lake floodplain Spatial distribution abundance and of Unionidae mussels in aeutrophic Limnologica

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Limnologica

j ou rn a l h om ep a g e :w w w . e l s e v i e r . c o m / l o c a t e / l i m n o

Spatial distribution and abundance of Unionidae mussels in a eutrophic floodplain lake

Katarzyna Zaj ˛ac

, Tadeusz Zaj ˛ac, Adam ´Cmiel

InstituteofNatureConservation,PolishAcademyofSciences,Mickiewicza33,31-120Kraków,Poland

a r t i c l e i n f o

Articlehistory:

Received13March2015

Receivedinrevisedform5February2016 Accepted11February2016

Availableonline17February2016

Keywords:

Spatialdistribution Floodplainlake Eutrophication Habitatselection Bivalvia

a b s t r a c t

AlthoughUnionidaemusselsproducelargebiomassandreachhighdensityinfreshwaterhabitats,lit- tleisknownabouttheirecology.Westudiedthedistributionof5speciesoffreshwaterunionidsina eutrophicfloodplainlake,ontransects,alongthelakeshoreandacrossthedepthgradient.Theclamdis- tributionwithinthewaterbodywasnotrandom:allspeciesformacrowdedzonealongthelakeshore, showingthehighestdensityatca.0.5mdepth.Thedistributionofthemostnumerousspecieschanged alongtheshoreinAnodontaanatinaandUniopictorumbutnotinA.cygnea,whosenumbersremained constant.Thepopulationnumbersofthemostnumerousspeciesshowedapositivecorrelationwithsilt layerthickness.Thegeneralizedmodelofalltheanalyzedfactorsinfluencingtheunionids’distribution confirmedthisrelationandindicatedatrade-offbetweenwaterdepthanddistancefrombank,which mightberesponsiblefortheoccurrenceofthezoneatsomeoptimumdepth.Unionidshaveanimpor- tantinfluenceonfreshwaterecosystemfunctions,thustheirzonationimpliesthattheirfunctionsare alsospatiallystructured.

©2016ElsevierGmbH.Allrightsreserved.

Introduction

Ecologyisoftensaidtobeconcernedwithunderstandingthe environmentalandbiologicalfactorsresponsibleforthedistribu- tionandabundanceoforganisms.Thistaskisespeciallyrelevant inviewoftheneedtohaltthedramaticdeclineofoneofthemost importantgroupsoffreshwaterorganisms—musselsofthefam- ilyUnionidae (Strayer,2008).Theimportanceof unionidsrelies onspecificfunctionsthatstronglyinfluencethewaterecosystem, suchaswaterpurifying(Puschetal.,2001), nutrientsloadsand cyclingwithinthewaterecosystem(Strayer,2014),andevenout- sideit(Novaisetal.,2015).Mediatingnutrientsheterogeneitycan influencelocalbiodiversity(Spooneretal.,2013)andalsoprovide shelterorsubstrateforotherorganisms(VaughnandHakenkamp, 2001).

Thereasonsforthedeclineoffreshwatermusselsinthepast weremainlylargescalerivertraining,withthedominatingroleof impoundmentschangingthewaterregimeonalargescale(Vaughn andTaylor,2001)aswellasdramaticwaterpollution(Bogan,1993;

Naimo,1995).Themostimportantthreatforthefutureseemsto

∗ Correspondingauthor.Tel.:+48123703536.

E-mailaddresses:kzajac@iop.krakow.pl(K.Zaj ˛ac),tzajac@iop.krakow.pl (T.Zaj ˛ac),cmiel@iop.krakow.pl(A. ´Cmiel).

beinvasionsofalienspecies(Sousaetal.,2011).Morestudiesare stillneededonthedecline ofthefreshwater musselpopulation integrity (Strayer, 2008),however theinformation onreference populationsandtheirhabitatis stillscarce(‘the RiversofEden’

concept of Strayer, 2014). Under favorable conditions Unionids canreachaveryhighabundanceandbiomassthus,considering theirstrongrelationshipwiththeecosystem(Vaughnetal.,2004), boththeirincreaseaswellasdecreasecanmarkedlyinfluencethe ecosystem’sfunctioning.Theotherimportantroleoffreshwater musselsisindication:achangeinUnionidsabundanceanddistribu- tionmayreflectlessperceptiblebutimportantalterationstotheir habitat,suchasa decreaseofinterstitialdissolvedoxygenlevel (SparksandStrayer,1998;GeistandAuerswald,2007),watertur- bidity(Österlingetal.,2010),andachangeofhydrologicalregime (Watters,2000;Gatesetal.,2015).

