Oxygen and carbon isoscapes for the Baltic Sea: Testing their applicability in fish migration studies
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Ecology and Evolution. 2017;1–13. | 1 www.ecolevol.org Received:28June2016 | Revised:18January2017 | Accepted:7February2017 DOI: 10.1002/ece3.2841 ORIGINAL RESEARCH Oxygen and carbon isoscapes for the Baltic Sea: Testing their applicability in fish migration studies Jyrki Torniainen1 | Anssi Lensu2 | Pekka J. Vuorinen3 | Eloni Sonninen4 | Marja Keinänen3 | Roger I. Jones2 | William P. Patterson5 | Mikko Kiljunen2 ThisisanopenaccessarticleunderthetermsoftheCreativeCommonsAttributionLicense,whichpermitsuse,distributionandreproductioninanymedium, providedtheoriginalworkisproperlycited. ©2017TheAuthors.Ecology and EvolutionpublishedbyJohnWiley&SonsLtd. 1NaturalHistoryMuseum,Universityof Jyvaskyla,Jyvaskyla,Finland 2DepartmentofBiologicalandEnvironmental Science,UniversityofJyvaskyla,Jyvaskyla, Finland 3NaturalResourcesInstituteFinland,Helsinki, Finland 4LaboratoryofChronology,Universityof Helsinki,Helsinki,Finland 5SaskatchewanIsotope Laboratory,DepartmentofGeological Sciences,UniversityofSaskatchewan, Saskatoon,SK,Canada Correspondence JyrkiTorniainen,NaturalHistoryMuseum, UniversityofJyvaskyla,Jyvaskyla,Finland. Email:[email protected] Funding information MajandTorNesslingFoundation,Grant/ AwardNumber:2010150,2011105,2012506 and2013040;AcademyofFinland,Grant/ AwardNumber:34139 Abstract Conventionaltagsappliedtoindividualshavebeenusedtoinvestigateanimalmovement,butthesemethodsrequiretaggedindividualsberecaptured.Mapsofregional isotopicvariabilityknownas“isoscapes”offerpotentialforvariousapplicationsinmigrationresearchwithouttaggingwhereinisotopevaluesoftissuesarecomparedto environmentalisotopevalues.Inthisstudy,wepresentthespatialvariabilityinoxygen ( δ18 OH 2O )anddissolvedinorganiccarbon(δ13CDIC)isotopevaluesofBalticSeawater. Wealsoprovideanexampleofhowtheseisoscapescanreveallocationsofindividual animalviaspatialprobabilitysurfacemaps,usingthehigh-resolutionsalmonotolith isotopedatafromsalmonduringtheirsea-feedingphaseintheBalticSea.Aclearlatitudinalandverticalgradientwasfoundforboth δ18 OH 2O andδ13CDICvalues.ThedifferencebetweensummerandwinterintheBalticSea δ18 OH 2O valueswasonlyslight, whereasδ13CDICvaluesexhibitedsubstantialseasonalvariabilityrelatedtoalgalproductivity.Salmonotolithδ18Ootoandδ13Cotovaluesshowedcleardifferencesbetween feedingareasandseasons.Ourexampledemonstratesthatdualisotopeapproachoffersgreatpotentialforestimatingprobablefishhabitatsonceissuesinmodelparameterizationhavebeenresolved. KEYWORDS isotopiclandscape,micromilling,modelevaluation,Salmo salar,spatialassignment, spatialinterpolation 1 | INTRODUCTION Several marking approaches have been employed to address questionsinmigrationecology.Untilrecently,conventionalextrinsicmarkers(i.e.,tags)appliedtoindividualshavebeenusedtoinvestigatetheir movement(Lucas&Baras,2000),butthesemethodsrequiretagged individualsberecapturedtoacquirespatialinformation.Duringrecent yearssomeinvestigationshavebeenconductedtostudylong-term movementsofindividualadultAtlanticsalmon(Salmo salarL.;Figure1) intheseausingtagsthatrecordenvironmentalcharacteristicsalong themigrationroutes(e.g.,Chittenden,Ådlandsvik,Pedersen,Righton, &Rikardsen,2013).However,duetothepresentsizeofthetags,the studiedfishhavetobelargeand,therefore,donotnecessarilyrepresentthemajorityofthepopulation. Intrinsicbiochemicalmarkerssuchasstableisotopescanprovide analternativeapproachtotrackindividualmovementsoverlargegeographical distances such as between continents (Hobson & Norris, 2008).All animals are isotopically marked by the environment they liveinandbytheirdiet.Theassignmentofanindividualtoacertain areaworksbyestimatingprobabilitiesofoccurrenceforanimalindividualsbycomparingvaluesobtainedfromtissuesamplestoisotopic landscapes(i.e.,isoscapes;Wunder,2010).Agreatadvantageinusing
