fmartinho phd thesis 2009 - pdf - estudo geral · estuarine fish assemblages as indicators of...

Estuarinefishassemblagesasindicatorsofenvironmental

changes:theMondegoestuarycasestudy

DoctoraldissertationinBiology(ScientificareaofEcology)presentedtotheUniversityofCoimbra

DissertaçãoapresentadaàUniversidadedeCoimbraparaobtençãodograudeDoutoremBiologia(especialidadeemEcologia)

FilipeMiguelDuarteMartinho

UniversityofCoimbra

2009

Estuarinefishassemblagesasindicatorsofenvironmentalchanges:theMondegoestuarycasestudy

II

Thisthesiswassupportedby:

InstitutodeInvestigaçãoInterdisciplinar

UniversityofCoimbra

PhDgrantattributedtoFilipeMartinho

III/AMB/33/2005

IMAR–InstituteofMarineResearch

UniversityofCoimbra

Fundingandsupport

FacultyofSciencesandTechnology

UniversityofCoimbra

FacultyofSciences

UniversityofLisbon


III

Thisthesisisbasedonthefollowingmanuscripts:

Martinho,F.,Leitão,R.,Viegas,I.,Neto,J.M.,Dolbeth,M.,Cabral,H.N.,Pardal,M.A.,2007.The

influenceofanextremedroughtevent inthe fishcommunityofasouthernEurope temperate

estuary.Estuarine,CoastalandShelfScience75:537‐546.

DOI:10.1016/j.ecss.2007.05.040.

Martinho, F., Dolbeth, M., Viegas, I., Cabral, H.N., Pardal, M.A., 2009. Does the flatfish

community of theMondego estuary (Portugal) reflect environmental changes? Submitted to

JournalofAppliedIchthyology.

Martinho, F., Dolbeth, M., Viegas, I., Teixeira, C.M., Cabral, H.N., Pardal, M.A., 2009.

Environmentaleffectsontherecruitmentvariabilityofnurseryspecies. Estuarine,Coastaland

ShelfScienceinpress.

DOI:10.1016/j.ecss.2009.04.024

Martinho, F.,Dolbeth,M.,Viegas, I.,Cabral,H.N.,Pardal,M.A.,2009. Sampling estuarine fish

assemblageswith beam and otter trawls: differences in structure, composition and diversity.

SubmittedtoEstuarine,CoastalandShelfScience.

Martinho, F., Viegas, I., Dolbeth, M., Leitão, R., Cabral, H.N., Pardal, M.A., 2008. Assessing

estuarineenvironmentalqualityusingfish‐basedindices:performanceevaluationunderclimatic

instability.MarinePollutionBulletin56:1834‐1843.

DOI:10.1016/j.marpolbul.2008.07.020


V|Contents

CONTENTS

ABSTRACT 1

RESUMO 5

GENERALINTRODUCTION 9

Estuaries:drivers,pressuresandresponses 9

Estuarinefishfauna 11

Recruitmentvariabilityofmarinespecies 13

Climateforcingandsystems’changes 16

Assessingecologicalstatusoftransitionalwaters 18

Studysite–theMondegoestuary 21

References 24

GENERALAIMANDTHESISOUTLINE 35

CHAPTERI

TheinfluenceofanextremedroughteventinthefishcommunityofasouthernEurope

temperateestuary

39

Introduction 41

MaterialsandMethods 43

Results 46

Discussion 52

References 60

CHAPTERII

DoestheflatfishcommunityoftheMondegoestuary(Portugal)reflectenvironmental

changes?

65


VI|Contents

Introduction 67


Results 71

Discussion 78

References 86

CHAPTERIII

Environmentaleffectsontherecruitmentvariabilityofnurseryspecies 93

Introduction 95


Results 100

Discussion 105

References 114

CHAPTERIV

Samplingestuarinefishassemblageswithbeamandottertrawls:differencesin

structure,compositionanddiversity

121

Introduction 123


Results 128

Discussion 135

References 145

CHAPTERV

Assessingestuarineenvironmentalqualityusingfish‐basedindices:performance

evaluationunderclimaticinstability

151

Introduction 153


VII|Contents


Results 162

Discussion 168

References 175

GENERALDISCUSSION 179

Estuarinefishassemblages:structureandcomposition 179

Linkingclimatepatternstorecruitmentvariabilityinfishspecies 182

Managementoftransitionalwaters 186

Conclusions 190

References 190

FUTUREPERSPECTIVES 199

AGKNOWLEDGEMENTS 201


1|Abstract

Abstract

Themain objective of this thesiswas to assess the influence of an extremeweather event

(drought) inthefunctioningoftheMondegoestuary(Portugal)fishassemblage,basedonfield

surveysconductedfrom2003to2007.Theoccurrenceofanextremedroughteventduringthis

time frame, provided an important case study on the effects of a significant reduction in

precipitationandfreshwaterflowinestuarinefishcommunities,namelyattwodifferentscales:

(a)structureandcompositionofthefunctionalguildscomposingtheestuarinefishassemblage,

aswell as the classification of the EcologicalQuality Status, and (b) interannual variability in

abundanceandrecruitmentlevelsinthemarinespeciesthatusetheestuaryasanurseryarea.

The response of theMondego estuary fish assemblage to the droughtwas firstly evaluated

regardingthevariationsinstructureandcompositionofthehabitatuseguildsthatcomposethe

assemblage:estuarine residents,marine juveniles,marine stragglers, freshwater, catadromous

andmarinespeciesthatusetheestuaryasanurseryarea.Thefishassemblagewascomposed

mainly of estuarine residents andmarine species that use the estuary as a nursery area, in

conformityofmostoftheEuropeanAtlanticestuaries.Duringthedroughtperiod,depletion in

freshwater specieswasobserved,whilemarine stragglers increased inabundanceand species

number,asaresponsetoahighersalineintrusioninsidetheestuary.Inaddition,areductionin

abundanceof the estuarine residentswas alsoobserved.Among the environmental variables

analyzed,precipitationwastheonethatbestexplainedthevariabilityinthefishassemblage.

The flatfish communitywasanalyzed inmoredetail,beingpossible todefine threegroupsof

species: one group composed of species present throughout the study period and in high

densities‐PlatichthysflesusandSoleasolea;onegroupcomposedoflessabundantspeciesbut

regularlypresent‐ScophthalmusrhombusandSoleasenegalensis;andanothergroup,composed

ofoccasionalspecies,presentonlyduringthedroughtperiod‐Arnoglossuslaterna,Buglossidium

luteum,DicologlossahexophthalmaandPegusalascaris.Abundancedatawascomplementedby

multivariate analysis,with river runoff, salinity anddissolvedoxygenbeing theenvironmental

variablesthatsignificantlyinfluencedthedistributionofflatfishspecies.Inaddition,thespecies


2|Abstract

mostaffectedbythedroughtevent,inwhichasignificantreductioninabundancewasobserved,

were thosewhose southern limitofdistributionoccurs athigher latitudes. Inopposition, the

flatfishassemblageof theMondegoestuarywascomposedofahigherspeciesnumberduring

thedrought, as a consequenceofan increase inmarine straggler species, typicalof southern

latitudes.Earlysummeraveragesalinityandprecipitationvalueswereappointedasgoodproxies

for estimating abundance levels of P. flesus and S. solea, respectively, emphasizing the

importance of hydrodynamics for the recruitment and abundance of these commercially

importantspecies.

The interannual variability in abundance of 0‐group fish of themarine species that use the

Mondego estuary as a nursery area was evaluated, and related to a set of environmental

variables.ForDicentrarchuslabraxandP.flesus,adecreasingtendencyinabundanceof0‐group

fishwas observed,with river runoff,precipitation and the east‐westwind componenthaving

been identified as variableswith significant influence for both species. The north‐southwind

componentwasalsosignificantforP.flesus.TheabundancepatternsofS.solea juvenileswere

onlyrelatedwithriverrunoff from theMondegoRiver,with the lowestdensities foundduring

the drought.However, after the drought, S. solea 0‐group fish densities increased to similar

levels of 2003. Taking into account the recent climate change projections for the Iberian

Peninsula,namelyareductioninprecipitationlevels,thisstudyledtotheconclusionthatmarine

specieswhose recruitmentoccurs in early spring (D. labrax andP. flesus) are expected tobe

moreaffectedbyalesserextentofriverplumestocoastalareas.

Toevaluatetheinfluenceofsamplinggearinthedeterminationofthestructureandcomposition

of the Mondego estuary fish assemblage, two commonly used fishing gears for scientific

purposeswere compared ‐ beam and otter trawl.Despite both sampling gears provided the

same species richness (20 espécies), the structure and composition of type‐specific fish

assemblages was to some extent divergent, with a higher relative abundance of estuarine

residents in beam trawl samples driving the main differences. Regarding the commercially

importantandmostabundantspeciesinbothgears,D.labrax,P.flesusandS.solea,differences


3|Abstract

in median total length and length‐frequency distributions were observed, with beam trawl

samplesproviding individuals thatbelong tosmaller length‐classes,adetermining factorwhen

targeting0‐groupfish inrecruitmentstudies.Abundanceestimatesforthesespecieswerealso

different inboth sampling gears,which canbe related todifferences in spatialoccupationof

differentsize‐classesalong theestuary,as larger fish tend tomove todeeperestuarineareas.

Regarding the compliancewith theWater FrameworkDirective (WFD),different structuresof

estuarine fish assemblagesmayprovidewithdifferent classificationsof the EcologicalQuality

Status(EQS).

Also in the contextof theWFD, the classificationof theEQSof theMondegoestuaryby five

selectedmultimetric fish‐based indiceswas compared,aswellas the indices’ responses toan

extremedrought.TheselectedindicesweretheEBI(Deeganetal.,1997),EDI(Borjaetal.,2004),

EFCI(HarrisonandWhitfield,2004),EBI(Breineetal.,2007)andTFCI(Coatesetal.,2007).Based

on these indices, theEQSof theMondegoestuary rangedbetween “Poor”and“High” status,

evidencingthehigh levelofmismatchamongmethodologies.TheEBI (Breineetal.,2007)was

the only index that evidenced clear interannual and seasonal variations, while others were

seasonallyconstant.TheEDI(Borjaetal.,2004)andTFCI(Coatesetal.,2007)classifiedregularly

theMondegoestuarywith thehigheststatus,beingproposedas themostsuitable indices for

application in this estuary. The results are examined in the scope of the EUWFD, regarding

monitoringstrategies,applicationofindicesandEQSassessment.


5|Resumo

Resumo

A presente tese teve como objectivo principal avaliar a influência de um evento climático

extremo (seca) no funcionamento da comunidade piscícola do estuário do Rio Mondego

(Portugal),tendocomobasecampanhasdeamostragemrealizadasde2003a2007.Aocorrência

deuma seca extremaduranteoperíodode amostragem,permitiuum casode estudomuito

importanteemqueosefeitosdeumareduçãosignificativanaprecipitaçãoenocaudaldoRio

Mondegoforamavaliadosnacomunidadedepeixesestuarinos.Arespostadestascomunidades

à seca extrema foi avaliada em escalas distintas: (a) estrutura e composição dos grupos

funcionais que constituem a comunidade, bem como a classificação do Estado deQualidade

Ecológica (EQE), e (b) variabilidade interanual na abundância e níveis de recrutamento nas

espéciesmarinhasqueutilizamoestuáriocomozonadeviveiro.

A respostada comunidadepiscícolado estuáriodoMondego à seca foi inicialmente avaliada

tendoemcontaavariaçãonaestruturaecomposiçãodosgruposecológicosrelacionadoscomo

uso do habitat: residentes estuarinos, marinhos juvenis, marinhos ocasionais, espécies

dulçaquícolas,migradorescatádromoseespéciesmarinhasqueutilizamoestuáriocomozonade

viveiro.Osgruposmaisabundantesnacomunidadeforamosresidentesestuarinoseasespécies

marinhasqueutilizamoestuário como zonade viveiro,em conformidade com amaioriados

estuários da costa Atlântica europeia. Durante o período de seca, foi observado o

desaparecimento das espécies dulçaquícolas, enquanto que as espéciesmarinhas ocasionais

aumentaram em abundância e em riqueza específica, em resposta a umamaior extensão da

cunhasalinanointeriordoestuário.Nomesmoperíodo,foiobservadatambémumareduçãona

abundânciadosresidentesestuarinos.Entreasvariáveisambientaisconsideradas,aprecipitação

foiaquemelhorexplicouavariabilidadenacomunidadedepeixes.

A comunidadedePleuronectiformes foi analisada comparticulardetalhe, tendo sidopossível

definir três grupos: um grupo composto por espécies presentes durante todo o período de

estudo e emdensidades elevadas – Platichthys flesus e Solea solea;um grupo compostopor

espéciesmenos abundantesmas também com presença regular – Scophthalmus rhombus e


6|Resumo

Soleasenegalensis;efinalmente,umoutrogrupocompostoporespéciesocasionais,presentes

apenas durante o período de seca – Arnoglossus laterna, Buglossidium luteum, Dicologlossa

hexophthalma e Pegusa lascaris. Os dados relativos à abundância das espécies foram

complementados com uma análise multivariada, através da qual foram determinadas as

variáveis ambientais que influenciaram significativamente a distribuição destas espécies no

estuáriodoMondego:escoamento,salinidadeeoxigéniodissolvido.Asespéciesmaisafectadas

pela seca, para as quais foi observada uma redução significativa na abundância, foram as

espéciescujo limiteSuldadistribuiçãoocorrea latitudesmaiselevadas.Duranteoperíodode

seca,acomunidadedePleuronectiformesapresentouumamaiorriquezaespecíficadevidoaum

aumento de espéciesmarinhas ocasionais, típica de zonas demenor latitude.Os valores de

salinidademédiaeprecipitaçãodoiníciodoVerãoforamapontadoscomobonspredictorespara

estimarosníveisdeabundânciadeP.flesuseS.solea,respectivamente,realçandoaimportância

dahidrodinâmicaparaorecrutamentoeabundânciadestasespéceiscominteressecomercial.

A variabilidade interanual nos níveis de abundância de juvenis das espécies marinhas que

utilizamoestuário como zonadeviveiro foramavaliadase relacionadas comum conjuntode

variáveisambientais.ParaDicentrarchus labraxeP.flesus,posteriormenteaoperíododeseca,

foiobservadaumatendênciadecrescentenaabundânciados juvenis,tendosido identificadoo

escoamento, a precipitação e a componente este‐oeste do vento como variáveis explicativas

com influênciasignificativaparaambasasespécies.Acomponentenorte‐suldoventotambém

foisignificativaparaP. flesus.Ospadrõesdeabundânciados juvenisdeS.solea foramapenas

relacionados como escoamentodoRioMondego, tendo sidoobservadas asdensidadesmais

baixas durante o início da seca. Contudo, posteriormente a este período, a abundância dos

juvenisdeS.solea recuperouparavaloressemelhantesaosde2003.Tendoemcontaasmais

recentes projecções para a Península Ibérica relacionadas com as alterações climáticas,

nomeadamente a redução dos valores de precipitação, este trabalho permitiu inferir que as

espéciescujoperíododerecrutamentoocorrenoiníciodaprimavera(D.labraxeP.flesus)serão

asmaisafectadaspelareduçãonaextensãodaplumadosriosnaszonascosteiras.


7|Resumo

Demodo a avaliar a infuência dométodo de amostragem na determinação da estrutura e

composição da comunidade piscícola do estuário do Rio Mondego, duas artes de pesca

usualmenteutilizadasemcampanhasdepescaparafinscientíficosforamcomparadas‐arrasto

devaraearrastodeportas.Apesardeambasastécnicasteremcapturadoomesmonúmerode

espécies (20 espécies), a estrutura e composição das comunidades associadas a cada técnica

foram até certo ponto divergentes, com o arasto de vara a capturar umamaior abundância

relativaderesidentesestuarinos.Noquedizrespeitoàsespéciesdeinteressecomercialemais

abundantesemambasastécnicasdeamostragem,D.labrax,P.flesuseS.solea,foramobtidas

diferenças namediana do comprimento total e também na distribuição das frequências de

comprimentos.As amostrasprovenientesdo arrastode vara foram compostaspor indivíduos

pertencentes às classes de menores comprimentos, um factor determinante no estudo de

padrõesderecrutamentodejuvenis.Asestimativasdeabundânciaparaestasespéciestambém

foramdistintasparaasduasartesdeamostragem.Deacordocomos resultadospreviamente

obtidos, é provável que diferentes determinações da estrutura das comunidades piscícolas

(relacionadocomaartedeamostragem)possainfluenciaraclassificaçãodoEstadodeQualidade

Ecológica(EQE)paraaimplementaçãodaDirectivaQuadrodaÁgua(DQA).

AindanocontextodaDQA, foiavaliadaaclassificaçãodoEQEporcinco índicesmultimétricos

para peixes, tendo sido avaliada também a sua resposta ao período de seca. Os índices

seleccionados foram os seguintes: EBI (Deegan et al., 1997), EDI (Borja et al., 2004), EFCI

(HarrisonandWhitfield,2004),EBI (Breineetal.,2007)eTFCI (Coatesetal.,2007).Tendopor

base estes índices, o EQE do estuário do Mondego variou entre “Pobre” e “Excelente”,

evidenciandoaelevadafaltadecorrespondênciasentreíndices.OEBI(Breineetal.,2007)foio

único índice cujos resultados apresentaram uma clara variação sazonal e interanual,

contrariamenteaosrestantes.OEDI (Borjaetal.,2004)eoTFCI (Coatesetal.,2007)foramos

índicesqueclassificaramregularmenteoestuáriodoRioMondegocomoestadoecológicomais

elevado, tendo sido propostos como os mais indicados para utilização neste sistema. Os


8|Resumo

resultados foram também avaliados no âmbito da DQA, tendo em conta estratégias de

monitorização,aplicaçãodeíndicesedeterminaçãodoEQE.


9|GeneralIntroduction

GeneralIntroduction

Estuaries:drivers,pressuresandresponses

Estuariesareamongthemostproductiveecosystemsoftheworld(Kennish,2002;McLuskyand

Elliott, 2004; Dolbeth et al., 2007b), supporting an important range of flora and fauna. As

transition areas, estuaries are arguably more complex than other ecosystems, with highly

interrelated processes between their physical, chemical and biological components (Molles,

1999;Elliottetal.,2002).Allied to theirhighproductivity, theavailabilityofdifferenthabitats

provides optimal settlement conditions for invertebrates, fish and birds, either for estuarine

residency,asnurseryareasorasmigrationroutes,includingtidalflats,oysterbeds,saltmarshes

andseagrassbeds(Becketal.,2001;Pihletal.,2002;Vasconcelosetal.,2007).Oneofthemain

attributes of estuarine areas is the salinity gradient, from the brackishwaters of the upper

reaches to the euhaline downstream areas. The salinity regime, coupled with the typical

hydrodynamic fluctuations of freshwater flow and seawater intrusion, creates the one of the

maingradientsthatisresponsibleforthedistributionoforganismswithinestuarinewaters(Thiel

etal.,1995;Whitfield,1999;Kimmerer,2002;Leitãoetal.,2007).Moreover,watercirculation

duetotidalandfreshwatercurrents isresponsibleforthetransportoforganisms,nutrientand

oxygencycling(Molles,1999;Gibsonetal.,2003;Lillebøetal.,2004).Asaconsequence,changes

inhydrological regimes,due todroughts, floodsorwater retention indams, can significantly

impacttheestuarinespecies,mainlybythedisplacementofsuitablehabitats(Kimmerer,2002).

Thewiderangeofgoodsandservicesprovidedbyestuarineareas,namelytourism,recreational

areas,protectionagainstfloods,replenishmentofcoastalfisheriesstocks,sedimentandnutrient

cycling, among others, led Costanza et al. (2007) to classify them among themost valuable

ecosystemsonEarth.However,duetotheirprivilegedlocation,estuarineandcoastalareashave

long been subjected to intense human activities, leading to an over‐exploitation of natural

resourcesandtodramaticchanges in land‐use,contributingtothedeteriorationofthenatural

environment (de Jonge et al., 2002;Dauvin andRuellet, 2009) (Fig. 1). These include habitat

destructionby bank reclamation,water quality impoverishmentbydomestic, agricultural and



industrial effluent discharges and nutrient enrichment (Cloern, 2001), and stock depletion by

overfishing.Infact,directdisturbanceonthesediment‐waterinterface(suchastheonecreated

by activities referred before) has the potential to impact estuarine communities through the

manyfunctionallinksbetweenthem(Austenetal.,2002).Ultimately,increasingstresslevelscan

changethewaytheestuarinesystemfunctionsforlocalfish,invertebrateandbirdcommunities,

withstrongimplicationsforthesupplyofgoodsandservices.

Figure1.Continental shelvesof theWorld (dark shade),defining theextensionofcoastalwaters(FromHolliganandReiners,1992).

Nutrientenrichment,andconsequentlyeutrophication, isseenasoneof themajorthreats for

thefunctioningoftheestuarineecosystem.Recently,FlemerandChamp(2006)pointedoutthat

themobilization of nitrogen and phosphorus through land clearing, application of fertilizers,

dischargeofhumanwastes,animalproductionandcombustionoffossilfuelsisthemainsource

of eutrophication in estuaries. Likewise, and especially in densely populated areas, several

effectsofeutrophicationhavebeendescribed,includingthegrowthofopportunisticmacroalgae

andconsequentreductioninseagrassbeds,developmentofanoxiaandhypoxiaevents,andasa

worst case scenario,massmortalityof fish and invertebrate fauna (e.g.Raffaelli et al., 1998;



Cloern,2001;Pardaletal.,2004).Insummary,structuralchangesinlocalcommunitieshavebeen

observed due to eutrophication, mainly by a reduction in species abundance and diversity

(Dolbethetal.,2003;Cardosoetal.,2004,2008;Pardaletal.,2004).

Recently,theDPSIRapproach(e.g.Elliott,2002;BorjaandDauer,2008)hasbeenintroducedfor

managingestuarineandcoastalecosystems,inwhichDrivers(humandemandsonthesystems)

andPressures (thepreciseactivities leading to change) result inStateChanges (in thenatural

features)and Impactson the socio‐economicusesof the systems; the latter in turn requirea

Response in order to reduce,mitigate and/or compensate any adverse effects (McLusky and

Elliott,2004).Thisconceptualframeworkisintendedtoidentifyacausalrelationshipwithinthe

DPScomponentandmostimportantlytodetermineandevaluatehumanandecologicalimpacts

(Borja and Dauer, 2008). This approach, in combination with recently developed worldwide

legislation for the protection ofwater resources, such as the EUWater FrameworkDirective

(WFD,2000/60/EC),theUSCleanWaterAct(USEPA,2002),theEUMarineStrategyFramework

Directive(MSD,2008/56/EC),theNationalLandandWaterResourcesAuditinAustralia(Heapet

al.,2001)andtheWaterActinSouthAfrica(Adamsetal.,2002),willimplyamorerationaluseof

waterresources,butwillalsoprovideaframeworkforanintegratedmanagementofthehighly

variableandvaluableestuarineecosystems.

Estuarinefishfauna

Estuarieshave longbeen regardedas importantareas for fish,actingmainlyasnurseryareas,

migration routes, feeding and shelter areas, providing an alternative habitat to the marine

environmentthatsupportslargenumbersoffish(Haedrich,1983;Becketal.,2001;McLuskyand

Elliott,2004).Overthe lastyears,severalstudieshavebeenconductedregardingestuarinefish

assemblages,tryingtorelatetheoccurrenceoffishspeciesinrelationwiththeestuarinehabitat.

Whenconsideringestuarinehabitatusebyfishassemblages,alternativeviewsoftheassemblage

areincreasinglybeingexplored,basedontheirfunctionalratherthantaxonomicaspects(Elliott

andDewailly,1995;Mathiesonetal.,2000;Francoetal.,2008).Theallocationofalltaxa toa



numberoffunctionalguildsallowsadescriptionoffishassemblagesintermsofverticalzonation,

habitat preferences, including the substratum preference of benthic/demersal species, and

dietary preferences (Mathieson et al., 2000). Elliot and Dewailly (1995) first introduced the

conceptofclassifyingfishspeciesinfunctionalguilds,asaresultofacomparisonofthestructure

and composition of European estuarine fish assemblages. As a result, the previous authors

defined the typicalEuropeanAtlantic seaboardestuarine fish assemblage, showing that there

were common patterns in estuarine usage by fihses, in spite of the differences in specific

composition.Morerecently,inordertostandardizetheirconceptsandapplications,Elliottetal.

(2007)reviewedtheguildapproachincategorizingestuarinefishspecies,sinceseveralfunctional

guildshadbeeneithercreatedoradapted toothergeographicalareas, leading tooverlapand

confusionbetweenconcepts.Moreover,anunderstandingoftheecosystemprocesses (i.e.the

functioning)of these transitionalenvironments isnecessary toenabletheirprotectionand the

sustainablemanagementrequiredbylegislation,suchastheEUHabitats(92/43/EEC)andWater

Framework Directive (2000/60/EC) (Franco et al., 2008). Concurrently, the functional guild

approach has been extensively usedworldwide (e.g.Mathieson et al., 2000;Malavasi et al.,

2004;Costa et al., 2007; Jovanovic et al., 2007;Martinho et al., 2007; Selleslagh andAmara,

2008; James et al., 2008), providing a good opportunity for comparing the functioning of

transitionalwatersforfishalongdifferentgeographicalareas.

Amongestuarine fishassemblages, theresidentspeciesareoneofthemostabundantgroups,

mainlythecommonandsandgobies,asdescribedelsewhere(e.g.Laffailleetal.,2000;Dolbeth

etal.,2007a; Jovanovichetal.,2007;Martinhoetal.,2007;Françaetal.,2008;Selleslaghand

Amara,2008).Thesespeciesareofutmostimportanceinestuarinetrophicwebsasintermediate

predators,beingconsumersofplankton,meio‐andmacrobenthos(DoornbosandTwisk,1987;

Salgado et al., 2004; Leitão et al., 2006), but also consumed bymacrobenthos (Baeta et al.,

2006), several larger fishes (Arruda et al., 1993;Martinho et al., 2008) and birds (Doornbos,

1984).Theplasticityandadaptabilityof thesespecies towardsenvironmentalchangesendows

them with the capacity to successfully occupy different biotopes, from brackish waters to



euhalineareas(BouchereauandGuelorget,1998;Leitãoetal.,2006).

Estuariesalsoplayanimportantroleasnurseryareaformarinefish(Becketal.,2001;Cabralet

al.,2007;Martinhoetal.,2007a).Thenurseryconceptwasfirstly introducedforfishthathave

complex life cycles, inwhich larvae are transported to estuaries,where theymetamorphose,

grow to subadult stages, and thenmove to adult habitats offshore (Beck et al., 2001). This

ontogenicniche separationgeneratesagreatecologicaldistinctionbetween life‐stages,which

prevents population size at one stage from being regulated in accordancewith the carrying

capacity of the next ontogenic habitat (Costa et al., 2002). Among these species that use

estuaries as nursery habitats (marine‐estuarine dependent species), competition seems to be

diminishedbyabundant foodresources (e.g.Dolbethetal.,2007b)orbyresourcepartitioning

producedbythelikelycompetitors(Amaraetal.,2001;Costaetal.,2002),namelytemporaland

spatial segregationwithin nursery areas (Martinho et al., 2007b). In this context, numerous

factors have been catalogued as determinant for the distribution of these species within

estuarinewaters,mostofthemrelatedtosubstratetype,hydrologicalfeaturesandthepresence

ofrootedvegetation,creatingacomplexmosaicofspecifichabitats(CabralandCosta,1999;Pihl

etal.,2002;Françaetal.,2009).Toagreatextent,thesespeciesareofhighcommercialvalue,

requiring efficientprotectionmeasures,preferablybasedon thebest available knowledgeon

habitatdescriptors,physiologicaltolerancesandecologicalrequirements.

Recruitmentvariabilityofmarinespecies

Marinespeciesthatuseestuariesasnurseryareasareoneoftheabundantecologicalgroupsin

estuarine fishassemblages (e.g.ElliottandDewailly,1995;Malavasietal.,2004;Cabraletal.,

2007; Martinho et al., 2007a,b). Particularly, the European sea bass (Dicentrarchus labrax),

flounder(Platichthysflesus)andthecommonsole(Soleasolea)areamongthemostabundantin

Portuguese estuaries (Cabral et al., 2007; Martinho et al., 2007a,b; Ribeiro et al., 2008).

Accordingly,thesespecieshavehighcommercialvaluemainlyinadultstages,sounderstanding

thedynamicsof recruitmentvariability isa crucial step foranaccurate fisheriesmanagement



strategy.Inthesespecies,spawningtakesplaceoffshore, implyingthemigrationof larvaefrom

the continental shelf towards coastal areas and estuaries (e.g. Norcross and Shaw, 1984;

Koutsikopoulos and Lacroix, 1992). Larval dispersion has several advantages, such as the

possibilityofcolonizationofnewsettlementhabitats,geneflowandtheminimizationof intra‐

specific competition.Nevertheless, these advantages canbediminishedby thehighmortality

andpredationratesthatyounglarvaearesubjectedto,andalsoduetothedifficultiesinfinding

theaccesstosuitableestuarinehabitats(Baileyetal.,2005).Moreover,slightvariationsindaily

mortalityratesoperatingovertheeggand larvalstagesarecapableofgeneratingvariations in

recruitmentordersofmagnitudegreaterthanthoseactuallyobserved(Heath,1992).Forthese

species, connectivity between estuarine and coastal areas is of great importance (Dame and

Allen,1996;Ray,2005),beingnotonlyinfluencedbynaturalconditions(e.g.riverflow),butalso

bytheanthropogenicfactorsthatareconspicuousinmostEuropeanestuaries(Ableetal.,1999;

LePapeetal.,2007,Vasconcelosetal.,2007).

Recruitment variability has been attributed as one of the main causes of fluctuating stock

numbers, either a consequence of density‐dependent factors acting mainly inside estuarine

waters,suchaspredation,mortality,competitionforfoodandshelter(vanderVeeretal.,2000),

ordensity‐independent factors acting essentiallyduring the estuarine colonizationphase (van

derVeeretal.,2000),suchashydrologicalfeatures,coastalwindspeedanddirection,currents,

salinity,turbidity,watertemperatureprecipitationandlargeocean‐atmospherepatternssuchas

theNorthAtlanticOscillation(NAO)(e.g.Marchand,1991;Amaraetal.,2000;vanderVeeretal.,

2000; Attrill and Power, 2002; Bailey et al., 2005; Vinagre et al., 2007;Wilson et al., 2008;

Martinhoetal.,2009).

For the Portuguese coast, spawning data is unavailable formostmarine fish species, being

impossible to relate abundance patterns and recruitment variability with spawning stock

biomass.However,someattemptshavebeenmadetorelatevariationsinhydrodynamicsandin

theNAOwiththerecruitmentlevelsofmarine‐estuarinedependentspecies(Vinagreetal2007;

Martinhoetal.,2009),marine‐estuarineopportunists (Santosetal.,2001,2004)andwith the



structure and composition of coastal marine fish assemblages (Henriques et al., 2007).

Hydrodynamics,mainly relatedwith river runoff patterns and the extent of river plumes to

coastal areas,hasbeen identified as critical for recruitment, acting asproximity indicatorsof

nursery areas for fish larvae (e.g.Marchand,1991;Amara et al.,2000;Metcalfe et al.,2006;

Vinagreetal.,2007;Martinhoetal.,2009).Sincemostofthesespeciesuse,atsomepartoftheir

larval cycle, selective tidal stream transport (STST) from the continental shelf to estuarine

nurseries (van der Veer et al., 1991; Jennings and Pawson, 1992; Amara et al., 2000), other

aspects such as tidal currents, local topography and upwelling events also contribute,mainly

locally,forvariationsinwatercirculation,retentionandtransportpatterns,whichmayinfluence

the amount of potential settlers and ultimately recruitment levels (Rijnsdorp et al., 1985;

Lancasteretal.,1998;Metcalfeetal.,2006).Moreover,andgiventhatriverrunoff ispresently

influenced bywater retention in dams and to extremeweather events such as droughts or

floods, it is expected that high recruitment variability in these specieswill occur in a nearby

future.

On theotherhand, ithasbeen stressed the important effectof temperatureon recruitment

variability.Asanexample,Simsetal.(2004)notedthatthereproductivemigrationphenologyof

amarine‐estuarinedependentspecies(P.flesus)appearstobedriventoalargeextenttoshort‐

termclimate‐inducedchanges inthermalresourcesoftheiroverwinteringhabitat.Moreover, it

hasbeensuggested itseggsarehighlysensitivetowatertemperatureshigherthan12°C inthe

winter,inducinghighmortalitylevels(VonWesternhagen,1970).Thereductioninabundanceof

thisspeciesinthesouthernAtlanticcoastofPortugalhasbeenrelatedwiththisfact,possiblyas

aconsequenceofclimatechange‐induced increase inseatemperature(Cabraletal.,2007).For

other marine‐estuarine dependent species, temperature has been also reported as a

determiningfactorinrecruitment,suchasD.labraxandS.solea(e.g.vanderVeeretal.,2001;

LePapeetal.,2003a;Picketetal.,2004).Ultimately,AttrillandPower (2004) stated that the

thermal resources within estuarine nursery areas have a temporal (rather than spatial)



dimension,whichmayberesponsibleforfishmigrationpatterns,andtoalargeextent,fishuse

estuarinehabitatstoexploitoptimalthermalhabitatsratherthanfoodsupply.

Large‐scale oceanographic patterns have also been considered to influence recruitment

variability inmarine fishes. In fact, the NAO has been correlatedwith a range of long‐term

ecologicalmeasures,includingcertainfishstocks.Suchenvironmentalinfluencesaremostlikely

toaffectsusceptiblejuvenilesduringestuarineresidency,asestuariesarecriticaljuvenilenursery

or over‐wintering habitats (Attrill and Power, 2002). In general, a positive phase of theNAO

inducesdryweatherinsouthernEuropeanandwetweatherinnorthernEurope,whileanegative

phase inducesanoppositepattern.OnthePortuguesecoast,theNAOhasbeendeterminedto

influencenotonly the sea surface temperature (SST),but also thewind and currentpatterns

(Henriquesetal.,2007),whichcanhaveasynergisticeffectonthefactorsthatinteractdirectly

withrecruitmentvariability.

Recently,a firstattempt todetermine thenurseryoforiginofseveralmarine fishspecieswas

performedbyVasconcelosetal.(2008),assessingthecontributionofeachestuarytothecoastal

stocksbymeansofotolithelementalfingerprints.Asnotedelsewhere,thistechniquehasproven

to be suitable for discriminating nursery origins and connectivity between juvenile and adult

habitats,beingcrucialforthemanagementandconservationofestuarineandcoastalstocks.

Climateforcingandsystems’changes

Sincetheindustrialrevolution,animportantmilestoneforthedevelopmentofHumankind,CO2

and other greenhouse gases (GHG) have been increasing in the atmosphere,mainly due to

humanactivities.Particularly,GHGemissionsincreasedinabout80%between1970and2004,as

a primary outcome of the use fossil fuels, with land‐use change providing also a small

contribution(IPCC,2007).Asaresult,globalwarming,andconsequentlyclimatechangeandits

main expressions, pose an important challenge for both scientists and stakeholders for the

managementof terrestrialandmarineecosystems,mainly inwhatconcerns thedevelopingof

adaptationandmitigationstrategies.Accordingly,oneofthemajorchallengesinthe21stcentury



willbe theaccessof theglobalpopulation to freshwater resources (Gleick,2002; IPCC,2007).

