Poor nutritional quality of primary producers and zooplankton driven by eutrophication is mitigated at upper trophic levels
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This is a self-archived version of an original article. This version may differ from the original in pagination and typographic details. Author(s): Title: Year: Version: Copyright: Rights: Rights url: Please cite the original version: CC BY 4.0 https://creativecommons.org/licenses/by/4.0/ Poor nutritional quality of primary producers and zooplankton driven by eutrophication is mitigated at upper trophic levels © 2022 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd. Published version Taipale, Sami Johan; Ventelä, Anne‐Mari; Litmanen, Jaakko; Anttila, Lauri Taipale, S. J., Ventelä, A., Litmanen, J., & Anttila, L. (2022). Poor nutritional quality of primary producers and zooplankton driven by eutrophication is mitigated at upper trophic levels. Ecology and Evolution, 12(3), Article e8687. https://doi.org/10.1002/ece3.8687 2022
Ecology and Evolution. 2022;12:e8687. | 1 of 18 https://doi.org/10.1002/ece3.8687 www.ecolevol.org Received:4September2021 | Revised:22January2022 | Accepted:7February2022 DOI: 10.1002/ece3.8687 RESEARCH ARTICLE Poor nutritional quality of primary producers and zooplankton driven by eutrophication is mitigated at upper trophic levels Sami Johan Taipale1 | AnneMari Ventelä2 | Jaakko Litmanen1 | Lauri Anttila2 ThisisanopenaccessarticleunderthetermsoftheCreativeCommonsAttributionLicense,whichpermitsuse,distributionandreproductioninanymedium, providedtheoriginalworkisproperlycited. ©2022TheAuthors.Ecology and EvolutionpublishedbyJohnWiley&SonsLtd. 1DepartmentofBiologicaland EnvironmentalScience,Universityof Jyväskylä,Jyväskylä,Finland 2PyhäjärviInstitute,Ruukinpuisto, Kauttua,Finland Correspondence SamiJohanTaipale,Departmentof BiologicalandEnvironmentalScience, UniversityofJyväskylä,Jyväskylä, Finland. Email:[email protected] Funding information Thisresearchwassupportedbythe AcademyofFinlandresearchgrant 333564,awardedtoSamiJ.Taipaleand bythefoundationofKalataloudenja merenkulunkoulutuksenedistämissäätiö, awardedtoLauriAnttila. Abstract Eutrophicationandrisingwatertemperaturein freshwatersmayincreasethetotal production of a lake while simultaneously reducing the nutritional quality of food web components. We evaluated how cyanobacteria blooms, driven by agricultural eutrophication(ineutrophicLakeKöyliöjärvi)orglobalwarming(inmesotrophicLake Pyhäjärvi),influencethebiomassandstructureofphytoplankton,zooplankton,and fishcommunities.Intermsofthenutritionalvalueoffoodwebcomponents,weevaluatedchangesintheω-3andω-6polyunsaturatedfattyacids(PUFA)ofphytoplankton andconsumersatdifferenttrophiclevels.Meanwhile,thelakesdidnotdifferintheir biomassesofphytoplankton,zooplankton,andfishcommunities,laketrophicstatus greatly influenced the community structures. The eutrophic lake, with agricultural eutrophication,hadcyanobacteriabloomthroughoutthesummermonthswhereas cyanobacteria were abundant only occasionally in the mesotrophic lake, mainly in earlysummer.Phytoplanktoncommunitydifferencesatgenuslevelresultedinhigher arachidonicacid,eicosapentaenoicacid(EPA),anddocosahexaenoicacid(DHA)contentofsestoninthemesotrophicthanintheeutrophiclake.Thiswasalsoreflected intheEPAandDHAcontentofherbivorouszooplankton(DaphniaandBosmina)despitemoreefficienttrophicretentionofthesebiomoleculesinaeutrophiclakethan inthemesotrophiclakezooplankton.Planktivorousjuvenilefish(perchandroach)ina eutrophiclakeovercametheloweravailabilityofDHAintheirpreybymoreefficient trophicretentionandbiosynthesisfromtheprecursors.However,themostefficient trophicretentionofDHAwasfoundwithbenthivorousperchwhichpreycontained onlyalowamountofDHA.Long-termcyanobacterialbloomingdecreasedthenutritionalqualityofpiscivorousperch;however,thedifferencewasmuchlessthanpreviouslyanticipated.Ourresultshowsthatlong-termcyanobacteriabloomingimpacts thestructureofplanktonandfishcommunitiesandlowersthenutritionalqualityof sestonandzooplankton,which,however,ismitigatedatuppertrophiclevels. KEYWORDS benthicinvertebrates,freshwaterfoodweb,ontogeneticdietshift,perch,phytoplankton, polyunsaturatedfattyacids
