Modeling water quality in the Anthropocene: directions for the next-generation aquatic ecosystem models
$Wolf M Mooij
1,2, Dianneke van Wijk
1,2,3, Arthur HW Beusen
4,5,
Robert J Brederveld
6, Manqi Chang
1,2, Marleen MP Cobben
7,8, Don L DeAngelis
9, Andrea S Downing
10, Pamela Green
11,
Alena S Gsell
1, Inese Huttunen
12, Jan H Janse
1,4, Annette BG Janssen
3, Geerten M Hengeveld
13,14, Xiangzhen Kong
15, Lilith Kramer
16, Jan J Kuiper
10,17, Simon J Langan
18, Bart A Nolet
19, Rascha JM Nuijten
19,
Maryna Strokal
3, Tineke A Troost
16, Anne A van Dam
20and Sven Teurlincx
1“Everythingchangesandnothingstandsstill”(Heraclitus).Here wereviewthreemajorimprovementstofreshwateraquatic ecosystemmodels—andecologicalmodelsingeneral—as waterqualityscenarioanalysistoolstowardsasustainable future.Totackletherapidanddeeplyconnecteddynamics characteristicoftheAnthropocene,wearguefortheinclusion ofeco-evolutionary,novelecosystemandsocial-ecological dynamics.Thesedynamicsarisefromadaptiveresponsesin organismsandecosystemstoglobalenvironmentalchange andactatdifferentintegrationlevelsanddifferenttimescales.
Weprovidereasonsandmeanstoincorporateeach
improvementintoaquaticecosystemmodels.Throughoutthis studywerefertoLakeVictoriaasamicrocosmoftheevolving novelsocial-ecologicalsystemsoftheAnthropocene.TheLake Victoriacaseclearlyshowshowinterlinkedeco-evolutionary, novelecosystemandsocial-ecologicaldynamicsare,and demonstratestheneedfortransdisciplinaryresearch approachestowardsglobalsustainability.
Addresses
1DepartmentofAquaticEcology,NetherlandsInstituteforEcology (NIOO-KNAW),P.O.Box50,6700ABWageningen,TheNetherlands
2AquaticEcologyandWaterQualityManagement,Wageningen University&Research,P.O.Box47,6700AAWageningen,The Netherlands
3WaterSystemsandGlobalChangegroup,WageningenUniversity&
Research,P.O.Box47,6700AAWageningen,TheNetherlands
4PBLNetherlandsEnvironmentalAssessmentAgency,P.O.Box30314, 2500GHTheHague,TheNetherlands
5DepartmentofEarthSciences-Geochemistry,Facultyof
Geosciences,UtrechtUniversity,P.O.Box80021,3508TAUtrecht,The Netherlands
6Witteveen+BosConsultingEngineers,Ecologygroup,P.O.Box233, 7400AEDeventer,TheNetherlands
7DepartmentofTerrestrialEcology,NetherlandsInstituteforEcology (NIOO-KNAW),P.O.Box50,6700ABWageningen,TheNetherlands
8TheoreticalEvolutionaryEcologyGroup,DepartmentofAnimalEcology andTropicalBiology,UniversityofWu¨rzburg,Wu¨rzburg,Germany
9USGS,WetlandandAquaticResearchCenter,Gainesville,FL32653USA
10StockholmResilienceCentre,StockholmUniversity,Kra¨ftriket,2BSE- 10691,Stockholm,Sweden
11EnvironmentalSciencesInitiative,AdvancedScienceResearch CenterattheGraduateCenter,CityUniversityofNewYork(CUNY),New York,NY10031USA
12FreshWaterCentre,FinnishEnvironmentInstitute-SYKE,P.O.Box 140,00251Helsinki,Finland
13Biometris,WageningenUniversity&Research,Droevendaalsesteeg1, 6708PBWageningen,TheNetherlands
14ForestandNatureConservationPolicygroup,WageningenUniversity
&Research,P.O.Box47,6700AA,Wageningen,Netherlands
15DepartmentofLakeResearch,HelmholtzCentreforEnvironmental Research(UFZ),Bru¨ckstrasse3A,39114Magdeburg,Germany
16Deltares,DepartmentofEcologyandWaterQuality,P.O.Box177, 2600MHDelft,TheNetherlands
17NaturalCapitalProject,StanfordUniversity,Stanford,California,USA
18InternationalInstituteforAppliedSystemsAnalysis(IIASA),A-2361 Laxenburg,Austria
19DepartmentofAnimalEcology,NetherlandsInstituteforEcology (NIOO-KNAW),P.O.Box50,6700ABWageningen,TheNetherlands
20AquaticEcosystemsGroup,IHEDelftInstituteforWaterEducation,P.