Thefrequencyandmagnitudeofextremeweathereventsareexpectedtoincreaseinthefuture

due to climate change (Mirza, 2003), inducing changes in the Earth’s global oceanic and

atmospheric circulation patterns. Moreover, ocean acidification, sea level rise, reduction in

thickness and extent of glaciers, ice sheets and sea ice, and increase in ocean and air

temperature are all severe consequences of global warming (IPCC, 2007), with strong

implicationsforcoastalecosystems. Inestuarineareas,themain impactsofclimatechangeare

thoughttobeassociatedwithriverflow,eitherbyfloodordroughtevents.Intheparticularcase

ofdroughts,severalauthorshavepointedout theeffectsofreductions inriver flowatseveral

latitudes,mainlyforfishandinvertebrates(e.g.AttrillandPower,2000a;LePapeetal.,2003b;

HarrisonandWhitfield,2006;Costaetal.,2007;Marquesetal.,2007;Martinhoetal.,2007a)

and for thewaterquality ingeneral (Attrillandpower,2000b;Elsdonetal.,2009).Moreover,

Erzini et al. (2005) andMeynecke et al. (2006) also reported on the reduction in landings of

commercialspeciesasaconsequenceofareducedextentofriverplumestocoastalareas.

For the Iberian Peninsula, a reduction in precipitation amounts (concentrated in the winter

months)andconsequentdroughts,combinedwiththeexpectedincreaseinairtemperatureare

amongthemainprojectedregionalimpactsofglobalwarming(Mirandaetal.,2006;IPCC,2007).

In fact, six of the last ten years have been classified by the PortugueseWeather Institute

(http://www.meteo.pt) among the driest and/orwarmest since 1931.When looking at both

precipitationandriverrunoffvaluesforthelasttwentyyearsfortheMondegoRiverbasinarea,

itisnotabletherapidshiftbetweenfloodsanddroughtsinconsecutiveyears(Fig.2).Inaddition,

in 2005 a severe droughtwas recorded,with significant reductions in precipitation and river

runoff,when compared to the long‐term average values.As a consequence, a change in the

structure and composition of estuarine planktonic and fish communitieswas observed, as a

responsetotheupwarddisplacementofbrackishhabitats(Marquesetal.,2007;Martinhoetal.,

2007a), aswell as a reduction in abundance and production of the estuarine residents and

marine‐estuarinedependentspecies(Martinhoetal.,2007a,2009;Dolbethetal.,2008).



Figure2.Long‐termvariationofprecipitationandriverrunoffintheMondegoRiverbasin.

Thus,sincestochasticphenomenaliketheonespreviouslyreportedareexpectedtoincreasein

frequency over the next years, it is essential to understand their influence on estuarine

ecosystems,since thegoodsandservicesprovidedby themmightbedangerously threatened.

Moreover, changes in abundance of key species in the estuarine system, such as fish or

decapods,willhaveserious implicationsforthestructureanddynamicsofestuarinefoodwebs

(AttrillandPower,2000a),andultimatelyforthefunctioningofwholeecosystem.

Assessingecologicalstatusoftransitionalwaters

TheWater FrameworkDirective (WFD; 2000/60/EC) is amilestone document concerning the

protection and enhancement of European rivers, lakes, groundwater, transitional and coastal

waters.Themainobjectivesofthisdirectiveare:(a)topreventfurtherdeterioration,toprotect

and to enhance the status ofwater resources; (b) to promote sustainablewater use; (c) to

enhanceprotectionandimprovementoftheaquaticenvironment,throughspecificmeasuresfor

theprogressivereductionofdischarges; (d)toensuretheprogressivereductionofpollutionof



groundwaterandpreventitsfurtherpollution;and(e)tocontributetomitigatingtheeffectsof

floodsanddroughts.Ultimately,EUmemberstatesarerequiredbytheWFDtoachieveaGood

EcologicalStatusinallwaterbodiesby2015.Recently,theMarineStrategyFrameworkDirective

(MSFD; 2008/56/EC)was adopted by the EU, in order to extend this level of protection for

coastalwaters, providing an opportunity for a comprehensive policy for a sustainable use of

Europe’senvironmentallydegradedseas(Meeetal.,2008).

The concept of ecological status developed in theWFD is defined in terms of the biological

communityquality,aswellasthesystems’hydrologicalandchemicalcharacteristics(Teixeiraet

al., 2008).Moreover, the application of theWFD requiresmethods capable of distinguishing

betweendifferent levelsof ecologicalquality to classify surfacewatersby comparingpresent

datawith a reference situation (Borja,2005).However,one aspect isofparticular relevance:

since estuarinewaters constitute naturally stressed, highly variable ecosystems that are also

exposed tohigh levelsofanthropogenic stress (Dauvin,2007;ElliottandQuintino,2007), is it

possible to distinguish between natural and anthropogenic‐induced stress? This question has

been identifiedastheEstuarineQualityParadox (e.g.Dauvin,2007;ElliotandQuintino,2007),

and is of particular relevance when using ecological indicators to determine the Ecological

QualityStatusfortransitionalwaters.Infact,sinceestuariesarenaturallyhighvariablehabitats

(i.e. in terms of salinity, temperature, oxygen and sediment dynamics), an over‐reliance on

ecosystemstructural features,suchasdiversity, inquality indicatorsmakes itmoredifficult to

detectanthropogenicstress(ElliotandQuintino,2007).

Inestuaries,thebiologicalelementsconsideredfordeterminingtheEcologicalQualityarealgae,

benthicinvertebratesandfish.Theuseoffishasindicatorsofenvironmentalchangehasrecently

gained attention,mainlydue to the advantages inusing theseorganisms,when compared to

other groups such as thebenthic invertebrates.According toWhitfield andElliott (2002), the

main advantages of using fish as indicators are: (1) they are typically present in all aquatic

systems,with the exception of highly pollutedwaters; (2) there is extensive life‐history and

environmental response information available for most species; (3) in comparison to many



invertebrates, fishesare relativelyeasy to identifyandmost samples canbeprocessed in the

field, with the fishes being returned to the water (non‐destructive sampling); (4) fish

communitiesusually include a rangeof species that represent a variety of trophic levels and

include foodsofbothaquaticand terrestrialorigin; (5) fishesarecomparatively long‐livedand

thereforeprovidea long‐termrecordofenvironmentalstress; (6)theycontainmany lifeforms

andfunctionalguildsandthusarelikelytocoverallcomponentsofaquaticecosystemsaffected

by anthropogenic disturbance; (7) they are both sedentary andmobile and thuswill reflect

stressorswithinoneareaaswellasprovidinggroupstogiveabroaderassessmentofeffects;(8)

acutetoxicityandstresseffectscanbeevaluatedinthelaboratoryusingselectedspecies,some

ofwhichmaybemissingfromthestudysystem;(9)theyhaveahighpublicawarenessvaluesuch

that thegeneralpublicaremore likely torelate to informationabouttheconditionof the fish

community thandataon invertebratesor aquaticplants; (10) societal costsof environmental

degradation, including cost‐benefit analyses, are more readily evaluated because of the

economic, aesthetic and conservation values attached to fishes. Recently, several ecological

indicators have been developed worldwide for fish assemblages, based on multimetric

approaches(e.g.Deeganetal.,1997;Borjaetal.,2004;HarrisonandWhitfield,2004;Breineet

al., 2007; Coates et al., 2007). As required by theWFD, fish‐based indicators for transitional

watersmustevaluatethecompositionandabundanceoffishspeciesand/orfunctionalgroupsin

comparisonwithareferencevalue,determinedeitherbyaphysicalcomparisonwithacontrol

area (which is difficult to locate), hindcasting (which requires good previous data), predictive

modelling (which requires adequate empirical or stochastic models) or expert judgement

(subjective anddifficult toquantify) (Whitfield and Elliott,2002).Moreover, and according to

Muxikaetal.(2007)oneofthemostchallengingaspectsoftheWFD istodeterminereference

conditionsforeachtypology,whichshouldbeadevelopingtopicforfutureresearch.



Studysite–theMondegoestuary

Thepresent studywas carriedout in theMondegoestuary (40º08’N;8º50’W), located in the

western Atlantic coast of Portugal, awarm temperate region,with a continental temperate

climate.Thesourceof theMondegoriver is locatedatSerradaEstrelaandextendsalong227

Km,drainingahydrologicalbasinofapproximately6670Km2,the largestentirelycomprised in

thePortugueseterritory(Lourenço,1986;Marquesetal.,2002)(Fig.3A).Initsterminalpart,the

MondegoRiverformsavastalluvialplain,theLowerMondegoRegion,whichconsistsof15000

haofagriculturalland(Marquesetal.,2002),wherethemainharvestedcropisrice.Overhalfof

amillionpeopleliveinthebasin,mainlyinthemediumandlowerareas.

Nearthecoast,theestuary isdivided intwoarms,northandsouth,separatedbyanalluvium‐

formed island – the Murraceira Island (Fig. 3B). The two arms have different hydrological

features:thenortharmisdeeper,with4‐10mduringhightideandtidalrangeof1‐3m,whilethe

southarmisshallower,with2‐4mdeepathightideandtidalrangeof1‐3mandwaslargelysilted

up in itsupstreamareasuntil2006.Themain freshwater circulation is carriedout trough the

northarm,while inthesoutharmwatercirculation inmainlycausedbytidal influenceandthe

freshwater input from the Pranto River, a small tributary, which is controlled by a sluice,

according to thewater needs of the surrounding rice fields. The estuary occupies an area of

8.6Km2,where75%correspondstointertidalmudflatsinthesoutharm,andlessthan10%inthe

north arm. The downstream areas of the south arm exhibit Scirpusmaritimus and Spartina

maritimamarshesandZosteranoltiibeds(Lillebøetal.,2004).Theestuaryhasbeenclassifiedas

highly productive, particularly the intertidalmacrobenthic assemblages (Dolbeth et al., 2003,

2007b),withhighervaluesintheseagrassZ.nolttiibeds.Regardingspecialprotectionlegislation,

theestuaryhasbeenclassifiedasanImportantBirdArea(IBA;PT039)andasaRAMSARsite(site

no.1617).

In thissystem, theanthropogenicactivitiescoupled to favourablephysicalcharacteristics (high

waterresidencetimeandshallowness)andclimateconditions(lowprecipitation)haveimposed

a high environmental pressure resulting in an eutrophication process (Martins et al., 2001;



Dolbethetal.,2003;Marquesetal.,2003;Cardosoetal.,2004;Pardaletal.,2004;Lestonetal.,

2008).

SPA

IN

POR

TUG

AL

FIGUEIRA DA FOZ

NORTH ARM

SOUTH ARM

PRANTORIVERINTERTIDAL AREAS

SALTMARSHES

1 Km

40” 0

8’ N

8” 50’ WA B

ATLANTICOCEAN

Figure3.Geographical locationoftheMondegoRiverbasin(shadedarea)(A)anddetailedschemeoftheestuary(B),showingthetwoarms,intertidalandsaltmarshareas.

As an outcome, andmainly due to the increase in occurrence of greenmacroalgaeUlva spp

blooms,theZ.noltiibedsofthesoutharmdeclinedfrom15hain1986to0.02hain1997.From

1998onwards,arestorationprogrammewasimplemented,inordertoprotectandenhancethe

Z.noltiibeds,mainlybyphysicallyprotecting theexistingareas,andbydiverting theorganic‐

enrichedfreshwaterdischargesfromthePrantoRiverintothenortharmoftheestuary(Martins

etal.,2005).Fromthatmomenton,theareacoveredbyZ.noltiihasbeen increasing,reaching

4.7hain2006.In2006wasstartedanotherphysicalinterventionintheestuary,byenlargingand

keepingpermanentlyopentheupstreamcommunicationbetweenbotharms,whichallowedto

reducethewaterresidencetimeinthesoutharmthroughahigherwatercirculation.

Among themain anthropogenic pressures, organic pollution, bank reclamation and shipping



activitiesarethemostimportant.Since1984,severalinterventionswereconductedinthelower

Mondegovalley inorderto improve irrigationefficiency forthesurroundingagricultural fields,

whichincludedtheconstructionofchannels,regularizationofmarginstoreducefloodsandthe

constructionofsluicestocontrolthewaterlevelinthericefields(Cardosoetal.,2007).Onthe

otherhand,thecityofFigueiradaFozhasover60.000inhabitants,whosewastewater(partially

untreated)instilldischargedinthenortharmoftheestuary.Inaddition,mostofthetraditional

salt‐farmsintheMurraceiraIslandhavebeenconvertedintosemi‐intensiveaquacultures,whose

wastewater isalsodischarged inbotharms.Additionally, theportofFigueiradaFoz,which in

2006moved1.1milliontonsoftotalcargo,isresponsibleforthemainindustrialpressureinthe

estuarine area. At themoment the Port Authority is expanding the port’s facilities,with an

expectedincreaseinyearlytotalcargoof1.8to2milliontons.Consequently,constantdredging

for maintaining the man navigation areas constitutes one of the major threats for benthic

organisms,suchasfishandinvertebrates.Resourceexploitationfromfishingactivitiestargeting

mainlyseasonalspecies,suchassealampreyPetromizonmarinusandshadAlosaalosa,coupled

withillegalcatchesofEuropeaneelAnguillaanguilla,seabassD.labrax,flounderP.flesus,and

soleS.solea(Jorgeetal.,2002;Leitãoetal.,2007),aswellasthecaptureofcocklesandclams

(Cardosoetal.,2007)increasetheanthropogenicpressurethattheestuaryissubjectedto.

Overthelast15years,appliedresearchhasbeenconductedintheMondegoestuary,providinga

comprehensivedatasetonseveralareas,suchassedimentandnutrientdynamics(e.g.Coelhoet

al., 2004),primary and secondaryproduction (e.g.Cardoso et al., 2002;Dolbeth et al., 2003;

2007b),intertidalandsubtidalbenthicinvertebrates(e.gCardosoetal.,2004;2007;Verdelhoset

al.,2005;Viegasetal.,2007),plankton (e.g.Marquesetal.,2007), fish (Dolbethetal.,2007a;

2008; Leitão et al., 2007;Martinho et al., 2007a,b,; 2008) and bird species (e.g Lopes et al.,

2006). Regarding the fish component, theMondego estuary has been described as an active

nurseryareaformarinefish(Leitãoetal.,2007;Martinhoetal.,2007a,b;2008;Dolbethetal.,

2008),being responsible for importantstocksoff thecentralPortuguesecoast (Vasconceloset

al.,2008).



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35 |GeneralAimandThesisOutline

GeneralAimandThesisOutline

Estuarinefishassemblagesareamongthemost importantfaunalgroups intransitionalwaters,

mainly due to their commercial, social and aesthetic values. However, and despite their

ecologicalaspectsarerelativelywellknown,thereisstillmuchtolearnabouttheirrelationships

with global climate change, as some vital features such as recruitment, productivity and

ecological functions might be threatened. In this thesis, it is presented a conceptual and

integrative approach on using estuarine fish assemblages as indicators on environmental

changes.Theprimaryaimwastoassesstheinfluenceofanextremeweatherevent(drought)in

the functioning of the Mondego estuary fish assemblage at two levels: fish assemblage

(structure,composition,ecologicalqualitystatus)andparticular functionalgroups (abundance,

recruitmentlevels,interannualvariability).Moreprecisely,theinfluenceofthedroughteventon

thefishassemblagewasassessedaccordingtothefollowingquestions:

• Isthestructureandcompositionofestuarinefishassemblagesinfluencedbydroughts?

• Is recruitment variability in marine‐estuarine dependent fish species related with

environmentalforcing?

• Do distinct sampling methods provide different estimates of the structure and

compositionofestuarinefishassemblages?

• Istheassessmentoftheecologicalqualitystatus intransitionalwatersconditionedby

climateinstability?

Thesemainquestionsareaddressed in the fivechapters thatconstitute the focalpointof this

thesis.Intheend,ageneraldiscussionandoverviewoftheresultsispresented,integratingthe

responsetothepreviousquestions,mainconclusionsandfutureresearchareas.



ChapterI

Inthisthesis,thepremisethatestuarinefishassemblagesaregoodindicatorsofenvironmental

changeswas testedand implemented.Hence, the firstchapterdealswith the responseof the

Mondegoestuaryfishassemblagetoaseveredroughtthatoccurredduringthestudyperiod.In

TheinfluenceofanextremedroughteventinthefishcommunityofasouthernEuropetemperate

estuary (Estuar. Coast. Shelf Sci., 2007, 75: 537‐546), a comprehensive approach on the

variations in the structureanddynamicsof the fishassemblage isconductedbymeansof the

estuarineuseguildapproach,basedonthechangesinthefishcommunityasaresponsetothe

upward displacement of brackish habitats, due to a lower freshwater flow into the estuary,

coupledwithahigherseawaterintrusion.Thischapterprovidesthefirstlong‐termapproachon

thestudyoffishassemblagesintheMondegoestuary,beingusedasabasisforfuturework.

ChapterII

Thesecondchapterbringsanewapproach,by focusingonly theestuarine flatfishcommunity.

ThemainobjectivesofDoes the flatfish communityof theMondegoestuary (Portugal) reflect

environmentalchanges?were to study thedistributionandabundancepatternsof the flatfish

speciesinrelationwiththedroughtevent,andultimately,todetermineiftheflatfishcommunity

couldbeusedasaneffectiveearlyindicatorofstatechanges,suchasdroughts.Tocomplement

theinformationonseasonalabundancedataofflatfishspecies,multivariateanalysiswereused

to determine the relationships between species and significant environmental parameters. In

addition, two different steps were taken, by analyzing the response of flatfish species with

different latitudinal distributions to variations in freshwater runoff and temperature regimes,

andalsotodetermine ifearlysummerenvironmentalparameterscouldbeusedasaproxyfor

abundancevaluesofflatfishspecies.



ChapterIII

Recruitment variability is one of themain causes of interannual variations in abundance of

marinefishes. InEnvironmentaleffectsontherecruitmentvariabilityofnurseryspecies(Estuar.

Coast.ShelfSci.,2009,inpress),severalenvironmentalfactorssuchasriverrunoff,precipitation,

seasurfacetemperature,salinity,theNAO indexandwindspeedanddirectionweretested, in

order to determine which were most significant in explaining interannual variability in

recruitmentlevelsinthreemarinefishthatusetheestuaryasanurseryarea:D.labrax,P.flesus

andS.solea.Forachievingthispurpose,agamma‐basedGeneralizedLinearModelwasusedto

relatetheyearlyabundancelevelsof0‐groupfishwiththeenvironmentaldata.Theresultswere

comparedwithrecentprojectionsforclimatechangescenariosfortheIberianPeninsula,mainly

anincreaseinextremeweathereventssuchasdroughts.

ChapterIV

Efficient monitoring and management plans need to be based on cost‐effective sampling

methodologies.Thus,chapterfourfocusesonassessingtheeffectofsamplinggearused inthe

determination of the structure and composition of estuarine fish communities. In Sampling

estuarinefishassemblageswithbeamandottertrawls:differencesinstructure,compositionand

diversity,thegear‐specificfishassemblageswereanalyzedandcomparedbasedonestuarineuse

and feeding guilds.Multivariate analyses were used to detect differences regarding species

compositionandrelativeabundanceofgear‐specificassemblages.

Regarding themostabundantand commercially important species inbothgears,D. labrax,P.

flesusandS.solea,differences inmedian total lengthand length‐frequencydistributionswere

analyzed,aswellasabundancetrendsovertime.Resultsarediscussedregardingthedesignof

more efficient field surveys. Concerning the WFD, distinct results in the structure and

compositionofestuarine fishassemblages (either inspeciesor functionalgroups)obtainedby

different samplinggearscansignificantly influence thedeterminationof theEcologicalQuality

Status.



ChapterV

The WFD requires that fish assemblages should be sampled every three years for the

determination of the Ecological Quality Status (EQS) in transitional waters. However, since

different indicesfordeterminingtheEQScanprovidedistinctresults, it isnecessarytoanalyze

and assess differences and similarities between them, to insure that in the intercalibration

process,EuropeanUnion(EU)memberstatesstandardizetheirapproaches.Inthe lastchapter,

Assessing estuarine environmental quality using fish‐based indices: performance evaluation

under climatic instability (Mar.Poll.Bull.,2008,56:1834‐1843), the variationof five selected

multimetricindicesforthedeterminationoftheEQSoftransitionalwaterswasevaluated,aswell

asthe indices’responsestoanextremedrought.Theselected indicesweretheEBI(Deeganet

al.,1997),EDI (Borjaetal.,2004),EFCI (HarrisonandWhitfield,2004),EBI (Breineetal.,2007)

andTFCI(Coatesetal.,2007).Theconsistencybetweenindiceswasanalyzedbythepercentage

ofmismatch in the total samplingperiod (i.e. thepercentageof the totalnumberof times in

which one index classifies as “Good“ or “High” status,while another classifies as “Medium”,

“Poor”or“Bad”status).Sincethe indicesweredevelopedforotherregionssuchastheUnited

States, United Kingdom, South Africa, Belgium and Spain, their applicability in Portuguese

estuaries was discussed. The results are examined in the scope of the EUWFD, regarding

monitoringstrategies,applicationofindicesandEQSassessment.


39 |ChapterI

ChapterI

Theinfluenceofanextremedroughteventinthefishcommunityofasouthern

Europetemperateestuary

Abstract

Between 2003 and 2006, a severe drought occurred throughout theMondego River catchment’s area,inducinglowerfreshwaterflowsintotheestuary.Asaconsequence,both2004and2005wereconsideredasextremedroughtevents.FromJune2003toJune2006,thefishassemblageoftheMondegoestuarywassampled monthly in five stations during the night, using a 2‐m beam trawl. Fish abundance wasstandardizedasthenumberofindividualsper1000m2perseasonandtheassemblagewasanalysedbasedonecologicalguilds:estuarine residents,marine juveniles,marineadventitious, freshwater,catadromousandmarinespecies thatuse theestuaryasanurseryarea.A totalof42speciesbelonging to23 familieswereidentified,withestuarineresidentsandnurseryspeciesdominatingthefishcommunity.Variationsinthefishcommunitywereassessedusingnon‐metricMDS,beingdefinedthreedistinctperiods:summerandautumn2003,2004/2005andwinterandsummer2006.Themaindrought‐inducedeffectsdetectedwerethedepletionoffreshwaterspeciesandanincreaseinmarineadventitiousin2004/05,duetoanextendedintrusionofseawaterinsidetheestuaryandasignificantreductioninabundanceduringthedriestperiodofestuarine resident species. Nevertheless, from themanagement point of view, it could be stated thatalthoughsomevariationsoccurredduetoenvironmentalstress,themaincoreoftheMondegoestuaryfishcommunityremainedrelativelyunchanged.

Keywords

Fishassemblages::Ecologicalguilds::Climaticchanges::Droughtevents::Temperateestuary::Mondego


41 |ChapterI

Introduction

The increasing rate of global climate change seen in the last century and the predictions to

accelerate into thepresentone,willsignificantly impacttheEarth'soceansandcoastalwaters

(ShortandNeckles,1999;Mirza,2003).Stochasticeventssuchasweatherextremescancause

fluctuations in the conditioning factors but often affect the state directly, for example, by

eliminating parts of populations (Scheffer et al., 2001). Extreme environmental events (e.g.

extremedroughts/floods)canseriouslychangetheamountofwaterflowingwithinriversystems

(Tallaksenet al.,1997). Inestuaries, theseeffectshaveonlybeen addressed in a few studies

concerninginvertebrates(Attrilletal.,1996;AttrillandPower,2000)andfishes(e.g.Garciaetal.,

2001;Ecoutinetal.,2005).Suchenvironmentalinstability,combinedwithanthropogenicderived

pressures such as dredging activities, waste water and general organic pollution, will have

significant impactsonestuarinefishcommunities.Hence,understandingtheeffectsofchanges

in freshwater flowonestuarinesystems iscrucialtocomprehendmoreaboutthedynamicsof

thesekeyecosystems, since riverdischarge intomanyestuaries is substantiallyaltereddue to

human socio‐economic development andmay be in fact sensitive to climate change (Gleick,

2003).

Estuarieshave longbeenregardedas importantsitesforfish(e.g.Haedrich,1983;Mcluskyand

Elliot,2004),andarecharacterizedbyarelativelylowdiversitybuthighabundanceofindividual

taxa,mostofwhichexhibitwidetolerancelimitstothefluctuatingconditionsfoundwithinthese

systems (Whitfield, 1999). In order to simplify information and to allow a better comparison

amongdifferentsystems,ElliottandDewailly(1995)definedthestructureofthetypicalAtlantic

Seaboard estuarine fish community, in termsof ecological guilds: estuarine residents,marine

adventitious visitors, diadromous (catadromous or anadromous) migrant species, marine

seasonal migrants, marine juvenile migrants which use estuaries as nursery grounds and

freshwateradventitiousspecies.Therefore,theknowledgeoftheeffectsandchangescausedby

environmental extreme variations in the above ecological groups should yield insightson the

presentstatusandtoforeseefuturechangesinfishcommunities.


42 |ChapterI

PreviousworksregardingtheMondegoestuaryfishcommunityfocusedmainlyonthestructure

according to the ecological guilds previously referenced and also on the importance of the

estuary as a nursery area for commercialmarine species (for further details see Jorge et al.,

2002;Leitãoetal.,2006;2007;Martinhoetal.,2007).Asageneraltrend,inthelast15yearsit

wasnoticedamajordecline inspeciesnumberfrom1989‐1992to2003/04,mostlyfreshwater

species (Leitão et al., 2007). According to the same authors, this decline could be partially

attributedtoachangeintheestuarineenvironment,assalinityincreasedoverthepastyearsdue

tocontinuousdredgingactivitiestodeepenthemainshippingchannel,withintheestuary.Also,

the decrease in the environmental quality of the estuary due to eutrophication pulses and

consequentmacroalgaeblooms (Cardosoetal.,2004;Dolbethetal.,2007a) couldhavebeen

responsibleforthelossoflessresilientspecies.

InPortugal,severalweatherextremeshavebeen recorded in thepastyears.According to the

PortugueseWeather Institute (http://web.meteo.pt/pt/clima/clima.jsp), in2003was registered

the second hottest summer since 1931,with the longest heatwave since 1941. In 2004, an

extremely dry year, precipitation levelswere far below average. June 2004was the hottest

month since 1931. In the year 2005, which was also an extremely dry year, the lowest

precipitationvaluessince1931wereregistered.JuneandAugust2005werethesecondandthird

hottest months since 1931. This year was considered of severe drought until September

throughoutthePortugueseterritory,andwastheharshestofthepast60years.UntilJune2006,

96%ofthePortugueseterritoryremainedunderweakdroughtconditions(PortugueseWeather

Institute,http://web.meteo.pt/pt/clima/clima.jsp).Thisseriesofconsecutivechangesalloweda

directcomparisonbetweenyearsofdifferenthydrologicalregimes.

Withinthisframeworkofevents,theobjectivesofthisworkwerea)toidentifythechangesthat

occurred in the fishcommunityof theMondegoestuaryalonga threeyearperiod, from June

2003 to June 2006 and b) to assess if drought conditions influenced the distribution and

compositionofthefishcommunity.


43 |ChapterI

MaterialsandMethods

Studysite

TheMondegoRiverestuary(40º08'N,8º50'W)isasmallintertidalsystem,locatedinthewestern

coastofPortugal(Fig.1). Itcomprisestwoarms(northandsouth)thatseparateatabout7km

fromtheshoreandjoinagainnearthemouth.Thenortharmisdeeper,with5to10mdepthat

hightideandtidalrangeof2to3m,whilethesoutharm isshallower,with2to4mdepthat

hightideandtidalrangeof2to3m.Thesoutharm isalmostsiltedup intheupstreamareas,

whichcausesthefreshwatertoflowmainlybythenortharm.Thewatercirculationinthesouth

arm ismainlydependentonthetidesandonasmallfreshwater input,carriedoutthroughthe

Pranto River, a small tributary system,which is regulated by a sluice according to thewater

needs in thesurrounding rice fields. In thesoutharm,about75%of the totalareaconsistsof

intertidalmudflats,whileinthenortharmtheystandforlessthan10%.

The main point sources of pressure and disturbance in theMondego are: a) dredging and

shippinginthenortharmandb)rawsewagedisposalandhighnutrientinputsfromagricultural

and fish farms intheupstreamareasofthesoutharm.Combinedwithahighwaterresidence

time,this ledtoaneutrophicationprocess,resulting inoccasionalspringmacroalgaebloomsof

Enteromorphaspp.overthepasttwodecades(e.g.Pardaletal.,2004;Dolbethetal.,2007).Asa

result theancient largemeadowsofZosteranoltii (Horneman,1832)are restricted toa small

patchinthedownstreamarea(Cardosoetal.,2004).

Samplingproceduresandhydrologicaldata

Thefishcommunitywassampledmonthlyatfivestations(Fig.1),fromJune2003toJune2006

(except in July,September,OctoberandDecember2004,due to technicalconstraints).Fishing

tookplaceduringthenight,athighwaterofspringtides,usinga2mbeamtrawlwithonetickler

chain and 5mmmesh size in the cod end.At each station, three trawlswere towed for an

averageof5minuteseach,coveringatleastanareaof500m2.Allfishcaughtwereidentifiedand


44 |ChapterI

counted.Bottomwaterwasanalyzed for temperature,salinity,dissolvedoxygenandpHwhile

fishingtookplace.

Hydrologicaldatawasobtained from INAG–PortugueseWater Institute (http://snirh.inag.pt).

Bothmonthlyprecipitation (from January2002 to June2006)and long‐termmonthlyaverage

precipitation (from1933 to2006)wereobtained from theSoure13F/01G station.Freshwater

runoffwasacquiredfromINAGstationAçudePonteCoimbra12G/01A,nearthecityofCoimbra

(located40kmupstream).

�

�

�

��E

D

C

B

A ��

��

��

��

��

��

��

��

��

��

��

��

��

��

��

��

��

Figure1.TheMondegoRiverestuary–locationofthe5samplingstations.

Dataanalysis

Thecommunitystructurewasanalyzedbasedonsixecologicalguildsestablished fromhabitat

pattern usage (adapted from Elliott and Dewailly, 1995): marine adventitious species (MA),


45 |ChapterI

marine juvenile migrant species (MJ) (occurring usually in low densities in estuaries as an

alternativehabitat),marinespecies thatuse theestuaryasnurserygrounds (NU) (occurring in

clear seasonalpatterns,higherdensitiesand remaining longerperiods inestuaries),estuarine

resident species (ER), catadromous adventitious species (CA) (no anadromous species were

found)andfreshwateradventitiousspecies(FW).Monthlyfishabundancedatawereexpressed

as thenumberof individualsper1000m2.Fora straightforward synthesisandanalysisof the

obtained results,monthlydatawere averagedby season, as follows: summer – from June to

August;autumn–fromSeptembertoNovember;winter–fromDecembertoFebruary;spring–

from March to May. Whenever one (or more months) was absent, seasonal values were

calculatedwiththeavailabledata.Spatialvariabilitywasnottakenintoaccountduetothesmall

sizeoftheestuary.

Multivariatestatisticswereusedtoinvestigatevariationsinthestructureofthefishcommunity

throughout the study period. A Bray‐Curtis similarity matrix was computed using seasonal

abundances of fishes of each guild (square root transformed), from which the non‐metric

multidimensionalscaling (MDS)ordinationplotwasgeneratedusingPRIMERsoftwarepackage

(version 5.0) (Clarke andWarwick, 2001). To validate the interpretation of theMDS, itwas

performed the ANOSIM test (analysis of similarities), built on a simple nonparametric

permutationprocedure,appliedtothesimilaritymatrixunderlyingtheordinationofthesamples

(treatments) (Clarke andWarwick, 2001). The BIOENV procedure (PRIMER software package,

version 5.0) (Clarke andWarwick, 2001) (all permutations of trial variables, Spearman rank

correlation)was used to find the best combinationof environmental variables explaining the

variationsinthefishcommunity.

Salinity anomalies were calculated as the average monthly salinity subtracted to the

corresponding average throughout the study period. Differences between yearswere tested

using anANOVA. Tukey‐type a posteriori testswere used,whenever the null hypothesiswas

rejected. Spearman rank correlations between fish abundance (per ecological guild) and


46 |ChapterI

environmentalparameterswerecalculated.Asignificancelevelof0.05wasconsideredinalltest

procedures.

Results

Environmentalcharacterization

Considerablevariationsinprecipitationandfreshwaterrunoffwereobservedduringthesurveys.

While in2003/04precipitationvalueswerehigherthanthe1931‐2006average,2004and2005

were considered of extreme drought, with below average precipitation and low freshwater

discharge(Fig.2).Freshwaterflowevidencedaseverereduction,withthe lowestvalue in2005

almosttenfoldlowerthanthehighestin2003.

Salinity was highly variable at all stations, particularly at the most upstream ones (F=34.1,

p<0.05).In2005,salinityvalueswerehigherinallstationsthanintheremainingyears.Thisfact

was particularlymarked in station E (reaching 20 in September 2005). Significant differences

were found between salinity values of 2003/04 and 2004/05 (q=0.006, p<0.05, Tukey‐type a

posteriori test). Negative anomalies occurred mainly in 2003/04, while positive anomalies

occurred mostly in 2005, indicating higher than average salinity values (Fig. 3). For further

detailed informationon salinity variations in the sampling stations seeMarqueset al. (2007).

Temperatureshowedatypicalvariationforthetemperateregions,varyingfrom8.82±1.69ºCto

22.74±2.55ºC(Table1).

Fishassemblage

Throughoutthestudyperiod,atotalof10697individuals,belongingto42speciesand23families

composedtheMondegoestuaryfishassemblage(Table2).Themostabundantspecieswerethe

estuarine residents (ER)PomatoschistusmicropsandPomatoschistusminutus, thespecies that

usetheestuaryasnurserygrounds(NU)Dicentrarchuslabrax,SoleasoleaandPlatichthysflesus,

andthemarine juvenilemigrants(MJ)Diplodusvulgaris.Juvenilestagescomposedmostofthe

estuarinecommunity(unpublishedresults).


47 |ChapterI

0

250000

500000

750000

1000000

1250000

1500000

J FMAMJ J ASONDJ FMAMJ J ASONDJ FMAMJ J ASONDJ FMAMJ J ASONDJ FMAMJ

0

50

100

150

200

250

300

Water runoff Average rainfall (1933 - 2006) Rainfall

Wa

ter

run

off

(da

m3

)

Ra

infa

ll(m

m)

20052004 200620032002

Figure 2.Monthly precipitation and river runoff values from January 2002 to June 2006,plottedagainsttheaverageprecipitationvaluesfor1933‐2006.

-10

-5

0

5

10

15

20

25

30

35

J J A S O N D J F M A M J J A S O N D J F M A M J J A S O N D J F M A M J

2003 2004 2005 2006

Salinity anomalies Salinity Temperature

Figure 3. Average monthly variation of bottom salinity, temperature (ºC) and salinityanomaliesforthestudyperiod,intheMondegoestuary.

48 |ChapterI

Table1.Monthlyvariation(meanvalues±standarddeviation)ofbottomwatersalinity,temperature(ºC),dissolvedoxygen(mg/l)andpH.

