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The role of bivalves in the Balgzand: First steps on an integrated modelling approach Kooijman, S.A.L.M.
published in Ecological Modelling 2017
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10.1016/j.ecolmodel.2017.04.018
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Kooijman, S. A. L. M. (2017). The role of bivalves in the Balgzand: First steps on an integrated modelling approach. Ecological Modelling, 359, 34-48. https://doi.org/10.1016/j.ecolmodel.2017.04.018
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ContentslistsavailableatScienceDirect
Ecological Modelling
jo u r n al ho m e p ag e :w w w . e l s e v i e r . c o m / l o c a t e / e c o l m o d e l
The role of bivalves in the Balgzand: First steps on an integrated modelling approach
S.Saraivaa,∗,L.Fernandesb,J.vanderMeerc,d,R.Nevese,S.A.L.M.Kooijmand
aSwedishMeteorologicalandHydrologicalInstitute(SMHI),Folkborgsvgen17,SE-60176Norrköping,Sweden
bActionModulers,EstradaPrincipal,29r/cPaz,2640-583Mafra,Portugal
cRoyalNetherlandsInstituteforSeaResearch(NIOZ),P.O.Box59,1790ABDenBurg,Texel,TheNetherlands
dVrijeUniversiteit,Dept.ofTheoreticalBiology,deBoelelaan1087,1081HVAmsterdam,TheNetherlands
eInstitutoSuperiorTécnico,EnvironmentandEnergySection,Av.RoviscoPais,1,1049-001Lisboa,Portugal
a r t i c l e i n f o
Articlehistory:
Received8November2016
Receivedinrevisedform29April2017 Accepted30April2017
Availableonline1June2017
Keywords:
Musselbed IBM
Ecosystemmodel DEBtheory MOHID Balgzand
a b s t r a c t
Thepresentpaperdescribesaprocessorientedmodellingtoolthatintegratesphysical,biogeochemi- cal,ecologicalandphysiologicalfactorsgoverningbivalvepopulatedmarineecosystems.Thismodelling toolistheresultofthecouplingbetweenanindividual-basedpopulationmodelforbivalves(basedon theDynamicEnergyBudgetstheory,DEB)andahydrodynamic/biogeochemicalmodel(MOHIDWater ModellingSystem).ThemodelwasimplementedintheBalgzandarea(WaddenSea,TheNetherlands)in afineresolutiondomaintostudymusselpopulationdynamicsandtoquantifytheinfluenceofmussel communitiesonthepelagicsystem.Modelresultsforareferencescenario(2009/2010)areinagreement withobservations,andprovideaconsistentquantitativedescriptionoflocalhydrodynamicsandbiogeo- chemicalcycles.TheBalgzandactsasasinkofphytoplanktonduetobivalves’filtration,andasource ofammonia,exportingabout40%morethantheinputflux.Theseresultssuggestsignificantammonia regeneration.Resultsshowthatdespitethelongandalmostcontinuousspawningseason,onlyafew cohortsareabletosurvive.Earlystagemortality(top-down),inparticularcannibalismandshrimppre- dation,cancontrolthepersistenceofnewcohortsinthefirstmonthalthoughstarvation(bottom-up) representsthemaincauseofbiomasslossinanoverall.Thetendencyisthatnewmusselbedsareformed inareasadjacenttoalreadyexistingmusselbedsandchanneledges.Bivalves’activityintensifiesthe seasonalpatternsoffoodandnutrientsinareasclosetothemusselbeds,thoughnotchangingtheirover- allspatialdistribution.Thisstudynotonlyconfirmsbutalsoquantifiesmussels’potentialtoinfluence ecosystemfunctioningduetotheirroleinnutrientcycling.Asthefirstintegratedmodellingstudythat focusonthemussels’bedsintheBalgzand,themaindifficultiesonthemodeldesign,setupandresults analysiswereovercome.Themodelcannowbeusedfurther,testedandimprovedinthesameorother systemsinordertoserveasaneffectiveandreliablescientificandmanagementtool.
©2017ElsevierB.V.Allrightsreserved.