2 | TORNIAINEN ET Al. biochemical markers is that they can be linked to those individuals that actually survived the migration to their breeding habitats, and therefore,betterrepresentthepopulation.Asfishotolithsarealmost completely mineralized from the carbonate of the environmental water(Kim,O′Neil,Hillaire-Marcel,&Mucci,2007;Patterson,Smith, &Lohmann,1993;Solomonetal.,2006),analysisandcomparisonof otolithandwaterstableisotopescanrevealthelocationswherethe otolithofanindividualfishisformed.However,ifthechosentissues/ materials are dissimilar, spatial assignment (matching of tissue and sourceisotopevalues)needsfractionationequationsbetweenthechosentissueandsourceisotopevaluesduetothedifferentfractionation oftheelementisotopesviaenvironmentalandphysiologicalfactors. Isoscapesofferpotentialforvariousapplicationsinenvironmental andecologicalresearch(Bowen,Wassenaar,&Hobson,2005;Dawson &Siegwolf,2007;Hobson&Wassenaar,2008),wherebytheisotope valuesofselectedtissuesarerelatedtoenvironmentalisotopevalues, andnotjustoneelement,butseveralelements(i.e.,multi-isotopeisoscape;e.g.,Hobsonetal.,2012;García-Pérez&Hobson,2014).The mostambitiousapproacheshavebeentheconstructionsofisoscapes onaglobalscale(e.g.,Amundsonetal.,2003;Bowen&Revenaugh, 2003;LeGrande&Schmidt,2006),whereseveralstudieshaveledto convincingresultsregardinganimalmigrationamongmanytaxainterrestrialandaquaticenvironments(Best&Schell,1996;Chamberlain, Bensch, Åkesson, & Andersson, 2000; Hanson, Wurster, EIMF, & Todd,2010,2013;Hobson&Wassenaar,1996;Wassenaar&Hobson, 1998).However,althoughinformationaboutanimalmovementsand spatialusageoftheirhabitatsattheintercontinentalscaleisimportant inecologicalresearchandconservation,manycrucialeventsoccuralso atsmallerscaleswithinthedistributionofsmallerdistancemigrants. Unfortunately,theavailabilityofisoscapedataforstudiesatamore localspatialscaleappearstobesparseorthedistanceofthesurvey stationsofglobalisoscapedatamaybetoolargeforadequatelocal isotopicdiscrimination(seeBowen&Revenaugh, 2003).Therefore, additionalisotopicdataareneededtoincreasetheresolutionofglobal isoscapestoenablemoreprecisereconstructionofanimallocations andmovement. Theaimsofthisstudywere(1)toprovidehorizontalandvertical isotopicgriddeddatasets(i.e.,isoscapes)ofoxygen( δ18O H 2O )anddissolvedinorganiccarbon(δ13CDIC)forthewateroftheBalticSea.(2) Asanexamplewedemonstratethepotentialoftheseisoscapesusing twoAtlanticsalmon individuals fromthe River Simojoki.Combined withtheisotopedatafromthesalmonandspatialprobabilitysurface maps,weshowprobablelocationsofindividualfishinvarioustime pointsduringtheirsea-feedingmigrationphaseintheBalticSea.We alsodemonstratehowparameterizationofthemodelsinfluenceson locationestimates. 2 | MATERIAL AND METHODS 2.1 | Sampling and isotope analyses of water BalticSeawatersampleswerecollectedduringthreedifferentcruises bytheR/VArandaoftheFinnishEnvironmentInstitute(SYKE).To evaluateapossibleseasonalimpactonseawaterisotopevalues,we collectedtwosummersetsandonewintersetofsamples.Thedates ofthecruiseswere(1)24Mayto11June2010,(2)9Augustto27 August2010,and(3)17Januaryto3February2011.Thefirstcruise coveredthewholeBalticSeafromtheBothnianBaytotheSouthern BalticProper,excludingtheGulfofFinland(Figure2),whichwasthe onlyareasampledduringthesecondcruise.Thethirdcruise,inwinter,coveredtheBalticSeaexceptareassouthofGotland.Seawater wassampledatadepthof10mfromeverysamplingstation(altogether316samplesfrom134stationvisits,blackdotsinFigures3 and4).From25stations,waterwasalsosampledverticallyat5–50m FIGURE1 Atlanticsalmon(Salmo salar) FIGURE2 MapoftheBalticSeawiththelocationoftheRiver Simojoki(uppermostrightcorner).Themarkedpathwaysshow transectsusedforcreatingverticalinterpolationsinFigure4
| 3 TORNIAINEN ET Al. intervalsdependingonwaterdepthatthesite(Figure4).Maximum distancesbetweensamplingstationswerelessthan100km.Water samples were taken using a CTD/Rosette sampler (Rosette 1015, Seabird,SBE911/GeneralOceanics,SIS:Plus500). Rosettesamplerrecordsconductivity,fromwhichsalinitywasautomaticallycalculated.Fromeverysamplingoccasionofwaterforisotopeanalysispurpose,salinitywasrecorded.Samplewatercollected for δ13CDICanalysis,wereinjectedinto12-mlborosilicateExetainer vials(cat.no438B;LabcoLtd.,HighWycombe,UK)preparedinthe laboratory,where0.2mlof85%orthophosphoricacid(H3PO4)was addedintoeachvial,whichwasthensealedwithacap(containinga rubberseptum)andflushedandfilledwithaheliumatmosphere.In thefield2–4mlofseawaterfromeachstationandsampledepthwas injectedthroughtherubberseptumintothevial.Samplewater for δ18O H 2O analysiswerecollectedin20-mlglassscintillationvialsand filledfullensuringnoairbubbles.Allsampleswerestoredinanunlit FIGURE3 Interpolatedmapsforthe BalticSeaof δ18 OH 2O values(a,b)and δ13CDICvalues(c,d)from10metersin summer(a,c)andwinter(b,d).Blackdots representsamplinglocations (a) (c) (b) (d) Longitude(E) Latitude(N) –7 –8 –9 –10 2 1 0 –1 –2 510 15 20 25 30 35 510 15 20 25 30 35 66 64 62 60 58 56 54 66 64 62 60 58 56 54 Summer Winter δ18O(‰)δ 13C(‰) FIGURE4 Interpolatedcross-sectional surfacesofvertical δ18 OH 2O andδ13CDIC values. δ18 OH 2O valuesfromsouthtonorth in(a)summerand(b)winter,andfromwest toeastin(c)summerand(d)winter.