Distribution trends of European dragonflies under climate change
Tim Termaat1,2 | Arco J. van Strien3 | Roy H. A. van Grunsven1 | Geert De Knijf4 | Ulf Bjelke5 | Klaus Burbach6 | Klaus‐Jürgen Conze7 | Philippe Goffart8 | David Hepper9 | Vincent J. Kalkman10 | Grégory Motte8 | Marijn D. Prins1,11 | Florent Prunier12 | David Sparrow13 | Gregory G. van den Top1 | Cédric Vanappelghem14,15 | Michael Winterholler16 | Michiel F. WallisDeVries1,17
AbstractAim: Polewardrangeshiftsofspeciesareamongthemostobviouseffectsofclimatechangeonbiodiversity.Asaconsequenceoftheserangeshifts,speciescommunitiesarepredictedtobecomeincreasinglycomposedofwarm‐dwellingspecies,butthishas only been studied for a limited number of taxa,mainly birds, butterflies andplants.Asspeciesgroupsmayvaryconsiderablyintheiradaptationtoclimatechange,it isdesirabletoexpandthesestudiestoothergroups,fromdifferentecosystems.Freshwater macroinvertebrates, such as dragonflies (Odonata), have been rankedamongthespeciesgroupswithhighestpriority.Inthispaper,weinvestigatehowthe
Climatechangehasaprofound impactontheoccurrenceofmanyspecies of plants and animals (Parmesan & Yohe, 2003; Root etal., 2003;Walther et al., 2002).One of themost distinctive con‐sequencesisthepolewardshiftofspeciesdistributionrangesasaresultof increasingtemperatures,resulting inchanges inthecom‐position of species communities (Chen, Hill, Ohlemüller, Roy, &Thomas,2011;Hickling,Roy,Hill,Fox,&Thomas,2006;Kampichler,VanTurnhout,Devictor,&VanderJeugd,2012;Lindström,Green,Paulson,Smith,&Devictor,2013;Masonetal.,2015).Speciesvaryintheirresponsetoclimatewarming,duetodifferenttemperaturerequirementsanddifferentdispersalandcolonizationcapacities.Ingeneral,warm‐dwellingspeciesandspecieswithgooddispersalca‐pacityaremorelikelytobe“winners”thancold‐dwellingspeciesandspecieswithpoordispersalcapacity(Francoetal.,2006;Rosset&Oertli,2011;Virkkala&Lehikoinen,2014).Asaconsequence,com‐munitiesarepredictedtobecomeincreasinglycomposedofwarm‐dwelling,mobilespecies.
Thismayseemstraightforward,buttheeffectsofclimatechangeon species’ trends and community compositions have only beenstudiedfora limitednumberoftaxa(butseeHicklingetal.,2006;Masonetal.,2015),mainlybirds,butterfliesandplants(Bertrandetal.,2011;Britton,Beale,Towers,&Hewison,2009;Clavero,Villero,&Brotons,2011;Davey,Devictor,Jonzén,Lindström,&Smith,2013;
Devictoretal.,2012a;Jiguetetal.,2010;Roth,Plattner,&Amrhein,2014;Virkkala&Lehikoinen,2014).Togainabetterunderstandingofhowclimatechangeaffectstotaldiversity,moretaxaneedtobecovered,includingtaxafromdifferenthabitats.Freshwatermacroin‐vertebratesshouldberankedamongthefaunalgroupswithhighestpriority,astheyhaveverydifferentlifehistoriesfrombirdsandbut‐terfliesandoccupyverydifferentecosystems.Theyareknowntoreactquicklytoawiderangeofchangesintheirhabitats(Rosenberg&Resh, 1993). Furthermore, freshwater covers only 0.8% of theEarth's surface, while supporting almost 6% of all described spe‐cies,mostofwhichareinsects(Dijkstra,Monaghan,&Pauls,2014;Dudgeonetal.,2006).Atthesametime,theyareamongthemostseverelythreatenedecosystemsintheworld,withaquaticspeciesbeingmorethreatenedthanterrestrialspecies(Collenetal.,2014;Darwalletal.,2018;Dudgeonetal.,2006).Forthesereasons,fresh‐water invertebrateshavebeenindicatedasanessentialfuturead‐ditiontoEurope'sbiodiversitymonitoringprogramme(Feest,2013;Thomas,2005).
Unfortunately, monitoring freshwater invertebrates comeswithdrawbacks.Mostgroupsaresospecies‐rich thatcollecting,sortingandidentifyingsamplestospecies levelrequiremuchef‐fortandexperience.Therefore,thenumberofspecialistsstudyingthesegroupsis,inmostcountries,limited,whichresultsinanin‐completepictureofspecies’distributions.Dragonflies (Odonata)present an exception to this rule. Adult dragonflies are large,
occurrence of dragonflies in Europe has changed in recent decades, and if thesechangesareinparallelwithclimatechange.Location: Europe.Methods: Weuse data from10 European geographical regions to calculate occu‐pancy indicesandtrendsfor99 (69%)of theEuropeanspecies.Next,wecombinetheseregionalindicestocalculateEuropeanindices.Todetermineifchangesinre‐gionaldragonflycommunitiesinEuropereflectclimaticwarming,wecalculateSpeciesTemperatureIndices(STI),Multi‐speciesIndicators(MSI)andCommunityTemperatureIndices(CTI).Results: 55of99consideredspecies increased inoccupancyatEuropean level,32speciesremainedstable,andnonedeclined.Trendsfor12speciesareuncertain.MSIof cold‐dwelling andwarm‐dwelling species differ in some of the regions, but in‐creasedatasimilarrateatEuropeanlevel.CTIincreasedinallregions,exceptCyprus.TheEuropeanCTIincreasedslightly.Main conclusions: Europeandragonflies,ingeneral,haveexpandedtheirdistributioninresponsetoclimatechange,eventhoughtheirCTIlagsbehindtheincreaseintem‐perature.Furthermore,dragonfliesprovedtobeasuitablespeciesgroupformonitor‐ingchangesincommunities,bothatregionalandcontinentallevel.