Month Salinity Temperature(ºC) O2(mg/l) pH

Month Salinity Temperature(ºC) O2(mg/l) pH

Jun‐03 18.10±11.52 21.24±1.11 5.53±0.72 8.05±0.20 Mar‐05 22.54±12.97 16.26±0.75 9.57±1.37 8.03±0.23

Jul‐03 22.54±13.45 21.22±3.61 8.24±1.76 8.04±0.26 Apr‐05 26.78±8.78 17.94±1.78 9.07±1.43 8.13±0.21

Aug‐03 19.86±12.22 21.64±2.28 8.09±1.71 8.03±0.26 May‐05 30.72±6.28 18.26±2.60 9.08±1.18 8.05±0.18

Sep‐03 20.78±14.14 20.88±1.26 7.51±0.97 7.95±0.16 Jun‐05 29.68±6.39 21.04±2.91 8.73±1.32 7.81±0.16

Oct‐03 21.68±13.34 15.92±0.42 9.29±1.07 7.85±0.27 Jul‐05 24.24±11.67 22.74±2.55 7.62±1.30 7.91±0.13

Nov‐03 21.28±14.06 15.62±0.28 8.93±1.06 7.86±0.44 Aug‐05 27.46±6.29 18.42±2.29 7.99±0.75 8.06±0.09

Dec‐03 19.28±11.88 12.02±0.97 10.76±1.13 8.00±0.28 Sep‐05 30.48±6.63 17.40±1.78 8.63±0.92 7.99±0.12

Jan‐04 18.24±11.23 11.52±1.52 10.46±0.35 7.89±0.27 Oct‐05 25.90±11.35 17.56±0.67 8.84±1.28 7.92±0.10

Feb‐04 20.64±13.01 12.62±1.17 9.77±1.39 8.28±0.11 Nov‐05 20.66±13.73 14.12±0.72 8.24±0.21 ‐

Mar‐04 19.68±12.53 14.46±1.48 10.13±0.45 8.31±0.22 Dec‐05 15.14±10.91 10.86±0.94 ‐ ‐

Apr‐04 22.88±10.82 16.32±1.26 9.98±1.02 8.00±0.19 Jan‐06 20.70±13.14 10.92±1.36 10.06±0.59 7.72±0.07

May‐04 22.92±11.31 20.04±2.71 7.89±1.76 8.10±0.19 Feb‐06 22.78±8.17 11.93±0.88 10.59±0.53 7.78±0.13

Jun‐04 25.25±12.49 18.50±3.05 7.53±1.19 8.04±0.14 Mar‐06 15.28±14.26 16.44±1.28 9.25±0.42 8.37±0.14

Aug‐04 22.60±12.74 20.24±2.73 8.45±1.04 7.99±0.46 Apr‐06 16.64±14.82 18.76±2.27 8.41±1.20 8.08±0.36

Nov‐04 17.44±10.22 10.98±1.06 9.52±0.48 ‐ May‐06 27.20±9.86 20.58±3.37 8.00±1.04 8.02±0.12

Jan‐05 24.28±10.58 8.82±1.69 ‐ ‐ Jun‐06 26.06±6.02 21.04±2.36 8.02±0.85 7.99±0.16

Feb‐05 29.78±7.99 9.92±0.38 11.99±0.79 8.28±0.04


49 |ChapterI

Freshwaterspecies(FW)(Barbusbocagei,CarassiusauratusandGambusiaholbrooki)wereonly

occasionally collected until the winter of 2004. Marine adventitious species (MA) such as

Arnoglossus laterna, Buglossidium luteum, Gaidropsarus mediterraneus, Solea lascaris and

Symphodusbaillonionlyappearedafter the summerof2004. In fact,A. laterna,B. luteum,S.

lascarisandTrisopterusluscuswereonlycapturedinsidetheestuarythroughout2005.

Thenumberofspeciespermonthwasconstantoverthestudyperiod,withanaveragenumber

of15(±3).However,differencesinthetotalnumberofspeciesperyearwereobserved,withthe

highestvalues recorded in2005/06–35species, then2003/04–34,and finally2004/05–29

species.

Regardingthenumberofspeciesperecologicalguild(Fig.4A),therewasan increase inmarine

adventitious species (MA) since the spring of 2005, composing almost 25% of the species

number. On the opposite, there was a decrease in marine juvenile migrant species (MJ).

Estuarineresidents(ER)andnurseryspecies(NU)comprisedabout50%ofthespeciesnumber.

Intermsofdensities(Fig.4B),thenurseryspecies(NU)dominatedtheassemblage in2003/04,

while in2004/05and2005/06 thecommunitywasdominatedby theestuarine residents (ER),

particularly Pomatoschistus species, comprising about 75% of the community in the autumn

2004 and spring and summer 2006. In 2005, the relative abundance ofmarine adventitious

species(MA)alsoincreased.

Themost significant changes in the fish assemblagewere detected in three guilds: estuarine

residents(ER),freshwateradventitious(FW)andmarineadventitious(MA)(Fig.5).Considering

marineadventitiousspecies(MA),therewasanincreaseindensitiesmainlyin2005,duringthe

period of extremely low precipitation and freshwater flow. In 2006, abundance valueswere

similartothosefoundin2003.Anoppositepatternwasfoundforestuarineresidents(ER),with

lowdensitiesinthedriestperiods(2004and2005).Thesespeciesexhibitedsummerabundance

peaks,butinhighermagnitudein2003and2006.

50 |ChapterI

Table 2.Mondego estuary fish community: distribution of species according to Family and EcologicalGuild (CA – catadromous; ER –estuarineresident;MA–marineadventitious;FW–freshwater;MJ–marinejuvenile;NU–nursery)andaveragenumberofindividualsper1000m2forallthestudyperiod.

Species Family EcologicalGuild AverageNind.1000m‐2

Species Family EcologicalGuild AverageNind.1000m‐2

Ammodytestobianus Ammodytidae MA 0.119±0.34 Lizaaurata Mugilidae MJ 0.014±0.04

Anguillaanguilla Anguillidae CA 0.633±0.94 Lizaramada Mugilidae CA 0.250±0.58

Aphiaminuta Gobiidae MA 0.062±0.22 Mugilcephalus Mugilidae MJ 0.005±0.02

Arnoglossuslaterna Scophthalmidae MA 0.016±0.06 Mullussurmuletus Mullidae MJ 0.104±0.17

Atherinaboyeri Atherinidae ER 0.789±1.29 Nerophislumbriciformis Syngnathidae ER 0.008±0.05

Atherinapresbyter Atherinidae ER 0.098±0.21 Parablenniusgattorugine Blenniidae MA 0.003±0.02

Barbusbocagei Cyprinidae FW 0.007±0.04 Platichthysflesus Pleuronectidae NU 1.501±1.64

Buglossidiumluteum Soleidae MA 0.003±0.02 Pomatoschistusmicrops Gobiidae ER 8.155±11.58

Callionymuslyra Callionymidae MA 0.148±0.27 Pomatoschistusminutus Gobiidae ER 3.685±6.04

Carassiusauratus Cyprinidae FW 0.002±0.01 Sardinapilchardus Clupeidae MJ 0.275±1.10

Chelonlabrosus Mugilidae MJ 0.009±0.04 Scophthalmusrhombus Scophthalmidae MJ 0.050±0.07

Ciliatamustela Gadidae MJ 0.129±0.21 Solealascaris Soleidae MA 0.025±0.07

Congerconger Congridae MA 0.018±0.04 Soleasenegalensis Soleidae MJ 0.099±0.15

Dicentrarchuslabrax Moronidae NU 7.507±7.93 Soleasolea Soleidae NU 1.663±1.42

Dicologlossahexophthalma Soleidae MJ 0.002±0.01 Sparusaurata Sparidae MJ 0.020±0.05

Diplodusvulgaris Sparidae MJ 1.422±1.84 Spondyliosomacantharus Sparidae MA 0.018±0.07

Echiichthysvipera Trachinidae MA 0.027±0,07 Symphodusbailloni Labridae MA 0.047±0.11

Engraulisencrasicolus Engraulidae MA 0.052±0.17 Syngnathusabaster Syngnathidae ER 0.165±0.25

Gaidropsarusmediterraneus Gadidae MA 0.002±0.01 Syngnathusacus Syngnathidae ER 0.257±0.52

Gambusiaholbrooki Poeciliidae FW 0.011±0.06 Triglalucerna Triglidae MJ 0.120±0.26

Gobiusniger Gobiidae ER 0.124±0.14 Trisopterusluscus Gadidae MA 0.102±0.24


51 |ChapterI

0%

25%

50%

75%

100%

Sum Aut Wint Spr Sum Aut Wint Spr Sum Aut Wint Spr Sum

MA MJ NU ER CA FW

2003 2004 2005

0%

25%

50%

75%

100%


MA MJ NU ER CA FW

2006

B

A

N.

Ind

N.

Sp

p

Figure4.SeasonalvariationoftherelativecompositionofeachEcologicalGuild,accordingtothenumberofspecies(A)andnumberofindividualsper1000m2(B).CA–Catadromous;ER–Estuarineresidents;MA–Marineadventitious;FW–Freshwater;MJ–Marinejuvenilemigrants;NU–Nursery.Sum–summer;Aut–autumn;Wint–winter;Spr–spring.

Freshwaterspecies(FW)werelastrecordedinestuarinewatersinthewinterof2004andinvery

low densities. Taking into accountmarine juvenilemigrant (MJ) and nursery (NU) species, a

decreaseindensitieswasalsoobservedalongthestudyperiod.

Statisticalanalysisofthefishassemblage

The fish community (based on the ecological guilds) was seasonally separated in the MDS

ordinationplot,particularlytheyearsof2003and2006(Fig.6).Differencesbetweenseasonsand

years were identified, mainly in 2003 and 2006, which were farther separated from the


52 |ChapterI

remaining years. Furthermore, 2006 exhibited high variability among seasons, showing the

greatestscatterwithinthesameyear.Bothsummersof2003and2006werecloselylinkedinthe

ordinationplot.Allseasonsof2004and2005werecloserinthediagram,alongwiththespringof

2006.Anoppositionbetweentheautumnof2003and2004wasobserved.

SignificantdifferencesweredetectedwithANOSIMbetween years at the5% level:2005was

significantlydifferentfrom2006(R=0.426;p=0.029).Althoughnotsignificantly,differenceswere

also found between 2003 and 2004 (R=0.857; p=0.067) and between 2003 and 2005 (R=1;

p=0.067). The BIOENV procedure revealed that dissolved oxygen, pH and precipitationwere

responsibleforexplaining34%ofthevariabilitywithinthefishcommunity.

Spearman rankcorrelationsof theabundanceofeachecologicalguildwith theenvironmental

conditionsshowedapositivecorrelationof thenurseryand residentsguildswith temperature

(rs=0.56;p<0.05and rs=0.64;p<0.05, respectively) (Table3).Negativecorrelationswere found

between the estuarine residents and precipitation (rs=‐0.54; p<0.05) and between marine

adventitiousandwaterrunoff(rs=‐0.81;p<0.05).

Discussion

Fishcommunity

TheMondego estuary fish assemblagewas similar to the typical European Atlantic seaboard

estuarinecommunitydefinedbyElliottandDewailly(1995),Pihletal.(2002)andbyMathieson

etal.(2000)fortidalmarshes,withadominanceofestuarineresidents(ER)andspeciesthatuse

estuariesasnurseryareas (NU).Thepresentresultscorroboratethe findingsofMalavasietal.

(2004),inwhichtheestuarineresidentscompriseabout50%ofthefishcommunityoftheVenice

lagoon. Unlike larger estuaries, marine juvenile migrants (MJ) were less important in both

numberof speciesand totaldensities.Pihletal. (2002) found thatwithinagroupof selected

estuarine systems, great regional variance exists in the composition and abundance of the

ecological guilds making up the estuarine fish assemblages, mainly due to particular


53 |ChapterI

characteristicsofeachestuarinesystem.Thisseemstoagreewithourresults,asthedifferences

foundcanbeattributedtothesmallsizeoftheMondegoestuaryandtoitssmallopening,which

canlimittheentranceofmarinespecies.

0

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2003 2004 2005 20062003 2004 2005 2006 2003 2004 2005 20062003 2004 2005 2006

A

B

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E

FC

Species number Density N. Ind. 1000 m-2

Figure5.Seasonalvariationofthespeciesnumberandnumberofindividualsper1000m2ofeachEcologicalGuild,A–Marineadventitious(MA);B–Marinejuvenilemigrants(MJ);C–Nursery(NU);D‐Estuarineresidents(ER);E–Catadromous(CA);F–Freshwater(FW).Sum–summer;Aut–autumn;Wint–winter;Spr–spring.

The most important families of the Mondego estuary fish assemblage were Gobiidae,

Moronidae, Soleidae, Pleuronectidae, Sparidae and Atherinidae.When comparingwith other

European estuarine systems (e.g. Laffaille et al., 2000;Cabral et al., 2001;Gordo andCabral,

2001;Potteretal.,2001;Costaetal.,2002;Hampeletal.,2003;Malavasietal.,2004),themain

differencethatcanbefoundistheabsenceofMugilidaeasoneofthemostimportantfamilies.


54 |ChapterI

Beamtrawlingisoftenconsideredasuitablemethodforsamplingbenthicspecies,buttendsto

underestimatepelagicspecies(Thieletal.,2003)suchasmugilids.

2003 2004 2005 2006

sum03

aut03

wint04

spr04

sum04

aut04

win05

spr05

sum05

aut05 wint06

spr06

sum06

Stress: 0.08

Figure6.TwodimensionalMDSordinationplotofthefishcommunityaccordingtoseason.Sum–summer;Aut–autumn;Wint–winter;Spr–spring.

The nursery species (NU)D. labrax, P. flesus and S. solea comprised a significantpart of the

assemblage,inconformitywithotherEuropeanestuaries(e.g.ElliottandDewaily,1995;Laffaille

etal.,2000;GordoandCabral,2001;Malavasietal.,2004),reinforcingtheimportanceofsmall

estuariesasnurseryareasand theirrole for themaintenanceofcoastalstocks.Asoutlinedby

Martinhoetal.(2007),seasonalabundancepeaksforthesespecieswererecorded,anddirectly

linked to the seasonal patterns of recruitment andmigration between enclosed and coastal

waters. In termsofnumbers, the fishcommunitywasdominatedbyP.microps.Thisestuarine

resident(ER)wasthemostabundantsincetheautumn2004,andinagreementwithLeitãoetal.


55 |ChapterI

(2006), tends to occupy inner areas of the estuary, thus reducing competition with other

GobiidaespeciessuchasP.minutus,which ismainlyconcentratedatthemouthoftheestuary

(Leitãoetal.,2006;Dolbethetal.,2007b).

OnesignificantaspectofthisworkwasthereappearanceofS.bailloni,amarinespeciesthatlives

in association with seagrass beds. This species had been captured in the previous study

performedbyJorgeetal.(2002)intheearlynineties,butwasabsentuntilthesummerof2004.

The relevance of this finding can be related to the success of the eutrophicationmitigation

measures implemented in theestuary since1998 (for furtherdetails see Lillebøet al.,2005),

whichledtoarecoveryoftheareacoveredbyZ.noltii(15hain1986;0.02hain1997;4.7hain

2006)inthesoutharmoftheestuary,increasingtheavailablehabitatforthisspecies.Currently,

amanagementprogramistakingplace,inordertorestorethecommunicationofthenorthand

southarms, to improve thewatercirculationand to reduce the residence time,aimingat the

restorationoftheseagrassmeadows.

Extremedroughteventsandtheirimpactsinfishassemblages

Having inmind that themeasurement of any ecological response by the fish community, or

individual specieswithin a community,must take cognisance on the key role played by the

physico‐chemical environment in influencing the structure and functioning of that estuary

(WhitfieldandElliott,2002),thisworktriedtoassesstheinfluenceofextremedroughteventsin

thefishcommunity.

Due to theoccurrenceof twoconsecutiveextremedryyears, severalchangesoccurred in the

Mondego river basin. In fact, according to the Portuguese Weather Institute

(http://web.meteo.pt/pt/clima/clima.jsp), in these lastyearsseveredifferences inclimatehave

been recordedwhen compared to the general climate patterns for the period of 1961‐1990.

Withdecreasingprecipitationlevelsandinanextremedroughtsituation,freshwaterwasstored

indamslocatedupstream,whichledtoadecreaseinwaterrunofftotheestuary,from2004to

2005.According toWhitfield (1999),variations in theriver flow inestuaries influencenotonly


56 |ChapterI

the salinity but also the biochemical properties of thewater body. Furthermore, decreasing

freshwater flow results in the incursionofsalinewaters into reachesof theestuarypreviously

dominated by freshwater (Attrill et al., 1996), and in agreement, strong positive salinity

anomalieswere observedmainly in 2005, indicating that higher than average salinity values

occurredthroughouttheestuary.

Table 3. Spearman rank correlations between the average abundance of fishes of eachEcologicalGuildandsomeenvironmentalparameters.Sal–salinity;Temp–temperature;O2–dissolvedoxygen;pH–pH;AvgPrecip–averageprecipitation;AvgRunoff–averageriverrunoff.*aresignificantvaluesforp<0.05.

Guild Sal Temp(ºC) O2(mgl‐1) pH AvgPrecip(mm)

AvgRunoff(dam3)

MA 0.49 0.00 0.26 0.23 0.24 ‐0.81*

MJ 0.24 0.34 0.27 ‐0.01 0.05 0.05

NU 0.24 0.56* 0.06 0.18 0.17 0.05

ER 0.18 0.64* ‐0.36 0.51 ‐0.54* ‐0.16

CA 0.01 0.11 0.29 0.48 0.29 ‐0.06

FW 0.01 0.43 0.17 0.38 0.17 ‐0.05

Typicalmarineadventitiousspecies(MA)likeA.laterna,B.luteum,S.lascarisandT.luscuswere

only captured in the estuary during the period where the highest drought effects were

experienced–2005,benefitingfromahigherextentoftheincursionofseawaterintotheestuary

(due to low freshwater runoff). In fact,noneof these specieshadeverbeendescribed in the

Mondegoestuary,accordingtothebaselinestudyperformedbyJorgeetal.(2002) intheearly

nineties.Thispointsoutanincreaseinsalinityoverthepastdecadeinsidetheestuary,relatedto

theeffectsoflowfreshwaterflowcombinedwithcontinuousdredgingactivitiesinthenortharm

(thelocationofthecommercialharbour)whichincreasesthesalinityincursioninsidetheestuary

(e.g.Marchandetal.,2002;Leitãoetal.,2007).


57 |ChapterI

According to the present data, it was possible to define three distinct periods in terms of

environmentalconditions:a)2004and2005,when theharshestdrought inducedeffectswere

felt;b)2003,whenprecipitationlevelswereconsiderednormalandc)2006,whenprecipitation

levelswereslightly lowerthannormal/regularyears.Theseperiodswere identified intheMDS

plot,showing theseasonsof2004and2005grouped together,andalthoughhighdissimilarity

between2003and2006wasdetected,summervaluesofbothyearslooksimilar.

Thisindicatesthatthechangesinthefishcommunityduetotheeffectsoflowprecipitationand

freshwater flowweremore significant in 2004/05. Accordingly, themain changes in the fish

community were the depletion of freshwater species (FW) and an increase in marine

adventitious species (MA), supported by the strong negative correlation between marine

adventitiousspecies(MA)andfreshwaterrunoff,andadecreaseinabundanceoftheestuarine

residents (ER)during thedriestperiod.The increase inmarine adventitious species (MA)had

alreadybeenreportedin1992byJorgeetal.(2002),asaconsequenceofahydrologicaldryyear.

Theoppositionfoundbetweentheautumn2003andautumn2004seemstobecausedbyashift

intherelativeproportionsofestuarineresidents(ER)andnurseryspecies(NU).Inaddition,the

ordinationofsamplesintheMDSplotsuggeststhatthefishcommunityshowedmoreseasonal

changesinwetyearsthanindryyears,aspreviouslyobservedbyPotteretal.(1986)andCuesta

etal.(2006)inothertemperateestuaries.AsoutlinedintheBIOENVanalysis,precipitationwas

oneofenvironmentalparametersbestexplainingthevariabilityinthefishcommunity.

Referencesoftheimpactsofdroughteventsontemperateestuarinefishcommunitiesarescarce

in literature,withmore available information on planktonic (e.g.Marques et al., 2007) and

invertebratebenthiccommunities(e.g.Attrill,1996;AttrillandPower,2000;Cuestaetal.,2006).

Thepreviousauthorsconcluded that inyearsof low freshwater flow,andmainly in theupper

reachesofestuarineareas,freshwatercommunitiesweregraduallyreplacedbyotherstolerant

to higher salinities due to a higher saline incursion. This seems to corroborate the present

results,evenifcomparingdifferenttrophiclevels.Furthermore,AttrillandPower(2000)pointed

out that fluctuations in key benthic species such as Carcinusmaenas or Crangon crangon in


58 |ChapterI

responsetoclimaticchangescan inducevariations inthewholeestuarinecommunity.Drakeet

al.(2002)suggestedthatshort‐termsalinityfluctuationsduringwarmerperiodsmaynegatively

affectspeciesthatcompletetheir lifecyclewithintheestuary.Likewise,theestuarineresidents

(ER) presented lower densities during the dry period and according to Fonds and Van Buurt

(1974),themortalityofP.micropsandP.minutus’eggs(themostabundantresidentspecies)is

highlydependentonsalinity,conditioningtherecruitment’sstrength(maximumeggsurvivalat

5‐35withmaximumlarvalsizeat5‐15forP.micropsand,15‐35formaximumeggsurvivalwith

maximumlarvalsizeat35forP.minutus).Also,predationpressureonthesespeciescouldhave

increasedduetothehigherabundanceofmarineadventitious(MA)species,particularlyatthe

mouthoftheestuary(forfurtherdiscussiononthistopicseeDolbethetal.,2007b).Accordingto

Garciaetal. (2001),surveys inawarm‐temperatesouth‐westernAtlantic intermittentlyclosed

lagoon (SouthBrazil) led to theconclusion thatduringLaNiñaepisodes (coldanddryevents)

therewasan increase inmarinespecies insidethe lagoon,asaconsequenceof lowfreshwater

inputandahigherintrusionofseawaterintotheupperreaches.Thesamepatternwasobserved

byEcoutinetal.(2005)inacoastallagoonintheIvoryCoast.

However, and despite the changes described above, the majority of the fish assemblage

remained rather unchanged. In the three years of sampling, the tenmost abundant species

alwayscomprisedmorethan90%ofthenumberofindividualsofthefishcommunity,composing

themain coreof the community (Table4) and indicating that themajor changesoccurred in

specieswithlowerfrequencies.SimilarresultswereobtainedbyCostaetal.(2007)fortheTagus

estuary,when comparing various sampling periods from 1978 to 2002. The previous authors

reported that the structure of the fish community remained relatively unchanged during

subsequentdryandwetyears,althoughhigherdensitieswererecorded indryyears.Toassess

whether climatic extremes have long term and more significant impacts on estuarine fish

communitieswill require even longer and geographicallywider data bases, due to the slow

responsetimetodisturbancethatcharacterizesfishspecies(Cabraletal.,2001).


59 |ChapterI

Table4.Speciesabundanceranking(%ofnumberofindividualsper1000m2)fortheperiodsof2003/04,2004/05and2005/06.Onlythe20mostabundantspeciesareshown.

2003/04 2004/05 2005/06

Species % Species % Species %

D.labrax 34.58 P.microps 42.85 P.microps 40.43

P.microps 20.31 D.labrax 15.89 D.labrax 17.79

P.minutus 17.55 P.flesus 8.70 P.minutus 8.79

D.vulgaris 7.00 S.solea 5.92 S.solea 7.05

P.flesus 5.69 P.minutus 5.79 A.boyeri 6.82

S.solea 5.52 D.vulgaris 3.46 P.flesus 2.64

A.anguilla 2.46 A.boyeri 3.38 S.pilchardus 2.39

S.acus 0.89 A.anguilla 3.34 D.vulgaris 2.09

A.boyeri 0.86 A.tobianus 1.47 S.acus 1.20

L.ramada 0.78 L.ramada 1.33 A.anguilla 1.19

S.pilchardus 0.62 C.lyra 1.22 T.luscus 1.11

T.lucerna 0.60 S.abaster 1.13 C.lyra 1.04

C.mustela 0.56 S.acus 0.64 M.surmuletus 0.90

S.abaster 0.44 C.arautus 0.61 L.ramada 0.89

G.niger 0.39 A.presbyter 0.55 A.presbyter 0.86

A.minuta 0.28 E.encrasicolus 0.55 S.senegalensis 0.74

S.rhombus 0.25 G.niger 0.50 S.abaster 0.58

S.senegalensis 0.21 M.surmuletus 0.48 G.niger 0.55

A.tobianus 0.17 S.bailloni 0.45 C.mustela 0.43

E.vipera 0.12 T.luscus 0.41 E.encrasicolus 0.36

In conclusion, and despite interanual variations in recruitment and mortality rates, it was

possible to assess some effects of extreme drought events on a temperate estuarine fish

community.This influenceseems tobe increased in thecaseof theMondegodue to itssmall

area (3.4 km2), with lower thresholds to fast environmental variations. Moreover, and in

conformity with Attrill et al. (1996), the influence of severe drought conditions, which are


60 |ChapterI

predicted to increase over the subsequent years, should be strongly considered when

undertaking management plans for estuaries and river catchment areas. Also, prolonging

ongoingmonitoringprogrammes shouldbeencouraged, inorder tounderstand the long term

effects of climatic changes in key systems such as the estuarine environment. The use of

ecological guilds proved to be a strong tool in assessing changes in the estuarine system by

reducingvariabilityandallowingdirectcomparisonsbetweenestuariesinthefuture.

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65 |ChapterII

ChapterII

Does the flatfish community of the Mondego estuary (Portugal) reflectenvironmentalchanges?

Abstract

The temporalandspatialpatternsofabundanceof the flatfishcommunityof theMondegoestuarywereinvestigatedfrom2003to2007,basedonmonthlybeamtrawlsamples.Duringthestudyperiod,aseveredrought occurred,with consequent reductions in river runoff. A total of eight flatfish species occurredwithin theestuary,withseasonalspecificrichnessandabundancevaryingconsiderably,beingpossible toidentify threemaingroups:onegroup composedof speciespresent throughout the studyperiodand inhigh densities: Platichthys flesus and Solea solea; one group composed of less abundant species butregularly present: Scophthalmus rhombus and Solea senegalensis; and another group, composed ofoccasional species, that occured mainly during the drought period: Arnoglossus laterna, Buglossidiumluteum,DicologlossahexophthalmaandPegusa lascaris.Flatfishdistributionpatternsvariedaccording totheestuarineuseguild:marine‐estuarinedependentfishoccurredmainly intheupperreaches,whilethemarine stragglers andmarine‐estuarine opportunists occurredmostly in the downstream areas. Specieswithmorenorthernlatitudinalaffinitieswerethemostaffectedbythedroughtrelatedwithalesserextentofriverplumestothecoastalarea,resultinginareductioninabundancelevels.Ontheotherhand,flatfishspecieswithmoresouthernaffinities increased inabundanceduringthedrought,benefitingalsofromanincreaseinestuarinewatertemperature.Earlysummersalinityandprecipitationvaluesweregoodproxiesfor estimating abundance levels of P. flesus and S. solea, respectively, emphasizing the importance ofhydrodynamicsfortherecruitmentandabundanceofthesecommerciallyimportantspecies.

Keywords

Flatfish::Drought::Riverrunoff::Mondegoestuary::Soleasolea::Platichthysflesus


67 |ChapterII

Introduction

Flatfishspeciesareoneofthemaincomponentsofestuarinefishassemblages(e.g.Mathiesonet

al., 2000;Cabral et al., 2007; Franco et al., 2008),using estuariesmainly asnursery areasor

temporary habitats as an alternative to coastal areas (Beck et al., 2001). In estuaries, the

distribution and abundance of flatfishes has been related to both biotic (prey abundance,

predation) and abiotic factors, such as temperature, salinity, sediment type and freshwater

runoff(e.g.Rogers,1994;Amaraetal.,2000;Werneretal.,1997;Poweretal.,2000;Simsetal.,

2004). In flatfish species, reproduction strategies usually include batch spawning in offshore

waters, and larvae finding estuarine and coastal waters, where the chances of survival and

maximizing growth are higher. However, given the natural variability in current speed and

direction, thepotential fordriftandmigration tonurseryenvironments, themselvesofvarying

quality,might be expected to result in high recruitment variability (Bailey et al., 2005),with

consequent highmortality in juvenile stages. In agreement, recruitment variability in flatfish

seemstobemainlyregulatedbydensity independent(i.e.environmental)factors,relatedwith

transportandretentionmechanisms,wind,tidalcurrentsandestuarinecirculation(seevander

Veeretal.,2000;Baileyetal.,2005 for reviews),being theavailabilityofhighqualitynursery

areas alsoessential for a successful recruitment (Florinet al.,2009).Differences inontogenic

state(i.e.juvenilesandadults)interactwithseasonalfluctuationsinabioticandbioticfactorsto

produce differential distribution and habitat use at a variety of spatial and temporal scales

(Gibsonetal.,1996).

TheAtlantic coastof Portugalprovides anatural case study for the latitudinaldistributionof

flatfishspecies,since it isthesouthernrange limitfornorthernspecies,andthenorthern limit

for southern species, representing the transition between northeastern Atlantic warm‐

temperateandcold‐temperateregions(Ekman,1953;Briggs,1974).Fromthemorethantwenty‐

five species thatoccur in thePortuguese coast (Albuquerque,1956;Cabral,2002),eighthave

beenobserved in theMondego estuary (Leitão et al.,2007;Martinho et al.,2007a).Mostof

thesespecieshavehighcommercialvalue,providingimportantlocaloffshorefisheries(Poweret


68 |ChapterII

al.,2000;Vasconcelosetal.,2008).Hence,understanding thedynamicsof flatfishabundance

andrecruitmentpatternsinestuariescanofferaninsightonthesuccessofcoastalfisheriesina

nearbyfuture.Recently,Cabraletal.(2007)reportedontherelative importanceofPortuguese

estuarinenurseriesforflatfishspecies,statingthattheiroccurrencewasnotonlydependenton

thelatitudinalgradient,butalsoonspecifichabitatpreferences.Flatfishspeciesareknowntobe

impacted by environmental degradation of anthropogenic origin (such as dredging, bank

reclamation,chemicalandorganicpollution),whichcanaffecttheirdistributionwithinnurseries

by changes in habitat suitability and availability, food abundance or sediment contamination

(Vinagreetal.,2005;Pérez‐Rusafaetal.,2006;Schlacheretal.,2007;Vasconcelosetal.,2007;

Courratetal.,2009).Additionally, it isknownalso thatchannelmorphologyandhabitatniche

requirementsinfluencefishanddemersalassemblages(ElliottandHemingway,2002).

Duetotheirlocation,transitionalwatersareexpectedtobeinfluencedbyclimatechangeandits

mainexpressions,suchasanincreaseinfrequencyofextremeweathereventsandsealevelrise.

According to the PortugueseWeather Institute (http://www.meteo.pt), six of the last twelve

yearshave ranked among thehottestanddriestof thepastonehundred years. In2004and

2005,aseveredroughtwasobserved in thePortuguese territory,withseveral implications for

theestuarinecommunities,suchasadecline insecondaryproductionof the intertidalbenthic

invertebrateandfishcommunities(Dolbethetal.,2007,2008),adisplacementofplanktonicand

fish assemblages to upstream areas (Marques et al., 2007; Martinho et al., 2007a) and a

reduction inabundanceand recruitment levelsof severalmarine‐estuarinedependent species

(Dolbeth et al., 2008;Martinho et al., 2009). For this reason, understanding the effects of

weatherextremes,andthehydrologicalfeaturesassociatedwiththem,onestuarineandcoastal

ecosystemsisanaddedvaluefortheestablishmentofsuitablemanagementplansaswellasfor

theimplementationofclimatechangemitigationmeasures.Theobjectivesofthisworkwereto

studythedistributionandabundancepatternsofflatfishspecies intheMondegoestuary,their

relationwith thedrought event that tookplaceduring the studyperiod, and todetermine if


69 |ChapterII

estuarineflatfishcommunitiescanbeusedaseffectiveearlyindicatorsofclimaticevents,suchas

droughts.

MaterialsandMethods

Studysite

This studywas conducted in theMondego estuary, located in the Atlantic coast of Portugal

(40º08'N,8º50'W).Intheterminalpart,theestuaryisdividedintwoarms–northandsouth(Fig.

1)thatjoinagainnearthemouth.Thetwoarmshavedifferenthydrologicalfeatures:thenorth

armisdeeper,with5to10mdepthathightideandtidalrangeof2to3m,whilethesoutharm

isshallower,with2 to4mdepthathigh tideand tidal rangeof1 to3m. In thenortharm is

located the commercial harbour, being subjected to constant dredging to deepen themain

shippingchannel.Thesoutharmissilteduptosomeextentintheupstreamareas,whichcauses

thefreshwatertoflowmainlybythenortharm. Inthesoutharm,about75%ofthetotalarea

consistsofintertidalmudflats,whileinthenortharmtheyaccountforlessthan10%.Thewater

circulation in the south arm ismainly dependent on tides and on a small freshwater input,

carried out through the Pranto River, a small tributary river which is regulated by a sluice

accordingtothewaterneedsinthesurroundingricefields.

Flatfishsamplinganddataacquisition

Flatfishabundancedatawasobtainedfrommonthlynightsamples,fromJune2003toJuly2007.

Samplingwasconductedatfivestations(M,N1,N2,S1,S2;Fig.1),usinga2mbeamtrawlwith

oneticklerchainand5mmmeshsize inthecodend.Ateachstation,threetowsofabout five

minutesatthespeedofoneknotwerecarriedout,coveringatleastanareaof500m2.Allfish

caughtwere immediatelyfrozen,andtakentothe labforposterior identificationandcounting.

After fishing, temperature, salinity,dissolvedoxygenandpHweremeasured inonesampleof

bottomwater.


70 |ChapterII

Hydrological data were obtained from the Portuguese Water Institute (INAG,

http://snirh.inag.pt): monthly precipitation (from 2003 to 2007) and long‐term average

precipitation(1961‐1990)wereobtainedfromtheSoure13F/01Gstation(neartheestuary),and

freshwaterrunoffwasacquiredfromINAGstationAçudePonteCoimbra12G/01A,nearthecity

ofCoimbra (located40kmupstream).Sea surface temperature (SST) for the1º Latx1º Long

square nearest to theMondego estuarywas obtained from the International Comprehensive

Ocean‐AtmosphereDataSet (ICOADS)onlinedatabase (http://dss.ucar.edu/pub/coads,Slutzet

al.,1985).

100m

500m

ATLA

NTIC

OCEA

N

PORT

UGAL

MONDEGORIVER

37” N

39” N

41” N M

S1

S2

N1N2

NORTH ARM

SOUTH ARM

FIGUEIRA DA FOZ

MONDEGORIVER

PRANTORIVER

9” W

Km0 1

A B

ATLA

NTIC

OCE

AN

SALTMARSHESINTERTIDAL AREAS

2000

m

SLUICE

SPAI

N

COIMBRA

Figure1.Locationof theMondegoestuaryon thePortuguesecoast (A)and thesamplingstationswithintheestuary(B).

Dataanalysis

Monthly flatfish abundancedata (individualsper1000m2)wereobtained from averaging the

totalnumberofindividualsaccordingtothesurveyedarea.Seasonalabundanceestimateswere

determinedbyaveragingmonthlydata,according to the following routine:winter (December,

January, February) and spring (March, April,May), summer (June, July, August) and autumn

(September,October,November).Theenvironmentalvariableswerealsoaveragedbyseason,to


71 |ChapterII

provideaneasierapproachonthefive‐yeardataset.Spearmanrankcorrelationswereusedto

determine if significant relationships existed between the seasonal abundance estimated for

each species and the environmental parameters. In addition, the abundance values in June,

consideredasaproxyforearlysummerabundance levelsandcorrespondingtotheendofthe

estuarinecolonizationperiodforbothspecies,werecomparedwiththeenvironmentalvariables

measured in the same month using linear regression analyses. Prior to the analysis, the

assumptions(normality,homogeneityandindependenceofthevariance)ofthelinearregression

wereverified.

Toevaluatetherelationshipbetweenflatfishspeciesabundanceandenvironmentalvariables,a

redundancyanalysis(RDA)wasperformed.FortheRDAitwasusedtheseasonalabundancedata

foreachspecies.Allenvironmentalvariableswereused inafirstanalysisandtheirsignificance

was testedwith a forward selectionprocedure.Afterwards, a seconddb‐RDAwasperformed

usingonlythesignificantenvironmentalvariables.TheRDAwaschosenafterdetectingthelinear

response of the flatfish abundance datawith theDetrended Correspondence Analysis (DCA).

These analyses were performed with CANOCO software (version 4.5) (Ter Braak, 1995). A

significancelevelof0.05wasconsideredinalltestprocedures.

Results

Environmentalbackground

Duringthestudyperiodaseveredroughtoccurred,withasignificantreduction inprecipitation

and freshwater runoff to the estuary (Fig. 2). The hydrological years of 2003 and 2006were

consideredasregular,while2004,2005and2007wereextremelydryyears,withtheharshest

effectsobservedfromthesummer2004totheendof2005(classifiedastheworstdroughtsince

1931 by the PortugueseWeather Institute). Significant differences were obtained for yearly

runoffvaluesduring thestudyperiod (H=16.923;p<0.001).Regardingprecipitation,during the

droughtperiodnearlyallvalueswerebelowthe1961‐1990 long‐termaverage levels(Fig.2).In

theautumn2006,heavyrainfallwasrecorded(Table1,Fig.2),inducingthelowestsalinityvalues


72 |ChapterII

throughout the study period. This variation in precipitation and runoff regimes influenced

considerablythesalinitypatterns insidetheestuary,withhigheraveragesalinityvalues in2005

(Fig.3A).