2 of 18 | TAIPALE ET AL. 1 | INTRODUCTION Globally, freshwater ecosystems are challenged by land use and many factors connected to climate warming, such as changing precipitation, eutrophication (as an increase in total phosphorus) (Hasler,1947),andwaterbrowning(anincreaseofDOC)(Karlsson etal.,2009;Leechetal.,2018;O'Reillyetal.,2003).Intheboreal zone,lakewatertemperatureandprecipitationareincreasing,which may increase nitrogen (N), phosphorus (P), and dissolved organic carbon (DOC) loading, especially from agricultural and peatland- dominated catchments (Lathrop et al., 2019; Ruosteenoja et al., 2016).Changing environmentalconditions affectecosystem function and phytoplankton, zooplankton, and fish community structure(Havens,2008;Jeppesenetal.,2010,2012;Kevaetal.,2021; Sukeniketal.,2015;Venteläetal.,2016).Atthesametime,these conditions also impact the nutritional value of the phytoplankton andthustheproductionandthetransferofessentialbiomolecules through food webs (Lau et al., 2021; Müller-Navarra et al., 2004; Taipaleetal.,2016,2019). The ω-3andω-6polyunsaturatedfattyacids(PUFA)havebeen foundtohavemanyphysiologicallynecessaryfunctionsinallanimals includinghumans(Artsetal.,2009;Simopoulos,2000).Becauseanimalscannotsynthesizeω-3andω-6PUFAdenovo,theyneedto obtainthesemoleculesfromtheirdiet.Therefore,short-chainω3 andω-6PUFAofα-linolenicacid(ALA,18:3ω3)andlinoleicacid(LA, 18:2ω6)areusuallyconsideredessentialfattyacids(EFA)or“essentialnutrients”foranimals(Parrish,2009).However, eicosapentaenoicacid(EPA,20:5ω3),docosahexaenoicacid(DHA,22:6ω3),and arachidonicacid(ARA,20:4ω6)arephysiologicallymostimportant for consumers (Hulbert & Abbott, 2012; Parrish, 2009; Stanley- Samuelsonetal.,1988).Therefore,theymaybecalledphysiologicallyessentialorsemi-essentialPUFA(Taipaleetal.,2019). In marine and freshwater ecosystems, green algae and cyanobacteriaareclassifiedasnon-EPAandnon-DHA-synthesizers,while golden algae, dinoflagellates, cryptophytes, diatoms, and raphidophytesareprimaryproducersofEPAandDHA(Ahlgrenetal.,1992; Jónasdóttir,2019;Taipaleetal.,2013;Taipale,Vuorio,etal.,2016). However,EPA-andDHA-synthesizingphytoplanktontaxacanalso be found abundantly in eutrophic lakes (Lepistö & Rosenström, 1998). A clear decline in the nutritional quality of seston can be seeninhyper-eutrophiclakes(Müller-Navarraetal.,2004;Taipale et al., 2019). Therefore, it is important to monitor the abundance ofEPA-andDHA-synthesizingphytoplanktontaxa(cryptomonads, golden algae, diatoms, dinoflagellates, raphidophytes, euglenoids) throughout the summer to understand the nutritional quality of phytoplankton.Agriculturaleutrophicationhasbeenthemainreason for increased cyanobacteria blooms in boreal and temperate lakes(Jørgensen&Rast,2001).However,thegrowingabundanceof cyanobacteriabloomsintherecentpastisrelatedtoclimatechange andespeciallyduetotheincreasedtemperatureoflakes(Dengetal., 2016; Elliot, 2012; Paerl & Huisman, 2008; Pätynen et al., 2014; Rasconietal.,2017).Previousstudieshaveshownthatadecrease inthenutritionalqualityofphytoplanktonismainlyattributedtothe changes by the phytoplankton community structure, but also becausethenutritionalvalueofphytoplanktoncellsdecreasesbyeutrophication(Kevaetal.,2021;Lauetal.,2021;Taipaleetal.,2019). Herbivorous zooplankton is a key link in connecting phytoplankton and planktivorous fish and thus the nutritional value of zooplanktonisimportantforthegrowthoffishfry(Taipaleetal., 2018). However, individual zooplankton taxa differ by their nutritionalvalue(Kratina&Winder,2015).Thisisbecausecladocerans usuallyaccumulateEPAwhereascopepodsarerichinDHA(Brett etal.,2009;Hiltunenetal.,2016;Smynteketal.,2008;Taipaleetal., 2011).Moreover,zooplanktonsaregenerallyinefficientintheirabilitytobiosynthesizeALAtoEPAandDHA.Thus,theyarestrongly dependentonthefattyacidqualityintheirdiet(Elertetal.,2003; Koussoroplisetal.,2014;Taipaleetal.,2011).Herbivorouscladoceran(DaphniaandBosmina)isakeystonespeciesinmostlakeecosystems(Bergquistetal.,1985;Kerfootetal.,1988;Lynch&Shapiro, 1981).Itcandetecthighnutritionalqualitypatchesandcanselectivelyfeedonhighnutritionalqualityparticles(Hartmann&Kunkel, 1991;Schatz&McCauley,2007).Moreover,fattyacid-basedmodelinghasshownthatsestonmicrobial(includingalgae)composition doesnotnecessarilymatchwithassimilateddiet(Taipaleetal.,2019). This is because herbivorous zooplankton (Daphnia and Bosmina) favors high nutritional quality diet (Galloway et al., 2014; Taipale etal.,2019).Cyanobacteriabloomsmayleadtopoorerenergyflow inaquaticfoodwebsbecausetheypoorlysupportzooplanktonsomaticgrowthandreproduction(Bednarskaetal.,2014;Elertetal., 2003;Peltomaaetal.,2017;Porter&McDonough,1984).Theycan alsobelinkedtotheuppertrophiclevelonlybycertainzooplankton