colourful insects, which are easy to spot and relatively easy toidentify at species level,making them attractive to a large pub‐lic.Withamanageable143speciesrecordedinEurope(Kalkmanet al., 2018), they constitute a suitablegroup for citizen scienceprojects.Furthermore,dragonfliesarewellestablishedasusefulorganismstoassessandmonitoraquaticandwetlandecosystemquality(Oertli,2008),andtheyareknowntoreactquicklytocli‐mate change (Bush, Theischinger, Nipperess, Turak, & Hughes,2013;Hassall,2015).
InmostEuropeancountries,dragonfly recordinghas increasedinrecentdecades,mediatedbythepublicationofseveralgoodfieldguidesandnationaldistributionatlases.ThishasresultedinasteepincreaseinavailabledistributiondatafromcitizenscienceprojectsandthepublicationofaEuropeandistributionatlasin2015(Boudot&Kalkman,2015).Themajorityofthesedistributiondatarefertorecordscollectedwithoutstandardization,whichareunsuitableforstraightforwardcalculationofdistributionstrends.However,previ‐ous studieshave shown that these “opportunistic” recordscanbeusedtoderivereliabletrendestimatesofdragonfliesonanationalscale,ifoccupancymodelsareapplied.Thesemodelstaketheimper‐fectdetectionofspeciesintoaccount,andthereby,theymaysimul‐taneouslycorrectforobservationandreportingbiasaswell(Isaac,
Van Strien,August,DeZeeuw,&Roy, 2014;Van Strien, Termaat,Groenendijk, Mensing, & Kéry, 2010; Van Strien, Van Swaay, &Termaat,2013).Moreover,VanStrien,Termaatetal.(2013)showedinapilotstudy,usingrecordsofasinglespeciesfromfivewesternEuropeanregions,thatoccupancyindicesfrommultipleregionscanbecombinedtocalculatesupraregionalindicesandtrends.
Inthispaper,weinvestigatehowtheoccurrenceofdragonfliesinEuropehaschangedinrecentdecades,andifthesechangesareinparallelwithclimatechange.Weusedistributiondatafrom10Europeangeographicalregions—rangingfromSwedentoCyprus—tocalculateoccupancy indicesandtrends forasmanydragonflyspecies as possible.Next,we combine these regional indices tocalculate European indices. To determine if changes in regionaldragonflycommunitiesinEuropereflectclimaticwarming,wecal‐culateSpeciesTemperatureIndices(STI),Multi‐speciesIndicators(MSI)andCommunityTemperatureIndices(CTI).Wehypothesizethat (a) warm‐dwelling species have more positive trends thancold‐dwellingspecies, that,asaconsequence, (b)warm‐dwellingspecies have increased their share in regional communities and(c)thattheseeffectsincreaseonasouth–northgradientthroughEurope,astheratioofwarm‐andcold‐dwellingspeciesdecreaseswithincreasinglatitude.
F I G U R E 1 ParticipatingEuropeangeographicalregions,hereconsideredascountriesorloweradministrativedivisions
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2 | METHODS
2.1 | Species records
We gathered dragonfly distribution records, from 1990 onwards,from the following European geographical regions (countries orlower administrative divisions, hereafter referred to as “regions”):Sweden,Britain (UnitedKingdomexcludingNorthern Ireland), theNetherlands,NorthRhine‐Westphalia (aGerman state),Bavaria (aGerman state), Flanders (a Belgian region, including Brussels re‐gion),Wallonia (aBelgian region),France,Andalusia (aSpanishau‐tonomouscommunity)andCyprus(Figure1).Theresultingdatasetincluded recordsof99 species,whichequals69%of all dragonflyspeciesrecordedinEurope(Kalkmanetal.,2018).
Allrecordsusedinthisstudycoveradultdragonfliesonly.Themajority of these records are “opportunistic,” that is, collectedwithout a standardized field protocol and without a design en‐suringthegeographical representativenessofsampledsites.Theperiodofdatacoverageandthenumberofrecordsperunitareavary considerably among regions, depending on data availability(Supporting Information Table S1). All data in each region werevalidated by experts to prevent false‐positive records. To stan‐dardizethegeographicalreferencesystem,allobservationsweremapped in the ETRS89/ETRS‐LAEA (EPSG:3035) reference sys‐tem.Becauseweused1×1kmgridsquaresasthedefinitionofasiteinouranalyses,allobservationswerereferencedto1×1kmETRS‐LAEAsquares.