1. Introduction
Bivalves, which are common to many coastal habitats, are probably ecologically and economically the best studied ben- thic suspension feeding group (Dame et al., 2001).The ability to predict the dynamics of bivalve populations in response to environmentalchange,natural or humaninduced, is useful for themanagementofcoastalecosystems,eitherwiththepurpose ofcommercial exploitation optimization,environmentalimpact assessment,climatechangesimplicationsorassessingtheimpact
∗ Correspondingauthor.
E-mailaddress:sofia.saraiva@smhi.se(S.Saraiva).
of exoticspecies introduction.Mathematical models havebeen usedtoaddresssomeofthesequestions.Althoughtheycanvary enormouslyintermsofcomplexity,theirfocusiseithermoreori- entedon(i)theeco-physiologyoftheindividualbivalves,coupled ornotwithbiogeochemicalandbiologicalmodels,butwith‘simpli- fied’descriptionsofphysicalprocesses(e.g.Brinkmanetal.,1993;
Barettaetal.,1995;Dowd,1997;ScholtenandSmaal,1998;Ren andRoss,2001;SavinaandMénesguen,2008;Brigolinetal.,2009;
Ferreiraetal.,2009)oron(ii)physicaltransport,usingcomplex physicalmodelswhereonly‘simple’formulationsforbiogeochem- ical/biologicalprocesseswereintroduced,e.g.GETM(Burchardand Bolding,2002), COHERENS (Luyten etal., 1999), MOHID Water ModellingSystem(Miller andPinder, 2004).Generally,thefirst groupofmodelsaimstopredictthebivalveproductionandthesec- http://dx.doi.org/10.1016/j.ecolmodel.2017.04.018
0304-3800/©2017ElsevierB.V.Allrightsreserved.
S.Saraivaetal./EcologicalModelling359(2017)34–48 35
ondgroupaimstopredicttheimpactofbivalvesactivityonsystem properties,suchasprimaryproduction.Theconstantdevelopments incomputerhardwareand programminglanguagesenabledthe developmentofmodelsthatcouplecomplexdescriptionsofboth ecologicalandphysicalprocesses.Thechallengeisnowtogetbet- terpredictionsofbivalveproductionandpopulationdynamicsin interactionwithaneverchangingenvironmentbyimprovingthe descriptionof foodavailability and relevantphysical processes, suppliedbythe‘physicaltransport’typeofmodels.Someexam- plesofthisapproachcanbefoundintheliterature(e.g.Klincketal., 2002;Hofmannetal.,2006;Goffetal.,2017)
Severaldifficultiesarise comparedwiththetraditionalmod- ellingapproachfollowedforphytoplanktonandzooplankton.Most ofthesedifficultiesarecausedbytwofacts:(i)bivalveshaveboth apelagicstage,wheretheyaretransportedinthewatercolumn and directlydependonphysical processes,and a benthicstage (e.g.deVooys,1999);(ii)theirfoodrequirement(bottom-uppro- cesses)andtheirinteractionswithotherspecies(competitionand top-downprocesses)stronglychangethroughouttheirlifecycle (embryo, juvenile and adult stages). Reproduction and recruit- mentsuccesscannotbedeterministicallypredictedifthesetwo factsarenotproperlyaddressed.Insomeofthecurrentmodelling approachestheproblemis solvedeitherbyimposing spawning eventsata specifictime (e.g.Maaretal.,2010)orbyconsider- ingthemdependentonenvironmentalvariables(e.g.Gerlaetal., 2014).Somestudies alsofocusonthedispersal andsettlement ofthelarvae(e.g.Bidegainetal.,2013).However,inthosestud- iesthereproductionis detached fromthebivalve development stage.Inaddition,understandingtop-downcontrolrequiresthe simulationoftheindividualsize,throughouttheirmainlivestages (larvae,juvenileandadult),sincepredatorshavesizepreferences.
Sizestructureinthepopulationhasbeennormallyneglectedor imposed,though.Probablybecausemostmodelshavebeendevel- opedforenvironmentalimpactassessment,whereeitherthesize structureisartificiallycontrolled,asinaquaculturesystems,orsim- plybecauseitisfoundtoocomplex.However,modelaimsgonow beyondaquacultureassessmentsandnewquestionsareraised,for exampleonpopulationresponsestoclimatechange.Otherexam- plesarerelatedtotheintroductionofnewspeciesinlower,same anduppertrophiclevels,changesinfoodquality,changesinhabitat morphology,changesinhydrodynamics,temperatureorsalinity.