taxa(e.g.,Chydorus;Tõnnoetal.,2016).Environmentalchanges(e.g., eutrophication,browning,globalwarming)havebeenshowntohave differentimpactsonthenutritionalvalueofzooplankton(Kevaetal., 2021;Lauetal.,2021;Senaretal.,2019).Asaresult,itappearsthat thelowernutritionalvalueofphytoplanktondoesnotalwaysaffect highertrophiclevels.However,arecentstudyofproductivityand temperaturegradientinsub-arcticlakesshowedthatthezooplanktoncommunitychangedfromtheCalanoid(Eudiaptomus graciloides) dominated community towards herbivorous cladocerans (Daphnia andBosmina),resultinginadecreaseintheEPAandDHAcontentof zooplanktoncommunity(Kevaetal.,2021). Environmental changes and especially eutrophication have been known to change the structure of fish communities (Keva etal.,2021).Itiswelldocumentedthatcyprinidfish,e.g.,roach (Rutilus rutilus)and bream(Abramis brama), areultimatewinners TAXONOMY CLASSIFICATION Chemicalecology;Globalchangeecology;Trophicinteractions
| 3 of 18 TAIPALE ET AL. intheeutrophicationinboreallakes,whereasvendace(Coregonus albula)andburbot(Lota lota)areknowntobelosers(Tammietal., 1999).However,itisnotwellknownhowdependentdifferentfish speciesareontheEPAandDHAcontentoftheirprey.Theability offreshwaterfishtobiosynthesizelonger-chainPUFAfromtheir precursorsisreportedlybetterthanwithmarinefish(Sargentetal., 1999).Nevertheless,thereisa paucityofstudieswithdifferent freshwaterfishspeciesarelacking.Eutrophicationandbrowning impacton theEPA andDHA contentoffishmusclearecontradicting(Ahlgrenetal.,1996;Kevaetal.,2019;Strandbergetal., 2016; Taipale, Vuorio, et al., 2016). However, some fish species couldseeminglymitigatethelownutritionalqualityoftheirprey. Ahlgrenetal.(1996)foundthatEPAandDHAcontentofroachis higherinoligotrophiclakesthanineutrophiclakes,whereasthey didnotfindasimilardifferenceintheperch,whichisincontrastto ourpreviousfindingwithpiscivorousperch(Taipale,Vuorio,etal., 2016).Chaguacedaetal.(2020)recentlyreportedthatthecontent ofARA,EPA,andDHAarestrongly regulated overontogeny in perchmusclesbasedontheirFAprofilesandcompound-specific stableisotopes(Scharnweberetal.,2021).However,itisnotclear howthelowavailabilityofDHA,causedbycyanobacteriabloomingdrivenbyeutrophicationorclimatechange,impactEPA and DHAcontentoffishatdifferenttrophiclevels. Since European perch (Perca fluviatilis) have three ontogenetic dietarystages,itisanidealfishspeciestoevaluateeutrophication's impact on the nutritional value of the same species at different trophiclevels.Perchfryeatszooplankton,fromwhichitgradually moves to thebenthosand on tofishfood(Estlanderetal., 2010, 2012; Haakana et al., 2007; Rask, 1986). Previously, it was found thatthepiscivorous(length>20cm)perchofoligo-andmesotrophiclakescontainmoreEPAandDHAthanperchineutrophiclakes (Gladyshev et al., 2018; Taipale, Vuorio, et al., 2016). Chaguaceda etal.(2020)suggestedstrongregulationofEPAandDHAinperch muscle. Here, (H1), we hypothesized that long-term cyanobacteria blooms by agricultural eutrophication increases the biomasses of phytoplankton,zooplankton,andfishcommunities,butalsochanges thestructureofplanktonandfishcommunities.Weassumedthat long-termcyanobacterialbloomdecreasesthebiomassofEPA-and DHA-synthesizingphytoplanktontaxa,favorssmallcladoceranover copepods,andincreasesthenumberofcyprinidsoverpercidsfish. Secondly,wehypothesized(H2)thatthenutritionalqualityofsestonisdecreasedbylaketrophicstatus(Kevaetal.,2021;Lauetal., 2021;Müller-Navarraetal.,2004;Taipale,Vuorio,etal.,2016).We alsoassumedthatthisdecreaseinthenutritionalqualityofprimary producersisreflectedatdifferenttrophiclevelsviachangesinthe nutritionalqualityoftheirprey.Finally,weassumed(H3)thatconsumerstrytocompensatefortheirlowernutritionalqualityofprey bymoreefficienttrophicretentionandbiosynthesisofphysiological essentialPUFA. 2 | MATERIALS AND METHODS 2.1 | Study area The research material was collected during the summer of 2017 from mesotrophic Lake Pyhäjärvi and eutrophic Lake Köyliönjärvi, which are both located in southwest Finland, as shown in Table 1. Weather conditions are similar for these two lakes,whichcanbeseeninequalsurfacetemperatureduringthe 2000s(PERMANOVA:Pseudo-F1,157 =0.33,p =.578).However, these two lakes differ in their productivity (PERMANOVA: Pseudo-F1,129 = 190.4, p = .001) and nutrients (PERMANOVA forTPandTN:Pseudo-F1,181/185 = 475/622, p =.001)basedon measurementsbetween2000and2017(Herttadatabase,Finnish EnvironmentalCentre).Basedontotalphosphorusandchlorophyll concentration,LakeKöyliönjärvicanbeconsideredaeutrophicor