Ecological integrity assessment in aquatic ecosystems: A multi-scale approach towards the definition of the ecological status of Mediterranean reservoirs

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Universidade de Trás-os-Montes e Alto Douro Vila Real, 2008

WorkSupervisedBy:

Prof.Dr.JoãoAlexandreCabral

Prof.Dr.MiguelÂngeloPardal

EDNA CARLA JANEIRO CABECINHA DA CÂMARA SAMPAIO

ECOLOGICAL INTEGRITY

ASSESSMENT IN AQUATIC

ECOSYSTEMS:

A multi-scale approach towards the

definition of the ecological status of

Mediterranean reservoirs

Tese apresentada para oefeito de obtenção do grau de Doutor em Ciências do Ambiente, de acordo com o dispostonoDecretoͲLein.º216/92,de13deOutubro.

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Origemdasfotografias: http://www.susqu.edu/bibliogy/algae/links.htm http://cnpgb.inag.pt/gr_barragens/gbportugal/index.htm

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ToFilipeandLia

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ECOLOGICAL

INTEGRITYASSESSMENT

IN

AQUATICECOSYSTEMS:AmultiͲscale

approach

_{towardsthedefinitionofthe}

ecological

statusofMediterranean

reservoirs

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Acknowledgements

Acknowledgements/Agradecimentos

Um trabalho de investigação não traduz de todo o esforço isolado de uma pessoa, antes constitui o resultado de várias contribuições que, no seu conjunto, dão corpo às ideias expressas, e permitem a sua apresentação final. Assim, é da minha vontade deixar aqui manifestaaesseconjuntodepessoastodoomeureconhecidoesinceroagradecimento.

Ao Professor Armando Mascarenhas Ferreira, Magnífico Reitor da UTAD, pelo dinamismo que vemimprimindoànossaacademia,permitindoqueopercursocientíficoepromoçãoacadémica dosseusmembrossejamaisfacilitadaepeloincentivodadoaolongodestesanos.

Ao Professor Carlos Correia e ao Professor António Fontaínhas Fernandes, como actual e exͲ coordenador do Departamento de Engenharia Biológica e Ambiental, pelas facilidades concedidasnarealizaçãodestetrabalho,bemcomopelosseusconstantesincentivos.

Ao Professor João Cabral, orientador científico desta dissertação, pela solicitude, disponibilidade,paciênciaeencorajamento,masacimadetudo,pelasuainestimávelamizadee dedicação que foram uma constante ao longo deste 10 anos de trabalho conjunto. Muito obrigada…

AoProfessorMiguelPardal,coͲorientadorcientíficodestadissertação,pelaamizadeeempenho pessoal manifestados, pelas clarificadoras e sempre oportunas sugestões ao longo de todo o trabalho,bemcomonarevisãocuidadadotexto.Obrigadapelapaciênciaedisponibilidadenas revisões,sempreparaontem,massobretudopeloincentivo,pelobomhumor,assimcomopelas palavrasamigasnashorasdifíceis.

Ao Professor Rui Cortes, que desde a primeira hora se disponibilizou para me ajudar. A sua amizade,paciência,disponibilidadeeencorajamento,asrespostasàsminhasinúmerasquestões e dúvidas, foram sempre uma constante. Obrigada pela paciência e incentivo, pelas extensas, masprofícuas,discussõesaolongodestemeupercursocientífico.Omeusinceroobrigado. To Professor Paul Van den Brink, for his kindness and scientific support, as well as for all the brainͲstormings realized through the countless eͲmails. It was a fundamental support in the multivariateanalysesperformedandinthemeticulousrevisionofthepapers.

À ProfessoraTeresa Ferreira pela forma solícita com sempre respondeu às minhas questões e pelaformainteressadacomqueseguiuodesenrolardestetrabalho.

AoINAGeaoLABELEC,esteúltimonapessoadoEng.ºLourençoGil,pelacedênciadosdados que tornaram possível a concretização desta tese. Gostaria ainda de salientar a simpatia e disponibilidadedoEng.ºLourençoGileasuaconstantepreocupaçãoemresponderatodasas dúvidaspormimcolocadas.

Aos Professores Martinho Lourenço e João Paulo Moura, obrigada pela amizade, por acreditarem nas minhas ideias e pela forma empenhada como me ajudaram, abdicando de muito do vosso precioso tempo, na condução e materialização dos meus reptos. Sem vocês o passoemfrentenaprocuradainterfaceespacialnãoteriasidopossível.

Aos colegas e amigos do Laboratório de Ecologia, com os quais compartilho o meu diaͲaͲdia, obrigada pela vossa amizade e preciosa ajuda, pelas animadas e dinâmicas discussões na procura de soluções para os mais variados imbróglios da modelação. Obrigada a todos pelo

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Acknowledgements

impagável bom humor e estímulos constantes. Ao Pedro um obrigado especial pelos “candelabros”,peladisponibilidadeepaciêncianacomposiçãodasimagens.

Aos colegas do GAPI da UTAD, em particular ao Dr. Jorge Machado, pela amizade e ajuda inestimávelemtodooprocessodepedidodepatente.

A todos os colegas do DEBA e aos amigos fantásticos que tenho agradeço a amizade e as palavras de constante incentivo. Um Obrigado muito especial à Carla Amaral, à Rosário Anjos, TeresaPinto,CláudiaPatrícia,D.Helena,CármenMoreira,MoutinhoPereira,DarioSantos…,por partilharemcomigoosmeusdesesperos,asangustias,aslágrimaseasconquistas.Obrigadapela vossaamizadeecarinhoquemuitoprezo. AoProfessorJoséManuelMoutinhoPereira,gostariaaindadeagradecerpelaformacomome ajudounarevisãominuciosadotexto

Ao Professor Dario Santos não há palavras para agradecer toda a sua inestimável ajuda e disponibilidade, abdicando de muito do seu precioso tempo. Muito obrigada pela paciência e carinho infindáveis que imprimiu na formatação desta tese. Fica o repto para aprender a trabalharcomoCorel.

AoEng.ºAlbertoVasconcelos,eaoseuLINUX,pormetersalvoamimeàtese.Obrigadapela amizade,disponibilidadeeprofissionalismonestequefoioperíodomaisnegrodestetrabalho.

Não posso deixar de agradecer ao Professor Torres de Castro, ao Professor Azevedo e ao ProfessorCoutinhoquepeloseuconstanteincentivoeamizade. ÀequipadosServiçosdeReprografiadaUTAD,pelaeficácianacomposiçãográficaeimpressão finaldestadissertação. Àminhafamíliaeatodososcolegaseamigosquecomigosecruzaramequedealgummodo contribuíramparaqueestepercursofosseomaisagradávelpossível. AosmeusPais,portodooamor,compreensão,paciênciaeprincipalmenteportodaaforçaque sempremederamparaconcretizarestegrandeobjectivodaminhavida.

À minha sogra, D. Angelina Sampaio, companheira inseparável nestes últimos meses. Um Obrigadosentidopelasuaamizadeeincentivosincondicionais,semsiistonãoteriasidopossível aconcretizaçãodesteprojecto.

Ao Filipe e à Lia, as minhas duas âncoras, obrigada por me aturarem e por serem parte integrante do meu ser…. Espero poder compensar as horas de brincadeiras (e escorregas) perdidas….