Allthesequestionscanonlybeaddressedifsizestructureiscon- sideredinthepopulationbecausetheunderlyingprocessesaresize dependedandconsequentlytheirrelativeimportanceintimeand spaceandthatcanbedonethroughthesimulationoftheindivid- ualbivalvedevelopment.Forthispurpose,energybudgetmodels havereceivedsomeattention(BeadmanandKaiser,2002),inpar- ticulartheDEBtheory,proposedbyKooijman(1986,2000,2010).
Itisbasedonamechanisticviewofanorganism’smetabolicpro- cesses,includinggrowth,maturationandreproduction,wherethe basicprinciplesandformulationsarevalidforalldifferentstagesof theindividual.Thedirectconsequenceisthatthesamesetofequa- tionscanbeusedtosimulatethecompletelifecycleofabivalve.
Thisisanadvantageinthecouplingwithhydrodynamicandbio- geochemicalmodelsthatalreadyhaveahighlevelofcomplexity.
Yet,thisapproachcansignificantlyincreasemodelcomplexity,i.e.
highernumberofstatevariables,more/differentuncertaintiesto copewith,highernumberofparameterstoestimate,largeramount andvariabilityofinputdata,highercomputationaltime,andalso largervolumesofoutputresultstoanalyse.
Advantages and disadvantages of complex modelsuse have beendiscussedinthelastyears(e.g.Fultonetal.,2003;Curyetal., 2008;Hannahetal.,2010),althoughwithmorefocusonfisheries andend-to-endmodels.Conclusionsarenotyetestablished,butthe factisthatverysimplisticmodelsfailtocapturecriticalinteractions andsystemcomponents,butextremelycomplicatedmodelscanbe
impactedbyuncertainty,computationalcostandlackofaccuracy (Fulton,2010;Hannahetal.,2010).Modelsaresuitablycomplex ifallcriticalprocesses,driversandcomponentsunderscrutinyare captured(Fulton,2010),which canbedifficulttoassess.Inthis paper,withtheaimofpredictingthebivalvepopulationdynam- icsandquantifytheirinfluenceonthepelagicsystem,wepropose that themodel shouldbeabletosimulatethesize structureof thepopulation,basedontheindividualdevelopment,throughits mainlifestages(larvae,juvenileandadult)inadynamicenviron- mentwithchangesinnutrients,temperature,andfooddrivenby physicalprocesses,aswellaspredators’seasonalabundance.Fol- lowingthisidea,thepresentpaperdescribesaprocessoriented modellingtoolthatcouplesanindividual-basedpopulationmodel forbivalves(basedontheDynamicEnergyBudgetstheory,DEB) andahydrodynamic/biogeochemicalmodel(MOHIDWaterMod- ellingSystem)anditimplementationintheBalgzandarea(Wadden Sea,TheNetherlands).
2. Materialandmethods 2.1. Modeldescription
2.1.1. MOHIDWaterModellingSystem
MOHID(www.mohid.com)isathreedimensional(3D)water modellingsystemdeveloped atInstituto SuperiorTécnico(IST), Universityof Lisbon.It consistsof asetof coupledmodelsthat aimtosimulatethemainphysicalandbiogeochemicalprocesses in aquatic systems (Miller and Pinder, 2004).MOHIDhas been implemented and validated in differentcoastal/estuarine areas (e.g.Leitãoetal.,2005;Trancosoetal.,2005;Saraivaetal.,2007;
Vazetal.,2009).Thesystemisbasedonthefinitevolumecon- ceptanditisdesignedinahierarchicalmodularstructure,using anobjectorientedapproach.Thehydrodynamicmodelsolvesthe primitivecontinuityandmomentumequationsforthesurfaceele- vationand3Dvelocityfieldforincompressibleflows,inorthogonal horizontalcoordinatesandgenericverticalcoordinates,assuming hydrostaticequilibrium andBoussinesqapproximation(Martins etal.,2001).Momentum,massandheattransportarecomputed usingageneric3Dadvection-diffusionlibraryincludinghighorder advectionschemes.Italsoincludesafinesedimenttransportmod- ulesimulatingsettling,depositionanderosionforagenericclassof particlesand/orparticulatematter.Erosionanddepositionfluxes dependonbottomshearstressesthatarecalculatedasfunction of near bottom currents and wave induced stress. The model comprises severalmodules tocompute pelagic biogeochemical processes.ThecurrentstudyusestheWaterQualityModule,based onformulationsinitiallydevelopedbytheUSEnvironmentalPro- tectionAgency(EPA)(Bowieetal.,1985).ItisconsideredaNPZD modelanditsbasefeaturesinclude:explicitsimulationofnitro- genandphosphorouscycles;assumptionofconstantC:N:Pratios fororganicmatterandplankton;onegroupofphytoplankton,one groupofzooplankton,dissolvednutrientsanddissolvedandpar- ticulateorganicmatter(detritus).Thepelagicecologicalprocesses parametrizationis mainly adaptedfrom EPA. Modelledbenthic ecological processes, occurring in deposited sediments, include themineralizationoforganicmatter.Detailedinformationonthe modelstructure,formulationsanddefaultparametrizationcanbe foundinwww.mohid.com.
