Pots were filled with 250 g DW of soil (SA, OA or C) moistened with distilled
water to 80% of the field capacity and sowed with L. perenne seeds at 0.4 g seed pot-1
(P: planted). Parallel to this one, another complete set remained unplanted (UP:
unplanted). All treatments were conducted in quadruplicate. Plants were then
allowed to grow for one month in a soft polyethylene-covered greenhouse (Venlo-
type) located in Derio (Bizkaia) at a latitude of 43º 17’ N, a longitude of 2º 52’ W
and an altitude of 65 m above sea-level. The climate in this region is Atlantic
temperate. Minimal temperature set points controlling air-heating were 14/18 ºC
night/day, and maximal temperature set points were 18/20 ºC night/day. Vent
opening temperatures were 20/25 ºC night/day. During the experiment, average
temperature was 15/24 ºC night/day, average relative humidity 45.7%, and average
photosynthetically active radiation 472 μmol photon m-2 s-1. After this month,
plants were harvested and washed thoroughly with deionized water to remove soil
particles. Fresh weights of shoots and roots were recorded and samples of leaves
(0.1 g) were collected from each pot to determine photosynthetic pigments
(chlorophyll a, chlorophyll b and carotenoids) content according to Wellburn
(1994). For the analysis of plant metal concentrations, shoots and roots were oven-
dried at 70 ºC for 48 h and their DWs recorded. Subsamples (0.4 g) of dried plant
tissue were digested with a mixture of HNO3/HClO4 (Zhao et al., 1994) and metals
in the digest were determined using inductively coupled plasma atomic emission
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spectrometry (ICP-AES; Varian, Palo Alto, CA). The reliability of the digestion and
analytical procedure was tested including blanks and standards of plant leaves (IPE,
Wageningen University, The Netherlands) with every batch of sample digest.
Finally, soil was sampled, by gently shaking off the rhizosphere soil that adhered to
roots, sieved to <2 mm and subjected to physicochemical and biological
characterization.
9.3.2 Soil physicochemical and biological characterization For soil physicochemical analysis, the soil was air-dried at 30 ºC for 48 h,
sieved to <2 mm, and stored at room temperature. Soil pH, cation exchange
capacity (CEC), electrical conductivity (EC), particle size distribution, and contents
of soil OM, total N and extractable P and K+ were determined following standard
methods (MAPA, 1994). Total metal concentrations in soil were determined using
ICP-AES following aqua regia digestion (McGrath and Cunliffe, 1985). The
reliability of the digestion and analytical procedure was tested including blanks and
standards of soil (ISE, Wageningen University, The Netherlands) with every batch
of sample digest. The soluble/available fraction of metals was extracted using 0.01
M CaCl2, as described by Houba et al. (2000), and Cd, Pb and Zn concentrations in
each extract were analyzed by flame atomic absorption spectrometry (SpectrAA-250
plus; Varian, Palo Alto, CA).
Regarding soil biological parameters, soils were sieved to <2 mm and stored
fresh at 4 ºC until analysis. Microbial biomass carbon (Cmic) was measured by the
fumigation-extraction method (Vance et al., 1987).
β-glucosidase, acid phosphatase and arylsulphatase activities were determined
according to a modification of Tabatabai (1994). One gram of soil (DW) was mixed
with 1.6 mL of buffer (20 mM modified universal buffer-MUB, pH 6.0, for β-
glucosidase; 20 mM MUB, pH 6.5, for acid phosphatase; 500 mM acetate buffer, pH
5.8, for arylsulphatase) and 0.4 mL of substrate [4-nitrophenyl-β-D-glucopyranoside
(1.5% w/v) for β-glucosidase; 4-nitrophenyl phosphate disodium salt (1.85% w/v)
for acid phosphatase; potassium 4-nitrophenyl sulphate (1.3% w/v) for
arylsulphatase]. The mixture was incubated at 37 oC for 45 min and the reaction
stopped with 0.4 mL of 500 mM CaCl2 and 1.6 mL of 500 mM NaOH for
arylsulphatase and acid phosphatase, and with 0.4 mL of 500 mM CaCl2 and 1.6 mL
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of 100 mM Tris (hydroxymethyl) aminomethane buffer-THAM, pH 12, for β-
glucosidase. After centrifugation (1250 x g, 5 min), the absorbance value of the
samples was read at 410 nm. Dehydrogenase activity was determined following a
modification of Von Mersi and Schiner (1991). One gram of soil (wet weight) was
mixed with 0.4 mL of 100 mM THAM, pH 7.0, and 0.4 mL of iodonitrotetrazolium
chloride-INT (0.5% w/v). The mixture was then incubated at 25 oC for 4 h and the
reaction stopped with 8 mL of methanol. After centrifugation (1250 x g, 5 min), the
absorbance value of the samples was read at 490 nm. Specific enzyme activity was
calculated as the value of each enzyme activity divided by the mg of Cmic kg-1 DW
soil.
Potentially mineralizable nitrogen, Nmin, an indicator of the capacity of the soil
to supply plant-available N, was measured as described by Powers (1980). Specific
Nmin (Nmin in μg N-NH4+ kg-1 DW soil divided by Cmic in mg of C kg-1 DW soil) was
also calculated.
For the analysis of community level physiological profiles (CLPPs), Biolog
EcoPlatesTM were used according to Epelde et al. (2008a, b). For each reading time,
average well colour development (AWCD) was determined. The plates
corresponding to an incubation time of 50 h were chosen for further calculations (at
approximately this incubation time, the highest rate of microbial growth was
observed in the EcoPlatesTM). The number of utilized substrates (i.e., the number of
substrates with an absorbance value >0.25; this value marked the beginning of the
exponential phase in the EcoPlatesTM), equivalent to species richness, S, was
calculated at this 50 h incubation time. Similarly, Shannon’s diversity index (H’=-
∑pilog2pi) and Simpson’s diversity index (1-D; D=∑pi2) were calculated considering
absorbance values at each well as equivalent to abundance of individuals in each
species.
9.3.3 Statistical analysis Differences between treatments were analyzed with one-way ANOVA using
Microsoft Stat View Software (SAS Institute, 1998). Fisher’s PLSD-test was used to
establish the significance of the differences among means. Results from
physicochemical (pH, EC, OM, total N, C/N, extractable P and K+, CaCl2-
extractable Cd, Pb and Zn concentrations) and biological (Cmic, β-glucosidase, acid
phosphatase, arylsulphatase, dehydrogenase, Nmin, AWCD, S and H’ from Biolog
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EcoplatesTM) determinations were used to perform a principal component analysis
(PCA) with Canoco 4.5 for Windows. Pearson’s correlations were calculated
between soil physicochemical and biological parameters, as well as soil metal
concentrations and plant metal accumulation using SPSS Programme (SPSS, 1989).
9.4 Results 9.4.1 CaCl2-extractable metal concentrations in soil
In unplanted pots, amendments (SA and OA) led to significantly lower values
of CaCl2-extractable metal concentrations, as compared to controls (Table 9.1).
Indeed, SA-treatment reduced the CaCl2-extractable concentration of Cd, Pb and
Zn by 11, 53 and 13%, respectively. The addition of cow slurry led to a 37, 55, 32%
reduction of CaCl2-extractable Cd, Pb and Zn, respectively. Most important, within
the three treatments studied here (OA, SA, control), significantly lower values of
CaCl2-extractable metal concentrations were found in planted versus unplanted pots
(Table 9.1). Table 9.1: CaCl2-extractable metal concentrations in soil samples at the end of the experiment. C: unamended controls; SA: synthetic amendment; OA: organic amendment; UP: unplanted; P: planted. Values followed with different letters are significantly different (P<0.05) according to Fisher’s PLSD-test. Mean values (n = 4) ± standard errors.
Cd Pb Zn
(mg kg-1 DW soil)
C-UP 1.15 ± 0.01a 4.44 ± 0.02a 450.7 ± 4.2a
C-P 1.06 ± 0.00b 3.92 ± 0.06b 421.7 ± 11.2b
SA-UP 1.02 ± 0.01b 2.09 ± 0.03c 393.0 ± 2.9c
SA-P 0.81 ± 0.01c 1.28 ± 0.02d 304.3 ± 4.3d
OA-UP 0.73 ± 0.03d 2.00 ± 0.13c 308.5 ± 5.4d
OA-P 0.62 ± 0.01e 1.23 ± 0.06d 265.8 ± 4.4e
evaluation of the efficiency of metal phytoremediation processes with microbioloGical indicators of soil health
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9.4.2 Plant parameters
SA- and OA-treated plants had significantly higher values of shoot and root
biomass than unamended controls (shoot biomass in SA and OA-plants was 111
and 90% higher than in control plants, respectively; root biomass in SA and OA-
plants was 105 and 284% higher than in control plants, respectively) (Table 9.2).
Throughout the experiment, control (unamended) plants showed clear visual
symptoms of chlorosis as reflected by their significantly lower values of
photosynthetic pigments content as compared to SA and OA-treated plants (Table
9.2). Table 9.2: Shoot and root biomass and photosynthetic pigments contents of Lolium perenne plants at the end of the experiment. C: unamended controls; SA: synthetic amendment; OA: organic amendment; UP: unplanted; P: planted. Values followed with different letters are significantly different (P<0.05) according to Fisher’s PLSD-test. Mean values (n = 4) ± standard errors.
Shoot Root Chlorophyll a+b Carotenoids
(g DW pot-1) (µg g-1 DW tissue)
C 0.70 ± 0.09b 0.19 ± 0.00c 1092 ± 81b 212 ± 13b
SA 1.48 ± 0.04a 0.39 ± 0.03b 2898 ± 107a 477 ± 19a
OA 1.33 ± 0.08a 0.73 ± 0.07a 2224 ± 301a 375 ± 51a
Regarding metal concentrations in L. perenne plants (Table 9.3), significantly
higher values of shoot metal concentrations were found in control than amended
plants. Furthermore, significantly lower values of shoot Cd and Zn concentration
were found in OA- than in SA-treated plants (no significant differences were found
between SA- and OA-treated shoots for Pb). On the other hand, Cd was
accumulated to a significantly greater extent in amended roots (SA and OA) than
control roots (values of root Cd concentration were 158 and 26% higher in SA and
OA-treated plants, respectively, as compared to controls). On the contrary, Pb was
accumulated to a significantly lower extent in amended (SA and OA) than in control
roots (values of root Pb concentration were 24 and 28% lower in SA and OA-
treated plants, respectively, as compared to controls). Finally, significantly highest
9. evaluation of the efficiency of a phytostabilization process with bioloGical indicators of soil health
185
185
and lowest values of root Zn concentration were found for synthetically amended
and organically amended plants, respectively.
Translocation factors (TF = shoot metal concentration / root metal
concentration) decreased in both SA- and OA-treated pots (Table 9.3). Lowest and
highest translocation factors were found for Pb and Zn, respectively (Table 9.3).
In terms of total amount of metal (Cd + Pb + Zn) phytostabilized in L. perenne roots, highest values were found in organically amended pots (i.e., OA-pots: 416.95
μg pot-1; SA-pots: 380.02 μg pot-1; control pots: 146.45 μg pot-1). Most of this metal
corresponded to Zn, i.e. the amount of Zn phytostabilized in roots was (in μg pot-1)
366.46, 351.39 and 128.63 in OA, SA and controls, respectively.
evaluation of the efficiency of metal phytoremediation processes with microbioloGical indicators of soil health
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18
7
Tab
le 9
.3:
Shoo
t an
d ro
ot m
etal
conc
entra
tions
and
tra
nslo
catio
n fa
ctor
s of
Loli
um p
erenn
e pl
ants
at
the
end
of t
he e
xper
imen
t. C:
una
men
ded
cont
rols;
SA
: sy
nthe
tic a
men
dmen
t; O
A: o
rgan
ic am
endm
ent;
UP:
unp
lante
d; P
: plan
ted.
Valu
es fo
llow
ed w
ith d
iffer
ent l
ette
rs a
re s
igni
fican
tly d
iffer
ent (
P<0.
05) a
ccor
ding
to
Fish
er’s
PLSD
-test
. Mea
n va
lues
(n =
4) ±
stan
dard
err
ors.
Sh
oots
R
oots
T
rans
loca
tion
fact
or
C
d Pb
Zn
C
d Pb
Zn
C
d Pb
Zn
(mg
kg-1 D
W ti
ssue
)
C
0.74
± 0
.02a
10
.5 ±
1.8
a 61
3 ±
24a
1.
24 ±
0.0
1c
92.5
± 0
.0a
677
± 0
b 0.
59 ±
0.0
2a
0.11
± 0
.02a
0.
91 ±
0.0
4a
SA
0.60
± 0
.04b
2.
8 ±
0.6
b 32
2 ±
15b
3.
20 ±
0.0
1a
70.2
± 3
.2b
901
± 0
a 0.
19 ±
0.0
1b
0.04
± 0
.01b
0.
36 ±
0.0
2b
OA
0.25
± 0
.01c
2.
7 ±
0.8
b 15
9 ±
5c
1.56
± 0
.08b
67
.6 ±
4.8
b 50
2 ±
57c
0.
17 ±
0.0
1b
0.04
± 0
.01b
0.
33 ±
0.0
3b
Tab
le 9
.4:
Soil
phys
icoch
emica
l pa
ram
eter
s at
the
end
of
the
expe
rimen
t. C:
una
men
ded
cont
rols;
SA
: syn
thet
ic am
endm
ent;
OA
: org
anic
amen
dmen
t; U
P:
unpl
ante
d; P
: plan
ted.
Valu
es f
ollo
wed
with
diff
eren
t let
ters
are
sig
nific
antly
diff
eren
t (P<
0.05
) acc
ordi
ng to
Fish
er’s
PLSD
-test
. Mea
n va
lues
(n =
4) ±
sta
ndar
d er
rors
.
pH
C
EC
E
C
OM
N
C
/N
Ext
. P
Ext
. K+
(mE
q 10
0 m
L-1 )
(µS
cm-1)
(%)
(m
g l-1
)
C-U
P 4.
63 ±
0.0
2e
3.36
± 0
.08c
24
30 ±
15c
4.
66 ±
0.0
4cd
0.17
± 0
.00c
15
.9 ±
0.1
cd
6.67
± 0
.20d
43
.3 ±
1.3
d
C-P
4.
77 ±
0.0
2d
3.05
± 0
.02c
24
33 ±
7c
4.80
± 0
.04c
0.
17 ±
0.0
0c
16.4
± 0
.4bc
7.
67 ±
0.2
0c
44.7
± 0
.4d
SA-U
P 4.
93 ±
0.0
2c
6.27
± 0
.12a
26
60 ±
19b
4.
44 ±
0.0
1e
0.17
± 0
.00c
15
.2 ±
0.1
d 14
.50
± 0
.25a
14
8.3
± 2
.5b
SA-P
5.
28 ±
0.0
2b
6.18
± 0
.11a
22
08 ±
27d
4.
63 ±
0.0
3d
0.16
± 0
.00d
17
.1 ±
0.3
ab
13.5
0 ±
0.2
5b
50.0
± 2
.4d
OA-
UP
5.30
± 0
.00b
5.
13 ±
0.1
0b
2723
± 1
1a
5.18
± 0
.04b
0.
19 ±
0.0
0a
15.9
± 0
.1cd
14
.00
± 0
.35a
b 25
3.5
± 3
.2a
OA-
P 5.
70 ±
0.0
4a
ND
† 22
13 ±
16d
5.
42 ±
0.0
9a
0.18
± 0
.00b
17
.3 ±
0.1
a 13
.25
± 0
.41b
12
1.0
± 4
.5c
† Non
-det
erm
ined
9. evaluation of the efficiency of a phytostabilization process with bioloGical indicators of soil health
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188
9.4.3 Soil physicochemical and biological parameters
Table 9.4 shows the values of soil physicochemical parameters at the end of
the phytostabilization experiment. In unplanted pots, the addition of synthetic
amendment led to significantly higher values of soil pH, CEC, EC, extractable P and
extractable K+, and significantly lower values of OM content, as compared to
controls. In unplanted pots, OA-treated soils showed significant higher values of all
physicochemical parameters, as compared to controls. The presence of plants under
both amendments (SA, OA) resulted in significantly higher values of soil pH and
OM content, and significantly lower EC, total N and extractable K+ (Table 9.4).
Figure 9.1: Microbial biomass C at the end of the experiment. C: unamended controls; SA: synthetic amendment; OA: organic amendment; UP: unplanted; P: planted. Bars with different letters are significantly different (P<0.05 or lower) according to Fisher’s PLSD-test. Mean values (n = 4) ± standard errors.
Regarding Cmic (Figure 9.1), in unplanted pots, synthetic amendment
significantly reduced this parameter while, on the contrary, the addition of cow
slurry led to significantly higher values. Under SA (not under OA), planted pots
showed significantly higher values of Cmic than unplanted pots. Values of Nmin
followed a similar trend (Figure 9.2), although, in this case, organically amended
planted pots had significantly higher values of this parameter than OA-treated
unplanted pots. In unplanted pots, specific rates of Nmin (μg N-NH4+ mg-1 Cmic)
evaluation of the efficiency of metal phytoremediation processes with microbioloGical indicators of soil health
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189
were significantly lower in OA (3.43 ± 0.18) than in SA (7.66 ± 0.57) or control
soils (6.50 ± 0.47). In addition, in organically amended soils, the presence of plants
resulted in higher values of this parameter (6.37 ± 0.30). No significant differences
were found between planted and unplanted soils in SA- or control pots regarding
specific Nmin (Figure 9.2).
Figure 9.2: Potential mineralizable N at the end of the experiment. C: unamended controls; SA: synthetic amendment; OA: organic amendment; UP: unplanted; P: planted. Bars with different letters are significantly different (P<0.05 or lower) according to Fisher’s PLSD-test. Mean values (n = 4) ± standard errors.
9. evaluation of the efficiency of a phytostabilization process with bioloGical indicators of soil health
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189
In unplanted pots, both amendments (SA and OA) significantly increased and
decreased β-glucosidase and acid phosphatase activity, respectively, as compared to
controls (Table 9.5). Under organic amendments, planted pots had significantly
higher values of dehydrogenase and arylsulphatase activity than unplanted pots.
Similarly, under synthetic amendment, planted pots had significantly higher values
of dehydrogenase, β-glucosidase and acid phosphatase activity than unplanted pots.
In control unamended pots, the presence of plants led to significantly higher values
of β-glucosidase and acid phosphatase activity. Table 9.5: Soil enzyme activities and their respective specific activities (enzyme activity / Cmic) at the end of the experiment. C: unamended controls; SA: synthetic amendment; OA: organic amendment; UP: unplanted; P: planted. Values followed with different letters are significantly different (P<0.05) according to Fisher’s PLSD-test. Mean values (n = 4) ± standard errors.
Dehydrogenase β-glucosidase Arylsulphatase Acid phosphatase
(mg INTF kg-1 20 h-1) (mg ρ-Nitrophenol kg-1 h-1)
C-UP 33.3 ± 0.6c 46.4 ± 0.9e 37.8 ± 3.6bc 454.8 ± 5.6b
C-P 37.3 ± 3.0c 56.1 ± 2.3d 39.8 ± 2.1b 509.5 ± 10.5a
SA-UP 48.3 ± 2.0c 65.1 ± 1.3c 31.4 ± 0.8c 392.6 ± 3.7c
SA-P 151.1 ± 9.7b 79.7 ± 1.5b 33.4 ± 0.5bc 454.8 ± 12.6b
OA-UP 145.8 ± 2.7b 120.9 ± 3.8a 39.6 ± 2.0b 406.0 ± 6.5c
OA-P 257.8 ± 5.7a 117.2 ± 0.9a 51.1 ± 3.2a 424.8 ± 16.3bc
SPECIFIC ACTIVITIES
C-UP 0.40 ± 0.03c 0.55 ± 0.03b 0.46 ± 0.07b -
C-P 0.45 ± 0.05c 0.67 ± 0.03b 0.48 ± 0.05b -
SA-UP 0.81 ± 0.08b 1.08 ± 0.07a 0.52 ± 0.04b -
SA-P 1.33 ± 0.18a 0.69 ± 0.06b 0.29 ± 0.02a -
OA-UP 0.69 ± 0.02bc 0.57 ± 0.03b 0.19 ± 0.01a -
OA-P 1.29 ± 0.05a 0.59 ± 0.02b 0.26 ± 0.02a -
Except acid phosphatase, enzyme activities studied here were positively
correlated with Cmic (R = 0.805, P<0.001 for dehydrogenase; R = 0.917, P<0.001
evaluation of the efficiency of metal phytoremediation processes with microbioloGical indicators of soil health
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190
for β-glucosidase; R = 0.491, P<0.015 for arylsulphatase) and then specific enzyme
activities (enzyme activity / Cmic) were calculated for these three enzymes (Table
9.5). Organic amendment in unplanted pots did not significantly affect
dehydrogenase and β-glucosidase specific activities, as compared to controls. On the
contrary, synthetic amendment in unplanted pots resulted in significantly higher
values of these two specific enzyme activities (dehydrogenase, β-glucosidase).
Comparing planted and unplanted pots, under synthetic amendment the presence of
plants significantly reduced the values of β-glucosidase and arylsulphatase specific
activity, while this inhibitory effect was not observed under OA. Under both
amendments, the presence of plants significantly increased values of dehydrogenase
specific activity.
Table 9.6 presents the values of the different parameters (AWCD, S, H’ and 1-
D) calculated from EcoplatesTM. In unplanted pots, SA led to significantly lower
values of all those parameters as compared to controls. On the contrary, in both the
absence and presence of plants, OA significantly increased AWCD, S and H’.
Significant differences between planted and unplanted pots were found in
synthetically amended soils (higher values of AWCD, S, H’ and 1-D in planted pots)
but not in OA-treated soils.
Table 9.6: Average well colour development (AWCD) and diversity indexes (S = richness; H’ = Shannon’s diversity; 1-D = Simpson’s diversity) calculated from EcoPlatesTM absorbance data (50 h incubation time) at the end of the experiment. C: unamended controls; SA: synthetic amendment; OA: organic amendment; UP: unplanted; P: planted. Values followed with different letters are significantly different (P<0.05) according to Fisher’s PLSD-test. Mean values (n = 4) ± standard errors.
AWCD S H’ 1-D
C-UP 0.39 ± 0.02d 14.33 ± 0.20c 2.54 ± 0.00c 0.91 ± 0.00a
C-P 0.55 ± 0.03c 17.00 ± 0.35bc 2.73 ± 0.02bc 0.93 ± 0.00a
SA-UP 0.06 ± 0.01e 1.67 ± 0.20d 0.45 ± 0.14d 0.32 ± 0.10b
SA-P 0.65 ± 0.02bc 18.33 ± 0.89b 2.78 ± 0.05b 0.93 ± 0.00a
OA-UP 0.72 ± 0.01ab 22.00 ± 0.00a 2.97 ± 0.00ab 0.94 ± 0.00a
OA-P 0.85 ± 0.13a 24.67 ± 1.74a 3.07 ± 0.08a 0.95 ± 0.00a
9. evaluation of the efficiency of a phytostabilization process with bioloGical indicators of soil health
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192
Finally, the application of a PCA to all soil physicochemical and biological
parameters (Figure 9.3) separated controls from amended pots (SA and OA) along
PC2 which accounted for 20% of the variance. Along PC2, SA-unplanted pots were
separated from all the other treatments. PC1, which accounted for 54% of the
variance, separated planted controls from SA and OA-treated planted pots. As
suggested in Figure 9.3, apart from acid phosphatase activity which was negatively
correlated with extractable P (R= -0.663, P<0.001; these two parameters extended
along the negative and positive axis of the PC2, respectively), most of the biological
parameters clumped together (along the positive axis of the PC1) and were
positively correlated with soil pH and OM content and negatively with CaCl2-
extractable metals (which extended along the negative axis of PC1). A negative
correlation between CaCl2-extractable metals and soil pH (R = -0.971, P<0.001 for
Zn; R = -0.972, P<0.001 for Cd) was found.