In the summers of 2003 and 2005, heat waves were also recorded (Portuguese Weather

Institute),which translated into the highest averagewater temperaturemeasured inside the

estuary, especially in 2005, and also into the highest summer difference between estuarine

watertemperatureandSSTintheadjacentcoastalarea(3.24ºCbothin2003and2005)(Fig.3B).

Moreover,2005was theyearwith thehighest rangebetween the lowestandhighestaverage

water temperature (8.8ºC in Januaryand22.7ºC in July,respectively) (Fig.3B).Anoverviewof

theenvironmentalconditions(seasonalaverage±standarddeviation)ispresentedinTable1.

Figure 2.Monthly variation of precipitation (mm), long‐term precipitation average (mm)(1961‐1990)andriverrunoff(dam3)intheMondegoriverbasin.


73 |ChapterII

Table1.Seasonalvariationofaveragevalues(standarddeviationbetweenbrackets)oftheenvironmentalparametersmeasuredfrom2003to2007.

Year Season Salinity

Temperature(ºC)

O2(mgl‐1)

pH

Runoff(dam3)

Precipitation(mm)

SST(ºC)

Summer 20.17(2.24)

21.37(0.24)

9.15(2.27)

8.26(0.05)

47718.67(455.68)

18.87(11.44)

19.20(1.11)

2003

Autumn 21.25(0.45)

17.47(2.95)

9.57(1.17)

8.11(0.12)

134833.00(159587.73)

124.77(114.84)

18.35(2.05)

Winter 19.39(1.20)

12.05(0.55)

9.77(2.29)

8.07(0.17)

337229.67(126423.41)

50.93(16.36)

14.55(0.40)

Spring 21.83(1.86)

16.94(2.84)

10.72(0.46)

8.25(0.08)

69822.67(47941.03)

40.93(7.54)

14.68(0.60)

Summer 23.93(1.87)

19.37(1.23)

9.52(0.00)

7.62(0.00)

46705.00(4710.65)

19.27(26.10)

20.10(0.85)

2004

Autumn 17.44(0.00)

10.98(0.00)

9.40(0.00) ‐ 78794.00

(59163.03) 6.60(8.96)

16.65(0.00)

Winter 27.03(3.89)

9.37(0.78)

13.22(0.00)

8.16(0.21)

45317.00(33791.99)

30.13(23.14)

14.30(0.42)

Spring 26.68(4.09)

17.49(1.07)

10.89(0.23)

8.25(0.04)

24203.67(7096.59)

53.73(11.23)

15.33(1.53)

Summer 27.13(2.74)

20.73(2.18)

9.33(0.53)

8.00(0.14)

31398.0082842.42)

4.57(2.54)

19.45(0.78)

2005

Autumn 25.68(4.91)

16.36(1.94)

9.73(1.27)

8.11(0.06)

31399.67(21905.51)

65.50(43.22)

17.97(0.91)

Winter 19.54(3.95)

11.24(0.60)

10.21(1.24)

7.74(0.01)

155682.67(91389.55)

68.60(20.26)

15.03(0.87)

Spring 19.71(6.52)

18.59(2.08)

9.21(0.60)

8.16(0.19)

204779.33(168483.29)

47.57(47.00)

15.57(1.91)

Summer 26.50(0.62)

18.32(3.85)

9.36(0.29)

7.99(0.23)

29084.00(3266.24)

14.33(16.49)

20.05(0.49)

2006

Autumn 15.38(11.38)

17.30(3.40)

9.40(0.00)

7.63(0.20)

342115.67(352776.52)

183.13(84.89)

19.47(0.42)

Winter 22.43(0.00)

14.40(0.00)

10.65(0.21)

7.87(0.39)

414494.33(313290.91)

86.07(51.79)

15.18(0.46)

Spring 23.58(3.08)

14.25(0.78)

8.20(0.00)

7.55(0.00)

122979.33(70556.38)

63.97(25.80)

16.00(0.00) 20

07

Summer 27.06(3.89)

14.90(0.00)

8.50(0.00)

7.53(0.00)

75159.50(17084.41)

50.00(0.00)

19.50(0.00)


74 |ChapterII

Figure3.MonthlyvariationofsalinityatstationsM (mostdownstreamstation),N2 (mostupstream station) and estuarine average salinity values (A), and estuarine averagetemperature and sea surface temperature (SST) for the 1º Lat x 1º Long nearest to theMondegoestuary(B).

Flatfishdistributionandabundancepatterns

During the study period eight flatfish species were captured in the Mondego estuary:

Arnoglossus laterna (scaldfish), Buglossidium luteum (solenette), Dicologlossa hexophthalma

(ocellatedwedge sole),Pegusa lascaris (sand sole),Platichthys flesus (flounder),Scophthalmus

rhombus (brill), Solea senegalensis (Senegalese sole) and Solea solea (common sole).P. flesus


75 |ChapterII

andS.soleawerethemostubiquitousandabundantspecies(maximumdensityof3.71±2.74and

4.14±0.00 Ind1000m‐2, respectively), showing seasonal summerabundancepeaks (Fig.4A,B).

From 2005 onwards, the abundance peaks of P. flesuswere of lowermagnitude than in the

previousyears.RegardingS.solea,summerabundancepeakswereofsimilarmagnitudeduring

thestudyperiod,with lowervalues in2004.In2006,theabundancepeakwasdisplacedtothe

autumn(Fig.4B),coincidingwithanincreaseinprecipitationandriverrunoff.S.rhombusandS.

senegalensiswere lessabundant,butwerepresent inmostof thesamplingeventsduring the

study period (maximum densities of 0.15±0.12 and 0.25±0.27 ind. 1000m‐2, respectively).

SeasonalabundancepeakswereobservedforS.rhombusinthesummermonths(Fig.5A),while

forS.senegalensisabundancepeakswereobserved in theautumn (Fig.5B).Abundancepeaks

for these specieswere in the sameorderofmagnitudebetween species and seasons,but S.

rhombuswasabsentinthesummersof2004and2007.Asfortheremainingspecies,abundance

patternsvariedbetweenseasons,butwereallcapturedinsidetheestuaryduringthedryperiod

(Fig.6).A. laternawas captured in theautumn2004,when thehighestdensitieswere found

(0.28±0.00 Ind 1000m‐2), and in the summer and autumn 2005 (Fig. 6A). B. luteum and D.

hexophthalmawereonlycaught inoneoccasion (autumn2005andwinter2006,respectively),

withmaximumdensitiesof0.03±0.03and0.02±0.04ind.1000m‐2(Fig.6B,C).P.lascariswasonly

observed in the estuary during 2005, from spring to autumn, being themaximum densities

recordedinthislastseason(0.15±0.14Ind1000m‐2)(Fig.6D).

TheordinationdiagramobtainedbytheDCA(Fig.7)revealedaclearsalinitygradientfromthe

mouthoftheestuarytotheupstreamareas,withtheflatfishspeciesdistributingaccordingly:the

marine stragglersA. laterna,B. luteum,D.hexophthalma,P. lascarisand themarine‐estuarine

opportunistsS.rhombusandS.senegalensisoccurringinmoresalinedownstreamareas(M,N1

andS1),withhigheroxygen levels,whiletheabundantmarine–estuarinedependentspeciesS.

soleaandP.flesusdistributedessentiallyintheupstreamareas(N2andS2).Particularly,S.solea

wasinfluencedbyhigherrunoffvalues(mostlyinthewintersof2003,2006and2007,Fig.2).


76 |ChapterII

Figure4.Seasonalabundancepatterns(N.Ind1000m‐2)ofP.flesus(A)andS.solea(B)fromJune2003toJuly2007.Barsrepresentthestandarddeviation.Shadedarearepresentsthedroughtperiod.

Significant correlations (Spearman rank correlation)between theaverage seasonalabundance

values and the corresponding environmental parameters were obtained for P. lascaris and


77 |ChapterII

estuarineaveragesalinity (rs=0.494;p<0.05),forP. lascarisandriverrunoff(rs=‐0.584;p<0.05)

andforS.soleaanddissolvedoxygen(rs=‐0.498;p<0.05).

Figure 5. Seasonal abundance patterns (N. Ind 1000m‐2) of S. rhombus (A) and S.senegalensis(B)fromJune2003toJuly2007.Barsrepresentthestandarddeviation.Shadedarearepresentsthedroughtperiod.


78 |ChapterII

Theseresultsare inaccordancewiththeDCAanalysis.Forevaluatingtherelationshipbetween

early summer abundance of the dominant species and the environmental parameters, a

regression analysis was used to model the densities in June for each species. Significant

relationships were obtained for P. flesus and estuarine average salinity (R2=0.896; t=‐5.059;

p<0.05),andforS.soleaandprecipitation(R2=0.765;t=3.125;p<0.05)(Fig.8).

Figure6.Seasonalabundancepatterns(N. Ind1000m‐2)ofA. laterna(A),B. luteum(B),D.hexophthalma (C) and P. lascaris (D) from June 2003 to July 2007. Bars represent thestandarddeviation.Shadedarearepresentsthedroughtperiod.

Discussion

TheflatfishcommunityoftheMondegoestuary

Among the twenty‐five species that have been reported for the Portuguese Atlantic coast


79 |ChapterII

(Albuquerque,1956;Cabral,2002),eightwerecaughtinsidetheMondegoestuary.Amongthese

species,severalestuarinehabitatuseguildswererepresented,beingpossibletodetectdifferent

responses regarding the weather events that took place. Accordingly, the life strategies of

estuarineorganismscreatethestructureoftheestuarineecosystem,reflect itsfunctioningand

canbeusedtodeterminethespatialandtemporalutilizationoftheavailableresourcesofspace

and food (Francoetal.,2008).Over thestudyperiod, flatfishspecific richnessandabundance

varied considerably, being possible to identify three main groups: one group composed of

speciespresentthroughoutthestudyperiodandinhighdensities(P.flesus,S.solea),onegroup

composed of less abundant species but regularly present (S. rhombus, S. senegalensis) and

anothergroup, composedofoccasional species,presentmainlyduring thedroughtperiod (A.

laterna,B.luteum,D.hexophthalma,P.lascaris).Infact,thetwomostabundantflatfishspecies

inthisstudy,P.flesusandS.solea,areamongthemostabundantspeciesoftheestuarinefish

assemblage,aspreviouslyreportedbyMartinhoetal.(2007a).Atawiderscale,Pleuronectidae

andSoleidaeareoneofthemostabundantfamiliesinEuropeanestuarinefishassemblages(e.g.

Laffailleetal.,2000;Mathiesonetal.,2000;Potteretal.,2001;Courratetal.,2009).Accordingly,

thesespeciesuse theestuarymainlyasanurseryarea, inwhich juvenilesstay foraperiodof

about two years, migrating afterwards to the adjacent coastal area (Dolbeth et al., 2008;

Martinhoetal.,2008).Bothspeciespresentedsummerabundancepeaksreflectingmainly the

estuarinecolonizationperiodby0‐groupfish,althoughP.flesusshowedadecreasingtendencyin

abundance,mainlyafterthedroughtperiod.

S. rhombus and S. senegalensis, although common species in the flatfish assemblage, were

presentinmuchlowerdensities,withsummerandautumnabundancepeaks,respectively.Both

speciesbelongtothemarine‐estuarineopportunistsecologicalguild,whooftenenterestuarine

waters, particularly as juveniles, but use to different degrees nearshore marine waters as

alternativehabitats (Elliottetal.,2007).Theseasonaldifferences inabundancepeaksbetween

both species reflected theirdifferent spawningperiods: fromMarch toAugust forS. rhombus

(Nielsen,1986c)andfromMaytoAugustforS.senegalensis(Quéroetal.,1986).


80 |ChapterII

Figure 7. RDA analysis, showing the relationship between flatfish community densitiesthroughout the estuary and significant environmental variables (after forward selection).Symbols,positionof the sampling stationswithin theordination space;blackvector lines,flatfish speciesdensities;greyvector lines, relationshipofenvironmental variables to theordination axis,whose length isproportional to their relative significance. Total variationexplainedbythediagram:25%.

The remaining species, A. laterna, B. luteum andD. hexophthalma,marine stragglers, and P.

lascaris,amarine‐estuarineopportunist species,wereonly captured inside theestuaryduring

thedryperiod,occurringmainlyinthelowerreachesoftheestuary,wherethemarineinfluence

is still high. Generally, these species appear in estuarine waters in small numbers, being

associatedwithcoastalmarinewaters(Elliottetal.,2007).Giventhe latitudinal locationofthe

estuary,theflatfishcommunitywascomposedofspecieswithbothsubtropicalandtemperate

affinities,sincemanyflatfishspecieshavetheirsouthernandnortherndistribution limitsalong


81 |ChapterII

thePortuguesecoast(Cabral,2002)(Table2).Moreover,thisarearepresentstwodistinctcoastal

climaticdivisions,beingthetransitionbetweennortheasternAtlanticwarm‐temperateandcold‐

temperateregions(Ekman,1953;Briggs,1974).

Influenceofenvironmentalchangesinestuarineflatfishcommunities

AccordingtoCabraletal.(2007),theoccurrenceofflatfishspeciesinPortugueseestuariesseems

tobedependentmainlyon the latitudinalgradientandonspecifichabitatpreferences. In the

Mondegoestuary,flatfishspeciesweredistributedindifferentestuarineareas,withthemarine‐

estuarinedependentspeciesP. flesusandS.soleaoccurring in the innermostareas,while the

other species,allmarine stragglersandmarine‐estuarineopportunists,occurredmainly in the

lowerestuarine reaches. In fact,distributionof flatfish in temperateestuarineareashasbeen

relatedwith sedimentpreferences, food availability and salinity tolerances (e.g. Power et al.,

2000;Vinagreetal.,2005;Martinhoetal.,2007b).Regardinglatitudinaldistributions,theflatfish

speciespresent in theestuarybelong todifferentbiogeographic ranges,either showingmore

northern(suchasP.flesusandS.rhombus)orsouthernaffinities(suchasD.hexophthalmaand

P.lascaris).

Concurrently, patterns related with latitudinal distribution and habitat preferences can be

influencedbyclimatechange,eitherbyanorthwarddisplacementofsuitablehabitatsduetothe

increaseinseawatertemperature,orbylocalweathereventsinducedbyglobalchanges,suchas

droughts, floodsandheatwaves. In fact, severalauthorshave reporteda consistenteffectof

environmental changes on the recruitment and abundance of flatfish species in temperate

estuaries,mainlyhydrodynamicsandfreshwaterflow(e.g.LeggetandFrank,1997;vanderVeer

etal.,2000;Vinagreetal.,2007;Wilsonetal.,2008;Martinhoetal.,2009).Inthepresentwork,

severalchanges in the flatfishcommunityweremainly inducedby the reduction in freshwater

flow,essentiallyat two levels:adecrease inabundanceof themarine‐estuarinedependentP.

flesus in the years that succeeded the drought period, and an increase inmarine straggler

82 |ChapterII

Table2. Lifehistory traitsof theeight flatfish speciesobserved in theMondegoestuary from2003 to2007, ranked according to thedistributionrange.Datasources:1Nielsen,1986a;2Nielsen,1986b;3Nielsen,1986c;4Quéroetal.,1986;5FroeseandPauly,2009.

Species Distributionrange Biogeographicalarea Habitat Spawningperiod

P.flesus 72°N‐30°N5

Temperate EasternAtlantic,fromtheWhiteSeatoMediterraneanandBlackSea2

Continentalshelf,brackishwaters(juveniles),softbottoms2 February‐June2

S.rhombus 64°N‐30°N5

Temperate EasternAtlantic,MediterraneanandBlackSea3

Continentalshelf(shallowerareas),sandybottoms3 March‐August3

S.solea 67°N‐17°N5Subtropical

EasternAtlantic,MediterraneanandsouthwardtoSenegal4

Continentalshelf,estuariesandlagoons,mainlybetween0‐200m,sandandmud4

January‐April(Mediterranean),December‐May(BayofBiscay),April‐June(NorthSea)4

B.luteum 64°N‐3°S5

Subtropical EasternAtlanticandMediterranean4 Continentalshelf,mainlybetween10‐40m,sandybottoms4

February(Mediterranean),March‐June(BayofBiscay),July‐August(EnglishChannel,NorthSea)4

A.laterna 62°N‐17°S5

Subtropical

EasternAtlantic,MediterraneanandsouthwardtoCapeBlanc1

Continentalshelfupto200m,mixedmuddybottoms1 April‐August1

P.lascaris 57°N‐32°S5

Subtropical EasternAtlantic,westernMediterraneanandsouthwardtoSouthAfrica4

Continentalshelf,mainlybetween20‐50m,gravel,sandandmuddysand4

May‐September,peakinJune‐July(IberianPeninsula,BayofBiscay,westEnglishChannel)4

S.senegalensis 47°N‐14°N5

Subtropical EasternAtlantic,Mediterranean(rare)andsouthwardtoSenegal4

Continentalshelf,estuariesandlagoons,mainlybetween0‐100m,sandandmud4

May‐August(peakinJune)(IberianPeninsula,BayofBiscay)4

D.hexophthalma 34°N‐17°S5

Subtropical EasternAtlantic,MediterraneanandsouthwardtoAngola4 Demersal,shallowwaters4 Nodataavailable


83 |ChapterII

flatfishes during the driest period, as a consequence of higher salinity intrusion in the lower

reaches(Martinhoetal.,2007a).

ForP. flesus and S. solea, recruitment variability, and consequentlyestuarine abundance,has

been described as mostly depending on density independent factors, such as precipitation,

freshwater runoff, SST, the North Atlantic Oscillation (NAO), tidal and wind circulation (e.g.

Marchand,1991;Amaraetal.,2000;AttrillandPower,2002;Simsetal.,2004;Hendersonand

Seaby,2005;Baileyetal.,2008).Inaddition,forPortugueseestuaries,riverrunoffwasidentified

asoneofthemainsourcesofvariationinducingtheabundanceforP.flesusandS.solea(Vinagre

etal.,2007;Martinhoetal.,2009).Moreover,twodifferentresponseswereobtainedforthese

speciesregardingtheimpactsofthedroughtperiod:P.flesus,whichistheonlyflatfishspeciesin

Europethatcanbe found infreshwater,wasmostlyaffectedbythereduction inriver flow,as

lowerdensitieswere found in theestuaryafter thisperiod (inaccordancewith the significant

negative relationship between P. flesus early summer abundance and salinity). This could be

relatedtoitsearlyspringspawningperiod(whenriverrunoffwasmorereduced),comparingto

theearlywinterspawningperiodofS.solea,whenriverrunoffisatitsmaximumextension.On

theotherhand,forS.soleanosignificant impactonabundance levelswasobservedduringthe

drought period, except for the displacement of the abundance peak in 2006 to the autumn,

whichmatchedanincreaseinprecipitationandriverrunoff.Theroleplayedbyland‐basedrunoff

in increasingcoastalfisheryproductionhasbeenrecognizedforthecommonsole(Salen‐Picard

et al., 2002), and in addition, the significant relationship between early summer S. solea

abundanceandprecipitationreinforcedthisstatement.

Regarding S. senegalensis, studies in the Portuguese coast aremainly restricted to the Tagus

estuary. In this context, Vinagre et al. (2007) noted that the abundance of this species in

estuarine areas was also positively correlated with river runoff, mainly through a higher

extensionofriverplumestocoastalareasthatactasproximityindicatorsofthenurseryareasfor

fishlarvae.AsforP.lascaris,studiesarescarceandmainlyrelatedtofisheriesmanagement(e.g.

Pinheiroetal.,2005;Marquesetal.,2006).Inagreementwiththepresentresults,Cabraletal.


84 |ChapterII

(2000) found that in the Sado estuary (southern Portugal) this species was only present

occasionally.Furthermore,thesignificantcorrelationswithriverrunoffandsalinity(negativeand

positive,respectively)reinforce the ideathat theabundanceof thisspecies in theestuarywas

mainlydrivenbythedrought‐inducedchanges.

Thespecieswithmorenortherntemperateaffinities,P.flesusandS.rhombus,seemedthemost

affected by the drought period, either by the reduction in freshwater runoff, but also by

temperature, which exerts its influence in all environments and directly affects organism

physiology(AttrillandPower,2004).Infact,duringthedroughtperiod,andasaconsequenceof

aheatwave,theestuarinetemperaturewashigherthan intheotheryears.Sincebothspecies

areatthesouthernlimitoftheirdistributionrange(Nielsen,1986b,c;FroeseandPauly,2009),

an increase in estuarine temperature couldbe a limitation for those species. P. flesus,which

occursalmostexclusively inthenorthernestuariesofthePortuguesecoastabove39ºN(Cabral

etal.,2007;Vasconcelosetal.,2007),maybesubjectedtoamoresignificantimpactofextreme

climaticeventssuchastheonesheredescribed,since ithasbeensuggestedthatP.flesuseggs

are highly sensitive to water temperatures higher than 12°C in the winter, inducing high

mortalitylevels(VonWesternhagen,1970).

Likewise,Simsetal.(2004)pointedoutthatthemigrationphenologyofP.flesusinthewestern

EnglishChannelappearstobedriventoalargeextentbyshort‐term,climate‐inducedchangesin

thethermalresourcesoftheiroverwinteringhabitat.Thissuggeststhatclimatefluctuationsmay

have significant effectson the timingof thepeak abundanceof fishpopulations (Sims et al.,

2004).Moreover, and in agreementwithMartinho et al. (2009), since this species spawns in

early spring (Nielsen,1986b), further reductions in river flowand the increase inSST thatare

expectedtotakeplaceintheIberianPeninsula(Mirandaetal.,2006)willsignificantlyinfluence

futurerecruitment levels,aswellastheoccurrenceofthisspecies inthisestuary.Ontheother

hand,theincreaseinestuarinetemperaturecanpotentiallybenefittheflatfishspecieswithmore

southernaffinities(Table2).


85 |ChapterII

Figure8.Significant linear regressions (p<0.05)between theabundanceestimates in Juneforeachyearofthetwomostabundantspecies,Platichthysflesus(A),Soleasolea(B)andthecorrespondentenvironmentalparameters.

For the Bristol Channel (United Kingdom), Henderson and Seaby (2005) identified that an

increaseinabundancelevelsofS.soleawashighlypositivelycorrelatedwithanincreaseinwater

temperature in theearlygrowing season. In addition, this species spawnsmainly in theearly

winter (Quéro et al., 1986; Koutsikopoulos and Lacroix, 1992)when reductions in freshwater

runoffwere not so evident,whichmay have contributed to a constancy of recruitment and

abundance levels (inaccordancewithVinagreetal.,2007;Martinhoetal.,2009).For the less

abundant species A. laterna, B. luteum, D. hexophthalma and P. lascaris, all with southern

affinities, an increase in SST could inducehigher abundance values inside the estuarine area.


86 |ChapterII

AlthoughnosignificantrelationshipsofflatfishabundancewithSSTweredetermined,whichcan

bea limitation inducedby the five‐yeardatabase.AttrillandPower (2002)demonstrated that

long‐term juvenile fish abundance is best explained by temperature differentials between

estuarine and coastal waters. Thus, further investigations in relating the abundance of key

species with water temperature should be conducted,mainly in what concerns recruitment

patternsandthetimingofmigrationsbetweenestuarineandcoastalwaters.

Conclusions

This work was provided a new insight of using flatfish assemblages as indicators of

environmentalchanges.Evidencethatthisparticulargroupisagoodindicatorofenvironmental

status in estuarinewaters relieson the recent inclusion inmulti‐metric indices forevaluating

both the ecological quality status of transitional waters (Uriarte and Borja, 2009) and the

anthropogenicpressuresinthemainPortugueseestuaries(Vasconcelosetal.,2007).Ultimately,

thespeciesrichnessandabundanceoffishesinestuariescomesdowntoamatteroffunction,in

accordancewithElliottetal.(2007)andFrancoetal.(2008):ifflatfishassemblageschange,will

thefunctionoftheecosystemremainorwillitchange?Inthiscase,evidencewaspresentedthat

thefunctionoftheMondegoestuaryasanurseryareaforflatfishspeciescanbereduced,inlight

of the present climate change scenarios,where salinity and temperature seem to be having

synergisticeffects,actingovertheabundanceanddistributionrangesofflatfishspecies.Finally,

the use of early summer environmental parameters, namely salinity for P. flesus and

precipitationforS.solea,demonstratedtobeagoodsurrogateforexpectedabundance levels,

so furtherresearchon this topicshouldbeaddressed, inorder toprovidepromptandreliable

indicatorsofestuarineabundanceofthesecommerciallyimportantflatfishspecies.

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92 |ChapterII





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93 |ChapterIII

ChapterIII

Environmentaleffectsontherecruitmentvariabilityofnurseryspecies

Abstract

The recruitment variability of themarine fish speciesDicentrarchus labrax, Platichthys flesus and SoleasoleawasevaluatedintheMondegoestuary(Portugal)from2003to2007.Therelationshipsbetweenseasurfacetemperature,NAO index,coastalwindspeedanddirection,precipitationandriverrunoffpriortotheestuarinecolonizationandthedensitiesof0‐groupfishwereevaluatedusinggamma‐basedGeneralizedLinearModels.D.labraxandP.flesus0‐groupdecreasedindensitiestowardstheendofthestudyperiod,while S. solea, despite low densities in 2004, increased densities in 2007. For D. labrax, river runoff,precipitationandeast‐westwindweresignificant;forP.flesus,precipitation,riverrunoffandbothnorth‐southandeast‐westwindcomponentsweresignificantparameters,whileforS.soleaonlyriverrunoffwasimportant.Resultswerecomparedwithrecentprojectionsforclimatechangescenarios,toevaluatetheireffectsonfuturerecruitmentlevels.

Keywords

Recruitmentvariability::Flatfish::SeaBass::Riverrunoff::Hydrodynamics::NAO


95 |ChapterIII

Introduction

Estuariesareregardedashighlyimportantsitesforfish,particularlyasnurseryareasformarine

species(Becketal.,2001;McLuskyandElliott,2004).Ingeneral,spawningtakesplaceoffshore,

implyingthemigrationof larvaefromthecontinentalshelftowardscoastalareasandestuaries

(e.g. Norcross and Shaw, 1984; Koutsikopoulos and Lacroix, 1992). Among other factors,

hydrodynamics isakeyfactorfortherecruitmentsuccessofmarinefishes(vanderVeeretal.,

2000;Wilson et al., 2008); given the natural variability in current speeds and direction, the

potential fordrift intonurseryenvironmentsofvaryingqualitymightbeexpected to result in

highrecruitmentvariability(Baileyetal.,2005).

Larvaldispersioninearlystageshasseveraladvantages,suchasthepotentialfordispersionand

colonization of new habitats, gene flow and minimization of intra‐specific competition.

Nonetheless,thereareeminentrisksindispersiontowardsestuarinewaters,oneofwhichisthe

highvariabilityinrecruitmentstrength.Thisproblemisacuteformarinefisheswhoseplanktonic

stageshavehighmortalityrates(commonlymeasuredat5–40%perday)andwhoselarvalstages

maymetamorphoseintoquitedifferentjuvenileforms(Baileyetal.,2008).Amongotherspecies,

manyflatfishhavetheirmajorspawningperiodinwinter‐earlyspring,whenstrongstorm‐related

windspredominate,sotherecouldbeadaptationstowind‐inducedcirculation(Marchand,1991;

Bailey et al., 2005). In the caseofmany estuarine‐dependent specieswhose juvenilenursery

habitatsarespatiallydistinctfromspawninglocations,physicalprocessesaffectingthetransport

during the pelagic stages are of great importance to year‐class strength (Amara et al., 2000;

Baileyetal.,2005).Infact,recruitmentsuccessinmarinespeciesseemstoberegulatedmostly

by density‐independent factors (van der Veer et al., 2000) related with the surrounding

environmentandclimate,butalsobydensity‐dependentmechanismssuchaspredation,feeding

and mortality. The strongest evidence of density‐dependent regulation of recruitment in

temperateflatfishes,bothcoastalandoffshore,isthestronganddirectrelationshipbetweenthe

sizeofthenurseryareaandtheoutputofjuveniles(levelofrecruitment)(Rijnsdorpetal.,1992;

vanderVeeretal.,2000).


96 |ChapterIII

It isgenerallyagreedthatriverplumesmayhaveacrucialroleas indicatorsoftheproximityof

nurseryareasforfishlarvae(e.g.Marchand,1991;Amaraetal.,2000).Thismeansthatinyears

of high river drainage these plumes extend over a greater area, increasing the probability of

beingdetectedbyfishlarvaespawnedinthecoastthatwillthendirecttheirmovementtowards

thenurserygrounds(Vinagreetal.,2007).Inagreement,Martinhoetal.(2007a)reportedhigher

densitiesofestuarineresidentsandmarinespeciesthatuseestuariesasnurserygroundsinyears

withhigher freshwater flow.Changes inprecipitationand river runoff regimes (due toclimate

change)willsignificantly impactoncoastalecosystems,andparticularlyonmarine fishspecies

whoselarvalstagesdependonfindingestuarinewaters.Inaddition,largeoceanicpatternssuch

astheNorthAtlanticOscillation(NAO)havebeencorrelatedwitharangeoflong‐termecological

measures,includingtheabundanceofcertainfish.Suchenvironmentalinfluencesaremostlikely

toaffectsusceptiblejuvenilesduringestuarineresidence(AttrillandPower,2002),thushavinga

potentiallyinfluentialroleindeterminingstockrecruitmentlevels.Accordingly,variationsinthe

NAOindexwerelinkedtodifferentprecipitationscenariosoverthePortugueseterritory(Zhang

etal.,1997),beingapotentialindicatorofchangesinclimatepatternsovertheyears.

Previouswork conducted in theMondego estuary (Portugal, Southern Europe) (Leitão et al.,

2007;Martinhoetal.,2007a,b;Dolbethetal.,2008;Martinhoetal.,2008)reportedthat this

estuaryactsasan importantnurseryground formarinespeciessuchas theEuropeanseabass

Dicentrarchus labrax, flounderPlatichthys flesusandsoleSoleasolea. In fact,theseareamong

themostabundantspeciesofthefishcommunity(Martinhoetal.,2007a).Thus,understanding

the combined effectsofboth large‐scaleoceanic andhydrologicalpatternswith local specific

pressures is crucial to the estimation of recruitment levels and ultimately, to the stock

assessment for coastal fisheries. Accordingly, the objectives of thisworkwere to assess the

influence of the NAO, coastal wind speed and direction, sea surface temperature (SST),

precipitation and river runoff on the recruitment variability of threemarine species that use

estuariesasnurseryareas:D.labrax,P.flesusandS.soleaandtoevaluatetheimpactoffuture

climatechangescenariosontherecruitmentofthesespecies.


97 |ChapterIII

MaterialsandMethods

Studysite

TheMondegoRiverestuaryisasmallintertidalsystem,locatedinthewesternAtlanticcoastof

Portugal(40º08'N,8º50'W)(Fig.1).Itsterminalpartisdividedintwoarms(northandsouth)that

joinagainnearthemouth.Thenortharmisdeeper,with5to10mdepthathightideandtidal

rangeof2to3m,whilethesoutharm isshallower,with2to4mdepthathightideandtidal

rangeof1 to3m.The south arm isquite siltedup in theupstream areas,which causes the

freshwater to flowmainly by the north arm. In the south arm, about 75% of the total area

consistsofintertidalmudflats,whileinthenortharmtheyaccountforlessthan10%.Thewater

circulation inthesoutharm ismainlydependentonthetidesandonasmallfreshwater input,

carriedout through thePrantoRiver, a small tributary system,which is regulatedby a sluice

accordingtothewaterneedsinthesurroundingricefields.

100m

500m

ATLA

NTIC

OCEA

N

PORT

UGAL

MONDEGORIVER

37” N

39” N

41” N M

S1

S2

N1N2

NORTH ARM

SOUTH ARM

FIGUEIRA DA FOZ

MONDEGORIVER

PRANTORIVER

9” W

Km0 1

A B

ATLA

NTIC

OCE

AN

SALTMARSHESINTERTIDAL AREAS

2000

m

SLUICE

SPAI

N

COIMBRA

Figure1.GeographicallocationoftheMondegoestuaryinthePortuguesecoast(A)andofthefivesamplingstationswithintheestuary(B).


98 |ChapterIII

TheAtlanticcoastoftheIberianPeninsulaisdominatedinthesummermonthsbyequator‐ward

windsthatgenerallystart in lateMayorearlyJuneandpersistthroughuntil lateSeptemberor

earlyOctober (Smythetal.,2001).Thesewinds causeanequator‐wardmean surface flow to

formabovethepredominantlypole‐wardslopecurrentandhencetogeneratecoastalupwelling,

inducingEkmantransportofthesurfacewaterawayfromthecoast(Huthnance,1995;Smythet

al.,2001;Masonetal.,2005).Duringthewinter,windschangebetweennortherlyandsoutherly

components,favourableofbothupwellinganddownwellingevents,respectively(e.g.Santoset

al.,2004).LocalfeaturesofthenorthwestcoastofPortugalincludetheWesternIberiaBuoyant

Plume(WIBP),a lowsalinitysurfacewaterfedbythewinter‐intensifiedrunoffofseveralrivers

(Santosetal.,2004),and the IberianPolewardCurrent (IPC),aweakundercurrent thatoften

extendstothesurfaceinthewinter(Pelizetal.,2003).

Samplingstrategiesanddataacquisition

Fishwere collected from June2003 to July2007, in the following regime: from June2003 to

November2006on amonthlybasis, and from January2007 to July2007,every twomonths.

Samplingwascarriedoutatfiveselectedstations(M,N1,N2,S1andS2)(Fig.1B)atnight,usinga

2mbeamtrawl,withoneticklerchainand5mmmesh‐sizeinthecodend.Ateachstation,three

towsofaboutfiveminuteswerecarriedout,coveringatleastanareaof500m2.Allfishcaught

wereimmediatelyfrozen,andinthelabwereidentifiedandcounted.

HydrologicaldatawasobtainedfromtheINAG–InstitutodaÁgua(http://snirh.inag.pt):monthly

precipitation (from 2003 to 2007) was obtained from the Soure 13F/01G station (near the

estuary),andfreshwaterrunoffwasacquiredfromINAGstationAçudePonteCoimbra12G/01A,

nearthecityofCoimbra(located40kmupstream)(SeeFig.1A).NorthAtlanticOscillation(NAO)

Index(givenbythepressuredifferencesbetweenLisbon(Portugal)andReykjavik(Iceland))data

was supplied by NOAA/National Weather Service – Climate Prediction Center

(http://www.cdc.noaa.gov). Sea surface temperature (SST),wind data, both north‐south and

east‐west components, were acquired from the International Comprehensive Ocean‐


99 |ChapterIII

Atmosphere Data Set (ICOADS) online database (http://dss.ucar.edu/pub/coads, Slutz et al.,

1985)concerningthe1ºLatx1ºLongsquarenearesttotheMondegoestuary.

Dataanalysis

Data on abundance of 0‐group juveniles was plotted from the original trawl data matrix

according toDolbeth et al. (2008) andMartinho et al. (2008)whodetermined thatonlyone

cohort isproducedeachyear.Fishdensities (individualsper1000m2)weredeterminedas the

numberof0‐group fish caught in the total sampledarea.Monthlydatawas calculatedas the

averageofalldensitiesfromthefivesamplingstationsforeachspecies.Fromeachyearlycohort,

thedensitiesof the first threemonthswhen estuarine catches startwere chosen, since they

represented the onset of the 0‐group settlement period; at this time, fish are approximately

threemonths old. In general, S. solea’s recruitment to estuarinewaters starts in thewinter,

whereas for P. flesus and D. labrax the recruitment usually starts in early and late spring,

respectively (Dolbethetal.,2008;Martinhoetal.,2008).Theenvironmentalparameterswere

obtainedonthethirdmonthpriortothefirstestuarinecatch,basedontheirexpectedinfluence

onthecolonizationprocess.