The distribution of freshwater mussels in different types of water bodies is still far from being described and understood (Strayer,2008).Itisworthnoticingthatthespatialdistributionof musselsmayhavesignificantconsequencesfortheecosystem(e.g.

biogeochemicalhotspots,AtkinsonandVaughn,2015),becausethe mussels’distribution influencesthespatial distributionof their

‘services’,e.g.thematerialcapturedfromthewatercolumnisusu- allydepositedintheformoffeceswithinmusselbed(nutrients

‘focusing’,HowardandCuffey,2006);alsothenutrientsaccumu- latedbymusselsarereleased(intheformofdecomposingdead http://dx.doi.org/10.1016/j.limno.2016.02.002

0075-9511/©2016ElsevierGmbH.Allrightsreserved.

complanata(Lightfoot,1786) andAnodonta grandisSay,1829in LakeBernard(Fig.2inGhentetal.,1978),orbetweenAnodontasp.

andUniosp.inKortowskieLake(WidutoandKompowski,1968).

However,unionids are also regarded as a guild of suspension- feedingorganisms,forwhichsubstantialinterspecificdifferences hasnotbeensatisfactorilydemonstrated(Vaughnetal.,2008).

Inlentichabitatssomepatternssuggestingdepthoptimafor unionidsinhabitinglakeshavebeendescribedat0.5–2mdepth (Dillon,2004;Cyr,2008,butseealsoGoł ˛abetal.,2010)butthe dataarestillsparseandthespecificfactorsregulatingthevertical distributionofmusselsremaintobediscovered.Dillon(2004)sug- gestedthatbecauselight,temperature,foodandflowratedecline withdepth,musselsshouldliveasclosetothelakesurfaceaspossi- ble,andthatmortalityfactorssuchasfallingwaterlevel,thickiceor predationreducetheirnumberintheshallows.Someotherauthors addthedisturbingimpactof waves(Cyr,2008)orlittoral zone sedimentationfacilitatingyoungrecruitment(Cyretal.,2012).

In fact, similar generalfactors (i.e. light, wave action, flow) are responsible for one of the most striking features of lentic habitats—zonation(Weaver and Clements,1938; Nicholson and Aroyo,1975;Wetzel,2001).FollowingtheargumentsofWarren (2012)ontheutilityof speciesdistributionmodels(SDM;used insteadofdefiningecologicalnichemodelsENM),thelakezonation canbeeasilyand,forsomepurposes,sufficientlydescribedonthe basisofthreesimplevariablesreflectingthemainenvironmental gradientsofthistypeofhabitat:(1)horizontaldistancefrombank;

(2)ifthelakeissuppliedbyariver,thehorizontalgradientalong thedirectionalmovementofwaterthroughthelake;and(3)water depth.

Ofcourse,thelistofenvironmentalandbioticfactorsrespon- sibleforactualecologicalnichesandresultingspatialdistribution oftheunionidspecieswithinalakeisprobablyverylong,requir- ingalot ofefforttobeproperlyanalysed.Amongthem, oneof themostimportantecologicalfactorsrelated tothedistanceto theshoreis waveaction, which createsenoughturbulence not onlytoinfluencetheshorevegetation(Keddy,1984),butalsore- suspendparticulatematerial(Hiltonetal.,1986),whichcanbea substratebothforanchoringandsourceoforganicmatterasfood formussels.Distancealongtheflowcanreflect,forexample,the sedimentation(Hiltonetal.,1986)orinflowofvariousexogenous chemically–orbiologically–activecompounds(Richardsonand Mackay,1991).Depthinfluencesalake’sverticalzonationthrough itswell-known effects on primary production, oxygencontent, toxiccompoundsetc.(Wetzel,2001).Thislistshouldbesupple- mentedbythesedimentlayer,whoseroleisnotobvious:itcanbe atypicalanchoragesubstrateformusseladultsandjuveniles(Cyr etal.,2012);however,itcanbealsoanegativecomponentinter- feringwiththeirfeeding(Kat,1982)orrelatedtotheabsorptionof ammonia(Wetzel,2001).

Ifthereisa stronglinkbetweenthebasiclakeenvironmen- talgradientsandother,perhapsmorecomplexecologicalfactors, thenevenwithoutknowingalltheunderlyingprocesses,itshould bepossibletopredictthedistributionandabundanceofunionids simplyonthebasisoftheabove-mentionedthreemeasurements, which can operate like the Cartesian coordinate system for a

duringextensiverivertrainingworks.Haltofthelateralerosion causesthatfloodplainlakesarenolongercreated,withexisting onesdisappearing,togetherwithmusselsinhabitingthem,dueto biologicalsuccession(Zaj ˛ac,2002).