Figure 9.3: Principal component analysis of soil physicochemical and biological parameters. C: unamended controls; SA: synthetic amendment; OA: organic amendment; UP: unplanted; P: planted. PC1 and PC2 account for 54 and 20% of the variance, respectively. Only those parameters showing a fit range >40% have been included. GLU: β-glucosidase; DH: dehydrogenase; Cmic: microbial biomass C; Nmin: potentially mineralizable N; OM: organic matter content; SUL: arylsulphatase; PHO: phosphatase; Zn, Cd, Pb: CaCl2-extractable metal concentrations; AWCD, S and H’ from Biolog EcoplatesTM.
evaluation of the efficiency of metal phytoremediation processes with microbioloGical indicators of soil health
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193
9.5 Discussion
Metal contaminated soils represent a threat to soil ecosystems, hampering
plant growth and reducing soil functionality (Kumpiene et al., 2009) by (i) reducing
the soil microbial biomass and activity as a result of selection of metal tolerant
organisms that are less metabolically efficient (Giller et al., 1998) and (ii) inhibiting
the activity of hydrolase enzymes that are important in nutrient cycling (Tyler et al.,
1989). Then, demonstration of recovery of soil functionality and increasing
complexity of microbial communities in phytostabilized soils might be a key issue
for the acceptance of such a remediation option (Kumpiene et al., 2009). In other
words, ecological restoration of mine degraded soils, achieved by the application of
amendments and phytostabilization, must be assessed based not only on soil
chemical properties and metal availability, but also on assays that measure soil
microbial activity or community structure and enzyme actitivies related to the
biocycles of nutrients (Alvarenga et al., 2008; Hinojosa et al., 2004; Zhang et al.,
2006). Liao et al. (2005) reported that soil microbiological parameters have great
potential as early sensitive, effective and reliable indicators of stresses or
perturbations in soils affected by mine wastes.
The mine soil studied here was only moderately contaminated in terms of
total metal concentrations, but the levels of CaCl2-extractable metals were relatively
high, possibly due to its sandy-loam nature and low pH. Soils of these characteristics
usually present a high risk of metals leaching to groundwater and an elevated
toxicity to soil biota, making them good candidates for phytostabilization
experiments.
Regarding CaCl2-extractable metal concentrations, although both amendments
led to lower values, this reduction was more accentuated in OA-treated soils. Metal
bioavailability in soil can be reduced through the addition of OM so that insoluble
metal-organic complexes with humic acids are formed, thereby lessening the risk of
metal toxicity to plants and microbes (Kirkham, 1977). Much work has been carried
out on the utilization of manure (Rotkittikhun et al., 2007), compost (Gomez et al.,
2006) and sewage sludge (Chiu et al., 2006) for this purpose. Importantly, we
observed a further reduction in CaCl2-extractable metal concentrations in planted
versus unplanted soils, indicating a superior remediation efficiency in the presence of
9. evaluation of the efficiency of a phytostabilization process with bioloGical indicators of soil health
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194
plants. It has been reported that a vegetation cover further improves the chemical
and biological characteristics of the contaminated soil by increasing OM content,
nutrient levels, CEC and biological activity, allowing the creation of a self-sustaining
ecosystem (Pérez de Mora et al., 2005, 2006).
The synthetic and organic amendments led to the development of a healthy L. perenne cover as opposed to control plants that showed clear visual symptoms of
phytotoxicity throughout the experiment as reflected by their lower values of
biomass and photosynthetic pigments content. Similarly, in a previous study
(Barrutia et al., 2009), we found that synthetic fertilization overcame phytotoxicity
symptoms in non-tolerant Rumex acetosa populations. Some amendments are known
to be effective at lowering soil metal toxicity while providing a release of valuable
nutrients for plant growth (Chiu et al., 2006). Vangronsveld et al. (1995) treated a
Zn-polluted soil with beringite and compost quickly stimulating the growth of a
healthy vegetation cover. In a field phytostabilization experiment (Li et al., 2000),
compost addition lowered soluble Zn and Cd concentrations resulting in lower
phytotoxicity. Indeed, the presence of healthier plants in highly contaminated
mining sites following organic amendments was the result of the amendments’
ability to reduce phytoavailable soil metal concentrations (Mench et al., 2003) as well
as the improvement of soil nutritional conditions. The reduction in CaCl2-
extractable metal concentrations observed in the soil of planted pots was mainly due
to modification of the rhizosphere characteristics, not to plant metal uptake.
Regarding metal concentrations in L. perenne shoots, the lower values of amended
versus control plants might be the consequence of such reduction in CaCl2-
extractable metal concentrations. The fact that translocation factors were lower in
amended than in control plants is of considerable importance, as it indicates that
our phytostabilization process reduced the risk of metals entering the food chain.
Finally, although shoot Zn concentrations were high in control and amended pots,
both OA- and SA-treatments managed to lower them below phytotoxic threshold
levels (>500 mg Zn kg-1) (Chaney, 1993). In any case, the addition of cow slurry
resulted in all metal concentrations in plant shoots being below toxic levels for
herbivore consumption (Chaney, 1989).
evaluation of the efficiency of metal phytoremediation processes with microbioloGical indicators of soil health
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The addition of synthetic and organic amendments increased crucial soil
physicochemical properties (pH, OM and CEC) which could explain the observed
low values of CaCl2-extractable metals. This effect was enhanced in planted pots.
Under both amendments, L. perenne growth increased soil pH, a noteworthy
improvement in acid mine soils such as ours, and OM content which, again,
indicates a superior remediation efficiency in the presence of plants. In both planted
and unplanted soils, synthetic amendment decreased the content of soil OM (and of
total N in the case of planted soils) which could be explained by a more rapid
turnover/oxidation of OM under SA-treatment. The significantly lower values of
total N and extractable K+ found in planted versus unplanted pots under both
amendments might be due to plant uptake of inorganic forms of these essential
nutrients.
Our experiment was carried out for a short period of time to investigate the
potential of microbiological indicators of soil health to detect early changes in soil
properties derived from phytostabilization, in an attempt to highlight their
sensitivity and rapid response. The addition of nutrients and OM to the soil usually
increases the biomass and activity of the soil microbial community and,
simultaneously, affects the impact of contaminants, like metals, on biological
parameters such as enzyme activities. In this respect, soil enzymes are highly
sensitive to metals and, therefore, have been recommended as standard biochemical
indicators to assess quality of metal contaminated soils (Hinojosa et al., 2004, 2008).
Tejada et al. (2008) reported an increase in enzyme activities in metal-contaminated
soils as a result of the addition of organic amendments. Similarly, in our study, the
addition of cow slurry led to an increase in dehydrogenase activity (dehydrogenase is
an oxidoreductase enzyme which has been used as a measurement of overall
microbial activity, since it is an intracellular enzyme related to the oxidative
phosphorylation process; Tabatabai, 1994) and β-glucosidase activity (it reflects the
state of the soil OM and the mineralization and humification processes) in both
planted and unplanted soils, suggesting an stimulation of the C cycle as a response
to the application of labile OM. Soil hydrolases, such as β-glucosidase, urease and
phosphatase, are sensitive indicators of management-induced changes due to their
strong relationship with soil OM content and quality (Tejada et al., 2006). In planted
pots, synthetic amendment also led to an increase in dehydrogenase and β-
9. evaluation of the efficiency of a phytostabilization process with bioloGical indicators of soil health
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196
glucosidase activity, in this case probably due to the addition of essential nutrients to
a mine soil characterized by low levels of such nutrients and to the positive effects
of plant growth. On the other hand, significantly higher values of dehydrogenase
and β-glucosidase specific activities found in SA-treated unplanted soils, as
compared to controls (cow slurry did not significantly affect these two specific
enzyme activities in unplanted pots), suggests a stress response of the soil microbial
community to the addition of our synthetic amendment. Lastly, under both
amendments, L. perenne growth increased dehydrogenase activity (as compared to
amended unplanted pots), one more time highlighting the positive effect of plants
on soil microbial activity.
Acid phosphatase activity (an indicator of organic P mineralization) decreased
as a response to both amendments in planted and unplanted soils, which can be
attributed to feedback inhibition of the enzyme activity by available-P (acid
phosphatase activity was negatively correlated with the content of soil extractable P).
The increase in acid phosphatase and β-glucosidase activity found in control and
SA-soils (not in OA-treated soils) as a result of L. perenne growth might be explained
by an stimulatory effect caused by root exudates. Several studies reported increased
soil hydrolase activities following the revegetation of metal-contaminated soils
(Izquierdo et al., 2005; Pérez de Mora et al., 2005, 2006; Zhang et al., 2006).
Not surprisingly, most biological parameters were positively correlated with
soil pH and OM content, emphasizing the beneficial effects of an increase in these
parameters in acid mine soils. Wang et al. (2006) also found a correlation between
soil biological activities and pH which was well characterized by linear or quadratic
regression models.
Microbial biomass parameters have been widely used for assessing soil quality
and the degree of restoration in degraded and/or contaminated soils (Clemente et
al., 2006, 2007; Pérez de Mora et al., 2005). The lower values of Cmic in SA-treated
unplanted soils as compared to controls may be caused by amendment-induced
toxicity. Previous studies have reported a negative effect of synthetic amendment
addition on total microbial biomass (Sarathchandra et al., 2001) and bacterial
populations (Biederbeck et al., 1996). Killham (1985) suggested that soil
microorganisms under stress divert energy from growth to cell maintenance
evaluation of the efficiency of metal phytoremediation processes with microbioloGical indicators of soil health
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functions which may be a plausible explanation for these lower Cmic values. The
presence of L. perenne reverted this toxic effect, possibly due to overall beneficial
effects of plants on soil microbial communities. We have previously reported the
positive effects of revegetation on microbial communities in metal-contaminated
soils (Epelde et al., 2008a, b; Hernández-Allica et al., 2006a). As compared to bare
soil, vegetated soils frequently have a higher microbial biomass and activity, owing
to the presence of additional surfaces for microbial colonization and root exudation
of organic compounds (Delorme et al., 2001). In agreement with our data, Clemente
et al. (2006) reported a positive effect of organic amendments on Cmic. The only
difference between data of Cmic and Nmin (OA planted pots had higher values of
Nmin than OA unplanted pots while regarding Cmic no significant differences were
observed between OA-treated planted and unplanted pots) again suggests that the
presence of plants activates soil microbial activity.
Regarding CLLPs, in general, synthetic amendment had a negative or no effect
on all parameters while the addition of cow slurry increased overall activity (AWCD)
and functional diversity (S, H’) of the heterotrophic cultivable soil microbial
community. Sarathchandra et al. (2001), in a urea fertilization trial, also found higher
values of H’ and AWCD in unfertilized than in fertilized soils. In OA-treated soils,
the easily mineralizable OM might have favoured the development of the soil
microbial activity, together with its microbial biomass and functional diversity.
These results are in agreement with other studies (Gomez et al., 2006) where OM
incorporation resulted in significant increases of AWCD, S and H’.
9.6 Conclusions
The addition of amendments, especially cow slurry, improved the properties
of the contaminated mine soil and reduced metal toxicity and bioavailability. This
reduced toxicity, together with the benefits provided by the addition of nutrients,
allowed the establishment of a healthy L. perenne vegetation cover in the mine soil
which, through the modification of crucial soil physicochemical properties (pH, OM
content), further enhanced soil biological parameters, increasing the biomass,
activity and functional diversity of the microbial community. The beneficial effects
of phytostabilization were more accentuated in organically amended than in
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synthetically amended soils. Our phytostabilization procedure reduced the risk of
metals entering the food chain, with the addition of cow slurry resulting in shoot
metal concentrations below toxic levels for herbivore consumption. In this study, L. perenne has been used as a model species under greenhouse controlled conditions but
now further research is needed to verify the beneficial effects of phytostabilization
under long-term field conditions with native metallophytes. Use of native plants is
certainly desirable as they are usually tolerant to local environmental conditions and,
most important, provide a foundation for natural ecological succession.
Phytostabilization is an aesthetically pleasing, useful technology that might help
restore degraded mine soils to some acceptable condition for revegetation by
decreasing soil metal bioavailability and overcoming nutrient deficiency in such soils.
The sensitivity, rapid response and integrative character of biological indicators of
soil health make them valuable tools for the short-term assessment of the efficiency
of phytostabilization processes.
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10. LINKS BETWEEN PSEUDOMETALLOPHYTES AND RHIZOSPHERE MICROBIAL COMMUNITIES IN A
METALLIFEROUS SOIL
Epelde et al., in preparation for publication
10.1 Abstract
The objective of this work was to study, in a slightly polluted metalliferous soil, the
short-term interactions between pseudometallophytes and rhizosphere microbial
communities as reflected by the values of soil microbial properties with potential as
bioindicators of soil health, in an attempt to quantify improvements in soil health derived
from pseudometallophyte growth and metal phytoextraction and phytostabilization under
different pseudometallophytes compositions. To this aim, plant consortia consisting of 1-
3 pseudometallophytes with different metal-tolerance strategies (hyperaccumulator:
Thlaspi caerulescens; accumulator: Rumex acetosa; excluder: Festuca rubra) were grown for two
months in a mine soil. At the end of the experiment, the following soil microbial
properties were determined: enzyme activities, biomass C, functional and structural
diversity, and bacterial and fungal abundance. Growing together with T. caerulescens proved
stimulatory for the other two pseudometallophytes, probably due to T. caerulescens metal
phytoextraction. R. acetosa, in combination with T. caerulescens, extracted the highest
amounts of Zn from our metalliferous soil. Lowest values of microbial functional
diversity were found in soils planted only with R. acetosa. Except for β-glucosidase, in
general, a negative correlation was found between enzyme activities and number of
pseudometallophytes present in the study pots. Highest values of microbial biomass C
were observed in the presence of the three pseudometallophytes. A methodology to link
the concept of soil health to that of ecosystem health is here proposed, assigning soil
microbial properties to attributes of ecosystem health (vigor, organization and stability).
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10.2 Introduction
It is increasingly recognized that aboveground and belowground components of
terrestrial ecosystems are closely related (Rodríguez-Loinaz et al., 2008). Plant diversity
and composition can alter rhizosphere microbial communities due to, among other
factors, differences in the quantity and quality of root exudates and plant litter, leading to
increased heterogeneity of organic substrates with its concomitant effects on the soil
decomposer community (Broughton and Gross, 2000; Stephan et al., 2000). In turn,
belowground microbial communities are known to decompose soil organic matter (OM),
stabilize soil structure and release nutrients for plant growth (Porazinska et al., 2003), thus
affecting vegetation structure.
On the other hand, soil microbial properties, especially those related to the biomass,
activity and diversity of the soil microbial communities, are becoming more and more
used as biological indicators of soil health (i.e., the soil´s continued capacity to sustain plant
growth and maintain its functions) (Coleman et al., 1998), due to their rapid response,
sensitivity and capacity to provide information that integrates many environmental factors
(Hernández-Allica et al., 2006a). In any event, whatever occurs in the soil has a profound
effect not only on soil health but also on ecosystem health. The concept of ecosystem health
has been elaborated as a comprehensive, multiscale, dynamic, hierarchical measure of
system´s (i) vigor, which may be quantified in terms of productivity, throughput of material
and energy in the system, etc.; (ii) organization, which may be assessed in terms of both
diversity of components and their degree of mutual dependence; and (ii) resilience/stability, which may be determined in terms of the system´s ability to maintain its structure and
pattern of behaviour in the presence of stress (Rapport, 1998; Alkorta et al., 2004a).
Many of the Earth’s fragile ecosystems such as metalliferous mining sites can be
considered ‘unhealthy’ in the sense that, in them, toxic metals often adversely affect the
number, activity and diversity of soil organisms, and restrict the growth of all but the
most tolerant plants (Wong, 2003). However, metalliferous soils are frequently home to
an endemic plant diversity that offers huge potential for the development of
environmental technologies such as, for instance, the phytoremediation and revegetation
of metal-enriched environments (Barrutia et al., 2008). Metallophytes are plant species
that have evolved biological mechanisms to resist, tolerate, or thrive in metalliferous soils
(Whiting et al., 2004). Similarly, pseudometallophytes are plants that colonize both
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metalliferous and non-metalliferous environments. The combination of
(pseudo)metallophytes with different physiological strategies (exclusion, accumulation,
hyperaccumulation) to deal with the toxic levels of heavy metals present in metalliferous
soils appears a most promising approach for phytoextraction (the utilization of
hyperaccumulating plants that have the capacity to accumulate, translocate and tolerate
high amounts of metals) and/or phytostabilization (the utilization of excluder plants to
convert metal pollutants into inert, immobile forms) (Epelde et al., 2009a). After all, the
limitations of one species might be overcome by the advantages of another.
Regrettably, so far, only a few studies have addressed the interactions between
aboveground and belowground communities in polluted environments (Phillips et al.,
2008; Yang et al., 2007). Then, the main objective of this work was to study, in a slightly
polluted metalliferous soil, the short-term interactions between pseudometallophytes and
rhizosphere microbial communities as reflected by the values of soil microbial properties
with potential as bioindicators of soil health, in an attempt to quantify improvements in
soil health derived from pseudometallophyte growth and metal phytoextraction and
phytostabilization under different pseudometallophytes compositions. The utilization of
pseudometallophytes for phytoextraction and phytostabilization was also discussed. Most
interestingly, and to our knowledge in a pioneering way, a methodology to link the
concept of soil health to that of ecosystem health is here proposed.
10.3 Materials and methods
10.3.1 Soil characterization and experimental design
A short-term microcosm pot study was carried out with soil collected from the top
layer (0-30 cm) of the Pb/Zn “Txomin” mine area located in the province of Biscay
(northern Spain). Immediately after collection, the soil was sieved to <2 mm, air-dried at
30 ºC for 48 h, and subjected to physicochemical characterization according to standard
methods (MAPA, 1994). The soil was sandy loam, with a pH of 4.4, an OM content of
6.3%, a total nitrogen (N) content of 0.25%, a C/N ratio of 17.1, a phosphorus (P)
content of 2.7 mg kg-1 DW soil, and a potassium (K+) content of 41 mg kg-1 DW soil.
Total concentrations of heavy metals in soil were determined using flame atomic
absorption spectrometry (AAS, Varian) following digestion with a mixture of
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HNO3/HClO4 (Zhao et al., 1994). The following values of total metal concentration were
found (mg kg-1 DW soil): 0.93, 325.3 and 320.8 for Cd, Pb and Zn, respectively. For the
determination of soil metal fractions, the sequential extraction procedure of Berna et al.
(2000) was employed. This procedure subdivides metals into 5 operationally defined
fractions: (i) MgCl2-extractable fraction (soluble/exchangeable); (ii) NaOAc-extractable
fraction (carbonates), which is assumed to recover metals associated with carbonates; (iii)
NH2OH·HCl+HCl-extractable fraction (FeMnOxides), which contains metals associated
with the reducible Fe oxides and Mn oxides; (iv) H2O2-extractable fraction (OM), which
retains metals complexed by OM; and (v) HF+HCl-extractable fraction (residual) in
which crystalline minerals are dissolved and metals constituting the lattices solubilised. In
our soil, Cd was mainly bound to OM (37%) and Fe/MnOxides (29%); 62% of Pb was in
the Fe/MnOxides fraction; 45% of Zn was bound to carbonates (Figure 1). On average,
higher percentage values were found in the soluble/exchangeable (26%) than in the
residual fraction (14%).
Figure 10.1 : Soil metal (Cd, Pb and Zn) fractions according to sequential extraction: MgCl2-extractable (SOLUBLE/EXCHANGEABLE); NaOAc-extractable (CARBONATES); NH2OH·HCl+HCl-
extractable (FeMnOxides); H2O2-extractable (OM); and HF+HCl-extractable (RESIDUAL).
For this study, plant consortia consisting of 1-3 pseudometallophytes with
different metal-tolerance strategies (hyperaccumulator: Thlaspi caerulescence; accumulator:
Rumex acetosa; excluder: Festuca rubra) were used. T. caerulescens J. & C. Presl. and R. acetosa
L. seeds of the local Lanestosa ecotypes were collected from the “Txomin” mine and then
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germinated for two and one months, respectively, on a mixture of perlite and vermiculite
(2:3 v/v, moistened with deionized water) in a growth chamber under the following
conditions: 20/16 ºC day/night temperature, 70% relative humidity, and a photosynthetic
photon flux density of 300 µmol photon m-2 s-1 by supplementing natural illumination
with white cold lamps. Subsequently, seedlings (see treatments below) were transferred to
study pots (14 cm diameter x 10 cm height) containing 800 g FW (20% humidity) of the
mine soil. F. rubra L. was seeded (0.05 g of seeds for each T. caerulescens or R. acetosa
seedling; seeds were obtained from “Zulueta Corporación para la Naturaleza”, Spain)
directly in the study pots. In a preliminary experiment carried out under the same
greenhouse conditions described below, it was found that, after two months of growth,
the addition of 0.05 g of F. rubra seeds to our soil resulted in a similar biomass to that
obtained for each T. caerulescens or R. acetosa seedling at the end of the greenhouse
experiment (see below). This was done to compensate for the different growth rates
presented by the three pseudometallophytes, in an attempt to achieve a similar biomass of
each pseudometallophyte at the end of the experiment.
Eight treatments were conducted in triplicate: (1) T: T. caerulescens alone (six
seedlings); (2) R: R. acetosa alone (six seedlings); (3) F: F. rubra alone (0.30 g of seeds); (4)
T+R: 50% T. caerulescens (three seedlings) + 50% R. acetosa (three seedlings); (5) T+F:
50% T. caerulescens (three seedlings) + 50% F. rubra (0.15 g of seeds); (6) R+F: 50% R. acetosa (three seedlings) + 50% F. rubra (0.15 g of seeds); (7) T+R+F: one third T. caerulescens (two seedlings) + one third R. acetosa (two seedlings) + one third F. rubra (0.10
g of seeds); and (8) C: control unplanted pots. Plants were then allowed to grow for two
months in a soft polyethylene-covered greenhouse (Venlo-type) located in Derio (Biscay)
at a latitude of 43º 17’ N, a longitude of 2º 52’ W and an altitude of 65 m above sea-level.
The climate in this region is Atlantic temperate. Minimal temperature set points
controlling air-heating were 14/18 ºC night/day and maximal temperature set points were
18/20 ºC night/day. Vent opening temperatures were 20/25 ºC night/day. During the
experiment, average temperature was 17/29 ºC night/day, average relative humidity 55%,
and average photosynthetically active radiation 454 µmol photon m-2 s-1. Throughout the
experimental period, plants were bottom watered periodically as needed.
10.3.2 Plant parameters
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After two months of growth, shoots were harvested separately for each species and
washed thoroughly with deionized water. Shoot fresh weights (FW) were recorded and,
subsequently, plant material was oven-dried at 70 ºC for 48 h to determine dry weights
(DW). Subsamples (0.4 g) of dried shoot tissue were digested with a mixture of
HNO3/HClO4 (Zhao et al., 1994) and Cd, Pb and Zn in the digest were determined using
AAS.
10.3.3 Soil physicochemical and microbial properties
For analysis of physicochemical parameters, rhizosphere soil was collected (by
gently shaking off the soil that adhered to roots), air-dried at 30 ºC for 48 h, sieved to <2
mm, and stored at 4 ºC until analysis. Soil pH (1:2.5 w/v, soil:water) was measured
following standard methods (MAPA, 1994). Water-soluble organic carbon (WSOC) was
extracted by shaking soil (horizontal shaker at 175 rpm) with distilled water (1:5 w/v) for
1 h. Then, 3.5 ml of chromium reagent [chromium (VI) oxide (0.06% w/v); sulfuric acid
(65% v/v)] were added to 2 ml of extract and incubated at 150 ºC for 60 min. Organic C
concentration was determined colorimetrically at 445 nm. Total concentrations of heavy
metals in soil were determined as above. For the estimation of metal bioavailability, CaCl2-
extractable (0.01 M) metal fractions in soil were determined following Houba et al. (2000)
and then analyzed by AAS.