2.1.2. Individualbasedpopulationmodelforbivalves
Thepopulationof bivalvesisrepresentedbyseveralcohorts.
Eachcohortconsistsofanumberofidenticalindividualsbornatthe sametimeandwiththesameproperties(e.g.size,biomass,state ofdevelopment).TheindividualmodelisthestandardDEBmodel (Kooijman,2000,2010),coupledwithafeedingprocessesmodel,
specificallydesignedforbivalves(Saraivaetal.,2011).DEBthe- oryassumesthattheassimilatedenergyisfirststoredasreserve;
subsequentlythereserveisutilizedtofueltheothermetabolicpro- cesses,followingtheso-called-rule:afixedfractionofmobilized reserveisusedforsomaticmaintenanceandgrowth,therestisused formaturitymaintenanceandmaturation(embryosandjuveniles) orreproduction(adults).Theallocationofenergytoreproduction is temporarilyaccumulated ina reproductionbuffer. A spawn- ingevent,whichisdependentontemperatureandgonad-somatic massratio(GSR),emptiesthereproductionbufferandgivesori- gintoanewcohortinthesystem.Differenttypesofparticles,food and/orinorganicmaterial,canberetainedbybivalvesthroughfil- tration.Themodelalsoassumesthattheorganismisabletousethe reproductionbuffertocopewithsomaticmaintenancecosts(re- absorptionofgametes)duringstarvationperiods.Duringextreme starvationstructurewillbeused,meaningthattheorganism’sflesh shrinks,thoughmaintainingthesameshelllength.Inthesameline, thebivalve isabletoreduceitsmaturitylevel inordertocope withmaturity maintenance(rejuvenation).To simulatepossible differencesbetweenindividuals (e.g.positionandextremelocal fooddepletion)withinonecohort,anextrastarvationmortality isconsideredwhen theconditionoftheindividuals islow.This assumptionpretendstosimulatethedeathofindividualsinthe cohortduetolocalfooddepletionpreventingthesuddendeath ofthewholecohort.Aschematicrepresentationoftheindividual modelandalistofthemainparameterscanbefoundinthesupple- mentarymaterialbutadetaileddescriptionispresentedinSaraiva etal.(2012)wherethemodelperformancewastestedfordifferent locationsintheNorthSea.
Atthepopulationlevelthemodelincludes:initialeggmortality, backgroundmortality,foodcompetition,cannibalism,andimposed predationbyshrimps,crabs andbirds.Predator abundanceand intakeareconsideredaforcingfunctioninthemodel,meaningthat thereisnofeedbackfromthebivalvepopulationonthepredators.
Eachpredatorhasapreysizerangepreference,andthepredation impactineachcohortisproportionaltothefractionofthenumber ofindividualsinthecohortandthetotalnumberofpreyavailable.