hyper-eutrophiclake,whereasLakePyhäjärvicanbeconsidered tobeamesotrophiclake(Bengtssonetal.,2012).Moreover,Lake Köyliönjärvi is a shallow lake (mean depth 3 m) with the deepestpointof13m,whereasthemeandepthofLakePyhäjärviis 5m,withthedeepestpointbeing26m.Bothlakessufferfroman overlyhighnutrientloadfromtheircatchments.LakeKöyliönjärvi usuallyexperienceslargecyanobacterialbloomsinsummer,which temporarily declined in the 1990s due to fish removal (Sarvala et al., 2000). Lake Pyhäjärvi has been subjected to a variety of water protection measures since the 1980s, thereby decelerating the lake's eutrophication development (Ventelä et al., 2007, 2016).Inthe2000s,climatechangeaffectedthephytoplankton community, and cyanobacteria blooms have become more frequentinLakePyhäjärvi(Dengetal.,2016).Thisdevelopmentwill Parameter Unit Mesotrophic Lake Pyhäjärvi Eutrophic Lake Köyliönjärvi 2000– 2017 2017 2000– 2017 2017 Totalphosphorus µgP/L 19± 5.2 22 ± 7.0 116 ± 36.1 77 ± 42.3 Totalnitrogen µgN/L 422 ± 50 422 ± 76 1190± 324 992± 347 Chlorophyll µg/L 7.5 ± 3.6 8.0 ± 3.1 65.1 ± 33.7 61 ± 28.7 Turbidity FNU 2.4 ± 1.1 2.4 ± 0.7 25.5 ±13.9 23.0 ± 6.7 Secchi Depth m 2.5 ± 0.6 2.3 ± 0.2 0.6 ± 0.2 0.5 ± 0.1 Temperature °C 18.4 ± 2.6 17.0 ±1.9 18.7 ± 2.3 17.0 ± 2.2 TABLE 1 Totalphosphorus,nitrogen, chlorophyll,turbidity,Secchidepth. andtemperatureformesotrophicLake PyhäjärviandeutrophicLakeKöyliönjärvi
4 of 18 | TAIPALE ET AL. befurtheracceleratedinfuturebasedonthemodeling(Pätynen etal.,2014). 2.2 | Phytoplankton and zooplankton community and fatty acid sampling Throughoutthesummermonths(June–August)of2017,thewater quality (Secchi-depth, water temperature, turbidity, chlorophyll-a, totalphosphorus, phosphatephosphorus,andtotal nitrogen),and communitycompositionofphyto-andzooplankton,andtheirfatty acidcompositionandcontent,weremonitored.Asampleof0–5m water column was taken with a tube sampler (model: Sormunen, volume 6.3 L) to analyze quantitatively the community compositionofthephyto-andzooplankton.Planktoncommunitysamples wereanalyzedbythecommerciallaboratoryLounais-Suomenvesi- ja ympäristötutkimus Oy,wherecertifiedpersons countedphytoplanktonandzooplanktonsamples.Physico-chemicalwatersamples weretakenwithaLimnostubesampler(volume2.6L)andanalyzed bytheLounais-Suomenvesi-jaympäristötutkimusOylab.ThesamplepointsinthelakeswereselectedtobeinlinewiththeenvironmentalmonitoringprogramoftheFinnishEnvironmentalInstitute, inordertoutilizethewaterqualitymaterialfoundintheHerttadatabase(www.syke.fi/avointieto).Intotal,thesummersamplingcampaignincludedsixsamplesforLakePyhäjärviandfivesamplesfor LakeKöyliönjärvi. Polyunsaturatedfattyacids(PUFA)ofseston(phytoplankton) availableforherbivorouszooplanktonwerestudiedbypre-filtering sestonwitha50µmsieveandthenfilteringaspecificamountof waterthroughGF/Ffilterpaper(Whatman).Sampledherbivorous cladoceran was majorly (>95%) Daphnia and Bosmina and contained random (<5%) Chydorus, Ceriodaphnia, or Diaphanosoma. Itwasusedtoestimatethenutritionalqualityofdietforplanktivorousperchsinceherbivorouscladoceran(especiallyDaphnia together with Bosmina)isthemajorpreyforplanktivorousperch (Estlanderetal.,2010;Ruohonen,2006).Thezooplanktonsample was collected horizontally with a 50 µm plankton net and main genera were picked up with microscope glass. Surface water (0–2mwatercolumn)wassampledwithatubesampler(model: Sormunen,volume6.3L)forthefattyacidcompositionandcontentanalysisofseston. 2.3 | Zoobenthos community and fatty acid sampling Inadditiontoseasonalphyto-andzooplanktonsampling,zoobenthoswassampledonceinthelittoralzonedepthof2–3minlate summer2017.Inbothstudylakes,asimilarsamplingprocedurefor onesamplepointwascarriedoutwithanEkmangrab.Thesamples werefilteredbya500µmscreentoremovethefinematerialand thenallmacroscopiczoobenthoswerepickedupinthelaboratory. Chironomidaelarvaeweretheonlyabundantgroupinbothlakesamples.Accordingtoearlierstudies(notpublished),inLakePyhäjärvi atleast,Chironomidaelarvaeformasignificantpartofthedietfor benthivorousperch. 