O.Box3015,2601DADelft,TheNetherlands
Correspondingauthor:Mooij,WolfM(w.mooij@nioo.knaw.nl)
CurrentOpinioninEnvironmentalSustainability2018,36:85–95 ThisreviewcomesfromathemedissueonGlobalwaterquality EditedbyNynkeHofstra,CarolienKroeze,MartinaFlo¨rke,and MichellevanVliet
Received:08June2018;Accepted:21October2018
https://doi.org/10.1016/j.cosust.2018.10.012
1877-3435/ã2018ElsevierLtd.Allrightsreserved.Thisisanopen accessarticleundertheCCBYlicense(http://creativecommons.org/
licenses/by/4.0/).
$Pleasenotethattheterm‘Anthropocene’isnotformallyrecognizedbytheU.S.GeologicalSurveyasadescriptionofgeologictime.
Thechallenge ofsustainabledevelopment
“Earthprovidesenoughtosatisfyevery[one’s]needsbut notevery[one’s]greed”(MahatmaGandhi)
Sincethedawnofhistory,humanshavetriedtoimprove the quality of their lives throughtechnological innova- tion,scientificdevelopmentandsocialorganization.After WorldWarII,this‘progress’culminatedinwhatisknown as ‘the great acceleration’. Hence, we now live in the
‘Anthropocene’,definedbyagloballymeasurableimpact of human activities on system Earth [1,2], and we are transgressingplanetaryboundaries[3,4].Tomeethuman needswithinthemeansoftheplanet,KateRaworth[5,6]
recently presented the ‘Doughnut Economics’ frame- work.DoughnutEconomicsspecify“asafeandjustspace forhumanity”[5]intermsofelevenfundamentalhuman needsthattogetherprovideasocialfoundationandnine aspectsof global environmental changethatprovide an ecologicalceiling. Essentialhumanneedsandplanetary boundaries are also covered by the UN Sustainable DevelopmentGoals[7,8].Bothframeworksprovidetar- getssocietyshouldstriveforinitsquestforasafeandjust future(Figure1)butleavethequestionhowtogetthere unanswered [9]. Consequently, we require scenario
analyses to providedecision makerswith feasible path- waysto asustainable future, that meet “the needs of the presentwithoutcompromisingtheabilityoffuturegenerationsto meettheirown needs”[10].
Mathematicalmodels are essential tools to capture our knowledge of numerous and intricate causal relations between human activities and environmental impacts andtotranslatethemintoscenariosforsustainabledevel- opment[11–14].Thepowerofscenarioanalyseshasbeen clearly shown by the work of the IPCC. They define multiple greenhouse gas emission scenarios and make projections for global temperature development under eachscenariothatarenowwidelyusedinpolicymaking [15].Morerecently,IPBESwasestablishedasthebiodi- versityandecosystemfocusedanalogueofIPCC[16–18].
WithinthedomainofIPBES,weherefocusonfreshwater aquaticecosystemsandaimforscenariooutputonwater quality [19,20]. Freshwater aquatic ecosystems were instrumentaltotheformulationoftheecosystemconcept [21–23],areseenas‘sentinelsofclimatechange’[24]and providemany essentialecosystem servicesto humanity [25].Therefore,freshwateraquaticecosystemmodelscan stronglycontributetosustainabledevelopment.
State-of-the-art aquatic ecosystem models vary enor- mouslyin complexity.Lumpedmodelscomprising one or two non-linear differential equations [26] or even a
Figure1
Ecological system
Social system Novel
ecosystems
Eco- evolution
Doughnut Economics
Sustainable Development Goals
Current Opinion in Environmental Sustainability
Thechallengeofsustainabledevelopment.
DoughnutEconomicsandUNSustainableDevelopmentGoalsprovideasearchimageforasafeandjustfuturefortheinhabitantsofspaceship Earthbymeetinghumanneedswithinthemeansoftheplanet.Inthisstudywepresentreasonsandmeanstoincludeeco-evolutionary,novel ecosystemandsocial-ecologicaldynamicsinaquaticecosystemmodelsaswaterqualityscenarioanalysistoolsforsustainabledevelopment.