For analysis of microbial parameters, rhizosphere soil was sieved to <2 mm and
stored fresh at 4 ºC until analysis. Regarding enzyme activities (they can be used as
indicators of the functional status or condition of the soil environment) (Naseby and
Lynch, 2002), dehydrogenase activity (EC 1.1) was determined according to Taylor et al.
(2002). β-glucosidase (EC 3.2.1.21), arylsulphatase (EC 3.1.6.1) and acid phosphatase (EC
3.1.3.2) activities were determined according to Dick et al. (1996) and Taylor et al. (2002),
as described in Epelde et al. (2008a). Urease (EC 3.5.1.5) activity was determined
according to Kandeler and Gerber (1988), as described in Rodríguez-Loinaz et al. (2008).
Microbial biomass C was measured by the fumigation-extraction method (Vance et
al., 1987) assuming an extractability of 0.38 (Wu et al. 1990).
Microbial functional diversity was determined through community level
physiological profiles (CLPPs) with Biolog EcoplatesTM, which reflect the potential of the
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After two months of growth, shoots were harvested separately for each species and
washed thoroughly with deionized water. Shoot fresh weights (FW) were recorded and,
subsequently, plant material was oven-dried at 70 ºC for 48 h to determine dry weights
(DW). Subsamples (0.4 g) of dried shoot tissue were digested with a mixture of
HNO3/HClO4 (Zhao et al., 1994) and Cd, Pb and Zn in the digest were determined using
AAS.
10.3.3 Soil physicochemical and microbial properties
For analysis of physicochemical parameters, rhizosphere soil was collected (by
gently shaking off the soil that adhered to roots), air-dried at 30 ºC for 48 h, sieved to <2
mm, and stored at 4 ºC until analysis. Soil pH (1:2.5 w/v, soil:water) was measured
following standard methods (MAPA, 1994). Water-soluble organic carbon (WSOC) was
extracted by shaking soil (horizontal shaker at 175 rpm) with distilled water (1:5 w/v) for
1 h. Then, 3.5 ml of chromium reagent [chromium (VI) oxide (0.06% w/v); sulfuric acid
(65% v/v)] were added to 2 ml of extract and incubated at 150 ºC for 60 min. Organic C
concentration was determined colorimetrically at 445 nm. Total concentrations of heavy
metals in soil were determined as above. For the estimation of metal bioavailability, CaCl2-
extractable (0.01 M) metal fractions in soil were determined following Houba et al. (2000)
and then analyzed by AAS.
For analysis of microbial parameters, rhizosphere soil was sieved to <2 mm and
stored fresh at 4 ºC until analysis. Regarding enzyme activities (they can be used as
indicators of the functional status or condition of the soil environment) (Naseby and
Lynch, 2002), dehydrogenase activity (EC 1.1) was determined according to Taylor et al.
(2002). β-glucosidase (EC 3.2.1.21), arylsulphatase (EC 3.1.6.1) and acid phosphatase (EC
3.1.3.2) activities were determined according to Dick et al. (1996) and Taylor et al. (2002),
as described in Epelde et al. (2008a). Urease (EC 3.5.1.5) activity was determined
according to Kandeler and Gerber (1988), as described in Rodríguez-Loinaz et al. (2008).
Microbial biomass C was measured by the fumigation-extraction method (Vance et
al., 1987) assuming an extractability of 0.38 (Wu et al. 1990).
Microbial functional diversity was determined through community level
physiological profiles (CLPPs) with Biolog EcoplatesTM, which reflect the potential of the
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germinated for two and one months, respectively, on a mixture of perlite and vermiculite
(2:3 v/v, moistened with deionized water) in a growth chamber under the following
conditions: 20/16 ºC day/night temperature, 70% relative humidity, and a photosynthetic
photon flux density of 300 µmol photon m-2 s-1 by supplementing natural illumination
with white cold lamps. Subsequently, seedlings (see treatments below) were transferred to
study pots (14 cm diameter x 10 cm height) containing 800 g FW (20% humidity) of the
mine soil. F. rubra L. was seeded (0.05 g of seeds for each T. caerulescens or R. acetosa
seedling; seeds were obtained from “Zulueta Corporación para la Naturaleza”, Spain)
directly in the study pots. In a preliminary experiment carried out under the same
greenhouse conditions described below, it was found that, after two months of growth,
the addition of 0.05 g of F. rubra seeds to our soil resulted in a similar biomass to that
obtained for each T. caerulescens or R. acetosa seedling at the end of the greenhouse
experiment (see below). This was done to compensate for the different growth rates
presented by the three pseudometallophytes, in an attempt to achieve a similar biomass of
each pseudometallophyte at the end of the experiment.
Eight treatments were conducted in triplicate: (1) T: T. caerulescens alone (six
seedlings); (2) R: R. acetosa alone (six seedlings); (3) F: F. rubra alone (0.30 g of seeds); (4)
T+R: 50% T. caerulescens (three seedlings) + 50% R. acetosa (three seedlings); (5) T+F:
50% T. caerulescens (three seedlings) + 50% F. rubra (0.15 g of seeds); (6) R+F: 50% R. acetosa (three seedlings) + 50% F. rubra (0.15 g of seeds); (7) T+R+F: one third T. caerulescens (two seedlings) + one third R. acetosa (two seedlings) + one third F. rubra (0.10
g of seeds); and (8) C: control unplanted pots. Plants were then allowed to grow for two
months in a soft polyethylene-covered greenhouse (Venlo-type) located in Derio (Biscay)
at a latitude of 43º 17’ N, a longitude of 2º 52’ W and an altitude of 65 m above sea-level.
The climate in this region is Atlantic temperate. Minimal temperature set points
controlling air-heating were 14/18 ºC night/day and maximal temperature set points were
18/20 ºC night/day. Vent opening temperatures were 20/25 ºC night/day. During the
experiment, average temperature was 17/29 ºC night/day, average relative humidity 55%,
and average photosynthetically active radiation 454 µmol photon m-2 s-1. Throughout the
experimental period, plants were bottom watered periodically as needed.
10.3.2 Plant parameters
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culturable portion of the heterotrophic microbial community to respond to C substrates
(Bending et al., 2004), following Epelde et al. (2008a). Average well colour development
(AWCD) was calculated at a 44 h incubation time (at approximately this incubation time,
the highest rate of microbial growth was observed in the Biolog EcoPlatesTM).
Soil samples for DNA analysis were sieved to < 2 mm and stored fresh at -20 ºC.
DNA was extracted from soil samples (0.25 g FW) using Power SoilTM DNA Isolation
Kit (MO BIO Laboratories, California) according to manufacturer’s specifications. Prior
to DNA extraction, soil samples were washed twice in 120 mM K2HPO4 (pH 8.0) to
wash away extracellular DNA from soil without loss of intact cells (Kowalchuk et al.,
1997). In this way, most of the extracted DNA comes from live bacterial cells
(nonetheless, a small fraction of the extracted DNA might be associated with unlysed
dead cells or extracellular DNA not completely washed from the soil samples)
(Kowalchuk et al., 1997). With this extracted DNA, real-time PCR and PCR-DGGE were
carried out.
Real-time PCR was done to quantify rhizosphere bacterial and fungal biomass. For
amplification of rRNA gene fragments, Ba519f/Ba907r and Fung5f/FF390r primers
(Lueders et al., 2004a, b) were used for bacteria and fungi, respectively. Each 25 μl
reaction contained 5 μl of template, 12.5 μl of ABsolute QPCR SYBR green 2 x reaction
mix (AbGene, Epsom, UK), 0.25 μl of each primer (30 μM), 2.5 μl bovine serum albumin
(BSA, 40 mg ml-1) and 4.5 μl of water. Standards were made from full-length PCR-
amplified 16S rRNA or 18S rRNA genes from pure bacterial and fungal isolates,
respectively, following Yergeau et al. (2007a). All mixes were made using a CAS-1200
pipetting robot (Corbett Research, Sydney) to reduce variation caused by pipetting errors.
PCR conditions were: 95 ºC for 15 min; 94 ºC for 30 s; 52 ºC (48 ºC for fungi) for 30 s;
72 ºC for 60 s (40 cycles); and melt curve from 65 to 98 ºC. PCR amplification and
product quantification were performed using the Rotor-Gene 3000 (Corbett Research).
rRNA gene copies were quantified against the standard curve using ROTOR-GENE 6.
For the determination of microbial structural diversity, PCR-DGGE (denaturing
gradient gel electrophoresis) was carried out. Bacterial and fungal rDNA was amplified by
using F968-GC/R1378 (Heuer et al., 1997) and FR1-GC/FF390 (Vainio and Hantula,
2000) primer pairs, respectively. All PCRs were carried out in 25 μl volumes containing
2.5 μl of 10 x PCR buffer, 0.5 μl of each primer (30 μM), 2.5 μl of dNTPs mix (2 mM)
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and 3.5 U μl-1 of Expand high fidelity polymerase (Roche, Mannheim). Amplifications
were carried out on a PTC-200 thermal cycler (MJ-Research, Waltham). PCR conditions
for bacteria were: initial denaturation at 94 ºC for 2 min; 92 ºC for 30 s; 55 ºC for 1 min;
68 ºC for 45 sec (+1 sec cycle-1; 35 cycles) and extension at 68 ºC for 5 min. Conditions
for fungi were: initial denaturation at 94 ºC for 4 min; 92 ºC for 30 s; touchdown 55 ºC to
47 ºC for 1 min; 68 ºC for 45 sec (+1 sec cycle-1; 40 cycles) and extension at 68 ºC for 10
min. All DGGE analyses were done with a D-Code Universal Mutation Detection System
(Bio-Rad, Hercules) with a denaturating gradient of 45 to 65% for bacteria and 40 to 55%
for fungi (100% denaturant is defined as 7 M urea and 40% v/v formamide). DGGE was
performed using 20 µl of the PCR product in 0.5 x TAE buffer at 60 ºC (1 x TAE = 40
mM Tri-acetate, 20 mM sodium acetate, 1 mM EDTA, pH 8.0). Gradient gels were
topped with 10 ml of acrylamide containing no denaturant. Electrophoresis was
performed at 200 V for 15 min followed by 70 V for an additional 16 h. Electrophoresis
gels were stained with ethidium bromide and digital images captured using an ImaGo
apparatus (Gentaur, Brussels) upon UV transillumination. Banding patterns were
normalized with respect to standards of known composition and dendrogram
construction was performed using Imagemaster elite program 4.20 (Amersham
Bioscience, Rosendaal).
Richness (S) and Shannon’s diversity (H’) (Magurran, 2004) were calculated from
data on enzyme activities, CLPPs (S = number of substrates with an absorbance value
>0.25 at a 44 h incubation time) and DGGE (S = band number; abundance values were
obtained from band intensity) according to Mijangos et al. (2006, 2009). Areas under
AWCD curves (see below) were calculated following a trapezoidal approximation
(Guckert et al., 1996).
10.3.4 Soil ecosystem health
A methodology to link the concept of soil health to that of ecosystem health is here
proposed. To this aim, values of soil microbial properties were assigned to the three
attributes of ecosystem health abovementioned: vigor, organization, and
resilience/stability. We propose the following soil microbial properties for: (i) VIGOR:
overall enzyme activity (OEA), as indicator of the soil´s overall catalytic capacity (it was
calculated from the values of β-glucosidase, acid phosphatase, arylsulphatase and urease,
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as follows: the highest value for each enzyme activity was considered as 100; the other
values were transformed accordingly; finally, the average of all four enzyme activities was
calculated); area under AWCD curve, as indicator of the soil´s overall functional-catabolic
capacity; microbial biomass C, as indicator of the soil´s capacity to support microbial growth;
productivity of sorghum, as indicator of the soil´s capacity to support plant growth (see
below); (ii) ORGANIZATION: S and H’ from enzyme activities, as indicator of functional-
catalytic diversity; S and H’ from CLPPs, as indicator of functional-catabolic diversity; S and H’ from bacterial and fungal PCR-DGGE, as indicator of structural-genotypic diversity; and
(iii) STABILITY: resistance and resilience indexes calculated (see below), after transient heating
at 40 oC or copper (Cu) amendment, from data on soil basal respiration and nitrification potential rate (NPR).
Values of all these soil properties were scaled from 1 to 10 (1 = lowest value; 10 =
highest value). Within each attribute, mean values of the proposed soil properties were
calculated. Overall ecosystem health was determined as the mean of the three attributes.
For the essay on sorghum productivity, at the end of the experiment, rhizosphere
soil was collected from the pots. Twenty-five seeds of Sorghum bicolor x sudanense were
directly seeded in pots (9 cm diameter x 7 cm height) containing 200 g FW of this soil and
incubated under the same greenhouse conditions described above. In a preliminary
experiment, sorghum plants proved capable of growing in our metalliferous soil. Ten days
after seeding, germination rate was determined. Twenty days later, sorghum shoots were
harvested and their FW recorded. Shoots were then oven-dried at 70 ºC for 48 h to
calculate DW.
Similarly, at the end of the experiment, rhizosphere soil was collected from the
pots to carry out a soil stability experiment following a modification of Griffiths et al.
(2000): 6 replicates of fresh soil (each equivalent to 50 g DW) from each treatment were
incubated under dark in airtight jars at 30 ºC and a water holding capacity (WHC) of 60%,
for preconditioning purposes, during 1 week. Subsequently, two of the replicates were
heat-stressed at 40 ºC for 18 hours and then left unwatered (disturbance: “heat wave +
drought”); another two replicates were amended with 600 mg Cu kg-1 DW soil as CuCl2
(the addition of the water-dissolved CuCl2 increased the WHC up to 80%) (disturbance:
“Cu-amendment”); the remaining two replicates were left untreated as controls (for
comparison purposes, water was added to the soil to adjust the WHC to 80%). Twenty
evaluation of the efficiency of metal phytoremediation processes with microbioloGical indicators of soil health
208
208
208
days later, WHC was adjusted to 80% in one of the two heat-stressed replicates
(disturbance: “heat wave”). Thus, three different types of disturbance were studied: (1)
Cu-amendment (persistent disturbance); heat wave + drought (persistent disturbance),
and heat wave (transient disturbance). Soil basal respiration and NPR were determined in
all 6 jars according to ISO 16072 Norm and ISO 15685 Norm, respectively, at 20 and 60
days of incubation. From the values of soil basal respiration and NPR, resistance (RS) and
resiliency (RL) indexes were calculated (Orwin and Wardle, 2004):
where D0 is the difference between control (C0) and disturbed at 20 days, while Dx is
the difference between control and disturbed at 60 days of incubation. These indexes are
bounded by -1 and +1, a value of +1 meaning maximal resistance or resilience.
In Cu-amended soils, the bioavailable fraction of Cu was determined (0.01 M CaCl2
as extractant) by AAS throughout the incubation time, as a possible decrease in
bioavailable Cu concentration could modify data interpretation (however, bioavailable Cu
concentration did not vary throughout the experimental period and then data are not
shown). Likewise, WSOC was measured at the end of the incubation (60 days), to
determine its possible effect on values of soil basal respiration and NPR.
10.3.5 Statistical analysis
Differences among treatments were analyzed by one-way ANOVA using Microsoft
Stat View Software (SAS Institute). Tukey Kramer-test was used to establish the
significance of the differences among means. Pearson’s correlations were calculated using
SPSS Programme (Inso Corporation).
10.4 Results
10.4.1 Plant parameters and soil properties
At the end of the experiment, T. caerulescens biomass was significantly higher in T+F
than in T or T+R pots (Table 10.1). Similarly, significantly highest values of F. rubra
biomass were observed in T+F pots. Although differences were not statistically
( ) 12
)(0
0 −+
=x
x DDD
tRL( )00
00
21)(
DCD
tRS+
−=
10. links between pseudometallophytes and rhizosphere microbial communities in a metalliferous soil
209
209
209
significant, highest values of R. acetosa biomass were found in T+R pots (on average, 19
leaves per R. acetosa plant were observed in T+R pots versus 12 in R pots). Regarding plant
height, F. rubra plants reached a mean value of 24 cm in T+R pots versus only 13 cm in F
pots and 10 cm in both R+F and T+R+F pots.
Table 10.1. Shoot biomass and Zn concentration achieved by each pseudometallophyte in the different treatments at the end of the experiment. Values followed with different letters are significantly different
(P<0.05 or lower) according to Tukey Kramer-test. Mean values (n = 3) ± standard errors.
T. caerulescens R. acetosa F. rubra
Shoot biomass (g DW plant-1)
T 0.27 ± 0.07a
R 0.57 ± 0.03a
F 0.12 ± 0.01a
T+R 0.26 ± 0.02a 0.93 ± 0.02a
T+F 0.54 ± 0.04b 0.52 ± 0.03b
R+F 0.81 ± 0.11a 0.11 ± 0.01a
T+R+F 0.42 ± 0.01ab 0.77 ± 0.05a 0.14 ± 0.01a
Shoot Zn concentration (mg Zn kg-1 DW)
T 364 ± 37a
R 374 ± 32a
F 154 ± 12a
T+R 417 ± 48a 428 ± 10a
T+F 399 ± 18a 149 ± 8a
R+F 339 ± 33a 145 ± 9a
T+R+F 541 ± 38a 404 ± 64a 158 ± 5a
With regard to plant metal accumulation, negligible values of Cd and Pb shoot
concentration were found in the three pseudometallophytes. As far as Zn is concerned
(Table 10.1), significantly higher values of Zn shoot concentration in T. caerulescens were
observed in T+R+F (541 mg Zn kg-1 DW) than in T pots (364 mg Zn kg-1 DW). By
contrast, no significant differences were observed among treatments regarding Zn shoot
concentration in R. acetosa and F. rubra (on average, R. acetosa accumulated 386 mg Zn kg-1
DW shoot while F. rubra accumulated 152 mg Zn kg-1 DW shoot). Concerning the total
evaluation of the efficiency of metal phytoremediation processes with microbioloGical indicators of soil health
210
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210
amount of Zn phytoextracted from the soil (shoot metal concentration x shoot biomass)
(Figure 10.2), highest values were found in T+R pots (1.51 mg), closely followed by R
(1.26 mg) and T+R+F (1.10 mg) pots. On the contrary, only 0.11 mg of Zn were
phytoextracted in F pots.
Figure 10.2: Amount of Zn extracted under each treatment. Values followed with different letters are significantly different (P<0.05 or lower) according to Tukey Kramer-test.
On the other hand, no significant differences were observed among treatments
regarding soil total or bioavailable metal concentrations (data not shown).
Regarding correlations between pseudometallophytes composition and soil
physicochemical properties, soil pH was significantly lower (P<0.001) when R. acetosa was
present in the pots (pH = 4.6 and 5.1 in the presence and absence of R. acetosa,
respectively). A positive correlation was found between soil pH and biomass of T. caerulescens (R = 0.657, P<0.020) and R. acetosa (R = 0.677, P<0.016). A positive
correlation was observed between soil pH and WSOC (R = 0.467, P<0.021).
10. links between pseudometallophytes and rhizosphere microbial communities in a metalliferous soil
211
211
211
T
able
10.2
: Valu
es o
f enz
yme
activ
ities
in th
e di
ffer
ent t
reat
men
ts a
t the
end
of t
he e
xper
imen
t. O
vera
ll E
nzym
e A
ctiv
ity (O
EA
) was
calc
ulat
ed fr
om th
e va
lues
of
β-gl
ucos
idas
e, ac
id p
hosp
hata
se, a
rylsu
lpha
tase
and
ure
ase,
as fo
llow
s: th
e hi
ghes
t valu
e fo
r eac
h en
zym
e ac
tivity
was
con
sider
ed a
s 100
; the
oth
er v
alues
wer
e tra
nsfo
rmed
acc
ordi
ngly;
fina
lly, t
he m
ean
of a
ll fo
ur e
nzym
e act
iviti
es w
as c
alcul
ated
. Valu
es fo
llow
ed w
ith d
iffer
ent l
ette
rs a
re si
gnifi
cant
ly di
ffere
nt (P
<0.
05 o
r lo
wer
) acc
ordi
ng to
Tuk
ey K
ram
er-te
st. M
ean
valu
es (n
= 3
) ± st
anda
rd e
rror
s.
D
ehyd
roge
nase
β-
Glu
cosi
dase
Ar
ylsu
lpha
tase
Ac
id p
hosp
hata
se
Ure
ase
(m
g IN
TF
kg-1 2
0 h-
1 ) (m
g ρ-
Nitr
ophe
nol k
g-1 h
-1)
(mg
N-N
H4+
kg-
1 h-
1 ) O
EA
Con
trol
41.3
± 0
.00*
81
.7 ±
1.2
9a
1.90
± 0
.07a
18
85 ±
122
.1ab
13
9 ±
3.7
2a
86 ±
3ab
T
42.2
± 0
.00*
82
.7 ±
2.3
6a
2.01
± 0
.07a
18
90 ±
37.
3a
134
± 4
.73a
b 87
± 2
a
R
42.6
± 0
.00*
98
.2 ±
6.8
4a
1.51
± 0
.09b
19
12 ±
141
.5a
120
± 7
.96a
bcd
83 ±
3ab
c
F <
40
82.0
± 8
.72a
1.
65 ±
0.0
5ab
1794
± 1
28.0
ab
131
± 2
.06a
bc
81 ±
4ab
c
T+R
<
40
94.4
± 7
.11a
1.
40 ±
0.0
4b
1473
± 1
7.6a
b 10
8 ±
1.4
6bcd
73
± 1
abc
T+F
52
.6 ±
6.6
5a
81.3
± 2
.74a
1.
41 ±
0.0
5b
1635
± 3
4.0a
b 10
6 ±
2.0
4cd
72 ±
2bc
R+F
58
.2 ±
4.1
4a
82.0
± 6
.63a
1.
43 ±
0.0
6b
1377
± 1
7.1b
10
4 ±
5.0
0cd
69 ±
2c
T+R
+F
<40
91
.7 ±
7.3
8a
1.33
± 0
.06b
14
76 ±
24.
8ab
102
± 5
.54d
71
± 1
c *O
nly
one
of th
e re
plica
tes w
as a
bove
det
ectio
n lim
it
evaluation of the efficiency of metal phytoremediation processes with microbioloGical indicators of soil health
212
212
212
With regard to enzyme activities (Table 10.2), values for dehydrogenase were below
detection limit in F, T+R and T+R+F pots. β-glucosidase values showed no significant
differences among treatments (this activity was positively correlated with soil bioavailable
Zn concentration; R = 0.499, P<0.013). Control and T pots showed significantly higher
values of arylsulphatase than all the other pots. T and R pots had significantly higher
values of acid phosphatase than R+F pots (Table 10.2). Lastly, control pots showed
significantly higher values of urease than T+R+F pots. Three enzyme activities were
negatively correlated with the number of pseumetallophytes present in the pots: acid
phosphatase (R = -0.659, P<0.001), arylsulphatase (R = -0.731, P<0.001) and urease (R =
-0.800, P<0.001). These three enzyme activities showed a positive correlation with soil
pH (R = 0.415, P<0.044 for acid phosphatase; R = 0.581, P<0.003 for arylsulphatase; R
= 0.533, P<0.007 for urease) and WSOC (R = 0.765, P<0.001 for acid phosphatase; R =
0.452, P<0.027 for arylsulphatase; R = 0.586, P<0.003 for urease). Values of OEA were
higher in control pots and in those with only one pseudometallophyte, as compared to
those with 2-3 pseudometallophytes.