δ13CDIC values,fromsouthtonorthin(e)summer and(f)winter,andfromwesttoeastin (g)summerand(h)winter.Blackdots representsamplinglocationsanddepths (a) (b) (c) (d) (e) (g) (f) (h) δ18O (‰)δ 13C (‰) Depth(m) 0 100 200 300 0 50 100 150 –5 –6 –7 –8 –9 –10 –11 –5 –6 –7 –8 –9 –10 –11 20 22 24 26 28 20 22 24 26 28 56 58 60 62 64 56 58 60 62 64 Longitude(E) 2 1 0 –1 –2 –3 –4 –5 2 1 0 –1 –2 –3 –4 –5 0 100 200 300 0 50 100 150 20 22 24 26 28 20 22 24 26 28 56 58 60 62 64 56 58 60 62 64 Latitude(N) Longitude(E) Latitude(N) Summer Winter
4 | TORNIAINEN ET Al. refrigerator(+4°C)inadarkroompendinglaboratoryanalysis.Inthe laboratory,similarvialsasusedforδ13CDICsampleswerefilledwith 0.5mlseawaterandequilibratedwithCO2foratleast24hrat25°C. Analysesofsamplesstartedwithinaweekafterarrivaltothelaboratory,firsttheδ13CDICsamplesimmediatelyafterarrival.Theδ13CDIC valuesareexpressedrelativetoVPDB(ViennaPeeDeeBelemnite), measured and calibrated/normalized against international IAEA (InternationalAtomicEnergyAgency[IAEA])standardsNBS19(orTS- Limestone;Calciumcarbonate,δ13C=+1.95‰)andLSVEC(Lithium carbonate,δ13C=−46.6‰);±0.14‰.Valuesareexpressedrelativeto VSMOWandcalibrated/normalizedtotheVSMOW(ViennaStandard Mean Ocean Water [VSMOW], δ18O=0‰)—SLAP (Standard Light AntarcticPrecipitation,δ18O=−55.5‰)scale;±0.1‰.Allwatersampleswereanalyzedforbothδ13CDICand δ18O H 2O attheLaboratory of Chronology, Finnish Museum of Natural History, University of Helsinki, using a GasBench II and Delta Plus XL (Thermo Fisher Scientific,Bremen,Germany). Statisticaltestingofseasonaldifferencesin δ18O H 2O andδ13CDIC values(pairedsamplesttest)wasperformedusingPASWStatistics18 forWindows(SPSSInc.,Chicago,IL,USA).Interpolatedisoscapesfor δ13CDICand δ18O H 2O wereconstructedusingOceanDataView(ODV) softwareversion4.5.5(Schlitzer,2002,2011). 2.2 | Otolith sampling, micromilling and stable isotope analysis In order to test applicability of Baltic Sea isoscapes in fish migrationstudies,weanalyzedotolithsfromtwoexamplefemaleAtlantic salmon(hereafterBalticsalmonorsalmon)originallycaught,asthey werereturningtotheRiverSimojoki(Figure2)tospawnin2008,by theNaturalResourcesInstituteFinland(LUKE)aspartoftheprogram tomonitoryolk-sacfrymortality(M74syndrome:e.g.,Keinänenetal., 2012; original LUKE code numbers SS5447 and SS5461, hereafter FISH1and2,respectively).Bothsalmonhadspenttwoyearsfeedinginthe sea.Theorigin (wild orhatchery-reared) andage of the salmonwasdeterminedfromthescalenucleusandscalegrowthpattern(Hiilivirta,Ikonen,&Lappalainen,1998).FISH1wasofwildorigin (5,300g,80cm)andFISH2wasofhatchery-rearedorigin(6,300g, 81cm). Both sagittal otoliths were removed from the head of the salmon,cleanedindeionizedwatertoremoveanyremainingorganic tissue,anddriedovernightat60°C. Bothotolithsweresampledforδ13Candδ18Oanalysisusingthe custom-built three-dimensional computer-controlled micromilling systemintheSaskatchewanIsotopeLaboratoryattheUniversityof Saskatchewan following the procedure of Wurster, Patterson, and Cheatham(1999).Thissystemallowed31–32samplingpathstobe followed concordantwith growth banding in both otoliths. Isotope ratios of samples were determined using a Finnigan MAT 253 directlycoupledtoaKiel-IVautomatedcarbonatepreparationdevice (Thermo–Fisher Scientific).Accuracy and precision were monitored byroutineanalysisofNBS-19standard,yieldingastandarddeviation forreplicatestandardsthatwasconsistentlylessthan0.09forboth δ13Oandδ18Ovalues.Allotolithisotopemeasurementsarereported inthestandarddeltanotation(permil)relativetotheVPDBstandard asδ18Ootoandδ13Coto.Fromtheotolithdataofeachsalmon,three samplemillingpathswereselectedforcloserinspection,namely1st seawinter(1SW),thefollowingsummer(2SS),andthe2ndseawinter (2SW)toassignthesalmontoBalticSeaareasforeachperiod.During theseamigrationphase,Balticsalmonexperiencehighseasonalfluctuations in ambient temperature.These periods are clearly seen in theotoliths,asotolithcarbonatewiththe highestδ18Ootovaluesis accretedduringcoldwinterperiod,whilethelowestδ18Ootovalues representhighesttemperaturesinthesummer(Figure6;Wurster& Patterson,2003). 