Assessing resilience in long-term ecological data sets

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Assessing resilience in long-term ecological data sets

F. Müller

^a,∗

, M. Bergmann

^b

, R. Dannowski

^c

, J.W. Dippner

^d

, A. Gnauck

^e

, P. Haase

^f

, Marc C. Jochimsen

^g

, P. Kasprzak

^h

, I. Kröncke

ⁱ

, R. Kümmerlin

^j

, M. Küster

^k

, G. Lischeid

^c

, H. Meesenburg

^l

, C. Merz

^c

, G. Millat

^m

, J. Müller

ⁿ

, J. Padisák

^o

, C.G. Schimming

^p

,

H. Schubert

^q

, M. Schult

^k

, G. Selmeczy

^r

, T. Shatwell

^s

, S. Stoll

^f

, M. Schwabe

^t

, T. Soltwedel

^b

, D. Straile

^g

, M. Theuerkauf

^k

aInstituteforNaturalResourceConservation,DepartmentofEcosystemManagement,UniversityofKiel,24118Kiel,Germany

bAlfred-Wegener-InstitutHelmholtz-ZentrumfürPolar-undMeeresforschung,27570Bremerhaven,Germany

cLeibnizCentreforAgriculturalLandscapeResearch(ZALF),15374Müncheberg,Germany

dLeibnizInstituteforBalticSeaResearchWarnemünde,18119Rostock,Germany

eBrandenburgUniversityofTechnologyatCottbus-Senftenberg,D-15711KönigsWusterhausen,Germany

fSenckenbergResearchInstituteandNaturalHistoryMuseumFrankfurt,DepartmentofRiverEcologyandConservation,63571Gelnhausen,Germany

gLimnologicalInstitute,UniversityofKonstanz,Germany

hLeibniz-InstituteofFreshwaterEcology&InlandFisheries,Berlin,DepartmentofExperimentalLimnology,16775Neuglobsow,Germany

iSenckenbergamMeer,DepartmentofMarineResearch,26382Wilhelmshaven,Germany

jInstitutfürSeenforschung,Langenargen,Germany

kUniversityofGreifswald,InstituteofGeographyandGeology,17487Greifswald,Germany

lNorthwestGermanForestResearchStation,D-37079Göttingen,Germany

mNationalParkAuthorityWaddenSeaofLowerSaxony,26382Wilhelmshaven,Germany

nBavarianForestNationalPark,DepartmentofConservationandResearch,94481Grafenau,Germany

oDepartmentofLimnology,UniversityofPanonia,Egyetemu.10,8200Veszprém,Hungary

pInstituteforNaturalResourceConservation,DepartmentofEcohydrology,UniversityofKiel,24118Kiel,Germany

qUniversitätRostock,InstitutfürBiowissenschaften,AGÖkologie,18051Rostock,Germany

rMTA-PELimnoecologyResearchGroupEgyetemu.10,8200Veszprém,Hungary

sLeibniz-InstituteofFreshwaterEcology&InlandFisheries,Berlin,DepartmentofEcosystemResearch,12587Berlin,Germany

tNationalparkamtMüritz,17237Hohenzieritz,Germany

Keywords:

Long-termecologicalresearch LTER

Ecosystemresilienceandadaptability Spatio-temporalscales

Indicatorselection

a b s t r a c t

Inthispapertheconceptofresilienceisdiscussedonthebaseof13casestudiesfromtheGermanbranch oftheInternationalLong-TermEcologicalResearchProgram.Intheintroductiontheresilienceapproach ispresentedasonepossibilitytodescribeecosystemdynamics.Therelationswiththeconceptsofadapt- abilityandecologicalintegrityarediscussedandtheresearchquestionsareformulated.Thefocalresearch objectivesarerelatedtotheconditionsofresilientbehaviourofecosystems,theroleofspatio-temporal scales,thedifferencesbetweenshort-orlong-termdynamics,thebasicmethodologicalrequirementsto exactlydeﬁneresilience,theroleofthereferencestateandindicatorsandthesuitabilityofresilienceas amanagementconcept.Themainpartofthepaperconsistsof13smallcasestudydescriptions,which demonstratephasetransitionsandresilientdynamicsofseveralterrestrialandaquaticecosystemsat differenttimescales.Inthediscussion,someproblemsarisingfromtheinterpretationofthetimeseries arehighlightedanddiscussed.Thetopicsofdiscussionaretheconceptualchallengesoftheresilience approach,methodologicalproblems,theroleofindicatorselection,thecomplexinteractionsbetween differentdisturbances,thesigniﬁcanceoftimescalesandacomparisonofthecasestudies.Thearticle endswithaconclusionwhichfocusesonthedemandtolinkresiliencewithadaptability,inorderto supportthelong-termdynamicsofecosystemdevelopment.

∗ Correspondingauthorat:InstituteforNaturalResourceConservation,DepartmentofEcosystemManagement,UniversityofKiel,Olshausenstrasse75,D24118Kiel, Germany.Tel.:+494318803251;fax:+494318804083.

E-mailaddress:fmueller@ecology.uni-kiel.de(F.Müller).

Konstanzer Online-Publikations-System (KOPS) URL: http://nbn-resolving.de/urn:nbn:de:bsz:352-0-380160 Erschienen in: Ecological Indicators ; 65 (2016). - S. 10-43

https://dx.doi.org/10.1016/j.ecolind.2015.10.066

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1. Introduction

Withintheinternationallong-termecologicalresearchprogram atmanysitesaroundtheglobe,severalecologicalattributesand indicatorsaremeasuredandinterpretedinlongtimeseriesthatare mostlybasedontheecosystemapproach.¹Oneoftheirpurposesis anempiricalsupportbyprovidingdataandknowledgetoillustrate, proveorimprovetheoreticalconceptsorpractical management options.In ordertodemonstrate suchapplications,theinduce- mentofthetenthanniversaryoftheGermanLTERbranch²was usedtoarrangesomedata-basedcontributionsaroundtheques- tions“Canwecontributelong-termdevelopmentaldatatoanalyze theresilienceofecosystems?”and“Howcanwepositionresilience amongotherconceptionsofecosystemdevelopment?”