2.4 | Fish community and fatty acid sampling Fish community structure and biomasses were obtained from the national fish monitoring database (Hertta/Koekalastusrekisteri) managed by the Natural Resources Institute Finland. This study coveredtheyears2012,2015,2017,and2020foreutrophicLake Köyliönjärvi.Similarly,2009,2012,2015,and2019werecoveredfor mesotrophicLakePyhäjärvi.Briefly,NORDICmultimeshsurveynets (Appelbergetal.,1995)wereusedforgillnetsampling.Gillnetsamplingfollowedrandomstratifiedsampling,includingnetsinpelagic, metalimnetic,andbenthicgillnets(Olinetal.,2016),whereasgillnet samplingwasdoneyearlyduringJulyandAugust.Theannualnumberofgillnetnightswere40foreutrophicLakeKöyliönjärviand56 formesotrophicLakePyhäjärvi.Tocomparefishbiomassesbetween lakes,weusedBPUE(wetmassperuniteffort=kgfishpergillnet night)(Rasketal.,2020)ofindividualfishspecies.Tocomparethe structureofperchcommunitiesinthesetwolakesweusedCPUE (numberoffishpergillnetnight)oftheperchgroup(dietgroup).The perchcommunitywasdividedintocategoriesincludingitsontogeneticdietshift(Estlanderetal.,2010;Estlander,etal.,2012),planktivorous(length:<15cm),benthivorous(15–19cm),andpiscivorous (>19cm).Thesecategoriesrelatetothemaindietbutplanktivorous fishmayalsofeedonbenthicinvertebrates,andbenthivorousperch feedsonsmallerfish(Amundsenetal.,2003;Estlanderetal.,2010, 2012). Perch individuals for fatty acid analysis were caught in the late summer of 2017. Perches from mesotrophic Lake Pyhäjärvi were received from professional fishers who used open-water seine fishing and gillnets for catching fish. Perch fry were also nettedfromapier.PerchinLakeKöyliönjärviwerecaughtusing theNordicgillnetseries.Duetotherapiddevelopmentofyoung fish,theyoung-of-the-yearperchwerecaughtwithintwoweeks, frombothlakes,toensurethecomparisonbetweenthelakeswas relevant.FrywerecaughtonSeptember12inLakeKöyliönjärvi andSeptember2and11inLakePyhäjärvi.Thelength,weight,and sexofeachfishweredetermined(TableS1).Agewasdetermined mainlybyusinggill-coveringbone,operculum,and,insomecases, a more precise determination was made by examining scales. Samplesforfattyacidanalysisweretakenfromthedorsalmusclesandstoredat−20°Cuntiltheywerefreeze-driedwithinone monthfromsampling.Theresearchmaterialcoveredatotalof48 fishinLakePyhäjärviand37fishinLakeKöyliönjärvi(TableS1). Inadditiontoperch,fiveindividualsofsmallroach(<10cm)were obtainedfrombothlakestoestimateifPUFAcontentofomnivorousfishandpotentialdietforpiscivorousperchdifferintheir PUFAcontent.
| 5 of 18 TAIPALE ET AL. 2.5 | Fatty acid analysis Lipids were extracted from the freeze-dried seston, cladocera, Chironomidae, and fish samples in Kimax borosilicate tubes with chloroform-methanol (2:1) mixture. Fatty acids were methylated using mild sulfuric acid. Methyl esterified samples were analyzed on a Shimadzu GC-MS-QP2010 Ultra (Nishinokyo-Kuwabara-Cho, Kioto, Japan) with helium as carrier gas. Column was Zebron ZB- FAME (35 m × 0.25 mm × 0.20 µm). The temperature of the injectorwas270°Candweusedasplitlessinjectionmode(foronemin). Temperaturesoftheinterfaceandionsourcewere250and220°C, respectively.Phenomenex®(Torrance,California,USA)ZB-FAMEcolumn(30m×0.25 mm×0.20 µm)with5mGuardianwasusedwiththe following temperature program: 50°C was maintained for one min, thenthetemperaturewasincreasedat10°C/minto130°C,followed by7°C/minto180°C,and2°C/minto200°C.Thistemperaturewas heldforthreeminutes,andfinally,thetemperatureincreased10°C/ minto260°C.Thetotalprogramtimewas35.14minandthesolvent cuttimewasnineminutes.Fattyacidswereidentifiedbytheretention times(RT)andusingspecificionswhichwerealsousedforquantification(Taipale,Hiltunen,etal.,2016).Fattyacidconcentrationswere calculatedusingcalibrationcurvesbasedonknownstandardsolutions (15,50,100,and250ng)ofaFAMEstandardmixture(GLCstandard mixture 566c, Nu-Chek Prep, Elysian, MI, USA) and using recovery percentageofinternalstandards.ThePearsoncorrelationcoefficient was>0.99foreachindividualfattyacidcalibrationcurve.Additionally, we used 1,2-dinonadecanoyl-sn-glycero-3- phosphatidylcholine (Larodan, Malmö, Sweden) and free fatty acid of C23:0 (Larodan, Malmö,Sweden)asinternalstandardsand tocalculatetherecovery percentages.Thefattyacidcontentofseston(<50 µm)wascalculated basedonphytoplanktoncarbonasdescribedbyTaipaleetal.(2019). Otherwise,fattyacidcontentwascalculatedbasedonthedryweight ofzooplankton,zoobenthos,orfishmuscle. Trophic retention of ARA, EPA, and DHA by zooplankton, Chironomidae, roach, and different ontogenetic stages of perch werecalculatedbythefollowingequation(referredtoasaccumulationfactorbyHessen&Leu,2006): Trophic retention = (FAdiet/FAconsumer) – 1, where FAdiet representsARA,EPA,andDHAcontent(µgmg/C)ofdietandFAconsumer citestheircontentintheconsumers.Theaveragedietcomposition foreachconsumerwastakenfrompreviousstudies.Forherbivorous zooplankton,weusedseston,0+perch,androach.Forplanktivorousperch,weusedherbivorouscladoceran,whereasforbenthivorousperch,weused20%ofherbivorouszooplanktonand80%of Chironomidae.Weused0+ perch androach for piscivorous perch (Estlanderetal.,2010;Ruohonen,2006). 