2.3 | Creating isotopic (isoscapes) and temperature maps for the Baltic Sea Isoscapesforδ13CDICand δ18O H 2O aswellastemperaturemapswere constructedusingODVsoftware.UsedmapdataforhorizontalisotopemapswerereceivedfromthedatabaseoftheLeibnizInstitute for Baltic Sea Research Warnemünde (IOW; Seifert, Tauber, & Kayser,2001)andforbothhorizontalmapsandverticalprofilesfrom the General Bathymetric Chart of the Oceans (GEBCO_08 Grid). GEBCO_08GridhadtobeconvertedintoNetCDFformatcompatiblewithODVwithRStatisticssoftwarev3.0.1(RCoreTeam,2013) using package RNetCDF (Michna, 2012). Interpolated maps were producedusingDataInterpolatingVariationalAnalysis(DIVA)griddingsoftware(Troupinetal.,2012)includedinODV(DIVAparameters:scalelengthschosenautomatically;signal-to-noiseratio=40; qualitylimit=3.0;excludingoutliers).VerticalprofileswerealsocreatedusingDIVAgridding(scalelengthschosendependingonused data;signal-to-noiseratio=40;qualitylimit3.0;excludingoutliers). ThecoastlinesinthemapsarebasedontheGlobalSelf-consistent Hierarchical High-resolution Shorelines database v 2.1 (Wessel & Smith,1996). Asthespatialcoverageofcollected δ18O H 2O wasrelativelysparse forassignmentmodels,andsomelargerareaslackedmeasurements, wecreatedpredictivemodels to estimate δ18O H 2O valuesfromthe BalticSeawatersalinity(S)datawhichisanexcellentpredictorfor δ18O H 2O andiscommonlyusedtoestimateoceanseawaterisotope values(e.g.,LeGrande&Schmidt,2006).The δ18O H 2O –Srelationship isfrequentlylinearlyrelated(LeGrande&Schmidt,2006),butinthe BalticfreshwaterinflowfromlargeriversintoGulfofBothniaandGulf ofFinlandhaveaneffectontherelationships.Therefore,wecreated separatemodelsfortheGulfofBothnia,theGulfofFinlandandfor therestoftheremainingareaoftheBalticSea.Shapeofthepredictive modelforeachareawasselectedbasedongoodnessoffitandmodel residualswereevaluatedusingquantile–quantileplots.Modelswere furtherappliedtoseawatersalinitysamplingsurveysobtainedfrom BalticMarineEnvironmentProtectionCommission(HELCOM)database(Andersson,2014)tocreateseasonal δ18O H 2O mapsfortheBaltic Sea.Dataonlyforsummer(July–August)andwinter(February–March) fortheperiodthestudysalmonhadspentinthesea(2007–2008) wereselected.Aswefoundstatisticallysignificantseasonaldifference in measured δ18O H 2O values, three separate δ18O H 2O maps [winter
| 5 TORNIAINEN ET Al. 2007(1SW),summer2007(2SS)andwinter2008(2SW)]werecreatedtobeusedinassignmentmodels.Modeledvalueswerecombined withmeasuredvaluesfromthesameseasontogainbetterspatialcoverage. Marked within-season differences were not found between HELCOMandourownmeasurementsbasedonvisualvalidationofsalinitydata,obtainedfromdepths5–15m,indicatingthatalso δ18O H 2O valuesbehavethesameway. Salmon summer temperatures were fixed at 11.5°C, calculated frompreferredtrue10mstayingdepthsofsalmoninBalticsalmon data storage tag study by Westerberg, Sturlaugsson, Ikonen, and Karlsson(1999).Forwintertemperatures(2007–2008),weusedall available temperature profiles collected from HELCOM database (Andersson,2014)coveringthewholeBalticSea(meantemperatures fromdepths5–15m)andcreatedaninterpolatedsurfaceforthepreferred10mstayingdepth.Interpolatedmetabolicallyderivedbicarbonateδ13Cdietvalueswerederivedfromδ13Cvaluesofsalmondietary speciesaroundtheBalticSea(AppendixS3). 2.4 | Creation of otolithrelated isoscapes from δ18OH2O, δ13CDIC, δ13Cdiet and water temperature Understanding the dependence of ambient water temperature and δ18O H 2O values on δ18Ooto is necessary to obtain comparable values of δ18Ooto and δ18O H 2O for spatial assignment of salmon (e.g., Pattersonetal.,1993).Moreover,theδ13Cotovalueisamixofbicarbonateδ13CDICfromambientwaterandmetabolicallyderivedbicarbonate δ13Cdiet (Solomon etal., 2006; Wurster & Patterson, 2003). Wethereforecorrected δ18O H 2O andδ13CDICvaluesusingliterature- derivedfractionationequations,afterwhichthecorrectedvaluesare consideredas“otolithisoscape”ofbothelements(AppendixS1).This permitsadirectcomparisonofotolithandBalticSeawaterisotopes, therebyprovidingaprobabilisticspatialassignmentofsalmonduring theirsea-feedingphase. Initially, δ18O H 2O values are calculated relative to the VSMOW scaleandδ18OotovaluesrelativetotheVPDBscalefromtheIAEA. To enable direct comparison of δ18Ooto(VPDB) with δ18Owater(VSMOW), δ18Owater(VSMOW) values were converted to VPDB using following equation(fromClark&Fritz,1997): Oxygen isotope values of otoliths reflect those of the ambient water(Campana,1999;Farrell&Campana,1996;Thorrold,Jones,& Campana, 1997), with a