Table 10.3: Values of microbial biomass carbon (MBC), and fungal and bacterial abundance as
determined by real-time PCR. F:B ratio: ratio of fungal to bacterial abundance. Values followed with different letters are significantly different (P<0.05 or lower) according to Tukey Kramer-test. Mean values
(n = 3) ± standard errors.
MBC Fungi Bacteria F:B ratio
(mg C kg-1 DW soil) (107 copies g-1 DW soil)
Control 226 ± 15.4a 1.26 ± 0.58a 46.41 ± 15.87a 0.024 ± 0.003a
T 240 ± 0.7ab 1.00 ± 0.27a 42.72 ± 11.52a 0.024 ± 0.004a
R 264 ± 38.4ab 1.97 ± 1.01a 14.03 ± 1.33a 0.126 ± 0.055a
F 316 ± 15.5ab 1.43 ± 0.77a 70.34 ± 42.87a 0.029 ± 0.007a
T+R 251 ± 16.0ab 1.20 ± 0.58a 42.45 ± 27.92a 0.058 ± 0.019a
T+F 262 ± 8.2ab 0.97 ± 0.34a 47.31 ± 25.84a 0.032 ± 0.009a
R+F 285 ± 13.9ab 1.76 ± 0.13a 55.34 ± 3.77a 0.032 ± 0.001a
T+R+F 340 ± 8.5b 2.74 ± 1.41a 131.09 ± 79.26a 0.026 ± 0.003a
T+R+F pots had significantly higher values of microbial biomass C than control
pots (Table 10.3). No significant differences were found among treatments regarding
10. links between pseudometallophytes and rhizosphere microbial communities in a metalliferous soil
213
213
213
bacterial and fungal abundances calculated from real-time PCR (Table 10.3). Although
differences were not statistically significant, highest values of fungal and bacterial
abundances were observed in T+R+F soils. Bacterial and fungal abundances were
positively correlated among each other (R = 0.820, P<0.001) and followed similar trends,
except for R pots. In R pots, lowest values of bacterial abundance and concomitant
highest values of F:B (fungal abundance: bacterial abundance) ratio were observed
(differences were not statistically significant).
Figure 10.3 shows the AWCD curves obtained from Biolog EcoplatesTM. At 44 h of
incubation, values of AWCD in T+F and T pots were significantly higher than in C and R
pots. A positive correlation was found between values of AWCD and biomass of T. caerulescens (R = 0.694, P<0.012) and F. rubra (R = 0.712, P<0.009). On the contrary, no
significant differences were found among treatments regarding values of area under the
AWCD curves (data not shown). A positive correlation was found between area under
AWCD curves and biomass of T. caerulescens (R = 0.658, P<0.020) and F. rubra (R = 0.653,
P<0.021). Values of area under AWCD curves and AWCD at 44 h incubation were
positively correlated with soil pH (R = 0.477, P<0.019 for area under AWCD curves; R =
0.591, P<0.002 for AWCD at 44 h).
Figure 10.3: Average well colour development (AWCD) curves for each treatment. Mean values (n = 3).
evaluation of the efficiency of metal phytoremediation processes with microbioloGical indicators of soil health
214
214
214
Regarding S and H’ calculated from enzyme activities, no significant differences
among treatments were observed (Table 10.4). Values of S and H’ from enzyme activities
were negatively correlated with soil bioavailable Zn concentration (R = -0.568, P<0.004
for S; R = -0.569, P<0.004 for H’). In contrast, S and H’ from CLPPs (Table 10.4) did
show some significant differences among treatments: highest and lowest values of S and
H’ were found in T+F and R pots, respectively. Concerning S and H’ calculated from
PCR-DGGE for bacteria and fungi (Table 10.4), no significant differences among
treatments were observed.
Table 10.4: Richness (S) and Shannon´s diversity (H’) indexes calculated from enzyme activities, CLPPs
and DGGE (both bacterial and fungal) data. Values followed with different letters are significantly different (P<0.05 or lower) according to Tukey Kramer-test. Mean values (n = 3) ± standard errors.
Enzymes CLPPs DGGE
S H’ S H’ S-Bact H’-Bact S-Fungi H’-Fungi
Control 4.33 ± 0.27a 2.09 ± 0.09a 19.33 ± 0.54abc 4.09 ± 0.04abcd 19.00 ± 0.47a 4.17 ± 0.03a 13.00 ± 0.82a 3.50 ± 0.10a
T 4.33 ± 0.27a 2.10 ± 0.09a 24.33 ± 1.52bab 4.39 ± 0.07ab 17.00 ± 1.89a 3.94 ± 0.15a 11.67 ± 1.09a 3.34 ± 0.13a
R 4.33 ± 0.27a 2.09 ± 0.08a 14.33 ± 1.09c 3.67 ± 0.06c 14.33 ± 1.19ª 3.75 ± 0.12a 10.00 ± 1.25a 3.10 ± 0.20a
F 4.00 ± 0.00a 1.99 ± 0.01a 21.33 ± 2.60abc 4.18 ± 0.16abd 13.00 ± 1.63a 3.58 ± 0.17a 12.33 ± 0.54a 3.43 ± 0.04a
T+R 4.00 ± 0.00a 1.99 ± 0.00a 19.00 ± 0.47bc 4.04 ± 0.05abcd 15.67 ± 0.98a 3.88 ± 0.09a 11.33 ± 0.27a 3.39 ± 0.02a
T+F 4.67 ± 0.27a 2.20 ± 0.09a 26.67 ± 0.27a 4.50 ± 0.02a 14.67 ± 0.72a 3.79 ± 0.07a 12.00 ± 0.82a 3.35 ± 0.10a
R+F 4.67 ± 0.27a 2.20 ± 0.09a 18.33 ± 1.09bc 4.01 ± 0.07bcd 14.67 ± 1.66a 3.78 ± 0.16a 12.00 ± 0.47a 3.40 ± 0.03a
T+R+F 4.00 ± 0.00a 1.99 ± 0.01a 17.00 ± 0.82bc 3.83 ± 0.06cd 16.67 ± 0.98a 3.97 ± 0.08a 13.00 ± 1.25a 3.43 ± 0.12a
10.4.2 Soil ecosytem health
10.4.2.1 Sorghum productivity essay
The rate of sorghum germination was significantly higher in control and R pots (6.9-
and 5.5-fold higher, respectively), as compared to all the other pots. Similarly, productivity
values were significantly higher in control (7.7-fold) and R (7.6-fold) pots, as compared to
all the other pots.
10. links between pseudometallophytes and rhizosphere microbial communities in a metalliferous soil
215
215
215
T
able
10.5
: Valu
es o
f soi
l res
istan
ce a
nd re
silien
cy in
dexe
s, ca
lculat
ed fr
om re
spira
tion
and
NPR
dat
a, in
all t
reat
men
ts at
the
end
of th
e exp
erim
ent,
whe
n su
bjec
ted
to th
ree
diffe
rent
type
s of d
istur
banc
e: (i)
Cu-
amen
dmen
t; (ii
) hea
t wav
e-dr
ough
t; an
d (ii
i) he
at w
ave
(see
text
). V
alues
follo
wed
with
diff
eren
t let
ters
are
signi
fican
tly
diffe
rent
(P<
0.05
or l
ower
) acc
ordi
ng to
Tuk
ey K
ram
er-te
st (l
ower
cas
e let
ters
: am
ong
treat
men
ts; u
pper
cas
e let
ters
: am
ong
dist
urba
nces
). So
il re
spira
tion
valu
es
follo
wed
with
an
aste
risk
are
signi
fican
tly d
iffer
ent (
P<0.
05 o
r low
er) a
ccor
ding
to T
ukey
Kra
mer
-test
as c
ompa
red
to th
eir c
orre
spon
ding
NPR
valu
es. M
ean
valu
es
(n =
2) ±
stan
dard
err
ors.
R
ESI
STAN
CE
R
ESI
LIE
NC
Y
C
u-am
endm
ent
Hea
t wav
e-dr
ough
t &
H
eat w
ave
Cu-
amen
dmen
t H
eat w
ave-
drou
ght
Hea
t wav
e
R
esp.
N
PR
Res
p.
NPR
R
esp.
N
PR
Res
p.
NPR
R
esp.
N
PR
Con
trol
0.75
± 0
.01a
A*
0.53
± 0
.02a
A
0.39
± 0
.05a
B 0.
38 ±
0.0
9aA
0.04
± 0
.00a
A*
-0.4
7 ±
0.0
3aA
0.04
A
-0.4
8A
0.99
B -0
.26A
T
0.89
± 0
.03a
A
0.57
± 0
.06a
A
0.35
± 0
.06a
B 0.
29 ±
0.0
7aA
-0.3
1 ±
0.1
1aA
-0.5
5 ±
0.0
9aA
-0.1
0A
-0.1
5A
0.88
A
-0.1
0A
R
0.93
± 0
.01a
A*
0.38
± 0
.01a
bA
0.46
± 0
.04a
B 0.
33 ±
0.0
6aA
-0.6
9 ±
0.0
3aA*
0.26
± 0
.05a
A
-0.1
9A
0.17
A
0.31
A
0.00
A
F 0.
86 ±
0.0
3aA*
0.26
± 0
.03b
A
0.25
± 0
.02a
B 0.
23 ±
0.0
5aA
-0.3
7 ±
0.0
6aA
0.20
± 0
.23a
A
0.12
A
0.06
A
0.82
A
0.39
A
T+R
0.
91 ±
0.0
5aA*
0.40
± 0
.03a
bA
0.22
± 0
.02a
B 0.
21 ±
0.0
2aA
0.07
± 0
.34a
A
-0.0
7 ±
0.1
1aA
0.06
A
0.51
A
0.98
A
0.71
A
T+F
0.
75 ±
0.0
0aA*
0.32
± 0
.04a
bA
0.42
± 0
.05a
B 0.
43 ±
0.1
7aA
-0.2
8 ±
0.0
0aA*
0.09
± 0
.01a
A
-0.1
3B
0.47
B 0.
99C
0.28
AB
R+F
0.
83 ±
0.1
0aA*
0.22
± 0
.02b
A
0.19
± 0
.01a
B 0.
32 ±
0.0
4aA
-0.2
0 ±
0.0
1aA
-0.2
0 ±
0.0
5aA
0.11
B -0
.15A
0.
84C
-0.2
5A
T+R
+F
0.81
± 0
.00a
A*
0.26
± 0
.01b
A
0.23
± 0
.02a
B 0.
57 ±
0.0
6aA
-0.3
5 ±
0.0
7aA
0.01
± 0
.07a
A
0.01
A
0.05
A
0.72
A
0.55
A
evaluation of the efficiency of metal phytoremediation processes with microbioloGical indicators of soil health
216
216
216
10.4.2.2 Soil stability
Resistance and resilience indexes calculated from basal respiration and NPR data are
presented in Table 10.5. Regarding RS calculated from respiration data in Cu-amended
and heat-treated soils, no significant differences were observed among treatments.
Significantly lower values of RS calculated from respiration were found in heat-treated
versus Cu-amended soils (probably due to the 41% increase in WSOC observed in Cu-
amended soils).
As far as RS from NPR in Cu-amended soils is concerned, C and T soils showed
significantly higher values of RS than F, R+F and T+R+F soils. By contrast, no
significant differences in RS from NRP were found among treatments in heat-treated
soils. No significant differences in RS from NPR were observed between Cu-amended
and heat-treated soils.
Concerning RL (Table 10.5), in Cu-amended soils, no differences were found
among treatments. In “heat wave-drought” soils, highest values of RL were observed in F
soils when calculated from respiration data and in T+R soils when calculated from NPR
data. In “heat wave” soils, highest values of RL were observed in T and T+F soils when
calculated from respiration data and in T+R soils when calculated from NPR data. In
T+F and R+F soils, significantly higher values of RL were observed in “heat wave-
drought” and “heat wave” soils than in Cu-amended soils when RL was calculated from
respiration data. Likewise, RL calculated from soil respiration data were higher in “heat
wave” soils than in “heat wave-drought” soils (differences were statistically significant in
C, T+F and R+F). The addition of water to the “heat wave” soils led to a 30% increase in
WSOC (this parameter remained constant in “heat wave-drought” soils), resulting in a
stimulated soil microbial community.
10.4.2.3 Attributes of ecosystem health and overall ecosystem health
Control, T, R and F soils showed higher values of vigor than those soils where 2-3
pseudometallophytes were present (Table 10.6). Lowest and highest values of
organization were found in R and T+F soils, respectively. Lowest values of stability were
found in T and R soils. Highest values of stability were found in T+R soils. Finally, lowest
values of overall ecosystem health were found in R soils. Highest values of overall
ecosystem health were found in F and T+F soils.
10. links between pseudometallophytes and rhizosphere microbial communities in a metalliferous soil
217
217
217
Table 10.6: Soil vigor, organization, resiliency and overall health in the different treatments at the end of the experiment. Values were scaled from 1 to 10 (1 = lowest; 10 = highest).
Vigor Organization Resiliency Health
Control 5 6 5 5
T 5 6 4 5
R 5 3 4 4
F 6 4 7 6
T+R 3 4 8 5
T+F 4 7 7 6
R+F 4 6 5 5
T+R+F 4 4 6 5
10.5 Discussion
10.5.1 Soil and plant parameters
Although our metalliferous soil was only slightly polluted with metals, it did surpass
the reference critical values reported for the protection of ecosystems in the Basque
Country for soils of these characteristics (i.e., 0.8, 32.8 and 60.1 mg kg-1 for Cd, Pb and
Zn, respectively) (IHOBE, 1998). We selected for this study a metalliferous soil with a
low level of metal polution in order to be able to detect improvements in soil ecosystem
health in a short-term experiment such as ours.
In the “Txomin” mine, soil metal concentrations might be responsible for the
relatively high soil OM content, as OM accumulation in metal polluted soils might occur
due to metals impeding mineralization cycles (Chander and Brookes, 1991). As a
consequence of the scarce mineralization of OM, nutrient contents (N, P and K+) are also
very low in the “Txomin” mine soil. In metalliferous soils, microbial communities are
usually exposed to high levels of available toxic heavy metals (Figure 1), with concomitant
negative consequences for soil ecosystem functioning. In this respect, as reported by van
der Heijden et al. (2008), microbial diversity is likely to have the biggest impact on
ecosystem performance in nutrient poor ecosystems.
As far as plant biomass is concerned, growing together with T. caerulescens proved
stimulatory for the other two pseudometallophytes (Table 10.1). In previous works, we
confirmed the Zn hyperaccumulation capacity of the Lanestosa ecotype of T. caerulescens
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used in this study (Hernandez-Allica et al., 2006; Epelde et al., 2009b). In the current
work, total Zn concentration in soil was low and, consequently, shoot metal
concentration in T. caerulescens was much lower, not reaching the threshold value of 10,000
mg Zn kg-1 DW indicated by Baker et al. (2000) for Zn hyperacummulators. In any case,
it appears plausible that the stimulatory growth effect caused by T. caerulescens on the other
pseudometallophytes might be due to its metal phytoextraction: T. caerulescens showed
highest values of shoot Zn concentrations, but was closely followed by R. acetosa. We have
recently highlighted the potential of R. acetosa for Zn phytoextraction (Barrutia et al.,
2008). Unfortunately, one of the most important constraints for the utilization of T. caerulescens for metal phytoextraction is its low biomass production and slow rate of
growth. Actually, regarding total metal phytoextracted from soil, the greater shoot
biomass of R. acetosa, as compared to that of T. caerulescens, compensated for its lower
shoot metal concentration (Figure 10.2): R. acetosa, mainly in combination with T. caerulescens, phytoextracted the highest amounts of Zn from our soil (T+R was the best
option for phytoextraction).
F. rubra phytoextracted by far the lowest amount of Zn. This species might be a
good candidate for metal phytostabilization. Certainly, for phytostabilization, low values
of shoot Zn concentration are desired, as the risk of metals entering the food chain
decreases. The simultaneous utilization of both approaches (phytoextraction and
phytostabilization) for the phytoremediation of metal polluted sites appears an interesting
option, as metal uptake by phytoextracting plants does not seem to be diminished by the
presence of phytostabilizating plants.
Values of soil pH increased with increasing values of T. caerulescens and R. acetosa
biomass. In agreement with other works (Luo et al., 2000; Epelde et al., 2008a), metal
accumulation in T. caerulescens appears not to be achieved through soil acidification.
Regarding soil microbial properties, enzyme activities control the rates of soil
nutrient cycling and provide a unique integrative biological assessment of soil function,
especially those catalyzing a wide range of biological processes, such as dehydrogenase,
urease, phosphatase, etc. (Nannipieri et al., 2002). In our study, values of dehydrogenase
activity were most of the times below detection limits which indicates a very low level of
overall microbial activity in our soil. Except for β-glucosidase, in general, a negative
correlation was found between enzyme activities (and OEA) and number of
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pseudometallophytes present in the pots (Table 10.2). On the contrary, Yang et al. (2007)
found urease to be higher in two and four species mixtures compared to monoculture,
while no significant effects of species mixtures on acid and alkaline phosphatases or
dehydrogenase were observed.
Regarding CLPPs (Figure 10.3), no differences among treatments were found
regarding area under AWCD curves (nevertheless, T and T+F pots showed significantly
higher values of AWCD at 44 h). The area calculation procedure has the advantage of
collapsing the absorbance versus time curves down to a single value that integrates
information from the entire incubation period (it incorporates the lag phase, the rate of
development and the extent of dye development for each well) (Guckert et al., 1996). In a
study by Loranger-Merciris et al. (2006), three and four species mixtures had higher
culturable bacterial activity than monocultures and two species mixtures.
Remarkably, a positive correlation was observed between soil pH and many
microbial parameters (acid phosphatase, arylsulphatase, urease, OEA, AWCD, area under
AWCD curve). Similar results were reported by Wang et al. (2006), confirming the
character of master variable for soil pH.
Highest values of microbial biomass C were observed in T+R+F pots (Table 10.3).
Although differences were not statistically significantly, highest values of bacterial and
fungal abundances were also found in T+R+F pots (the three parameters, i.e. microbial
biomass C and bacterial and fungal abundances, followed similar patterns). Zak et al.
(2003) reported that plant communities influence soil microbial biomass mainly through
plant litter and root exudates rather than through plant diversity per se. In a study by Yang
et al. (2007), plant mixtures did not affect microbial biomass C.
Highest values of F:B ratio were found in R pots, suggesting a high fungal
abundance in the R. acetosa rhizosphere. The relative abundance of bacteria and fungi in
ecosystems receives a large amount of attention, but little is known about its functional
significance (van der Heijden et al., 2008). In general terms, bacteria-dominated food
webs might enhance rates of nutrient mineralization and availability of nutrients to plants,
whereas fungal-dominated food webs promote slow and highly conservative cycling of
nutrients (Wardle et al., 2004).
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From an ecological perspective, in the soil ecosystem, functional diversity, as
opposed to structural diversity, provides more relevant information (Torsvik and Øvreås,
2007). There are different methods to determine functional diversity of soil microbial
communities such as, for instance, enzyme activities (Larson et al., 2002) and CLPPs
(Preston-Mafham et al., 2002). In our study, enzyme activities responded negatively to soil
bioavailable Zn concentration. This negative correlation was not observed for total Zn
concentration, emphsizing the higher toxicity caused by bioavailable metals (as compared
to non-bioavailable metals). Concerning CLPPs, lowest values of S and H’ were found in
R soils, which could well be related to the high F:B ratios observed for this treatment.
Meanwhile, in agreement with AWCD data, highest values of S and H’ were observed in
T+F soils. In the work by Yang et al. (2007), soil microbial functional diversity was higher
under two and four species mixtures than under monocultures. The lack of correlation
between data on enzyme activities and CLPPs here found in not surprising, as Biolog
EcoPlatesTM reflect the potential of only the culturable portion of the heterotrophic
microbial community to respond to C substrates, while enzyme analyses reflect the status
of the whole microbial community.
The use of cultivation-independent methods, such as PCR-DGGE, removes the
bias imposed by techniques based on culturing organisms (Ellis et al., 2003). Indeed,
culture-independent methods take into account a greater complexity than that
traditionally studied with culture-dependent methods (Yang et al., 2001), although the
relevance of this fact in terms of ecosystem function is rarely discussed (McCaig et al.,
2001). In our study, no differences were found among treatments regarding bacterial or
fungal structural genotypic diversity (Table 10.4). In contrast, various studies have shown
that composition of soil microbial communities may vary markedly depending on
aboveground vegetation (Bardgett et al., 1998; Wardle et al., 1999), mainly through
development of beneficial rhizobacteria by the release of specific sugars and amino acids
into the rhizosphere (Kowalchuk et al., 2002).
10.5.2 Soil ecosystem health
Most interestingly, and to our knowledge in a pioneering way, a methodology to link
the concept of soil health to that of ecosystem health is here described. To this aim, we
propose to interpret the values of biological indicators of soil health (particularly, those
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related to the biomass, activity and diversity of the soil microbial communities) from the
point of view of the attributes measured when assessing ecosystem health: vigor,
organization and stability (Rapport, 1998), in an attempt to integrate many different soil
parameters within a single concept, i.e. overall ecosystem health. Although these types of
integrative approaches often entail loss of valuable information and an oversimplification
of the frequently overwhelming complexity of ecosystems, they are of great value for, and
mostly needed by, soil managers, legislators, conservation decision-takers and so on. Data
on ecosystem health must be analyzed from a environmental manager´s point of view,
more than from an ecologist´s perspective.
We propose vigor to be measured from values of OEA (enzyme activities provide a
unique integrative biological assessment of soil function), area under AWCD curves,
microbial biomass C and sorghum productivity (sorghum was chosen for productivity
essays in metalliferous soils due to its metal tolerance). Interestingly, soils with only one
pseudometallophyte showed higher values of vigor than those where 2-3
pseudometallophytes were present.
Organization refers to ecosystem complexity and is affected by both diversity of
species and number of pathways of material exchange between each component
(Costanza et al., 1998). Consequently, we propose organization to be measured from
values of S and H’ from enzyme activities, CLPPs and PCR-DGGE. Highest values of
organization were found in T+F soils, which also had highest values of overall ecosystem
health.
The concept of stability comprises both resilience, the property of the system to
recover after disturbance, and resistance, the inherent capacity of the system to withstand
disturbance (Lazzaro et al., 2006). There is a lot of confusion regarding the terminology
used in ecological stability studies, with a variety of terms, such as constancy, resilience,
persistance, resistance, elasticity, etc. used differently and often interchangeably in the
literature, but it is not within the scope of this manuscript to engage in a comparative
discussion on those terms (for a very interesting discussion on the topic, see Grimm and
Wissel, 1997). We propose stability (possibly the most important attribute of ecosystem
health in soils subjected to pollution) to be assessed through the integration of resistance
and resilience indexes calculated after disturbances (Cu-amendment; heat wave-drought;
heat wave) using soil respiration and NPR data. Interestingly, T+R showed the highest
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and lowest values of stability and vigor, respectively, indicating a lack of correlation
between different attributes of ecosystem health. On the other hand, regarding the
different patterns obtained when calculating RS from respiration versus NPR data, this is
not an unexpected results, since soil respiration is a measure of general activity while NPR
targets a much narrower process in terms of microbial phylogeny. Griffiths et al. (2001)
compared functional stability on paired grassland soils to which different environmental
impacts were applied (different levels of plant biodiversity, polluted versus non-polluted,
etc.). These authors reported that the polluted soil was less resistant to heat stress than
the corresponding non-polluted. On the other hand, there was an apparent delay in the
recovery of the one-species grassland soil, but it showed a greater resilience than the six-
species soil.