ThroughoutthisstudywerefertoLakeVictoriaasamicrocosmoftheevolvingnovelsocial-ecologicalsystemsthataretypicalofthe Anthropocene(Box1).
singlestatisticalrelation[27]representthe‘simple’endof this complexity spectrum [28]. They aim to generate insight in thedominantresponses of thesystem to the dominantstressfactors. Suchmodelshavebeenapplied successfullyto manyimportantecosystems onEarth,as wellastosocietal[29],medical[30,31]andpsychological [32] dynamic systems. On the ‘complex’ end of the spectrumareintegratedecologicalmodels[33]thatlink multipleecosystems[34]andcanbeappliedinecological management[35],andmodelsthatzoominonecological detail (e.g. individual-based models)[36],make projec- tionsonshortertimescales[37]orcombinesimplemodels withgoalfunctions(e.g.structuraldynamicmodels)[38].
Rather than arguing for the superiority of one of these approaches, we see considerable complementarity and redundancyamong them andargue thatwe canexploit suchmodeldiversitytogetamorecompletepictureofthe systemsunderstudy[39].
Most aquatic ecosystem models use a combination of correlations,patternsandcause-and-effectrelations,with process-basedmodelsmostexplicitlycoveringthelatter [40]. PCLake is a well-studied and well documented example of a process-based aquatic ecosystem model.
Originally developed for shallow lakes only [41], the model now also applies to ditches[42] and deeplakes [43],andawetlandversionisunderconstruction[44].In the scientific domain, PCLake has been successfully linkedto theoriesonalternativestable states[28],com- petition[45]andfoodwebdynamics[46].Intheapplied domain,themodelhasbeenembeddedin1D,2Dand3D hydrodynamical drivers [47] and multiple modeling frameworks [48],usedto assessclimatechange impacts on lake ecosystems [49], used to provide ecological dynamics for modeling contaminant distributions in aquaticsystems[50],andsuccessfullyappliedtoamuch widerrangeoflakeecosystemsindifferentclimatezones than themodelwasoriginally intendedfor[51,52].
Here wepresent threemajorchallengestoimprove the applicabilityofaquaticecosystemmodels—andecologi- calmodelsingeneral—forsupportingsustainabledevel- opment in this time of global environmental change (Figure1).Thefirstchallengearisesfromthenotionthat ifsocietalchangeleadstoenvironmentalchange,thiswill ultimately lead to adaptive responses in organisms and species through eco-evolutionary dynamics [53]. Sec- ondly,becauseeachspeciessolvesthe‘adaptivepuzzle’
inauniqueway,ormaygoextinct,thiswillleadtonew speciesinteractionsandnovelecosystemdynamics[54].
Thirdly,notonlyecosystemsbutalsosocietiesshownon- linearandsometimeshystereticresponsestostress,lead- ing to complicated social-ecological dynamics [55,56].
Thesechallengesarelogicallyarrangedalonganaxisof complexitythatrangesfromsingle individualsto whole societies.Inthispaperwerevieweachofthesechallenges and referto Lake Victoria asan iconic exampleof how
eco-evolutionary, novel ecosystem and social-ecological dynamicsinteract(Box1).
Eco-evolutionary dynamics
“Nothing in biology makes sense except in the light of evolution”(TheodosiusDobzhansky)
Adaptation is an essential and admired property of life and hence we need to consider it when we aim for understandingandprojectingfuturelife[57].Itinvolves both ecological and evolutionary mechanisms. Recent studiesconvincinglyshowthattimescalesofevolutionary adaptationoverlapwithecologicaltimescales,leadingto eco-evolutionarydynamics[53,58,59](Figure2).Yetthe majority of state-of-the-art aquatic ecosystem models largely ignore adaptation through ecological processes.
A partial exception to this is that many models put emphasisonplasticityoforganismsintheirstoichiometry withafocusonflexiblecarbontophosphorusandcarbon tonitrogenratios[60–62].However,mostmodelsignore many other well-known ecological adaptive responses,
Box1ThecaseofLakeVictoria.