The ecological discussions about resilience started with Holling’sfundamentalpaperin1973andhaveprovokedalong- termcareeroftheconceptfromecologicalsystemsanalysis(e.g.

Gunderson and Pritchard, 2012; Walker and Salt, 2012) into social–ecological systems (e.g. Berkes and Folke, 1998), recent policyprograms(EuropeanCommission,2012),social–ecological strategies(e.g.Gundersonetal.,2012)andlaw(Garmestanietal., 2013). This development has been accompanied by resilience approachesinmanyotherscientiﬁcdisciplines,suchaspsychol- ogy,economics,sociologyortechnology.Theresultisanenormous amountof differentcomprehensions,vagueapproaches, diffuse termsandstronglyutilizedmetaphors.Withinthisbroadﬁeldit isadvisabletoconcentrate,andthereforethefocusofthispaperis putontherelationsofresilienceandthedynamicsofecosystems.

These ecosystems can be understood as nonlinear large- scale and complex, dynamic, thermodynamically open systems (Jorgensen,1992).Theyarecharacterizedbyfeaturesofintegrity, health, complexity, multidimensional stability, bufferand stor- agecapacity aswell asby specialdynamic characteristics such as observability, controllabilityand information processing and storage(Gnaucketal.,2010).Structuresinecosystemsarequal- iﬁed by physical, chemical and biological ecosystem elements andtheirspatio-temporalpatterns(Pahl-Wostl,1997).Functions arerelated totransfersandcirculationsof matteraswellasto energydepletion,tointerrelationsbetweenecosystemelements and interrelations between anecosystem and its environment.

Ecosystemsfurthermoremaybecharacterizedbytheirhighdimen- sionalityreferredtothenumberofstaticanddynamicelements andtheirbehaviour,bytheiruncertaintyofinterrelationswitha restricteddegreeofmathematicalcalculability.Therefore,ecosystems shouldbe consideredas stochasticallydisturbed dynamic systems(StraˇskrabaandGnauck,1985).

Analyzing key variables of ecosystem dynamics, De Angelis (1980),Pimm(1984),Pimmetal.(1991)aswellasGrimmetal.

(1992)andGrimmandWissel(1997)havediscusseddifferentcon- ceptsofecologicalstability.Especially,GrimmandWissel(1997) considered163deﬁnitions of 70differentstability concepts.At least, they found three different stability notions: Constancy,³ resilience,andpersistence.Theyunderstandstabilityasamulti- layeredconceptincludingtheconceptsofresistanceorelasticity (followingSchaeferandTischler,1983).Fromamathematicalview- point,Pahl-Wostl(2000)statedthatfourconceptsarerelatedto stability:resilience,persistence,⁴resistance,⁵andvariability.⁶

1http://www.ilternet.edu/.

2http://www.ufz.de/lter-d/.

3Constancy:thesystemstaysessentiallyunchangedafterapertubation.

4Persistence:demonstrateshowlongavariablelastsbeforeitischangedintoa newvalue.

5Resistance:measuresthedegreetowhichavariableischanged,followinga pertubation.

6Variability:thedegreetowhichavariablevariesovertime.

The international Resilience Alliance⁷ (Folke, 2006; Janssen etal.,2006)hasstronglyandsuccessfullysupportedtheconcept ofresilienceincombinationwithviabilitytheory(Martin,2004;

Martinetal.,2011)withinthecontextofsocio-economyandecol- ogy. The network focussed its interest onthe management of agent-based complex systems and theirfunctioning. Therefore, GrimmandCalabrese (2011)distinguishedanalytical (including constancy, resistance and engineering resilience of single state variablesandtheirdynamics)andsyntheticaspectsofresilience (coveringpersistenceand ecologicalresilience). Wewilldiscuss theﬁrstoftheseapproachesinthefollowing.

Inthispaper,resilienceisgenerallyunderstoodasadynamic indicatorofecosystembehaviouraftertheoccurrenceofadisturb- ance.Fig.1isdemonstratingtheprocessesfollowingadisturbance atasmalltimescale:attheleftside,aselectedindicatorvariable isdevelopingwithinarelativelyinvariablebasinofattractionof theecosystem.Attimed1apertubation⁸ishappeningwhichdoes notexceedtheresistanceofthesystem,thevalueseasilyreturn tothebasinofattraction.Atthemomentd₂thesystemexperi- encesadisturbance⁹withacertaindurationandabruptness,which changesthevalueoftheobservedstatevariablefromAdowntoB.In thecaseD₂,thevariabledoesnotrecoverandthesystemismoving towardsanewattractorstateasaconsequenceofaregimeshift.¹⁰ ThesecondtrajectoryCleadstoincreasingvaluesoftheobserved variable,reachingtheoldattractor’scharacteristicsagain.Inthis casewecantalkaboutresiliencewhichingeneralistheabilityof anecosystemtoreturntotheoriginalattractorstateafteradisturb- ance.Resiliencecanbeindicatedbythereturntimeoftherecovery dynamicsorbythemagnitudeofthedisturbance(F).

Fig.2takesintoconsiderationamuchlongertimeintervalin amodiﬁedversionoftheadaptivecycle(seee.g.Gunderssonand Holling,2002;Burkhardetal.,2011).Startinginapioneerstage,an ecologicalsuccessionproceedsslowlyprovokingasteadyincrease ofecosystemvariables,likeexergystoragewhichshowsaninter- linkedgrowthwiththeconnectednessofthesystem.Duringthis periodcomplexiﬁcation¹¹isadominatingdevelopmentalprocess.

Atthislong-termviewpoint,resilienceisrelatedtotheshorttime intervals,while thesystemis remainingin therecentattractor basin.Thisvaluerangeisnotconstant,butchangingoverthesuc- cessionalperiod,wherebyseveralindicatorsareincreasinginan orientormanner(Joergensenetal.,2007).Suchbehaviouriscalled adaptability,theabilityofanecosystemtodevelopinacomplex- ifyingsuccession,wherebycertainindicatorvalues(orientors)are steadilyincreasing(seeMülleretal.,2010a,b).