Finally, when averaging vigor, organization and stability to obtain a final value of
soil overall ecosystem health, no major differences among treatments were observed
(including control unplanted soils), indicating that the growth of the different
pseudometallophytes did not exert a clear overall beneficial effect on rhizosphere soil
health, which is understandable taking into account the short duration of our experiment.
Much further research is needed to: (i) unravel the links between aboveground
pseudometallophytes and belowground rhizosphere microbial communities in
metalliferous soils and (ii) properly quantify the improvement in soil ecosystem health
caused by pseudometallophytes growth in metalliferous soils.
10.6 Conclusions
As far as plant biomass is concerned, growing together with T. caerulescens proved
stimulatory for the other two pseudometallophytes, probably due to its metal
phytoextraction. R. acetosa, especially in combination with T. caerulescens, phytoextracted
the highest amounts of Zn from our metalliferous soil. Lowest values of microbial
functional diversity (S and H’), as reflected by the values of CLPPs obtained with Biolog
EcoplatesTM, were found in soils planted only with R. acetosa. Except for β-glucosidase, in
general, a negative correlation was found between values of enzyme activities and number
of pseudometallophytes present in the pots. Highest values of microbial biomass C were
observed in the presence of the three pseudometallophytes. Most interestingly, a
methodology to link the concept of soil health to that of ecosystem health is here
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proposed, assigning soil microbial properties to attributes of ecosystem health. Although
these types of integrative approaches often entail loss of valuable information and an
oversimplification of the frequently overwhelming complexity of ecosystems, they are of
great value for, and mostly needed by, soil managers, legislators, conservation decision-
takers and so on. When averaging vigor, organization and stability to obtain a final value
of soil overall ecosystem health, no major differences among treatments were observed
(including control unplanted soils), indicating that the growth of the different
pseudometallophytes did not exert a clear overall beneficial effect on rhizosphere soil
health.
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11. SÍNTESIS
La supervivencia de nuestra sociedad está ligada de forma inextricable a la salud del
suelo. Por desgracia, en las últimas décadas, se ha liberado al suelo una gran cantidad de
sustancias químicas contaminantes que están afectando seriamente la funcionalidad y
sostenibilidad de este recurso, convirtiéndose así en un problema medioambiental de
enorme repercusión y trascendencia. Por suerte, existen en la actualidad una serie de
tecnologías de descontaminación de suelos contaminados que presentan un enorme
potencial para paliar/solucionar la preocupante degradación de nuestros suelos derivada
de la acumulación de contaminantes. Dentro de estas tecnologías, en este trabajo se ha
profundizado en la fitorremediación, una fitotecnología que se basa en la capacidad de
algunas especies vegetales (y microorganismos asociados) para tolerar, absorber, acumular
y degradar compuestos contaminantes (Salt et al., 1995).
El marco conceptual en el que se sustenta este trabajo es la convicción de que el
objetivo último de un proceso fitorremediador de suelos contaminados no debe ser
solamente eliminar el contaminante o, en su defecto, reducir su concentración hasta los
límites marcados en la legislación, sino recuperar la salud del suelo (Epelde y cols., 2009a),
entendida ésta como la capacidad de este vital recurso para realizar sus funciones de
forma sostenible (Coleman y cols., 1998), desde una doble perspectiva antropocéntrica-
bio/ecocéntrica. En consecuencia, es indispensable disponer de un conjunto de
indicadores fiables y relevantes que nos permitan evaluar la salud del ecosistema edáfico,
para así poder monitorizar la eficacia de los procesos fitorremediadores de suelos
contaminados (Epelde y cols., 2008c). En este trabajo se ha optado por las propiedades
microbiológicas con potencial indicador de la salud del ecosistema edáfico, frente a las
propiedades físico-químicas tradicionales, en la firme creencia de que dichas propiedades
microbiológicas presentan ciertas ventajas como herramientas monitorizadoras de la
eficacia de procesos fitorremediadores, léase, su rapidez de respuesta, su mayor
sensibilidad, su carácter integrador, y la posibilidad de incorporar en ocasiones el
componente temporal a la evaluación de la funcionalidad del suelo, con el consiguiente
interés para los estudios sobre la sostenibilidad de este recurso (Mijangos y cols., 2009).
Dentro de la extensa casuística de la contaminación de los suelos, este trabajo ha
focalizado, aunque no exclusivamente, su atención a la contaminación por metales en
entornos mineros y a la utilización de especies pseudometalofitas para procesos
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fitoextractores y fitoestabilizadores. Las especies nativas pseudometalofitas propias de
entornos mineros presentan una elevada tolerancia a la presencia de concentraciones altas
de metal en suelo y son, asimismo, capaces de crecer en las condiciones adversas
habituales en estos entornos metalíferos (Becerril y cols., 2007). Ciertamente, la utilización
de estas especies nativas pseudometalofitas para fitotecnologías de revegetación y
recuperación de ecosistemas degradados y contaminados con niveles altos de metales es
una alternativa de gran interés (Becerril y cols., 2007).
En el entorno minero de Lanestosa (Bizkaia), a pesar de que los suelos están sin
duda contaminados con niveles muy elevados de Zn, Pb y Cd, se observa una gran
diversidad de flora; no obstante, muchas especies presentan bajas producciones
biomásicas y tasas de crecimiento lentas (Barrutia, 2008), lo cual es esperable en
organismos que han de dedicar gran parte de su maquinaria metabólica y energía a
sobrevivir en condiciones extremas (Salt y cols., 1995). Análogamente, los metales del
suelo afectan a la biomasa, actividad y diversidad de los microorganismos edáficos, si bien
éstos son también capaces de desarrollar mecanismos de tolerancia frente a dichos
compuestos tóxicos (Kelly y cols., 1999). Por otro lado, las plantas y las comunidades
microbianas edáficas están estrechamente relacionadas y el estudio de los vínculos entre
ambos compartimentos biológicos es un tema de indiscutible actualidad (Rodríguez-
Loinaz y cols., 2008). Por desgracia, existen pocos estudios focalizados en la comprensión
de dichos vínculos (“aboveground-belowground links”) que hayan sido realizados en
suelos contaminados (Phillips y cols, 2008; Yang y cols., 2007) y, en este momento, no
tenemos constancia de que alguno haya sido desarrollado en un entorno minero altamente
contaminado por metales (como es el caso de la mina de Lanestosa) en condiciones de
campo.
Por ello, en el Capítulo 4 se estudiaron consorcios de plantas, encontrados de forma
natural en la mina de Lanestosa, compuestos por 1-4 especies pseudometalofitas que
presentan diferentes estrategias de tolerancia a metales: hiperacumuladora: Thlaspi caerulescens; acumuladora: Jasione montana; indicadora: Rumex acetosa; exclusora: Festuca rubra.
Además de analizar la respuesta fisiológica y el potencial fitorremediador de estas
especies, se profundizó en los posibles vínculos entre las especies pseudometalofitas y sus
respectivas comunidades microbianas rizosféricas. Cuando crecía de forma individual (en
ausencia de las otras especies), Thlaspi caerulescens confirmó su capacidad para
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hiperacumular Zn (alcanzó concentraciones de Zn en tallo de hasta un 2.7%) y Pb
(concentración máxima en tallo: 0.14%), corroborando su potencial como especie de gran
interés para estudios/procesos de fitoextracción (McGrath y cols., 2001b; Lombi y cols.,
2002). Por su parte, Jasione montana y Rumex acetosa acumularon también cantidades
considerables de Zn y Pb. Rumex acetosa, especie indicadora según estudios previos
llevados a cabo en este mismo emplazamiento (Barrutia, 2008), no respondió como tal en
este trabajo, posiblemente debido a las elevadas concentraciones de metales presentes en
la zona de estudio. Finalmente, Festuca rubra sí mostró su carácter exclusor, lo cual
confirma su interés para procesos fitoestabilizadores. De acuerdo a los parámetros
fisiológicos cuantificados en este estudio, ninguna de estas cuatro especies
pseudometalofitas mostró síntomas fitotóxicos agudos (ratificando la ausencia de
síntomas visuales de fitotoxicidad que presentaban las plantas en la mina; no obstante,
como se ha mencionado anteriormente, los individuos de estas especies presentaban en
general por una reducida biomasa), lo cual confirma su tolerancia a los metales presentes
en la mina. Procede subrayar que Thlaspi caerulescens mostró algunas características
interesantes relacionadas con la tolerancia al estrés (Collin y cols., 2008), léase, niveles
elevados del ratio A+Z/VAZ y del contenido en tocoferol.
En este estudio (Capítulo 4), no se encontraron correlaciones entre la riqueza de
plantas pseudometalofitas y las propiedades del suelo estudiadas. Sin embargo, la mayoría
de las propiedades microbiológicas del suelo sí estuvieron positivamente correlacionadas
con la biomasa total de las plantas (la suma de las biomasas de todas las especies presentes
en el consorcio). En contraste, a medida que aumentaba la biomasa de Thlaspi caerulescens, se observaba un descenso de los valores de estas propiedades microbiológicas. Es
importante destacar aquí que las propiedades microbiológicas del suelo tuvieron un efecto
mayor sobre la biomasa vegetal que viceversa (35.2% frente a 14.9%). Por otra parte, la
biomasa de Rumex acetosa estuvo positivamente correlacionada con las actividades
enzimáticas del suelo y los valores de S (riqueza) y AWCD (desarrollo de color medio de
los pocillos) obtenidos con las placas Biolog EcoPlatesTM. La biomasa de Jasione montana
estuvo positivamente correlacionada con el carbono de la biomasa microbiana, mientras
que la biomasa de Festuca rubra aumentó en suelos con valores más altos de actividad
fosfatasa ácida, arilsulfatasa y deshidrogenasa. Al contrario, la biomasa de Thlaspi caerulescens aumentó en los suelos con valores más bajos de las propiedades
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microbiológicas estudiadas. Por último, las propiedades físico-químicas y microbiológicas
del suelo mostraron asimismo una fuerte correlación entre ellas.
En relación con la fitoextracción (o utilización de plantas para extraer metales de los
suelos y posteriormente acumularlos en los tejidos aéreos; potencialmente una de las
fitotecnologías de recuperación de suelos contaminados más prometedoras), en este
estudio se investigó asimismo en profundidad la capacidad de una de las especies
pseudometalofitas más interesantes identificadas en la mina de Lanestosa: el ecotipo local
de la especie hiperacumuladora de Zn y Cd Thlaspi caerulescens. De entre las numerosas
(más de 400) especies hiperacumuladoras descritas en la bibliografía (Brooks, 2000),
Thlaspi caerulescens ha sido propuesta como especie modelo para la investigación en
fitoextracción (Assunção y cols., 2003), habiendo sido ampliamente estudiada a este
respecto (Hernández-Allica y cols., 2006a,b; Epelde y cols., 2008a; McGrath y cols., 2006).
Como era esperable debido a su condición de especie hiperacumuladora (las especies
hiperacumuladoras son capaces de tolerar, absorber y acumular en sus tejidos altas
concentraciones de metales, extrayéndolos de forma eficiente del suelo; Assunção y cols.,
2003), el ecotipo Lanestosa de Thlaspi caerulescens demostró su potencial para procesos
fitoextractores de Zn y Cd. A este respecto, en los Capítulos 5 y 6 se muestran dos
estudios de fitoextracción en continuo realizados con este ecotipo. Las plantas de Thlaspi caerulescens demostraron a escala microcosmos su gran tolerancia a niveles elevados de
metales, su capacidad para crecer sin problemas en suelos contaminados por dichos
metales y, sobre todo, su capacidad para hiperacumular Zn y Cd en los tejidos aéreos.
Respecto a la concentración de metales en los suelos vegetados con Thlaspi caerulescens, se observó una disminución de Zn y Cd, tanto total como extractable en
CaCl2, que fue mayor a concentraciones más elevadas. En el Capítulo 5, los valores de
metales totales en suelo sufrieron una disminución más pronunciada que los
correspondientes valores de metal biodisponible (extractable), lo cual puede deberse a las
cinéticas de reposición de las fracciones metálicas disponibles y a la acumulación de metal
en las raíces de Thlaspi caerulescens (Whiting y cols., 2001; Hamer y Keller, 2002).
En el Capítulo 5, la contaminación por metales no causó una clara inhibición de las
actividades enzimáticas del suelo, considerando éstas de forma individual. Por otra parte,
los resultados de diversidad obtenidos a partir de los valores de las actividades enzimáticas
del suelo (diversidad catalítica) y los obtenidos a partir de los perfiles fisiológicos a nivel de
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comunidad (CLPPs; diversidad funcional-catabólica calculada con Biolog EcoPlatesTM) no
fueron concordantes: la presencia de metales en el suelo hizo disminuir significativamente
los valores del índice de diversidad Shannon (H’) obtenidos a partir de los valores de las
actividades enzimáticas y aumentar (aunque no significativamente) los valores de S y H’
obtenidos con las placas Biolog EcoPlatesTM. Sin embargo, éste no es un resultado
sorprendente: las actividades enzimáticas reflejan el estado de la comunidad microbiana
edáfica en su totalidad (en particular, el potencial catalítico de la comunidad microbiana
edáfica en condiciones óptimas de pH, concentración de substrato, temperatura, etc.),
mientras que las placas Biolog EcoPlatesTM reflejan la capacidad (potencial catabólico-
metabólico, funcional) de tan sólo la porción cultivable de la comunidad microbiana
heterótrofa para utilizar las 31 fuentes de carbono (donadores de electrones a la cadena de
transporte respiratoria) incluidas en las Biolog EcoPlatesTM (estos 31 substratos se dividen
en 5 familias químicas: aminas/amidas, aminoácidos, carbohidratos, ácidos carboxílicos y
polímeros). Cabe destacar aquí que la D-celobiosa, el ácido ketobutírico, el ácido D-
málico y la glucosa-1-fosfato fueron utilizados en mayor proporción en los suelos
vegetados con Thlaspi caerulescens y contaminados con metales que en el resto de
tratamientos (no vegetados y/o no contaminados). A este respecto, en plantas
hiperacumuladoras, los niveles de los ácidos cítrico, málico, malónico y oxálico se han
visto correlacionados con la presencia de elevadas concentraciones de Ni o Zn en su
biomasa (Lee y cols., 1978; Tolrá y cols., 1996). En cualquier caso, las plantas de Thlaspi caerulescens muestran constitutivamente concentraciones elevadas de ácido málico/malato
en sus tejidos (Shen y cols., 1997; Boominathan y Doran, 2003).
En el Capítulo 6, se detectó que la presencia de metales en el suelo afectaba a su
funcionamiento: la contaminación por Zn redujo los valores de respiración basal e
inducida por substrato, además de la abundancia de genes oxidadores de amonio (con
1.000 mg Zn kg-1). Análogamente, la presencia de Cd en el suelo hizo disminuir la
abundancia de genes de bacterias totales (con 50 y 250 mg Cd kg-1) y de oxidadores de
amonio (con 250 mg Cd kg-1). Es relevante mencionar que la abundancia de genes
oxidadores de amonio (la oxidación de amonio es el proceso limitante en la tasa de
nitrificación; Yuan y cols., 2005) estuvo positivamente correlacionada con los niveles de
nitrato en suelo. Asimismo, la contaminación por metales (Zn, Cd) afectó a la diversidad
estructural (DGGE) y funcional genética (microarray de genes funcionales Geochip): al
contrario que los parámetros de abundancia de genes y actividad biológica, el número de
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genes detectados en todas las categorías del microarray (léase, ciclo del nitrógeno,
carbono, azufre y fósforo; reducción y resistencia a metales; degradación de
contaminantes orgánicos) aumentaron en los suelos contaminados con metales frente a
los no contaminados. Análogamente, la redundancia funcional o número de variantes
detectados dentro de cada familia de genes estudiados en el Geochip (e.g., actividad
celulasa, resistencia al Zn), pareció aumentar en los suelos contaminados con metales
frente a los no contaminados.
En el Capítulo 5, se observó que como resultado del proceso fitoextractor (que
engloba tanto el crecimiento de Thlaspi caerulescens como la fitoextracción de metales
llevada a cabo por dicha especie hiperacumuladora), la actividad de cinco enzimas del
suelo con funciones clave en los ciclos del C, N, P y S (β-glucosidasa, ureasa, fosfatasa
ácida, fosfatasa alcalina, arilsulfatasa) aumentaba. De hecho, fue la presencia de Thlaspi caerulescens, más que la fitoextracción de metales en sí, la que tuvo mayor influencia en las
propiedades microbiológicas del suelo. En los suelos contaminados con metales, la
presencia de Thlaspi caerulescens hizo aumentar en un 154, 115, 140, 37 y 164% la actividad
β-glucosidasa, arilsulfatasa, fosfatasa ácida, fosfatasa alcalina y ureasa, respectivamente. En
numerosas ocasiones se ha descrito que los suelos vegetados presentan mayores tasas de
actividad microbiana, frente a los no vegetados, debido a la presencia de superficies
adicionales para la colonización microbiana y a los compuestos orgánicos liberados por
las raíces de las plantas (Tate, 1995; Delorme y cols., 2001).
Igualmente, en el Capítulo 6, se describe que la respiración basal e inducida por
substrato, así como la abundancia de genes de bacterias totales y de degradadores de
quitina, aumentaron significativamente en los suelos en los que Thlaspi caerulescens estaba
presente. Aunque la diversidad estructural genética (DGGE) no varió en los suelos
vegetados con Thlaspi caerulescens, el número de genes detectados en el microarray de genes
funcionales así como la redundancia funcional sí se vieron incrementados. La abundancia
de genes de resistencia a Zn y/o Cd fue mayor en presencia de Thlaspi caerulescens. Aunque
ya se pueden encontrar en la bibliografía estudios diversos sobre las comunidades
microbianas propias de los suelos contaminados con metales (Brim y cols., 1999; Sandaa y
cols, 1999b), la información sobre la composición de las comunidades microbianas
rizosféricas de plantas hiperacumuladoras es todavía muy escasa.
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Por desgracia, las plantas hiperacumuladoras como Thlaspi caerulescens tienen
habitualmente un baja producción de biomasa y tasas de crecimiento lentas (igualmente,
por el momento, desconocemos las prácticas agronómicas más adecuadas para optimizar
su crecimiento), lo cual dificulta sobremanera la viabilidad de los procesos de
fitoextracción en continuo. Por consiguiente, y al objeto de solventar asimismo el
inconveniente de tener que sembrar de nuevo la planta fitoextractora después de cada
cosecha, en el Capítulo 7, procedimos a investigar el potencial fitoextractor del sorgo, una
especie de características agronómicas conocidas, elevada biomasa y capaz de rebrotar
después de la cosecha. Así, se estableció un ensayo de fitoextracción en continuo con el
cultivar de gran biomasa y crecimiento rápido Sorghum bicolor x sudanense en un suelo
contaminado con Zn y Cd. Es interesante reseñar que la planta del sorgo tiene además
interés como cultivo energético para la producción de bioetanol, siendo esto una ventaja
que innegablemente debería tenerse en cuenta a la hora de considerar esta especie como
candidata para la fitoextracción: la aceptación y viabilidad de la fitoextracción como
tecnología descontaminadora de suelos contaminados con metales se vería
substancialmente incrementada en el caso de generar algún producto comercializable a
partir de la planta cosechada (de hecho, cualquier aspecto que sirva para aportar valor
añadido al proceso fitorremediador, casi siempre excesivamente dilatado en el tiempo, es
de gran valor a la hora de justificar la viabilidad de esta fitotecnología). Por ello, a ser
posible, las especies de plantas candidatas para la fitorremediación también deberían ser
evaluadas desde el punto de vista de su capacidad para realísticamente generar productos
que pudieran tener un valor económico como, por ejemplo, suplemento alimenticio,
acondicionador de suelo, aditivo energético, etc. (Bañuelos, 2006).
En nuestro estudio, las plantas de sorgo se mostraron altamente tolerantes a la
contaminación por metales, siendo capaces de lograr un buen crecimiento en su
presencia. Además, en las dos primeras cosechas de las tres que se realizaron en este
estudio, los valores de concentración de Cd en tallo excedieron los 100 mg Cd kg-1. En la
tercera cosecha, la acumulación de metal en tallo disminuyó, posiblemente debido a la
reducción observada en los valores de concentración de metal biodisponible en el suelo.
En este caso, al contrario a lo anteriormente mencionado para Thlaspi caerulescens, no se
observó ninguna reposición de las fracciones metálicas biodisponibles desde las fracciones
no biodisponibles.
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Por otra parte, en este ensayo de fitoextracción en continuo con sorgo, se observó
que, en los suelos contaminados con metales, la actividad deshidrogenasa se encontraba
correlacionada con las fracciones biodisponibles de dichos metales, pero no así con las
concentraciones totales correspondientes. En general, las propiedades microbiológicas
determinadas en este estudio (i.e., actividad deshidrogenasa, CLPPs, respiración basal,
respiración inducida por substrato-glucosa, respiración inducida por substrato-solución
modelo rizodepósito, cociente de respiración) mostraron valores más bajos en los suelos
contaminados con metales frente a los no contaminados. A este respecto, se ha descrito a
menudo que los metales influyen negativamente en las propiedades biológicas del suelo y,
por ende, en su funcionalidad (Kandeler y cols., 1996; Giller y cols., 1998; Kelly y Tate,
1998). Después de todo, es bien sabido que los metales pueden afectar negativamente al
crecimiento, morfología y metabolismo de los microorganismos del suelo mediante
perturbaciones de carácter funcional, desnaturalización de proteínas, destrucción de la
integridad membranal, etc. (Leita y cols., 1995).
Una vez más, en el ensayo de fitoextracción con sorgo, también se apreció un
incremento de los valores de las propiedades microbiológicas del suelo medidas en los
tratamientos vegetados, frente a los no vegetados, tal y como ocurría en los Capítulos 5 y
6. Al final del experimento de fitoextracción, los valores del AWCD y de los índices de
diversidad calculados a partir de datos obtenidos con las placas Biolog EcoPlatesTM, así
como los de respiración basal y respiración inducida por substrato-glucosa, fueron
similares en los suelos vegetados contaminados y en los vegetados no contaminados. Es
más, al aplicar el índice de Jaccard a los datos obtenidos con las placas Biolog
EcoPlatesTM, el valor más alto correspondió a la pareja “suelo vegetado contaminado-
suelo vegetado no contaminado”. En consecuencia, se puede concluir que, como
resultado del proceso de fitoextracción con sorgo, que incluye tanto el crecimiento de la
planta como la fitoextracción del metal propiamente dicha, se consiguió recuperar la
funcionalidad del suelo. En lo concerniente a la recuperación de la funcionalidad del suelo
derivada de cualquier proceso fitoextractor, un objetivo ideal razonable es volver a las
condiciones presente en un suelo control válido (léase, un suelo vegetado, no
contaminado de similares características edafoclimáticas).
Sin embargo, al final del experimento con sorgo, y de acuerdo al índice de
germinación con Lepidium sativum, se percibió que los suelos fitorremediados seguían
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siendo significativamente más fitotóxicos que los suelos control no contaminados. Esta
discrepancia entre los resultados obtenidos con el ensayo de germinación frente a los
obtenidos durante la determinación de las propiedades microbiológicas edáficas no es
sorprendente: al fin y al cabo, el ensayo de germinación refleja exclusivamente el efecto de
la contaminación por metales en una especie de planta específica (en este caso, Lepidium sativum), mientras que las propiedades microbiológicas muestran el estado de la
comunidad microbiana edáfica, por lo que no necesariamente tienen que comportarse de
idéntica forma.
Respecto a las propiedades físico-químicas del suelo estudiadas en este ensayo con
sorgo (pH, conductividad eléctrica, contenido en materia orgánica, nitrógeno total,
fósforo y potasio extraíble), se concluyó que no eran tan sensibles como las propiedades
microbiológicas para la evaluación del efecto de la contaminación sobre la funcionalidad
del suelo y de la eficiencia de los procesos fitoextractores.