Inthe1980s,theconcurrenteffectsoftheintroductionofNile perch(Latesniloticus)[78]andeutrophicationcausedLake Victoria’secosystemtoshiftdramatically[79]throughvariousof eco-evolutionaryadaptations(Figure2).Hundredsofendemic haplochrominespecieswentextinct[80,81],Nileperchbecame dominant,andothernativespecies,suchasthecypriniddagaa (Rastrineobolaargentea)claimedanewplaceinthefoodweb (Figure3).Thesetwoanthropogenicprocesses—speciesintro- ductionsandeutrophication—transformedtheecosystem’s functioningandstructure[82].Thisledtonewevolutionarypath- waysforthesurvivingnativespecies.Survivinghaplochromine cichlidshaveevolvedandadaptedtheirmorphology,dietsand mating[83].Differentspeciesappeartohavesolvedthe
‘adaptationpuzzle’inauniqueway[84],thusalteringtheflowof nutrientsandmatterthroughthefoodweb[82].Societieshave adaptedtothenovelecosystem’snewresources,buildingan importantexportindustryonNileperch—creatingnewand differentjobopportunitiesaswellasinfrastructureandland-uses inthewiderwatershed[85].Inturn,ever-evolvingsocietalneeds areshapingthedynamicsofLakeVictoria’secosystem,through fishingpressure,coastaldevelopmentandfurtherland-use changesthatinfluencethenutrientloadingofthelake[85](Fig- ure4).LakeVictoriaisamicrocosmoftheevolvingnovelsocial- ecologicalsystemsthataretypicaloftheAnthropocene(Figure1):
ithasbecomemorepopulated,andthroughtradeandtechnol- ogy,isincreasinglyconnectedtothebroaderworldaswellasto itsownresources,acceleratingratesofchange,aswellas increasingthevulnerabilityofpeoplestoglobaltradeandto resourcecollapse[86].SustainabledevelopmentforLakeVictoria impliesunderstandingthedynamicandevolvingnatureofsocial- ecologicalsystemsandboundariesofsocialneeds—asopposed toseeminglyfixedlimitstoresourcesorthresholdstoEarth systemdynamics—keepinginbalancetheratesanddirections ofchangesofhumanneedswiththoseofecosystemfunctioning.
suchas inducible defenses[63]or behavioral responses [64] to the presence of predators. Maybe even more importantly, adaptation of organisms to changing conditions through evolutionary mechanisms and their interactionwithecologicalprocessesineco-evolutionary dynamics is mostly ignored despite the empirical evi- denceoftheirimportance[65–67].
There are multiple ways to build adaptation and eco- evolutionary dynamics into process-based ecological models. Trait-based models incorporate adaptation by making a specific trait a state variable that is affected bythe adaptive process [69]. For example, Bruggeman andKooijman[70]definedafour-parameterphytoplank- ton model that minimizes physiological detail, but includes a sophisticated representation of community diversityandinter-specificdifferences.Trait-basedmod- elscancoverbothphenotypicplasticityandevolutionary dynamicsin theaveragetraitvalueofapopulation[71].
Individual-basedmodelsinsteadfocus ontraitvariation by modeling a sample of individuals that represents standing phenotypic or genetic variation [72,73]. A
fundamentaldifferencebetweentrait-basedandindivid- ual-basedmodelsisthatinthelatterevolutioncanbean emergent property, whereas in trait-based models the courseof evolutionisprescribedbythefitness function builtintothemodel[36,74].
LifeonEarthhasshownremarkableresiliencebyover- coming no less than five mass extinction events [75].
Therefore, there is no reason to doubt the adaptive potential of natureto overcome theongoingsixthmass extinction event [76]. At the geologic time scale (e.g.
millionsof years and longer,Figure 2 righthand side), macroevolutioncanbeexpectedtocounteractthecurrent ongoingmassextinctionandrestoreglobalbiodiversityto pre-extinction levels. In contrast to this, at short time scales (e.g. days and shorter, Figure 2 left hand side) ecologicalprocessessuchasdifferencesinalgalbuoyancy leadingto surfacelayersof algalblooms[37]or variable stoichiometry will dominate [77]. At the time scale of humangenerations(e.g.decades,Figure2center),how- ever,eco-evolutionarydynamicscomeintoplayandwill determine the survival, distribution and abundance of
Figure2
Time scale of adaptation
Mechanism of adaptation
response time within generation multiple generations geologic time Eco-Evo
Evo genotype sorting macroevolution
microevolution selection
mutation
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Current Opinion in Environmental Sustainability
Eco-evolutionarydynamics.