Afloodplainlakeoffersaperfectsiteforastudyintotheecol- ogyoflenticenvironments:thesetypesoflakesaresmallandtheir generalmorphological,hydrologicalandbiologicalprocessesare similar(e.g.zonation).Afloodplainlakeis animportanthabitat for bivalves(Brockand Van DerVelde, 1996; Zaj ˛ac,2002).We havemadeanextensivestudyoftheabundanceanddistribution of5speciesofunionidsintheZalewPi ´nczowski.Thisfloodplain lakeoffersaveryinterestingperspectiveforresearchofunionids becauseitcompriseallspecieswhichoccurinthistypeofhabitatin CentralEurope.Theaimofthestudywastodemonstrate,that,inan eutrophichabitat,unionidsarenon-randomlydistributedwithin thelake,andtheiroccurrencecanbedefinedusingsimplehabi- tatfactors.Wealsowantedtotestwhetherthesimplemeasures ofenvironmentalgradientsaresuitabletofindinterspecificniche differences infreshwater mussels, which would bereflected in theirspatialdistribution(Warren,2012).Followingthisapproach, weanalyzeddistributionofdifferentspeciesinrelationtodepth, distancefromandalongtheshore,andsedimentlayerand,consid- eringtheveryeutrophiccharacterofthelakeandexistingsmall flowofthewaterhomogenisingthedistributionofresources,we didnotexpectdifferencesinthedistributionofthemussels,when theirfoodisnotalimitingfactor(Vaughnetal.,2008).

Materialandmethods Studysite

ZalewPi ´nczowski(Fig.1)isanoldriverbedleftafterstraight- eningofthemainchannel.Constructionworkwascompletedin 1973.Atthetime ofthis studythewater bodywasin anearly stageofsuccession(sandbottom,novegetation).Theoldriverbed isblockedfromtheeastbyaroadbankanditsmaximumdamming heightis185.80ma.s.l.,withnopossibilityofregulatingthewater

Fig.1. GeneralviewofZalewPi ´nczowskilake,showingtransectslocalizationsand transectsamplingscheme.

Fig.2. ShapeofZalewPi ´nczowskibankanddistributionofmudwithinthestudiedarea.Thepresentedfiguresaresurfacesgeneratedbysplineprocedure(Statistica12.0), fittingwaterdepthandsiltlayermeasurementsfor273samplingplotsdistributedon13transectsalongthesouthernbank(20plotspertransect,every0.5m,perpendicular tobank,lakeoutlinegivenabove).

level.Thelakecovers11.35ha,itsmaximumdepthis1.54m,and itsvolumeis160,000m³.Itissuppliedbythechannelfollowing thepreviouscourseoftheriver,withwaterintakefromthenew mainriverchannel,1.8kmfromthelake.Watersupplytothelake isQ=0.17m³/s;flowisdetectableonlyinthechannelsupplying water(0.07m/s).Themainpartofthelakecontainsalmoststill water;watermovementthereiscausedratherbywindandtem- peraturedifferences.Waterexchangetakes8days(formoredetails, seeStru ˙zy ´nski,2007).

Theprofileofthelakebankisartificialonthenorthside(con- creteslabs)andnaturalonthesouthbank.Thesouthbankdescends moreorlessmonotonicallyto1–1.2mdepth, whereitbecomes approximatelyflat(Fig.2a).Ontheslopearesiltdepositsranging inthicknessfrom0to37cm;overlargeareasthelayeristhin(mean 5.97cm,SD=6.08;siltlayer<5cmthickin62%ofall273sampled plots;5–15cm thickin32%ofplots;>15cmthickinonly6%of plots;Fig.2b),tendingtoformathickeralluviumca.5mfrombank (Fig.2c).Thesiltcontains5.9%organicmatterasdeterminedbyash- ingasiltsample’spreviouslydriedconstantweight.Itisacolloid composedofloessparticlesoriginatingfromloesssoilsoccurring intheNidaValley.Thecolloidisdepositedonfinesand.

In Zalew Pi ´nczowski lake thewater pHis very high (mean 8.69, range 8.62–8.74 during summer, depending on site and time of measurement). Water conductivity was measured at 465␮S/cm(limestoneandgypsumareasincatchment).Thewater is highly eutrophic (mean chlorophyll content 104␮g/L (range 37.6–143.2␮g/L),withoutphosphorus.Meanoxygencontentwas 18.7mg/L,rangingfrom15.5mg/Lbeforedawn(3:00a.m.)nearthe bottom,to22.2mg/Lintheafternoon(2:00p.m.)nearthesurface (measurementsmade3September2002ontransectnos.3and4;

Fig.1).

Theamplitude of changes inthe water levelwas 51cm (30 August2003:71cm;8October2002:122cm).Theicelayerdur- ingaperiodoftypicalwinterfrost(−20^◦Cto−10^◦C)was51cm thick(24January2006,ourmeasurement).

The lakebank is overgrownwith a narrow strip of Phalaris arundinacea Linnaeus,1753and Glyceriamaxima (C.J. Hartman) O.R.Holmberg,1919,withsomeareascoveredbyCarexacutaLin- naeus,1753.Thewatervegetationshowszonation:toadistance of2.5–4m(mostlyca.3m)frombanktherewasacompactcar- petofCeratophyllumdemersumLinnaeus,1753,mixedwithElodea canadensisMichaux1803andHydrocharismorsus-ranaeLinnaeus, 1753,inmoreorlessequalproportions.Thistypeofvegetationwas extremelydense,growingfromthebottomtothesurface,filling 100%oftheareaofthiszone.Fromthiszoneto6mfrombankwas astripofdispersedstemsofPotamogetonsp.(<5stems/m²).The vegetationwasdevelopedalongthesouthernshoreofthebroad easternpartofthelakeandwasnotpresentinthenarrowwestern part.