Alreadythesetwoviewpointsshowthatthetermresiliencecan beusedinseveraldifferentcontexts.Todemonstratethebroad rangeofthesecomprehensions,Table1issummarizingdifferent definitionsofresilience.Itisvisiblethattherearemanydifferent comprehensionsandthatwithinthetableacertaindevelopmentis documentedfrom“pure”ecologicalaspectstosocio-ecologicalsystems.Alsotheroleofchangeisvaluedindifferentcategories:while inthefirst,initialdefinitionthereturntotheprecedingattractor

7www.resalliance.org.

8Pertubation:Anychangeofexternalparameters,includingthoseinputswhich donotchangethebehaviour/stateoftheinvestigatedsystem.

9Disturbance:Apertubationwhichmodiﬁesthestateofthesystemor“anypro- cessthateffectsecosystem,community,orpopulationstructureand/orindividuals withinapopulationdirectlyorindirectlyviachangestothebiophysicalconditions”

(Standishetal.,2014).

10Regimeshift:Developmentofanecosystemafteradisturbancewhichleadsto newsteadystatesoutsidetheattractordomainoftheoriginalsystem.Thedomainof attractioncanbecharacterizedbythelong-termaveragevaluesandtheirvariability.

11Complexiﬁcation:Duringtheundisturbeddevelopmentofecosystems,inmany casesthecomplexitysteadilyincreases,tobeindicatede.g.bybiodiversity,hetero- geneity,cycling,storagerise,ﬂowarticulation,symbiosis,andothercharacteristics (orientors).

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.... G

^Duration

Old attractor state

Indicator Ecosystem

Variable

Magnitude

After White and Jentsch (2001)

f'ig. 1. Conceptual scheme on the potential behaviour of ecosystem variables after disturbances.

After White and Jentsch (2001 ).

domain is used as a target function, in the younger comprehensions, e.g. in the10thexampleinTable1, theabilityfordevelopmentfunc- tions as a goal of resilience. We will come back to these distinctions throughout the discussion chapter of this paper.

As dte comprehension of resilience is rather diverse, the quan- tification and indication also can be characterized by a high variability of approaches. There are two mainstreams, related to the terms "engineering resilience" and "ecological resilience". While the first one is assessed on the basis of the duration a system needs to return to the state it had before the disturbance (return time of focal variables after Pimm, 1984), the ecological resilience shall be measured by the magnitude of disturbance that can be absorbed before the system changes its structure, functions and controls (Gundersson and HoiJing, 2002; Peterson, 2002). We wiJI

Exergy stored

Resilient behaviour:

~ remaining in the old

basin of attraction

Renewal Reorganization

see that both approaches are related to interesting methodological challenges. Other proposals for resilience indication are related to the trend of an ecosystem to maintain ecosystem integrity when subject to a disturbance (Ludwig et al., 1997; Redman et al., 2000) or to the degree to which the system is capable of self-organization (Harrison et al., 2004). We will use the case-studies to see if these proposals are realistic from an empirical point-of-view.

As our case studies are generally linked with long-term approaches, we can build upon some papers in the literature on using long-term approaches to characterize the long-lasting development of resilience. For instance, Mirtl et aL (2013), Parr et al.

( 2003) and Red man and Kinzig (2 003) are investigating these items from general and conceptual viewpoints, while other authors are applying resiJience approaches to specific ecosystem types, such as

Maturity Conservation

~

Orlentor Behaviour

~ optimizing

>-

^ecosystemproperties ^emergent -t long·term trajectory

7

-ttl Adaptation

Connectedness Fig. 2. Resilience and adaptability during ecosystem development.

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Table1

Modiﬁcationsintheunderstandingsofresilienceatdifferentlevelsofintegration,afterBrand(2005).

Levelofcomprehension Deﬁnition Source

1 Originaldeﬁnition Measureofthepersistenceofsystemsandoftheirabilitytoabsorbchangeanddisturbance andstillmaintainthesamerelationshipsbetweenpopulationsorstatevariables

Holling(1973) 2 Disturbance-focused Magnitudeofdisturbancethatcanbeabsorbedbeforethesystemchangesitsstructureby

changingthevariablesandprocessesthatcontrolbehaviour

Hollingand Gunderson (2002) 3 Ecological–functional Capacityofasystemtoabsorbdisturbanceandreorganizewhileundergoingchangesoasto

stillretainessentiallythesamefunction,structure,identityandfeedbacks

Gundersson andHolling (2002) 4 Ecological–systemic (1)Capacityofasystemtoundergodisturbanceandmaintainitsfunctionsandcontrols,tobe

measuredbythemagnitudeofdisturbancethatthesystemcantolerateandstillpersist (2)Abilityofthesystemtoresistdisturbanceandtherateatwhichitreturnstothe pre-disturbancesteadystate(engineeringresilienceafterPimm(1984)

Carpenteretal.

(2001)

5 Ecological–quantitative (1)Theamountofchange(externalpressure)thesystemcansustainwithoutchangingthe domainofattraction

(2)Thedegreetowhichthesystemiscapableofself-organization (3)Thedegreetowhichthesystemcanbuildcapacitytolearnandadapt

Walkeretal.

(2002)

6 Social–ecological:

ecosystemservices

Theunderlyingcapacityofanecosystemtomaintainecosystemservicesinthefaceofa ﬂuctuatingenvironmentandhumanpertubations.

Deutschetal.

(2003) 7 Social–ecological:

societalprogress

Thecapacityofecosystemstosustainsocietaldevelopmentandprogresswithessential ecosystemservices

Folkeetal.

(2003) 8 Social–ecological:

functionsandservices

Resiliencereferstothemagnitudeofchangeordisturbancethatasystemcanexperience withoutshiftingintoanalternatestatethathasdifferentstructuralandfunctionalproperties andsuppliesdifferentbundlesofecosystemservices

Resilience Alliance(2010)

9 Explicitlynormative Maintenanceofnaturalcapital Ott(2001)

10 Dynamic:development Resilienceisthecapacityofasystem,beitanindividual,aforest,acityoraneconomy,todeal withchangeandcontinuetodevelop.Itisabouthowhumansandnaturecanuseshocksand disturbanceslikeaﬁnancialcrisisorclimatechangetospurrenewalandinnovativethinking.