2.2 | Generating non‐detection data
Occupancy models require detection/non‐detection data col‐lectedduringreplicatedvisits.Validreplicatedvisitsareonlythosevisitsmadeinaperiodofclosurewithintheyear;thisistheperiodduringwhichasiteisconsideredeithertobeoccupiedorunoccu‐piedbythespeciesandnotabandonedorcolonized(MacKenzieetal.,2006).Fordragonflies,weconsideredtheperiodofclosureasthemainflightperiodofaspecies.Closureperiodsweredefinedfor each combination of species and region. For each combina‐tion,approximately5%ofboththeearliestandthelatestrecordswereexcluded,resultinginthespecies’mainflightperiod.Thesemain flightperiodswereexpressed in Juliandates.Forexample,weusedJuliandates125–210astheclosureperiodofPyrrhosoma nymphula(anearlyflyingspecies)inFranceandJuliandates200–240astheclosureperiodofAeshna viridis(alateflyingspecies)inSweden.
Almostalldataobtainedwererecordsofspeciespresence.Thenon‐detectionrecordsofagivenspeciesweregeneratedfromtheinformation of sightings of other dragonfly species, followingVanStrienetal.(2010)andVanStrien,VanSwaayetal.(2013).Anyob‐servationofagivenspecieswastakenas1(detection),whereaswerated0(non‐detection) ifanyspeciesotherthanthegivenspecieshadbeenreportedbyanobserverataparticular1×1kmsiteandonaparticulardatewithinthespecies'closureperiod.
2.3 | Species trend analysis
2.3.1 | Annual occupancy estimates and trends: regional level
First,wecalculatedannualoccupancyperspecies,foreachregionseparately.WeappliedthesamedynamicoccupancymodelasVanStrienet al. (2010) andVanStrien,VanSwaayet al. (2013) toes‐timate annual occupancy ψ, adjusted for detection probability p. Because all parameters in themodelmay differ between regions,theanalyseswereperformedseparatelyforeachregionandthere‐gionalresultswerecombinedinasecondstep.ThedescriptionofthemodelisderivedfromRoyleandKéry(2007)andRoyleandDorazio(2008).Here,ψ istheproportionofsuitable1×1kmsquaresthatisoccupied.Asquareisdefinedassuitableifthespecieshadbeenrecordedthereat leastonce in1990–2008.Theoccupancymodelconsistsoftwohierarchicallycoupledsubmodels,oneforoccupancyandonefordetection,thelatterbeingconditionalontheoccupancysubmodel.Theoccupancysubmodelestimatesannualprobabilityofpersistenceφt andofcolonizationγt andcomputes theannualoc‐cupancyprobabilitypersiterecursivelythrough:
Thus,whethersiteioccupiedinyeart−1isstilloccupiedinyeartisdeterminedbythepersistenceprobability,andwhethersitei un‐occupiedinyeart−1isoccupiedinyeartdependsonthecoloniza‐tionprobability.Alloccupancyprobabilitiespersite togetheryieldtheestimatedannualnumberofoccupied1×1kmsitesperregion.Thesamesiteswereincludedintheanalysisforallyears;estimatesfor sites not surveyedduring someyearswerederived from sitesthatweresurveyedinthoseyears.
Thedetectionsubmodelestimatestheyearlydetectionp,butinaddition,pismadeasafunctionofcovariates.WeusedtheJuliandate as a covariate forp because thedetectionof the species isexpectedtovaryovertheseason,duetochangingpopulationsizeduringthecourseoftheflightperiod.Detectionisalsoreducedifobserversdonotreportalltheirsightings.Hence,weincludetheincompletenessofrecordingasacovariatefordetection.Wedis‐tinguished: (a) single recordsofany speciesonone siteanddatewithoutrecordsofotherspecies,(b)shortday‐lists,thatis,recordsoftwoorthreespeciesmadebyasingleobserverononesiteanddateand(c)comprehensiveday‐lists,thatis,recordsofmorethanthreespeciesperobserver,siteanddate.These listsmayormaynotincludethespeciesinquestion.Thesecategorythresholdsaresufficientlylownottobeconfoundedbyrealdifferencesinspeciesnumberbetweensites.Inmost1×1kmsitesintheregions,therearemore than three species to be found and oftenmanymore.Effectsofbothcovariateswereincludedinthedetectionsubmodelviaalogitlink:
�it=�i,t−1�t−1+ (1−�i,t−1)�t−1
logit(pijt)=�t+�1 ∗dateijt +�2 ∗date2ijt
+�∗1(short day - list)ijt+�∗
2(comprehensive day - list)ijt,
| 5TERMAAT ET Al.
wherepijtistheprobabilitytodetectthespeciesatsiteiduringvisitj in year t,αtistheannualinterceptimplementedasarandomeffect,β1 and β2are the linearandquadraticeffectsof thedateofvisit j and δ1 and δ2aretheeffectsofshortday‐listsandcomprehensiveday‐lists,relativetosinglerecords.