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ABSTRACT Abstract WorldwideaquaticecosystemshavebeenimpactedbybroadͲscaleenvironmentalpressures suchasagriculture,pointandnonpointͲsourcepollutionandlandͲusechangesoverlapping in space and time, leading to the disruption of the structure and functioning of these systems. In face of this global change, declines in environmental quality of rivers and respectivereservoirsareofincreasingconcern.Thishasleadtoanincreasingsearchfornew technologies for the monitoring of reservoirs to establish priorities of conservation, protection and restoration to achieve the “Maximum Ecological Potential” of these water bodies.Inthiscontext,theobjectiveofthisthesiswastodevelopnewtools,supportedby multivariate statistical analyses and modelling methodologies, which can be applied in assessing the ecological status of Mediterranean reservoirs, in the scope of the Water Framework Directive (WFD). This work intended to design integrated methodologies to capture the aquatic ecosystems complexity through a multiͲscale approach, in order to develop and understand the local and regional mechanisms that operate in reservoirs. To better understand the occurring changes in the structure and functioning of this systems, severalecosystemcomponents(e.g.hydromorphological,physical,chemicalandbiological) and several disturbance factors (e.g. land use changes, hydrometric variations, point and nonͲpointsourcepollution,etc.)wereincorporated,atdifferentspatialandtemporalscales of analysis.The thesis was structured into seven chapters based in the analysis of extensive data bases, namely longͲterm data bases collected in the field by the Laboratory of Environmental and Applied Chemistry (LABELEC) managed by the Portuguese Electricity Group (EDP), in five different Portuguese hydrographic regions (Lima, Cavado and Ave, Douro, Mondego and Tagus catchment), throughaperiodofnineyears(1996to2004).Themajorobjectivesofthisthesiswere:

x To establish the typology and the TypeͲspecific reference condition of the Portuguese hydroelectricreservoirsbasedonbioticandabioticqualityelements,namelyphytoplanktonas waterqualityindicator,throughamultiͲscaleapproach.

x To determine the importance of environmental variables at different spatial (geographical, regionalandlocal)andtimescales(seasons,years)onthephytoplanktoncommunitystructure ofthestudiedreservoirsTypes.

x Todetermine,overtime,thedegreeofimpairmentofthesereservoirsbycontrastingitwitha referencesite,asproposedbytheWFD.

x To develop a modelling multiͲscale approach, based on an holistic Stochastic Dynamic Methodology (StDM), in order to predict the ecological status tendencies in Mediterranean reservoirs as a response to land use changes in the respective watersheds. Therefore, the Douro’s basin was used to test and validate the StDM model, as well as evaluate the StDM performance in capturing how expected changes at land use level scenarios will alter the reservoirwaterquality,namelyatphysicochemicalandphytoplanktonlevels.

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ABSTRACT TheresultsofthedifferentapproacheswereconsistentinthetypologydefinedforthePortuguese reservoirs, as well as in the observed pollution gradients, which in some extend reflected the degradation associated to the conversion of the agroforestry areas into industrialized and semiͲ urbanareas.Therefore,itwaspossibletoidentifytwotypesofdammedwaterbodieswhichwere characterized by different hydromorphological features, water chemistry characteristics and by a specificphytoplanktontaxacomposition:

x Type 1 represents lowland reservoirs located in the main rivers (Douro and Tagus) characterized by higher concentrations of nutrients and water mineral content. This “riverinereservoirs”,resemblesmoreariverthanalake,withshorthydraulicretention times, good mixing and relative high water velocities, never or rarely affected by stratification phenomena. In general, is located in densely populated, industrialized or agriculturalareas,receivinghighinputsoforganicmatterandindustrialdischarge. x Type 2 represents deeper high altitude “artificial lake reservoirs”, largely located in

tributaries, with a high residence time, with longer water storage and release cycles operatingunderseasonalinfluence,stronglyaffectedbystratificationphenomena.

Itwaspossibletoassigncharacteristicphytoplanktontaxaassemblagestoeachtypeofreservoir.For bothregulatedsystemstypes,wasalsopossibletoestablishthecharacteristictaxaofdisturbedand less or non disturbed sites. Such ascription is an essential prerequisite for the development of an assessmentprocedureaccordingtotheWFD,wheretheassessmentshouldbedonebycomparing theactualspeciescompositiontotheonethatwouldbepresentunderreferenceconditions. Our findings of the importance of local and regional scale factors on phytoplankton community structure lend support to earlier studies, reflecting the importance of habitat and largeͲscale (landscape)factorsonreservoirecosystemsanddemonstratethatPhytoplanktoncouldbeagood ecologicalindicatorformultiͲscaleandcumulativedisturbanceeffectswithaviewtointegratefuture worldwidemonitoringinreservoirs.

Regarding the developed modelling multiͲscale approach (StDM), the overall results were encouraging since they seem to demonstrate the tool reliability in capturing the stochastic environmentaldynamicsoftheselectedmetricsfacingspatialexplicitscenarios.Theultimategoalof thisapproachwastocouplemonitoringassessmentandthedescribedmodellingtechniquestoease managementanddecisionmakingregardingtherequirementsoftheWFD.

Overall,themethodologiespresentedinthisthesiscouldcontributetotheimplementationof theWFDinPortugal,withregardspecificallytotheevaluationoftheecologicalstatus,providingnew toolsfortheecologicalintegrityassessmentoflenticwaters,andpretendtocontributetoalarger understandingofthestructuralandfunctionalhumaninducedalterationsthatoccurinPortuguese aquaticecosystems.

Key words: Reservoirs, Ecological condition; reference sites; catchments; biomonitoring;

phytoplankton; Multivariate analysis, StochasticͲdynamic modelling, multiͲscale approach, WaterFrameworkDirective.

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RESUMO Resumo

Mundialmente os sistemas aquáticos têm sido afectados por diversas pressões a larga escala, nomeadamenteaintensificaçãoagrícolaeoaumentodefontestópicasedifusas,quesesobrepõemno espaçoenotempoetêmlevadoàrupturadaestruturaedofuncionamentodestessistemas.Faceaesta alteração global, o declínio da qualidade ambiental dos rios e respectivas albufeiras, tem sido alvo de umacrescentepreocupação.Nestecontexto,temsurgidoumacrescenteprocuradenovastecnologias paraamonitorizaçãodealbufeirasquepermitamestabelecerprioridadesdeconservação,protecçãoe restauração,quepossibilitemalcançaroestadoecológicorequeridoouumbompotencialecológicopara estasmassasdeáguafortementemodificadas.Assim,oobjectivodestatesefoiodesenvolvimentode novas ferramentas assentes em análises estatísticas multivariadas e metodologias de modelação, que possibilitam a determinação do estado ecológico de albufeiras mediterrâneas, no âmbito da Directiva Quadro da Água (DQA). Este trabalho pretende desenvolver metodologias integradas que captem a complexidadeinerenteaosecossistemasaquáticosatravésdeumaabordagemmultiͲescala,demodoa compreender melhor os mecanismos locais e regionais que operam nestas massas de água. Para uma melhor compreensão das alterações ocorridas na estrutura e funcionamento das albufeiras, vários componentes destes ecossistemas foram incorporados a diferentes escalas temporais e espaciais de análise, nomeadamente, parâmetros hidromorfológicos, físicos, químicos e biológicos e ainda vários factoresdeperturbação(i.e.,alteraçõesdosusosdosolo,variaçõeshidrométricasefontesdepoluição tópicasedifusas).Atesefoiestruturadaemsetecapítuloscujaanálisefoisuportadaporextensasbases de dados, nomeadamente as séries temporais de longoͲtermo, referentes ao período 1996Ͳ2004, compiladaspeloLaboratóriodeAmbientedoGrupoElectricidadedePortugal(EDP,LABELEC).Abasede dadosenglobaumconjuntode34albufeirasqueseestendemporcincoregiõeshidrográficasdistintas (BaciasdoLima,CávadoeAve,Douro,MondegoeTejo).