Stockholm Resilience Center(2015)

11 Political:

transformation

Resilientsystemsinagriculturallandscapesareabletorecovertheirfundamentalstructure andfunctionalityinthefaceofchangeortotransformintonewregimeswherethishas desirableenvironmentalandsocialoutcomes

CGIAR(2014)

forests(e.g.Sanzetal.,2013;Chapinetal.,2010),agro-ecosystems (e.g.CabellandOelofse,2012),urbansystems(Redmanetal.,2004;

Evans,2011),landscapes(e.g.Cumming,2011a;Zurlinietal.,2014), coastalareas(e.g. Newton,2011), oceans(e.g. Mazzocchietal., 2012;Pugnettietal.,2013,orAdametal.,2011),freshwaterecosys- tems(e.g.Willisetal.,2010;JacksonandFuereder,2006;Shade etal.,2012),orarcticecosystems(e.g.Chapinetal.,2004;Prowse etal.,2006).Furtherelaborationsonlong-termresiliencehavee.g.

beencarriedoutbySymstadetal.(2003)withrespecttobiodi- versitydynamicsandVihervaaraetal.(2013)toinvestigatethe consequencesofclimatechange.

Thecontributionoflong-termecologicalresearchtotheknowl- edge about disturbance dynamics has been review by Turner etal.(2003).Theseauthorsemphasizethatespeciallylong-term researchcandetect,monitor,andunderstandunanticipatedevents, itiscapableofdeterminingtheofscaleandheterogeneity,show neglecteddynamicsofslowvariablesandincluderareevents(ﬁre, ﬂood,drought,hurricanes,insectpests,exoticspecies,landuse, climate)whicharenotdetectableatshorttime-scales.Asinmany casesspatio-temporalhierarchiesareconnectedwitharegulatory dominationbyconstraintsfromslow,long-termprocesses,long- termresearchcanbeextremely helpfulinbetterunderstanding thecontrolstructuresofecosystems.Therefore,weareaskingif long-termresearchisalsosuitableininvestigatingtheresilienceof ecologicalsystems.

Tofollowthisobjective,fourfocalquestionswillbeposed:

-Underwhichconditionscanweﬁndresilientbehaviourofecosys- temsintheinvestigatedlong-termdatasets?

-Which is the role of spatio-temporal scales? Is resilience restrictedtoecosystemdynamicswithinshort-termdynamics ordoesitalsoappearatlongertimescales?

-Whicharethe methodologicalrequirementstoexactlydeﬁne resilience?Whichistheroleofthereferencestateand which inﬂuencescanbeassignedtotheselectedindicators?

-Isresilienceasuitablemanagementconceptwithrespecttolong- termecologicaldynamics?Inwhichcasesshoulditbeusedas

a management guideline andin which casesshouldit not be applied?

Duetotheinterdisciplinaryconcept,therestrictedspaceand thecentralrole of casestudies,this article doesnot follow the traditionallengthandstructureofscientiﬁcpublications.Thereis nomaterialsandmethodssection;eithersomecharacteristicsare givenwithinthesinglecasestudydescriptionorthereisareference tooriginalpaperswhichprovidemuchmoredetailedinformation onthemethodology.Themainpartofthearticleisdedicatedto thecasestudyreports.Thecasestudiesarearrangedinasequence oftemporal scales(from longtermtoshorttermobservations), mainlyreferringtothedurationofthetimeseries.Eachcasestudy reportincludesanintroductoryparagraph,wherethedescribed processesandproblemsareexplainedandtherelevanceforthe objectivesofthepaperisdiscussed.Furthermoreinitialinformation isprovidedconcerningthestudysiteasanLTERresearcharea,the appliedspatialandtemporalscales,thefocalinvestigateddistur- bances,theappliedindicatorsandtheirindicanda,therespective referencepointsandthemethodofquantiﬁcation.Afterthecase studydescriptionstheresultsaresummarizedanddiscussedand someconcludingremarkswillbegiven.

2. Casestudies

The setof case studiescontains 5 terrestrialsites, 4 marine seascapesand3freshwatersystems.Withtheexceptionof“Haus- garten”,situatedintheFramStraitoftheNorthernAtlanticOcean, allsitesarepositionedinGermanland-andseascapes(seeFig.3).

The northern sites (Bornhöved Lakes, Serrahn,Uckermark) can becharacterizedbyrelativelyﬂatareaswhichhavebeenmainly createdbythePleistoceneglaciationsofNorthernEurope.Lange Bramke,BavarianForestandHessearesituatedinthelowmoun- tainrangeswhileLakeConstanceislocateddirectlyattheedgeof theAlps.Incontrast,thesitesWaddenSeaandNorderneyareparts oftheNorthSeaandtheDarß-Zingst-BoddenChainisa lagoon systemattheBalticSea.

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Table2 StabilitycriteriaafterGigonandGrimm(1997)appliedofthecasestudiesinthispaper.Formoreinformationonthestudysites,pleasevisittheLTER-Dwebsitehttp://www.ufz.de/lter-d/index.php?de=155838orLTER-Europe websitehttp://www.lter-europe.net/sites-platforms/lter-europe-mapES-approach=Ecosystemapproach. StabilitycriterionSitename Serrahnbeech forest(SER)LakeConstance (LAK)Darß-Zingst Boddenchain (DZB) Bornhöved wetlands(BOR)LangeBramke (LAN)Bayerischer Wald (BAY) Offshore Norderney (NOR) WaddenSeaof LowerSaxony (WAT) HesseRivers (HES)Bornhöved beachforest (BHF)