Fieldprotocol

Thedatawerecollectedon8–12August2003.Alongthesouth- ernbankofZalewPi ´nczowskilake,13transects,each10mlong, weredemarcatedperpendiculartothebankatintervalsof50m.

Thetransectof10mlengthcoveredthewholebankslope:fromthe edgeoftheemergentvegetationtopracticallytheflatbottomofthe lake.Oneachtransectwaterdepthandthesiltlayerweremeasured every0.5m. Atthesamepointsbottomsampleswerecollected fromanareaof0.385×1musingadredgerake38.5cmwidewith nylonnetting(3mmmesh)(273samplestaken,21bottomsam- plesoneachtransect;Fig.1).Allthebottomsedimentwastaken toa20cmdepthandsieved,withthemusselsretainedintherake netting.Wheresamplingpointswereovergrownwithvegetation, orwheretwigsorlargepiecesoflitterwerepresent(whichcould interferewithsedimentsamplingbyblockingtheentrancetothe rakenetting),thatmaterialwasgentlyremovedpriortosampling andcheckedtoavoidoverlookingsmallmussels.

Statisticalanalysis

Thefrequencyofunionidsfoundinthebottomsamplesshows atypicalPoissondistribution,withzeroprevailingandsmallnum- bersofmussels(1,2,3...);thatiswhynonparametrictestsareused heretoanalysetheiroccurrence.Therelationofmusselnumberto waterdepthhasatypicalquadraticshape.ThePoissondistribution oftheresponsevariabledisallowstheuseofanyparametrictest toexaminethedatafittothequadraticfunction.Instead,follow- ingthemethodsusedinquantifyingstabilising(quadratic)natural selection(Broodieetal.,1995),wetransformedthepredictordata (e.g.waterdepth,distancefrombank)asdeviationfromthemean bysubtractingthemeanfromeachofthepredictorobservations (X_obs−Xm).Whenthesedeviationsweresquaredtheyweretrans- formedtopositivevaluesreflectingthedifferencebetweenagiven valueandthemean.AnegativerelationbetweenNmusselsand squareddeviationfromthemeanimpliesthatthequadraticfunc- tionisconvex(highestnumbersofmusselsfoundatdepthsclose tothemean).ApositiverelationbetweenNmusselsandsquared deviationfromthemeanimpliesthatthequadraticfunctionrelat- ingthemisconcave(highestnumberofmusselsfoundatdepths farfromthemean).BecausetherelationsbetweenNmusselsand squareddifferenceindeptharelinearaftersquaring,theycanbe testedwithnonparametrictestsassumingalinearrelation,suchas theSpearmanrankcorrelation.

Spatial autocorrelation tests whether similar (or dissimilar) valuesofgivenvariableclustertogetherinspace.Thespeciesdis- tributioninZalewPi ´nczowskilake(Table1)wasexploredusingthe globalMoran’sIstatistic(Moran,1948),whichtestsspatialauto- correlation:whethertherearerelationshipsbetweenlocationand

auto-correlationoccurswhenIMiscloseto+1(valuesareclustered together),negativewheniscloseto−1(dissimilarvaluesarenext toeachother);valueof0indicatesnoautocorrelation.

Itisreasonabletoassumethatthedistributionofmusselswithin thelakecanbecausedbycollinearand/ormultiplefactors,even withinthesimplifiedsystemofanalysisoftheirdistribution,e.g.

therelationbetweenmusseloccurrenceandthesiltlayermightbe acoincidencerelatedtothequadraticrelationofbothmusselnum- berandsilttothesamevariable,waterdepth.Inordertotackle thisproblem,wecalculatedageneralizedlinearmodel(GLZ),with thenumberofmusselsofagivenspeciesastheresponsevariable havingaPoissondistribution,anddistancefromthesoutherncor- ner(transectlocation,Fig.1),distanceperpendiculartothebank, waterdepthandsiltlayerthicknessaspredictors.Resultsofthis analysisenableanassessmentoftherelativestrengthanddirection oftheanalyzedrelationshipsseparatelyforgivenspecies,having controlledinfluencesofothervariables.

InFig.6wehavepresentedthenumberofindividualsfortwo speciesinrelationtothetwobasicdimensionsofthelake’seco- logicalgradients:distancealongtheshoreanddistancefromthe shore,asexamplesofvisualizingmodelsofmusselsdistribution.

Tovisualizethegeneralisedmusselsdistributionweusedspline 3Dsurfacesfittedtoactualquantitativedataontheiroccurrence in273samplingplotson13transectsalongtheshore,usingthe Statistica12package.