Osprincipaisobjectivosdestateseforam:

x Estabelecer a tipologia e as condições de referência de cada Tipo, das albufeiras Portuguesas

com fins hidroeléctricos definidos, através de uma abordagem multiͲescala baseada nos elementos abióticos e bióticos, nomeadamente nas comunidades fitoplânctonicas como indicadoresdaqualidadedaágua(Capítulo2).

x Determinar a importância das variáveis ambientais na estruturação da comunidade de

fitoplâncton nos Tipos de albufeiras estudadas a diferentes escalas espaciais (geográfica, regionalelocal)etemporais(estaçõesdoano,anos)(Capítulo3).

x Determinar,comopropostopelaDQA,ograudeperturbaçãodasdiversasalbufeiras,aolongo

do tempo, através da comparação com os locais de referência para cada um dos Tipos determinados(Capítulo4).

x Desenvolver um modeloEstocásticoͲDinâmico (StDM), baseado numa abordagem multiͲescala,

parapreveroestadoecológicodealbufeirasMediterrâneasfaceaalteraçõesdeusodosolonas

respectivas bacias hidrográficas. Neste contexto, a bacia do Douro foi utilizada para testar e validaromodelodesenvolvido(Capítulo5),assimcomoavaliarasuaperformancenaprevisão de alteração da qualidade da água de uma albufeira, nomeadamente ao nível ambiental e

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RESUMO

biológico (fitoplâncton), face a expectáveis cenários espaciais de alteração de uso do solo (Capítulo6).

Os resultados das diferentes abordagens foram consistentes na definição da tipologia das albufeiras

portuguesas estudadas, assim como nos gradientes de poluição observados, que de algum modo parecem reflectir a degradação associada à conversão de áreas agroͲflorestais em áreas industriais ou semiͲurbanas. Assim, foi possível identificar dois Tipos de massas de água com características hidromorfológicas, químicas e biológicas distintas, nomeadamente com comunidades fitoplântonicas específicas:

Tipo 1, albufeiras localizadas nos rios principais (Douro e Tejo) caracterizadas por elevadas concentraçõesdenutrienteseminerais.EsteTipodealbufeiras“fioͲdeͲágua”,assemelhaͲsemuito maisaumsistemalóticodoqueaumsistemalêntico,apresentandotemposderesidênciabaixos (dias), boa mistura e uma relativa elevada velocidade da corrente, nunca ou muito raramente ocorreestratificação.Emgeral,situamͲseemáreasdensamentepovoadas,industriaisouagrícolas sujeitasaelevadosinputsdematériaorgânicaedescargasindustriais.

Tipo 2, verdadeiros reservatórios, profundos e situados a altitudes elevadas. Geralmente, encontramͲselocalizadasnostributárioseapresentamelevadostemposderesidência(semanasa meses).Consequentemente,sãofortementeafectadosporfenómenosdeestratificação.

Foi possível, determinar as comunidades fitoplânctonicas características de cada um dos Tipos de albufeirasreferidos.Paraambosostiposdesistemasregulados,foitambémpossívelestabelecerostaxa característicos dos locais perturbados e dos locais menos perturbados ou de referência. Esta caracterização é um préͲrequisito essencial para o desenvolvimento de um processo de avaliação de acordo com a DQA, dado que a avaliação deve efectuarͲse através da comparação da composição de espéciesactualcomaqueestariapresenteemcondiçõesdereferência.

Os resultados relativos à importância das escalas local e regional na estrutura e composição do fitoplânctonvieramcorroborarestudosanteriores,reflectindoaimportânciadohabitatedapaisagem nos ecossistemas lênticos. Estes resultados parecem demonstrar que o fitoplâncton pode ser um bom indicadorecológiconaavaliaçãoholísticadosefeitosdepressõescumulativasoumultiͲescala,podendo viraserintegradonofuturo,anívelregionaloumundial,namonitorizaçãodealbufeiras.

Relativamente ao modelo EstocásticoͲDinânmico (StDM) desenvolvido, de uma maneira geral os resultados foram encorajadores dado que parecem demonstrar a consistência desta ferramenta em captaradinâmicaambientalaleatóriadasmétricasseleccionadasfaceacenáriosespaciaisexpectáveis. Estetipodeabordagemholísticapodeeventualmentefacilitaroordenamentodestasmassasdeágua, assimcomoatomadadedecisãosegundoasexigênciasdaDQA.

Globalmente, as metodologias desenvolvidas nesta tese poderão contribuir para a implementação da DQAemPortugal,especialmentenaavaliaçãodoestadoecológico,fornecendonovasferramentaspara aavaliaçãoda integridadeecológica de sistemaslênticos, epretendeaindacontribuirparaumamaior compreensãodas alteraçõesestruturaise funcionaisque ocorrem nos sistemasaquáticos portugueses devidoapressõesantropogénicas.

PalavrasͲchave: Albufeiras; Condição ecológica; Locais de referência; Bacia hidrográfica; Biomonitorização; Fitoplâncton; Análise multivariada; Modelação EstocásticoͲDinâmica; Abordagem multiͲescala,DiretivaQuadrodaÁgua.

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i CONTENTS TableofContents

1.4. New challenges in management and decision making: modelling approaches regardingtheWFDrequirements……… 16 1.5.References………. 22 CHAPTER2ͲMultiͲscaleapproachusingphytoplanktonasafirststeptowards thedefinitionoftheecologicalstatusofreservoirs 2.1.Abstract……… 27 2.2.Introduction……… 27 2.3.Materialsandmethods……… 29 2.3.1.Studyarea……… 29 2.3.2.Environmentalparametersandchlorophylla……… 32 2.3.3.Phytoplanktonanalysis……… 33 2.3.4.Statisticalanalysis……… 36 2.4.Results……… 37 2.4.1.Environmentalvariables……… 37 2.4.2.AnalysisbasedonPhytoplanktonassemblages……… 42 2.5.Discussion……… 46 2.6.Acknowledgements……… 52 2.7.References……… 52 CHAPTER 3 Ͳ Ecological relationships between phytoplankton communities and different spatial scales in European reservoirs: implications atcatchmentlevelmonitoringprogrammes 3.1.Abstract……… 57 3.2.Introduction……… 57 3.3.Materialsandmethods………. 59 3.3.1.Studyarea……… 59 3.3.2.Environmentalparametersandchlorophylla……… 60 3.3.3.Phytoplanktonanalysis……… 64 3.3.4.Statisticalanalysis……… 64 3.4.Results……… 67

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ii

CONTENTS TableofContents

3.4.1.Phytoplanktoncomposition……… 67

3.4.2. Environmental gradients and their relation to phytoplankton taxa (CCA models)……… 68 3.4.3.Relativeimportanceofspatialvs.timefactors……… 72 3.5.Discussion……….. 75 3.6.References……… 82 CHAPTER4ͲAssessingenvironmentalqualityofEuropeanreservoirsunder theWaterFrameworkDirectiveusingPRCanalysis 4.1.Abstract……… 89 4.2.Introduction………. 89 4.3.Materialsandmethods……… 91 4.3.1.Studyarea……….. 91 4.3.2.Environmentalparametersandchlorophylla……… 91 4.3.3.Phytoplanktonanalysis……… 95 4.3.4.Statisticalanalysis……… 95 4.4.Results………. 99 4.5.Discussion……… 105 4.6.Conclusions………. 109 4.7.Acknowledgements……… 109 4.8.References……… 109 CHAPTER 5 Ͳ A Stochastic Dynamic Methodology (StDM) for reservoir’s water quality management: validation of a multiͲscale approachinasouthEuropeanbasin(Douro,Portugal) 5.1.Abstract……… 115 5.2.Introduction……… 116 5.3.Materialsandmethods……… 119 5.3.1.Studyarea………. 119 5.3.2.Environmentalparametersandchlorophylla………. 121 5.3.3.Biologicalvariables……… 123 5.3.4.Statisticalanalysisandmodellingprocedures……… 123 5.4.ResultsandDiscussion………. 127 5.4.1.MultiͲlevelinteractions……… 127 5.4.2.Conceptualizationofthemodelandequations……… 129 5.4.3.Modelsimulations………. 136 5.5.Conclusions………. 142 5.6.Acknowledgements……… 142 5.7.References……… 143