Biologicalsystemshavetwofundamentallydifferentmechanismstoadapttochangingenvironmentalconditions:throughecologicalor
evolutionaryadaptation.Withintheecologicaldomain,organismscanrespondatdifferenttimescalesthroughbehaviorandphenotypicplasticity tochanginglocalconditions,orevadethosechangingconditionsbymovementormigration.Communitiesofspeciescanrespondtochanging localconditionsthroughspeciessorting,orevadethoseconditionsbyrangeshifts.Noneoftheseresponsesrequiresevolutionthroughashiftin thegeneticmakeupoforganismsorspeciesbutmostoftheseresponsescreatenewselectionregimesandcanthusleadtomicroevolution.This microevolutioncantheninturninvokenewecologicalresponsesleadingtoeco-evolutionarydynamics.ThecaseofLakeVictoria(Box1) exemplifiessuchintertwinedeco-evostrands,wheredifferentcomponentsofthesocial-ecologicalsystem’sintergenerationalecological adaptationinfluencesthesocial-ecologicalsystem’sothercomponents.Forinstance,theNileperchboom-amulti-generationalrangeshift- resultedinbehavioralchanges,theexploitationofavailablephenotypicplasticity,migrationandhybridizationinthesurvivinghaplochromine cichlidspecies,potentiallyacceleratingtheirmicroevolution[68].Thecombinationofhaplochromines’microevolutionandplasticityintermsofdiet anddiurnalbehaviorcoincidedwiththecypriniddagaa’strophicnicheshiftandexpansionofitspopulation.Water-qualitychanges,shiftsinfish- speciescompositionsandtrophicrolesalsoinfluencespeciessortinginphytoplanktonandzooplanktoncommunities.Fromtheincreasingfishing pressuretothecreationofaneconomyandinfrastructurearoundinternationaltradethatfollowedtheNileperchboom,wecanfollowtheeco- evolutionoftheeconomicsystem.
speciesfor humangenerationstocome andtherebythe feasibilityof goalsset bytheSustainable Development GoalsorDoughnutEconomics.Eco-evolutionarydynam- ics shouldtherefore be includedin modelsfor scenario analyses toreachthesegoals.
Novel ecosystem dynamics
“There are more things in heaven and earth, Horatio, than are dreamt of in your philosophy” (William Shakespeare)
Adaptationsto,andextinctionsbecauseof,environmen- tal change will necessarily break up existing species interactions and create new ones [87]. For example, sudden changes such as dam construction can obstruct migration andlead toeco-evolutionary dynamicsin the alewife-zooplankton system [88].Slower environmental changes, such as climate change, mayresult in trophic mismatches in lakes [62] and create new species inter- actions due to range shifts [89,90]. Another important factor altering speciesinteractionsis thatof exotic spe- cies, here defined as species of which the dispersal capacityisaugmentedbyhumanactivity[91,92].Exotic
species may become invasive because they are better direct or indirect competitors [93], can benefit from disturbance, secrete novelchemicals, are released from theirnaturalenemies[94],oralternatively,becausethey carrytheirnaturalenemieswiththem,whicharelethalfor thenativespeciestheycompetewith[95].Thismyriadof new species and traits leads to novel ecosystems, with unique configurations and functioning [54] (Figure 3).
Herewedefinenovelecosystemsasthehuman-modified, engineered or built ecosystems typical of the Anthropocene.
Therearemultiplewaysto incorporatenovel-ecosystem dynamicsintomodels.ModelssuchasPCLakeautomati- callycovershiftsinphenologyandmismatchesthatmay arise because the life-history and phenology of all the model’s functional groups are temperature-dependent, with differential response curves [49]. As statedearlier, however, many other adaptive eco-evolutionary mecha- nisms are not covered by the model. And even more importantly,theprocessofspeciesextinctionandinvasion itselfisnotdynamicallymodelled.Theimpactofinvasive speciesisdifficulttocaptureinmodelsgiventhestochas- ticityinwhenandwheretheyarriveandinwhosecompany [96].Oncethisinformationisknown,theincorporationof specific invasive species, or even whole new functional
Figure3
Holocene Anthropocene
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Current Opinion in Environmental Sustainability
Novelecosystemdynamics.
SpeciesinteractionsinfoodwebsevolvedundertherelativelystableconditionsoftheHoloceneandwilldrasticallychangeduetorapidglobal environmentalchangeintheAnthropocene.Forexample,speciesinvade(1),potentiallyreplacingotherspecies(2),goextinct(3),havedifferential phenotypicresponsesleadingtoatrophicmismatch(4),oradaptbyexploitinganewresource(5),allleadingtonovelecosystemdynamics.In thecaseofLakeVictoria(Box1),theNileperchrepresentsanintroducedspecieswithanewpositioninthefoodweb(1),theintroducedNile tilapiaoutcompetednativehaplochrominecichlidspecies(2),swathsofbenthivoroushaplochromineswentextinct(3),somesurviving
zooplanktivoroushaplochrominesevolvedchangesinthemorphologyoftheirmouthsandadaptedtodifferentfoods(4)andfinally,dagaastarted eatingbiggerpreyinresponsetoenvironmentalchanges(5).Pleasenotethatwedidnotaimtomimicthetrophicpositionofeachofthese examplesfromLakeVictoriaintheabstractfoodwebshowninthefigure.