Results

AmongtheUnionidaewerecordedthefollowingfivespecies:

Anodonta anatina (Linnaeus, 1758), A. cygnea (Linnaeus, 1758), Pseudanodontacomplanata(Rossmässler,1835),Uniopictorum(Lin- naeus,1758)andU.tumidusRetzius,1788.Basicdatadescribing theiroccurrencearepresentedinTable1.Althoughalmostallof thestudiedspeciesshowedasignificantpositiveautocorrelation, indicatingthatnearbylocationsofsimilarattributevaluesaremore spatiallyclustered thanrandomlydistributed, thevalues ofthe globalMoran’sIaresmall(Table1).ThesignificanceofMoran’s Iisprobablycausedbythelargesamplesize(N=273)butitsvalue indicatesalowlevelofautocorrelation.

Distributionalongflow

Thetotalnumberofthetwomostabundantspeciesrecordedin eachoftheanalysed13transectsdecreasedalongthecourseofthe shore;theirnumbercorrelated negativelyandsignificantlywith transectnumber(i.e.thedistancefromthesoutherncornerofthe lake;Fig.3):A.anatina(r_S=−0.61,n=13,p=0.027)andU.picto- rum(rS=−0.64,n=13,p=0.018).However,A.cygnea,alsoamong themostnumerousspecies,showedvirtuallynopatternalongthe shoreline(r_S=0.04,n=13,p=0.886).Theleastnumerousspecies, U.tumidus,showedsomenegativetendencyofnumberofindi- vidualspertransect,butitdidnotchangesignificantlyalongthe shore(r_S=−0.39,n=13,p=0.191).ThesituationwassimilarforP.

complanata(rS=−0.48,n=13,p=0.099).

tivetrendalongthelakeshorewasmeansiltdepthpertransect (r_S=−0.55,n=13,p=0.049).Meansiltdepthpertransectwassig- nificantlycorrelatedwiththenumberofmusselspertransectfor bothA.anatina(rS=0.57,n=13,p=0.002)andU.pictorum(rS=0.60, n=13,p=0.031).

Verticaldistributionandwaterdepthoptimum

The most numerous species showed an evident tendency towarda squarefunctionrelationbetweenthenumberof indi- viduals in a given sampling plot and water depth, indicating some optimum at 0.4–0.6m depth (Fig. 4a–d). All thestudied speciesexceptfortheleastnumerousone,P.complanata,showed significantnegativecorrelationsbetweentheirnumberin273bot- tom samplesand the squareddifference betweenactual depth and mean depth: A. anatina (r_S=−0.47, p<<0.0001), A. cygnea (rS=−0.47,p<<0.0001),U.pictorum(rS=−0.48,p<<0.0001),and U.tumidus(rS=−0.24,p<0.0001),and nonsignificantforP.com- planata(r_S=−0.06,p=0.35).

Distancefrombank

Becausewaterdepthishighlycorrelatedwiththedistancefrom bank(r_S=−0.92,n=273, p<<0.0001), asimilarsquare function patterncouldalsobefoundintherelationbetweenmusseldistri- butionanddistancefrombank.Allthestudiedspecies,exceptfor theleastnumerousone,showedsignificantnegativecorrelations betweentheirnumberin273bottomsamplesandthesquareddif- ferencebetweenactualandmeandistancefrombank:A.anatina (r_S=−0.47,p<<0.0001),A.cygnea(r_S=−0.43,p<<0.0001),U.pic- torum(rS=−0.44,p<<0.0001),U. tumidus(rS=−0.18,p=0.003), andnonsignificantforP.complanata(r_S=−0.03,p=0.57).

Fig.3. DistributionofthetwomostnumerousUnionidaespeciesalongthebankof thefloodplainlake.

Fig.4. VerticaldistributionofUnionidaeinZalewPi ´nczowskilake:numberofindividualsfoundinagivensamplingplotversuswaterdepthofthatplot(P.complanatanot shownduetosmallnumberandlackofstatisticalsignificance).

Silt

Thenumberofclamsrecordedinsamples(includingsamples withnoclams)usuallyshowedapositiveandsignificantcorrelation withsiltlayerthickness,exceptforU.tumidus,whichshowedno significantrelationship(Table2).However,excludingthesampling plotswherenoclamswerefound(zerovaluesofresponsevariable) madethepreviouslysignificantrelationscompletelynonsignifi- cant,suggestingthatthepositiverelationsbetweenclamfrequency andsiltlayerreflectedonlybinomialdifferencesbetweensiteshav- ingnoclamsandtheothersites.

Interspecificdifferencesindistribution

TherewasvirtuallynodifferencebetweenUnionidaespeciesin thewaterdepthofoccupiedplots;theyalllivedatsimilardepths (Fig.5; H(4,433)=3.05,p=0.549)and insiltof similarthickness (Fig.5;H(4,433)=3.48,p=0.481).