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iii CONTENTS TableofContents

CHAPTER 6 Ͳ Modelling multiͲscale approach to simulate relevant spatial and dynamic ecological patterns for reservoir’s water quality management:ScenarioͲtesting 6.1.Abstract……… 149 6.2.Introduction………. 149 6.3.Materialsandmethods……… 152 6.3.1.Studyarea……….. 152 6.3.2.Environmentalparametersandchlorophylla……….. 154 6.3.3.Biologicalvariables………. 156 6.3.4.StatisticalanalysisandmodellingproceduresͲStDM……… 156 6.3.5.CellularAutomataandLandUseChangeͲCA………. 159 6.3.6.Scenariosimulations………. 162 6.4.ResultsandDiscussion………. 165 6.5.Conclusions………. 170 6.6.Acknowledgements……… 172 6.7.References……… 173 CHAPTER 7 Ͳ Final remarks and future perspectives: Function and managementofPortuguesereservoirs

7.1.Finalremarks……….. 179 7.2. FutureperspectivesforWFDimplementationandadaptationtoclimatechange onmanagementprocesses………… 188 7.3. References……… 191 APPENDIX Appendix1……… 195 Appendix2……… 201

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v FIGURES ListofFigures

LISTOFFIGURES

CHAPTER1ͲGeneralIntroduction Figure1.NumberoflargedamsinMediterraneancountries.……… 7 Figure2.Decisionschemefordeterminingreferenceconditions,basedonthedata availability………. 13 Figure3.Thedevelopmentofecologicalandenvironmentalmodels………. ₁₆ Figure 4. Diagram representing the major steps needed for assessing the ecological

integrity of the Portuguese hydroelectric reservoirs studied in this thesis. The underlinewordsrepresentthetwomethodologiesnotusedintheEstablishment of_{theTypeͲspecificreferenceconditions.……… 21}

CHAPTER2ͲMultiͲscaleapproachusingphytoplanktonasafirststeptowards thedefinitionoftheecologicalstatusofreservoirs

Figure 1. Location of the 34 reservoirs studied and their distribution through six catchments: Ave, Cávado, Mondego, and the Portuguese part of the international_{basinsofLima,DouroandTagus……….. 30} Figure 2. Classification of sites by Ward's method based on cityͲblock distance, with

environmental data set. The discontinuous line is the cutting line for defining tworeservoirs’sgroupsandsubgroupsofGroup1(G2.1andG2.2).SeeTable1 for_{reservoirs’sabbreviations………. 38} Figure 3. (a) Discriminant analysis of environmental data relative to cluster structure.

Axis interpretation is based on correlation between each variable and the first two discriminant factors. (b) Spatial distribution of the defined reservoirs’ groups.Filled(blue)andemptysymbols(red)representreferenceandimpaired reservoirs,respectively.……….. ₄₁ Figure 4. Differences in some environmental variables concentrations, from epiͲ and

hypolimnion,inthetwogroupsofreservoirsandwithineachgroup,inreference (blue)andimpaired(red)sites.BoxandWhiskerdiagramsshowmedian,range and 25th

and 75th

percentiles of values for samples in each group.………..₄₃ Figure 5. (a) Site dendrogram and (b) nonͲmetric multidimensional scaling (nͲMDS)

ordination for 34 Portuguese reservoirs, based on phytoplankton assemblage data.(c)nͲMDSforGroup1and(d)Group2,respectively.Dottedlinesindicate reservoir groups produced by cluster analysis. Circles and triangles represent reference_{andimpairedreservoirs,respectively……… 45}

CHAPTER3ͲEcologicalrelationshipsbetweenphytoplanktoncommunitiesand different spatial scales in European reservoirs: implications at catchmentlevelmonitoringprogrammes

Figure1.LocationofthetwoPortuguesereservoirstypesstudiedandtheirdistribution throughsixcatchments:Ave,Cávado,Mondego,andthePortuguesepartofthe international basins of Lima, Douro and Tagus. Triangles and circles represent reservoirsofType1andType2,respectively……….

61

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vi

FIGURES ListofFigures

Figure 2. Canonical correspondence analysis (CCA) of phytoplankton assemblages in Portuguese reservoir in the ordination space of first and second axis; (A) in all studiedreservoirs;(B)in10reservoirsofType1and(C)in24ofType2.(A,Band C)ordinationofsamplingsites,(A1,B1andC1)ordinationofphytoplanktontaxa. Only significant and independent environmental variables are shown. Full environmentalvariableandphytoplanktontaxanamesaregiveninTable1and Appendix1,respectively………. 69 Figure 3. Variance partitioning of phytoplankton communities (pCCA) in reservoirs of

Type 1 (A, B) and Type 2 (C, D) using environmental variables at three spatial scalesandtime.InAandC,overalljointeffectswerenotfurthersubdivided.InB andD,Unique(graybars)andjoint(blackbars)effectsaregivenseparatelyfor eachscale:time(T),local(L),regional(R)andgeographical(G).GRTLrepresents variance_{explainedbyallenvironmentalvariables……….. 74} Figure4.PartialCanonicalCorrespondenceAnalysisforthetwotypesofreservoirs,with

157 taxa and environmental variables at three different spatial scales: geographical_{(G),regional(R)andlocal(L).1and2refertoreservoirsoftype1} and 2, respectively. Full environmental variable and phytoplankton taxa names aregivenintable1andAppendix1,respectively.Onlytaxawithhigherfitand best_{correlatedwithaxisoneareshown.……….. 76}

CHAPTER 4 Ͳ Assessing environmental quality of European reservoirs under theWaterFrameworkDirectiveusingPRCanalysis

Figure 1. Location of the 34 reservoirs studied and their distribution through six catchments: Ave, Cávado, Mondego, and the Portuguese part of the international basins of Lima, Douro and Tagus. Triangles and circles represent reservoirsofType1andType2;Fullandopensymbolsrepresentimpairedand reference_{sitesoneachtype,respectively………. 92} Figure 2. Comparison of species richness from reference and impaired sites of both

reservoirtypes(A).FiguresBandCshow,forreferenceandimpairedsites,the comparisonbetweenthediversityofthephytoplanktoncommunitiesassociated only to well known tolerant taxa, namely Chlorophyta, Cyanophyta and mesoͲ eutraphentic to hypereutraphentic diatoms, of Type 1 and Type 2, respectively……… 100 Figure 3. Diagram showing the first component of the PRC of the differences in taxa

composition of the phytoplankton (A) and measured physicoͲchemical parameters(B)betweentheType1reservoirshavingdifferentecologicalstatus (II through V). The taxa and parameter weights shown in the right part of the diagramrepresenttheaffinityofeachtaxaandparameter,respectively,withthe response shown in the diagram. For the sake of clarity, only species with a weightlargerthan1orsmallerthanͲ1andparameterswithaweightlargerthan 0.25orsmallerthanͲ0.25,areshown.Insamplingdate,1,2,3and4represent spring,_{summer,autumnandwinterofeachyear,respectively………... 102} Figure 4. Diagram showing the first component of the PRC of the differences in taxa

composition of the phytoplankton (A) and measured physicoͲchemical parameters(B)betweentheType2reservoirshavingdifferentecologicalstatus (I through V). The taxa and parameter weights shown in the right part of the