Uckermark (UCK)HAUSGARTEN (HAU)LakeStechlin (STE) Whichlevelof organization?Paleoecology LandscapeES-approach SeascapeES-approach SeascapeES-approach LandscapeES-approach WatershedES-approach LandscapeES-approach SeascapeES-approach RegionES-approach Fed.StateES-approach EcosystemES-approach LandscapeES-approach SeascapeES-approach Ecosystem Whichspatial scale?a∼300ha Profiles540km2 Samplesites∼800km2 Samplesites∼35km2 Samplesites0.8km2 Samplesites∼250km2 Samplesites∼50km2 Samplesites∼1400km2 Samplesites∼21,200km2 Samplesites∼0.3km2 Samplesites∼150km2 Samplesites∼100km2 Samplesites∼4.2km2 Samplesites Whichtemporal scale?b−10,000a→ Pollendyn.1960→ Annualdata1960→ Annualdata1970→ Sel.datac1980→ Annualdata1980→ Decadedata1980→ Annualdata1980→ Annualdata1990→ Annualdata1990→ 14days2000→ Dailydata1999→ Annualdata07-092011 14days Whichfocal disturbance?Landuse ClimateEutrophicationEutrophicationLanduse changesAcid depositionAirpollution andpestsClimate NOAClimate Wintercond.Invasions climateClimate DroughtClimate DroughtWarmwater anomalyClimate Storm Whichindicators?Plantspecies PollenPhosphourus PlanktonMacrophyto- benthosIntegrity indicatorsMatterfluxesTrees SpiderfaunaMacro-faunaBluemussel faunaFishcommunitySoilchemistryGround-water headMega-faunaLakechemistry Whichstability feature?ResilienceResilienceResilienceResilienceResilienceResilienceResilienceResilienceResilienceResilienceResilienceResilienceResilience Whichreference state?Conditions −6000abpConditions 1965Conditions ∼1980Conditions aldercarrsConditions 1975Conditions 1980Conditions 1980Conditions 1980Conditions 1990Conditions 1989Conditions 2000Conditions 2002Conditions 2011 Whichmethods?Soilandpollen analysisLimnological ES-analysisLimnological ES-analysisES-analysis ES-modellingSoilsolution analysisES-analysis StructureMarine ES-analysisMapping Biomass/areaFishing databaseSoilsolution analysisHydrological registrationFootageLimnological analysis Which uncertainties?→original literature→original literature→original literature→original literature→original literature→original literature→original literature→original literature→original literature→original literature→original literature→original literature→original literature Whichnormative loadings?dHistorical Recombina.Checkof restorationES-approach andprotectionCheckof restorationForest MonitoringES-approach, restorationES-approach andprotectionES-approach andprotectionIndicatortestForest monitoringES-approach andprotectionES-approach andprotectionES-approach andprotection aInthefirstrowthespatialextentisassessed,fortheresolutioninthesecondrow,discipline-specificsamplingsizeswereused bThefirstrowshowsthetemporalextent,whilethesecondrowinformsabouttheresolutionofthe(oftenaggregated)datasets. cSelecteddatafromcomprehensivemodeloutputs,measurementsandspace-for-time-investigations. dWithrespecttothenormativeloadingsitmightbestatedthatallparticipantsareworkingwithholistic,long-termecosystemapproachesandthattheauthorsfeelaresponsibilityforimprovingthestateoftheinvestigated ecosystems.Thus,inmostcases,resilienceisawelcomeappearance.

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Fig.3. Geographicalpositionsofthecasestudyareas.

Theresiliencerelated characteristicsofthesitesarelistedin Table2whichalsoprovidesinformationontheappliedmethod- ologies,thefocalscales,theinvestigateddisturbancesand their specialfeatures.Thetablealsoprovidesinformationonthebasic requirementsforstabilityinvestigationsasformulatedbyGigon andGrimm(1997).

Resilienceofforestecosystems–anexamplefromanancient beechforestoftheUNESCOWorldNaturalHeritagesiteSerrahn–

MüritzNationalPark(SER) (M.Theuerkauf,M.Küster,M.Schult,M.Schwabe)

Nationalparksareplacestoenjoy,experienceandlearnabout nature.AnappropriatemanagementofNationalParksrequiresa profoundunderstandingof ecosystemdynamics overlong time scales.However,suchlongtermperspectiveisusuallylimiteddue tothelackoflongtimeseriesofobservations.InMüritzNational Park,forexample,timeseriesofnatureobservationstypicallycover somemonthsoryears. Only4 seriescover upto25 years.The longesttimeseriesofforestobservationsavailablefromtheregion coversome150years–whichisstillrathershorttostudytheslow responseofforestecosystemsfollowingdisturbances.

InMüritzNationalParkthuspalaeoecologicalresearchisapplied toextendtimeseriesintothepast.Tostudyecosystemchangein thegreatestpossibledetail,palaeoecologicalstudiesinthepark coverbothvegetationandtheabioticenvironment,includingsed- iments and soils (e.g., Kaiser et al., 2002; Küster et al., 2012, 2014).Palaeoecological research started in thearea withinthe frameworkofanextendedecosystemresearchproject(Scamoni, 1963).Toexploretherelationshipbetweenlandscapepatternsand

vegetationdevelopment,Müller(1962)produced23 pollendia- gramsfroma10by10kmlandscapewithlargecontrastsinsoils andreliefconditions.Thisstrongfocusonecologicalquestionshas certainlybeenauniqueapproachinpalaeoecology.However,due tolow temporalresolution (mostly>200years) andthelackof independentdatingMüller(1962)waslimitedlyabletoaddress questions one.g. shortlivedvegetationresponse toe.g.human disturbance.MorerecentstudiesfocusontheLateHoloceneland- scapehistory,includingthehistoryoftheancientbeechforestsof Serrahn,whicharepartoftheUNESCOWorldNaturalHeritage.

Thetwomainquestionsofthisstudyare:(i)Whendidbeechfor- estestablishintheregion?(ii)Howdidbeechforestsrespondto humandisturbances?

Thecoldclimateofthelasticeageresultedinalargelyopen, treelesslandscape.WiththeonsetoftheHolocenewarmperiod 11,700yearsago,forestsagainexpandedandaround10,000years ago,densebroadleaved(withe.g.alder,elm,hazel,limeandoak) andconiferousforests(dominatedbypine)hadestablished.Beech wasinitiallyabsentfromtheseforests.Pollendatasuggestthatﬁrst (Fig.4),smallbeechpopulationsestablishedsome6000yearsago.