2.6 | Bulk stable isotope analysis and trophic position Approximately 0.6–1.2 mg of freeze-dried seston, zooplankton, benthic invertebrates, or fish muscle sample was weighted and encapsulatedtotincups.The15N/14NwasmeasuredusingaCarlo- Erba Flash1112serieselementalanalysis connectedto a Thermo FinniganDeltaPlusAdvantageisotoperatiomassspectrometerin continuousflowmode.Isotopicdataarepresentedinstandarddelta notationwithunitspermil(‰)andrelativetotheViennaPeeDee Belemnite(VPDB)internationalstandard.Precessionandaccuracy were determined through repeated measurements of an internal workingstandardthatwasfoundtobe0.2and0.3,respectively. Trophiclevel(TL)ofconsumers(herbivorouscladocera(Daphnia andBosmina),Chironomidae,roach,andperch)wasdeterminedby usingδ15Nvalues(Postetal.,2002). where λreferstothetrophicpositionofthebaselineorganism,δ15Nconsumernitrogenstableisotopevalueofagivenconsumer,andδ15Nbaselinenitrogenstableisotopevaluesofbaselineorganism(sestonin ourcase)instudylake.Δ15Nisatrophicfractionationfactorthatwas set3.4‰pertrophiclevelaccordingtoPost (2002).Perchweredividedintoplanktivorous(TL<3.6),benthivorous(TL3.6–3.9),andpiscivorous(TL>3.9)categoriesbasedontrophiclevels. 2.7 | Estimating the herbivorous cladoceran diet We used the measured cladoceran FA profiles to estimate relativecladocerandietcompositions(%).WeusedQuantitativeFatty Acid Signature Analysis in R (QFASAR) (Bromaghin, 2017; Iverson etal.,2004)withχ2distancemeasure(Stewartetal.,2014),which isthemostaccuratecurrentfattyacid-basedmethodforherbivorous cladoceran diet estimation (Litmanen et al., 2020). The diets wereestimatedwithanFAprofilelibraryformedofhomogeneous dietfeedingexperimentsconsistingofdinoflagellates,goldenalgae, cryptophytes,diatoms,greenalgae,euglenoids,cyanobacteria,actinobacteria,andmicrobessustainingon(terrestrial)particulateorganicmatter/detritus(Gallowayetal.,2014;Litmanenetal.,2020). The standard deviation for the diet estimates was produced with 100 sample bootstrapping in QFASAR (Table S2). The estimation was conducted with R Statistical Software v. 3.6.1 (R Core Team, 2019). 2.8 | Statistical analysis WeusedPERMANOVA(Primer7)analysisandBray-Curtissimilarity to compare phytoplankton, zooplankton, and fish community structureatclass,genus,orspecieslevel,usinglaketrophicstatus (mesotrophicoreutrophic)andmonthasfactors.Weusedthesame approachtocomparefattyacidcompositionandcontentofessential fatty acids in phytoplankton (seston), herbivorous cladoceran, benthic invertebrates, and perches. PERMANOVA with Euclidean distance as resemblance matrix was used for univariate analysis (Andersonetal.,2017).Non-metricmultidimensionalscalingNMDS TLconsumer =λ+ ( δ15 N consumer −δ 15 N baseline ) ∕Δ15N,
6 of 18 | TAIPALE ET AL. was used to separate communities’ structure, fatty acid composition, and content of essential fatty acids (Primer 7). The correlationsbetweenMDS1andMDS2andvariableswereanalyzedwith Spearman correlation analysis. Hierarchical Cluster analysis was usedtocreatesimilaritygroupsinNMDS.Weusedbubbleplotsto illustratethetotalbiomassofphytoplankton,zooplankton,andfish communitiesinNMDS. 3 | RESULTS 3.1 | Water quality and phytoplankton community Totalphosphorus,nitrogen,chlorophyll,andturbidityweresignificantlyhigherineutrophicLakeKöyliönjärvithaninmesotrophic LakePyhäjärviandlaketrophicstatusexplained66%ofthedifference( Tables1and2).Whenusingt wofactoranalysis,trophicst atus explained62%ofthevariance(PERMANOVA:Pseudo-F1,13 =71.3, p =.001)andmonthexplained9%ofthevariationofphosphorus, nitrogen, chlorophyll, and turbidity (PERMANOVA: Pseudo-F1,13 (trophicstatus/month)= 40.6./2.9, p =.001/.045).ThetemperatureofsurfacewaterwasequalinbothlakesandwhereasSecchi depthwashigherinthemesotrophicLakePyhäjärvi thanin the eutrophic Lake Köyliönjärvi during the open water season 2017 (Table2). Cyanobacteria,diatoms,andgreenalgaewerepercentuallythe threemostabundanttaxaineutrophicLakeKöyliönjärvi,whereas cyanobacteriaanddiatomswerepercentuallythemostcommon classesinLakePyhäjärvi.Thecontributionofdinoflagellatesduring summermonthswassignificantlyhigherinLakePyhäjärvithanin LakeKöyliönjärvi,butotherwise,thelakesdidnotdifferintheir phytoplanktoncompositionatclasslevel(seeTable2).However, the contribution of DHA-synthesizing taxa (cryptophytes, dinoflagellates, golden algae) was higher