temperature-dependent fractionation (e.g., Pattersonetal.,1993).Followingcommonpractice,weusedthelinear temperature-dependentfractionation(e.g.,Pattersonetal.,1993). where Tistemperature(103/K),whereKisambientwatertemperatureinKelvin,andparameterα isthefractionationfactorbetween otolith and ambient water [α=(δ18Ooto(VPDB)+1,000)/( δ18O H 2O (VPDB)+1,000)]. Model fractionation constants a and b in four previous studies covering salmonid fishes are variable (a=−41.14, b=20.43:Godiksenetal.,2010;a=−33.43,b=17.88:Hansonetal., 2013; a=−33.49, b=18.56:Pattersonetal., 1993and a=−41.69, b=20.69:Storm-Suke,Dempson,Reist,&Power,2007).Toevaluate theeffectandvariationofdifferentparameterstosalmonassignment, thenumericallymostdistantparametersfromeachother(i.e.,Hanson etal.,2013;Pattersonetal.,1993)wereselectedforsalmonassignment(i.e.,forprobabilitysurfaces),hereafterModel3andModel1, respectively.Alsoanaverageofallfourmodels(a = −37.44,b = 19.39) wascalculatedandusedaccordingly,hereafterModel2(AppendixS2). Thefollowingequationgivestheotolith-relatedδ18O(VPDB)isoscapevaluesinrelationtowatertemperature(T)and δ18O H 2O (VPDB)values,thatcanbecomparedtoδ18Ootovaluesenablingtheassignment ofsalmontoseaareasbasedontheirotolithisotopevalues: Anotolith-relatedδ13Cotoisoscapewascalculatedasfollows(e.g., Solomonetal.,2006;Wurster&Patterson,2003)toallowcomparison betweenδ13CDICandδ13Coto: where δ13Cdietisameanδ13Cvalueofsalmonprimarypreyspeciesin theBalticSea(sprat[Sprattus sprattus],Balticherring[Clupea harengus membras]andthree-spinedstickleback[Gasterosteus aculeatus])ina particularlocation(AppendixS3)andMistheproportionofmetabolic carboninthesalmonotolith(Sherwood&Rose,2003): where Kcaud(Atlanticsalmoncaudalfinratio;Minns,King,&Portt, 1993)is2.4. 2.5 | Salmon assignment using otolith and water isotope values Toestimatethelocationsofsalmonindividualsintheir1SW,2SS and second 2SW from δ18Ooto and δ13Coto values, we calculated probabilitydensitysurfacesforeachsalmonbyusingadeterministicgridcoveringtheBalticSeafollowingtheapproachpresented inWunder(2010)withRStatisticssoftwarev3.0.1(RCoreTeam 2013).WefirsthadtoreinterpolateallDIVAinterpolationresults (waterand diet-basedisotopes,temperatures,etc.which werein differentkindsofnondeterministicgrids)fromODVintoadeterministicgridtoenableustocalculatethefractionationequations forallgridlocations.Thisreinterpolationwasperformedwithlocal (Nmax =4) inverse-distance weighting interpolation available in theRpackagegstat(Pebesma,2004).Theprobabilitydensitysurface calculation approach assumes water-temperature-dependent δ18O(VPDB)valuesandDIC-diet-basedδ13Cvaluestobenormallydistributedateachgridpointandthencalculatestheprobabilitiesof obtainingthemeasuredvaluesoftheotolithfromnormaldistributionswithmeanparametersaccordingtotheVPDB-correctedinterpolatedisotopevalues.Standarddeviationsofδ18Oandδ13Cvalues wereestimatedbasedonobservedvariationsof δ18 O H2O (ɛ=0.019) andδ13CDIC(ɛ=0.216)valuesobtainedfromthesamelocationand depth,andthevariationofobservedδ18Ootovaluesintheotoliths δ18 O H2O(VPDB) =0.97002×δ 18 O H2O(VSMOW) − 29.98. 1,000×ln α=a+b∕T, δ18 O (VPDB) =e ( a+b∕T ) ∕ 1,000 ×(δ 18 O H2O(VPDB) +1,000)− 1,000. δ13 C oto = M ×δ13 C diet + (1 − M) ×δ13 C DIC, M=0.025+0.066×Kcaud,
6 | TORNIAINEN ET Al. ofseveralfishindividuals(ɛ=0.207estimatedfromGodiksenetal., 2010). The resulting probability surfaces do not represent two- dimensionalprobabilitysurfaces(totalprobabilityineachmapsisnot scaledtobe1)andtheminimumandmaximumprobabilityvaluesare notthesameinallmapsasiscommoninthiskindofapproach(see e.g.,Wunder,2010).Instead,thesesurfacesvisualizewheretheprobabilityofobtainingthemeasuredvalueoftheotolith(ortheprobability ofpresenceofparticularindividualatacertaintime)isthegreatest, andwhereitis(much)lower.Inthosemapswherebothoxygenand carbon isotopes have been taken into account, probabilities were calculated by multiplying isotope-wise probabilities, assuming independence,whichmaynotbestrictlytrueforthiskindofphenomenon.However,ourdatadidnotallowforfullestimationofcovariance betweentruedatavaluesduetopartiallydifferingmeasurementor observation locations. Nevertheless, the covariance of interpolated surfaceswasabout10-foldsmallerthanthevariancesofindividual isotopes.Therefore,weexpectthatanypossibleerrorintheresults, duetodependenceinisotopevalues,issmall. Tostudy,howsensitiveourapproachistomeasurementerrors relatedtothestableisotopes,weconductedasimplesensitivityanalysisbyaddingand/orsubtractingtheobservedstandarddeviationsof watersamples(basedonliterature)ofδ13Candδ18Oto/fromtheactualmeasuredvalues,andperformedthecalculationoftheprobability ofpresenceforFISH2onthefirstwinter(1SW)usingthemodelby Hansonetal.