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vii FIGURES ListofFigures

diagramrepresenttheaffinityofeachspeciesandparameter,respectively,with the response shown in the diagram. For the sake of clarity, only taxa with a weightlargerthan1orsmallerthanͲ1andparameterswithaweightlargerthan 0.25orsmallerthanͲ0.25,areshown.Insamplingdate,1,2,3and4represent spring,summer,autumnandwinterofeachyear,respectively………... 104

CHAPTER5ͲAStochasticDynamicMethodology(StDM)forreservoir’swater qualitymanagement:validationofamultiͲscaleapproachina southEuropeanbasin(Douro,Portugal)

Figure 1 Ͳ Location of the study area in the Douro river basin with the different watershedsandrespectivereservoirs,usedasdatasourcesintheconstructionof theStDMmodel:Crestuma(CRT),Carrapatelo(CRP),Varosa(VRS),Régua(RG), VilarͲTabuaço(VLR),Valeira(VAL),Pocinho(PCN),Bemposta(BMP),Picote(PCT) andMiranda(MRD).ThedatafromtheTorrão(TR)reservoir(dashedarea)was separatedforvalidationpurposes……….. 120 Figure2ͲConceptualdiagramofthesubͲmodelusedtopredictthesoilusedynamics,

representing the level 1 in the global StDM model, the base for assessing the ecologicalstatusofthereservoirsintheDourowatershed.The specification of allvariablecodesisexpressedinTable1……… 130 Figure 3 Ͳ Conceptual diagram of the subͲmodel used to predict the responses of the

water column environmental variables to changes due to soil use dynamics, representingthelevel2intheStDMmodelfortheDourowatershedreservoirs. ThespecificationofallvariablecodesisexpressedinTable1……… 132 Figure 4 Ͳ Conceptual diagram of the subͲmodel used to predict the responses of

biological variables to changes in the water column environmental variables, representinglevel3intheStDMmodelfortheDourowatershedreservoirs.The specificationofallvariablecodesisexpressedinTable1………. 134 Figure5ͲConceptualdiagramsofthesubͲmodelusedtogeneratemonthlystochastic

calculations from the environmental data incorporated into the model: (A) standard diagram used for physical stochastic variables, and (B) standard diagramusedformonthlymeteorologicalstochasticsimulations.Forillustration purposes, the diagrams for the volume of the reservoir (VOL) and cumulative precipitation(CPREC)areshownasrespectiveexamples……… 135 Figure6ͲGraphicalcomparisonsbetweensimulations(dottedline)andobservedvalues (solidline)forthephysicochemicalvariables,thelevel2oftheStDMmodel.The specificationofthevariablecodesisexpressedinTable1……… 138 Figure7ͲGraphicalcomparisonsbetweensimulations(dottedline)andobservedvalues (solidline)forthebiologicalvariablesandforthetrophicstatusindicesanalysed, the level 3 of the StDM model. The specification of the variable codes is expressedinTable1……….. 140

CHAPTER6ͲModellingmultiͲscaleapproachtosimulaterelevantspatialand dynamic ecological patterns for reservoir’s water quality management:ScenarioͲtesting

Figure 1 Ͳ Location of the study area in the Douro river basin with the different watershedsandrespectivereservoirs,usedasdatasourcesintheconstructionof

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viii

FIGURES ListofFigures

theStDMmodel:Crestuma(CRT),Carrapatelo(CRP),Varosa(VRS),Régua(RG), VilarͲTabuaço(VLR),Valeira(VAL),Pocinho(PCN),Bemposta(BMP),Picote(PCT) andMiranda(MRD).ThedatafromtheTorrão(TR)reservoir(dashedarea)was usedforscenariossimulationpurposes……….. 153 Figure2ͲConceptualdiagramoftheStDMmodelusedtoassesstheecologicalstatusof thereservoirsintheDourowatershed,inamultiͲscaleapproach.Themodelis composed by different subͲmodels and their interactions: Level 1, soil use dynamics model; Level 2, predict the responses of the water column environmentalvariablestochangesduetolandusechanges;Level3,predictthe responsesofbiologicalvariablestochangesinenvironmentalvariables……… 158 Figure 3 – Diagram flow showing the relations between Stella, GIS and the Cellular

Automata(CA).TheseproceduresaredescribedinSection2.5ofthetext…………. 161 Figure 4 – Exemplificative diagram of the application of the Cellular Automata (CA)

transitionalrules.Thesimulationalgorithmincreasestheareaofaspecifiedland use(landuseA),asindicatedbytheoutputStellafile,throughtheidentification of_{thenearestneighbours(landuseB,decreased)………} 163 Figure5–StDMcomputersimulationsfortheaveragevaluesofaquaticenvironmental

(Level 2) and biological variables (Level 3) from the Torrão reservoir water columnthroughaperiodof10years.Thelinesresultfromtheaveragevaluesof 10 monthly stochastic simulations based on the scenario described in Table 3. The_{specificationofthevariablecodesisexpressedinTable1……….. 166} Figure 6 – StDM computer simulations for the average values of trophic state indices,

namely TSI for chlorophyll a, Total phosphorus, Total N and Secchi depth from theTorrãoreservoirwatercolumnthroughaperiodof10years.Thelinesresult from the average values of 10 monthly stochastic simulations based on the scenario described in Table 3. The dotted lines represent the limits of the differentreservoirtrophicstatelevels,fromoligotrophy(<30)tohypereutrophy (>70)_{(seeTable2fordetails).……… 167} Figure 7 Ͳ StDM computer simulations showing the seasonal yearly pattern of

phytoplanktonsuccession,representedbydiatoms(DTM),greenalgae(CLP)and cyanobacteria(CN)richnessandchlorophyllaconcentration,inTorrãoreservoir. Thelinesresultfromtheaveragevaluesof10monthlystochasticsimulations,for the first year simulated, based on the scenario described in Table 3……… 168 Figure8–CellularAutomatasimulation,throughaperiodof10years,oflandusechange

inTorrãowatershed,basedonthescenariodescribedinTable3.(A)represents theinitialstateand(B)thefinaloutput10yearslater………. 171

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ix ListofTables TABLES

LISTOFTABLES

CHAPTER1ͲGeneralIntroduction

Table 1 – Impacts of reservoirs in the downstream water quality (modified from Jørgensenetal.2005)

9

CHAPTER2ͲMultiͲscaleapproachusingphytoplanktonasafirststeptowards thedefinitionoftheecologicalstatusofreservoirs

Table 1 Ͳ Ranges and median values of important limnological properties of the 34 reservoirssurveyedsince 1996to2004.a)“RunͲofriver”reservoir;b)Reservoir. Trophicstate:1,UltraͲoligotrophic;2,Oligotrophic;3,Mesotrophic;4,Eutrophic; 5,Hypereutrophic.Ecologicalstatus:fromI,HighstatustoV,Lowstatus.……… ₃₄