Theinter‐annualrelationshipbetweenthedensitiesofthethreespeciesandtheenvironmental

patterns (predictors)were analyzedwith aGeneralized LinearModel (GLM) in R software (R

DevelopmentCoreTeam,2008),wherethenumberoffishisrelatedtoothermeasuredvariables

through distributional assumptions (Stefánsson, 1996). A gamma distribution (only positive

densities)wasusedtomodelthenon‐zerocatches(MyersandPepin,1990;Stefánsson,1996).

The GLMwas builtwith an additivemethodology: predictorswere tested independently for

significance and subsequently, significant predictors were added to determine the residual

deviance,thepercentageexplainedbyeachpredictorandthetotalpercentageofthedeviance

explainedbythemodel.Thefinalmodelwasfittedonlywiththesignificantvariables.Giventhat

theconsideredspecieshavedifferentcharacteristics in termsofspawning, larvaldevelopment


100 |ChapterIII

and recruitment patterns, GLM analyses were performed separately for each species. A

significancelevelof0.05wasconsideredinalltestprocedures.

Results


Throughoutthestudyperiod,bothprecipitationandriverrunoffhadclearseasonalandyearly

variations (Fig.2).During2004and2005anextremedroughtwasrecorded,withprecipitation

andriverrunoffvaluesmuchlowerthanthe1961‐1990average(Fig.2).Theharshesteffectsof

the drought were experienced in 2005. In 2003, 2006 and 2007, precipitation levels were

comparableamongyearsandtothe1961‐1990average(Fig.2),beingconsideredregularyears.

Riverrunofflevelsoverthethirdmonthpriortotheestuarinecolonizationby0‐groupjuveniles

presentedhighvaluesin2003and2004forD.labrax,in2003,2004and2006forP.flesusandin

2003,2006and2007 forS. solea (Table1).Over the sameperiod,precipitation levels ranged

from 35.90mm to 80.90mm forD. labrax, from 45.30mm to 80.90mm for P. flesus and from

0.00mmto257.00mmforS.solea.

0

250000

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er

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(da

m3)

0

50

100

150

200

250

300

Pre

cip

ita

tio

n(m

m)

River runoff Precipitation Avg Precipitation 1961-1990

Figure2.Monthly variationofprecipitation (mm), long‐termaverageprecipitation (1961‐1990)(mm)andriverrunoff(dam3)from2003to2007intheMondegoRiverbasin.


101 |ChapterIII

Seasurfacetemperature (SST)rangedfrom13.74ºCto15.57ºCforD. labrax,withthe lowest

values in2005and2006(Table1).ForP.flesus,SSTvariedfrom14.15ºCto15.57ºC,withthe

lowestvaluesin2003,andforS.soleahigherSSTvalueswererecorded,rangingfrom14.15ºCto

19.59 ºC. As a general trend, SST over the thirdmonth prior to the estuarine colonization

increasedtowardstheendofthestudyperiod.NAO index inthethirdmonthpriorto0‐group

firstappearanceintheestuary(Table1)rangedfrom‐1.83to1.02forD.labrax,beingnegative

in2005and2006,andpositiveintheremainingyears.ForP.flesus,theNAOindexhadnegative

valuesin2004and2005,andpositivevaluesin2003,2006and2007,rangingfrom‐0.30to1.26.

ForS. solea, theNAO indexwaspositive in2003and2006,beingnegative in2004,2005and

2007,varyingfrom‐2.24to1.26.

Table1.Valuesof theenvironmentalvariablesused in thegamma‐basedGLManalysisbyyearandspecies.

Species Year SST RiverRunoff Precipitation NAO WindN‐S WindE‐W (ºC) (dam3) (mm) Index (ms‐1) (ms‐1)

2003 14.15 403410.00 80.90 0.32 ‐1.55 0.00

2004 14.28 125055.00 35.90 1.02 ‐3.50 0.89

2005 13.91 26931.00 66.70 ‐1.83 2.95 0.00

2006 13.74 87139.00 78.40 ‐0.51 ‐1.65 4.65 D.lab

rax

2007 15.57 68402.00 61.30 0.17 ‐6.00 1.22

2003 14.15 403410.00 80.90 0.32 ‐1.55 0.00

2004 14.46 248020.00 61.60 ‐0.29 ‐2.67 0.00

2005 14.68 29532.00 47.30 ‐0.30 ‐3.06 2.50

2006 14.52 120468.00 45.30 1.26 ‐5.36 ‐0.94 P.flesus

2007 15.57 68402.00 61.30 0.17 ‐6.00 1.22

2003 14.15 403410.00 80.90 0.32 ‐1.55 0.00

2004 18.64 53594.00 242.10 ‐1.26 0.00 0.00 2005 18.17 51028.00 0.00 ‐1.10 ‐2.76 0.68 2006 14.52 120468.00 45.30 1.26 ‐5.36 ‐0.94 S.

solea

2007 19.59 284262.00 257.00 ‐2.24 3.51 2.90


102 |ChapterIII

Concerning the upwelling favourable winds (North‐South component; negative values for

northerlywinds) (Table1), forP. flesus therewasaclear increase in intensityalong the study

periodfrom‐1.55ms‐1to‐6.00ms‐1.ForD.labrax,positivewindswereonlyregisteredin2005,

varying from ‐6.00ms‐1to2.95ms‐1,and forS.solea,southerlywindsonlyoccurred in2007,

rangingfrom‐5.36ms‐1to3.51ms‐1.Forallspecies,therewasanincreaseinnorth‐southwind

intensity towards theendof the studyperiod.East‐Westwind component (Table1) (negative

valuesforeasterlywinds)hadingenerallowerandpositivevaluesforallspecies,evidencingan

increase in intensity towards the end of the study period. The only negative values were

recordedin2006forP.flesusandS.solea.

Yearlyvariationsin0‐groupfishdensities

Densities of 0‐group fish where highly variable between 2003 and 2007, with the highest

densitiesforthethreespeciesbeingreported in2003(Fig.3).D. labraxwasthespecieswhose

highestaverageyearlydensitieswererecorded(19.1Ind.1000m‐2in2003)(Fig.3A).From2004

onwards, densities decreased considerably, with aminimum of 1.0 Ind. 1000m‐2 in 2007. A

similartendencywasreportedforP.flesus,withthehighestaverageyearlydensitiesin2003(2.8

Ind.1000m‐2)andthelowestin2006(0.3Ind.1000m‐2)(Fig.3B).S.solea0‐groupfishevidenced

a distinct pattern: average yearly densities in 2003where higher (2.8 Ind. 1000m‐2), but the

lowestvalueswhereachieved in2004 (0.6 Ind.1000m‐2),and from2005 to2007 therewasa

tendencytoincreasealmostto2003levels(Fig.3C).

Peakdensities for the three specieswerecompared to theones found in themost important

Portuguese estuarine systems, according to the available literature,mainly from beam trawl

surveys(Table2).ForD.labrax,peakdensitiesintheMondegoestuarywerehigherthaninother

estuaries,andforP.flesusandS.soleadensitieswerecomparableacrosstherangeofselected

estuarinesystems,withtheexceptionoftheMinhoestuary,wheredensitieswereclearlyhigher.


103 |ChapterIII

0.00

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30.00

2003 2004 2005 2006 2007

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-2

A

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2003 2004 2005 2006 2007

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-2

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0.00

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3.00

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5.00

2003 2004 2005 2006 2007

Ind.1000m

-2

C

Figure3.Meandensities(±standarddeviation)ofD.labrax(A),P.flesus(B)andS.solea(C)byyear,from2003to2007.


104 |ChapterIII

Table2.PeakdensitiesreportedforD.labrax,P.flesusandS.soleaalongthemainestuarinesystemsofthePortuguesecoast.

Species Location MaxDensity Sampling Reference

(Estuary) (Individuals1000m‐2) gear

RiadeAveiro 145.3 Beachseine Pomboetal.(2007)

Mondego 320.0 Beamtrawl Martinhoetal.(2007b)

Tejo 81.8 Beamtrawl CabralandCosta(2001)

D.lab

rax

Guadiana 10.0 Ottertrawl Chícharoetal.(2006)

Minho 236.0 Beamtrawl Cabraletal.(unpublisheddata)

Douro 9.1 Beamtrawl Vinagreetal.(2005)

RiadeAveiro 23.2 Beachseine Pomboetal.(2007) P.flesus


Minho 67.0 Beamtrawl Cabraletal.(unpublisheddata)

Douro 8.0 Beamtrawl Vinagreetal.(2005)

RiadeAveiro 0.6 Beachseine Pomboetal.(2007)


Tejo 25.9 Beamtrawl CabralandCosta(1999)

Sado 24.5 Beamtrawl Cabral(2000)

S.solea

Mira 15.7 Beamtrawl Cabraletal.(unpublisheddata)

Relationbetweenenvironmentalparametersand0‐groupabundance

ThefinalresultsoftheGeneralizedLinearModels(GLM)arereportedinTable3.Theanalysisof

devianceforD.labraxshowedthatriverrunoff,precipitationandtheeast‐westwindcomponent

wheresignificantpredictorsexplainingthe0‐groupdensities(p<0.05).Besidesthemaineffects,

thefirst‐orderinteractionbetweenriverrunoffandprecipitationalsowassignificant.Themodel

explained78.6%ofthedeviance,beingriverrunoffmostlyresponsibleforthis(44.9%)(seeTable

3). The predictors precipitation and east‐west wind component contributed similarly to the

deviance (15.3% and 17.6%, respectively), and the interaction between river runoff and


105 |ChapterIII

precipitationcontributedwith0.7%. Ingeneral,therewasatendencyforhigherdensitiesof0‐

group D. labrax during the period of estuarine settlement in years of high river runoff and

precipitation (Fig.4A,B), inaccordancewiththepreviousanalysis.Onthecontrary,yearswith

higherintensityofwesterlywindswereassociatedwithlowerdensities(Fig.4C).

AnalysisofdevianceforP.flesus indicatedthatriverrunoff,precipitationandbothnorth‐south

and east‐west wind components were significant predictors (Table 3). Themodel explained

74.9%ofthedeviance,withriverrunoffalsobeingresponsibleforthemajorityofthedeviance

(73.7%).The remainingpredictors:precipitation,north‐southandeastwestwind components

accountedfor1.2%ofthedeviance(0.89%,0.003%and0.27%,respectively).Nosignificantfirst‐

order interactionswerefoundbetweenthemaineffects.SimilartoD. labrax,P.flesus0‐group

abundancewashigher inyearswithhigherriverrunoffandprecipitation (Fig.5A,B).Likewise,

lower densities were where associated with higher intensity of westerly winds, and lower

densitieswherealsoassociatedwithhigherintensityofnortherlywinds(Fig.5C,D).RegardingS.

solea,themodelaccountedfor46.1%ofthedeviance(Table3).

From thesetofchosenpredictors,only river runoffwassignificant in theGLManalysis,being

responsibleforthewholedeviance.SimilarlytoP.flesus,nofirst‐orderinteractionsbetweenthe

maineffectswherefound.Inaccordancewiththepreviousspecies,higherdensitiesofS.solea0‐

groupfishwerefoundinyearswithhigherriverrunoff(Fig.6).

Discussion

Recruitmentvariability:roleofenvironmentalstressors

The present work focuses on the influence of environmental aspects on the recruitment

variabilityofmarine fishspecies thatuseestuariesasnurseryareas:D. labrax,P. flesusandS.

solea.Thesespeciesareamong themostabundantmarine fishes inPortugueseestuaries (e.g.

Ribeiroetal.,2006;Cabraletal.,2007;Martinhoetal.,2007a),withtypicalseasonalabundance

peaks reflecting estuarine colonization by the young‐of‐the‐year. Since the present database

concerns only five consecutive years, it was not possible to determine trends regarding


106 |ChapterIII

recruitmentvariabilityandstrength,sincethesespeciesareknowntohavehighlyvariability in

recruitment rates inconsecutiveyears (CabralandCosta,2001).Climateand itsmain features

such as rain, SST, theNAO,wind speed anddirection,aswell as tidalmovements andocean

currents, have been recognized as key issues in the estuarine colonization and settlement

processesofbothmarinefishandinvertebratelarvae(e.g.Marchand,1991;Amaraetal.,2000;

AttrillandPower,2002;AlmeidaandQueiroga,2003;Baileyetal.,2008).

Oneofthemostsignificantaspectsofthisworkwastheidentificationoftheimportanceofriver

runoffinthisprocessforthethreespeciesinstudy.

In fact, thiswas theonlyparameter thatwassignificant forallspecies.Previousstudies in the

Tagus estuary (Portugal) revealed that river drainage is a determining factor in the estuarine

colonizationprocessundertakenbymarinespecies,particularlyforsoles(Vinagreetal.,2007).In

theBayofVilaine(France),Amaraetal.(2000)pointedoutthatthe initiationofsoleestuarine

colonization is regulatedbyacombinationof river flow,winddirectionand intensityand tidal

cycle.

During the study period a severe drought occurred, leading to a significant decrease in

precipitationandriverrunoffvalues.Accordingtothepresentresults,higherrunoffvalueswere

associatedwithhigherdensitiesofD.labrax,P.flesusandS.solea,aswellasprecipitationforD.

labraxandP.flesus.Riverrunoffnotonlyaffectstheextentofriverplumes intocoastalareas,

butcanalsoberesponsibleforsalinitychangeswithinestuarinewaters(oneofthemainfactors

responsible for the structuring of estuarine fish communities (e.g.Marshall and Elliott, 1998;

Drakeetal.,2002;Costaetal.,2007;Leitãoetal.,2007),protractingordiminishingtheavailable

habitatsforfishandsuitablenurseryareas.Effectively,Marquesetal.(2007)andMartinhoetal.

(2007a)describedahigherproportionofmarinespeciesinplanktonandfishcommunitiesduring

lowrunoffperiods,respectively,duetoahigherextentofthesalinityincursioninsideestuarine

waters.


107 |ChapterIII

Table3.Analysisofdeviancetableforthegamma‐basedGLMfittedtothedensitiesdataofthespeciesconsideredinstudy.(Res.Dev.–Residualdeviance;%Expl.–Percentageofthedevianceexplainedbythemodel).

Species Parameters p‐value Res.Dev. Deviance %Expl.

Null 31.772

Maineffects

Runoff 0.0163 17.478 14.294 44.989

Precipitation 0.0003 12.628 19.144 15.265

WindE‐W 0.0109 7.035 24.737 17.604

Interactions

Runoff:Precipitation 0.0034 6.799 24.973 0.742

D.lab

rax

Totalexplained 78.600

Null 11.207

Maineffects

Runoff 0.0006 2.944 8.263 73.729

Precipitation 0.0024 2.845 8.362 0.885

WindN‐S 0.046 2.845 8.362 0.003

WindE‐W 0.0166 2.815 8.392 0.266

P.flesus


Null 24.055

Maineffects

Runoff 0.0093 12.977 11.078 46.053

S.solea



108 |ChapterIII

Theimportanceofriverplumesfortheestuarinecolonizationoffishandinvertebratelarvaehas

been related to theexistenceofchemicalcues thatorient larvae towardsestuarineareasand

settlementhabitats,suchasodor,temperature,salinityandturbidity(e.g.Miller,1988;Gibson,

1997;ArvelundandTakemura,2006;KrimskyandEpifanio,2008)andtopotentialhigherprimary

production(Costaetal.,2007).Also,inaccordancewithVinagreetal.(2007),awiderextentof

riverplumesduringhighfreshwaterflowwillenhancethechanceoflarvaedetectingandmoving

towardsestuarinewaters,whichisinagreementwiththepresentresults.

0.00

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Precipitation (mm)

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)

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.1

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A B

C

Figure4.Densitiesof0‐groupD. labrax(Ind.1000m‐2)(firstthreemonths) inrelationwithriver runoff (dam3) (A), precipitation (mm) (B) and wind E‐W component (m s‐1) (C)concerningthethirdmonthpriortotheperiodofestuarinecolonization.

Regarding fisheries, Salen‐Picard et al. (2002) identified a positive relationship between high

runoff values and S. solea landings after a 5‐year time lag in the Golf of Lions (France,


109 |ChapterIII

Mediterraneancoast).Thesameauthorspointedoutthatfloodingeventswereresponsiblefor

anincreaseinbenthicfoodresourcesforjuvenilefish.SentchevandKorotenko(2004)basedon

three dimension particle‐tracking transport models, evidenced that tides and freshwater

discharge play a critical role in influencing flounder larval transport over the eastern English

Channel,fromspawningareastonurserygrounds.Forthethreestudiedspecies,thespawning

season in temperate latitudes and estuarine colonization processes seem to have evolved to

matchtheseasonwhenriverplumeshavetheirmaximumextent,thusincreasingthechancefor

recruitmentsuccess.

Oneimportantregulatoryaspectintheestuarinecolonizationoflarvaeandyoungstagesseems

to be transportation from the continental shelf to estuarine nurseries, with several authors

stressingthe importanceofwind‐drivenandtidal‐drivencirculation (e.g. JenningsandPawson,

1992; Amara et al., 2000; Sentchev and Korotenko, 2004). In the present study, wind was

determinedasasignificantpredictorforD.labrax(E‐Wcomponent)andforP.flesus(N‐SandE‐

W components). Nevertheless, for both wind components, the weakest intensities were

associatedwiththehighestdensitiesof0‐groupfish,possiblyindicatingthatlowerwindintensity

induceseitherweakerupwellingeventsorturbulence.Thepresentresultsareinaccordancewith

priorresultsobtainedbyAmaraetal.(2000),whopointedoutthatstrongoffshorewindscanbe

unfavourable to theestuarinedispersion.ForD. labrax,Lancasteretal. (1998)concluded that

differences inrecruitment levelscouldbeattributedtovariations incoastalwinddirectionand

strength.

For several species, selective tidal stream transport (STST) has been proposed as the main

process for larvaeenteringestuaries. ForP. flesus,passive transportoccurs in theirearly life,

followed by active STST (van derVeer et al., 1991), inwhich fishesmake use of strong tidal

currentsoveronepartofthetidalcyclefortransportation(ForwardandTankersley,2001).Inthe

BayofBiscay(France),Lagardèreetal.(1999)observedthatS.solealarvaeweremainlylocated

inthelowerpartofthewatercolumnbeforemigrationtoestuaries.Vinagreetal.(2007)pointed

outthatsolesundertakeverticalmovementstoescapethetop layerofwatermassesthatare


110 |ChapterIII

most susceptible towindandoffshoreadvection, important inupwelling systems suchas the

Portuguesecoast.Inopposition,fieldstudiesconductedinSouthWalesindicatedthatD.labrax

larvaetendedtooccurintheupperpartofthewatercolumn,andthearrivalofpost‐larvaeinto

shelteredbaysandestuariesusuallytakesplaceduringspringtides(JenningsandPawson,1992).

ThesedifferencescouldbeattributedtothedifferentverticalguildsofD.labrax,ademersaland

moreactiveswimmingspecies,andP.flesusandS.solea,bothbenthicspecies.

0.00

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6.00

7.00

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Wind E-W (m s-1

)

Ind.1000m

-2

B

DC

Figure5.Densitiesof0‐groupP. flesus (Ind.1000m‐2) (first threemonths) in relationwithriverrunoff(dam3)(A),precipitation(mm)(B),windN‐Scomponent(ms‐1)(C),andwindE‐W component (m s‐1) (D) concerning the third month prior to the period of estuarinecolonization.

Thedominanceofdensity‐independent factorsoperatingata localscaleon theeggand larval

stagesstressestheimportanceofhydrodynamiccirculationasakeyfactorindeterminingyear‐


111 |ChapterIII

classstrength(LeggetandFrank,1997).Also,recruitmentvariabilityhasbeenshowntodepend

onthepelagicstageduration(vanderVeeretal.2000),eitherbeforemetamorphosisorduring

the juvenileperiod(Lagardèreetal.,1999;Amaraetal.,2000).Despitefish larvaehavingbeen

described as active swimmers, Gibson (1997) stressed that during the estuarine colonization

processestheyarestillunderthe influenceofhydrodynamic forcesandsuccessfulrecruitment

duringthisstageismostlydependentuponfavorablehydrographicconditions.Althoughdensity‐

independent factors have been shown to influence recruitment variability in the marine

environment prior to estuarine colonization (e.g. Rijnsdorp et al., 1992), density dependent

factorsmay also have a high preponderancewithin nursery grounds, inducing high levels of

juvenilemortality(Gibson,1994;Rogers,1994).

0.00

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6.00

7.00

0 100000 200000 300000 400000 500000

River runoff (dam3)

Ind

.1

00

0m

-2

Figure6.Densitiesof0‐groupS. solea (Ind.1000m‐2) (first threemonths) in relationwithriverrunoff(dam3)concerningthethirdmonthpriortotheperiodofestuarinecolonization.

For the species in study therewas no relationship between early juvenile densities and sea

surface temperature.However,according toRijnsdorpetal. (1992), recruitment is likely tobe

mostly influenced by water temperature in the marine environment prior to or during the

immigration tonurseryareas. For S. solea, LePapeetal. (2003) foundapositive relationship

betweenSSTandthegrowthofyoungrecruits.Thesameauthorsalsopointedoutthatwarmer


112 |ChapterIII

temperaturesareanimportantfactorfortheattractiontoestuarinenurseries.Inopposition,for

severalflatfishspecies(dabandplaice),anegativerelationshipbetweenyear‐classstrengthand

water temperature has been determined (van der Veer et al., 2000). Regarding D. labrax,

Jennings and Pawson (1992) pointed out that, in UKwaters, post‐larvaemigrate to inshore

waterswhentemperaturesarehigherthanthoseofthesurroundingsea.

TheNorthAtlanticOscillation (NAO)hasbeen correlatedwitha rangeof long‐termecological

measures, including fish stocks. Such environmental influences are most likely to affect

susceptiblejuvenilesduringestuarineresidency,asestuariesarecriticaljuvenilenurseryorover‐

winteringhabitats(AttrillandPower,2002).Nonetheless,noneoftheselectedspeciesrevealed

to have a significant influence by the NAO, which as a large‐scale oceanographic process,

influencesnotonlytheSST,butalsothewindandcurrentpatternsalongthePortuguesecoast

(Henriques et al., 2007). The main effects of the NAO on the recruitment and estuarine

colonization ofmarine fish can bemost likely observed at a broader scale, either in time or

space, than theonesused in this study.Nevertheless, the isolationof single factors that can

influence recruitmentpatterns canbe somewhatdifficult, since themovement fromoffshore

waterstoinshoreprotectedareasisacomplexandintricateprocess.Infact,itislikelythatlocal‐

and meso‐scale singularities in hydrography, bathymetry or landscape structure may also

contribute to regionaldifferences in transportprocesses (Baileyetal.,2008). Inaddition,and

accordingtoMestresetal.(2007),theextensionofriverplumes,derivedfromtheonlypredictor

thatwasconsideredsignificantintheGLManalysisforthethreespecies(riverrunoff),isclearly

influencedbythemainlocaldrivingmechanisms,namelytheprevailingwindandthefreshwater

discharge rate, and even within a species, there may be local adaptations reflecting quite

differentstrategies(Baileyetal.,2008).

D.labrax,P.flesusandS.soleainPortugueseestuaries

RegardingD.labrax,thehighestdensitiesinPortugueseestuarieswererecordedintheMondego

estuary.InarecentworkbyVasconcelosetal.(2008),theauthorsidentifiedbyotolithelemental


113 |ChapterIII

fingerprintsthatabout40%ofthecoastalstocksofthisspecieswereoriginatedintheMondego

nurseries, thus reinforcing the roleof theMondegoestuary forcoastal stocks.ForP. flesus,a

decrease indensities towards south is consistentwithCabral et al. (2001),who reported the

decrease in densities near its southern limit of distribution, located along the center of the

Portuguese Atlantic coast. The highest densitieswere recorded in theMinho estuary (North

Portuguesecoast),andinagreement,Vasconcelosetal.(2008)indicatedthatatleasthalfofthis

species’ coastal stockswereoriginated inanorthernestuary (Douroestuary).As for S. solea,

nurseryoriginsweredeterminedtobemostlyfromtheMondegoandTagusestuaries,although

withlessreliability(Vasconcelosetal.2008).Thisspeciesseemstobethemostubiquitousinthe

Portuguesecoast,withsimilardensitiesfoundovertheselectedestuaries.However,thehighest

densitieswererecordedat theMinhoestuary,similarly toP. flesus.Asageneral trend,higher

densitieswerefoundinnorthernestuaries.

Climatechangescenarios:futureperspectivesinrecruitmentlevels

RecentclimatechangeprojectionsfortheIberianPeninsulapointoutthatbothtemperatureand

droughtperiodsareexpectedto increase,withaconcentrationofrainfall inthewintermonths

(Mirandaetal.,2006).Moreprecisely,andbasedon the IntergovernmentalPanelonClimate

Change–SpecialReportonEmissionsScenarios (IPCC‐SRES,2001)models,winterprecipitation

by theendof theXXIcentury ispredicted todecreaseanaverage15% (Mirandaetal.,2006).

Accordingtothepreviousauthors,reductionsinprecipitationamountsthroughouttheyearare

expected to be higher: ‐20% to ‐50%. Considering this, the decrease in precipitation and

consequentlyriverrunoffwillleadtoareductionoftheextentofriverplumestocoastalwaters,

whichhasbeendeterminedasan important factor for the recruitment successofmarine fish

thatuseestuaries asnursery areas.Asa significantoutcome, runoff regime shifts can induce

changes incoastalfisheries:Meyneckeetal. (2006)basedonadataseriesfrom1988to2004,

concluded that dry years were often associated with lower catches, leading to important

economicandsocial losses.Duetotheconcentrationofprecipitation intime,restrictedtothe


114 |ChapterIII

wintermonths,itispossiblethatspeciesthatmigratetoestuariesinspring,suchasD.labraxand

P.flesus,canbesignificantlyimpactedduetothedecreaseinrunoffandtothelesserextentof

riverplumes,inagreementwiththepresentresultsandwithVinagreetal.(2007).Infact,inthe

present study, these species showed adecrease indensitiesduring and after thedrought, in

oppositiontoS.solea.Inaddition,previousworkbyDolbethetal.(2008)indicatedabreakdown

ofsecondaryproduction innurseryspeciesduring thedrought,whichcanbean indicator that

continueddecreasesinriverrunoffcaninfactimpactonthesespecies.Regardingthisscenario,it

ispossible to infer thatD. labraxandP. flesuswillbemoreaffectedbydroughtevents in the

future,thusrequiringefficientmanagementmeasures.

Further improvementsonthisapproachwouldbethe integrationofplanktonandreproductive

biologydatainordertoobtainamoreaccuratescenariooftheestuarinecolonizationprocesses.

In addition, protracting this time‐series would allow a better definition of the physical and

environmentalconditionsthatcontributetotherecruitmentvariabilityinthestudiedspeciesand

thatoperateoverlargertimeandspatialscales.

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121 |ChapterIV

ChapterIV

Samplingestuarinefishassemblageswithbeamandottertrawls:differences in

structure,compositionanddiversity

Abstract

The effect of sampling gear used in the determination of estuarine fish communities’ structure andcompositionwereassessedduringfourseasonalfieldsurveysintheMondegoestuary,Portugal,conductedin2003and2004.Samplingwithbeamandottertrawlwasperformedatnight,attwodifferentlocationsinthenortharmoftheestuary.Ingeneral,seasonalottertrawlsampleswerecomposedwithahigherspeciesnumber,butunderestimatedtheestuarineresidentsincomparisonwithbeamtrawlsamples.Therelativeabundanceofzoobenthivoreswassimilar inbothgears,whileforthepiscivores,theirrelativeabundancewas about two timeshigher inotter trawl samples in2003, andopposite in2004.Multivariate analysisdetectedsignificantdifferencesinthestructureandcompositionofestuarinefishassemblagescapturedbythetwotechniques,withhigherwithin‐gearvariabilityinbeamtrawlsamples.Significantdifferencesweredetectedinmediantotallengthandlength‐frequencydistributionsofthemostabundantandcommerciallyimportantspeciesDicentrarchus labrax,PlatichthysflesusandSoleasolea,withthesmallestfishcapturedbybeamtrawl.Resultsarediscussedregardingthedesignoffieldsurveys,andcomparedwithotherfishinggears and several other factors, such as diel period, tow duration and tidal conditions. Concerning theEuropeanWater FrameworkDirective,distinct results in the structureand compositionofestuarine fishassemblages(either inspeciesorfunctionalgroups)obtainedbydifferentsamplinggearscansignificantlyinfluencethedeterminationoftheEcologicalQualityStatus.

Keywords

Samplingdesign::Fishassemblages::Ecologicalguilds::WaterFrameworkDirective::Mondego


123 |ChapterIV

Introduction

Estuariesareamong themostproductivesystems throughout theworldandat thesame time

among themost threatened from a varietyof conflictinghumanactivities,which impair their

ecologicalfunctions(McLuskyandElliott,2004;Dolbethetal.,2007a;Vasconcelosetal.,2007;

Hewitt et al., 2008). Increasing pressures can result in the impairment of estuaries’ main

functions, goods and services, with severe consequences for the environment and the

population.Withinestuarine(=transitionalwaters)communities,fishhavebeenusedmainlyfor

the assessment of (a) changes in composition and structure through time (e.g.Araújo et al.,

2000; Hemingway and Elliott, 2002), (b) spatial distribution (e.g.Martinho et al., 2007a), (c)

direct impacts of pollution sources (e.g. Lancaster et al., 1998), (d) recruitment variability of

commercially importantspeciesandnurseryareas (e.g.vanderVeeretal.,2001,Cabraletal.,

2007,Martinhoetal.,2007a)and(e)productionof individualspeciesand/orcommunities(e.g.

Pomboetal.,2007,Dolbethetal.,2008a).

Onecommonaspectofusing fishas indicatorsofstatechanges is theneed forefficient,cost‐

effectiveand representativesamplingmethods, inorder to retain themost information in the

leastnumberof samplespossible, since theyusually involvedestructive, expensive and time‐

consuming techniques. In fact,oneof themost importantdecisions indeveloping a sampling

program isgear selection (RozasandMinello,1997).Accordingly, severalmethodologieshave

beenusedforsamplingestuarinefishcommunities(somederivedfromcommercialfisheries)in

order to capture elements from the pelagic, demersal, benthic, marginal and cryptic

communities:beam trawl (e.g.MarshallandElliott,1998;Cabraletal.,2007;Martinhoetal.,

2007b),otter trawl (e.g.Thieletal.,1995;Rotherhametal.,2008),gillnets (e.g.Harrisonand

Whitfield, 2004), beach seine and fish traps (e.g.Gell andWhittington, 2002), fyke nets (e.g.

Mathiesonetal.,2000)powerplant coolers (e.g.Araújoetal.,2000;AttrillandPower,2002;

Greenwood,2008),dropsamplers(e.g.Almeidaetal.,2008)andvisualcensus(mostlyforrocky

substratesandcaves)(e.g.Henriquesetal.,2007;BussottiandGuidetti,2009)(SeeHemingway

andElliott,2002forafullreview).Recentworkhasnotedthatthestructureandcompositionof


124 |ChapterIV

fish samples canbe affectedby the choiceof gear type (Greenwood,2008) (due todifferent

catchefficienciesandareasampled (HemingwayandElliott,2002),dielperiod (Johnsonetal.,

2008), tow duration (Godø et al., 1990;Rotherham et al., 2008) and speed (Weinberg et al.,

2002). Although some of the factors here described refer to fisheries in coastal and deeper

marineareas, the sameconceptscanbeapplied toestuarine sampling.Given theabove‐cited

diversityof sampling gears and specifications,before implementing large‐scale and long‐term

monitoring surveys,an important first step is to test theeffectsofdifferent configurationsof

gear and samplingpracticeson retained samples (Gunderson, 1993;Rotherham et al., 2007).

AccordingtoHemingwayandElliott(2002),thechoiceofsamplingmethodologiesshouldatleast

take into account the targetorganisms, the substratum,hydrodynamic regime,habitat types,

spatialcoverageandalso logisticandsafety requirements.Forstudies thataim tocombineor

compare the results of previous studies, developing spatial comparisons, or use the relative

proportionofspecieswithinassemblages,samplingbiasesrelatedwithgearchoicemayseriously

misleadecologicalinterpretations(Guestetal.,2003).

TheEuropeanWater FrameworkDirective (WFD;2000/60/EC) requires for transitionalwaters

that fish communities should be sampled every three years for the determination of the

EcologicalQuality Status (EQS). In this particular case, it is very important that the sampling

methodologiesused indifferentestuariesandcountriesproducecomparableresults,giventhe

possibility of similar assemblages being classified as different or in opposition, different

assemblages being classified as equal. In fact, several authors have used different sampling

methods for theassessmentof theEQS:otter trawl ‐Deeganetal. (1997), trawl ‐Borjaetal.

(2004),gillnets‐HarrisonandWhitfield(2004),fyke‐nets–Breineetal.(2007)ormulti‐method

sampling(seinenets,beamandottertrawls)‐Coatesetal.(2007),whosedifferentresultshave

considerable implications inestablishingreferenceconditionsagainstwhichpresentandfuture

resultsaretobecompared.Recently,Martinhoetal.(2008b)evaluatedtheresultsobtainedby

the above authors, applying the proposed ecological indices in a small intertidal estuary

(Mondego estuary, Portugal, SW Europe), reinforcing the suggestion that similar sampling


125 |ChapterIV

methodologiesshouldbeadoptedbyEUmemberstates.Hence,theobjectivesofthisstudywere

toassessthedifferencesbetweentwofishsamplingmethods:beamandottertrawl,considering

specific richness, structure and composition of estuarine fish communities, and to determine

differences in abundance trends over time, median total length and length frequency

distributionsofthemostabundantspeciescommontobothtechniques.

MaterialandMethods

Studysite

TheMondego estuary is a small estuarine system, located on the Atlantic coast of Portugal

(40º08'N,8º50'W) (Fig.1). Its terminalpart isdivided in twoarms (northand south) that join

againnear themouth.Thenortharm isdeeper,with5 to10mdepthathigh tide,while the

southarm isshallower,with2to4mdepthathightide,beingthetidalrangeof2to4m.The

southarmissilteduptosomeextentintheupstreamareas,whichcausesthefreshwatertoflow

mainlyby thenortharm. In the southarm,about75%of the totalarea consistsof intertidal

mudflats,while in thenortharm theyaccount for less than10%.Thewater circulation in the

southarm ismainlydependenton the tidesandona small freshwater input from thePranto

River, a small tributary system. A commercial harbour is located in the north arm,with the

estuarinesedimentsbeingsubjectedtoconstantdredginginthemainnavigationareas.

Samplingdesign

In this experiment, two sampling sites were chosen in theMondego estuary, separated by

approximately3km(Fig.1):A–withtypicalmarineinfluence,located1.5kmfromtheestuary’s

mouth,8.7±1.2mdepth;B ‐withregularfreshwaterflow,5.5±0.5mdepth, located4.5km

fromtheestuary’smouth.Therestrictiontousetheottertrawlinthedeeperwatersofthenorth

armof the estuarydetermined the choiceof the sampling sites. Samplingwas carriedout at

night,sinceprevioussurveysindicatedthatdaytimesamplingwasinefficientinthisestuary,and

fishingstartedathighwaterofspringtides.Fieldworkwasconductedalongoneyear(June2003


126 |ChapterIV

toMay2004),withseasonalperiodicity (onesamplingoccasionperseason)and insimilar tide

conditionsbutindifferentdays,toinsuretheindependenceofdata(seeUnderwood,1997).At

eachstation, three replicateswerecollectedwitha2mbeam trawlwithone ticklerchainand

5mm stretchedmesh size in the cod end, andwith a 10m headline otter trawlwith 10mm

stretchedmeshsizeinthecodend.Thetwosamplinggearswerechosenbasedonthefactthat

theyareamongthemostextensivelyusedfishinggearsforstudyingestuarinefishassemblages

(see Hemingway and Elliott, 2002). At each station, three hauls along the current were

performedwitheachgear,coveringat leastanareaof500m2.Distance travelledbyeachhaul

wasmeasuredwithaGPSdevice,and tow speedwasapproximately1knot forbothgears.A

totalof 48 towswereperformed.All fish caughtwere immediately frozen, and subsequently

identified,countedandmeasuredfortotallength(TL)tothenearest1mm.