Figure4
Fishing intensity
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Current Opinion in Environmental Sustainability
Social-ecologicaldynamics.
Hypotheticalresponseoffishstockstofishingintensityandviceversainacoupledsocial-ecologicalsysteminspiredbyBox1in[107].PanelsI andIIdepictsocial-ecologicalcyclesofunsustainablefishery,panelsIIIandIVdepictsustainablefishery.Bluelinesrefertothedynamical propertiesoftheecologicalsystemandredlinestothedynamicalpropertiesofthesocietalsystem.PanelsIandIIIshowisoclineswithstable equilibriaassolidlinesandunstableequilibriaasdashedlines.PanelsIIandIVshowonlythestablepartsoftheisoclinesassolidlinesandthe catastrophictransitionsbetweenthemasdashedarrows.Becauseofstrongpositivefeedbacks,boththesocietalandecologicalstability landscapesexhibithysteresis(shadedzonesinpanelI).DifferentfromBox1in[107]wefocusonthesituationwhere:theunregulatedfishing intensityishigherthantheecologicaltippingpoint(panelIgapa)thustakingthesystemfromitspre-fisheryabundance(panelIIarrow1)through aseeminglyhealthyfisherywithlittleimpactonstocksize(panelIIarrow2)towardsacatastrophicshiftresultinginanexhaustedfishstock(panel IIarrow3);theexhaustionofthefishstockisdeeperthanthesocietaltippingpoint(panelIgapb)thusinvokingaregulatedfishery(panelIIarrow 4);theregulatedfishingintensityislowerthantheecologicaltippingpointforthefishstocktorecover(panelIgapc)thusresultinginarecovery ofthefishstock(panelIIarrow5);theabundanceoftherecoveredfishstockishigherthanthesocietaltippingpoint(panelIgapd)leadingto deregulationoffishingintensity(panelIIarrow6);thenthederegulatedfishingintensityisonceagainhigherthantheecologicaltippingpoint leadingtoanendlesslimitcycleofoverexploitation,regulation,recoveryandderegulation.Tobreakthiscycle,thesocietalresponsetoecological collapse(panelIVarrow7)shouldnotonlyimposeareductioninfishingintensitythatallowsthefishstocktorecover(panelIIIgape)butalso reduceoreliminatethehysteresisinthesocietalresponseandmaintainregulationafterstockrecovery(panelIVarrow8)thuscreatinga sustainablefisheryathighstocklevels(panelIIIpointf,panelIVpoint9).InLakeVictoria(Box1),sincetheintroductionofNileperch,fishing intensityhasincreased(goingfrompoints1to2inpanelII),riskingthecollapseofthestock(goingfrompoint2to3inpanelII).Toavertthis
groups,wouldrequirespecificbutpotentially simple model adjustments [97]. Theoptimization techniqueemployed in the BLOOMIImodelof phytoplankton dynamics isof particular interest when it comes to novel community dynamics[98].Insteadofspecifyingspecificspecies,this model defines the range of potential species. At any momentintime,theactualspeciescompositionischosen from this range based on an optimization goal such as biomassmaximization.
Recognizing the emergence of novel ecosystems will stimulate a new approach to ecosystem management and modeling. Until recently, the dominant view in ecologicalrestorationwasthatweshouldtry topreserve asmuchofthebiodiversityandnaturalareasonEarththat developed during the relatively stable climate of the Holoceneandwerestillinplaceattheonsetofthegreat acceleration[99].Withinthisparadigm,itseemedlogical tofocusourecosystemandlandscapemodelsonnatureas it once was. A full appreciation of the changes taking place in the Anthropocenehas given rise to aradically different view on ecological restoration [100] and the emergence of the concept of novel ecosystems [54].
Novel ecosystems are part of the human environment and niche, including urban, suburban, and rural areas [101,102], but also arise where most endemic species havegoneextinct,whetherornotdueto,butinanycase followed by, invasions of exotic species [103]. In the absenceofnaturalanalogs,modelsmightserveasvirtual realities of what might be possible within novel ecosystems.