in the mesotrophic lake (24.3±12%ofall)thanintheeutrophiclake(6.8±7.7%).Total phytoplanktonbiomasswashigherineutrophicLakeKöyliönjärvi thaninmesotrophicLakePyhäjärvi(seeFigure1).However,comparisonatclasslevelshowedthatonlybiomassesofgreenalgae washigherineutrophicLakeKöyliönjärvithaninmesotrophicLake Pyhäjärvi,whereasdiatombiomasswashigherinthemesotrophic Lake Pyhäjärvi than in the eutrophic Lake Köyliönjärvi (refer to Figure 1, Table 2). Due to the higher biomass of diatoms in the eutrophicLakeKöyliönjärvi,thebiomassofEPA-synthesizingtaxa wasalsohigher,whereasthebiomassofDHA-synthesizingtaxadid notdifferbetweenlakes(Table2).AccordingtothePERMANOVA, each lake explained 51% of the variation in phytoplankton biomasses at class level but explained only 36% of variation at the genuslevel(Table2). NMDSoutputshowedthatphytoplanktoncommunitystructure variedgreatlybetweenthetwolakesbutvariedmore,duringsummer months, in mesotrophic Lake Pyhäjärvi than in eutrophic Lake Köyliönjä r vi(F igure1c).Mor eove r,s imila ri tya na ly sis(SI MPER )showed thatthedissimilarityofphytoplanktoncommunitiesatthegenuslevel betweenthelakeswasrelativelyhigh(89.4%).Cyanobacteriagenus ofDolichospermumandMicrocystisanddiatomgeneraofAulacoseira weremoreabundanttaxaineutrophicLakeKöyliönjärvithaninmesotrophic Lake Pyhäjärvi, whereas Aphanizomenon (Cyanobacteria) was more abundant in the mesotrophic than in the eutrophic lake. The closer comparison of EPA- and DHA-synthesizing phytoplankton genus (SIMPER: Average dissimilarity =78.7%)showedthat Aulacoseira, Acanthoceras, Uroglena, Rhodomonas, Cryptomonas, and CeratiumweremoreabundantineutrophicLakeKöyliönjärvi(explaining61.1%ofdissimilarity).WhereasDinobryon,Tabellaria,Fragilaria, Rhizosolenia,andGymnodiniumweremoreabundantinmesotrophic LakePyhäjärvi(explaining15.4%ofdissimilarity). 3.2 | Zooplankton community NMDS output revealed changes in the zooplankton community structure between the lakes but also by the season (see Figure2c).Two-factorPERMANOVAofzooplanktonbiomassesat genus level showed the following statistical difference between the lakes (PERMANOVA (lake/month): Pseudo-F1,11 = 4.3/3.3, p =.017/.009).Lakeandmonthaccountedfor21%and32%ofall variation,respectively.Accordingtothesimilarityanalysis,mostof the difference between the lakes (SIMPER: average dissimilarity 67.8%)wasexplainedbythegenusoftheChydorus,Eudiaptomus, andMesocyclops,whichweremoreabundantintheeutrophicthan inthemesotrophiclake.However,Bosminawasmoreabundantin themesotrophicthanintheeutrophiclake.Nevertheless,herbivorouscladoceranwasthemostabundantzooplanktongroupinboth lakes (Figure 2a), of which Chyrodus, Daphnia, and Bosmina were the most abundant genus. Eudiaptomus graciloideswastheonly abundantherbivorouscalanoidinbothlakesandwerethesecond- most abundant zooplankton group with predator cyclopoids in bothlakes.Megacyclops,Mesocyclops,andThermocyclopswereall abundantinmesotrophicLakePyhäjärviwhereasMegacyclops did notoccurintheeutrophicLakeKöyliönjärvi.Predatorycladoceran (Leptodoras kindtii)wastheonlyzooplanktongroupwhichdiffered statistically significantly between lakes being more abundant in eutrophic Lake Köyliönjärvi than in mesotrophic Lake Pyhäjärvi (Table2,Figure2b). 3.3 | Benthic and fish communities Our benthic invertebrate sampling was not quantitative, but our samplingintwolakesshoweddifferencesinthepresenceofvarious benthicinvertebrates.Meanwhile,wefoundonlyChironomidaein eutrophicLakeKöyliönjärvi,whileoursamplingofmesotrophicLake PyhäjärviresultedinfindingseveralindividualsofAsellus aquaticus, Ephemeroptera,Oligochaeta,Megaloptera,andPlecoptera. Figure3ashowedthattheTotalBPUE(kgfishpergillnetnight) andCPUE(numberoffishpergillnetnight)in2012–2020washigher in eutrophic Lake Köyliönjärvi than in mesotrophic Lake Pyhäjärvi
| 7 of 18 TAIPALE ET AL. (Table 2). Laketrophicstatus explained83%and 79% ofthevariationin BPUE and CPUE, respectively.Thepercidswerefoundto contribute(BPUE%)20.6±6.1%and55.3.6±5.0%oftotalBPUEin eutrophicLakeKöyliönjärviandmesotrophicLakePyhäjärvi,respectively.Conversely,thecontributionofcyprinidswashigherinLake Köyliönjärvi(66.3±3.2%)thaninLakePyhäjärvi(18.6±6.5%).Roach (Rutilus rutilus)wasthemain(BPUE%= 42 ±4%)fishspeciesinLake Köyliönjärvianditsbiomasswasstatisticallyhigher(Table2)thanin LakePyhäjärvi.Correspondingly,perch(Perca fluviatilis)wasthemain (BPUE%=39±7%)fishspeciesintheLakePyhäjärvi;however,the BPUEofperchdidnotdifferbetweenlakes(Table2).Accordingto theSIMPER(averagedissimilaritybetweenlakes=50.7%,Table2) andNMDS(Figure3c),bleak,smelt,whitefish,andruffeweremore prevalent (BPUE%) in mesotrophic Lake Pyhäjärvi, whereas pike, pikeperch,bream,andwhitebreamweremoreprevalentineutrophic LakeKöyliönjärvi. Theabundanceofdifferentontogeneticgroupsofperchesdid notdifferstatisticallybetweenthelakesduetothehighvariationin mesotrophicLakePyhäjärvi(refertoFigure3b).However,planktivorousperchcontributed91±3%ofallperch(CPUE%)ineutrophic TABLE 2 StatisticalresultsforPERMANOVAbetweenmesotrophicandeutrophiclakes.