We fitted themodels in aBayesianmodeof inference usingJAGS(Plummer,2017)onthecomputerclusterLISA(https://sub‐trac.sara.nl). We chose uninformative priors for all parameters,using uniform distributionswith values between 0 and 1 for allparametersexceptδ1 and δ2 (valuesbetween−10and10),β1,β2 (valuesbetween−10and10)andαt(valuesbetween0and5)forthestandarddeviationofthenormaldistributionusedaspriorfortherandomyeareffect.
Foreachanalysis,weranthreeMarkovchainswithsufficientit‐erations toensureconvergenceas judged from theGelman‐RubinRhatstatisticandsavedthelast93iterationsforuseatsupraregionallevel.Thisnumberof iterations isanempiricallyobtainedcompro‐mise between the reliability of the estimates and data handlingcapacity.Themodelproducedannualestimatesofoccupancyperre‐gion,whichwereconvertedintoannualindiceswithfirstyear=100.Thetrendinoccupancywasconsideredsignificantifitsconfidenceintervaldidnotincludezero.
2.3.2 | Annual occupancy estimates and trends: European level
In thenext step, theannualoccupancyestimatesper regionwereaggregatedtoobtainEuropeanoccupancyindicesandtrendsfortheperiod 1990–2015.Missing yearly values from a particular regionwereestimated (“imputed”) fromaveragedyear‐to‐yearoccupancyratios in all other regions. For example, 1990 was missing in theSwedishdataset.To imputeoccupancyestimatesofSwedishspe‐cies,we applied the1991/1990 ratios fromall other regionswithdatafrombothyears.Asaconsequenceoftheseimputations,con‐fidenceintervalsincreasedforyearswithlackingdatafromoneormoreregions,especiallywhenthesewerelargeregions(e.g.,France).
Regionsdifferinthenumberofsitessurveyed,soanaiveaggre‐gationhastheriskofbiasedEuropeantrends.Hence,wedevelopedaproceduretoweighregionsaccordingtothesamplingintensityinrelationtotherangeofspeciesineachregion.ThisprocedureisanadaptationofproceduresappliedbyVanSwaay,Plate,andVanStrien(2002)andGregoryetal.(2005).Weightswerecalculatedasthequo‐tientofrelativerangeandrelativesamplingintensitytocompensateforoversamplingandundersampling.Relativerangewasdefinedastherangeofaspeciesinaregion,asapercentageofitstotalrangeinallregionsforwhichanoccupancyindexcouldbeobtained.Relativesampling intensitywasdefinedas thenumberof1×1kmsquaressurveyedatleastonceinthisperiodwithintheregionalrangeofthespecies, relative to the totalnumberof surveyedsquares inall re‐gionswithindices.Weightsperregionweresimilarforeachyearbe‐causethesamesiteswereintheanalysisforallyears.TheweightednumbersofoccupiedsiteswereaddedacrossregionsandconvertedintoEuropeanannualindiceswith1990=100.Wetookintoaccount
WecalculatedtheSTIforeachdragonflyspeciesoccurringinEurope(Boudot&Kalkman,2015) (Supporting InformationTableS2).TheSTIofagivenspeciesistheaveragetemperature(expressedinde‐greesCelsius)oftheEuropeanpart(excludingRussia)ofthespecies’rangeandistakenasaproxyforspecies’dependenceontempera‐ture.Thesecalculationswerebasedon2,736siteswithspeciesre‐cordsunderlyingtherangemapsof theEuropeanatlasbyBoudotandKalkman(2015;availablethroughKalkmanetal.,2018)andcli‐matedataofWorldClim(http://www.worldclim.org;accessedMarch2017;averagemonthlytemperaturesfor1960–1990).Theanalyseswerecarriedoutata50×50kmgridscale.Foreachgridsquare,wecalculatedtheannualmeantemperaturetoestimatetheSTIasthemean temperature of occupied squares.Although the distributiondatacoveredEuropetoagreatextent,wefounditnecessarytocor‐rectfordifferencesinsamplingintensitybetweenregions.Thiswasachievedbybootstrapping,whichconsistedof100 replicationsofasubsetofrandomlychosen50x50gridsquareswithinanareaof250×250km.STIswereestimatedasthemeantemperatureofalloccupiedsquaresoverallreplications.
The period covered by the temperature data fromWorldClim(1960–1990) differed from the period covered by the atlas’ rangemaps (>1990).However, relative differences in STI among speciesarerobusttothetimewindowconsidered(Devictoretal.,2012b).
2.5 | Multi‐species Indicators
To determinewhether warm‐dwelling species havemore positivetrends than cold‐dwelling species, we calculated Multi‐speciesIndicators (MSI), by combining the trends in occupancy indices ofcold‐dwelling and of warm‐dwelling species, respectively.We didthis for each region separately and for Europe as a whole. Cold‐dwellingspeciesweredefinedasspecieswithSTIlowerthan9.8°C,whichisthemedianSTIofallspeciesincludedinourstudy.Warm‐dwellingspeciesweredefinedasspecieswithSTI>9.8°C.StandarddeviationsofSTIdidnotdifferbetweenthetwogroups (one‐wayANOVA,F(1,97)=0.554,p=0.458).