Social-ecological dynamics
“Weusenaturebecauseit’svaluable,butwelosenature becauseit’sfree”(PavanSukhdev)
RootedintheseminalworkofHolling[104],itisnowwell established that ecological systems show non-linear responsestostressfactors,withthepossibilityofalterna- tive stable states [26]. This notion led to the term
‘ecological resilience’ to denote critical stress levels beyond which systems undergo a regime shift, which differsfromtheconceptof‘engineeringresilience’,which focuses onreturn timeto asingle equilibrium[105].In waterqualitymanagementecologicalresiliencetranslates into ‘critical nutrient load’ identification [51,106]. Pro- cesses in society also show non-linear and hysteretic responsestostress.Recently,Hughesetal.[107]pointed out that while human exploitation defines the stress
ecosystemsexperience,thedeterioratedecosystemstate willbeperceivedasastressfactorbysociety(Figure4).
Takinganexamplefromfisheries,Hughesetal.postulate that a coupled non-linear social-ecological system may move through acycleof fourstates (panelsI and IIin Figure 4). This cycle may repeat itself, or be broken through prudent management, reshaping the societal stability landscape (panels III and IV in Figure 4). By includingsocial-ecological dynamicsin ourmodels,and consideringsocial-ecologicalresilience,wemightbeable todevelopmorerealisticandencompassingmanagement scenarios forpathwaystowardssustainability[108].
Hysteretic responses of dynamical systems arise from positive,self-reinforcing feedbackloops.Suchfeedback loops can be revealed and studied through feedback diagrams to identify the dominant system components and their qualitative interactions (Figure 1 in [109]).
Subsequently,minimaldynamicmodelscanqualitatively capture specific feedback loops for bifurcation analysis.
Alternatively, more complex models may combine all interactionsconsideredtobeimportant,asPCLakedoes for lakeecosystems.Suchintegratedmodelsstillenable bifurcationanalysis,thoughwithmoreeffort[106].These three approaches are also valuable in studying social- ecological systems. For example, Downing combines connections across society, fisheries and limnology in feedback diagramsfor Lake Victoria, showing how the Nile perch fishery may go through the four phases in Figure 4[86].Figure4 depictssocial-ecologicalinterac- tionsarisingfromminimaldynamicmodels.Examplesof morecomplexmodelsthatincludesocial-ecologicalinter- actionscanbefound inIMAGE-GNM[110],MARINA [111]or VEMALA[112].Societyhaslongbeenembed- dedinmodelsasameasureofimpactontheenvironment.
Morerecently,throughtheecosystemserviceframework, somemodelscoverthedifferentusesoftheenvironment by societies. Ultimately, to close the social-ecological feedback loop, models should incorporate the dynamic and varying needs of societies thatshape these uses of ecosystem services and drive impacts on the environ- ment.[113].Coupledhuman-environmentsystemmod- els [114], hybrid modeling that combines a system dynamics with an agent-based approach [115] and dynamic modeling of ecosystem services and their socio-economic valuation [116] seempromising waysto include thosemutualsocial-ecologicaldynamics.
Asstatedin theintroduction,Sustainable Development Goals and Doughnut Economics aim to meet human needs within the means of the planet, and modelsare
(Figure4LegendContinued)situation,andfindastablesocial-ecologicalequilibrium(point9inpanelIV),responsestostockdeclinemustbe foundinsocietaldynamics(shapeoftheredisoclines).OnesuchinitiativemightbeecolabelingaimedtoreduceoverfishingofNileperchby effectivelyremovingtheroleofmiddlemeninthefishing-boattofilletingfactorytransaction.Ifsuccessful,thiswouldallowtighterresponsesin harvestingandpricingofthefishtoeliminateperverseincentivestofishmorewhenstocksgodown.Ithasbeenarguedhowever,thatsuchan initiativewillonlybeeffectiveifthesustainablefishingmethodinitselfoutcompetesother,unsustainablefishingmethods[86].
an essential tool to capture the mutual causal relations between human activities and environmental impacts.
While some claim that we are about to model all life onEarthinasinglecoherentmodel[117],wewouldlike to advocate a view on future model development for understanding social-ecological systems that is inspired by biodiversity.Within this view each model develops andshouldbejudgedwithinthecontextofitsniche.Just asnaturalbiodiversityischaracterizedbycomplementar- ityandredundancyamongcoexistingspecies,webelieve itisusefultomaintainahealthylevelofmodeldiversity and to employ the concept of ensemble runs [118] to allow social-ecological models to compete, show their fitnessand evolveintonewerversions[39].