(2013)forfractionation.Theamount±SDofwaterisotopemeasurementvariation(basedonliterature)waschosenbecause italsoreflectsabout±2SDofourownestimateofmeasurementaccuracy(0.09)ofotolithisotopevalues.So,theselimitsarealsorather closetobeingabout95%confidenceintervalofthemeasuredisotope values. 3 | RESULTS 3.1 | δ18OH2O, and δ13CDIC values in the Baltic Sea Differencein δ18O H 2O valuesbetweenseasonsat10mdepthatthe same locations was statistically significant (Paired samples T test: N = 31,p < .001).However,themean(±SD)valuesof δ18O H 2O were very similar (meansummer: −7.9‰±0.83, meanwinter: −7.6‰±0.74). Inaddition, δ18O H 2O valuesshowedaclearsouthtonorthlatitudinal decreasefromaround−6‰toaround−10‰(Figure3a,b).Aweaker longitudinaldecreasefromaround−6‰toaround−7.5‰occurred fromtheeasternendoftheGulfofFinlandtothewesternsideofthe NorthernBalticProper(Figure3a,b).Distinctdifferencesin δ18O H 2O valuesbetweenadjacentbasinswerealsoobserved(BothnianBay— BothnianSea—BalticProper—GulfofFinland),buttheBothnianSea andtheGulfofFinland,eventhoughnotdirectlyconnected,hadvery similarvalues(Figure3a,b)duetotheinfluxoffreshwaterfromrivers. Mean (±SD) δ13CDIC values were significantly different (Paired samplesTtest:N = 31,p < .001)betweensamplingtimes(meansummer:0.3‰±0.81,meanwinter:−0.9‰±0.54).δ13CDICvaluesdecreased withlatitudeinsummerfromaround2‰toaround−2‰(Figure3c). The differencewas smaller in thewinter (Figure3d).An increasing trendwasobservedinδ13CDICvaluesfromtheGulfofFinlandtothe BalticProperinbothseasons,fromaround−1‰toaround2‰in summerandfromaround−2‰toaround0‰inwinter(Figure3c,d). Verticalinterpolationofthetransectsshowedthat δ18O H 2O valuesin theCentralBalticProperwerehigherbelow~50mfromaround−6.5‰ toaround−5.5‰atthebottomandashighas−4‰intheSouthern BalticProper(Figure4a,b),whereasacleardecreasingtrendinsummer δ13CDICvaluesfromaround−1‰toaround−5‰atthebottomwas observed (Figure4e,f). Vertical interpolation also showed stability of δ18O H 2O valuesbetweensummerandwinter,whereasδ13CDICvalues exhibitedvariation between summer and winter in the upper water layer (up from ~50m; Figure4e–h). Below ~50m bothvalues were ratherstableovertime,exceptinthelesssalineareas(theBothnianSea, theBothnianBayandtheGulfofFinland)whereδ13CDICvaluesshowed minordecreasesduetoautumnwatercolumnturnover(Figure4). Therewasa strong δ18O H 2O –Srelationshipandthe coefficients ofdeterminationforallthemodelswerecloseto1.RelationshipappearedtobelinearonlyforSouthernBalticSea(R2=.98),whilein GulfofFinland(R2=.97)andGulfofBothniarelationshipswhereof logarithmicshape(R2=.99;Figure5). 3.2 | Carbon and oxygen isotope values of salmon otoliths Stableisotopeanalysisviamicromillingfromtheotolithnucleustothe otolithedgeshowedclearvariationinotolithisotopevalues.Inaddition,bothisotopevaluesofthetwootolithsanalyzedshowedsimilar life-historytrendsfromthenucleustotheotolithedge.δ18Ovaluesin theotolithnucleus(FISH1:−10.9‰;FISH2:−10.6‰)weremarkedly lowerthanthehighestvaluesobservedintheouterpartoftheotolith radius(FISH1:−5.9‰;FISH2:−6.6‰),andwiththelowestvaluesat theedgeoftheotolith(bothotoliths:−11.6‰;Figure6a,b). FIGURE5 Relationshipsbetweenseawatersalinityand δ18 OH 2O measuredin(a)GulfofBothnia,(b)GulfofFinlandand(c)Baltic Proper.Presentedmodelswereappliedwhenestimating δ18 OH 2O for eacharea –12 –11 –10 –9 –8 –7 –6 –5 –4 0246810121 41 6 a c b Salinity (‰) δ18O(‰) y = 0.263x - 8.684 R2= 0.98 y = 2.245ln(x) - 11.243 R2 = 0.97 y = 3.447ln(x) - 13.664 R2= 0.99
| 7 TORNIAINEN ET Al. Forbothotoliths,δ13Cvaluesalsoshowedclearvariationalong the otolith radius, from lowest δ13C values in the otolith nucleus (FISH1:−16.1‰;FISH2:−14.4‰)tohighestintheouterpartof theotolithradius(FISH1:−3.4‰,FISH2:−3.1‰),withintermediate valuesattheedgeoftheotolith(FISH1:−11.1‰;FISH2:−10.8‰; Figure6a,b).Bothotolithnuclei(i.e.,duringthejuvenilephase)exhibitedlowδ13Cotoandδ18Ootovalues.Thejuvenilephaseisotopevalues ofFISH1tendedtobelessvariablethanthoseofFISH2.Theotolith isotopevaluesofapparentpost-smoltmigrationfromthefreshwater tomoresalinearethemostdistinctbetweenthesetwosalmon.FISH 1otolith δ18Ovalues increasedto thehighestvaluesmoresharply thanthoseofFISH2,forwhichδ13Cvaluesincreasedinamorelinear manner.Otolithδ18OvaluesforFISH1werehigherduringthefirst seawinterthanthoseforFISH2,whilevaluesduringthesecondsea winterandapparentspawningmigration(steepdeclineinbothisotope valuesafter2SW)weresimilarforbothsalmon(Figure6a,b). 