MSIwerecalculated including theirconfidence intervals,usingtheRscript“MSItool”(Soldaat,Pannekoek,Verweij,VanTurnhout,&VanStrien,2017).Thismethodisdevelopedtoaccountforsam‐pling error of species indices in the calculation of Multi‐speciesIndicators, by calculating confidence intervals using Monte Carlosimulationsofannualspeciesindices.
2.6 | Community Temperature Indices
Ultimately, we calculated a CTI for each region, as the averageSTI of all species in the region, weighted by species occupancies
(probabilities of occurrence). CTI is thus expressed in degreesCelsius.Similarly,wecalculatedEuropeanCTI.AtemporalincreaseinCTIdirectly reflects that the speciesassemblage is increasinglycomposedofspeciesthatoccurathighertemperatures(thatiswithhigh STI). With this approach, we follow Devictor et al. (2012a),withtheprincipaldifferencethatwefocusonregionalcommunitiesbasedonoccupancydatafromkmsquares,insteadoflocalcommu‐nitiesbasedonabundancedatafromtransects(althoughDevictoretal.,2012aalsoincludedananalysisonpresence–absencedatawhichcompareswithourapproach).
In7outof10 regions,morespecies increased thandecreasedtheiroccupiedrange(Table1).TheseregionswereSweden,Britain,theNetherlands,North Rhine‐Westphalia, Flanders,Wallonia andFrance.NosignificantdifferencebetweenincreasinganddecliningspecieswasfoundforBavaria,becausethisregionhadahighnum‐berofstablespecies(36of59speciestrendswithsufficientlylowstandarderrors).ForAndalusiaandCyprus,thenumberofspeciestrendswith sufficiently low standard errorswas too small to findsignificantdifferencesbetweentrendclasses.
For all regions combined, 55 species moderately increased inoccupancy, indicating that they expanded their distribution at aEuropean level,32species remainedstableandnonedeclined.Asan example, indices of Sympecma fusca (a moderately increasingspecies) and Gomphus vulgatissimus (a stable species) are showninFigure2.Trendestimatesof12 specieshad too large standarderrors. European indices and trends of all species are provided inSupportingInformationDataS2.
TA B L E 1 Numberofspeciespertrendclasspergeographicalregion(fromnorthtosouth)andforEurope
Region Trend period N species Increase Stable Decline Uncertain % Increase χ2 p
F I G U R E 2 Europeanindex(1990–2015)ofSympecma fusca and Gomphus vulgatissimus.Linearregressionlines(dashedlines)werealignedthroughtheyeareffectstosummarizeoverallchange
MSIofwarm‐dwellingspecieswereincreasinginallregions(Figure3).Surprisingly,MSIofcold‐dwellingspeciesalsoincreasedinSweden,Britain, the Netherlands and North Rhine‐Westphalia. In Flanders,
F I G U R E 3 Multi‐speciesIndicators(MSI)ofwarm‐dwellingspecies(SpeciesTemperatureIndex>9.8°C)andcold‐dwellingspecies(SpeciesTemperatureIndex<9.8°C)pergeographicalregion(fromnorthtosouth)andforEurope.Thefirstyearwithdatawassetto100.Smoothedtrendlineswereplottedthroughtheyeareffectstosummarizeoverallchange.Shadedareasrepresentconfidenceintervals.Pleasenotethaty‐axesdiffer
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Wallonia and France, MSI of cold‐dwelling species was stable, inBavariaitdeclined,andinAndalusia,itwasuncertain(Table2).Cyprushas only one cold‐dwelling species (Enallagma cyathigerum), whichincreased.
ComparingMSItrendsofwarm‐dwellingandcold‐dwellingspe‐cies (Table2) shows the formerwas significantlymorepositive inBritain, the Netherlands, Flanders, Wallonia, Bavaria and France.
CTI increased in all regions, except Cyprus (Table 3; SupportingInformation Figure S1). Themost significantly increasing CTI was
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F I G U R E 3 (Continued)
| 9TERMAAT ET Al.
found for the Netherlands. The Dutch dragonfly fauna “warmed”at 9.5×10−3°Cyear−1 over the period 1991–2015 (0.23°C overthewholeperiod).Theweakest increasewas found forBritain, at1.2×10−3°Cy−1overtheperiod1990–2015(0.03°Coverthewholeperiod).TheEuropeanCTIincreasedjustasslowly,at1.2×10−3°Cy−1 overtheperiod1990–2015(0.03°Coverthewholeperiod).
4 | DISCUSSION
We found clear effects of climate changeon severalwarm‐dwell‐ingspecies,consistentwithobservedchangesinEuropeandistribu‐tionsinthelastfewdecades(Boudot&Kalkman,2015).Inaddition,thedifferencesinMSIofwarm‐dwellingandcold‐dwellingspecies
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F I G U R E 3 (Continued)
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indicate that climate changehas changeddragonfly occurrence atthecommunitylevelaswell.