Table 2 Ͳ Median values and standard deviation (S.D.) of important limnological

propertiesofthetwogroupsofreservoirs,andwithineachgroupcharacteristics ofreferenceandimpairedsites……… 39 Table3ͲPercentagebreakdownofaveragedissimilaritybetweengroupsofreservoirs,

and groups of impaired vs. reference sites for all reservoirs with hydroelectric powerinPortugal,usingSIMPERanalysis.GlobalRͲvaluesforthepairwiseanalysis ofsimilarity(ANOSIM)tests.Onlyp<0.001(***)wasregardedassignificant…………. 44 Table 4 – Average contribution (Ct%) of species mainly responsible for intraͲgroup

similarities:a)withineachgroupandwithinreferenceandimpairedsites(n=34); b)withinreferenceandimpairedsitesforeachgroup………. 47

CHAPTER3ͲEcologicalrelationshipsbetweenphytoplanktoncommunitiesand different spatial scales in European reservoirs: implications at catchmentlevelmonitoringprogrammes

Table1–Characterizationofthe34studiedreservoirs,sampledfrom1996to2006.……… 63 Table 2 Ͳ Number of taxa, samples and sites, total inertia and conditional effects

(lambda)ofspatial(G,RandL)scalesandtimeonphytoplanktonassemblagesfor all,type1andtype2reservoirs.(pCCA)ExplanatoryvariablesusedinpCCAs.*p< 0.05;**p<0.001;n.s.,p>0.05………... 65 Table 3 Ͳ Results of multivariate regression models of taxa (CCA) with environmental

variablesatdifferentspatialscales………. 68

CHAPTER 4 Ͳ Assessing environmental quality of European reservoirs under theWaterFrameworkDirectiveusingPRCanalysis

Table 1 – Sampling periodicity and median values of important physic and hydromorphologicalfactorsofthe34reservoirssurveyedsince1996to2004………. ₉₃ Table2–Spatialvariablesusedtodeterminetheecologicalstatusofthereservoir’

watersheds. ₉₄ Table3ͲMedianvaluesandstandarddeviation(sd)ofimportantlimnologicalproperties ofthefiveecologicalstatusclasses,fromthetwotypesofPortuguesereservoirs surveyedsince1996to2004.Ecologicalstatus:fromclassI,HighstatustoclassV,

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x

TABLES ListofTables

Low status. Response to perturbation: increase (ј), decrease (љ) and variable

(џ).……….

96 Table 4 – Environmental variables, respective codes and transformations used in the

principalcurveresponse(PRC)analysis.……… 98

CHAPTER5ͲAStochasticDynamicMethodology(StDM)forreservoir’swater qualitymanagement:validationofamultiͲscaleapproachina southEuropeanbasin(Douro,Portugal)

Table 1 – Codes and mean values for all the variables used in the StDM model constructionandvalidation………. 122 Table2ͲTheregressionequations,coefficientofdetermination(R2),FͲvaluesandtheir

significance level (*** P < 0.001) for all the variables combination selected as significantbystepwisemultipleregression.Forbiologicalvariablesthedry(D)and wet (W) months were discriminated. The specification of all variable codes is expressedinTable1.………. 128 Table3ͲRegressionanalysis(MODELII)results:intercepts,slopesandrespective95%

confidence limits (in parenthesis), degrees of freedom (d.f.), coefficient of determination(R2 ),FͲvaluesandtheirsignificancelevel(*P<0.05;**P<0.01; ***P<0.001)foralltheobservedvs.expectedvaluesoftheenvironmentaland thebiologicalvariablesconsideredfortheTorrãoreservoir.(n.s.)notsignificant. The_{specificationofallvariablecodesisexpressedinTable1……… 137}

CHAPTER6ͲModellingmultiͲscaleapproachtosimulaterelevantspatialand dynamic ecological patterns for reservoir’s water quality management:ScenarioͲtesting

Table 1 – Codes and mean values for all the variables used in the StDM model constructionandsimulations.……… 155 Table2–Alistofpossiblechangesthatmightbeexpectedinanorthtemperatelakesor reservoirsastheamountofalgaechangesalongatrophicstategradient(basedon CarlsonandSimpson,1996)……… 160 Table3–MajorcharacteristicsofthescenarioadoptedforTorrãoreservoirtakinginto accounttheDouroRiverBasinPlan(modifiedfromINAG,2000)………. 164

CHAPTER7ͲFinalremarks

Table 1 – Synopsis of the 5 approaches developed to assess the ecological integrity of Portuguese reservoirs: objectives, main conclusions of each chapter and its applicationintheWFD.………. 181

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G

eneral

Introduction

Based on: João Alexandre Cabral, Edna Cabecinha, Mário Santos, Paulo Travassos and

Pedro SilvaͲSantos. 2008. Simulating the ecological status of changed ecosystems by holistic applications of a new StochasticͲDynamic Methodology (StDM). In: Alonso M. S. and Rubio I. M. (Eds), Ecological Management: New Research. Nova Science Publishers, Inc.,NewYork.(inpress)

EdnaCabecinha,PedroSilvaͲSantos,RuiCortesandJoãoAlexandreCabral.2007.Applying a StochasticͲDynamic Methodology (StDM) to facilitate ecological monitoring of running waters, using selected trophic and taxonomic metrics as state variables. Ecological Modelling207:109Ͳ127.

EdnaCabecinha,RuiCortesandJoãoAlexandreCabral.,2004.PerformanceofastochasticͲ dynamic modelling methodology for running waters ecological assessment. Ecological Modelling175:303Ͳ317.

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3 CHAPTER1 GeneralIntroduction

1.1.Thesisframework

Thequalityandavailabilityoffreshwaterisone,ifnotthemost,essentialdeterminantsfor the health of ecosystems and human societies worldͲwide. Nevertheless, due to the pressuresofincreasingpopulationanddevelopingeconomyallovertheworld,thepresent situationofwaterqualityandrivermanagementisfarfromsatisfactory.Therecognitionof damaging effects of the destruction of habitats, chemical pollution, eutrophication and climaticalterationsontheaquaticorganisms,asaresultofthehumanactivities,combined with an urgent need of a more sensitive environmentally management of reservoir and ecologically sustainable, led the development of methods that improve the assessment of the ecological condition of these systems. Thus, in the present work were developed innovativemethodologiesthroughtheconjugationofmultivariatemethods,modellingand geographical information systems, to assess and manage the ecological integrity of Mediterranean lentic ecosystems, namely of Portuguese reservoirs with hydroelectric generation. This thesis attempted to overcome some of the actual gaps verified in the managementandmonitoringofthesesurfacewaters.

Toassesstheecologicalstatusofthestudiedaquaticecosystemsandtobetterunderstand the occurring changes in the structure and functioning of Portuguese reservoirs, were incorporated several ecosystem components (e.g. hydromorphological, physical, chemical and biological) and several disturbance factors (e.g. land use changes, hydrometric variations, point and nonͲpoint source pollution, etc.) at different spatial and temporal scalesofanalysis.

The thesis is structured into seven chapters based in the analysis of longͲterm data bases collectedinthefield,bytheLaboratoryofEnvironmentalandAppliedChemistry(LABELEC) managed by the Portuguese Electricity Group (EDP), in five different hydrographic regions (Lima,CavadoandAve,Douro,MondegoandTaguscatchment),locatedinNorthandCentre of Portugal. Exception made for chapters 5 and 6, which were based only in the Douro’s catchment data base. This information was complemented with extensive matrices arising fromanintensebibliographicalresearchandrequesttoseveralPortugueseentities.