3.3 | Probability surfaces for salmon locations in the seafeeding phase BasedontheModel1(Hansonetal.,2013)assignments,themost probablefirstseawinterlocationofFISH1wasintheBalticProper (Figure7a).Duringthenextsummerandthesecondwinter,FISH1 appearedtooccupywatersclosetotheGulfofRiga,andtheareasof thesouthwestandnorthernBalticProper,respectively(Figure7b,c). TheresultsforFISH2wereverysimilar,exceptthatinthefirstwinter itappearedtobelocatedintheBothnianSeaorintheGulfofRiga (Figure7d–f).ComparedtotheModel1,assignmentsoftheModel 3(Pattersonetal.,1993)werelocatedmorenorthernandalsocolder areasortoareaswithlowersalinity(theGulfofFinland;Figure7). Model2(theaveragemodeloffourmodelsusedinthestudy)salmon assignmentswerebetweenHansonetal.(2013)andPattersonetal. (1993)models(Figure7).Someoftheassignmentsofthemodels2 and3wereconfinedtosuchasmallareathatresultsofthemodels werenotveryvisibleintheassignmentmaps(Figure7). Total of eight different results (Figure8) were obtained from thesensitivityanalysisinadditiontotheresultobtainedwithactual measuredvalues.Increasingtheotolithδ18Ovaluecausesthemost probableareaintheGulfofBothniatoshiftslightlytowardwest,and decreasingitcausesthemostprobableareatoshiftslightlytoward east.Increasingδ13Cvalueseemstomaketheassignmentmoreconcentratedatonelocationanddecreasingitcausestheresulttobeless determined. 4 | DISCUSSION 4.1 | Isotope values of the Baltic Sea Wepresentedthedistributionofδ13CDICand δ18O H 2O valuesinthe BalticSeaduringbothsummerandwinterviainterpolatedhorizontal FIGURE6 Isotopevaluesoftwo exampleRiverSimojokisalmonotoliths micro-milledandanalyzedforoxygenand carbonstableisotopes:(a)FISH1(wild origin)and(b)FISH2(hatchery-reared). Opencirclesrepresentδ13Cvaluesand filledcirclesδ18Ovalues.Isotopepoint valuesusedinthesalmonassignmentto theprobablelocationsintheBalticSea duringtheirfirst(1SW)andsecondsea winter(2SW)andsecondseasummer (2SS)areindicated –20.0 –18.0 –16.0 –14.0 –12.0 –10.0 –8.0 –6.0 –4.0 –2.0 –12.0 –11.0 –10.0 –9.0 –8.0 –7.0 –6.0 δ 13 C(‰)δ 13 C(‰) δ18O(‰) –20.0 –18.0 –16.0 –14.0 –12.0 –10.0 –8.0 –6.0 –4.0 –2.0 –12.0 –11.0 –10.0 –9.0 –8.0 –7.0 –6.0 020406080100 Distance from nucleus (%) δ18O(‰) (a) (b) 1SW 2SS 2SW 1SW 2SS 2SW
8 | TORNIAINEN ET Al. isotopicmapsfromadepthof10mandalsoviaverticalcross-sections. Differencesbetweenseaareasinbothisotopevalueswereobserved. Horizontalδ13CDICvaluesclearlydifferedbetweensummerandwinter,whereas δ18O H 2O valuesremainedrathersimilar.Vertical δ18O H 2O valuesremainedstablebetweensummerandwinter,whereasδ13CDIC showedmarkeddifferencesbetweensummerandwinter,especially nearthesurface. The distinctive hydrologic characteristics of the Baltic Sea are clearlyreflectedinourmeasurements. δ18O H 2O valuesintheBalticSea aremainlycontrolledbytheinfluxfromtheDanishstraitsofdenser, more saline water with higher δ18O H 2O (see e.g., Dickson, 1973; Matthäus&Lass,1995)andthefreshwaterwithlower δ18O H 2O values runningofffromthecatchmentarea.Theobservedverticalgradientin isotopevaluesisalsoduetothepenetrationofmoresalinewaterwith higher δ18O H 2O valuesunderthelessdensefreshwaterwithlower δ18O H 2O values.ThisdenserwaterstagnatesinthedeeperbasinsisolatedbythesillsbetweendifferentBalticSeaareas(Matthäusetal., 2008)andleadstothearealsegregationof δ18O H 2O values.Asimilar phenomenoncanbeseeninmarineenvironmentsaroundtheworld (Schmidt, Bigg, & Rohling, 1999) and has been recorded from the SouthernBalticSea(Frohlich,Grabczak,&Rozanski,1988;Punning, Vaikmae,&Maekvi,1991).Temperature-relatedautumnoverturnof thewatercolumnbreaksdownthesummerstratificationandmixes thewaterabovethehalocline(downto~50m),butthedeeperwater FIGURE7 Probabilitysurfacesof locationsfortwoexampleRiverSimojoki Atlanticsalmons(FISH1and2)duringtheir feedingphaseoffirstseawinter(1SW;a andd,respectively),secondseasummer (2SS;bande,respectively)andsecond seawinter(2SW;candf,respectively)in theBalticSea.Calculationsarebasedon salmonotolithandBalticSeawaterδ18O andδ13Cvalues.Whiteandhigh-saturation colorsindicatethatallvaluesurfaces usedinthecalculationofprobabilities (temperature, δ18 OH 2O ,δ13CDICandprey isotopevalues)arereliableincontrastto lowconfidenceprobabilitiesindicatedin grayandgrayishcolors.Probabilitysurface resultsindicatedinredrepresenthigh probabilityofpresenceaccordingtothe usedmodelofHansonetal.