4.1 | Testing of hypotheses
4.1.1 | Regional level
Wehypothesizedthat(a)warm‐dwellingspeciesshowmoreposi‐tive trends than cold‐dwelling species and this was confirmedfor 6 of 10 studied regions (Bavaria, Britain, Flanders, France,Netherlands,Wallonia). In Sweden—the most northern region inour study—bothMSI of cold‐dwelling species andMSI ofwarm‐dwelling species were stable between 1990 and 2001 and bothincreasedinacomparablepacefrom2002onward.Thissuggeststhat climatic conditions in the 1990s were probably limiting formostspeciesinSweden,includingcold‐dwellingspecies.Withtheexceptionofsomeextremecold‐tolerantspecies,suchasA. caeru-lea and Somatochlora sahlbergii, all Swedish species reach theirnorthernrangelimit inthisregion.Recenttemperaturerisesthusappeartohaveresultedinimprovedconditionsfornearlyallspe‐cies.Furthermore,weexpectedthat(b)warm‐dwellingspecieshadincreasedtheirshareinregionalcommunities.Thiswasconfirmed
for all regions exceptCyprus,whereonlyone cold‐dwelling spe‐ciesoccurs.However,withanincreasingCTIof1.2×10−3°Cyear−1 onaverage,upto9.5×10−3°Cyear−1fortheNetherlands(Table3),this“warming”ofregionalcommunitiesevolvesmoreslowlythanthe increase in temperature itself (1.1×10−2°Cyear−1, after cor‐rectingforthedifferencein latitudinalgradientbetweenCTIandactualtemperature;Devictoretal.,2012a),butthedifferencefortheNetherlands isminimal.Thus,dragonflies inEuropeareaccu‐mulating a substantial “climatic debt,” that is, the difference be‐tweenshiftsintemperatureandshiftsindistribution(Devictoretal.,2012a;Menéndezetal.,2006),whichvariesbetweenregions.Ultimately,ourhypothesis that (c) trends inregionalCTI increaseon a south–north gradient through Europe is rejected. HighestCTI increaseswerefoundforregionsonamoderate latitude(theNetherlands, Flanders, Wallonia) and for Andalusia (althoughmeasured over a shorter time span), while lowest CTI increaseswere foundforBritain,FranceandBavaria.Regionsdiffer insizeand subsequently in latitudinal gradient. This may, in theory, af‐fect regional occupancy trends (and thus regional CTI trends) tosomeextent,possibly limiting thevalidityofacomparisonat theregionallevel.CalculatingCTIacrossequallysizedlatitudinalbandswouldbeapreferableapproach,butrequiresahigherdatadensity
AtEuropeanlevel,MSIofwarm‐dwellingandcold‐dwellingspecieswere similar, both having a slightly positive trend. At communitylevel though, the increase in European CTI of 1.2×10−3°Cyear−1
TA B L E 3 SlopeofCommunityTemperatureindex(CTI)pergeographicalregion(fromnorthtosouth)andforEurope
TA B L E 2 Multi‐speciesIndicator(MSI)trendsofcold‐dwellingspecies(SpeciesTemperatureIndex<9.8°C)andwarm‐dwellingspecies(SpeciesTemperatureIndex>9.8°C)pergeographicalregion(fromnorthtosouth)andforEurope
Region Trend period N species MSI trend ± SE Classification p
Sweden cold 1991–2014 42 1.025 ± 0.002 Moderateincrease 0.177
Sweden warm 1991–2014 12 1.030 ± 0.005 Moderateincrease
shows that warm‐dwelling species have slightly increased theirshare.TocomparethisoutcomewiththetrendsinCTIofEuropeanbirdsandbutterflies (providedbyDevictoretal.,2012a,asbasedonpresence–absencedata),we re‐calculated theEuropeanCTIofdragonflies for the sameperiod1990–2008.Over these18years,CTI of European dragonflies increased with 2.4×10−3°Cyear−1,whichiscomparablewiththeincreaseinCTIofEuropeanbutterflies(2.5×10−3°Cyear−1) andconsiderablygreater than the increase inCTIofEuropeanbirds (1.9×10−3°Cyear−1).This is in linewith thewell‐known ability of dragonflies to quickly colonize newhabitats(Corbet,1999).Dragonfliesshouldprobablybeconsideredasmoredispersivethanbutterflies,which,fortheirpart,mayshowaquickercommunityresponseatalocalscale,duetotheirgenerallyshorterlifecycle.ThenetoutcomeoftheseopposingdifferencesmayhaveresultedinasimilarCTItrendbetweendragonfliesandbutterflies.The slower responseofbird communities to climaticwarminghasbeensuggestedbyDevictoretal. (2012a) tobeaconsequenceoftheirslowerpopulationturnover.
Inconclusion,climatechangehasaconsiderablepositive im‐pactontheoccurrenceofdragonfliesinseveralEuropeanregions.However, at a continental scale, CTI's are changing only slowlyso far, due to the relatively positive response of cold‐dwellingspecies.