The thesis consists of seven chapters. The scientific articles and the book chapter that compose the introduction and the core of this thesis (five chapters) were published,

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4

CHAPTER1 GeneralIntroduction

accepted for publication or submitted in international journals belonging to the Journals Citation Report (JCR) basis. The structure and original content of these documents were maintained in the essential. Additionally, a patent based in the developed modelling environmental management tool, a Sthocastic Dynamic Methodology (StDM) model was submitted(PT103753,pat.pend.). Theindividualchaptersarebrieflydescribedinthenextparagraphswhichfurtherelucidate thespecificgoalsoftheresearch. Thepresentchaptergivesanoverviewofthe“stateoftheart"relatedtothedevelopment ofreservoirsandtheirsustainablewatermanagementandecologicalevaluationprocedures throughtheintegrationamoredynamicandholisticvisionoftheseaquaticecosystems.At the watershed level, the related physical, chemical and biological processes are numerous withcomplexinteractions.ToretrievethisinteractionasrequestedbytheEuropeanWater Framework Directive (WFD), in this chapter are highlight the significant efforts needed to analyze the relevant information, simulate the related processes, evaluate the resulting impacts, and generatesound decision alternatives. Therefore, the application of modelling techniques as decision support tools, that provide an important instrument to the implementation of the WFD as well as potentiate a meaningful dialogue among stakeholders,areexplored.

Chapter 2 establishes, through a multiͲscale approach, the typology of the Portuguese

hydroelectricreservoirsbasedonbioticandabioticqualityelements,namelyphytoplankton as water quality indicator. In this chapter, the TypeͲspecific reference condition for each reservoir Type was also defined, fundamental to the classification of reservoir’s ecological statusbasedonadeviationfromreferenceconditions,whichisthebasisoftheecological assessment.

Chapter 3 determines the importance of environmental variables at different spatial

(geographical, regional and local) and time scales (seasons, years) on the phytoplankton communitystructureofthetwoPortuguesereservoirsTypes.Theindividualimportanceof thethreespatialscalesandtimeinthecommunities’assemblageswasassessedbyvariance partitioning,thoughmultivariateanalysis.

Chapter 4 explores a suitable way of monitoring and assess ecosystem health of the two

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5

Response Curve (PRC) method was used to analyse changes in species composition and environmental variables between different sites over time. This allowed to estimate, in a temporal basis, the degree of impairment at a particular site by contrasting it with a referencesite,asproposedbyWFD.

Chapter5explorestheapplicabilityofaholisticStochasticDynamicMethodology(StDM)in

predictingthetendenciesofphytoplanktoncommunitiesandphysicochemicalconditionsin reservoirsasaresponsetothechangesintherespectivewatershedssoiluse.Thecaseofthe Douro’s basin was used to test and validate the StDM performance in this multiͲscale approach. StDM is a sequential modelling process developed in order to predict the ecological status of changed ecosystems, from which management strategies can be designed.

Chapter6asanextensionofthepreviousone,examinedtheapplicabilityofthedeveloped

StDM model, coupled with a Cellular Automata (CA) model, in capturing how expected changes at land use level scenarios will alter the reservoir water quality, namely at physicochemicalandphytoplanktonlevels.ThemethodologywasappliedtothePortuguese area of the Douro’s basin and illustrated with a series of stochasticͲdynamic and spatial outputs taking into account expected scenarios regarding land use changes. This kind of approachcouldbeveryuseful,fordecisionsupport,asaninvestigativetooltoforecastthe outcome of various scenarios and to guide current management in order to meet future targetsandtodevelopintegratedframeworksformanagementaccordinglytotheWFD. Finally,intheChapter7themainconclusionsofthepreviouschapterswerediscussed,their relevantachievementstowardsintegrativeandholisticanalysisofaquaticsystemsand,also, the new challenges in water management and WFD implementation facing the worldwide climatechangescenario.

The ultimate objective of this thesis is to provide methods that can be an object of enhancementforapplicationinotherregionsandthatmaycontributetothedevelopment of new assessment methodologies leading to an improvement of the characterization techniques and management strategies of aquatic ecosystems. To a national scale, the information contained in this thesis looks for participating in the implementation of the WFD,inthenextstageforthedefinitionofthemonitoringprograms,namelyby:

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6

identifyingreferenceconditions,

selectingrelevantecologicalindicatorsforassessmentofecologicalcondition; settingtheenvironmentaldescriptorswithbiologicalrelevance;

integratingvariouslevelsofobservationandsetsofvariables(bioticandabioticones) inanintegrativeway;

implementing multiͲscale approaches that may lead the ecological condition of reservoirsandfromwhichmanagementstrategiescanbedesigned.

1.2. Theimperativeneedofriverregulation

Over 45 000 times in the last century, people took the decision to build a dam. Dams or reservoirshavebeenbuilttoprovidewaterforirrigatedagriculture,domesticorindustrial use, to generate hydropower or help control floods. Nevertheless, reservoirs also altered and diverted river flows, affecting existing rights and access to water, and resulting in significant impacts on livelihoods and the environment (ICOLD, 2006). The International Commission on Large Dams (ICOLD, 1998) defined as large reservoirs, those whit a dam height of at least 15 meters and any volume of water, or those with water volumes exceeding1millionm3andofanydamheight.

Theearliestevidenceofriverengineeringistheruinsofirrigationcanalsovereightthousand years old in Mesopotamia. But the first use of dams for hydropower generation, is much more recent, around 1890 (ICOLD, 2007). By 1900, several hundred large dams had been builtindifferentpartsoftheworld,mostlyforwatersupplyandirrigation.Thelastcentury saw a rapid increase in large dam building. By 1949 about 5000 large dams had been constructedworldwide,threeͲquartersoftheminindustrializedcountries.Bytheendofthe 20thcentury,therewereover45000largedamsinover140countries.

The top five damͲbuilding countries account for nearly 80% of all large dams worldwide. Chinaalonehasbuiltaround22000largedams,closetohalftheworld’stotalnumber;the UnitedStatesandIndiahadoversixandfourthousandlargedams,respectively;andSpain andJapanhadover1000largedamseach(ICOLD,1998,2007;WCD,2000).

In the Mediterranean Spain, France, Turkey, and Italy hold the largest number of large dams. Nevertheless, Spain has the highest number of reservoirs per inhabitant worldwide withacapacityofsome50,000hm³(WWF,2006)(Fig.1).

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7 CHAPTER1 GeneralIntroduction 0 500 1000 1500 Albania BosniaͲHerzgovina Croatia France Greece Italy Portugal Slovenia Spain Yugoslavia Cyprus Jordan Lebanon Syria Turkey Algeria Egypt Libya Morocco Tunisia 306 25 29 569 46 524 103 30 1300 69 52 5 5 41 625 107 6 12 92 72 Numberoflargedams So u th Ea s t No rt h Me d ite rr a n e a n Reg io n InPortugal,thesestructuresarerelativelyrecent,mostlyfromthe20thcentury.Nowadays, thereare151largedams,morethanhalfofwhichareforirrigationpurposes,butgeneration of electrical energy play as

well an important role. The biggest o ne is the multipurpose dam of Alqueva at the Guadiana with a maximum height of 152m (ICOLD, 2006). The first studies in Portuguese reservoirs date from 1951 (Frade 1951, 1954, 1957, 1959), in the 80thies the National Institute of Fishery Investigation published the firsts reports using algae as biological pollution indicators (Oliveira, 1982, 1985, 1987). Through the 20th and 21st centuries,

many studies had been made, unfortunately these works cover only a few number of reservoirsandwererestrictedtoashortmonitoringperiods,i.e.,areveryscarcetheworks with longͲterm monitoring data basis and that incorporate a significant part or all the national reservoirs (see for exemple, Cabeçadas et al., 1986; Fereira, 1986; Brogueira and Pereira,1988;Vasconcelos,1991,2001;BoavidaandGliwicz,1996;INAG,2002;Figueiredo et al., 2006; Domingues and Galvão, 2007). Additionally, the Portuguese government have justlaunchedtheNationalProgramfortheDamswithHighHydroelectricPotential,withthe objectives to identify and define the new investments in this area through the 2007Ͳ2020 periods(INAG,2008).Therefore,theconstructionof10newinfrastructuresarenowbeing proposed,namelysixintheDouroriver(AltoTâmega,Daviões,Fridão,FozdoTua,Gouvães andPadroselos),twointheTagusriver(AlmorolandAlvito)andoneinMondegoandVouga