Asimismo, algunos metales como el Pb tienen una baja disponibilidad en el suelo, lo
que supone una limitación crucial a la hora de plantear su fitoextracción. El
descubrimiento de que la aplicación de agentes quelantes al suelo aumentaba la toma y
translocación por parte de las plantas de metales como el Pb (Blaylock y cols., 1997) abrió
una nueva vía para la fitoextracción de metales de baja disponibilidad y, en particular, para
la utilización de cultivares de gran biomasa en procesos fitoextractores de suelos
contaminados. Sin embargo, por desgracia, muchos quelantes resultan ser tóxicos tanto
para las plantas como para los microorganismos del suelo, además de suponer un riesgo
medioambiental derivado de la concomitante lixiviación de los metales quelados hacia
aguas subterráneas. Por ello, en los últimos años, se ha investigado profusamente en la
búsqueda de quelantes medioambientalmente respetuosos para su aplicación en procesos
de fitoextracción inducida de metales de baja disponibilidad (Grčman y cols., 2003;
Alkorta y cols., 2004d). En el Capítulo 8 se muestra un estudio en el que se investigó el
potencial del EDTA (ácido etilendiaminotetraacético) y del EDDS
(etilendiaminodisuccinato) para la fitoextracción inducida por quelantes de Pb utilizando
plantas de cardo (Cynara cardunculus). El EDTA es un quelante poco biodegradable y
altamente soluble en suelo, por lo que presenta un alto riesgo de provocar efectos
medioambientales adversos debido a la movilización de metales y a su alta persistencia.
Por otra parte, el EDDS es fácilmente biodegradable, causando una menor lixiviación de
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metales. Finalmente, se estudiaron los posibles efectos que la adición de estos quelantes
pudieran tener sobre la comunidad microbiana edáfica.
El EDTA fue mucho más eficiente que el EDDS para la fitoextracción de Pb con
Cynara cardunculus (el EDTA tiene una mayor afinidad por el Pb). El EDTA se degrada
muy lentamente en el suelo (Lombi et al., 2001), mientras que el EDDS tuvo una vida
media de tan sólo 24 h en nuestro estudio. Al aplicarse a los suelos contaminados con Pb,
el EDDS causó una mayor fitotoxicidad sobre las plantas de cardo que el EDTA. En la
bibliografía se encuentran resultados contradictorios sobre la capacidad del EDDS para
inducir la acumulación de Pb en plantas. Ciertamente, diferencias en las condiciones
experimentales (e.g., especie de planta utilizada, presencia de otros metales, tipo de suelo,
tiempo de exposición y cosecha, etc.) pueden explicar algunos de estos resultados
contradictorios (Grčman y cols., 2003; Kos y Leštan, 2003; Santos y cols., 2006).
Como el Pb es un metal poco biodisponible, no era de esperar que tuviera un efecto
negativo considerable sobre la microbiota del suelo. Efectivamente, la presencia de Pb en
el suelo no tuvo influencia en diversos parámetros indicadores de actividad microbiana
(léase, actividad deshidrogenasa, nitrógeno potencialmente mineralizable, respiración basal
y respiración inducida por substrato). Es más, la presencia de Pb tuvo un efecto positivo
en los valores de S y H’ obtenidos a partir de placas Biolog EcoPlatesTM. Este aumento de
los valores obtenidos a partir de los CLPPs en respuesta a la presencia de metales en el
suelo también se observó en otros estudios del presente trabajo (e.g., Capítulo 5). A este
respecto, se puede especular que la presencia de metales en el suelo induce la aparición de
poblaciones microbianas “estrategas r”, cultivables y de rápido crecimiento.
Por otro lado, el EDDS resultó ser menos tóxico para la comunidad microbiana
edáfica que el EDTA. En los suelos no contaminados con Pb, el EDTA tuvo un impacto
negativo en la actividad de la comunidad microbiana edáfica, como queda reflejado en su
efecto inhibitorio sobre la respiración basal y la actividad deshidrogenasa (el EDDS
también causó una disminución, aunque menor, de la respiración basal). Tanto en los
suelos no contaminados con Pb como en los contaminados, la adición de EDDS produjo
un aumento de los valores S, H’ y AWCD (este último también aumentó al añadir EDTA)
calculados a partir de datos obtenidos con placas Biolog EcoPlatesTM. La menor toxicidad
del EDDS hacia los microorganismos del suelo se podría explicar por el hecho de que el
EDDS es una sustancia natural que se degrada rápidamente en otros compuestos más
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benignos (Grčman y cols., 2003). En conclusión, aunque el EDDS tenga una menor
capacidad que el EDTA para inducir la fitoextracción de Pb en plantas de cardo, presenta
a su vez las importantes ventajas de su rápida biodegradación y menor toxicidad hacia la
comunidad microbiana edáfica.
En cualquier caso, en suelos con muy altas concentraciones de metales como suele
ser el caso de suelos mineros, la fitoextracción no parece en estos momentos una
tecnología viable debido al tiempo excesivamente largo requerido para disminuir la
concentración de dichos metales en el suelo hasta niveles aceptables (generalmente,
décadas). Por ello, en la actualidad, para estos casos se propone la fitoestabilización (o la
utilización de plantas para reducir la disponibilidad de los metales en el suelo y evitar así
su dispersión) como fitotecnología alternativa. Normalmente, la fitoestabilización se
combina con la aplicación de enmiendas orgánicas al objeto de aumentar el pH del suelo,
incrementar su contenido en materia orgánica, reducir la biodisponibilidad de los metales,
añadir nutrientes para las plantas, etc. (Alvarenga y cols., 2009a, b). Este tipo de
fitotecnología se puede asimismo denominar fitoestabilización asistida (Alvarenga y cols.,
2009a, b) o quimiofitoestabilización (Knox y cols., 2000). A este respecto, es importante
considerar el beneficio añadido que conlleva la reutilización de residuos orgánicos a modo
de enmienda. No obstante, no hay que olvidar que la aplicación de estas enmiendas debe
hacerse siempre bajo un control exhaustivo de los posibles efectos adversos que dichas
adiciones (dependiendo sobre todo de la composición de la enmienda orgánica) puedan
causar sobre el funcionamiento del ecosistema edáfico, en general, y de las comunidades
microbianas, en particular. En el Capítulo 9 se muestran los resultados obtenidos en un
ensayo de quimiofitoestabilización llevado a cabo combinando la adición de una
enmienda sintética (CalcinitTM + urea + PK14% + carbonato cálcico) u orgánica (purín
de vacuno) con el crecimiento de la planta Lolium perenne en un suelo minero contaminado
con Zn, Pb y Cd.
La quimiofitoestabilización mejoró las propiedades del suelo y redujo la
biodisponibilidad y toxicidad de los metales presentes en el mismo. La adición de purín de
vacuno aumentó los valores de las actividades deshidrogenasa y β-glucosidasa, el
nitrógeno potencialmente mineralizable, el carbono de la biomasa microbiana y
parámetros obtenidos con las placas Biolog EcoplatesTM, por lo que se concluyó que
había favorecido el desarrollo de la actividad microbiana, junto con su biomasa y
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diversidad funcional. La reducción de la toxicidad, junto con los beneficios provocados
por la adición de nutrientes, permitieron el establecimiento de una cubierta saludable de
Lolium perenne. Por su parte, el desarrollo de la vegetación colaboró en la mejora de
propiedades físico-químicas edáficas clave (léase, pH, contenido en materia orgánica) de la
rizosfera, aumentando aún más los valores de algunas de las propiedades microbiológicas
estudiadas, tales como la biomasa, actividad y diversidad funcional de la comunidad
microbiana rizosférica. En este ensayo, al igual que en muchos otros de los descritos en
este trabajo, se encontraron correlaciones entre las propiedades microbiológicas y físico-
químicas (e.g., pH, contenido en materia orgánica) del suelo. Es de destacar que la
actividad fosfatasa ácida estuvo negativamente correlacionada con el contenido de fósforo
extraíble del suelo, indicando muy probablemente una inhibición por retroalimentación.
En los suelos tratados con la enmienda sintética, se obtuvieron valores más altos de
actividad específica deshidrogenasa y β-glucosidasa, sugiriendo una respuesta de estrés a la
adición de dicha enmienda. A este respecto, Killham (1985) indicó que los
microorganismos del suelo sometidos a estrés pueden derivar la energía inicialmente
destinada al crecimiento hacia funciones de mantenimiento celular, lo que podría explicar
los valores más altos de actividad por unidad de biomasa observados en este estudio. Esta
toxicidad/estrés causado por la enmienda sintética no se observó en los suelos vegetados
con Lolium perenne, posiblemente debido a los conocidos efectos beneficiosos de las
plantas sobre la salud del suelo.
Nuestro procedimiento quimiofitoestabilizador disminuyó el riesgo de
entrada/incorporación de los metales a la cadena trófica, ya que la adición de la enmienda
orgánica condujo a niveles menores de metales en tallo (niveles por debajo de los límites
establecidos para consumo por herbívoros). A partir de los datos encontrados en este
estudio, se concluyó que la quimiofitoestabilización es una alternativa de gran interés para
la remediación de suelos mineros degradados: la mejora en la propiedades del suelo
derivada de la aplicación de enmiendas (e.g., aumento del pH, aporte de nutrientes, etc.)
favorece la implantación de una cubierta vegetal (revegetación) con los beneficios que ello
conlleva.
Curiosamente, la práctica totalidad de los estudios de fitorremediación se llevan a
cabo empleando una única especie de planta fitorremediadora. Sin embargo, la idea de
utilizar consorcios de especies de plantas que presenten distintas estrategias de tolerancia a
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los metales merece sin duda nuestro interés, ya que a priori parece factible que las ventajas
e inconvenientes de cada especie puedan complementarse con las/los de las otras
especies. Entre otros aspectos a considerar, debemos tener en cuenta la posibilidad de
que la diversidad de las comunidades microbianas aumente como resultado del
incremento en la diversidad de especies vegetales (una mayor diversidad vegetal implica
una mayor heterogeneidad de exudados orgánicos, creación de nuevos nichos, etc.)
(Broughton y Gross, 2000; Stephan y cols., 2000). Una mayor biodiversidad se ha
asociado en numerosas ocasiones a una mayor resiliencia (estabilidad) del ecosistema
frente a perturbaciones externas (Sankaran y McNaughton, 1999; Griffiths y cols., 2000).
Basándonos en los datos obtenidos en el Capítulo 4, llevamos a cabo un ensayo (Capítulo
10) de fitorremediación de suelos contaminados con metales empleando consorcios de 1,
2 y 3 especies pseudometalofitas con distintas estrategias de tolerancia a metales
(hiperacumuladora: Thlaspi caerulescens; indicadora: Rumex acetosa; exclusora: Festuca rubra).
Con carácter pionero, en este estudio, se propuso vincular los conceptos de salud del
suelo (en base a propiedades físico-químicas y microbiológicas con potencial indicador) y
salud del ecosistema (en base a sus atributos: vigor, organización y resiliencia). Mientras
que el vigor se puede cuantificar en términos de productividad o rendimiento de materia y
energía en el sistema, la organización se refiere a la complejidad de los ecosistemas. Por
último, el concepto de estabilidad incluye tanto resiliencia (la capacidad del sistema para
recuperarse de una perturbación) como resistencia (la capacidad del sistema para soportar
una perturbación).
El crecimiento de las otras plantas presentes en el consorcio fue superior en
presencia de Thlaspi caerulescens. En lo que se refiere a la acumulación de metales, como era
de esperar, la especie que alcanzó concentraciones superiores de metales en tallo fue
Thlaspi caerulescens. Sin embargo, el mayor crecimiento de Rumex acetosa hizo que esta
especie fuera la que extrajera al final una mayor cantidad de Zn del suelo. Un consorcio
formado por Thlaspi caerulescens y Rumex acetosa parece entonces una opción digna de
estudio en profundidad para mejorar la viabilidad de los procesos actuales de
fitoextracción. Festuca rubra, por su parte, fue la especie que acumuló la menor cantidad de
metales en sus tejidos (es una especie exclusora), con la consiguiente minimización del
riesgo de incorporación de metales a la cadena trófica, por lo que esta especie parece una
opción interesante para procesos fitoestabilizadores. Una combinación de las tres especies
aquí estudiadas también sería interesante, ya que la toma y translocación de metales por
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parte de las plantas fitoextractoras (Thlaspi caerulescens y Rumex acetosa) no se vió disminuida
por la presencia de Festuca rubra.
En relación con las actividades enzimáticas del suelo (controlan los ciclos de
nutrientes y pueden, a su vez, aportar un visión integrada de la funcionalidad del
ecosistema edáfico), en nuestro estudio de utilización de consorcios de plantas
pseudometalofitas para procesos fitorremediadores, la mayoría de las veces la actividad
deshidrogenasa se encontró por debajo del límite de detección, lo que indica una actividad
biológica general del suelo muy baja. Excepto para la actividad β-glucosidasa, se encontró
una correlación negativa entre el número de plantas presentes en el consorcio y los
valores de actividades enzimáticas (también respecto a la actividad enzimática global;
OEA: overall enzyme activity). Por otra parte, en relación con los datos obtenidos con las
placas Biolog EcoplatesTM, no se hallaron diferencias significativas entre tratamientos
respecto al área englobada por las curvas de AWCD. Los valores más altos de carbono de
la biomasa microbiana se hallaron en el tratamiento que combinaba las tres especies de
plantas pseudometalofitas. Los valores más altos del ratio “abundancia
hongos/abundancia bacterias” se encontraron en los tiestos de Rumex acetosa, sugiriendo
una presencia elevada de hongos en la rizosfera de esta especie exclusora.
Desde un punto de vista ecológico, se considera que la diversidad funcional puede
aportar información de mayor relevancia que la diversidad estructural (Torsvik y Øvreås,
2007). En este estudio, la diversidad funcional se determinó a partir de valores de
actividades enzimáticas y datos obtenidos con las placas Biolog EcoplatesTM. En lo
referente a las placas Biolog EcoplatesTM, los valores más bajos de S y H’ se encontraron
en los suelos vegetados con exclusivamente Rumex acetosa, aspecto que podría estar
relacionado con los altos ratios “abundancia hongos/abundancia bacterias” hallados en
este mismo tratamiento. Por el contrario, los valores más altos de S y H’ a partir de placas
Biolog EcoplatesTM se encontraron en los suelos vegetados con Thlaspi caerulescens y Festuca rubra (tanto juntas como por separado). En lo que se refiere a la diversidad estructural, no
se encontraron diferencias entre tratamientos respecto a la diversidad genotípica de
bacterias u hongos.
Como se ha mencionado anteriormente, con carácter pionero, en este trabajo, se ha
propuesto una metodología para vincular el concepto de salud del suelo con el de salud
del ecosistema (en base a sus atributos: vigor, organización y resiliencia). El vigor se
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cuantificó a partir de los valores de: (i) OEA; (ii) área bajo las curvas de AWCD; (iii)
carbono de la biomasa microbiana; y (iv) productividad vegetal (sorgo). Los suelos con
una sola especie presente en el consorcio mostraron valores más altos de vigor. La
organización se midió, en este estudio, a partir de los valores de S y H’ obtenidos con datos
de actividades enzimáticas (diversidad catalítica), placas Biolog EcoplatesTM (diversidad
funcional-catabólica) y DGGE (diversidad estructural-genética). Los niveles más altos de
organización se encontraron en el tratamiento que combinaba Thlaspi caerulescens y Festuca rubra. Por otro lado, se obtuvieron distintos patrones de respuesta al calcular la resistencia a
partir de datos de respiración basal versus datos de tasa de nitrificación potencial, lo cual
no es en absoluto sorpredente pues la respiración del suelo es una medida de actividad
biológica general, mientras que la tasa de nitrificación potencial refleja un proceso
filogenéticamente mucho más estrecho. Los suelos vegetados conjuntamente con Thlaspi caerulescens y Rumex acetosa mostraron los valores más bajos y altos de vigor y estabilidad,
respectivamente, indicando una falta de correlación entre los distintos atributos de salud
del ecosistema. Al calcular la media estadística de los tres atributos de un ecosistema sano
aquí estudiados, al objeto de obtener un valor final integrado de “salud del ecosistema
edáfico”, no se encontraron marcadas diferencias entre tratamientos (incluido el control
no vegetado).
La integración de los bioindicadores de la salud del suelo en el concepto “salud del
ecosistema” supone un intento de salto conceptual hacia la elaboración de una evaluación
del ecosistema edáfico más completa y jerárquica. De todos los parámetros determinados
durante el desarrollo de este trabajo, se podrían considerar como medidas de vigor del
ecosistema edáfico los siguientes: (i) actividad enzimática global del suelo (OEA), (ii) el
nitrógeno potencialmente mineralizable, (iii) la respiración basal e inducida por substrato,
(iv) el AWCD obtenido con las placas Biolog EcoPlatesTM, (v) el carbono de la biomasa
microbiana, (vi) la abundancia de genes obtenida por PCR a tiempo-real y (vii) la
capacidad del suelo para soportar crecimiento de plantas (productividad vegetal).
Asimismo, proponemos que la organización del ecosistema edáfico puede cuantificarse
con los índices de (i) diversidad funcional, obtenidos a partir de actividades enzimáticas,
placas Biolog EcoPlatesTM y microarrays de genes funcionales (Geochip), y (ii) diversidad
estructural, obtenida a partir de datos de PCR-DGGE. Finalmente, en lo que a la
estabilidad del ecosistema edáfico se refiere, se requiere la realización de ensayos de
respuesta a estreses diversos (e.g., contaminación por metales, sequía, golpe de calor, etc.),
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para posteriormente evaluar la respuesta del ecosistema edáfico mediante la
determinación de parámetros biológicos con potencial indicador de la
salud/funcionamiento del ecosistema edáfico. Aunque este tipo de aproximaciones son
indudablemente una clara simplificación de una realidad ecológica mucho más compleja,
son a su vez necesarias y de gran utilidad para gestores, legisladores, etc.
Como se puede observar en los distintos capítulos aquí presentados, a pesar de que
en los ensayos a corto plazo realizados en este trabajo la eliminación de los metales del
suelo derivada de los procesos fitorremediadores no fue considerable, la sola presencia de
la planta fitorremediadora condujo a una estimulación significativa de las propiedades
microbiológicas del suelo, lo cual sugiere una posible mejora de la salud del ecosistema
edáfico. Este hecho enfatiza el beneficio que puede aportar la mera revegetación de los
suelos contaminados con metales con especies tolerantes. Aunque el presente trabajo se
ha centrado en la evaluación de la eficacia de técnicas fitorremediadoras mediante el
empleo de propiedades microbiológicas del suelo (más que en la fitorremediación en sí),
sería deseable en el futuro realizar ensayos de larga duración, para poder así estudiar la
respuesta de las comunidades microbianas edáficas a disminuciones importantes en el
contenido en metales del suelo.
Por otro lado, en el presente trabajo, se han desarrollado ensayos con suelo minero
(contaminación crónica con metales) y con suelo artificialmente contaminado con
metales, con las ventajas y desventajas que ambas alternativas conllevan. Ciertamente, el
suelo minero representa una situación real de contaminación, mientras que en el suelo
artificialmente contaminado los ensayos reflejan el impacto a corto plazo de los metales
sobre las comunidades microbianas edáficas (en cualquier caso, en los ensayos con suelo
artificialmente contaminado, siempre se ha respetado un período de estabilización más o
menos largo entre la adición de los metales al suelo y el establecimiento del ensayo). Sin
embargo, un suelo artificialmente contaminado te permite seleccionar concentraciones y
combinaciones de metales determinadas y, sobre todo, disponer de un suelo control no-
contaminado adecuado (algo, en ocasiones, muy difícil de conseguir en situaciones reales
de suelos contaminados).
A partir de los resultados obtenidos en los estudios incluidos en este trabajo, se
confirma que las propiedades microbiológicas del suelo son herramientas metodológicas
muy sensibles, de rápida respuesta y gran potencial para evaluar/monitorizar la eficacia de
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procesos fitorremediadores de suelos contaminados con metales. Para una correcta
evaluación de la salud del ecosistema edáfico utilizando estas propiedades microbiológicas
con potencial bioindicador es crucial evitar centrarse en un sólo parámetro indicador; se
debe determinar una batería diversa de parámetros en la que, en la medida de lo posible,
estén incluidos indicadores de biomasa, actividad y diversidad microbiana. Asimismo, es
recomendable combinar indicadores del estado general de la comunidad biológica del
suelo (e.g., respiración basal, actividad deshidrogenasa) con aquellos que se centran en
procesos clave específicos (e.g., nitrificación). Por otra parte, tanto las técnicas
consideradas más clásicas (e.g., actividades enzimáticas, carbono de la biomasa microbiana,
respiración basal e inducida por substrato) como otras más punteras (e.g., RT-PCR, PCR-
DGGE, microarrays de genes funcionales) han demostrado su utilidad y
complementariedad.
De la experiencia obtenida aquí durante la utilización de las propiedades
microbiológicas del suelo como bioindicadores potenciales de la salud del ecosistema
edáfico, se pueden extraer una serie de conclusiones de carácter práctico: de entre las
actividades enzimáticas determinadas, la deshidrogenasa presenta la ventaja de ser muy
sensible y presentarse exclusivamente en células viables; desgraciadamente, no es posible
detectar esta actividad en muchos suelos pues los valores están por debajo del límite de
detección. El resto de actividades enzimáticas estudiadas tienen un papel clave en los
principales ciclos biogeoquímicos (ciclos del C, N, P y S), lo cual permite obtener
información sobre el impacto de las perturbaciones (e.g., contaminación con metales,
proceso fitorremediador) en dichos ciclos biogeoquímicos. A la hora de medir la actividad
del suelo también hemos empleado en este trabajo medidas de respiración basal y de
potencial de nitrificación; este último es un proceso clave (keystone) filogenéticamente
mucho más estrecho que la respiración; el estudio de procesos clave facilita la
interpretación en relación con la evaluación del impacto de perturbaciones sobre la salud
del ecosistema edáfico.
En relación con la determinación de la biomasa microbiana, se ha observado una
buena correlación entre los diferentes métodos utilizados en este trabajo para medir este
parámetro, lo cual aporta credibilidad a dichas medidas [este parámetro se he medido en
este trabajo de las siguientes formas: carbono de la biomasa microbiana; respiración
inducida por substrato (biomasa microbiana potencialmente activa); y RT-PCR
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(abundancia de genes)]. Además, se ha medido la abundancia de genes tanto estructurales
(midiendo la cantidad de fragmentos de rRNA de bacterias y hongos) como funcionales
(copias de genes de oxidadores de amonio y degradadores de quitina). Si bien es cierto
que la biomasa estructural y funcional están interrelacionadas y es complicado separarlas
conceptualmente, la utilización de la abundancia de copias de genes con una función
determinada aporta más información a la hora de estudiar el impacto de perturbaciones
sobre la funcionalidad/salud de la comunidad microbiana edáfica y, por ende, del
ecosistema edáfico.
Por otro lado, la utilización de índices ecofisiológicos, e.g. cocientes entre medidas
de actividad biológica y medidas de biomasa (e.g., actividades enzimáticas específicas,
cociente de respiración microbiana) es altamente recomendable pues permite detectar
situaciones de estrés de la comunidad microbiana edáfica.
Las técnicas de estudio de la diversidad microbiana (placas Biolog EcoPlatesTM, PCR-
DGGE, Geochip) generan una enorme cantidad de datos. La aplicación de los índices de
diversidad y uniformidad de Shannon a estos datos, en general, no ha aportado
información de gran relevancia. Por el contrario, el índice de similitud de Jaccard ha
resultado muy útil para ver qué tratamientos se parecían más y cuáles eran más dispares.