PO

RTU

GA

L

A

B

South Arm

North ArmAtlanticOcean

Intertidal Areas

Saltmarshes

Sampling Stations

40” 0

8’ N

8” 50’ W

1 Km

Figure1LocationoftheMondegoestuaryandoftheselectedsamplingstationsinthenortharmoftheestuary(AandB).


127 |ChapterIV

Dataanalysis

Toeliminatethevariabilityinherenttodifferentmeshsizes,allfishwithlessthan50mmTLwere

removedfromtheanalysis,since itwasthesmallestTLcapturedbythe10mmmeshsizeotter

trawl.Fishdatawasstandardizedasthenumberof individualsper1000m2,andwereanalyzed

according to thesampling regime:beamandotter trawl.Monthlydatawerecalculatedas the

averageofthethreehaulsforeachgear,andspeciesabundancedatawerestandardizedasthe

percentageoftotalcatches,toenabledirectcomparisonbetweensamplingmethods.Inorderto

assessthefishcommunitystructure,fishspecieswereclassifiedinecologicalguilds,accordingto

therecentreviewbyElliottetal.(2007):marinestragglers(MS),marine‐estuarineopportunists

(MMO),marine‐estuarinedependents (MMD),estuarineresidents (ER),catadromous (CA);and

inthetwomostrepresentativefeedingguildsinestuarinefishassemblages:piscivores(PV)and

zoobenthivores(ZB).

Differences in catch composition (speciesnumberper ecological guild, ecological and feeding

guildrelativeabundance)wereassessedwithKruskal‐Wallisnon‐parametricANOVA.Datawere

explored using ANOSIM to test for differences between sampling gears, and a non‐metric

multidimensionalscaling(nMDS)(Bray‐Curtissimilaritymatrix)wasusedtodeterminetrendsin

structureandcompositionoffishsamples.TheSIMPERprocedurewasperformedtodetermine

whichspeciescontributedmostforboththesimilarityinsamplinggearsandforthedissimilarity

betweenbeamandottertrawl.Priortotheseanalyses,abundancedatawerestandardizedusing

asquareroottransformation.Resultswerecomparedtodetermine ifthereweredifferences in

thestandardizedproportionsoffishspecies intheassemblages,andpresence/absencedatato

detectdifferentspeciescompositionbetweensamplinggears.Theseanalyseswereperformed

usingPRIMERsoftware(ClarkeandWarwick,2001).

Forthemostabundantspeciescaughtinbothgears,Dicentrarchuslabrax,Platichthysflesusand

Solea solea, differences regarding themedian total lengthwere assessedwith Kruskal‐Wallis

non‐parametricANOVA.For thispurpose, thedatasetusedconcerned the totalcatchesof the

foursamplingdatesforbothbeamandottertrawl.Differencesinlength‐frequencydistributions


128 |ChapterIV

were assessed with Kolmogorov‐Smirnov two‐sample tests, using the same dataset and

methodology.Regardingtheseasonalabundancetrendsforeachspecies,resultsbetweengears

werecomparedwithSpearmanrankcorrelations.Asignificance levelof0.05wasconsidered in

alltestprocedures.

Results

Structureandcompositionoffishcommunities

Atotalof2800fish(26species)werecollectedduringthestudy,1134frombeamtrawland1666

fromottertrawlsurveys,correspondingto20speciesinbothgears(Table1).Ottertrawlsamples

capturedahigherspeciesnumberandindividualswhenanalysedseasonally(withtheexception

of the summer 2003) (Fig. 2), particularly formarine‐estuarine opportunists (MMO),marine

stragglers (MS) and catadromous (CA) groups. In opposition, the beam trawl samples were

composed of a higher number of estuarine resident species (ER) (Fig. 2A, C, E, G).Marine

estuarinedependent (MMD) species,composedby someof themostabundant species in the

estuary,wereequally represented inbothgears in termsof speciesnumber (Fig.2).Forboth

gears, samples collected at station A (located at the estuary’smouth) had generally higher

species number of all ecological guilds. Significant differences between sampling gearswere

obtained forthespeciesnumberofallecologicalguilds:MS,H=6.610,p<0.05;MMO,H=7.580,

p<0.05;MMD,H=5.974,p<0.05;ER,H=0.773,p<0.05;CA,H=4.651,p<0.05.Whencomparingthe

densities(transformed inrelativeabundanceforabettercomparisonbetweensamplinggears),

considerabledifferenceswere found:beam trawl samplesweremainly composedbymarine‐

estuarine dependents (MMD) and estuarine residents (ER), while otter trawl samples were

mainly composed bymarine‐estuarine dependents (MMD) andmarine‐estuarine opportunists

(MMO)(Fig.3).


129 |ChapterIV

Table 1. Species list of theMondego estuary fish assemblage collected during the studyperiod,withrespectiveFamily,EcologicalGuild,FeedingGuild,averagedensityestimates(N.Ind 1000m‐2 ± standard deviation) and total species number for beam and otter trawlsamples;CA–catadromous,ER–estuarineresident,MS–marinestragglers,MMO–marineestuarineopportunists,MMD–marineestuarinedependents,and:ZP–zooplanktivores,ZB–zoobenthivores,PV–piscivores,OV–omnivores,DV‐detritivores.

Species Family EcologicalGuild

FeedingGuild Beamtrawl Ottertrawl

Anguillaanguilla Anguillidae CA ZB/OV 0.29±0.39 0.10±0.08

Aphiaminuta Gobiidae MS PV 0.26±0.64 ‐

Atherinaboyeri Atherinidae ER PV/OV 0.07±0.14 ‐

Atherinapresbyter Atherinidae ER ZB/OV 0.04±0.10 0.02±0.04

Callionymuslyra Callionymidae MS ZB/OV 0.12±0.35 0.01±0.02

Chelidonichthyslucerna Triglidae MMO PV 0.16±0.35 0.20±0.20

Ciliatamustela Gadidae MMO ZB 0.12±0.24 0.04±0.10

Congerconger Congridae MS PV ‐ 0.05±0.10

Dicentrarchuslabrax Moronidae MMD PV 3.34±6.50 1.56±2.28

Diplodusvulgaris Sparidae MMO ZB/OV 1.54±2.24 2.59±4.78

Echiichthysvipera Trachinidae MS ZB/OV ‐ 0.06±0.06

Gobiusniger Gobiidae ER ZB 0.08±0.22 0.03±0.06

Lizaaurata Mugilidae MMO DV/OV 0.03±0.09 0.01±0.02

Lizaramada Mugilidae CA DV/OV ‐ 0.01±0.02

Mugilcephalus Mugilidae MMO DV/OV ‐ 0.03±0.06

Mullussurmuletus Mullidae MMO ZB 0.08±0.23 0.04±0.08

Platichthysflesus Pleuronectidae MMD ZB 1.41±2.00 1.31±1.62

Pomatoschistusmicrops Gobiidae ER ZB 0.21±0.28 ‐

Pomatoschistusminutus Gobiidae ER ZB 3.84±5.91 ‐

Sardinapilchardus Clupeidae MMO PV 0.04±0.12 ‐

Scophthalmusrhombus Scophthalmidae MMO PV 0.11±0.24 0.20±0.14

Soleasenegalensis Soleidae MMO ZB ‐ 0.11±0.23

Soleasolea Soleidae MMD ZB 4.14±4.62 4.19±5.49

Sparusaurata Sparidae MMO ZB/OV 0.03±0.09 ‐

Syngnathusacus Syngnathidae ER ZB 1.24±3.41 0.05±0.08

Trisopterusluscus Gadidae MS ZB/OV ‐ 0.04±0.10

Totalspecies 20 20


130 |ChapterIV

ThehighrelativeabundanceofERinbeamtrawlsampleswasrelatedtothehighabundanceof

PomatoschistusmicropsandP.minutus.Also,inthebeamtrawlsamples,adominanceofMMD

andERwasobserved in all sampling events,with the exceptionof the Spring2004 (Fig.3G),

when ahighequitabilitybetween guildswasobserved. In theotter trawl samples,MMDand

MMOcomprisedthemajorityofthefishassemblage,asobservedinallsamplingevents(Fig.3B,

D, F, H). Significant differences between beam and otter trawl were only obtained for the

estuarineresidents(ER)(H=16.877,p<0.05).

Ingeneral, thezoobenthivores (ZB)comprisedasignificanthigherproportionof thebeamand

otter trawlsamples (Fig.4B,D,F,H).Theexceptionwas thewinter2004,when thepiscivores

(PV)weremoreabundant(Fig.4A,C,E,G).Thispatternwasobservedforbothbeamandotter

trawlsamples.However,nosignificantdifferenceswerefoundbetweenthecatchcompositionof

thefeedingguilds(PV,H=0.480,p>0.05;ZB,H=2.083,p>0.05).

TheANOSIMprocedurerevealedsignificantdifferencesbetweenassemblagescapturedbybeam

andottertrawlregardingthestructure(standardizedrelativeabundance,R=0.496,p=0.001)and

speciescomposition (presence/absence,R=0.587,p=0.001).Averagesimilarityvalues forbeam

trawlsampleswhere44.2%and55.0%(standardizedrelativeabundanceandpresence/absence

data, respectively), while for otter trawl samples, average similarity values were 56.7% and

67.6%(standardizedrelativeabundanceandpresence/absencedata,respectively).Theseresults

werealsosupportedbytheMDSanalysis(Fig.5),andinbothcases,higherwithin‐gearvariability

was registered for beam trawl samples. In agreementwith the previous guild approach, the

species thatmost contributed for the similarity (Bray‐Curtis similarity) in beam trawl surveys

weretheERP.micropsandP.minutus,theMMDD.labrax,S.soleaandP.flesus,andtheMMO

Diplodus vulgaris (SIMPER) (Table 2). In otter trawl samples, S. solea,D. labrax, P. flesus (all

MMD),D.vulgaris,ScophthalmusrhombusandCiliatamustela(allMMO),andAnguillaanguilla

(CA)contributedformorethan90%ofthesimilaritybetweensamples,accordingtotheSIMPER

procedure(Table2).


131 |ChapterIV

Figure2.Speciesnumber foreachecologicalguildcapturedwithbeamandotter trawlatsamplingstationsA,Band inallsamples;MS‐marinestragglers,MMO‐marine‐estuarineopportunists, MMD ‐ marine‐estuarine dependents, ER ‐ estuarine residents, CA –catadromous.

Differencesintypifyingspeciesweredrivenbyahigherspeciesnumberinthepresence/absence

analysis,whichincludedalsoChelidonichthyslucerna(MMO)andA.anguilla(CA)inbeamtrawl

samples,andEchiichthysvipera(MS) inottertrawlsamples(SIMPER)(Table2).A largenumber

ofspeciescontributedforthedissimilaritybetweensamplingmethods(Bray‐Curtisdissimilarity)

(Table3), corresponding toanaveragevalueof64.4% (standardized relativeabundancedata)

and53.5%(presence/absencedata)(ANOSIM).


132 |ChapterIV

Figure3.Relativeabundanceofeachecologicalguildcapturedbybeamandottertrawl,atsamplingstationsA,Band inallsamples;MS‐marinestragglers,MMO‐marine‐estuarineopportunists, MMD ‐ marine‐estuarine dependents, ER ‐ estuarine residents, CA –catadromous.

Variationsinabundance,totallengthandlength‐frequencydistributions

For themostabundantandcommercially important species inbothgears,D. labrax,P.

flesusandS.solea (allMMD) (seeFig.6),significantdifferenceswhere found inmedian

total lengthof fish caughtbybeam andotter trawl (D. labrax:H=119.683,p<0.001;P.

flesus:H=19.194,p<0.001;S.solea:H=112.772,p<0.001)(Fig.6).


133 |ChapterIV

Table 2. Speciespercent contribution for the similarity in each sampling gear comprisingmore than 90% of the similarity.Results from standardized relative abundance data andpresence/absencedataarecompared.

Species Beamtrawl Ottertrawl

P.microps 27.60

P.minutus 25.72

S.solea 15.24 31.85

D.vulgaris 10.08 11.66

D.labrax 9.48 15.82

P.flesus 4.94 15.64

S.rhombus 8.56

C.lucerna 6.00

A.anguilla 4.76

Stan

dardized

relativeab

unda

nce

Averagesimilarity 44.15 56.66

P.microps 21.38

P.minutus 21.38

S.solea 16.15 15.26

D.labrax 11.65 15.26

P.flesus 7.87 15.26


C.lucerna 4.11 10.47

A.anguilla 3.82 10.90

S.rhombus 12.31

E.vipera 5.01

Presen

ce/A

bsen

ce

Averagesimilarity 55.01 67.63

Significant differences in length‐frequency distributionswere also obtainedwith Kolmogorov‐

Smirnovtestsforthethreespeciesconsidered(D.labrax:KS=5.162,p<0.001;P.flesus:KS=2.776,

p<0.001;S.solea:KS=5.658,p<0.001).


134 |ChapterIV

Table 3. Species percent contribution for the dissimilarity between sampling gearscomprising more than 90% of the dissimilarity. Results from standardized relativeabundancedataandpresence/absencedataarecompared.

Species Standardizedrelativeabundance

Presence/Absence

P.minutus 14.53 10.36

P.microps 13.79 10.36

S.solea 10.53


D.labrax 9.52 2.51

P.flesus 9.08 3.77

S.rhombus 4.81 6.49

C.lucerna 4.39 5.33

A.anguilla 3.31 5.49

E.vipera 2.71 5.67

S.acus 1.99 4.15

M.surmuletus 1.67 3.13

S.senegalensis 1.66 4.87

S.pilchardus 1.56 2.39

A.minuta 1.56 2.51

G.niger 3.58

C.mustela 3.50

C.conger 3.36

A.presbyter 2.98

M.cephalus 2.22

A.boyeri 2.21

T.luscus 2.09

Averagedissimilarity 64.36 53.47

Largerfishcapturedwiththeottertrawlandalsothesmalllength‐classescapturedbythebeam

trawlmainlydrovethesedifferences(Fig.6).Comparingtheseasonaltrends indensitiesofthe

selectedspeciesalongthesamplingperiod,S.soleawasthemostabundantofthethreespecies,


135 |ChapterIV

both inbeamandotter trawl samples (Fig.7C).RegardingD. labrax,anabundancepeakwas

observed in thewintersamples (inbothsamplinggears) (Fig.7A),whileas forP. flesus, lower

densities were observed (Fig. 7B). However, no significant correlations (Spearman rank

correlation)were found for the abundance values in beam and otter trawl samples for each

species.

Discussion

Geartype‐specificfishassemblages

An underlying assumption in estuariesmanagement is thatmodified habitats contain altered

biologicalcommunities,andthatspeciesrichnessis,ingeneral,inverselyproportionaltodegree

ofdeterioration(Araújoetal.,2000). Inthiscontext,fishassemblageshavebeenusedbecause

theyareknown to change in compositionas theirhabitatsaremodified (Araújoetal.,2000).

Thus, this study aimed at identifying differences in estuarine fish assemblages sampled by

differentfishinggears,inordertoestablishfuturemonitoringprogrammeseitheratalocalora

broader scale. Effectively, the two fishing gears here tested gave significantly different catch

compositions,regardingthestructureandcompositionoftheMondegoestuaryfishassemblage.

Themaindifferencebetweenbothgearswasdrivenby theabsenceof theestuarine resident

gobiesP.micropsandP.minutus intheottertrawlsamples. Infact,theseareamongthemost

abundant species in the estuary (Dolbethet al.,2007b;Martinho et al.,2007b),being clearly

underestimatedbytheottertrawl.

Althoughthespeciesrichnesswasequalinbothgears,seasonalottertrawlsampleshadhigher

species number, with the exception of the summer 2003. In addition, the main difference

betweensamplinggearswasahigherspeciesnumberoftheestuarineresidents(ER)inthebeam

trawlandahighernumberofmarine‐estuarineopportunists(MMO)andmarinestragglers(MS)

in the otter trawl. Regarding the relative abundance of the ecological guilds, thebeam trawl

samplesweremorehomogeneous,althoughwithadominationofmarine‐estuarinedependent

(MMD),marine‐estuarineopportunists(MMO)andestuarineresidents(ER).


136 |ChapterIV

Figure 4. Relative composition of the most abundant feeding guilds (piscivores andzoobenthivores)capturedbybeamandottertrawl.

In otter trawl samples, a clear domination by themarine estuarine dependent (MMD) and

marine estuarineopportunists (MMO)was always evident. Suchdivergencebetween samples

can be attributed to the lack of estuarine residents in the otter trawl samples, as referred

previously. Inagreement,andaccording toOlinandMalinen (2003),estimatesof fishdensity,

speciescompositionandsizedistributionscandiffernotablydependingonthesamplingmethod

andtime.

Inthepresentstudy,theeffectofdielperiodwasnottakenintoaccount,sinceprevioussurveys


137 |ChapterIV

reportedthatthecatchefficiencyofthebeamtrawlwasnoticeablypoorduringdaytime,anddid

notservethepurposeforsamplingtheestuary’sfishfauna.Inagreement,severalauthorshave

statedthatnocturnalsamplesprovidehigherspeciesnumberandabundanceoffishspecies(e.g.

Grayetal.,1998;Guestetal.,2003;Unsworthetal.,2007;Johnsonetal.,2008;Rotherhamet

al.,2008),astheefficiencyoftrawlnetsincreaseswithdecreasedvisibility(vandeBroek,1979).

Moreover, ithasbeennotedthatmoreorganismsandspeciesarecaught inestuarineseagrass

beds atnight (e.g.Grayet al.1998;Guestet al.,2003;Unsworthet al.,2007),probablyas a

consequenceofincreasedavailabilityofinvertebratefoodresources(e.g.SogardandAble,1994;

Guestetal.,2003;Unsworthetal.,2007).

Significantdifferencesinmediantotallength(TL)andlength‐frequencydistributionswerefound

forthemostabundantandeconomically importantspecies:D. labrax,P.flesusandS.solea(all

MMD),asbeam trawl samples collectedmainly the smaller length‐classesof these species. In

opposition,ottertrawlsampleswerecomposedoflargerfishes,aswellasalargerminimumTL

caught.A similarpatternwas reportedbyGuestetal. (2003),whoobserveddifferences inTL

frequency distributions between beam trawl and seine net samples, being the smaller size‐

classescapturedbythebeamtrawl.SimilarresultswerealsoreportedbyGreenwood(2008).As

for the seasonal trends in abundance for these species, no significant correlations could be

attained between beam and otter trawl samples. Regarding D. labrax, a similar trend in

abundance couldbeobserved forbothbeam andotter trawl: thehighestdensities inwinter

samples,canbeexplainedbyaconcentrationof fish in themostdownstreamareas,near the

mouthoftheestuary.Asforthetwoflatfishes,P.flesusandS.solea,twodifferentcommunities

couldbedetected:summerandautumnsamples,mainlydominatedby0‐groupfish(Martinhoet

al.,2007a),beinglessabundantinottertrawlsamples(duetoalessercacthabilitybythisgear),

and winter and spring samples, composed of older fish (namely 1‐ and 2‐group fish) that

concentrateinthemostdownstreamareas(Martinhoetal.,2007a).


138 |ChapterIV

Figure 5. Multidimensional Scaling (MDS) ordination plots of standardized relativeabundance (A)andpresence/absencedata (B)of theestuarine fish communities sampledwithbeamandottertrawl.Samplesincludeallsamplingstationsanddates.

Thus, thedifferencesbetween species (demersal vs.benthic) canbe related todifferences in

spatialoccupationofdifferentsize‐classesalong theestuary (namely in thesampledareas),as

larger fish tend tomove to deeper estuarine areas (e.g. Leitão et al., 2006,Martinho et al.,

2007a).On the contrary, recent investigations byGreenwood (2008) pointed out that strong


139 |ChapterIV

positivecorrelationsexistedinseveralspecies’abundancetrendscollectedatbothpowerplant

cooling‐waterintakescreensandtwotrawlingmethods(pelagicandAgassiztrawls).

Implicationsforthedesignoffieldsurveys

Whendesigningasamplingprogramme,theuniquecharacteristicsofshallowestuarinehabitats

must be considered, and the choice of a technique depends on several factors including the

overallobjectivesofthesurvey,thetargetspeciesandthesamplingarea(HemingwayandElliott,

2002;Guestetal.,2003).Inaddition,thesamplingdesignshouldincorporateasfewsamplesas

possible(RozasandMinello(1997),thusreducingthenumberoffishkilledandtheneedforsub‐

sampling(Godøetal.,1990).Recently,someworkhasbeenconductedtocomparefishsampling

methods, inanattempttodesignmoreefficientfieldsurveys, introducingthevariablesofgear

type, diel period, tow duration and net height (e.g. Wieland and Storr‐Paulsen, 2006;

Greenwood,2008;Johnsonetal.,2008;Rotherhametal.,2008).

AccordingtoMorrisonetal.(2002),thechoiceoftideforfishsamplingisadeterminantfactor,

ashigh tide sampling inmudflats canbe substantially less informative.To reducebias related

with tides, in thisworkallsamplingeventswerecarriedoutatspring tides,startingatebbing

water. A further improvement of this approach would be to test differences related to

spring/neaptides(i.e.lunarcycles),assomefishspecies(e.g.soles)havebeendemonstratedto

perform tidal‐and lunar‐relatedmigrations (seeVinagreetal.,2006).Regarding towduration,

several authorshavepointedout that short tows (between 5 and 15minutes) capturemore

speciesdiversity (Godøetal.,1990;Rotherhametal.,2008)andabundance (Somertonetal.,

2003)relativelytolongertows.Smallertowsalsoallowforincreasingreplicationandprecisionin

surveys,withoutlargeincreasesincosts(PenningtonandVølstad,1991;Rotherhametal.,2008).

Regardingthedielperiodinwhichsamplingshouldpreferablybecarriedout,moststudiespoint

tonightsampling,withconsiderableincreasesinspeciesnumber,diversityandabundance(Gray

etal.,1998;Guestetal.,2003;Unsworthetal.,2007;Rotherhametal.,2008).


140 |ChapterIV

Figure 6. Comparison of total length frequency distributions for themost abundant andcommerciallyimportantspeciesD.labrax(A),P.flesus(B)andS.solea(C)inbeamandottertrawlsamples.

Consequently, futuremonitoring plans should include night sampling (as the present work),

despitethetechnicalconstraintsanddifficultiesassociated.Towingspeedisanotherfactorthat


141 |ChapterIV

shouldbeconsidered,asthecatchofbenthicspeciessuchasflatfishcanbemoreaffectedbythe

lossoffootropecontactwiththebottom(Weinbergetal.,2002).

As an alternative to a singlemethod,multi‐method sampling programmes can be used for

estuarine fish assemblages. Unlike sampling for other components such as the benthos or

plankton, the fish assemblage comprisesmanydifferent groups representingdifferentniches,

andthusrequiresmanydifferent–thoughcomplementary–methods (HemingwayandElliott,

2002).SuchanapproachhasbeenimplementedintheUnitedKingdomsince2002,giventhatit

was considered amore effectivewayof assessing the ecological statusof transitionalwaters

(Coates et al., 2007). The sampling gears used are seine nets, otter trawls and beam trawls,

targetingbothpelagicandbenthicfishspecies,deployedaccordingtosite‐specificcharacteristics

(seeCoatesetal.,2007).Despitetheadvantagesofsuchpracticeareevident,formanycountries

its feasibilitycanbequestioned,due to theconsiderablehuman resourcesandcosts involved.

Ultimately, the choice of sampling gear shall fall on one singlemethod.Aswith all sampling

gears, it is important to acknowledge that not allmembers of the fish assemblage will be

collectedandthosethatarewillbecaughtwithdifferingefficiencies(Greenwood,2008),sothe

choiceofsamplinggearmustbeacompromisebetweencatchcharacteristics,easeofuseand

theobjectivesofthestudy.

One limitationofthisworkwasthe inabilityofsamplingthewholeestuarinearea, imposedby

therestrictionofusingtheottertrawlonlyinthedeeperareas.Thiscanbeseenasaconstraint

inusingthistechniqueinshallowestuaries,asthecaseoftheMondego,sinceitisnotpossibleto

have a representative sample of the whole estuary. Apart from this exercise, a sampling

programmewas started in June 2003 (see Leitão et al., 2006; Dolbeth et al., 2007b, 2008a;

Martinhoetal.,2007a,b,2008a for furtherdetails),usinga2mbeam trawl (5mmmesh size),

providingawiderpictureofthechanges instructureandcompositionofthefishassemblages.

Accordingly, and since the species richnesswas equal in both gears (although not the same

speciescomposition),thebeamtrawlseemsamoresuitablemethodtouseinshallowestuaries.


142 |ChapterIV

Figure7.SeasonalvariationofdensityestimatesforD. labrax(A),P.flesus(B)andS.solea(C)basedonbeamandottertrawlsamples.

Otheradvantagesrelyonthefactthatitispossibletoestimatethesampledarea(inopposition

toseinenets)andtheeaseofuse(HemingwayandElliott,2002).Effectively,thebeamtrawl is


143 |ChapterIV

oneofthemostextensivelyusedmethodsforscientificsampling(HemingwayandElliott,2002),

butifneeded,theottertrawlcouldbeusedasacomplementforcapturinglargerfishandpelagic

species(asinMartinhoetal.,2008a).

CompliancewithWFDrequirements

TheWFD requires that for the fish component of transitionalwaters, sampling is conducted

every three years, and that the evaluation of the EcologicalQuality Status (EQS) is based on

speciesrichnessandabundanceofspecies/functionalgroups.Asaconsequence,differences in

the EQSmay occur due to bias introduced by different samplingmethodologies.Within this

framework, Coates et al. (2007) compared the EQS obtained for the Thames estuary (UK) by

beamtrawl,ottertrawlandseinenetsamples,andconcludedthatthebeamtrawlconsistently

providedthelowestestimatesofspeciesrichnessandEQS,sincethisgeartargetsmainlybenthic

fish communities (Hemingway and Elliott, 2002). This factwas not so evident in the present

work, since the beam trawl captured the same species number as the otter trawl, and also

showedmore equitability in the distribution of the species number trough the estuarine use

guilds. In addition, the otter trawl tended to underestimate the estuarine residents either in

species number or relative abundance, as is the case of the beach seine, which can

underestimate gobies and blennies (Gell andWhittington, 2002). The resident species are a

particularly important element of estuarine food webs, as determined by stomach contents

analysis(Leitãoetal.,2007;Dolbethetal.,2008b)andstable isotopeapproaches(Baetaetal.,

2008),andarealsocontemplatedinseveralmultimetricindicesusedtodeterminetheEQS:EBI

(species number) –Deegan et al. (1997), EDI (species number and abundance) –Borja et al.

(2004), EFCI (species number and abundance) – Harrison andWhitfield (2004), TFCI (species

numberandfunctionalguildsnumber)–Coatesetal.(2007)(SeeMartinhoetal.(2008b)forthe

comparison of indices). On the other hand, the otter trawlwasmore effective in capturing

marine‐estuarineopportunistspecies(MMO)inmostofthesamplingoccasions.


144 |ChapterIV

Regarding the feeding guilds, no significant differences between sampling gears could be

attainedduringthestudyperiod.However, intheparticularcaseofthesummer2003samples,

thevariability intherelativeabundanceofthepiscivoreswasveryhighbetween fishinggears.

Communityindicatorssuchastheproportionoffeedingguilds(amongothers)werealsousedby

Trenkeletal.(2004)toidentifydifferencesincatchcompositionforUKandFrenchtrawlsurveys

intheCelticSea.Likepointedoutbefore,differences inEQSobtainedbybeamandottertrawl

samplesmayoccur,consideringthatthefeedingguildsarealsocontemplatedinseveralindices

used: EDI (relative abundance) – Borja et al. (2004), EFCI (species number and relative

abundance)–HarrisonandWhitfield(2004),EBI(relativeabundance)–Breineetal.(2007),TFCI

(speciesnumberoffunctionalguilds)–Coatesetal.(2007).AsnotedbyCoatesetal.(2007),the

sampling regime will significantly affect the determination of the EQS, mainly due to gear

selectivity.

Conclusions

This study showed that, in low budget and human resources situations, both sampling gears

couldgiveeffectivequantificationofestuarinefishassemblages(withtheir inherent limitations

andselectivity).However,abettercoverageofthetotalestuarineareawould implytheuseof

thebeamtrawl,whichcanbeoperated inshallowerareassuchassmallchannelsandnearsalt

marshes.Inaddition,thebeamtrawlcapturedsignificantlysmallerlength‐classes,adetermining

issue when targeting in more detail recruitment patterns and smaller species, such as the

estuarine resident gobies. Efficient management plans, as required by the EuropeanWater

FrameworkDirective,needtobebasedoncost‐effectiveandbothquantitativeandqualitative

sampling,sofurtherdevelopmentoncomparingotheraspects(suchastowduration,tidalcycle

and mesh size) should be conducted in order to optimise resources and improve the data

requiredforbothresearchersandstakeholders.


145 |ChapterIV

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Lancaster, J.E.,Pawson,M.G.,Pickett,G., Jennings,S.,1998.The impactof the 'SeaEmpress'oil spillon


Leitão,R.,Martinho,F.,Neto, J.,Cabral,H.,Marques, J.C.,Pardal,M.,2006.Feedingecology,population

structureanddistributionofPomatoschistusmicrops (Krøyer,1838)andPomatoschistusminutus

(Pallas,1770)inatemperateestuary,Portugal.Estuarine,CoastalandShelfScience66,231‐239.



269–279.

Marshall,S.,Elliott,M.,1998.EnvironmentalinfluencesonthefishassemblageoftheHumberestuary,UK.


Martinho,F.,Leitão,R.,Neto,J.,Cabral,H.,Marques,J.C.,Pardal,M.A.,2007a.Theuseofnurseryareasby

juvenilefishinatemperateestuary,Portugal.Hydrobiologia587,281–290.

Martinho,F.,Leitão,R.,Viegas,I.,Neto,J.M.,Dolbeth,M.,Cabral,H.N.,Pardal,M.A.,2007b.Theinfluence



Martinho,F., Leitao,R.,Neto, J.M.,Cabral,H., Lagardère,F.,Pardal,M.A.,2008a.Estuarine colonization,




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abundanceofthefishfaunaofatemperatetidalmudflat.Estuarine,CoastalandShelfScience54,

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Hydrobiologia506,443‐449.

Pennington,M.,Vølstad, J.H.,1991.Optimum sizeof samplingunit forestimating thedensityofmarine

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151 |ChapterV

ChapterV

Assessingestuarineenvironmentalqualityusingfish‐basedindices:performance

evaluationunderclimaticinstability

Abstract

Theseasonalvariationof fiveselectedmultimetric indices forthedeterminationoftheEcologicalQualityStatus(EQS)oftransitionalwaterswasevaluated,aswellastheindices’responsestoanextremedroughtevent thatoccurred in2005.Thedatabaseused regards theMondego riverestuary,whichwas sampledfromJune2003toAugust2006onamonthlybasis.Amongtheselectedindices(EBI‐Deeganetal.(1997),EDI‐Borjaetal.(2004),EFCI‐HarrisonandWhitfield(2004),EBI‐Breineetal.(2007)andTFCI‐Coatesetal. (2007), the EBI by Breine et al. (2007) was the only that evidenced clear interanual and seasonalvariations. The EQS by the several indices ranged from “Poor” to “High”, depending on the indexconsidered,evidencingthehighlevelofmismatchbetweenindices.Theresultsarediscussedinthescopeof the EUWater Framework Directive, regardingmonitoring strategies, application of indices and EQSassessment.

Keywords

WaterFrameworkDirective ::Fish‐based indices ::EcologicalQualityStatus ::Ecological indicators ::Fishcommunity::MondegoEstuary


153 |ChapterV

Introduction

TheWaterFrameworkDirective(WFD,2000/60/EC)hassetanewapproachtothemanagement

andmonitoringofwaterresources,aimingtoachievea“Good”ecologicalstatusby2015 inall

Europeanwaterbodies(i.e.:Thevaluesofthebiologicalqualityelementsforthesurfacewater

body type should show low levels of distortion resulting from human activity, deviating only

slightly fromthosenormallyassociatedwithundisturbedconditions (Vincentetal.,2002).This

directive establishes a framework for the protection of groundwater, inland surface waters,

estuarine(=transitional)andcoastalwaters(Borjaetal.,2005),whosemainobjectivesare:(a)to

prevent furtherdeterioration, toprotectand toenhance the statusofwater resources; (b) to

promote sustainable water use; (c) to enhance protection and improvement of the aquatic

environment, through specific measures for the progressive reduction of discharges; (d) to

ensuretheprogressivereductionofpollutionofgroundwaterandprevent itsfurtherpollution;

and(e)tocontributetomitigatingtheeffectsoffloodsanddroughts.Accordingly,allEUmember

states are required to assess the Ecological Quality Status (EQS) of water bodies, and in

transitionalwaters (=estuaries) themeasurementofbiological integritywillbeemphasizedon

phytoplankton,macroalgae,benthosandfishes.

Transitionalwatersareofgreat importance for the fish fauna,playingavitalrolebyproviding

nurseryhabitats,reproductiongrounds,refugefrompredatorsandmigratoryroutes(Haedrich,

1983; Elliott andMcLusky, 2002; Cabral et al., 2007;Martinho et al., 2007a,b).Nevertheless,

thesesystemsarebeingsubjectedtohighenvironmentalpressureduetoanthropogenicforcing,

suchaseutrophication,overfishing,bankreclamationandgeneralenvironmentaldegradation.

Theuseoffishesasindicatorsofenvironmentalchangehasrecentlygainedattention(Whitfield

and Elliott, 2002), with several authors developingmultimetric tools in order to assess the

estuarineecosystemstatusforthefishcomponentatvariouslatitudes(ex:Deeganetal.,1997;

Borja et al., 2004; Harrison andWhitfield, 2004; Breine et al, 2007; Coates et al., 2007). In

addition,studiesofpopulationdynamics, food‐weborganizationandstructureofcommunities

have beenmore successful than single species bioassays atpredicting the effects ofmultiple


154 |ChapterV

stressesonbiologicalsystems(Schindler,1987;Plafkin,1989;Dolbethetal.,2007a).Theuseof

indicators provides the possibility to evaluate the fundamental condition of the environment

withouthaving to capture the full complexityof the system (Whitfield andElliott,2002),and

accordingtotheWFDguidance,theevaluationmethodsforthefishcomponentshouldtake in

accountbothaspectsofcompositionandabundanceoffishspecies.

Extreme climatic events, such as floods or droughts are increasing in frequency worldwide

(Mirza,2003),andasaconsequence,riverdischargeintomanyestuariesmaybeaffected(Gleick,

2003).IntheMondegoRiverbasin,aseveredroughtoccurredin2005,andwasclassifiedbythe

PortugueseWeatherInstitute(http://web.meteo.pt/clima/clima.jsp)astheworstdroughtofthe

past 60 years. As a result, the decreasing precipitation and runoff induced changes in the

estuary’splanktonicandfishcommunities,withanincreaseintypicalmarinespeciesduringthe

drought(Marquesetal.,2007;Martinhoetal.,2007b).SincetheimplementationoftheWFDby

EUmemberstateswillbeacontinuedprocess intime,tocopethevariousmethodologieswith

climate instability isakey issue for the successof suchanambitiousandpromisingdirective.

Withinthisframework,theobjectivesofthepresentworkweretocomparetheresultsobtained

by themethodologies developed by Deegan et al. (1997), Borja et al. (2004), Harrison and

Whitfield (2004), Breine et al. (2007) and Coates et al. (2007) for determining the Ecological

QualityStatusoftransitionalwatersusingfishdata,andtoevaluatetheirresponsesindifferent

climaticscenarios,namelyinthepresenceofanextremeevent(severedrought).