Onlyabout3000yearsagobeechstartedtoexpandandtoform widespreadforests.Itisstilldebatedwhybeechexpandedsolate innorthernGermany(andScandinavia).Ralska-Jasiewiczowaetal.

(2003)suggestthatthelateexpansionofbeechhasbeentriggered bya climaticshifttowardscooler andwetter conditions.Sofar thereispoorevidenceofsuchclimaticshift,however.Analterna- tivehypothesisisbasedontheobservationthattheexpansionof beechfollowsperiodsofintensehumanlanduse(e.g.Spangenberg, 2008;Bradleyetal.,2013).Thehypothesissuggeststhattheexpan- sionofbeechhasbeenaidedbyhumanactivity,i.e. beechonly expandedafterthepristineforestshadbeenopenedup.Itremains unexplained,whybeech,whichiswellabletoexpand indense shade,dependedonforestclearancetoexpand.Futureresearchin theareathusneedstofocusontheexactpatternand timingof beechexpansiontobetterunderstanditslateexpansion.

IntheMüritzregion,agriculturallandusestartedsome6000 years ago. Human activity since then can be characterized by repeatedchangesbetweenhighandlowlanduseintensities.Küster (2014)observedeightperiodsofincreasedsoilerosion,whichwell correspondtoperiodsofmoreopenvegetation,i.e.moreintense land use, recordedin thepollen data(Fig.4).While beechini- tiallyobviouslybeneﬁttedfromforestopeningduringtheBronze age/Ironageperiod,possiblymorethe50%ofbeechforestsinthe MüritzregionvanishedduringtheSlavonicsettlementperiodsand theMedieval.Inbetweentheseperiods,forestrecoverystarting withbirch(Betulapubescens/B.pendula), followedbyhornbeam (Carpinusbetulus)andthenbeechhasbeenobserved.Theseperiods oflowlanduseintensityaretooshort,however,forafullrecovery ofbeechforestsintheregion.

AlsotheWorldheritagesiteofSerrahnwithitsancientbeech forestshasbeenusedforfarminginformertimes.Astudyofsedi- mentsandsoilsfromSerrahnrevealedperiodsofintenselanduse resultinginsoilerosion,e.g.duringtheSlavonicperiodabout1000 yearsago(Fig.4).Duringtheseperiodspollendataclearlyindicate thatbeechwentlocallyextinctbutrecoveredafterabandonment ofthearea(Küster,2014).

Summarizing,itcanbestatedthatpalaeoecologyisasuitable tooltoprolongtimeseriesandthustostudylongtermdynamics offorestecosystems.Palaeoecologicalstudieshaverevealedthat beechonlyexpandedlateintheHolocene.Evidencesuggeststhat thepristine forestsofNorthernGermanyand Southern Scandi- naviahavebeen“stable”ecosystems,whichwereresilientagainst disturbancebybeechasanewforestelement.Onlyadditionaldis- turbancesduetohumanactivityallowedbeechtoexpand.Whythe expansionofbeech,whichiswellabletoestablishintheshade,was limited,isnotyetunderstood.Tounderstandthecausesofitslate

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Fig.4.ThehistoryofbeechintheMüritzarea(left)andintheareaofancientbeechforestsneartheWorldHeritagesiteSerrahn(right)asrecordedinproxiesofvegetation andsoilerosion(OSL:“opticallystimulatedluminescence”datings).PollendatafromLakeTieferSeeshowrecurrentchangesinpollendepositionofherbsandgrasses,which indicatechangesinlandscapeopennessoverthepast6000years.Atentativereconstructionofpastopenness(dashedline)indicatesthatduringseveralperiodsmorethan 50%ofthelandscapemayhavebeendeforested.Widespreaddeforestationtriggeredsoilerosion(blackcurves),whichisrecognizedatboththeregionalandlocalscale.

BeechexpandedintheareastartedduringthePre-RomanIronAge.Itreachedmaximumcoverduringthemigrationperiodwithlessintenselanduse,butagainlargely declinedtheintenselanduseintheSlavonicperiodandsincetheMedieval.

expansion,futurestudiesneedtoexploremoredetailsofbeech expansionbystudyingwelldatedsitesinhighresolution.Since beechestablishednearly3000years ago,itisahighlycompeti- tiveforesttreethatre-expandsafterrecurrentperiodsofintense landuse.However,regenerationtakescomparativelylong,sothat recoveryofbeechisnotcompletedinshorterregenerationperiods.

Furthermore,thiscasestudycandemonstratethatduringlongtime periodstherearehighprobabilitiesofexternalchanges,leadingto aseriesofnon-resilientbehaviouranddevelopmentaldynamics intonew,adaptedecosystemstates.

Responseofadeeplaketoeutrophicationandoligotrophication(LAK) (D.Straile,M.C.Jochimsen,R.Kümmerlin)

Cultural eutrophication is one of the most severe problems forthewater qualityof lakes(Schindlerand Vallentyne,2008).

Eutrophicationmayresultinhypolimneticanoxia(e.g.Barbieriand Simona,2001),extinctionofspecies(e.g.Vonlanthenetal.,2012) andbloomsoftoxiccyanobacteria(e.g.Taranuetal.,2015)thereby stronglyaffectinglakeecosystemservices.InmanyEuropeanlakes

eutrophicationacceleratedafter1945(Keatleyetal.,2011;Taranu etal.,2015),andoftenpromptedcountermeasures,e.g.theban ofphosphorus-containingdetergentsand/ortheestablishmentof sewageplants. Asa resultofsuccessfulphosphoruselimination inthecatchments,phosphorusconcentrationsdecreasedagainin manyEuropeanlakes(Jeppesenetal.,2005).