Moredetailonthepopulationmodelformulations,assumptions andsetupcanbefoundinthesupplementarymaterial,andafull descriptioninSaraivaetal.(2014).Thecouplingwiththeecosystem modelenabledtheinclusionoftwoadditionalmortalityeffectson thepopulationdueto:(i)exposuretohighvelocities;and(ii)non suitablesubstrateforsettlement.Whenexposedtohighvelocities musselsexperiencenotonlydifficultiesinfeeding(Newelletal., 2001),buttheycanalsobeflushedawayandeventuallydie.This studyassumesthatthedeathofmusselsoccurswhenvelocitiesare higherthan0.5m/s(calibrationparameter).Basedonthefactthat musselshaveapreferencetosettleonsubstrateswithcoarseshell debris(waKangerietal.,2014)themodelassumesasettlement probabilitythatissitedependent.Non-settledbivalveswilleven- tuallydie,duetotheeffectofcurrentsorburying.Inaddition,itis alsoassumedinthemodelthatsettlementoccursinstantaneously when,andwhere,theindividuallengthishigherthan0.026cm(de Vooys,1999).
2.1.3. Couplingbiologicalandphysicalprocesses
The coupling philosophy assumes that the biogeochemical processes onlydepend ontheenvironmentaland physiological conditionsoftheindividualsinaspecificplaceandtime.InMOHID, which is based ona computationalgrid tosolve thetransport equations,themethodologyconsistsin buildingabiogeochemi- calmodule,organizedinsuchformthatthesinksandsourcesterm isindependentofthegridandofthegridcelllocation.Thistermis solvedseparately,butconsistently,fromtheadvectionanddiffu- sionterms.Thisindependenceallowsthebiogeochemicalmodule tobeimplementedinanytypeofgrid(1D,2D,3D)andcanthusbe
Fig.1.Schematicrepresentationofthecouplingbetweentheindividualpopulation modelandtheecosystemmodel:modelstructure,linksandinformationexchange ineachtimestep.
seenasazero-dimensionalmodel,whereexternalforcingcondi- tionsareprovided(ex:light,temperature,salinity)andmassfluxes betweenstate variables (e.g.phytoplankton, ammonia,bivalve) arecomputedfor eachcontrolvolume usingonlythesinksand sourcestermoftheequations.Thisisalsoanefficientwaytoguar- anteeahighlevelofrobustnessin thecodeand tomaintainit.
ThepresentstudyfollowedthismethodologybybuildingaMod- uleBivalvethatcomputesthetimeevolutionofbivalveproperties (e.g.reserves,structure,length)foreachcohortineachgridcell,as wellasthecorrespondenteffectonotherwater propertiescon- centrations(e.g.phytoplankton,ammonia)due totheiractivity, illustratedbyFig.1.MOHIDstructurealsoenablesthatalmostany processcanbeswitchedon/off.Asaresult,themodelisflexibleand easytouseindifferentsystems,conditions,scenariosandmostof all,enablesthestudyofparticularprocesseswithinthesystem.
Thebivalves’statevariablesmakeuseofthisstructure.Forexam- ple,bivalvelarvaetransportcanbeswitchedon/offdependingon theindividuallength.Duringthelarvaephasetheindividualissub- jecttotransportbycurrentsandturbulence,andonceitreachesa certainsize(settlementsize),theindividualssettle,andthetrans- portisswitchedoff.Inaddition,themodelconfigurationonthis studyassumesthatfoodavailabilityisdeterminedbyphytoplank- tonconcentrationandmussellarvae(cannibalism)andthattotal suspendedmattercanbefilteredbutnotingestedbytheindividu- als.
2.2. Studyarea
ThemodelisimplementedfortheBalgzand,anintertidalarea approximately50km2insize,andlocatedinthewesternmostpart oftheDutchWaddenSea(Fig.2).Alongtermsamplingprogramat Balgzandstartedin1970andmanystudieshavebeenperformed inthearea(andintheWaddenSea) overa widerange oftop- ics:physicalprocesses,biogeochemicalcyclesinthewatercolumn andsediment,primaryproduction,zooplankton,bivalves,shrimps, crabs,birds.Thesumofallthesestudiesconstitutesanimportant sourceofknowledgeonthesystemprocessesanddynamics.Asa result,theWaddenSea,andinparticulartheBalgzand,issuited toperformanintegratedmodellingstudyasproposed,asahigh volumeofinformationanddatainseveralfieldsisrequired.Fig.2 presentsselectedmonitoringstationsfromdifferentsourcesand projects.These locations correspondtofield data stations with recentandconsistentfield datarecordsthatarefurtherusedto calibrateandvalidatethemodel.Atthesametime, theirdistri-