Concludingremarks
“We [do these] things, not because they are easy, but becausetheyarehard”(JohnF.Kennedy)
Theevolutionofmodelssofarillustratesthatcombining fields of knowledge is more than an additive process becausecombined process dynamics can leadto emer- gentproperties.Thequestionisthen:howdowedesign satisfactorymodelstounderstand thedynamicsofeven relativelynarrowquestionsofwaterquality?Wesuggest thatafundamentalpartoftheanswerliesinrecognizing thesubjectivityofallscientificapproachesandmethods, from the questions asked, to the variables chosen to observeand measure, through amyriad of assumptions andperceptions.Toconstrainsubjectivities,onecanfirst provideexplicitcontextstothemodelingquestions:what timeandspacescalesdotheydelineate?andthentrian- gulateacrossfieldsofstudytoco-producetheknowledge behindthemodeldesign[119].Theexerciseisaprocess of transformingmultidisciplinarityto transdisciplinarity.
The studybyDowning etal. [86]for instance, wherea teamof40scientistsco-designedasharedunderstand- ing of the social-ecological system of lake Victoria – generalized to the level of the whole lake in the post Nileperchboomera–tooktimeandpushedmost,ifnot all, contributors outside their comfort zones, into the comfortzonesoftheircolleagues.Theproductisneither afinalnoranabsoluterepresentation of LakeVictoria’s socialecologicalsystem.Itnonetheless represents more thanthesumofitsparts,andisausefulbuildingblockin thedesignoffutureresearch questionsandmodels.
It is difficult to predict what tools for water quality scenario analysis will look like in, say, a decade from now.America’spoliticians,scientists,engineers,workers andtaxpayersweredeterminedandabletoputhumans ontheMoon,andreturnthemsafelytoEarth,withinthe seven year deadline set by John F. Kennedy in late 1962 [120]. Scenario analysis and computer simulation
playedanimportantroleinthiselectrifyingachievement, whichconfrontedhumanswithapictureoftheEarthwe liveon.Thiswasthestartofagrowingunderstandingof theuniqueness and fragility of system Earth. Here we make a plea for incorporating eco-evolutionary, novel ecosystemandsocial-ecologicaldynamicsinaquaticeco- systemmodelsas part ofthe contemporaryglobal chal- lengetobalancehumanneedswithplanetaryboundaries.
Itisanintriguingquestionwhetherthescientificmethod canhandlethisaddedmodelcomplexityandcanproduce modelsforscenarioanalysiswhichmeettherequirements ofmodelunderstandingandmodeluncertaintytomake them suitable as decision support tools. We will never knowif wedon’ttry.
“It always seems impossible until it’s done” (Nelson Mandela)
Conflictofintereststatement Nothingdeclared.
Acknowledgements
Thispaperisbasedondiscussionsamongtheauthorsduringandafterthe GlobalWaterQualityworkshopatWageningenUniversity&Researchin September2017anddiscussionsoftheGlobalEnvironmentalChange thememeetingsofNIOO-KNAW.Wewouldliketothanktwoanonymous reviewersfortheirconstructivecommentsandsuggestions.ABGJandMS werefundedbytheKNAWprojectSURE+(projectnumberPSA-SA-E-01).
RJMNwassupportedthroughagrantoftheNetherlandsOrganisationfor ScientificResearch(NWO,NetherlandsPolarProgramme,866.15.206).
ASGwassupportedbyaNWOInnovationalResearchIncentivesScheme grant(016.Veni.171.063).XKandMMPCweresupportedbytheAlexander vonHumboldtFoundationinGermany(AvHREF3.3-NLD-1189416- HFST-P).MCwassupportedbyaChineseScholarshipprogramme.JJK wasfundedthroughtheMarianneandMarcusWallenbergFoundation ResearchExchangeProgramonNaturalCapital,ResilienceandBiosphere Stewardship.STwassupportedbySTOWA(grantno.443.269).DLDwas supportedbytheU.S.GeologicalSurvey’sGreaterEvergladesPriority EcosystemScienceprogram.PGwassupportedbytheCityUniversityof NewYork.Thisispublication6626oftheNetherlandsInstituteofEcology (NIOO-KNAW).
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