%citestothecontribution,FA%tofattyacid profile,concentrationtoµgFAmg/L,%,QFASAtothecontributionoffattyacid-baseddietestimates Component Df1 Df2 PseudoF P(perm) Difference Totalnitrogen 113 23.8 0.003 Mesotrophic<eutrophic Totalphosphorus 113 15.2 0.003 Mesotrophic<eutrophic Chlorophylla 113 31.6 0.001 Mesotrophic<eutrophic Turbidity 113 87.9 0.001 Mesotrophic<eutrophic Secchi depth 113 179.5 0.001 Mesotrophic>eutrophic Temperature 113 <0.001 1Mesotrophic=eutrophic Dinoflagellates(%) 111 3.9 0.04 Mesotrophic>eutrophic DHA-synth.taxa(%) 111 8.5 0.023 Mesotrophic>eutrophic Totalphytoplanktonbiomass 110 9.3 0.0018 Mesotrophic<eutrophic Diatoms(biomass) 110 9.3 0.005 Mesotrophic>eutrophic Greenalgae(biomass) 110 526 0.002 Eutrophic> mesotrophic Phytoplanktonbiomass(class) 110 9.3 0.023 Mesotrophic<eutrophic Phytoplanktonbiomass(genus) 111 6.2 0.003 Mesotrophic<eutrophic EPA-synth.taxa(biomass) 111 12.2 0.002 Mesotrophic>eutrophic DHA-synth.taxa(biomass) 111 0.002 0.95 Mesotrophic=eutrophic Predatorycladoceran 111 3.5 0.042 Mesotrophic<eutrophic BPUE 1 7 23.2 0.035 Mesotrophic<eutrophic CPUE 1 7 28.3 0.036 Mesotrophic<eutrophic Roach(biomass) 1 7 48.1 0.033 Mesotrophic<eutrophic Perch(BPUE) 1 7 0.27 0.641 Mesotrophic=eutrophic Seston(FA%) 112 22 0.002 Mesotrophic≠eutrophic Herbivorouscladoceran(FA%) 112 4.4 0.001 Mesotrophic≠eutrophic Chironomidaelarvae(FA%) 1 5 20.5 0.004 Mesotrophic≠eutrophic Roach(FA%) 1 8 3.2 0.059 Mesotrophic=eutrophic Perch(FA%;allsizestogether) 193 7.7 0.001 Mesotrophic≠eutrophic Perch,youngoftheyear(FA%) 122 13.4 0.001 Mesotrophic≠eutrophic Perch,planktivorous(FA%) 122 6.5 0.003 Mesotrophic≠eutrophic Perch,benthivorous(FA%) 126 11.2 0.001 Mesotrophic≠eutrophic Perch,piscivorous(FA%) 113 3.1 0.024 Mesotrophic≠eutrophic SestonicEPA(concentration) 125 0.025 0.864 Mesotrophic=eutrophic SestonicDHA(concentration) 125 49.6 0.001 Mesotrophic>eutrophic Goldenalgae(%,QFASA) 110 10.2 0.024 Mesotrophic>eutrophic Crypto(%,QFASA) 110 13.3 0.013 Mesotrophic>eutrophic tPOMmicrobes(%,QFASA) 110 6.2 0.034 Mesotrophic<eutrophic Dinoflagellates(%,QFASA) 110 2.1 0.169 Mesotrophic>eutrophic
8 of 18 | TAIPALE ET AL. Lake Köyliönjärvi, but 75 ± 17% of all perch in Lake Pyhäjärvi. Moreover,benthivorousperchcontributed20±15%ofallperchin LakePyhäjärvi,butonly6±3%ofallperchinKöyliönjärvi.Thecontributionofpiscivorousperchtooverallpercheswassimilarinboth lakes(~3 – 5 % ) . 3.4 | Food web structure based on fatty acids Accordingtothetwo-factorPERMANOVAanalysis(PERMANOVA (lake/species): Pseudo-F1/12145 = 6.2/124.3, p =.001),laketype explainedonly0.5%andspecies(organism)84%ofFAvariation, FIGURE 1 Phytoplanktonbiomassof thethreemostabundantclasses(a)and threehighnutritionalqualityclasses(b) inLakeKöyliönjärvi(eutrophic)andin LakePyhäjärvi(mesotrophic).(c)Non- metricmultidimensionalscalingoutput ofbiomassesofdifferentphytoplankton genera.Vectorscitetothephytoplankton genuswiththestrong(r >.75,p <.01) Pearsoncorrelation.Greenalgaeciteto thegenusofColeastrum,Monoraphidium, Oocystis,Pediastrum,andScenedesmus; CyanoscitetothegenusofChroococcus, Cyanodictyon,Microcystis,and Woronichia.Bubbleplotsshowthetotal phytoplanktonbiomassofthesampleand dashedlinesincludesampleswitha40% similarity FIGURE 2 Zooplanktonbiomassofthe (a)herbivorouscalanoids(Eudiaptomus), cyclopoids(Cyclopoida)andcladocerans (Bosmina,Ceriodaphnia,Chyrodys,Daphnia, Diaphanosoma,Holopedium,Limnosida) and(b)predatorcalanoids(Heterocope), cyclopoids(Eucyplops,Macrocyclops, Megacyclops,Mesocyclops,Thermocyclops), andpredatorycladocerans(Leptodora kindtii)inLakeKöyliönjärvi(eutrophic)and inLakePyhäjärvi(mesotrophic).(c)Non- metricmultidimensionalscalingoutput ofbiomassesofdifferentzooplankton genera.Vectorscitetothezooplankton genuswiththestrong(r >.60,p <.01) Pearsoncorrelation.Bubbleplotsshow thetotalzooplanktonbiomassofthe sampleanddashedlinesincludesamples with50%similarity
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