4.2 | Limitations of CTI
SeveralauthorshavehighlightedtheCTIasausefultoolforassess‐ingtheeffectofclimatechangeonthecompositionofcommunities(Devictor, Julliard,Couvet,& Jiguet,2008; Lindströmet al., 2013;Rothetal.,2014).However,ourresultsshowthatastableCTIdoesnotnecessarilymeanthatclimatechangeisnotaffectingtheoccur‐renceofspecies.InSweden,manydragonflyspecieshavebenefitedfrom climate warming, including species of cool conditions. ThishasledtoincreasingMSItrendsforbothwarm‐dwellingandcold‐dwellingspecies,whileleavingCTIalmostunaffected.WethereforerecommendareviewingofCTIinrelationtoMSIofwarm‐dwellingandcold‐dwellingspecies,especiallyinhigh‐latituderegionswheretemperaturesmayhavelimitedspecieswithlowSTIaswellashighSTI.Inaddition,weknowthatmanydragonflyspecieshavesubstan‐tiallyexpanded their rangenorthwards (Boudot&Kalkman,2015;Hickling,Roy,Hill,&Thomas,2005;Ott,2010).Dragonflycommuni‐tieshavechangedasaresultoftheseexpansions,yetthisismaskedbyanincreaseinotherspeciesresultinginaquitestableCTI.Forex‐ample,itislikelythatthereductioninorganicpollutionandnutrientinput inthe lastquarterofthe20thcenturyhascompensatedtheeffectsof increasing temperature for species that are sensitive tolowoxygenlevels(Ketelaar,2010;Termaat,VanGrunsven,Plate,&VanStrien,2015).TheselimitationsofCTIasanindicatorofclimatechangearealsorelevantwhencalculationsarebasedonlocalabun‐dances instead of regional distributions, even though CTI trendsbasedonabundancesshowastrongerresponsetoclimatechangethanwhenbasedonoccupancy(Lindströmetal.,2013;Virkkala&Lehikoinen,2014).
4.3 | Threats of climate change
WewereabletocalculateEuropeantrendsinoccupancyfor87spe‐cies (88%of speciesoccurring inourdata set). Fifty‐fiveof thesespecieshaveincreasedfrom1990to2015,while32haveremainedstable and none have declined. This is a remarkably positive out‐come, given the fact that the conservation status ofmany fresh‐waterorganisms isknown tohavedeterioratedglobally (Collenetal.,2014;Dudgeonetal.,2006).Althoughwerecognizethatsomespecies with a stable trend in occupancy (distribution) may havedeclinedinabundance(populationsize),weconsideritunlikelythatthiswouldchangetheoverallpictureofrangeexpansion,giventhatoccupancyandpopulationtrendsshowbroadsimilarity(VanStrienetal.,2010).
Nexttothepositiveeffectsofclimatechangeforwarm‐dwellingspecies,recentimprovementsinwaterqualityandtheexecutionofwetland restoration projects are likely to have contributed to therecoveryofdragonflies inat leastsomeof the regions (Parkinson,Goffart,Kever,Motte,&Schott,2017;Termaatetal.,2015).
Jaeschke, Bittner, Reineking, and Beierkuhnlein (2013) com‐binedclimatescenarioswiththeassumeddispersalabilitiesofsixspecies,topredictchangesintheirEuropeandistributionsby2035.Theirmodelpredictedastrongdeclineforfivespecies(Coenagrion mercuriale, −50%;C. ornatum, −67%;Leucorrhinia albifrons, −39%;L. caudalis,−58%;Ophiogomphus cecilia,−24%)andanincreaseforone species (L. pectoralis, +21%). These predictions are in sharpcontrastwiththeresultsofourstudyovertheperiod1990–2015,aswefoundstable trends inEuropeanoccupancy forC. mercuri-ale,L. caudalis and O. cecilia,andincreasingtrendsforC. ornatum,L. albifrons and L. pectoralis (SupportingInformationDataS1).Weexplainthesedifferencesbytheestimationsofmaximumspeciesdispersal abilities applied by Jaeschke et al. They used the ob‐servedmaximumdispersaldistancesmentioned in the literature,whichrefertoobservationsfromcapture–mark–recapturestudies.Thesestudiesmaygiveanestimationofdistancescoveredbythemajorityofthestudiedpopulation,butundoubtedlymissdispersaleventsbyindividualsovermuchlongerdistances(seealsoSuhling,Martens, & Suhling, 2017), leading to a severe underestimationof maximum dispersal abilities. These extreme dispersal eventsmayberareandseldomnoticed,but theydeterminethepaceatwhichspeciesdistributionsmayexpand.Nexttoannualestimatesofoccupancy,occupancymodelsalsoprovideannualestimatesofpersistenceandcolonization.Theseparametersmaybemore in‐formativeforfutureresearchontheeffectofvariationinspecies’dispersalabilities.
ThenotionthatEuropeandragonfliesaregenerallydoingratherwellanddonotappeartobegreatlyharmedbyclimatechange,doesnot apply to all species, nor to all regions. Some species, such asthearcticSomatochlora sahlbergiandthealpineS. alpestris, are in a “deadendstreet,”astheycannotshifttheirrangefurthernorthortoahigheraltitude(DeKnijfetal.,2011).Othercold‐dwellingspe‐cies,suchasCoenagrion hastulatum,aredoingwellinSweden,whilebeing threatened inmore southern regions. Furthermore, indirect
| 13TERMAAT ET Al.
effectsofclimatechangemayaffectdragonflies.Desiccationofhab‐itatssuchassmallstreamsandpondsisathreattoseveralspecies(Kalkmanetal.,2010,2018),especiallyinsouthernEurope,whichisanunderrepresentedregioninourstudy.Also,changesincommu‐nitiesincentralandnorthernEuropemayleadtomoreinterspecificcompetitionbetweendragonfly species, possibly threatening indi‐vidual species in the future.Ultimately, dragonflies across Europefacemultiplethreatsotherthanclimatechange,suchashabitatdeg‐radationanddestruction,eutrophication(Kalkmanetal.,2010)andexposure to pesticides (Jinguji, Thuyet,Uéda,&Watanabe, 2013;VanDijk,VanStaalduinen,&VanderSluijs,2013).Therelativecon‐tributionofthesedifferentenvironmentalchanges largelyremainstobeestablished.