Indudablemente, el potencial de los microarrays de genes funcionales (cubre más de 10.000
genes de más de 150 grupos) para medir biodiversidad no es comparable al de las placas
Biolog EcoPlatesTM. Sin embargo, a la hora de comparar/distinguir el efecto de distintos
tratamientos sobre las comunidades mcicrobianas edáficas, los CLPPs se presentan tan
válidos como el Geochip, además de ser más baratos y rápidos de analizar.
Por último, la estadística y, concretamente las técnicas de análisis multivariantes
(análisis de componentes principales, análisis de redundancia), resultan de gran utilidad a la
hora de interpretar los valores de las propiedades microbiológicas del suelo.
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Reflexiones finales
Durante los últimos años hemos profundizado en la posibilidad de utilizar una serie
de parámetros microbiológicos, habitualmente empleados en estudios pertenecientes al
campo de la Ecología Microbiana, como herramientas bioindicadoras/biomonitorizadoras
de la recuperación de la salud del ecosistema edáfico derivada de prácticas de
fitorremediación. Esto nos ha dado la oportunidad de familiarizarnos con una variedad de
técnicas fitorremediadoras enfocadas a la remediación de suelos contaminados con
metales. Aunque, tanto desde el punto de vista de la fitorremediación de suelos
contaminados con metales como en lo concerniente a la validez de los indicadores
microbiológicos para evaluar el impacto de la contaminación y monitorizar la eficacia de
procesos remediadores, los resultados parecen ciertamente prometedores, nos surgen una
serie de reflexiones que se presentan a continuación:
Si bien la fitorremediación es ciertamente una tecnología prometedora,
estéticamente agradable, no intrusiva, socialmente aceptada, ecológica y
medioambientalmente respetuosa y de bajo coste, en su estado actual de desarrollo, sigue
requiriendo plazos de tiempo muy superiores a otras técnicas de remediación con las que
inevitablemente compite y ha de competir en el futuro por su nicho/cuota de mercado
(en particular, el excesivamente largo periodo de tiempo requerido para alcanzar unos
niveles de recuperación aceptables sigue siendo el “talón de Aquiles” de la fitoextracción
de metales). En cualquier caso, parece claro que la casuística propia de cada
emplazamiento, el uso final destinado para el suelo, la naturaleza y el nivel de la
contaminación (tipo de contaminante, presencia simultánea de varios contaminantes,
concentraciones totales y disponibles), etc. tienen un papel determinante en relación con
la selección de la técnica (o técnicas) fitorremediadora a emplear. Posiblemente, de entre
las distintas estrategias de fitorremediación presentes en la actualidad, aquellas que
combinen la fitorremediación propiamente dicha con la obtención de productos que
aporten valor añadido al proceso (por ejemplo, la dendrorremediación con árboles para
luego obtener madera, además de secuestrar carbono; la utilización de plantas de interés
desde el punto de vista de la obtención de biocombustibles) serán las que tengan a largo
plazo mayor proyección comercial. Asimismo, consideramos que la
quimiofitoestabilización es una alternativa de futuro prometedor pues presenta el
interesante atractivo añadido de revalorizar residuos que, amén de disminuir la
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disponibilidad de metales en el suelo, aportan la materia orgánica y los nutrientes que
muchos suelos contaminados (e.g., suelos mineros) necesitan.
Por desgracia, la mayoría de los estudios de fitorremediación (como los aquí
incluidos) han sido realizados a escala microcosmos o a escala piloto en campo.
Innegablemente, llegados a este punto, es imperativo realizar más proyectos en campo a
gran escala para poder avanzar con solidez en el desarrollo de esta fitotecnología.
Uno de los impedimentos claros para el desarrollo de la fitorremediación (de hecho,
para cualquier tecnología de remediación de suelos contaminados) en numerosos países,
incluido el nuestro, es la facilidad que hoy en día existe para deshacerse de los suelos
contaminados en vertederos a bajo coste. En consecuencia, es indispensable que la
legislación limite la entrada de suelos contaminados a los vertederos a exclusivamente
aquellos casos en los que sea inevitable (como, por ejemplo, cuando dichos suelos
provoquen riesgos para la salud humana y/o no exista ninguna tecnología efectiva para su tratamiento).
Al fin y al cabo, el suelo es uno de nuestros recursos (no renovable a nuestra escala
temporal) más preciados y como tal debemos protegerlo frente a las numerosas amenazas
a las que está sometido, e.g. contaminación, erosión, sellado, salinización, etc. y
recuperarlo en la medida de lo posible cuando se encuentre en estado de degradación. No
debemos olvidar que el ecosistema edáfico nos provee de unos servicios (e.g., reciclaje de
nutrientes, descomposición de la materia orgánica, depuración de agua, eliminación de
contaminantes, etc.) de los que depende el bienestar de nuestra sociedad. Sin embargo, el
valor de estos servicios ecosistémicos no está por desgracia reconocido adecuadamente en los mercados económicos y las políticas de gestión medioambiental.
En cualquier caso, la metáfora de la “salud”, bien entendida (a este respecto, es
importante no caer en el error de considerar al suelo como un súper-organismo) y
aplicada, puede aportar una perspectiva de gran valor y utilidad para concienciar a la
sociedad en general y a los gestores de los suelos contaminados en particular, sobre la
imperiosa necesidad de mantener, proteger y recuperar este vital recurso. Como si de una
patología se tratara, y considerando al suelo como un paciente, frente a síntomas y signos
de que el ecosistema edáfico está sufriendo una “enfermedad” (como los que caracterizan
al conocido “síndrome de agotamiento del ecosistema”), el primer paso a seguir es la
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identificación de la etiología del síndrome (la causa de la enfermedad), la cual requiere una
caracterización exhaustiva del estado del paciente. Después, se debe realizar un
diagnóstico (conocer la naturaleza de la “enfermedad” mediante la observación de sus
síntomas y signos) y, a ser posible, una prognosis (conocimiento anticipado del
acaecimiento de la “enfermedad”). A continuación, se debe aplicar una terapia, como
puede ser la fitorremediación, para tratar de “curar la enfermedad” y, asimismo, establecer
un programa de seguimiento/monitorización de la evolución de la “enfermedad”, léase,
de la eficacia del tratamiento (por ejemplo, utilizando propiedades microbiológicas del
suelo como herramienta biomonitorizadora de la eficacia de la terapia fitorremediadora).
Por último, es necesario definir un valor umbral para los parámetros empleados durante la
monitorización de la evolución de la “enfermedad”, a partir del cual se considera que la
terapia ha tenido éxito y es posible interrumpir el tratamiento (por ejemplo, cuando los
parámetros indicadores medidos en el suelo fitorremediado se asemejen a los del suelo
control “sano”; por ejemplo, un suelo vegetado, no contaminado de similares
características edafoclimáticas). En cualquier caso, además de “curar” los suelos
contaminados, al igual que sucede con la salud humana, es vital abordar su prevención, i.e. frenar la preocupante contaminación que padece el suelo como consecuencia de la actividad humana.
Un aspecto crítico que diferencia la remediación y gestión de suelos contaminados
del tratamiento del agua o aire contaminado, es el hecho de que el suelo está generalmente
sujeto a derechos de propiedad (cosa que, por suerte, no ocurre ni con el agua ni con el
aire). En este sentido, un concepto innovador que podría ser de gran utilidad para
promover la conservación del suelo sería la creación de un “Banco de Suelos”, el cual
cuantificaría el valor económico de los servicios ecosistémicos que nos provee de forma
gratuita el suelo, antes y después de cualquier gestión o uso del mismo, y, basándose en un
sistema de préstamos y créditos, crearía un mercado de suelos en el que la moneda de
intercambio sería el valor económico en ese momento de dichos servicios ecosistémicos.
A este respecto, existen experiencias similares para promover la conservación de la
biodiversidad en Australia (“New South Wales BioBanking” y “Victorian Native
Vegetation Management Framework”). Ambos proyectos se centran sobre todo en los
profesionales de la construcción, donde éstos están obligados a proveerse de créditos de
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biodiversidad a través de un mecanismo de mercado para compensar la reducción de
diversidad que conlleva el desmonte de tierras y la construcción de edificios.
Respecto a la utilización de las propiedades microbiológicas del suelo como
bioindicadores de la salud del ecosistema edáfico y, en general, del empleo efectivo en la
práctica del concepto “salud del suelo”, el gran reto (todavía muy lejos de alcanzarse) es
definir con exactitud y precisión qué consideramos un “estado saludable” para un suelo determinado. Indudablemente, esta dificultad se deriva de la enorme heterogeneidad
espacio-temporal y complejidad (a nivel funcional, estructural y de respuesta) del
ecosistema edáfico. No hay que olvidar que las propiedades medibles suelen fluctuar en el
tiempo como resultado de perturbaciones naturales o mecanismos ecológicos internos.
Por otra parte, desde un punto de vista metodológico, la falta de métodos estándares de
análisis es un problema adicional de trascendencia a la hora de interpretar los resultados
de las propiedades microbiológicos aquí estudiadas. Asimismo, en aras de su deseable
incorporación a la metodología de evaluación de análisis de riesgo (herramienta de gran
valor para los gestores de suelos contaminados y en la que se apoya la legislación en esta
materia en muchos países), es imprescindible profundizar en la investigación sobre la
concordancia y coherencia entre datos ecotoxicológicos (obtenidos generalmente con
bioensayos que emplean organismos modelo acordados a este propósito) y ecológicos
(obtenidos, por ejemplo, como en este trabajo, mediante la aplicación de herramientas
metodológicas de la Ecología Microbiana). En este aspecto, es igualmente necesario
estudiar la correlación entre los datos obtenidos a diferentes niveles de organización
biológica (molecular, celular, organismo, población, comunidad, etc.) y con grupos
taxonómicos diversos.
Sea como fuere, los suelos contaminados y la fitorremediación son un escenario
ideal para profundizar en el funcionamiento del ecosistema edáfico, ese gran desconocido,
y en particular en las interacciones y vínculos entre las plantas y los microorganismos del
suelo. De hecho, los sistemas alterados/“enfermos” (e.g., suelos contaminados) son
frecuentemente escenarios idóneos para ahondar en el funcionamiento de los sistemas, tal
y como queda evidente en la aportación de la Medicina al conocimiento de la fisiología del
cuerpo humano.
Los microorganismos son los fundadores de la biosfera en la Tierra y juegan papeles
esenciales en el funcionamiento de los ecosistemas. En relación con el ecosistema edáfico,
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el conocimiento de la estructura y el funcionamiento de las comunidades microbianas es
crítico para entender el impacto de la contaminación sobre la salud y la sostenibilidad de
este recurso, y para evaluar con fundamento y relevancia ecológica el éxito de procesos
remediadores. Pero la abrumadora complejidad y diversidad de las comunidades
microbianas edáficas, junto con la no cultivabilidad de la mayoría de los microorganismos
del suelo, hace que la detección, caracterización y cuantificación microbiana en suelos sea
actualmente un desafío de grandes proporciones. Al igual que en muchas otras áreas de la
Biología, en los últimos años, la Biología Molecular ha provocado un avance enorme en el
desarrollo de la Ecología Microbiana. Los avances en este campo se suceden a una
velocidad a veces abrumadora: por ejemplo, hasta hace muy poco los microarrays de
DNA/RNA (e.g., Phylochip, Geochip) eran considerados una de las técnicas más
prometedoras para el estudio de la Ecología Microbiana Molecular; sin embargo, en este
momento, ya se empieza a hablar de la tecnología de secuenciación por paralelismo
masivo, capaz de dilucidar la secuencia de nucleótidos exacta de una muestra a una
velocidad vertiginosa (aproximadamente, 200.000 lecturas en 5 horas) como una
herramienta de mayor potencial. Por ello, es importante recordar que la
aplicación/utilización de innovadoras técnicas (moleculares) no debe ser un fin en sí
mismo sino un medio para responder a las cuestiones que nos planteemos durante el
estudio del ecosistema edáfico (en otras palabras, evitar el común error de estar
“movidos” por las nuevas técnicas, en vez de por las preguntas).
Estas nuevas técnicas nos ayudarán sin duda a profundizar en las consecuencias
funcionales que tienen los cambios en la composición y diversidad microbiana
encontrados habitualmente en los suelos contaminados. En presencia de elevadas
concentraciones de contaminantes en el suelo, es ciertamente posible que el supuesto alto
nivel de redundancia funcional propio de las comunidades edáficas no sea suficiente para
evitar una pérdida de funcionalidad, la cual puede acontecer siguiendo un patrón lineal,
exponencial, abrupto, etc. Una vez finalizada la perturbación (en este caso, la
contaminación del suelo), la comunidad edáfica, dependiendo de su resiliencia, puede
recuperarse y retornar al estado previo a la perturbación, derivar hacia otro estado de
equilibrio distinto, o ser incapaz de recuperarse anclándose en un permanente estado de
degradación que puede conducir al colapso irreversible del sistema.
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El establecimiento de Observatorios Microbianos (una red de emplazamientos
seleccionados donde se estudia la naturaleza de las comunidades microbianas y su
variabilidad y respuesta temporal-espacial frente a perturbaciones naturales y antrópicas y
gradientes medioambientales) en suelos “típicos” de ecosistemas diversos de una
determinada región es esencial para comprender mejor el funcionamiento y la dinámica de
las comunidades microbianas edáficas y, por ende, del ecosistema edáfico. Es deseable
que los Observatorios Microbianos incluyan emplazamientos contaminados, pues las
comunidades propias de muchos de estos lugares presentan propiedades singulares
derivadas de su adaptación a la contaminación, que pueden ser de interés, entre otras
cosas, para el desarrollo de tecnologías de remediación. En este contexto, es de gran
interés asimismo disponer de edafotecas completas de suelos (incluyendo suelos
contaminados) en las diferentes regiones, al objeto de beneficiarnos de la propiedad
historiográfica del suelo.
Independientemente de la abrumadora complejidad del ecosistema edáfico y en
particular de la red microcósmica autopoiética de la que depende su funcionalidad y
sostenibilidad, es vital que aquellos que nos dedicamos a su estudio sepamos simplificar,
sin por ello perder la esencia, dicha complejidad para poder trasmitir de forma eficaz a los
gestores del territorio y a la sociedad en general la enorme importancia y trascendencia de
la conservación de uno de nuestros recursos más valioso: EL SUELO.
12. ondorioa naGusiak eta tesia / conclusiones principales y tesis / main conclusions and thesis
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12. ONDORIOAK ETA TESIA
HASIERAKO OHARRA: kapitulu honetan lan honen ondorio nagusiak soilik aipatzen dira. Lan honetan garatutako gai desberdinei buruzko ondorio espezifikoak ikusteko, dagokien kapituluetara jo dezakezu (4-10 Kapituluak).
12.1 Ondorioak
1. Meatze-inguruneetako landare pseudometalofitoak metalen kutsadura jasateko gai dira,
fitoerauzketa eta fitoegonkortze teknologien garaperenako potentzial handia dutelarik.
Garrantzi handikoa da, fitoerauzketa edo fitoegonkortze prozesuan zehar, lurzoruaren
osasunean eragin onuragarrienak izango dituzten landare pseudometalofitoak aukeratzea.
2. Meatze-lurzoruetako propietate mikrobiologikoak lurzoru horietan hazten diren landare
pseudometalofitoen biomasarekin daude koerlazionaturik (eta ez landare
pseudometalofitoen aberastasunarekin). Edozein modutan, garrantzitsua da nabarmentzea
lurzoruko propietate mikrobiologikoek eragin handiagoa izan zutela landare
pseudometalofitoen biomasan, alderantziz baino. Gainera, meatze-lurzoru hauetan,
propietate mikrobiologiko eta fisiko-kimikoak oso koerlazionaturik daude.
3. Hemen aztertutako propietate mikrobiologiko desberdinen balioetatik ondorioztatzen
denez (lurzoruko mikrobio-komunitateen biomasa, aktibitate eta dibertsitatearekin
erlazionaturiko propietateak), metalen kutsadurak eragin nabaria du lurzoruaren
osasunean. Dena dela, geneen erredundantzia eta dibertsitate funtzionala emendatu egiten
dira metalen kutsadura dela eta.
4. Prozesu fitoerremediatzaileen ondorioz (bai metalaren erauzketa/egonkortzea, bai
landareen hazkuntza barne), lurzoru ekosistemaren osasunaren bioadierazle izateko
potentziala duten lurzoruko propietate mikrobiologikoen balioak emendatu egiten dira,
lurzoruaren egoeraren hobekuntza iradokiz.
5. Thlaspi caerulescens-en Lanestosa ekotipoak lurzoruko metal kontzentrazio altuak jasan
eta hauen aurrean egokiro hazteko gaitasuna du. Gainera, ekotipo honek bere aireko
zurtoinetan Zn eta Cd-a metatzeko gaitasun nabaria du, eta baita metal hauentzako
translokazio eta biokontzentrazio faktore oparoak ere. Zn edo/eta Cd-arekiko
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erresistentzia geneen ugaritasuna Thlaspi caerulescens-ekin landatutako lurzoruetan landatu-
gabekoetan baino altuagoa izatea interesgarria da.
6. Basarto landareak, biomasa ekoizpen altuak mantentzeaz batera, Cd kontzentrazio
handiak metatzeko gai dira aireko zurtoinetan. Metalez kutsaturiko lurzoruen
fitoerremediaziorako potentzial handia dute basarto landareek.
7. EDTA EDDSa baino askoz eraginkorragoa da Cynara cardunculus eta kelatzaile bidezko
Pb-aren fitoerauzketarako. Alabaina, EDDSak azkar biodegradatzearen abantaila dauka
eta EDTA baino toxikotasun gutxiago du lurzoruko mikrobio-komunitateentzat (kardu
landareentzat toxikoagoa den arren).
8. Prozesu kimiofitoegonkortzaileetan medeapenen erabilerak, batez ere behi-mindak,
metalez kutsaturiko meatze-lurren propietateak hobetu eta metalen toxikotasun eta
bioeskuragarritasuna jaitsarazten dituzte. Toxikotasunaren jaitsiera honek, elikagaien
gehitzeak dakartzan onurekin batera, Lolium perenne landareen hazkuntza osasuntsua
ahalbidetzen du.
9. Meatze-lurretan Thlaspi caerulescens egoteak/hazteak beste landare pseudometalofitoen
(Rumex acetosa eta Festuca rubra) hazkuntza estimulatzen duela dirudi, metalak fitoerauzteko
duen ahalmenagatik seguruenik. Rumex acetosa-k, Thlaspi caerulescens-ekin batera dagoenean
bereziki, aurkezten ditu erauzitako Zn balio altuenak meatze-lurzoru hauetan.
Orokorrean, kontsortzio batean landare pseudometalofitoen aberastasuna zenbat eta
altuagoa izan, errizosferako lurzoruan orduan eta baxuagoak dira aktibitate entzimatikoen
balioak eta orduan eta altuagoak mikrobio-biomasarenak.
10. Lurzoruaren osasunaren kontzeptua ekosistemaren osasunaren kontzeptuarekin
uztartu daiteke, ekosistemaren osasun-atributu ezpezifikoei propietate mikrobiologikoak
esleituz (indarra, egituraketa, egonkortasuna). Lan honetan epe motzean buruturiko
esperimentuetan ez zen landare pseudometalofitoen hazkuntzaren ondoriozko onurarik
ikusi lurzoru ekosistemaren osasunean (indarra, egituraketa eta egonkortasunaren arabera
estimatua).
11. Beraien sentsibilitate, azkar erantzuteko ahalmen eta izaera bateratzailea dela eta,
lurzoruko propietate mikrobiologikoak balio handiko bioadierazleak dira prozesu
fitoerremediatzaileen efizientzia ebaluatzeko.
12. ondorioa naGusiak eta tesia / conclusiones principales y tesis / main conclusions and thesis
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12.2 Tesia
Metalez kutsatutako lurzoruen fitoerremediazio eraginkorralortzeko kasu askotan denboraldi luzeegiak behar izaten diren arren, landare fitoerremediatzaileen hazkuntzak lurzoruaren osasunean ondorioonuragarriak ditu oso epe laburrera, lurzoruko mikriobio-komunitateen aktibitate eta funtzionaltasuna areagotzen baitu, eta hauexek diralurzoruaren funtzionamenduaren erantzule nagusiak. Ondorioz, edozeinprozesu fitoerremediatzaileren gorengo helburua, lurzoruaren osasunaberreskuratzea alegia, lurzorutik kutsadura ezabatu baino lehenagoerdiets daiteke.
Lurzoru ekosistemaren osasunaren adierazle izateko potentzial handia
duten lurzoruaren propietate mikrobiologikoak tresna hobezinak dira metalez
kutsatutako lurzoruen prozesu fitoerremediatzaileen efizientzia ebaluatzeko.
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12. CONCLUSIONES PRINCIPALES Y TESIS
NOTA INTRODUCTORIA: en el presente capítulo se mencionan exclusivamente las conclusiones principales de este trabajo. Para conclusiones más específicas sobre los diferentes temas desarrollados en este trabajo, se remite al lector a los capítulos correspondientes (Capítulos 4-10).
12.1 Conclusiones
1. Las plantas pseudometalofitas de entornos mineros son tolerantes a la contaminación
por metales y muestran un gran potencial para el desarrollo de tecnologías de
fitoextracción y fitoestabilización. Es importante seleccionar aquellas plantas
pseudometalofitas que, durante el proceso fitoextractor o fitoestabilizador, causan un
mayor efecto beneficioso sobre la salud del suelo.
2. Las propiedades microbiológicas en suelos mineros están correlacionadas con la
biomasa de las plantas pseudometalofitas que crecen en dichos suelos (no con la riqueza
de plantas pseudometalofitas). En cualquier caso, es importante destacar que las
propiedades microbiológicas del suelo tuvieron un efecto mayor sobre la biomasa de las
plantas pseudometalofitas que viceversa. Asimismo, en estos suelos mineros, las
propiedades microbiológicas y físico-químicas están muy correlacionadas.
3. La contaminación por metales tiene un claro impacto sobre la salud del suelo, como se
deriva de los valores de las diferentes propiedades microbiológicas del suelo aquí
estudiadas (propiedades relacionadas con la biomasa, actividad y diversidad de las
comunidades microbianas edáficas). No obstante, la redundancia y diversidad funcional
de genes aumentan como resultado de la contaminación por metales.
4. Como consecuencia de los procesos fitorremediadores (que implican tanto la
extracción/estabilización del metal como el crecimiento de las plantas), los valores de las
propiedades microbiológicas del suelo con potencial indicador de la salud del ecosistema
edáfico aumentan, sugiriendo una mejora en el estado del suelo.
5. El ecotipo Lanestosa de Thlaspi caerulescens muestra una alta tolerancia y capacidad de
crecimiento en presencia de elevadas concentraciones de metal en suelo. Asimismo, este
ecotipo muestra una notable capacidad para acumular Zn y Cd en sus tejidos aéreos, así
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252
como unos factores de traslocación y bioconcentración para estos dos metales muy
prometedores. Es interesante destacar que la abundancia de genes de resistencia al Zn y/o
Cd es mayor en suelos vegetados con Thlaspi caerulescens frente a los no vegetados.
6. Las plantas de sorgo son capaces de acumular altos niveles de Cd en sus tejidos aéreos
a la vez que mantienen una alta producción de biomasa. Las plantas de sorgo presentan
un gran potencial para la fitorremediación de suelos contaminados con metales.
7. El EDTA es mucho más eficiente que el EDDS para la fitoextración de Pb inducida
por quelantes con Cynara cardunculus. No obstante, el EDDS presenta la ventaja de su
rápida biodegradación y es menos tóxico que el EDTA para las comunidades microbianas
edáficas (aunque es más tóxico para las plantas de cardo).