Thistypicalhistoryofdisturbanceandrecoveryfromphospho- ruspollutionisalsosharedbyLakeConstance,alargeanddeep per-alpinelakeborderingGermany,Switzerland,andAustria.Lake Constanceexperiencedsevereeutrophicationinthe2ndhalfofthe 20thcentury(Fig.5a)withtotalphosphorusconcentrationsduring wintermixing(TP_MIX)increasingmorethanoneorderofmagni- tudewithin30years(from7␮g/Lin1952to87␮g/Lin1981)and anequallyrapiddeclinepfTPconcentrations thereafter(within 27yearsbackfrom81␮g/Lto8␮g/Lin2007),whichmakesthe lakeideallysuitedtostudyecosystemresilienceandreversibility todisturbance.

Theresponseoftotalphytoplanktonbiomassandthebiomass ofdifferentphytoplanktongroups hasbeeninvestigatedforthe period1965–2007(Jochimsenetal.,2013).Duringthisperiodtotal phosphorusconcentrationsduringwintermixing(TP_MIX)increased from36␮g/Ltowards87␮g/L,anddeclinedthereafterto8␮g/L

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Fig.5. (a)Developmentoftotalphosphorusconcentrationsduringwintermixisand ofphytoplanktonbiomass(annualaverage)during1965–2007.TheOLScusumtest (Zeileisetal.,2003)suggests1989(95%conﬁdenceintervals:1988–1991)asthetim- ingofaregimeshift,(b)communitycompositionofannualaveragephytoplankton biomassduringthestudyperiod.

in2007therebypassingtheTPMIXlevelof1965in1990.Despite aroughly10-foldchangeinTP_MIXconcentrationsannualaverage phytoplanktonbiomassonlyvariedbyafactorof2(Fig.5a).Fur- thermore,annualaveragebiomasswasratherconstantduringthe ﬁrst25yearsofthestudyperiod(thereafterP1)–despiteroughly 2-foldvariabilityofTP_MIXconcentrations–andduringthelast15 yearsofthestudyperiod(thereafterP2),duringwhichTPMIXcon- centrationsdeclinedapproximately4-fold.Hence,phytoplankton communityshowedtwoperiodsduringwhichtotalbiomasswas resilientwithrespecttolargechangesintotalphosphorousconcen- trations.OnlyafterTPconcentrationsdroppedbelowaspeciﬁcTP concentration,phytoplanktonbiomassdeclinedrapidlytoapprox- imately50%ofthebiomassreachedonaverageduringP1.

BiomassstabilityduringP1wasassociatedwithcompensatory dynamicsof thedifferentalgal groups (Jochimsen etal., 2013), i.e.increasesofsomegroupswitheutrophication(centricdiatoms, chlorophytes,conjugates)from1965towardsthe1970s/early80s were offset by the declines of other groups (pennate diatoms, chrysophytes)(Fig.5b).Furthermore,communitycompositionwas reversibleduringtheshiftfrommesotrophictoeutrophiccondi- tionsandviceversa(fromapproximately35␮g/Ltowards87␮g/L andback)atthisleveloftaxonomicaggregation(Fig.6).Non-metric multidimensionalscaling(NMDS)ordinationshowsthatthestudy yearscanbenicelyseparatedbyphosphorusconcentrations.Fur- thermore,yearswithTP_MIX between20and70␮g/Lbeforeand aftermaximumTP_MIX(i.e.before1972andafter1983)arelocated nearby,i.e.,communitycompositioninthelate1960swassimilar tocommunitycompositionin1989,1990(Fig.6),whenTP_MIXhas decreasedtolevelstypicalforthelate1960s(Fig.5a).

Compensatory dynamics were only observed during P1 and not during P2 suggesting that only during P1, but not during P2,theymighthavecontributedtobiomassstability(Jochimsen etal.,2013).BiomassstabilityduringP2mightatleastbepartially duetoa reduction ofgrazing pressure.A databasedmodelling studyhasshownthatduringthespringbloom,controlofphyto- planktonpopulationgrowthratesdidstronglychangefrom1980 towards2007(Kerimogluetal.,2013).Whileduringtheearly1980s phytoplanktongrowthduringthespringbloomwashardyphos- phoruslimited,phosphorouslimitationwasthemostimportant

0.6 0.4 0.2 0.0 0.2 0.4 0.6 0.4 0.2 0.0 0.2

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Fig.6.NMDSordinationofthemainalgalgroupsduring1965–2007.Thethree ellipsesrepresent99%conﬁdenceintervalsaroundthecentroidsofthreegroups basedonTPMIX levels:TPMIX <20␮g/L(rightellipse,1997–2002),>70␮g/L(left ellipse,1972–1983),andTPMIXbetween20and70␮g/L(1965–1973and1984–1996, centricellipse).

factor reducing phytoplankton growth rates during the spring bloomsofrecentyears.Incontrast,springphytoplanktoncontrol by microzooplankton (ciliates) and mesozooplankton (Daphnia) grazersstronglydeclinedfrom1980to2007.Likewise,herbivory duringsummerwasfurtherreducedbythedeclineofzooplankton abundances(unpublisheddata).Thedeclineofherbivorywaspre- sumablyfurtherenhancedbychangesinzooplanktoncommunity composition,e.g.alargerdeclineofnon-migratingDaphniagaleata relativetomigratingDaphnialongispina(Straile,2015),becauseD.

galeatacontributestophytoplanktonlossesthroughoutdayand night,whereasmigratingD.longispinafeedsonepilimneticphy- toplanktononly duringnight-time.Possibly,theoverall decline ofherbivorecontrolcontributedtothestabilityofannualaver- agephytoplanktonbiomassduringP2andthustotheresilience ofphytoplanktonbiomasstoafurtherdeclineofphosphoruscon- centrations.

The response of phytoplankton to eutrophication and olig- otrophicationinLakeConstanceexhibitsvariousaspectsofresilient behaviourattwolevelsofecologicalorganization.Atthelevelof totalbiomass,phytoplanktonwasresilienttochangesinnutrient availabilityduringtwotimeperiodswithstrikingchangesinTP concentrations.Unfortunately,thetimeseriesdoesnotencompass theperiodofphytoplanktonincreasepriorto1965andthusitis notpossibletoanalyzewhethertotalbiomasstrajectories were reversible.Incontrasttototalbiomass,communitycomposition wasnotresilienttochangingphosphorusconcentrationsduringthe twoperiodsofbiomassstability.Rather,communitycomposition wastightlylinkedtototalphosphorusconcentrations,resulting inresilientcommunitydynamics,i.e.reversibilityofcommunity compositionwithdecliningphosphorusconcentrations.