Table2

CorrelationsbetweenthenumberofUnionidaeindividualsfoundinaparticular samplingplotandsiltlayerthicknessatthesamepoint.Thefirstanalysisincludes allsamples(alsowithemptysamples,withnomusselsfound);thesecondanalysis isbasedonlyonthesampleswheremusselswerefound(emptysampleswithout musselsexcluded),rS—Spearman’srankcorrelationcoefficient.

Nindividuals/plotvs: Allsamples Onlysamples withmussels

n rS p n rS p

A.cygnea 273 0.29 <0.0001 138 0.10 0.24

A.anatina 273 0.24 <0.0001 142 −0.07 0.41

P.complanata 273 0.13 0.03 8 0.42 0.31

U.pictorum 273 0.30 <0.0001 121 0.06 0.52

U.tumidus 273 0.05 0.39 24 0.01 0.97

However,siltlayerthicknessshoweda quadratic relationto waterdepthandthedistancefrombank(Fig.2b,c).Thecorrelation betweensiltlayerthicknessandthesquareddifferencebetween actualandmeandepth(r_S=−0.35,n=273,p0.0001)wasofthe sametypeasthecorrelationforsiltthicknessanddistancefrom bank(rS=−0.34,n=273,p0.0001).

TheGLZmodelsanalysingmusselnumbersinrelationtoother measuredenvironmental factors (Table 3)revealed that: (1) A.

anatinaandU.pictorumdifferedintheirnumberinrelationtotran- sectlocationalongtheflow;(2)A.anatina,A.cygneaandU.pictorum showedatrade-offbetweendistancefrombank(alwaysnegative) andwaterdepth(alwayspositive);(3)inA.anatina,A.cygneaand U.pictorumtherewasasignificantpositiverelationbetweensilt

Fig.5. DistributiondifferencesinwaterdepthandsiltlayerdepthbetweenUnion- idaespeciesfoundinZalewPi ´nczowskilake:aa—Anodontaanatina,ac—A.cygnea, pc—Pseudanodontacomplanata,up—Uniopictorum,ut—Uniotumidus.

Siltlayerdepth 0.04 0.010 18.8 0.00001 4.34

P.complanata Transect −0.14 0.111 1.6 0.20 ns

Distance −0.38 0.336 1.3 0.25 ns

Waterdepth 0.05 0.032 2.7 0.10 ns

Siltlayerdepth 0.11 0.043 7.1 0.008 2.66

U.pictorum Transect −0.07 0.018 16.4 0.00005 −4.05

Distance −0.15 0.059 6.4 0.011 −2.53

Waterdepth 0.02 0.006 19.7 0.00001 4.44

Siltlayerdepth 0.04 0.010 21.1 <0.00001 4.59

U.tumidus Transect −0.06 0.053 1.2 0.27 ns

Distance −0.17 0.180 0.9 0.34 ns

Waterdepth 0.02 0.017 1.8 0.17 ns

Siltlayerdepth −0.01 0.037 0.0 0.88 ns

layerthicknessandnumberofindividuals.Uniotumidusshowed nosignificantrelationtoanyofthestudiedpredictors.

Discussion

Unionids, asindicated by theMoran statistics,do notoccur randomlywithinZalewPi ´nczowski.Contrarytoourexpectations, theverticaldistributionoftheunionidsinZalewPi ´nczowskilake showsa verydistinctpattern (quadratic)versusdepthanddis- tancefrombank,whichcanbeinterpretedasakindofoptimal zonewhichspreadsalongthelakeshore,howeveratadifferent distanceasregardsdifferentspecies.An‘optimum’orquadratic patternalsooverlapswiththezoneofsiltsedimentation,though forthreespeciesthenumberofmusselsshowsasignificantrela- tionwithsiltthickness,independentoftherelationstotheother measuredvariables(Table3).OnlyU.tumidusshowednorelation toanyofthemeasuredvariables.

Therelationwithsiltthicknesscanbeunderstoodonthebasis ofsedimentationprocesses:smallparticlesofsedimentshouldbe expectedto settlein thesame placeswhere young individuals wouldbedepositedjustafterleavingthefishhost(Cyretal.,2012).

Otherfactorsmayalsoberelevant,suchasslightdisturbancesfrom watercurrentsordepositionoforganicmatter.Largesiltdeposits arefrequentlyassociatedwithun-ionizedammoniaNH₃,which istoxictomussels(Augspurgeretal.,2003).Un-ionizedammo- niais produced duringthe decompositionof organicmatter in oxygen-poorconditions;anoxygendeficitcanlimittheoccurrence ofUnionidaeinoldriverbeds(Zaj ˛ac,2002).InZalewPi ´nczowski lake,however,oxygenconditionsdeterioratewithwaterdepthat night,butaresufficientthroughoutthewholewatercolumnfrom surfacetobottom(ownunpubl.data).