8. La adición de enmiendas en procesos quimiofitoestabilizadores, especialmente purín
vacuno, mejora las propiedades de los suelos mineros contaminados con metales y reduce
la toxicidad y biodisponibilidad de dichos metales. Esta reducción en la toxicidad, junto
con los beneficios derivados del aporte de nutrientes, permite el establecimiento de una
cubierta saludable de plantas de Lolium perenne.
9. La presencia/el crecimiento de Thlaspi caerulescens parece estimular el crecimiento de
otras plantas pseudometalofitas (Rumex acetosa y Festuca rubra) en suelos mineros,
probablemente debido a su capacidad para fitoextraer metales. Rumex acetosa,
especialmente en combinación con Thlaspi caerulescens, presenta los valores más altos de Zn
fitoextraído de estos suelos mineros. En general, a mayor riqueza de plantas
pseudometalofitas presentes en un consorcio, menores valores de actividades enzimáticas
y mayores valores de biomasa microbiana en suelo rizosférico.
10. El concepto de salud del suelo se puede vincular al concepto de salud del ecosistema,
asignando propiedades microbiológicas del suelo a atributos específicos de la salud del
ecosistema (vigor, organización, estabilidad). En los experimentos a corto plazo
desarrollados en este trabajo, no se pudo observar una mejora en la salud del ecosistema
edáfico (estimada en base a vigor, organización y estabilidad) como consecuencia del
crecimiento de plantas pseudometalofitas.
11. Debido a su sensibilidad, rapidez de respuesta y carácter integrador, las propiedades
microbiológicas del suelo son bioindicadores muy valiosos para la evaluación de la eficacia
de procesos fitorremediadores.
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12.2 Tesis
Aunque se necesitan, en muchas ocasiones, periodos de tiempoexcesivamente largos para conseguir una fitorremediación efectiva de sueloscontaminados por metales, el crecimiento de las plantas fitorremediadorasprovoca efectos beneficiosos sobre la salud del suelo al cabo de muy pocotiempo, incrementando la actividad y funcionalidad de las comunidadesmicrobianas edáficas que son las principales responsables delfuncionamiento del suelo. En consecuencia, el objetivo último de cualquierproceso fitorremediador, i.e. recuperar la salud del suelo, puede lograrsemucho antes de haber eliminado el contaminante del suelo.
Las propiedades microbiológicas del suelo con potencial bioindicador de la salud del ecosistema edáfico son herramientas muy válidas para la evaluación de la eficacia de procesos fitorremediadores de suelos contaminados con metales.
12. ondorioa naGusiak eta tesia / conclusiones principales y tesis / main conclusions and thesis
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12. MAIN CONCLUSIONS AND THESIS
INTRODUCTORY NOTE: in the current chapter, only the main conclusions from this work are included. For more specific conclusions regarding the different topics dealt with during the development of this work, please refer to the corresponding chapters (Chapters 4-10).
12.1 Conclusions
1. Pseudometallophytes from mining areas are tolerant to metal pollution and offer great
potential for the development of phytoextraction and phytostabilization technologies. It
is important to choose those pseudometallophytes that, during the phytoextraction or
phytostabilization process, cause the most beneficial effects on soil health.
2. Soil microbiological properties in mine soils appear correlated to the biomass of
pseudometallophytes growing on those metal polluted soils (not to pseudometallophytes
richness). In any case, it is important to highlight that the soil microbiological properties
had a stronger effect on the biomass of pseudometallophytes, rather than the other way
around. Likewise, in these mine soils, soil microbiological and physicochemical
properties are highly correlated.
3. Metal pollution has a clear impact on soil health, as indicated by the values of the
different soil microbiological propertiers here determined (properties related to the
biomass, activity and diversity of the soil microbial communities). However, functional
gene diversity and redundancy increase as a result of metal pollution.
4. As a consequence of phytoremediation processes (which involve both metal
extraction/stabilization and plant growth), the values of soil microbiological properties
with potential as bioindicators of soil health increase, suggesting an improvement in the
soil condition.
5. The Lanestosa ecotype of Thlaspi caerulescens shows a high metal tolerance and capacity
to grow at elevated soil metal concentrations. Most importantly, the Lanestosa ecotype
shows a remarkable capacity to accumulate Zn and Cd in its aerial tissues, as well as most
promising translocation and bioconcentration factors for these two metals. Interestingly,
evaluation of the efficiency of metal phytoremediation processes with microbioloGical indicators of soil health
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the abundance of Zn and/or Cd resistance genes is higher in Thlaspi caerulescens planted
versus unplanted soils.
6. Sorghum plants are able to accumulate high levels of Cd in their aerial tissues while
maintaining a high biomass yield. Sorghum plants have great potential for the
phytoremediation of metal polluted soils.
7. EDTA is much more efficient than EDDS for chelate-induced Pb phytoextraction with
Cynara cardunculus. However, EDDS has the advantage of its rapid biodegradation and is
less toxic to the soil microbial communities than EDTA (although it causes more toxicity
to cardoon plants).
8. The addition of amendments in chemophytostabilization processes, especially cow
slurry, improves the properties of metal polluted mine soils and reduces metal toxicity and
bioavailability. This reduced toxicity, together with the benefits provided by the addition
of nutrients, allows the establishment of a healthy Lolium perenne vegetation cover.
9. The presence/growth of Thlaspi caerulescens appears stimulatory for the growth of other
pseudometallophytes (Rumex acetosa and Festuca rubra) in mine soils, probably due to its
metal phytoextraction capacity. Rumex acetosa, especially in combination with Thlaspi caerulescens, phytoextracts the highest amounts of Zn from these mine soils. In general, the
higher the number of pseudometallophytes present in a consortium, the lower the values
of enzyme activities and the highest the values of microbial biomass C observed in the
rhizosphere soil.
10. The concept of soil health can be linked to that of ecosystem health by means of
assigning soil microbiological properties to specific attributes of ecosystem health (vigor,
organization and stability). In the short-term experiments carried out in this work,
pseudometallophytes growth did not exert a clear overall beneficial effect on soil
ecosystem health (according to vigor, organization and stability).
11. The sensitivity, rapid response and integrative character of the soil microbiological
properties make them invaluable bioindicators for the assessment of the efficiency of
phytoremediation processes.
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12.2 Thesis
Although effective soil metal phytoremediation can take, in many cases,unacceptably long periods of time, the growth of the phytoremediating plantscauses beneficial effects on soil health in a very short time, actually enhancingthe activity and functionality of the soil microbial communities which arelargely responsible for soil functioning. In consequence, the ultimate goal of anyphytoremediation process, i.e. the recovery of soil health, can be achieved muchearlier than the removal of the pollutant(s) from the soil.
The soil microbiological properties with potential as bioindicators of soil health are most valid tools for the evaluation of the efficiency of metal phytoremediation processes.
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aGradecimientos / acknowledGements / eskerrak
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AGRADECIMIENTOS/ACKNOWLEDGEMENTS/ESKERRAK
Primeramente, quisiera agradecer a mis directores de tesis, el Dr. Carlos Garbisu y la Dra. María Jesús Sevilla por todo su apoyo y por darme la oportunidad de realizar este trabajo.
Asimismo, me gustaría dar las gracias:
Al Instituto Vasco de Investigación y Desarrollo Agrario (NEIKER-Tecnalia) por permitirme el uso de sus instalaciones y por su apoyo.
A la Asociación Laboratorio de Investigación Caleb Brett Ibérica por su apoyo.
To the Centre for Terrestrial Ecology of the Netherlands Institute of Ecology (NIOO-KNAW) and especially to Dr. George A. Kowalchuk for his support during my stay there.
To the Institute for Environmental Genomics (IEG), University of Oklahoma and especially to Dr. Jizhong Zhou for his support during my stay there.
Al Departamento de Industria, Comercio y Turismo del Gobierno Vasco, por su apoyo económico a través de una ayuda del Programa Ikertu.
El primer día, Carlos me dijo que me había escogido como doctoranda porque corría maratones... ¡¡Ahora que esto está terminando, puedo entender el por qué!! Es a Carlos al que quiero mostrar todo mi agradecimiento, por transmitirme su pasión por la ciencia, por su esfuerzo en intentar formarme como investigadora, por sacar tiempo de donde no había para las eternas correcciones… Te debo mucho, tanto profesional como personalmente. Muchas gracias también a Txema Becerril, porque su visión entusiasta desde las plantas nos ha aportado mucho a los del suelo.
Una buena maratón no se puede correr sin “liebres”: mil gracias sobre todo a Javi, tiraste de mí desde el principio; a Oihana, teniente de infantería de las Rumex, de Eibar; y a Iker, siempre con tan buen ánimo y disposición.
273
AGRADECIMIENTOS/ACKNOWLEDGEMENTS/ESKERRAK
Primeramente, quisiera agradecer a mis directores de tesis, el Dr. Carlos Garbisu y la Dra. María Jesús Sevilla por todo su apoyo y por darme la oportunidad de realizar este trabajo.
Asimismo, me gustaría dar las gracias:
Al Instituto Vasco de Investigación y Desarrollo Agrario (NEIKER-Tecnalia) por permitirme el uso de sus instalaciones y por su apoyo.
A la Asociación Laboratorio de Investigación Caleb Brett Ibérica por su apoyo.
To the Centre for Terrestrial Ecology of the Netherlands Institute of Ecology (NIOO-KNAW) and especially to Dr. George A. Kowalchuk for his support during my stay there.
To the Institute for Environmental Genomics (IEG), University of Oklahoma and especially to Dr. Jizhong Zhou for his support during my stay there.
Al Departamento de Industria, Comercio y Turismo del Gobierno Vasco, por su apoyo económico a través de una ayuda del Programa Ikertu.
El primer día, Carlos me dijo que me había escogido como doctoranda porque corría maratones... ¡¡Ahora que esto está terminando, puedo entender el por qué!! Es a Carlos al que quiero mostrar todo mi agradecimiento, por transmitirme su pasión por la ciencia, por su esfuerzo en intentar formarme como investigadora, por sacar tiempo de donde no había para las eternas correcciones… Te debo mucho, tanto profesional como personalmente. Muchas gracias también a Txema Becerril, porque su visión entusiasta desde las plantas nos ha aportado mucho a los del suelo.
Una buena maratón no se puede correr sin “liebres”: mil gracias sobre todo a Javi, tiraste de mí desde el principio; a Oihana, teniente de infantería de las Rumex, de Eibar; y a Iker, siempre con tan buen ánimo y disposición.
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También han contribuido a esta tesis Marta, Onintze, Izas, Olaia, Saioa y más personas que me han ayudado durante estos años. No me puedo olvidar de la gente de los invernaderos de NEIKER-Tecnalia: gracias por cuidar de mis plantitas durante los fines de semana y escapadas varias.
A Fernando, por las soluciones a mil y un problemas en el laboratorio, pero también por las enseñanzas del tipo de que lo importante es el camino y no el llegar a meta. Gracias a Nahia, Haritz, Ainara, Oscar, Goio, Fenxia, Borja, Roberto, Olatz, Patri, Arrate… porque correr bien acompañada es mucho más divertido que hacerlo sola.
Many thanks to the ones that made me feel at home during my stay abroad. Special acknowledgements for the team of Terrestrial Microbial Ecology in Heteren for letting me pick up their knowledge.
Nire eskerrik beroenak familia eta lagunei, Markinar eta Bilbotarrei, bide ertzean animoak ematen izan zaituztedalako, zuengatik ez balitz aspaldi utzia nukeen; Ekozain taldeari, gogo eta asmo onez zein urrun iritsi daitekeen erakutsi didazuelako; biodantzariei, soinu-banda goxo horregatik; pisukideei, egunerokotasunaren zama arintzearren (jada ez daukat etxeko lanak ez egiteko aitzakiarik…).
Eta azkenik etxekoei, gehien jasaten nautenei. Zuek ere hor zaudetela badakit, eguzkia edo kazkabarra izan, eta beti eskertuko dizuet: beste mota bateko ekosistema toxikoak sendatzen ahalegintzen den ama eta zuhaitzak landatzen dituen aita, nonbaitetik atera behar nintzen ni ere! Baita Xabi ere, neba txiki itzel hori. Andoni, bizipoz kutsakor horrekin nire energi-iturria zara. Zein ametsen atzetik joango gara honen ondoren?
TESIS DOCTORALES PUBLICADAS
Nº 1. La raza Latxa: Sistemas de producción y características reproductivas. Eduardo uriartE EgurcEgui
Nº 2. Estudio y puesta a punto de un método simplificado de control lechero cualitativo en la raza ovina Latxa y su inclusión en el plan de selección. gustavo adolfo Maria lEvrino
Nº 3. Implicaciones tecnológicas de la composición química del pescado con especial referencia a los lípidos. rogElio Pozo carro
Nº 4. Estudio de suelos de Vizkaia. Margarita doMingo urartE
Nº 5. El Maedi o neumonía progresiva en el conjunto de las enfermedades respiratorias crónicas del ganado ovino en la Comunidad Autónoma Vasca. lorEnzo gonzálEz angulo
Nº 6. Estudio experimental de las fases iniciales de la paratuberculosis ovina. raMón a. JustE Jordan
Nº 7. Identificación, origen y factores fisicoquímicos que condicionan la contaminación por elementos metálicos de sedimentos de ríos. Estilita ruiz roMEra
Nº 8. Análisis financiero de proyectos de inversión en repoblaciones forestales. álavaro aunos góMEz
Nº 9. Desarrollo y evaluación del sistema integrado de diagnóstico y recomendación (DRIS) para la fertilización de las praderas permanentes. Marta Rodríguez Julia
Nº 10. Estudio de las mieles producidas en la Comunidad Autónoma del País Vasco. María tErEsa sancho ortiz
Nº 11. La biomasa microbiana como agente de las transformaciones de nitrógeno en el suelo tras el ente-rrado de la paja de cereal. JEsús ángEl ocio arMEntia
Nº 12. Análisis jurídico y económico de la implementación de la política agraria comunitaria en la Comunidad Autónoma del País Vasco. BEatriz PérEz dE las hEras
Nº 13. Nemátodos formadores de quistes (Globodera spp.) en patata (Solanum tuberosum L.): caracteri-zación taxonómica, reproducción y actividad de las formas juveniles. azucEna salazar Bayona
Nº 14. Ensayo comparativo de tres métodos de tratamiento antihelmítico estratégico en rebaños de ovejas latxas. ana luisa gracia PérEz
Nº 15. Estudio sobre una encefalitis vírica similar al Louping-ill en el ganado ovino de la Comunidad Autónoma Vasca. daniEl fErnándEz dE luco Martinéz
Nº 16. Análisis de caracteres involucrados en la selección y mejora de Lupinus hispanicus Boiss. et Reuter. vErónica arriEta Pico
Nº 17. Contribución al estudio de fermentaciones artesanales e industriales de Rioja Alavesa. Milagros viñEgra garcía
Nº 18. Estudio del manejo de la alimentación en los rebaños ovinos de raza Latxa y su influencia sobre los resultados reproductivos y de producción de leche. luis Mª. orEgui lizarraldE
Nº 19. El sector pesquero vizcaíno, 1800-1960. Análisis de la interacción de los elementos ambiental, extractivo y comercial en la pesquería. José agustín Maiz alcorta
Nº 20. Epidemiología, diagnóstico y control de la paratuberculosis ovina en la Comunidad Autónoma del País Vasco. J. J. aduriz rEcaldE
Nº 21. Agrupación de poblaciones locales de maíz (Zea mays L.) mediante caracteres morfológicos y parámetros ambientales. José ignacio ruiz dE galarrEta góMEz
Nº 22. Estudio del potencial melífero de Bizkaia. aMElia cErvEllo MartínEz
Nº 23. Influencia de los procesos de salado y ahumado sobre las características fisicoquímicas del queso Idiazabal (compuestos nitrogenados). francisco c. iBañEz Moya
Nº 24. El Euskal Artzain Txakurra (el perro pastor vasco) descripción y tipificación racial. Mariano góMEz fErnándEz
Nº 25. Evaluación de diferentes ciclos de selección recurrente en dos poblaciones sintéticas de maíz. gotzonE garay solachi
Nº 26. Valoración agronómica de la gallinaza: Compostaje. adolfo MEnoyo PuEllEs
Nº 27. Relación clima-vegetación en la Comunidad Autónoma del País Vasco. aMElia ortuBay fuEntEs
Nº 28. Influencia de los procesos de salado y ahumado tradicional sobre las características microbiológi-cas y organolépticas del queso Idiazabal. francisco J. PérEz Elortondo
Nº 29. Mastitis en la oveja Latxa: epidemiología, diagnóstico y control. Juan c. Marco MElEro
Nº 30. Contribución al conocimiento anatomopatológico y diagnóstico de la tuberculosis caprina y ovina por Mycobacterium bovis. M.ª MontsErrat gutiérrEz cancEla
Nº 31. Estudio de factores que pueden influir en la calidad de la pluma de gallos Eusko-oiloa (Variedad Marradune) para la fabricación de moscas artificiales utilizadas en la pesca de la trucha. rosa M.ª Echarri toMé
Nº 32. Estudio de la fracción lipídica durante la maduración del queso Idiazabal. Influencia de los proce-sos tecnológicos del tiempo de permanencia en salmuera y ahumado. ana isaBEl náJEra ortigosa
Nº 33. Influencia del tipo de cuajo y adición de cultivo iniciador sobre los compuestos nitrogenados durante la maduración del queso Idiazabal. M.ª solEdad vicEntE Martín
Nº 34. Estudio de la infección por Borrelia burgdorferi, grupo Ehrlichia phagocytophila y virus de la encefalitis ovina en las poblaciones de ixódidos de la Comunidad Autónoma Vasca. Marta Barral lahidalga
Nº 35. Lipolisis en el queso Idiazabal: efecto de la época de elaboración, del cultivo iniciador, de la pas-teurización y del tipo de cuajo. fElisa chavarri díaz dE cErio
Nº 36. Aspectos inmunopalógicos de la paratuberculosis de los pequeños rumiantes. Respuesta inmune asociada a la vacunación. Juan ManuEl corPa arEnas
Nº 37. Desarrollo y evaluación de nuevas técnicas de diagnóstico del Maedi-Visna. ana BElén ExtraMiana alonso
Nº 38. Estudios sobre Patogenia y Diagnóstico de la Adenomatosis Pulmonar Ovina. María MErcEdEs garcía goti
Nº 39. Análisis de los factores de explotación que afectan a la producción lechera en los rebaños de raza Latxa de la CAPV. roBErto J. ruiz santos
Nº 40. Crecimiento y producción de repoblaciones de Pinus radiata D. Don en el Territorio Histórico de Gipuzkoa (País Vasco). luis Mario chauchard Badano
Nº 41. Puesta a punto de técnicas PCR en heces y de Elisa para el diagnóstico de la Paratuberculosis. Estudio de prevalencia en ganado bovino. JosEBa M. garrido urkullu
Nº 42. Epidemiología y diagnóstico de la leptospirosis y la neosporosis en explotaciones de bovino leche-ro de la CAPV. raquEl achaErandio galdos
Nº 43. Relaciones aire-agua en sustratos de cultivo como base para el control del riego. Metodología de laboratorio y modelización. valEntín tErés tErés
Nº 44. Zonas endémicas de enfermedad de Lyme en la CAPV: estudio del papel de los micromamíferos en el mantenimiento de Borrelia burgdorferi sensu lato en el medio natural. horacio gil gil
Nº 45. Optimización del esquema de mejora de la raza Latxa: análisis del modelo de valoración e intro-ducción de nuevos caractéres en el objetivo de selección. andrés lEgarza alBizu
Nº 46. Influencia de las condiciones de almacenamiento, reimplantación y lluvia ácida en la viabilidad de Pinus radiata D. Don. MirEn aMaia MEna PEtitE
Nº 47. Estudio sobre encefalopatías en peces: patogenicidad del nodavirus causante de la enfermedad y retinopatía vírica (ERV) y transmisión experimental del prión scrapie a peces. raquEl arangurEn ruiz
Nº 48. Enfermedades transmitidas por semilla en judía-grano (Phaseolus vulgaris L.): detección, control sanitario y mejora genética. ana María díEz navaJas
Nº 49. Pastoreo del ganado vacuno en zonas de montaña y su integración en los sistemas de producción de la CAPV. nErEa Mandaluniz astigarraga
Nº 50. Aspectos básicos de la mejora genética de patata (Solanum tuberosum L.) a nivel diploide. lEirE Barandalla urtiaga
nº 51. El cuajo de cordero en pasta: preparación y efecto en los procesos proteolíticos y lipolíticos de la maduración del queso de Idiazabal. Mª. ángElEs BustaMantE gallEgo
Nº 52. Dinámica de la población de atún blanco (Thunnus alalunga Bonnaterre 1788) del Atlántico Norte. Josu santiago Burrutxaga
nº 53. El pino radiata (Pinus radiata D.Don) en la historia forestal de la Comunidad Autónoma de eus-kadi. Análisis de un proceso de forestalismo intensivo. Mario MichEl rodríguEz
nº 54. Balance hídrico y mineral del pimiento de Gernika (Capsicum annuum L., cv Derio) en cultivo hidropónico. Relaciones con la producción. hugo Macía olivEr
nº 55. Desarrollo de métodos moleculares y su aplicación al estudio de la resistencia genética y patogenia molecular del Scrapie. david garcía crEsPo
nº 56. Estudio epidemiológico y experimental de la transmisión y control del virus Maedi-Visna en ovino lechero de raza Latxa del País Vasco. vEga álvarEz MaiztEgui
nº 57. Desarrollo y aplicación de técnicas de diagnóstico serológico para el estudio de la transmisión calostral y horizontal del virus Maedi-Visna (VMV) en ovino. Mara Elisa daltaBuit tEst
nº 58. Integral Study of Calving Ease in Spanish Holstein Population. EvangElina lóPEz dE Maturana lóPEz dE lacallE
nº 59. Caracterización Molecular, Detección y Resistencia de Mycobacterium avium subespecie paratu-berculosis. ikEr sEvilla agirrEgoMoskorta
nº 60. Desarrollo de un sistema de fertilización nitrogenada racional en trigo blando de invierno bajo condiciones de clima mediterráneo húmedo. M.ª arritokiEta ortuzar iragorri
nº 61. Estructura y dinámica de la materia orgánica del suelo en ecosistemas forestales templados: de los particular a lo general. nahia gartzia BEngoEtxEa
nº 62. Análisis sensorial del vino tinto joven de Rioja Alavesa: descripción y evaluación de la calidad. iñaki Etaio alonso
nº 63. Biología del gusano de alambre (Agriotes spp.) en la Llanada Alavesa y desarrollo de estrategias de control integrado en el cultivo de la patata. ana isaBEl ruiz dE azúa Estívariz
nº 64. La sucesión en la ganadería familiar: el ovino de leche en el País Vasco. guadaluPE raMos truchEro
nº 65. Identificación molecular de las especies de piroplasmas en las poblaciones de Inóxidos de la Comunidad Autónoma del País Vasco. Distribución y prevalencia de babesia y theileria en los ungulados domésticos y silvestre. MirEn JosunE garcía
nº 66. Estudio de variables inmunológicas y bacteriológicas en relación con la inmunización frente a paratuberculosis en los rumiantes. María v. gEiJo vázquEz
nº 67. Bacterias lácticas de sidra natural: implicación en alteraciones y potencial probiótico de cepas productoras de (1,3)(1,2)-ß-D-glucanos. gaizka garai iBaBE
nº 68. Influencia de los sistemas de producción ovina en la calidad y las propiedades tecnológicas de la leche y el queso. EunatE aBillEira cillEro
nº 69. Los carnívoros silvestre como reservorios de enfermedades de interés en sanidad animal y salud pública. xEidEr gErrikagoitia sagarna
nº 70. Cattle nutrition as a strategy to mitigate gaseous nitrogen losses from dairy farming. haritz arriaga sasiEta
ISBN: 978-84-457-3092-8
9 788445 730928