Macrophytobenthosdynamicsinashallowbrackishlagoonofthe GermanBalticSeacoast(DZB)

(H.Schubert)

Brackishconditionshavebeenshowntoreducethenumberof macrozoobenthos(Remane,1934)aswellasmacrophytobenthos species(Schubertetal.,2011),restrictingtherealizationpotential

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Fig.7.Salinitydependencyofspeciesdiversity:Theﬁgureshowstherelationof speciesnumbersversussalinityformakrozoobenthos(line)andmakrophytoben- thos(dots)asobservedintheBalticSeabyRemane(1958,makrozoobenthos)and Nielsenetal.(1995,makrophytobenthos).

Fig. 8. Conceptual eutrophication model for the Darss-Zingst-Bodden after Schiewer(1994).

forsuccessiondrastically(Fig.7).Ifdisturbedby anthropogenic impactsas,e.g.eutrophication,brackishsystemsare thoughtto exhibitpronouncedchangesinspeciesoccurrences,expressedin standdensity and depthdistribution,rather than species composition.Thereasonforthisis seeninthereducedinterspeciﬁc competition,becausemanymarinespeciesreachtheirsalinitylimit underbrackishconditions.Thereducedspeciesinventoryleftis composedoforganismsabletothriveandreproduceunderbrackish conditions,butstillbeingfarfromtheiroptimum,thusintraspeciﬁc competitionisratherweak.

The LTER-site in focus here, the Darss-Zingst-Bodden-Chain (Fig.8),isoneofthefewexampleswheremacrophytecommunities ofabrackishwaterbodyhavebeenfollowedforseveraldecadesby repetitivesamplingoveraperiodofincreasingaswellasdecreasing eutrophication,drivingthesystemsfromameso-eutrophicstate tohypertrophicandbacktoeutrophicconditions(Schumannetal., 2009).

Theﬁrstdetailedsurveys,performedinthelate1930s,inprin- ciple showed the same species inventory as all later surveys;

justonespecies,Charatomentosa,couldnotbefoundduringthe period of heavy eutrophication. With increasing nutrient load between∼1960 and 1990 the following characteristic changes wereobserved:

-shiftincommunitystructurefrommacroalgae(Characeae)dom- inancytodominancyof phanerogams,thelatterincreasingin occurrence,butnotfullyreplacingthelossofmacroalgaebiomass andtherefore

-reductionofmacrophyte-vegetatedareasofthesystem,dueto both:

◦reduceddepthlimitofmacrophytecommunitiesand

◦reducedbiomassperareainthestillvegetateddepthzones.

Asuddendecreaseinnutrientloadoccurredin1989,mostprob- ablyduetoashiftintheprecipitationregimeofthecatchmentarea andstabilizedbychangesinagriculturepracticesinitiatedbythe politicalchangein1990.Themainresultwasareductioninnutri- entload,believedtorestorethemacrophytecommunitiesincase thatbistabilityofthesystemwillnotoccur.

Suchbistability(Scheffer,1998)hasbeendemonstratedforsev- erallimnetic systems. Verybriefly, bistability is theresult of a two-modeself-stabilizationbymeansofbioticinteractions.Under high-nutrient load conditions excessive phytoplankton growth suppressesmacrophytesbyshading.Macrophytestandsprovide shelterareasfor zooplankton, where theycanhide atdaytime, so losses by fish grazing are reduced, allowing efficient con- trol of phytoplankton by zooplankton grazing. This results in two self-stabilizing ecosystem states:a macrophyte-dominated state with low turbidity, where zooplankton grazing controls phytoplankton growth and a phytoplankton-dominated state, where macrophytes are almost absent because of high turbidity,leavingzooplanktonwithoutshelterandthereforeunableto controlphytoplankton growth.Butsince Jeppesen et al.(1994) demonstrated that at least one of the main stabilizing mecha- nismsdoesnotfunctionunderbrackishconditions,thequestion whether or not they occur in brackish systems is still not answered.

For thesysteminfocus here,Schiewer(1994)arguedabout theexistenceofbistability,becauseoftherathersteepgradients betweenHyper-andPolytrophicaswellasbetweentheEu-and Meso-/Eutrophicstates(Fig.8).Suchbistabilitywouldhamperthe re-establishmentoftheecosystemstatepresentbeforeeutrophi- cation in the courseof the process of remesotrophication. The followingecosystemstatesweredistinguishedbySchiewer(1994, seeFig.8):

I.oligo-mesotrophicconditions,before1969:nutrientlimitation;

lowbiomassofphytoplankton,dominatedbydiatomspecies;

submergedmacrophytes(charophytes)dominatingtheshallow areas.

II.meso-eutrophicconditionsbetween1969and1981:nutrient limitation,mainlynitrogen;increasingbiomassofphytoplank- ton,dominatedbygreenalgaeandcyanobacteria;submerged macrophytes(charophytesand potamogetonaceae)dominat- ingtheshallowareas.

III. eutrophic conditions: dramatic decrease in macrophy- tobenthos-cover.

IV.eutrophic–polytrophic conditions: irradiance limitation of phytoplankton,dominated bynano- and picophytoplankton species.

Schiewer(1994) assumed that becauseof bistability there- occurrenceofmacroalgaestandswilltakedecades,hisconceptual model(Fig.8)suggestedstrongbistability.

ButascanbeseenfromthedatasetgatheredbyBlümeletal.

(2002), consistingof therelative cover of macrophytesfor the individualpartsoftheBoddenchain,areestablishmentofmacroal- gaestartedalreadyin1995andreachedlevelscomparabletothe early1970salreadyataround2000,includingthere-occurrenceof theonlyspecieslostinbetween.Interestinglywatertransparency,