Althoughthe‘optimal’zonewasthesamealongthewholelake bankforallspeciesexceptP.complanata,theabundanceofindi- vidualschanged:A.anatina(Fig.6a)andU.pictorumdecreasedin abundancealongthelakebank,whereasA.cygneamaintaineda quadraticpatternandstablenumber(Fig.6b).Thisdecreasesug- geststhatthegeneralcharacterofthelakedifferentiatestheniches ofA.anatinaandU.pictorum(highabundanceandhighpeakat

‘optimal’waterdepthinthewide‘lake-like’partofthewaterbody;

Fig.6a)fromthatofA.cygnea(aflatterdistributionwithregardto depthandstablenumbersalongthebank;Fig.6b).Thenegative

correlationbetweensiltlayerthicknesswithdistancealongthe shorecannotexplainthedecreaseofthesetwospecies,because therelationbetweenA.anatinaandU.pictorumabundanceanddis- tancealongtheshoreissignificantwhencontrolledfortheamount ofsiltinGLZanalyses(Table3).Itisalsocharacteristicthatthebank profiledoesnotchangethatmuchalongtheshore.

Fig.6. ‘Cartesian’(lengthalongtheshoreanddistancefrombank)distributionmod- elsofA.anatinaandA.cygneainZalewPi ´nczowskilake:a—A.anatinashowsa distinctivedepthoptimumbutitsabundancedecreasesupstreamandthenagain increasesslightlyneartheisland(lakeoutlineshownforcomparisonalongthe

‘transect’axis);b—A.cygneashowaflatterdepthoptimumandlittledecreasein abundanceupstream;c—putativemodelofenvironmentalgradientsinfluencingthe

‘optimum’distributionofA.anatina;sizeofdotsisproportionaltothenumberof overlappingpoints.

ThelownumbersofU.tumidusandP.complanataimplythatthey donotpreferthehabitatconditions(stillwater,highlyeutrophic), although U. tumidus also shows the depth optimum found for theotherspecies.U.tumidusisoneofthedominatingspeciesin themain channel ofthe NidaRiver(Korzeniaket al.,2004).In theSzeszupaRiver,whichflowsthroughasystemoffivelakes, U.tumiduswasdominating,incontrasttothelakes,lyinginthe samerivercontinuity(Lewandowski,1990).P.complanatagener- allyseemstodifferfromalltheotheranalyzedunionids.Haukioja andHakala(1974)reportedthatthedepthdistributionofP.com- planatadifferedfromotherunionidsinhabitingtheirstudysite.P.

complanatawasfoundtobethedominatingspeciesinanoligotro- phiclakebyO ˙zgoM.(pers.comm.).

Interestingly,intheflowingwaterofalakeoutlet,A.anatinaand U.pictorumoccupieddifferentsiteswithinandalongthechannel, indicatingdifferentecologicalniches:U.pictorumdominatednear thelake,whereasA.anatinawasmoreabundantca.0.5kmdown- streamandthendecreased(BronmarkandMalmqvist,1982).Ina studybyNorelius(1967),A.cygneaandA.anatinadecreasedbut U.pictorumincreasedalongthecourseofalakeoutlet.Thosetwo situationsaredifficulttocomparedirectlywithouroutcomesfrom ZalewPinczowskilakebecause,there,thedistributionofmussels wasstudiedinrunningwaterandinanoutlet,notwithinthelake.

However,BronmarkandMalmqvist(1982)suggestedthatthedis- tributionofmusselsalongthecourseoftheflowwasrelatedtofood availability(seealsoRichardsonandMackay,1991).Taking this intoaccount,theincreaseinthenumbersofA.anatinaandU.pic- torumalongtheflowinZalewPinczowskilakemightbeexplained byhigherprimaryandnear-bankproductionoffoodwithinthe widelake-likepartofthiswaterbody. ThiswouldimplythatA.

cygneareliesonadifferentfoodsource,whichisaccessibleacross thewholelake.

We do not know exactly which factors determineoptimum depth,althoughthemechanismproposedbyDillon(2004),i.e.light, temperature,fooddeclinewithdepth,mortalityfactorsstronger in shallows,seems likely.We shouldnotethat thedepthopti- muminZalew Pi ´nczowskilakeismuch shallowerthaninlakes ofglacial origin(0.5mvs 1m).Widuto and Kompowski(1968) reportedasimilarpeakdensityforU.tumidusandU.pictorumin theeutrophic Kortowskie Lakein Poland.Asshown in Table3, theabundanceofallspeciesexceptforU.tumiduswaspositively correlatedwithsitesofsiltdeposition.Musselabundancewasneg- ativelycorrelatedwithdistancefromthebank(allotherthings beingequal,theyoccurredmorefrequentlyclosertothebank).

In terms ofdepth (all otherthingsbeing equal)theypreferred deeperlocations.Thiscreatesopposingoptimum-formingfactors (Fig.6c).