MaterialsandMethods

Studysite

TheMondegoestuaryisasmallintertidalsystem,locatedontheAtlanticcoastofPortugal(40º

08’N,8º50’W) (Fig.1),whereapproximately1072hacorrespond towetlandhabitats. In its

terminalpart,itcomprisestwoarmsthatjoinnearthemouth,separatedbyanalluvium‐formed

island(MurraceiraIsland).Thenorthernarmisdeeper(average10mduringhightide)andisthe

main navigation channel and the location of the commercial harbour. The southern arm is


155 |ChapterV

shallower(2–4mduringhightide)andwatercirculationismostlydependentonthetidesandon

the freshwater input from the Pranto River, a small tributary system. For further detailed

informationontheMondegoestuary’scharacteristicsseeTeixeiraetal.(2008).

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Figure1.GeographicallocationoftheMondegoestuaryandthefivesamplingstations(A‐E).

Samplingproceduresanddataacquisition

Fish sampling was performed monthly from June 2003 to August 2006 (except in July,

September,October,December2004andJuly2006,duetotechnicalconstraintsorbadweather

conditions),usinga2x0.5mbeamtrawlwithoneticklerchainand5mmmeshsizeinthecod

end. Sampleswere collectedduring thenight, athighwaterof spring tides and in5 stations

throughouttheestuary(Fig.1).Ateachstation,threetowswerecarriedout,coveringatleastan

area of 500m2 each. All fish caught were identified, counted,measured (total length) and


156 |ChapterV

weighted(wetweight).Bottomwatersalinityandtemperatureweremeasuredafterfishingtook

place.

Hydrologicaldatawasobtained from INAG–PortugueseWater Institute (http://snirh.inag.pt).

Monthly precipitation (from January 2002 to June 2006) and long‐term monthly average

precipitation(from1933to2006)wereobtainedfromtheSoure13F/01Gstation(locatednear

theestuary).FreshwaterrunoffwasacquiredfromINAGstationAçudePonteCoimbra12G/01A,

nearthecityofCoimbra(located40kmupstream).

Descriptionofthemultimetricindices

AvarietyofindiceshavebeenusedtoassesstheEcologicalQualityStatusofestuarinesystems.

In thepresentstudy, the resultsof fivemultimetric indicesand their responses toanextreme

drought event were evaluated: Estuarine Biotic Integrity Index (EBI) (Deegan et al., 1997),

EstuarineDemersal Indicators (EDI) (Borjaetal.,2004),EstuarineFishCommunity Index (EFCI)

(HarrisonandWhitfield,2004),Fish‐basedEstuarineBiotic Index (EBI) (Breineetal.,2007)and

theTransitionalFishClassification Index (TFCI) (Coatesetal.,2007).Allthemethodologiesand

respectivemetricsarebasedonpresence/absence,relativeproportionsandnumberoftaxaof

differentspeciesandfunctionalgroups.Unlikeinlargerestuaries(e.g.Breineetal.,2007;Coates

etal.,2007),theMondegoestuarywasnotdividedinsubareas,duetoitsrelativelysmallsize.

EstuarineBioticIntegrityIndex(EBI)(Deeganetal.,1997)

TheEstuarineBiotic Integrity Index(EBI)(Table1)wasdevelopedusingdatafromWaquoitBay

andvalidatedusingdatafromButtermilkBay,southernMassachusetts,USA.Eachmetrichasan

associatedscoreof0or5,andtheEBIrangesfrom0to40,beingcalculatedasthesumofscores

for eachmetric. Due to the inexistence of reference data, the authors only considered two

EcologicalQualityStatus (EQS):Medium (EBI≥25);Low (EBI<25).Although theEBIcanbeused

witheitherdensityorbiomassdata,inthepresentcaseonlydensitieswereused.Samplingwas

carriedoutusinga4.8mottertrawl(0.3cmmeshsizecodend).


157 |ChapterV

EstuarineDemersalIndicators(EDI)(Borjaetal.,2004)

TheEstuarineDemersal Indicators(Table2)weredevelopedfortheBasqueCountry,usingfish

andcrustaceansdataduetothesmallsizeoftheBasqueestuaries(inthepresentstudy,onlyfish

were considered). Each indicator/metric has an associated score of 1, 3 or 5. The sum of all

scores provides the final classification for the fish community, being then converted into the

Ecological Quality Ratio (EQR), which ranges from 0 to 1 with five equal thresholds, each

corresponding toanEcologicalQualityStatus (EQS):Bad (<0.2),Poor (0.2‐0.4),Moderate (0.4‐

0.6),Good,(0.6‐0.8)andHigh(0.8‐1.0).Thesamplingmethodwastrawling.

EstuarineFishCommunityIndex(EFCI)(HarrisonandWhitfield,2004)

TheEstuarineFishCommunityIndex(EFCI)(Table3)wasdevelopedforSouthAfricanestuaries.

Eachmetrichasanassociated scoreof0,3or5,and theEFCI iscalculatedas thesumof the

scores. The EFCI ranges from 0 to 70 with five thresholds: Very Poor (EFCI<20), Poor

(22≥EFCI≤38),Moderate(40≥EFCI≤44),Good(46≥EFCI≤62)andVeryGood(62≥EFCI≤70).Fishes

weresampledusinga30mx1.7mseine(15mmbarmeshsize)andafleetof10x1.7mgillnets

(45,75and100mmstretchedmeshpanels).

Fish‐basedEstuarineBioticIndex(EBI)(Breineetal.,2007)

TheFish‐basedEstuarineBiotic Index (EBI) (Table4)wasdeveloped for thebrackishsectionof

theScheldeRiverestuary.Eachmetrichasanassociatedscoreof0,0.25,0.5,0.75and1,andthe

EBIiscalculatedasthescores’averagevalue.Duetotheabsenceofreferencedata,theauthors

only defined the thresholds until Moderate status: Bad (EBI≤0.15), Poor (0.15>EBI≤0.30),

Moderate(EBI>0.30).However,andsincetheEBIrangesfrom0to1,itwasdecidedtodefinethe

remainingthresholds, inordertobettercomparetheresultswiththeothermethodologies,as

follows: Moderate (0.30>EBI≤0.55), Good (0.55>EBI≤0.80), High (EBI>0.80). Sampling was

performedusingapairoftwofyke‐nets(type120/80),deployedatlowtideandemptiedinthe

followingday.


158 |ChapterV

Table1.DescriptionoftheEstuarineBioticIntegrityIndex(EBI),afterDeeganetal.(1997).

Scores No. Metric

0 5

1 Numberofspecies(N) <6 ≥6

2 Dominance <3 ≥3

3 Fishabundance <3.8 ≥3.8

4 Nurseryspecies(N) <3 ≥3

5 Estuarinespawners(N) <3 ≥3

6 Residentspecies(N) <4 ≥4

7 Proportionbenthicfishes(%) <0.70 ≥0.70

8 Proportionabnormal(%) <0.01 ≥0.01

Table2.DescriptionoftheEstuarineDemersalIndicators(EDI),afterBorjaetal.(2004).

Scores No. Metric

1 3 5

1 Numberofspecies(N) <3 4‐9 >9

2 Pollutionindicatorspecies Presence Absence

3 Introducedspecies Presence Absence

4 Fishhealth(damage)(%affection) >50 5‐49 <5

5 Flatfishpresence(%) <5 5‐10or<60 10‐60

6 Abundanceofomnivorousspecies(%) <1or>80 1‐2.5or20‐80 2.5‐20

7 Abundanceofpiscivorousspecies(%) <5or>80 5‐10or50‐80 10‐50

8 Estuarineresidentspecies(N) <2 2‐5 >5

9 Abundanceofresidentspecies(%) <5or>50 5‐10or40‐50 10‐40


159 |ChapterV

Table 3. Description of the Estuarine Fish Community Index (EFCI), after Harrison andWhitfield(2004).

Scores No. Metric

1 3 5

1 Numberofspecies(N) ≥22 <22and≥12 <12

2 Rareorthreatenedspecies Presence Absence

3 Exoticorintroducedspecies Absence Presence

4 Speciescomposition(%similarity) ≥80 <80and≥50 <50

5 Speciesrelativeabundance(%similarity) ≥60 <60and≥40 <40

6 Speciesthatmakeup90%oftheabundance(N) ≥8 <8and≥4 <4

7 Estuarineresidentspecies(N) ≥5 <5and≥3 <3

8 Estuarine‐dependentmarinespecies(N) ≥14 <14and≥8 <8

9 Abundanceofestuarineresidentspecies(%) 25–75≥10and<25or

>75and≤90<10or>90

10 Abundanceofestuarine‐dependentmarinespecies(%) 25–75≥10and<25or

>75and≤90<10or>90

11 Benthicinvertebratefeedingspecies(N) ≥7 <7and≥4 <4

12 Piscivorousspecies(N) ≥3 <3and≥2 <2

13 Abundanceofbenthicinvertebratefeedingspecies(%) ≥10 <10and≥5 <5

14 Abundanceofpiscivorousspecies(%) ≥1 <1and≥0.5 <0.5

Table4.DescriptionoftheFish‐basedEstuarineBioticIndex(EBI),afterBreineetal.(2007).

Scores No. Metric

0 0.25 0.5 0.75 1

1 Numberofspecies(N) ≤7 >7 >9 >10 >11

2 Osmeruseperlanusindividuals(%) ≤0.33 >0.33 >1.12 >2.68

3 Marinejuvenilemigratingindividuals(%) ≤33.0 >33.0 >54.2 >73.1 >82.0

4 Omnivorousspecies(%) ≥16.44 <16.44 <7.90 <3.37 <1.17

5 Piscivorousspecies(%) ≤12.84 >12.84 >19.44 >27.23 >41.19


160 |ChapterV

TransitionalFishClassificationIndex(TFCI)(Coatesetal.,2007)

TheTransitional FishClassification Index (TFCI) (Table5)wasdeveloped for theThamesRiver

estuary, and compared to a reference estuarine fish community, derived from a number of

estuariesofthesametypologyastheThames.Eachmetrichasanassociatedscoreof1,2,3,4,

or5,andtheTFCIiscalculatedasthetotalscoreforeachsamplingdatedividedbythemaximum

possiblescore.TheEQS thresholdsare thesameas in themethodologybyBorjaetal. (2004).

Samplingwascarriedoutbasedonamulti‐methodapproach:intheuppertomidestuarya45x

3.5m seinenetwitha5mmknotlessmeshcentreand20mmwingswasdeployed from the

shore;a1.52mwidebeamtrawlwitha20mmknotlessoutermeshand5mmknotlesscodend

wastrawledfor250mparalleltotheseiningsite; inthemidand lowerestuarywerealsoused

paired8mwideotter trawlswitha40mmoutermeshwitha5mmknotless ‘codend’mesh

(Coatesetal.,2007).Accordingtotheauthors,andfortheTFCIonly,themeannumberoftaxa

within theupperquintile (top20%)wasdeterminedandusedas theboundaryvaluebetween

RS4andRS5.Percentagesof thisvaluewereused tocalculate theboundaries foreachmetric

(seeTable5).

Referencedata

Anidealreferencecommunityisderivedfromthesamesiteatthesametimeofyearusingthe

samemethods,duringaperiodwhentheenvironmentispristineandnoanthropogenicchanges

haveoccurred (Coates et al., 2007). Since referencedatawasnot available for theMondego

estuary(oranyotherPortugueseA2typeestuary‐Mesotidalwell‐mixedestuarieswithirregular

riverdischarge;Bettencourtetal.,2004) touse in theEstuarine FishCommunity Index (EFCI)

(HarrisonandWhitfield,2004)and intheTransitionalFishClassification Index (TFCI)(Coateset

al.,2007), itwasdeterminedthattheaveragedensitiesfromJune2003toMay2004wouldbe

usedasreference,sinceitwastheperiodwhenenvironmentalconditions(namelyprecipitation

and freshwater runoff)werewithin regularvalues.Thisdecisionwas taken inaccordancewith

Martinhoetal. (2007b),whooutlinedthatthefishcommunity issensitive (tosomedegree)to


161 |ChapterV

variationsinprecipitationandfreshwaterrunoffregimes.

Table5.Descriptionof theTransitional FishClassification Index (TFCI),afterCoatesetal.(2007) (Metrics 4, 5, 6, 8 and 9 scores defined according to theMondego estuary fishcommunity).

Scores No. Metric

1 2 3 4 5

1 Speciescomposition(%similarity) <19.9 20‐39.9 40‐59.9 6‐79.9 80‐100

2 PresenceofIndicatorSpecies Presence

3 Speciesrelativeabundance(%similarity) <19.9 20‐39.9 40‐59.9 6‐79.9 80‐100

4 Taxathatmakeup90%oftheabundance(N) <0.6 0.6‐1.19 1.2‐1.79 1.8‐2.39 ≥2.4

5 Estuarineresidentspecies(N) <0.6 0.6‐1.19 1.2‐1.79 1.8‐2.39 ≥2.4

6 Estuarine‐dependentmarinespecies(N) <0.6 0.6‐1.19 1.2‐1.79 1.8‐2.39 ≥2.4

7 Functionalguildcomposition(N) 0‐1 2 3

8 Benthicinvertebratefeedingspecies(N) <0.6 0.6‐1.19 1.2‐1.79 1.8‐2.39 ≥2.4

9 Piscivorousspecies(N) <0.6 0.6‐1.19 1.2‐1.79 1.8‐2.39 ≥2.4

10 FeedingGuildComposition(N) 0 1 2 3 4

Dataanalysis

The structure of the fish communitywas analyzed based on Ecological Guilds, derived from

habitatusagepatterns (adapted from Elliott andDewailly,1995):marine adventitious species

(MA),marine juvenilemigrantspecies (MJ;occurringusually in lowdensities inestuariesasan

alternativehabitat),marine species thatuse theestuaryasnurserygrounds (NU;occurring in

clear seasonalpatterns,higherdensitiesand remaining longerperiods inestuaries),estuarine

resident species (ER), catadromous adventitious species (CA) (no anadromous species were

found) and freshwater adventitious species (FW), and FeedingGuilds: planktivorous (PLANK),

benthicinvertebratefeeders(INVV),piscivorous(PISV),omnivorous(OMN)(adaptedfromElliott

andDewailly,1995,Breineetal.,2007andCoatesetal.,2007).Fishdensitieswereestimatedas

thenumberof individualsper1000m2.Wheneverneeded,datawastransformedaccordingto


162 |ChapterV

theproceduresproposedbyeachindex.

Results from the indices were compared based on Kendall’s coefficient of correlation. This

correlationcoefficientvariesbetween‐1(totaldisagreement)and1(perfectagreement),andif

the correlation equals zero, the rankings are completely independent. Differences between

seasonal results were tested with an ANOVA and Tukey‐type a posteriori tests were used

whenever thenullhypotheseswere rejected.Asignificance levelof0.05wasconsidered inall

testprocedures.

Results


Withinthestudyperiod,aseveredroughtoccurred in2004/2005,withassociatedreduction in

precipitation and freshwater runoff (Fig. 2A). In fact, only in 2003/2004 was recorded

precipitation values above the 1931‐2006 average, and freshwater runoff to the estuarywas

reducedalmost10‐foldfromthehighestvaluein2003tothelowestvaluein2005.Accordingto

the PortugueseWeather Institute (http://web.meteo.pt/pt/clima/clima.jsp), the 2005 drought

wastheharshestsince1931.

Temperatureshowedatypicalpatternfortemperatelatitudes,rangingfrom8.8±1.7to22.7±2.6

ºC,while salinity showed a clear increase during the drought (Fig. 2B). For further detailed

information on the drought conditions and itsmain effects on estuarine planktonic and fish

communitiesseeDolbethetal.(2007b),Marquesetal.(2007)andMartinhoetal.(2007b).

Estuarinefishcommunity

TheMondegoestuaryfishcommunitywasstudiedfromJune2003toAugust2006onamonthly

basis,beingsofaridentified42species,belongingto23Families(Leitãoetal.,2007;Martinhoet

al.,2007a,b)(Table6).Asageneralpattern,thefishcommunitywasdominatedbytheestuarine

residents(ER)PomatoschistusmicropsandPomatoschistusminutus,themarinespeciesthatuse

theestuaryasnurseryarea(NU)Dicentrarchuslabrax,SoleasoleaandPlatichthysflesus,andthe


163 |ChapterV

marine juvenile (MJ)Diplodus vulgaris. Freshwateradventitious species (FW) (Barbusbocagei,

Carassius auratus andGambusia holbrooki)were only occasionally caught until thewinter of

2004,andmarineadventitiousspecies (MA)suchasArnoglossus laterna,Buglossidium luteum,

Gaidropsarus mediterraneus, Solea lascaris and Symphodus bailloni only appeared after the

summer of 2004. In fact, A. laterna, B. luteum, S. lascaris and Trisopterus luscuswere only

capturedinsidetheestuaryin2005.

0

150000

300000

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l-0

5

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Salinity Temperature

Sa

linity

/Te

mp

era

ture

(ºC

)W

ate

rru

no

ff(d

am

)3 P

recip

itatio

n(m

m)

A

B

Figure 2.Monthly variation of precipitation (mm) and freshwater runoff (dam3) (A) andaverage temperature (ºC) and salinity (B) from June 2003 to August 2006. Dashed lineindicatestheaveragevalueoffreshwaterrunofffortheperiod1933‐2006.


164 |ChapterV

Regardingthetotalnumberofspecies (Fig3A),throughoutthestudyperiodwerecapturedan

averageof15 (±3)permonth; thehighest speciesnumberwas collected in January2005 (22

spp).Totalfishdensities(Fig.3B)werehigherinthebeginningofthestudy(~140ind.1000m‐2),

withanaveragevalueof27.4±25.1ind.1000m‐2throughoutthestudyperiod.Noclearseasonal

patternswereidentifiedbothforthenumberofspeciesandtotaldensities.

0.00

20.00

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Tota

ldensitie

sIn

d.1000m

2S

pecie

snum

ber

A

B

Figure3.Monthlyvariationofthenumberofspecies(A)andtotaldensities(N.Ind.1000m‐2)(B)ofthefishcommunityoftheMondegoestuaryduringthestudyperiod.


165 |ChapterV

Ecologicalquality:metricsresults

ThemonthlyevaluationbytheEstuarineBioticIntegrityIndex(EBI)isshowninFig.4A.Theindex

exhibitedaconstantvalueoverthestudyperiod,correspondingtoaMediumEcologicalQuality

Status(EQS).TheexceptionwasDecember2005, inwhichthe indexpresentedaLowEQS.The

EstuarineDemersalIndicators(EDI)proposedbyBorjaetal.(2004)(Fig.4B)classifiedingeneral

asGoodstatus,withthehighestamplitudeofvaluesduringthedroughtperiod:inMay2005,the

EDIclassifiedasModeratestatusandinAugust2005asHighstatus.InMay2006,thelowestEQR

wasobtained(0.44–Moderate)andinthewinterof2004thisindexclassifiedasHighstatus.

Although quite constant, the Estuarine Fish Community Index (EFCI) (Harrison andWhitfield,

2004)(Fig.4C)showedaslightdecreasingtendencyregardingtheEQSoftheMondegoestuary.

As a general pattern, this index classified as Good status from 2003 to 2005 (with few

exceptions),while all 2006was classified asModerate status. The Fish‐based EstuarineBiotic

Index (EBI) (Breineetal.,2007)wastheonly indexthatevidencedacleardecrease intheEQS

(Fig.4D),particularlyduringthedroughtperiod(frommid‐2004to2005).Asaresult,during2003

a Good statuswas obtained,while in 2004/2005 the values decreased and the estuarywas

classified inModerateandPoorstatus. In2006,the indexvalues increased,andaGoodstatus

was obtained in the end of the study period. Figure 4E reports the classification of the EQS

according to the Transitional Fish Classification Index (TFCI) (Coates et al., 2007). This index

evidenced the highest and more constant results, classifying as High status almost all the

samplingsituations,withtheexceptionofAugust2004,December2005andJune2006.

ComparisonofIndices

Table7shows the resultsof theKendall tau rankcorrelationcoefficientbetween theselected

indices (p<0.05). Significantpositive correlationswere foundbetweenBorja et al. (2004) and

Breineetal.(2007)(T=0.41),Coatesetal.(2007)andBreineetal.(2007)(T=0.31),Harrisonand

Whitfield(2004)andCoatesetal.(2007)(T=0.64);theonlysignificantnegativecorrelationwas

foundbetweenDeeganetal.(1997)andBorjaetal.(2004)(T=‐0.30).


166 |ChapterV

Table 6. Species list of the Mondego Estuary fish community, with respective Family,EcologicalGuild,FeedingFuild,Indicatorstatusandaveragedensity(numberof individualsper1000m2)trhoughoutthestudyperiod;CA–catadromous;ER–estuarineresident;MA–marine adventitious; FW – freshwater; MJ – marine juvenile; NU – nursery; PLANK –planktivorous;INVV–benthicinvertebratefeeder;PISV–piscivorous;OMN–omnivorous.

Species FamilyEcological

Guild

Feeding

Guild

Indicator

Species

Average

Nind.1000m‐2

Ammodytestobianus Ammodytidae MA PLANK N 0.115±0.33

Anguillaanguilla Anguillidae CA INVV/OMN Y 0.614±0.93

Aphiaminuta Gobiidae MA PLANK N 0.060±0.22

Arnoglossuslaterna Scophthalmidae MA PISV N 0.015±0.05

Atherinaboyeri Atherinidae ER PLANK/OMN N 0.768±1.27

Atherinapresbyter Atherinidae ER INVV/OMN N 0.096±0.21

Barbusbocagei Cyprinidae FW INVV/OMN N 0.007±0.04

Buglossidiumluteum Soleidae MA INVV N 0.003±0.02

Callionymuslyra Callionymidae MA INVV/OMN N 0.143±0.26

Carassiusauratus Cyprinidae FW INVV/OMN Y 0.002±0.01

Chelonlabrosus Mugilidae MJ DETR/OMN N 0.009±0.04

Ciliatamustela Gadidae MJ INVV N 0.126±0.21

Congerconger Congridae MA PISV N 0.018±0.04

Dicentrarchuslabrax Moronidae NU PISV N 7.540±7.82

Dicologlossahexophthalma Soleidae MJ INVV/OMN N 0.002±0.01

Diplodusvulgaris Sparidae MJ INVV/OMN N 1.394±1.81

Echiichthysvipera Trachinidae MA INVV/OMN N 0.026±0,07

Engraulisencrasicolus Engraulidae MA PLANK/OMN N 0.050±0.16

Gaidropsarusmediterraneus Gadidae MA INVV N 0.002±0.01

Gambusiaholbrooki Poeciliidae FW INVV/OMN N 0.011±0.06

Gobiusniger Gobiidae ER INVV N 0.121±0.14

Lizaaurata Mugilidae MJ DETR/OMN N 0.014±0.04


167 |ChapterV

Table6(cont.).SpecieslistoftheMondegoEstuaryfishcommunity,withrespectiveFamily,EcologicalGuild,FeedingFuild,Indicatorstatusandaveragedensity(numberof individualsper1000m2)trhoughoutthestudyperiod;CA–catadromous;ER–estuarineresident;MA–marine adventitious; FW – freshwater; MJ – marine juvenile; NU – nursery; PLANK –planktivorous;INVV–benthicinvertebratefeeder;PISV–piscivorous;OMN–omnivorous.

Species FamilyEcological

Guild

Feeding

Guild

Indicator

Species

Average

Nind.1000m‐2

Lizaramada Mugilidae CA DETR/OMN N 0.242±0.57

Mugilcephalus Mugilidae MJ DETR/OMN N 0.005±0.02

Mullussurmuletus Mullidae MJ INVV N 0.106±0.17

Nerophislumbriciformis Syngnathidae ER INVV N 0.008±0.05

Parablenniusgattorugine Blenniidae MA INVV N 0.003±0.02

Platichthysflesus Pleuronectidae NU INVV N 1.473±1.63

Pomatoschistusmicrops Gobiidae ER INVV N 8.061±11.41

Pomatoschistusminutus Gobiidae ER INVV N 3.623±5.96

Sardinapilchardus Clupeidae MJ PLANK N 0.267±1.08

Scophthalmusrhombus Scophthalmidae MJ PISV N 0.053±0.08

Solealascaris Soleidae MA INVV N 0.024±0.07

Soleasenegalensis Soleidae MJ INVV N 0.096±0.15

Soleasolea Soleidae NU INVV N 1.621±1.42

Sparusaurata Sparidae MJ INVV/OMN N 0.019±0.04

Spondyliosomacantharus Sparidae MA INVV/OMN N 0.018±0.06

Symphodusbailloni Labridae MA INVV/OMN N 0.053±0.12

Syngnathusabaster Syngnathidae ER INVV/OMN N 0.161±0.25

Syngnathusacus Syngnathidae ER INVV N 0.251±0.52

Triglalucerna Triglidae MJ PISV N 0.117±0.25

Trisopterusluscus Gadidae MA INVV/OMN N 0.099±0.24

Theconformitybetweenthemethodstestedwasingenerallow(Table7),astherelativenumber

of caseswhenone index classifieda samplingoccasionas “High”or “Good”and theotheras

“Moderate”, “Poor”or “Bad” (mismatch)washigh. The lowestmismatch valuewasobtained

betweentheindicesbyBorjaetal.(2004)andCoatesetal.(2007)(6%).Concerningtheseasonal


168 |ChapterV

variationoftheecologicalstatusofthesystem,onlytheEBI(Breineetal.2007)foundsignificant

seasonaldifferences(F=0.982;p<0.05),andinparticular,betweentheAutumn2003andAutumn

2004(q=0.04;p<0.05)andbetweentheWinter2004andWinter2005(q=0.048;p<0.05).Forthe

otherindices,nosignificantseasonalvariationswerefound.

Discussion

AssessingtheEQSanditsrelationwithdroughtevents

Anecologicallyparsimoniousapproachdictatesthatinvestigatorsshouldplacegreateremphasis

onevaluatingthesuitabilityofindicesthatalreadyexistpriortodevelopingnewones(Diazetal.,

2004).Inagreement,thisworkaimedatevaluatingtheperformanceoffiveselectedmultimetric

indices to assess the EcologicalQuality Statusof transitionalwatersusing fishdata and their

response toanextremedroughtevent thatoccurred in2005.Testingof indices isanexercise

aimingnotonlytoselectthebestappropriateindexforeachcase,butalsotoassurethatresults

arecomparableamongtwoormoreindices(SimbouraandReizopulou,2008).Oneofthemajor

concerns when undertaking this exercise was the lack of publications in this subject, in

opposition with the benthic component of transitional waters, which has generated a large

debateandaccordingly,severalmultimetricindicesarebeingtestedbyEuropeanmemberstates

(e.g.AMBI ‐Borjaetal.,2000;BENTIX ‐ SimbouraandZenetos,2002;BQI ‐Rosenbergetal.,

2004).

In general, all tested methodologies gave constant results throughout the study period,

particularlythe indicesproposedbyHarrisonandWhitfield(2004)andCoatesetal.(2007)(the

metricswith thehighestcorrelationvaluesbetween them).Thiswouldbeexpected,since the

metricbyCoatesetal.(2007)isanadaptationoftheSouthAfricanindexdevelopedbyHarrison

andWhitfield(2004)toEuropeantransitionalwaters,particularlytotheThamesRiver.


169 |ChapterV

A

B

C

D

E

EQ

RE

QR

EQ

RE

QR

EQ

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Figure4.Classification resultsof the selected indices (EQR)and correspondentEcologicalqualitystatus (EQS): (A)EBI ‐Deeganetal. (1997), (B)EDI–Borjaetal. (2004), (C)EFCI–HarrisonandWhitfield(2004),(D)EBI–Breineetal.(2007),(E)TFCI–Coatesetal.(2007).


170 |ChapterV

In theparticular caseof theworkdue toCoateset al. (2007), the systemwas almost always

classifiedasHighstatus,possiblyduetothetypeofdatausedasreferencecondition (thefirst

yearofthestudy).ThiswillbeacommonissueinimplementingtheWFD,sincequalityreference

datawillnotbeavailable formostestuaries,thusbecomingan importantsourceofbiaswhen

determiningtheEQS.Intermsofstatusclassification,theindicesproposedbyBorjaetal.(2004)

andCoatesetal.(2007)classifiedtheestuarywiththehigheststatus,evidencingthelowestlevel

ofmismatchamongalltheindicestested(Table7).

Table7.Kendalltaurankcorrelationcoefficientbetweenthetestedindicesandconformitybetween thedifferentmethods,givenby thepercentageofmismatch (relativenumberofcases inwhichoneofthemethodsclassifiedasamplingoccasionas“High”or“Good”andtheotheras“Moderate”,“Poor”or“Bad”(afterBorjaetal.,2007).*aresignificantvaluesforp<0.05.

EBI

Deeganetal.

(1997)

EDI

Borjaetal.

(2004)

EFCI

Harrisonand

Whitfield(2004)

EBI

Breineetal.

(2007)

TFCI

Coatesetal.

(2007)

EBI

Deeganetal.(1997) ‐ 91.18% 73.53% 41.18% 97.06%

EDI

Borjaetal.(2004) ‐0.30* ‐ 23.53% 55.88% 5.88%

EFCI

Harrisonand

Whitfield(2004)

0.21 ‐0.01 ‐ 44.12% 23.53%

EBI

Breineetal.(2007) ‐0.23 0.41* 0.22 ‐ 61.76%

TFCI

Coatesetal.(2007) 0.09 0.06 0.64* 0.31* ‐


171 |ChapterV

The only index that presented clear interannual and seasonal variations between year

fluctuationswastheEBIbyBreineetal.(2007),whichcouldbetheresultoftwoaspects:a)the

elimination of the metric correspondent to the abundance of O. eperlanus (due to the

inexistenceofthisspeciesinPortugueseandsouthernEuropeanwaters,sincethesouthernlimit

ofdistribution is theGirondeestuary,France (RochardandElie,1994)andb) this is the index

thathasthe lowestnumberofmetrics (4)withinthe indicescompared inthisstudy.Thus,the

useofa largernumberofmetricsseemsmoreadequateforthefishcomponentoftransitional

waters (acting as a buffer) and also the use of metrics based on single species should be

discouraged,sincethereisasmallnumberofspeciesthatcouldbeconsideredasindicatorand

presentinallEuropeanestuaries.Thedisadvantageofrelyingononesinglespecieshadalready

beenstatedbyBreineetal.(2007).

When comparing the classification status of all indices for the same period, considerable

variationsexisted (Fig.4).Thediverseornotconsistentresponsesof thedifferent indicesmay

lead todoubt inmanagers’minds regarding thevalueof themethods (Quintinoetal.,2006).

According to the same authors, the outcome of the use of the indicators has a financial

dimension, such thatareasmisclassifiedasbeing in ‘‘Poor status’’will then requireexpensive

remediationmeasures.Thiswasquiteevidentwhenanalyzing the levelofmismatchbetween

the indices tested, induced by the different background of samplingmethods, geographical

areas, seasons,pressuresanddeterminationofmetricsand thresholds for theEQS ranges. In

particular,theindexbyDeeganetal.(1997)gaveconsistentlythelowestresults,possiblydueto

thedeterminationofonly the thresholdsbetween “Low” and “Medium” status. Itwould also

havebeen thecaseof theEBIbyBreineetal. (2007),since referenceconditionscouldnotbe

attainedandtheboundariesbetweenthehigheststatusescouldnotbedefined.However,the

useofquintilemethodsandtheEQSscalefrom0to1alloweddefiningthethresholdsbetween

“Moderate”and“Good”andbetween“Good”and“High”statuses.

Oneoftheaspectshighlightedbythisworkwastheseasonalconstancyoftheindices(exceptin

theEBI),evidencingthatthechangesinducedbythedroughtinthefishcommunity,namelythe


172 |ChapterV

increase inmarine adventitious species and a decrease of the estuarine residents,mainly P.

minutus(Dolbethetal.,2007b;Martinhoetal.,2007b)werenotreflectedatotherguild levels,

which are themain components of the indices tested. A characteristic of a good ecological

indicatoristhatitshouldreflectchangesintheecosystem,whiletakingintoaccountthenatural

variabilityinherentofnaturalprocesses,inagreementwiththeEstuarineQualityParadox(Elliott

andQuintino,2007),whichwasverified forall indicesexcept for theEBI (Breineetal.,2007).

Thus, it is recommended that this last index should be usedwith cautiously, considering the

Mondegoestuaryfishdatabase.

Samplingmethodologies

Oneofthemainproblems inapplyingandcomparingtheselected indices isthediscrepancy in

samplingmethodologies,which included gillnetting, beam and otter trawling, deployment of

fyke and seine nets, allwith different efficiencies, catch rates and sampling efforts. An ideal

approach for the implementation of theWFDwould be amulti‐method sampling regime, in

agreementwithCoatesetal.(2007),sincetheparticularlimitationsofonesamplinggearwould

be surpassed by other. This, however,would have high costs implicated for the EUMember

States,intermsofsamplinggearsandfacilities,humanandtimeresources.

InthespecificcaseoftheMondegoestuary,Leitãoetal.(2007)foundthatottertrawlsamples

didnotcollectasmanyspeciesasbeamtrawlsamples,duetorestrictionsinoperatingtheotter

trawl imposedby the lowerdepthsof theupstreamareas.Also, thebeam trawl isoneof the

mostextensivelymethodsusedforscientificsamplingofestuarinefishassemblages(Hemingway

andElliott,2002),beingpossible toestimate theareacoveredbyeach trawl, inopposition to

seinenets.However,andaccordingtoCoatesetal.(2007),thebeamtrawl is likelytoproduce

sampleswithlowerrelativescoresthantheseinenetandottertrawlbecauseittargetsbenthic

fish communities, since it is amuchmore discriminative technique than the othermethods,

capturing lower speciesdiversity. In spiteof the samplingmethodused (or a combinationof

more), itshouldbestandardizedtheunits inwhichdata isconverted(e.g.catchperuniteffort


173 |ChapterV

(CPUE),numberofindividualsperunitarea),enablingtotestandcomparedifferentmethodsin

thefuture.

Definitionofguilds

An important component of fish‐based indices are the functional guild analysis and

classifications.Nonetheless,andduetodifferentclassificationschemes,somevariationoccurred

between indices,with some speciesbeingdifferently classified in the variousapproachesand

others not assigned to particular guilds. This could be corrected by building an European

database of fish species allocated to respective functional guilds (ecological, feeding, vertical

preferences,amongothers),usingtherecentlyreviewedandgenerallyacceptedconceptsofthe

guildapproachforcategorizingfishassemblagesbyElliottetal.(2007).

Also, it is known that some species can have ontogenic variations atdifferent latitudes, thus

being included indifferentguilds,whichshouldbetakenintoaccount.Asanexample,flounder

(P. flesus) is classified as a resident species in the UK (Elliott and Dewailly, 1995), while in

southernEuropeisclassifiedasspeciesthatusesestuariesasnurseryareas(Leitãoetal.,2007;

Martinhoetal.,2007a).Thus,itisrecommendedthatastandardizedguildapproachshouldtake

place,reducingthevariabilitybetween indicesandaccordingtoElliottetal. (2007),presenting

anopportunitytocompareandcontrastestuarineandothertransitionalhabitatsworldwide.

Monitoring

According to theWFDguidance, theminimalmonitoring frequency for the fish componentof

transitionalwatersshouldbeonceeverythreeyears,whichmayhavelittlebiologicalrelevance,

being probably inconsistent in terms of natural spatial and temporal variability,management

actionsordecisionmaking(deJongeetal.,2006).Inagreement,anddespitethatthemajorityof

the selectedmethodologies showed a good tolerance to the changes inducedby an extreme

droughtevent,suchalongtimeperiodwillprobablymissimportanteventsthatcantakeplacein

thehighlyvariableestuarineenvironment(suchassuddenpollutionandeutrophication,disease


174 |ChapterV

outbreaksorevenasynergisticeffectofextremeclimaticepisodes).Forthefishcomponent,and

sincenosignificantvariationswere foundbetweenseasons,theminimalmonitoring frequency

shouldbereducedtoonceeveryyear.ThechallengingaspectoftheWFDisitsholisticapproach

(deJongeetal.,2006),byassessingtheriverbasinasawhole(ecosystem‐basedmanagement);

thus,thebiologicalandchemicalelementsthatarebeingusedtoassesstheEcologicalQuality

Statusofwaterbodiesshouldideallyhaveshorterminimalmonitoringfrequencies(whichwould

certainlyalsoimplyahighereffortbytheEUmemberstatesintermsofbudget,timeandhuman

resources).