Figure1.NumberoflargedamsinMediterraneancountries. (modifiedfromICOLD,1998,2007;WCD,2000;WWF,2006)

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8

rivers (Girabolhos and Pinhosão, respectively) (INAG, 2008). In this context, we saw reinforcementtheneedtoseekfornewmethodologiesthatallowedtheassessingandthe managementoftheecologicalconditionofthesesurfacewaterbodies.

Thenatureoftheimpactsoflargedamsonecosystemsisgenerallywellknownbyscientists. Ausefulindicatorofthescaleofhumaninterventioninthisregardisarecentestimatethat dams, interͲbasin transfers, and water withdrawals for irrigation have fragmented 60% of theworld’srivers(WWF,2006).

Ecosystemimpactscanbeclassifiedaccordingtowhethertheyare(WCD,2000):

firstͲorder impacts that involve the physical, chemical, and geomorphological

consequencesofblockingariverandalteringthenaturaldistributionandtimingof streamflow;

secondͲorder impacts that involve changes in primary biological productivity of

ecosystems including effects on riverine and riparian plantͲlife and on downstream habitatsuchaswetlands;or

thirdͲorderimpactsthatinvolvealterationstofauna(suchasfish)causedbyafirstͲ

ordereffect(suchasblockingmigration)orasecondͲordereffect(suchasdecrease in the availability of plankton). In addition, changes the biochemical cycle in the naturalriverinesystem.

Ingeneral,thedampurposeisalsothemajorfactorindefiningtheoperatingrulesforthe reservoir. These, in turn, control the water level variations in the reservoir and the flow regimeinthedownstreamriver,bothimportantenvironmentalfactors.Thesewaterbodies and its biological communities are submitted to enormous spatialͲtemporal variations, caused by the hydric resource use regime they are subject. In terms of river hydrology, physical, chemical and biological variables in the downstream river are affected by the reservoirsinvariousways.InTable1arelisted,grossgeneralizationsthatdonotaccountfor multivariate effects, of some of these factors. Further details and many examples are providedbyPetts(1984,1989)andJørgensenetal.(2005).

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9

Table 1 – Impacts of reservoirs in the downstream water quality (modified from Jørgensen et al. 2005) Variable Changesindownstreamwaterquality Physicalvariables Riverchannelstructure Canbesubstantiallychangedbytheerraticwaterflowrates. Hydrobiology Decreaseorincreaseaveragewaterflowrates.

Thermics A decrease in average temperature occurs, with greater retention time and

outletdepth.

Turbidity Decreasesiltloadingsoccurs,whichmaycauseadecreaseinfloodsoilfertility.

Detritus Thecompositionparticleschangedfromabiotictobiotic;anditssizedecreases.

Light Lightpenetrationisincreased.

Chemicalvariables

Oxygen Veryaffectedbythereservoirtrophicstateandtheoutletdepth.

H2SandCO2 Concentrations increase, especially in eutrophic, stratified reservoirs with long

waterretentiontimes.

pH Generallydecreases.

Organicmatter Organic matter concentration decreases, if there are no sources of inͲlake

organicproduction. Phosphorus(P) ThePconcentrationsdecreases,andthedegreeofthedecreaseishigherwhen waterretentiontimeandtrophicdegreearegreater. Nitrates Nitratesconcentrationsareusuallynearlyunchanged. Nitrites Nitritesconcentrationsareusuallyincreased. Totalsolids Totalsoliconcentrationsremainnearlyunchanged. Biologicalvariables Phytoplanktoncomposition Thephytoplanktoncompositionchangesdownstream.Insmallrivers,thereisa transitionfromriverine(periphytic)speciestopelagicspecies.Inlargerivers,the numberoflacustrinespeciesincreasesbellowareservoir. Phytoplanktonbiomass andchlorophyllͲa

The quantities depend on the location of the outflow: surface outflows deliver morephytoplanktonandhigherchlorophyllͲacontents.

Zooplankton Zooplanktoncompositionchangesandbiomassusuallyincreasesintheoutflow.

Benthos Compositionisusuallyhighly changed.

Fish Reservoirs represent a barrier to fish migration. Feeding habitats are often

reduced. Fish abundance bellow reservoirs vary greatly, based on the specific conditions.

Therefore,thereservoirmanagementhastotakeintoconsiderationnotonlythereservoir itself, but also the reservoir outflows. People living downstream of a reservoir, fish populationsinthedownstreamriverandotherbiotashouldnotbehighlydisturbedbythe construction or operation of a reservoir (Jørgensen et al, 2005). Reservoir managers, researchers and decision makers must deal with the integration of water quality managementconcernsintotheoverallenvironmentalmanagementplanning.

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10

1.3.WaterFrameworkDirectiveasaguidelineforintegratedriverbasin

managementinEurope

On 23 October 2000 was finally adopted, by the European Parliament and Council, the Directive 2000/60/EC or short the EU Water Framework Directive (WFD) establishing a frameworkfortheCommunityactioninthefieldofwaterpolicy.

An important shift compared to other European Directives related to water policy (e.g. DrinkingWaterDirective,UrbanWasteWaterDirective)isthatanintegratedapproachwas taken. The objectives of water management are not only defined with regard to human needs but attention is also paid to the ecological demands of the aquatic ecosystem With the implementation of the WFD, the different Member States are committed to invest in rivermanagementtoimproveriverhealth.

In general, the directive distinguishes two major goals. First, the development of a managementsystemhastobebasedonnaturalriverbasindistrictswhicharethemainunits for river management (Blöch, 1999). Further, river basins and subͲbasin are to be distinguished. The second goal of the directive is the development of river basin managementplansandprogrammesofmeasurestoachieveatleasta‘goodsurfacewater status’in2015foralEuropeanwaterbodies.Intermsofenvironmentalobjectives,a‘good surfacewaterstatus’meansthestatusachievedbyasurfacewaterbodyisatleast‘good’for both its ecological status, or its ecological potential for a heavily modified or an artificial water body, and its chemical status. For reservoirs, as heavily modified water bodies (HMWB), the reference conditions on which status classification is based are within the range of “Maximum Ecological Potential” (MEP). The MEP represents the maximum ecological quality that could be achieved for these systems, once all mitigation measures thatdonothavesignificantadverseeffectsonitsspecifieduseoronthewiderenvironment havebeenapplied(GIG,2007).

IntheWFDtheecologicalstatusofsurfacewaterisdefinedas“…anexpressionofthequality of the structure and functioning of aquatic ecosystems associated with surface waters, classified in accordance with Annex V”. This implies that the classification systems of the ecologicalstatusofwaterbodiesshouldreflectthechangesinthestructureofthebiological communities and in the overall ecosystem functioning as a response to anthropogenic pressures. Therefore, the ecological status of a water body includes a combined effect of