(2013)(Model 1),greencolorindicateshighprobability orpresencewiththeaveragemodelof allfourusedmodelsinthisstudy(Model 2;Godiksenetal.,2010;Hansonetal., 2013;Pattersonetal.,1993;Storm-Suke etal.,2007)andbluecolorrepresents highprobabilityorpresenceonthemodel probabilitiesofPattersonetal.(1993) (Model3) Latitude (a) Model 1 high prob. Model 2 high prob. Model 3 high prob. Low probability Low confidence Latitude (b) Model 1 high prob. Model 2 high prob. Model 3 high prob. Low probability Low confidence Longitude Latitude (c) Model 1 high prob. Model 2 high prob. Model 3 high prob. Low probability Low confidence (d) Model 1 high prob. Model 2 high prob. Model 3 high prob. Low probability Low confidence (e) Model 1 high prob. Model 2 high prob. Model 3 high prob. Low probability Low confidence 54 56 58 60 62 64 6654 56 58 60 62 64 66 10 15 20 25 30 54 56 58 60 62 64 66 10 15 20 25 30 Longitude (f) Model 1 high prob. Model 2 high prob. Model 3 high prob. Low probability Low confidence FISH 1 FISH 2
| 9 TORNIAINEN ET Al. columnremainsratherstablemaintainingmoremarinecharacteristics (Lass&Matthäus,2008).However,inourstudy, δ18O H 2O valuesremainedstablebetweensummerandwinter,andonlyoccasionalstrong saltwaterpulses(e.g.,Dickson,1973;Matthäus&Lass,1995)could change this situation. Lack of winter isotope measurements south from Gotland might have affected the interpolatedvalues denoted inthemapswithgrayishcolors).TheFinnishEnvironmentInstitute (SYKE;http://www.itameriportaali.fi/en_GB/:2.6.2014)andHELCOM (Andersson,2014)havereportedstablehydrologyandsalinityofthe Balticduringthestudiedyears.Basedonthoseattributes,itisnotvery likelythat δ18O H 2O valuesinsummerwouldbeverydifferentfromthe valuesobservedinwinter. δ13CDICvaluesarecontrolledbysimilarmechanismsasthosethat control the water column characteristics and δ18O H 2O .The clearest distinction between the mechanisms based on temperature-related bioactivity. Preferential incorporation of 12C during photosynthesis FIGURE8 SensitivityanalysisofprobabilisticspatialassignmentModel1forFISH2in1stwinteratthesea(1SW).Originalotolithδ18Oand δ13Cvalues(figureinthemiddle)wereadjusted±1SD.Highprobabilitymeanswheretheprobabilityofobtainingthemeasured(ordeviated) valueoftheotolith(ortheprobabilityofpresenceofthisindividualat1SW)fromthecreatedotolithisoscapeisthegreatestbytheused model.Thehatched(low-saturationcolored)areasindicateregionswherethedensityofrealobservationsofatleastoneisoscape(usedinthe calculationofprobabilityofpresence)istoolowforreliableprediction 10 15 20 25 30 δ18Oat upper, δ13Cat lower limit High probability Low probability 10 15 20 25 30 δ18O at upper limit High probability Low probability 10 15 20 25 30 Both at upper limit High probability Low probability 10 15 20 25 30 δ13C at lower limit δ13C at upper limit High probability Low probability 10 15 20 25 30 Both isotopes as measured High probability Low probability 10 15 20 25 30 High probability Low probability 10 15 20 25 30 54 56 58 60 62 64 6654 56 58 60 62 64 6654 56 58 60 62 64 66 Both at lower limit High probability Low probability 10 15 20 25 30 δ18O at lower limit High probability Low probability 10 15 20 25 30 54 56 58 60 62 64 66 54 56 58 60 62 64 66 54 56 58 60 62 64 66 54 56 58 60 62 64 66 54 56 58 60 62 64 66 54 56 58 60 62 64 66 δ18Oat lower, δ13C at upper limit High probability Low probability Longitude Latitude Otolithδ13C value increases → Otolith δ18O value increases → 10 15 20 2 5 30 High pro b a bili t y L o w pro b a bil i t y 10 1 5 20 25 30 High pro b a bili t y L o w pro b a bili t y 10 1 5 20 25 30 High pro b a bili t y L o w pro b a bili t y 10 15 20 25 30 δ 1 3 C a t l o w e r l i m i t δ 1 3 C a t u pper li m it Hi g h probabilit y L o w probabilit y 10 15 20 25 30 Both isoto p es as measured H i g h probabilit y L o w probabilit y 10 15 20 25 30 Hi g h probabilit y L o w probabilit y B ot h at l o w e r limi t Hi g h probabilit y L o w probabilit y δ 1 8 O a t l o w e r l i m i t H i g h probabilit y L o w probabilit y 5 4 5 6 5 8 6 0 6 2 6 4 6 5 4 5 6 5 8 6 0 6 2 6 4 6 5 4 5 6 5 8 6 0 6 2 6 4 66 5 4 5 6 5 8 6 0 6 2 6 4 6 6 5 4 5 6 5 8 6 0 6 2 6 4 66 5 4 5 6 5 8 6 0 6 2 6 4 6 6 δ 1 8 O a t l o w e r , δ 1 3 C a t u p p e r l i m i t Hi g h probabilit y L o w probabilit y