Conclusions

Asamainconclusionitcanbestatedthatdespitesomevariation,alltheindicesgaveconsistent

results throughout the study period. However, the ones that seem more adequate for an

immediateapplicationandassessmentoftheEQSarethe indicesbyBorjaetal. (2004)andby

Coates et al. (2007), given the available dataset for theMondego estuary. Since there is no

referencedataavailable,theindexbyBorjaetal.(2004),withafewmodifications,adjustingitto

alargersizeofestuaries,sinceitwasbuiltforsmallsizedestuaries(Borjaetal.,2004),istheone

thatcancouldbe readilyusedandvalidated.Oneof themodifications thatwouldenable this

index to be used in a broader scalewould be changing the number of species in themetric

concerningthetotalnumberofspeciestoapercentageofthemaximumnumberofspeciesever

caughtinagivenestuary,sincethenumberofspeciesintheBasqueestuaries(fish+crustaceans

orfishonly)isquitelow,whencomparedtoothertransitionalwaters.

Nevertheless,thehighlevelofmismatchbetweentheselectedindicesindicatesthatthereisstill

a great amountofwork tobe done in the intercalibrationprocess, and concurrently, further

comparisons of different indices for the fish component of transitional waters throughout

Europeanmember states should be encouraged, in order to test their responses in different

water body typologies, time series, sampling methods and designs. Furthermore, the


175 |ChapterV

determinationoftheEQSintransitionalwatersusingfishdatawillbeachallengingtask,dueto

thehighmobilityoffishspecies,coupledwiththeunstableenvironmentthatcharacterizes

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179|GeneralDiscussion

GeneralDiscussion

Inthissection,anintegrativeapproachonthevarioustopicsdealtwithinthepreviouschapters

will be addressed, by summarizing and discussing the use of estuarine fish assemblages as

indicators of environmental changes, as well as themajor implications of extreme weather

events,suchasdroughts.Duringthestudyperiod,anextremedroughtoccurredthroughoutthe

Portugueseterritory,providinganaturalcasestudytoascertaininmoredetailtheprocessesand

relationshipsbetween fishand thesurroundingestuarineenvironment.According toWhitfield

and Elliott (2002), the measurement of any ecological response by a fish community, or

individual specieswithin a community,must take cognisance on the key role played by the

physico‐chemicalenvironmentininfluencingthestructureandfunctioningofthatestuary.Thus,

thestudyoftheestuarinefishassemblagewasperformedattwolevels:assemblage,byfocusing

on variations in structure and composition of functional guilds and in the ecological quality

status,andspecificfunctionalguilds,namelythemarinespeciesthatusetheestuaryasanursery

area, by concentrating on aspects relatedwith recruitment levels, interannual variability and

abundancepatterns.

Estuarinefishassemblages:structureandcomposition

Thefirstobjectiveofthisthesiswastodetermine ifthestructureandcompositionofestuarine

fishassemblageswasinfluencedbydroughtevents.Infact,severaldifferenceswerefoundinthe

estuarine use guilds composing theMondego estuary fish assemblage during the dry period.

Particularly, the fish belonging to the species that usemarginal estuarine areas, such as the

marine and freshwater stragglers, experienced one of the most significant changes, by an

increase and decrease, respectively, of the number of species and abundance. Changes in

freshwater regimes due to droughts, and consequent higher salinity intrusion in the upper

reachesofestuarinewaters, leadtoanupstreamdisplacementofsuitablehabitats (Kimmerer,

2002,Fernández‐Delgadoetal.,2007),havingapotentialimpactonthedistributionoffishand

planktonicspecies(e.g.AttrillandPower,2000;Marquesetal.,2007;Martinhoetal.,2007).As



for the estuarine resident and marine‐estuarine dependent species, which composed the

majority of the fish community, a decrease in abundance and productionwas also observed

during the dry period (Dolbeth et al., 2008). Seasonal abundance peaks,mainly due to the

recruitmentpatternsof the speciesbelonging to thepreviousecologicalguildsweregenerally

observed,asnotedelsewhere(McLuskyandElliott,2004;SelleslaghandAmara,2008).

Trends in species composition related with variations in river flow have been reported for

estuarinesystemsworldwide(e.g.Garciaetal.,2001;Ecoutinetal.,2005;Chícharoetal.,2006;

Costaetal.,2007;Henderson,2007;SelleslaghandAmara,2008),withthecommonpatternof

an increase in marine species during dry periods. Accordingly, a similar response was also

observed for the flatfish community,with themain changes in the structureand composition

beinginducedbydifferentriverflowregimes.Infact,oneofthemainimpactsofdroughtevents

is the reduction in seasonality, as observed by Potter et al. (1986) and Cuesta et al. (2006),

essentiallyinwhatprecipitationandriverflowisconcerned.Thepatternofoccurrenceofhigher

speciesnumberandabundanceofmarinestragglersduringdryyears,asreportedelsewhere,can

pointtoachangeinestuarinefoodwebsandpredator‐preyinteractions(AttrillandPower,2000;

Dolbethetal.,2008),withsignificantimpactsforlocalfishandinvertebrateassemblagesandfor

theecosystemfunctioning.

However, given the difficulty in distinguishing the effects of river flow from those of other

environmental variables (Costa et al., 2007), it is possible that the changes reported can be

maskedbyotherfactors,suchastemperature.Infact,temperatureisanotherimportantfactor

structuring estuarine fish assemblages (Attrill and Power, 2002;Henderson, 2007),being also

responsible forspecificpatterns,suchasspawningmigration (Simsetal.,2004),eggmortality

(vonWesternhagen,1970),growth (Amaraetal.,2009)orsmall‐scaledistributions (Vinagreet

al., 2009). Accordingly, temperature may have had an important contribution: during the

drought,theflatfishspecieswhosedistributionrangeincludehigherlatitudesweretheoneswith

a more distinct decrease in abundance, which can be related with an increase in water

temperatureandalso toahigher summer temperaturedifferentialbetweenestuarinewaters



andthesurroundingcoastalarea.AsimilarhypothesishasalsobeenraisedbyAttrillandPower

(2004), stating that the temperaturedifferentialbetweenestuarineandmarinewatersallows

fish tooptionallyexploitoptimal thermalhabitats.Becausemost fish species tend toprefera

specifictemperaturerange (Coutant1977;Scott1982), long‐termchanges intemperaturemay

lead toexpansionorcontractionof theirdistribution range.Thesechangesaregenerallymost

evidentnear thenorthernor southernboundariesof the species range;warming results in a

geographicshiftnorthwardandcoolingdrawsspeciessouthward(Ottersenetal.,2004).

Thebestevidenceof theeffectsofclimatechange inmarineecosystemscomes, in fact, from

distributionalshiftsinmarineorganisms,moreevidentnearthenorthernorsouthernboundaries

of theirdistributionranges (Drinkwateretal.,2009).Moreover,Henderson (2007)pointedout

that a change towarmwater communities occurred due to an increase in SST in the Bristol

Channel (UK).Thismayalsohaveoccurred intheMondegoestuaryduringthedroughtperiod,

withanincreaseinflatfishspecieswhosedistributionrangeincludessubtropicalareas,suchasA.

laterna,B. luteum,D.hexophthalmaandP. lascaris.SincethePortuguesecoastrepresentsthe

transitionbetweennortheasternAtlanticwarm‐temperateandcold‐temperateregions(Ekman,

1953; Briggs, 1974), the presence of several species in sympatry within this latitudinal area

constitutes an interesting and unique ecological context (Cabral et al., 2007),with particular

relevanceforthestudyofspeciesshiftsinhabitatuseduetoglobalchanges.

To identify changes across systems and geographical areas, the guild approach provides a

suitablebasis (Elliott andDewailly, 1995; Elliott et al.,2007; Franco et al., 2008). In fact, the

importanceoftheevaluationofthefunctioningofestuarineecosystemsbycategorizingfishinto

functional categories (such as habitat use, feeding and reproduction), relies on the ability to

separatefishstrategiesintheuseoftransitionalwatersystems(hencefunctionalaspects)from

“accidental behaviors”, e.g., connected to species identities and their distribution along

geographicalranges(Elliottetal.,2007).Theestuarinehabitatuseapproachhereusedsupports

theprincipleofthepreviousauhtors,thatsimilaritiesbetweenestuarinefishassemblagesexist

onthefunctionallevel(ratherthanonthespeciescomposition),suggestingasharedfunctional



roleoftransitionalwatersnotdetectedbythetaxonomicalcompositionanalysis(Francoetal.,

2008). Accordingly, theMondego estuary fish assemblage was similar in structure with the

typicalEuropeanAtlanticseaboardestuarinefishcommunity,asdescribedbyElliotandDewailly

(1995),withadominanceofestuarineresidentspeciesandmarine‐estuarinespecies.Themain

variations across estuarine systems,mostly in species composition and relative abundance of

functionalguilds,havebeenattributedtoparticularconditionsateachestuary(Pihletal.,2002),

which include hydrodynamic regimes, local topography, anthropogenic pressures and habitat

suitability(Schlacheretal.,2007;Vasconcelosetal.,2007).

Linkingclimatepatternstorecruitmentvariabilityinfishspecies

In recent decades there has been growing interest in climate variability and its effects on

fisheries and marine ecosystems (Parsons and Lear, 2001). Given the high commercial

importanceofthemarinefishspeciesthatuseestuariesasnurseryareas(i.e.marine‐estuarine

dependent species), itwas essential to evaluate themagnitude inwhich environmental and

climatic variables, both at local and global scales, influence the recruitment and abundance

processes in estuarine nurseries. In fact, climate influences marine fish directly through

physiology, as well as indirectly through affecting interactions with predators, prey, and

competitorsinadditiontoregulatingsuitablehabitat(Ottersenetal.,2004).Thus,theinfluence

ofseverallocalenvironmentalvariablessuchasprecipitation,riverrunoff,salinityandestuarine

water temperature, as well as large‐scale patterns including the NAO index, sea surface

temperature, and coastalwind speed and directionwasmeasured, in order to describe the

interannualvariabilityinrecruitmentstrengthofthreekeyspeciesintheMondegoestuary.

ForthethreemarinespeciesthatusetheMondegoestuaryasanurseryarea,D.labrax,P.flesus

and S. solea, river runoffwas significant in explaining yearly 0‐group abundance,with lower

densities found during the drought period. These results emphasize the importance of

maintainingecological freshwater flows,sinceriverrunoff is interrelatedwith theextensionof

river plumes to coastal areas, an important cue for orienting fish larvae towards estuarine



nurseries(Amaraetal.,2000;ForwardandTankersley,2001;Vinagreetal.,2007).Windspeed

anddirectionwerealsodeterminedassignificantfactorsfortheyearlyabundanceof0‐groupD.

labrax and P. flesus.Although in lowermagnitude,wind is responsible for several circulation

patterns,suchascoastalupwelling,surfacecurrentsandturbulence,whichcombinedwithlocal

topography, tidal and ocean currents can influence transport and retention mechanisms,

essential for fish larvae. In particular, flatfish larvae tend to concentrate in the lowerwater

masses (e.gLagardèreetal.,1999),mainly forescaping to the top layermasses thataremore

susceptibletowindandoffshoreadvection,typicalofupwellingsystemssuchasthePortuguese

coast(Vinagreetal.,2007).

All these reported influencesofenvironmental factors in the recruitmentvariabilityofmarine

fishleadtoonequestion:howwillmarinespeciescopewiththeenvironmentalinstabilitythatis

prone to take place in the forthcoming years? One of the major patterns of atmospheric

variability in theNorthernHemisphere is theNorthAtlanticOscillation (NAO), a hemispheric

meridional oscillation in atmosphericmasswith centers of action near Iceland and over the

subtropicalAtlantic (Visbeck et al., 2001; Trigo et al., 2002). This large‐scalepattern ishighly

correlatedwithprecipitationregimesintheIberianPeninsula,asitinterfereswiththetrajectory

ofdepressionsintheNorthAtlantic(Zhangetal.,1997;Trigoetal.,2002).Additionally,theNAO

has alsobeen correlatedwith changes in sea surface temperature (SST), aswell aswind and

currentpatternsoffthePortuguesecoast(Henriquesetal.,2007).Inthiswork,theeffectsofthe

NAO couldnotbe ascertained,probablydue to the small time frameof field sampling, as its

effectsaremainlyexperienced in the long‐term.Nevertheless, recentstudieshave related the

NAOwithabundanceandproductivityof fishcommunities (ParsonsandLear,2001;Attrilland

Power,2002;Henriquesetal.,2007),aswellason the recruitmentandmigrationpatternsof

particular species (Sims et al., 2004; Henderson and Seaby, 2005; Santojanni et al., 2006).

Although the NAO is a natural mode of atmospheric variability, surface (ocean and land),

stratospheric,orevenanthropogenicprocessesmayinfluenceitsphaseandamplitude(Visbeck

etal.,2001).Hence,adifferentcombinationoftheNAO,hightemperatureandsalinitymay, in



thefuture,produceaconsiderablelessfavourablecombinationresultinginrecruitmentcollapse

formanyspecies(Henderson,2007).Inaddition,sincefishspeciesareoftenfoundin,orseek,a

limited rangeofhydrographic conditions, large‐scale shifts inwatermassboundaries canalso

lead todistributionalchanges (Drinkwateretal.,2009),due tochanges inwaterstratification,

turbulence and advection mechanisms, essential for the dispersion of eggs and larvae to

estuarinenurseries(SentchevandKorotenko,2004).

Localpatternsalsoplayan important role indetermining recruitment strength,which include

precipitation, river runoff and salinity regimes. Recent projections for the Iberian Peninsula

indicatethatareductioninprecipitationamountsisexpectedtotakeplace,concentratedinthe

wintermonths (IPCC, 2001, 2007;Miranda et al., 2006), as well as an increase in extreme

weatherevents,suchasdroughtsorfloods(Mirza,2003;OkiandKanae,2006).Thus,sinceriver

runoffhasbeenappointedasonedeterminingfactorforrecruitmentofmarinefishesworldwide,

itisexpectedthatspeciesthatrecruitlaterinspringwillbemoreaffectedbythereductioninthe

extensionofriverplumes intothecontinentalshelf,wherespawningtakesplace.Precipitation

has also been determined as an important factor influencing estuarine fish production

worldwide. As an example,Meynecke et al. (2006) determined that the catches of several

Australian estuarine fish specieswere correlatedwith rainfall, indicating that fisherieswillbe

sensitivetotheeffectsofclimatechange.Inagreement,similarpatternshavebeendescribedin

southernPortugal, regarding river flowand localoffshore fisheries (Erzinietal.,2005). In the

present work, both these factors were determinant either in structuring the estuarine fish

assemblage,orintherecruitmentvariabilityoftheselectedspecies,pointingouttheimportance

ofsuchdensity‐independentmechanisms.Moreover,andsinceDolbethetal.(2008)reportedon

asignificantreductioninestuarineproductionofthesespeciesduringthedrought,itisexpected

that the function of the estuary as a nursery area for these speciesmay be impaired in the

future.

Theeffectsofclimatechangeonmarineorganismscanbefeltatvariouslevels,suchasgrowth,

swimming speed and activity rates, reproduction, phenology, recruitment, distribution or



mortality (Drinkwateretal.,2009).Of theprevious setofenvironmental factors, temperature

seems tobeanother importantvariableby controlling severalphysiological functions, suchas

growthandreproduction.FortheEnglishChannel,Simsetal.(2004)observedthatflounder(P.

flesus)migratedearlierfromestuarinenurseriestocoastalspawninggroundswhenthe largest

differences in temperaturesbetweennear‐estuaryandoffshoreenvironmentsoccurred,which

were in turn, related significantly to cold,negativephasesof theNAO. For the same species,

seawater temperature over 12ºC has a deleterious effect on the eggs’ survival (von

Westernhagen, 1970), which has been pointed out as the main cause for the reduction in

abundance of this species in southern Portuguese estuaries (Cabral et al., 2007).Moreover,

Pörtneretal. (2001)demonstrateda clear relationshipbetween climate induced temperature

fluctuations and the recruitment, growth performance and fecundity of cod stocks, as a

consequenceofmaintaining internalenergybudgets.Given theseearly indicatorsofchange in

phenologyandhabitatusepatterns,itisprobablethatasignificantreductionintheabundance

of these species in Portuguese estuaries may take place, mainly for those species whose

distributionrangeincludeshigherlatitudes.

The use of statisticalmethods such as GLM for determining which environmental variables

influencesignificantly therecruitmentvariabilityshowed tobeapowerful tool.This technique

has been extensively used worldwide, mainly for determining habitat suitability, species

occurrence and analysing fisheries catch data (e.g. Stefánsson, 1996; Le Pape et al., 2007;

Teixeira and Cabral, 2009; Vinagre et al., 2009). Hence, this approach combinedwith other

models such asGeneralized AdditiveModels (GAM) andHabitat Suitability Indices (HSI), can

improvetheassessmentofoptimalhabitats,aswellastheoccurrenceofspeciesgivenasetof

environmental characteristics. Moreover, descriptors of habitat suitability provide valuable

information, as required for implementingeffectiveecosystem‐basedmanagementplans (e.g.

River Basin Plans, Integrated Coastal Zone Management Plans), either for fisheries, marine

protectedareas,estuarineandcoastalecosystems.



Managementoftransitionalwaters

The EUWater FrameworkDirective (WFD)has established a framework for theprotectionof

groundwater,inlandsurfacewaters,estuarineandcoastalwaters,comprisinganewviewforthe

managementofwaterresources inEurope.Forthe firsttime,watermanagement is: (a)based

mainly upon biological and ecological elements,with ecosystems being at the centre of the

managementdecisions; (b)applied toEuropeanwaterbodies,asawhole;and (c)basedupon

thewholeriverbasin,includingalsotheadjacentcoastalarea(Borja,2005).Themainobjective

ofthisdirectiveistoobtaina“Good”EcologicalStatusinallEuropeanwaterbodiesby2015.In

this context, the requirement for the use of comparable methodologies among different

countries relieson the fact that,during the intercalibrationprocess for the implementationof

theWFD,EUmemberstatesneed tobe inabroadconsensus in themeaningof thedifferent

concepts included in the directive, mainly in the operative aspects (Borja, 2005), such as

samplingmethodologiesandprocessesfortheecologicalqualityassessment.Thus,theneedfor

establishing the Ecological Quality Status (EQS) in transitional waters based on the fish

component (in addition with algae and benthic invertebrates), led to the evaluation of the

previousaspects:samplingmethodologiesandmultimetricindices.

Regarding the first approach, two widely used fishing gears for sampling estuarine fish

assemblageswerecomparedintermsofstructureandcompositionofthefishassemblage,since

theeffectsofgeartypehaveconsiderableimplicationsfortheaccuracyandprecisionofsamples

obtainedfromecologicalandfishery‐independentsurveys(Greenwood,2008;Rotherhametal.,

2008).Effectively,anddespitethesamespeciesrichnesswasobserved inbothbeamandotter

trawl samples,different type‐specific assemblagesweredetermined. In fact, ahigher relative

proportionofestuarineresidentspeciesinthebeamtrawldrovethemaindifferencesbetween

beam and otter trawl samples. However, seasonal otter trawl sampleswere composed of a

higherspeciesnumber,asaresultofawidercatchabilityofpelagicspecies incomparisonwith

the beam trawl,which targetsmainly benthic and demersal species (Hemingway and Elliott,

2002). Similar results when comparing different sampling methods have been obtained by



several authors, attributing such variability to gear selectivity (e.g. Olin andMalinen, 2003;

Greenwood,2008).

Other factors suchasdielperiod, towduration, samplinggear, tidalphaseand sediment type

have been determined to exert an effect on the structure and composition of estuarine fish

samples. As an example, night samples consistently provide higher abundance and species

richnessestimates(e.g.Grayetal.,1998;Guestetal.,2003;Unsworthetal.,2007;Johnsonet

al.,2008;Rotherhametal.,2008),mainlyduetoanincreasedcatchefficiencyofsamplinggears,

and to the increase in food availability,mainly in seagrass beds (e.g. Sogard andAble, 1994;

Guestetal.,2003;Unsworthetal.,2007).Despitethedifficultiesandconstraintsofsamplingat

night (Heminway and Elliott, 2002), forthcomingmonitoring plans should be based on night

samples. In addition, habitat heterogeneity should also be considered, as it has been

demonstratedthatdifferentfishassemblagesareassociatedwithhabitatcomplexmosaics,such

asmudflats,baresand,saltmarshes,oysterandseagrassbeds(NagelkerkenandvanderVelde,

2004;Ribeiroetal.,2006;Françaetal.,2009).For theMondegoestuary, thebeam trawlwas

determinedas themostsuitablesamplinggear for fishassemblages,given the impossibilityof

operatingtheottertrawlintheshallowerupperreachesoftheestuary.Beamtrawlsareamong

themostextensivelyusedsamplinggearsforscientificpurposesthroughoutEurope(Hemingway

andElliott,2002), thusproviding a suitablemethod for further comparisons amongestuarine

areas.

ThereporteddifferencesinthefunctionalguildsoftheMondegoestuaryfishassemblagedueto

different samplingmethods,mainly regarding theestuarineuseand feedingguilds, isofgreat

importance for thedeterminationof theEQS, leading to the another crucial issue that is the

choice and harmonization of sampling methodologies. Notwithstanding the fact that in the

presentcasebothbeamandottertrawlcapturedthesamespeciesnumber,theircompositionin

ecologicaland feedingguildswastosomeextentdifferent,whichmightprovidewithdifferent

qualification iftheEQS. Inagreement,Coatesetal. (2007)statedthatdifferentsamplinggears

contributedtodifferencesintheEQS,asaresultofgearselectivity.Aswithallsamplinggears,it



is importanttoacknowledgethatnotallmembersofthefishassemblagewillbecollectedand

thosethatare,willbecaughtwithdifferingefficiencies(Greenwood,2008),soasaresult,most

fish‐basedindiceswillbemethod‐specificregardingguildcomposition,metricscoringthresholds

andreferenceconditions.

The use of estuarine fish assemblages as indicators of environmental changes was further

analyzed, by comparing several multimetric indices developed worldwide in terms of their

evaluationoftheEcologicalQualityStatus(EQS)oftheMondegoestuary.Moreover,itwasalso

assessed their response to the extreme drought event that took place during the sampling

period.Theuseofenvironmentalindicatorsnotonlyhelpsmonitorchangesinanecosystem,but

also aid in communication by summarizing complex information about the environment

(Harrison and Whitfield, 2004). In addition, these biologically criteria‐based tools have the

advantageofprovidinga reliableand flexibleevaluation,allowingat the same timeaneasier

communicationofresultstomanagers,stakeholdersandpolicymakers(Henriquesetal.,2008).

For thiswork, severalmultimetric indiceswere selected: EstuarineBiotic Integrity Index (EBI)

(Deegan et al., 1997), Estuarine Demersal Indicators (EDI) (Borja et al., 2004), Estuarine Fish

Community Index (EFCI) (HarrisonandWhitfield,2004),Fish‐basedEstuarineBiotic Index (EBI)

(Breineetal.,2007)andtheTransitionalFishClassification Index(TFCI)(Coatesetal.,2007). In

general, the EQS determined for theMondego estuary based on the fish component ranged

between “Bad” and “High”,with the EDIbyBorja et al. (2004) and the TFCIbyCoates et al.

(2007)givingconstantlythehigherresults.Thesewerealsotheindicesthatobtainedthelowest

mismatch values, providing consistent evaluations of the EQS among them. Thus, it is

recommendedthat, ifnospecific index isdeveloped inanearfuture,oneofthesetwo indices

shouldbeused (oradapted)forPortuguesetransitionalwaters.TheEBIbyBreineetal. (2007)

was the only that detected changes in the structure and composition of the fish assemblage

duringthedroughtperiod.Infact,testingofindicesaimsnotonlytoselectthebestappropriate

index foreach case,butalsoassures that resultsare comparableamong twoormore indices

(Simboura and Reizopoulou, 2008), which is a determinant process for the successful



implementationoftheWFD.

Moreover, fulfilling the requirements for theevaluationof theEQS raisesa fewquestions: (a)

How to disentangle the “signal” of anthropogenic effects against the “noise” of natural

variability? and also, (b) how to obtain suitable reference conditions, towhom compare the

degreeofsimilaritybetweenfishassemblages?Infact,onemajordifficultyinevaluatingtheEQS

istodistinguishbetweenthemultipleimpactsthataquaticecosystemsaresubjectedto,turning

it more intricate to study the response of estuarine fish assemblages to these pressures

(Vasconcelosetal.,2007;UriarteandBorja,2009).Inaddition,sincetransitionalwatersconsist

of highly dynamic and naturally stressed systems, separating the causes of change in the

structure and composition of fish assemblages can be a demanding task (Estuarine Quality

Paradox – see General Introduction),mainly if the available classification tools rely only on

ecosystemstructuralfeatures,suchasdiversity,insteadoffunctionalones(ElliottandQuintino,

2007).Accordingtothepreviousauthors,failingtodosocreatestheriskthatanyindicesbased

onthosefeaturesandusedtoplanenvironmentalimprovementsareflawed.Hence,theuseof

functional attributes in multimetric indices is highly advisable, as they will enable a better

understandingof the changes in theecosystem functioning,adeterminant featurewithin the

WFD.Asuitableapproachforreducingtheinfluenceofnaturalvariabilityistoadjustthemetric’s

criteriatoseasonsandsamplinggears,asstatedbyBreineetal.(2007).

The second questionwas related to the existence of reference data. In fact, one challenging

aspectoftheWFDistodeterminereferenceconditions,eitherbasedonhistoricaldataorexpert

judgement (Muxika et al.,2007). Since littlequalityhistoricaldata is available forPortuguese

estuaries, reference conditions need to be derived from either expert judgement, predictive

modelling, or as the present case, to rely on recent sampling data. This has the possible

disadvantageofbiasingthedeterminationoftheEQS,sinceatthepresent,aquaticecosystems

andtheassociatedfaunahavealreadyadegreeofdeviationregardingwhatcouldbedetermined

asa referencecondition.However, thismethodhasbeensuccessfully implementedbyseveral

authorsworldwide(e.g.HarrisandSilveira,1999;USEPA,2000;HarrisonandWhitfield,2004),in



whichwasusedthebestvaluesobservedtodefinetheexpectations (i.e.referenceconditions)

for eachbiotic attribute ormetric given the available dataset. Furthermore, the definition of

referenceconditionsshouldaccountforthegreatnaturalvariabilitythatcharacterizesestuaries,

namelyregardingthedifferenthabitatsavailableforfish.

Conclusions

Thiswork presented a comprehensive approach on the use of estuarine fish assemblages as

indicators of environmental changes. As amajor outcome, the components included in the

previous chapters,namely the fishassemblages, themarine species thatuse theestuaryasa

nurseryareaaswellas theassessmentof theEcologicalQualityStatus,wereall influenced in

criticalaspectsbyclimateand inoneof itsmainexpressions:precipitation regimes.Given the

expected increase in extreme weather events, such as droughts and floods, resource use

patternsbyestuarinefishfaunawillfacenewchallenges,duetochangesinnurseryfunctioning,

habitatsuitabilityandreducedwaterquality.Inviewofthis,theimpactsofglobalchangesmay

be farreaching than theestuarineborders,due to thehighlyvaluablegoodsandservices that

these ecosystems provide, including numerous economic activities directly or indirectly

connected to them. Ultimately, this work also strengthened the viewpoint that the use of

biologicalcriteria,particularlyestuarinefishassemblages,isapracticalandsuitableapproachto

provide information that supportsmanagement decisions, as required by recently developed

legislationfortheprotectionofwaterresources.

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199 |FuturePerspectives

FuturePerspectives

One usual pattern of scientific work is that when one objective is fulfilled, several other

questionsarise,mostofwhich interrelatedwiththepreviouswork,posingnewchallengesand

definingnewresearchdirections.Inthisthesis,thiswasnotanexception.Consequently,inthis

section are presented new research areas drawn from the present work, stressing the

importanceoffurtherinvestigationontheprocessesrelatingestuarinefishassemblagesandthe

surroundingestuarineandmarineenvironments.

Long‐termstudiesandclimatechange

The importanceof long‐termstudieshasbeenwidely recognized,being thebasisof reference

effortsindeterminingcausalrelationshipsbetweenbiotaandtheenvironment.Agoodexample

is theContinuousPlanktonRecordersurvey, inwhich theecologyandbiogeographyofmarine

plankton of the North Atlantic and North Sea has been studied since 1931. One important

featureinstudyingthehighlydynamicestuarineecosystemsiscross‐referencingdataatdifferent

levels,whichreinforces theestablishmentof long‐termmonitoringprogrammes. Italsoknown

thatglobalpatternssuchastheNorthAtlanticOscillation(NAO)operateoveralargetime‐scale,

being responsible forsomeof themost importantaspects inmarineecosystemssuchaswind

andwatercirculation,seawatertemperatureandprecipitationregimes.Inthiswork,arelatively

smalltimeframewasanalyzed,but itwaspossibletodetectsometrendsasaresponsetothe

occurrenceofextremeweatherevents.Prolongingthecurrentmonitoringprogrammewillallow

evaluating in what extension these extreme weather events impacted on the estuarine

communities,aswellasdeterminingtheeffectsofdifferentNAOphasesonthedistributionand

abundanceofestuarinefauna.Inaddition,long‐termdatacanalsobethefulcrumforaholistic

approach in understanding the effects of stochastic and/or small‐scale events in estuarine

communities,suchaspollutionoutbreaksandtoxicalgalblooms.


200 |FuturePerspectives

Connectivityanalysis

The issueof connectivitybetween theestuarineand coastalareas isdeterminant for the fish

species whose complex life cycle includesmigration between these two environments. This

analysishasaninvaluableimportance,mainlyduetothehighcommercialvalueofthesespecies.

Thus, itwould beworthy to analyze the contribution of theMondego estuary to the coastal

stocksof themost important fish species thatuse theestuaryasanurseryarea:D. labrax,P.

flesusand S. solea. Furtherdevelopmentson theuseofotolithmicrochemistry structure can

providemoredetailedinformationontheexportrates,andalsotowhichdegreetheseratesare

influencedbyenvironmental fluctuationsandextremeweatherevents.Theanalysisofspecific

patternsrelatedwithhabitatheterogeneitycanalsoprovidesuitable informationregardingthe

importanceofestuariesasnurseryareasformarinefish,beingpossibletoestimatethefunction

and value of particular habitats for each fish species. This can be performed by comparing

growthrates,RNA:DNAratiosandconditionfactors,orevenbymeansofDynamicEnergyBudget

models,inordertoassessthequalityandperformanceofestuarinenurseries.Bycombiningthis

informationwiththeanthropogenicpressures intheestuary,valuable insightscanbeprovided

foramoreadequatemanagementoftheestuarineecosystem.


201 |Acknowledgements

Acknowledgements

Itwasin2002,duringafieldtripintheMondegoestuarysaltmarshes,whentheideaofworking

withfishfirstcametolife,andsincethen,severalpeoplehavebeeninvolvedinstudyingthefish

assemblageof the estuary.And it’s to thosepeople,whohaveparticipated eitherdirectlyor

indirectly in thiswork that Iwould like tomost respectfullyacknowledge,as thesepastyears

havebeennothinglessthanatrueadventure.So,hereitgoes:

Tomy supervisors,ProfessorsMiguelPardalandHenriqueCabral, forproviding theguidance,

motivation andmost importantly, the knowledgeon the functioningofestuarineecosystems.

Thankyou forbelieving in thisproject, inmycapabilities,butmainly forbeingapersonaland

professionalexampleformeasayoungresearcherandasagrowingprojectofahumanbeing.

TotheIMAR–InstituteofMarineResearchandProfessorJoãoCarlosMarques,forprovidingall

thelogisticsandsupport,aswellasforsponsoringthefineartofphotography.

To Gabi,what can I say? Thank you for being therewith a smile, for all the administrative

assistance, forgivingmemuchusefull tips ingraphicalandwebdesign,aswellas for thebike

relatedconversations.

ToMarinaDolbeth,mydearfriend!Thankyouforourgenuinescientificdiscussions,forallthe

motivation,companionshipand involvement infieldand labwork,even if itmeant listeningto

yousinging...AstheysayinOldPortuguese:“Muitoobrigadoéoqueeutambémtedesejo!”

To IvanViegas, thankyou forbeingpresent inmostof theallnight‐long field trips, forall the

help, companionship and nice discussions.Despite all the enginemalfunctions, accidents and

ruinednets,wewerealwaysabletocomebackinonepiecefromournauticaladventures,and

withfishinourfreezers.



Tomyplanktonic colleaguesand friends:SóniaCotrim, LígiaPrimo,AnaMartaGonçalvesand

mostrecentlyJoanaFalcão.Thankyouforbeingamongthemostgiftedsailorsaskipperwould

wish (this includes catering, of course). Youmade the field tripsmuchmore pleasantwhile

chasingthatfast‐pacedplankton.

TotheJusticeirosPedroCoelho,RicardoLeitãoandTiagoVerdelhos!Youaretruefriends!Thank

you foralwaysbeing there for thebetterandworst,butmainly for thegoodmomentswhile

camping,biking,kayaking,travelling,goingtoconcerts,dinners,coffeesandgeneralnonsense.

HereIalsoincludeSaraLeston,forallthefriendshipandnicegourmetdinners.

ToeverybodyattheIMAR‐Coimbra,whoalsoparticipatedinthelongfieldtrips.ThankyouLilita

Teixeira,FilipaBessa,DanielCrespo,JoãoRito,HugoSousa,JoãoNeto,DánielNyitrai,Peterand

Frank.Youreffortwasnotinvain!Here,Iwouldalsoliketothankalltheotherfriendswhowork

or haveworked at the IMAR, creating such a friendly atmosphere: Ana Sousa, Sónia Costa,

españolasAranzázuMarcoteguie LauradePaz, Joana(s)BaptistaeOliveira,AlexandraBaeta,

FaniTeixeira,IreneMartins,MargaridaCardoso,RutePinto,HelenaVeríssimo,PatríciaCardoso,

Macha,FilipeCeia,JoãoFranco,Rui(s)MargalhoeGaspar,NélsonMartins,TiagoGrilo,andtoall

otherswhosenamesIcannotrememberrightnow!

TothestudentsattheCentrodeOceanografia,UniversityofLisbon,formakingmefeelathome

duringmyshortvisits.Particularly,thankyouSusanaFrançaforajoyfulsmile,andCéliaTeixeira

forthemuchneededhelpwithRsoftware.

ToFredericoNeves,forsharingsomeofthemostremarkingmomentswhilenotatwork,either

in photography trips or shredding down the hills (and knees…). Here, I would also like to

acknowledgeAntónioLuísCampos,forteachingmemorethansimplephototipsandtricks,and

forintroducingmetosomeofthemostbeautifullsingletracksincentralPortugal.



ToMariaJoãoFeio,forthenicewalksinthemountains,andmostrecently,togetherwithMarina

Dolbethandmyself,fortakingthestepfurtherinenvironmentalentrepreneurism.I´msurewe’ll

makeBIOSTREAMahugesuccess.

To allmy friends,whowill never stop beingmy friends. Your supportwas fundamental for

completingthistask.

Tomyfamily,whodespitesometimesnottrulyunderstandingmychoices(includinghavingtogo

fishingatnight),neverstoppedbelievingandsupportingme.AspecialthankyoutomyMother,

whoagainstallodds,managedtopullthrough.Youareatrueexample!“Muito,muitoobrigado

porseresaminhabase!”

ToCláudia,thankyouforbeinghere,forthehugesupportandforsharingallyourlife’smoments

withme.Whereverourpathleadsus,Icanonlyhopewecantakeittogether!

Toallofyou,onceagain:“Muitoobrigadoéoqueeuvosdesejo!”

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