Whatliesbehindthesefactors?Itiseasytoimaginethatachang- ingwaterlevel promoteshigher musselabundanceatagreater depth.Ifalake’swaterlevelfluctuateswithinarangeofca.0.5m, dependingondryingvs.precipitation,thenitcanbeassumedthat themusselswillescapefromnear-shoreshallowareas,wherethey arethreatenedwithdesiccationduringcontractionofthewater body.ThewaterlevelofZalewPi ´nczowskilakecanchangesignif- icantly,andquickly,especiallyinthesummer(seemethods).Such naturalandregularchangesinthewaterlevel,rangingfrom30to 50cmwithinamonth,havebeendocumentedforoldriverbeds in this area(Biela ´nskiet al., 2005).Other depth-relatedfactors includeicethickness(a0.5mlayeroficecontains allthewater volume0–5mfromtheshore;Fig.2a)andpredationfromwhite storksCiconia ciconia,theotter Lutra lutra, and muskrat Onda- trazibethicus(unpublishedobservations,Zaj ˛ac,2014)inshallow areas after contraction of the water body. On the other hand, sincedifferentkindsofmicroorganismsandorganicmatterpar- ticlesoreven dissolvedorganicmattercanbefoodformussels (Strayer,2008),andsincethebiomassofimmersedvegetationis

highnearthebank,thenear-bankareaislikely tobeasignifi- cantsourceofPOMandmicroorganismswashed outwardfrom theareaovergrown withplants bywaves (Hilton et al.,1986).

Thiscanberegardedasafactorpromotingtheshorewarddirec- tionofmusseloccurrence.Suchascenarioissupportedbydata fromCvancara(1972),whofoundthatmusselabundancediffered indepthatdifferentpartsofLongLake:theyoccurredata4–12m depthon a sandy/gravel bank,but only to a 1mdepthon the othersideof thelake,where mudand aquaticplants predomi- nated.Therelationshipwithdepthdoesnothavetobeassociated onlywithfood.Ahighertemperatureandoxygenationintheshal- lowsshouldprovidebettergrowthconditionsformussels;onthe otherhand,anight-timeoxygendeficitatdeeperlocalitiesand thepresence ofNH₃ might bea disadvantagetothem. Further detailed, small-scalestudiesofthesematters ofspeculationare required.

ItwaspointedoutbyVaughnetal.(2008),that“healthymussel communities typicallyoccurasmultispecies assemblages”.Tak- ingthisintoconsideration,wealsoobservedregularrecruitment ofjuvenilemusselsfromallspeciesin ourlake,sowecancon- cludethatwehavedescribedahealthymusselcommunitywhich shouldbetypical forwell-preservedfloodplain lakes.The large densityofmusselsinacertainzonewithinthelakealsoimplies thatspecificfunctionsplayedbymusselswithinalacustrinehabi- tat are also spatially restricted into the same narrow zone. It opensinterestingperspectivesforfurtherresearch.Accordingto ourresults,themussels’ecosystemfunctions(e.g.waterpurifica- tion,nutrientscycling)co-occurinZalewPi ´nczowskilakewithfine sedimentfocusing,whichisalsoasignificantabioticmechanism ofnutrientcycling(Mackayetal.,2012).Zonationofthemussels’

distributionmayalsointeractwithimportantbioticfactors(e.g.

parasiteoccurrence, Mülleret al.,2015),or lacustrinebiodiver- sity(e.g.therelationwithbitterlingRhodeussericeus,Smithetal., 2004).

Thepossibilityofdefiningthiszoneusingsimple‘xyz’measure- mentsprovidesthepossibilityofsavingeffortsintheprocessof environmentalimpactassessmentandinthemonitoringofeffects ofinvestment/conservationactions.Thefrequentlyappliedreloca- tionofmusselsthreatenedbyconstructionzones,shouldnotonly usetheseresultsfortheeffectivefindingofmusselsforreloca- tionbut,evenmoreimportantly,forelaborationofthecriteriafor selectingasuitablerelocationsite,takingintoaccountthevariable successofthisaction(CopeandWaller,1995).Thespatialdistribu- tiondemonstratedhereisconcordantwiththefindingsofAldridge (2000),whopostulatedthatsedimentremovalfromwatercourses shouldberestrictedtothemiddlepartofthechannel;accordingly, numerousprojectsofoxbowlakesrestoration, aimedusuallyat removaloforganicmatterfromthewaterbody,shouldcomplywith thisstandard.

Acknowledgments

We are greatly indebted to Tomek Wro ´nski for his invalu- ablehelpwithworkinthefieldandforanonymous“Substantial”

reviewerwhocontributedalottothispaper.Wealsowouldliketo thankMichaelJacobsforlineeditingthemanuscript.Thestudywas financedbyagrantfromthePolishMinistryofScienceandHigher Education(MNiSW;no.6PO4F09921)toK.Zaj ˛ac.

AppendixA. Supplementarydata

Supplementarydataassociatedwiththisarticlecanbefound, intheonlineversion,athttp://dx.doi.org/10.1016/j.limno.2016.02.

002.

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