4.4 | Trends from distribution data
WebasedourtrendcalculationsonreadilyavailabledistributiondatafromtenEuropeanregions,usingoccupancymodelstoaccountforimperfectdetection.Theserecordsallowedustoassessoccupancyindiceswithouttheneedforastandardizedfieldworkprogramme.Assuch,ourmethodimmediatelyinformsaboutdistributiontrendsandmayserveasan“earlywarningsystem”forspecieswithadete‐rioratingconservationstatusand,byproxy,thequalityoffreshwaterhabitats(Oertli,2008).However,ourstudylacksdatafromeasternEurope andwe have insufficient data from southern Europe ade‐quatelytorepresentthatarea.Unfortunately,18outof19dragonflyspeciesconsideredtobethreatenedatEuropeanlevelareconfinedto southernoreasternEurope (Kalkmanetal.,2018).Consideringthis, our European indices and trendsmay be biased to somede‐greeatpan‐Europeanlevel.However,dragonflydatasetsarerapidlygrowing inmanycountries, includingseveraleasternandsouthernEuropeancountries(Boudot&Kalkman,2015).Moreover,anetworkofEuropeanodonatologistshasexpandedoverthepastfewyearsand theusefulnessof aEuropeandragonflymonitoring scheme isgainingattention.WearethereforeconfidentthatEuropeanindiceswillbecomemorerobustwithfutureupdatesandwillhaveabettergeographicalcoverage.
4.5 | Future prospects
Overall, this studyhas shown thatdragonfliespresenta suitablespeciesgrouptogainbetterunderstandingofbiodiversitychangesandtheircauses, includingclimatechange,andthatsuitabledataneededfortheseanalysesarebecomingavailable.Dragonfliesmaytherefore satisfy the need for a biodiversity indicator based onfreshwaterinvertebrates(Feest,2013).Theyarelikelytorepresentothertaxawhichareprimarilywarm‐adapted.Usingopportunisticdataanalysedwithoccupancymodelsenablestheassessmentofspecies’distributiontrendsonbothregionalandEuropeanscale.Thesetrendsinformaboutthestateoffreshwaterhabitats,whichisurgentlyrequired(Darwalletal.,2018).Hence,wesuggestadd‐ingdragonfliesasanindicatorgrouptotheEuropeanbiodiversitymonitoring programme (European Environmental Agency, 2012),
We thank all dragonfly observerswho contributed to this studybymakingtheirobservationsavailabletotheirregionaldataman‐aging organizations.Data from Swedenwere obtained from theSwedish SpeciesObservation System; this system ismaintainedbytheSwedishSpeciesInformationCentreatSwedishUniversityof Agricultural Sciences. Data from Britain were obtained fromtheBritishDragonfly Society Recording Scheme.Data from theNetherlands were obtained from the Dutch National DatabaseFlora and Fauna. Most records are currently collected throughthe online platforms Waarneming.nl and Telmee.nl. Data fromNorthRhine‐Westphaliawereobtained from thedatabaseman‐agedbytheWorkingGroupDragonfliesNorthRhine‐Westphalia(AK Libellen NRW). Data from Bavaria were obtained from the“DatenbankArtenschutzkartierung,”maintained by theBavarianStateMinistryoftheEnvironment.DatafromFlanderswereob‐tained from the Flemish Dragonfly Society. Data fromWalloniawere obtained from SPW/DGARNE/DEMNA‐Working GroupGomphusandNatagora‐observations.Mostdragonfly records inboth Flanders andWallonia are currently collected through theonline platformsWaarnemingen.be and Observations.be, whichare managed by Natuurpunt and Natagora. Data from FrancewereobtainedfromthedatabasemanagedbytheFrenchSocietyofOdonatology (SfO).Data fromAndalusiawere obtained fromthe databasemanaged by Red deObservadores de Libélulas deAndalucía(ROLA).DatafromCypruswereobtainedfromtheda‐tabasemanaged by theCyprusDragonfly StudyGroup; this da‐tabase includes records collected through the online platformObservation.org.VincentDevictorkindlyprovided thevaluesofCTItrendslopesforbirdsandbutterfliesfromhis2012paperasbasedonpresence–absencedata.EddieJohnisthankedforproof‐readingthetext.
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Tim Termaat is an ecologist at Bosgroep Midden Nederland(ForestryOwnersGroup): a cooperation for sustainable forestand nature management in Ede, the Netherlands. Previously,he worked at Dutch Butterfly Conservation (Wageningen, theNetherlands)onprojectsconcerningthemonitoringandconser‐vationofdragonflies(Odonata).Hismaininterestisunderstand‐ingtheoccurrenceofdragonfliesondifferentscales,fromlocaltoecozone,andthefactorsdrivingcurrentchanges.
Authorcontributions:T.T.,G.D.K.,U.B.,K.B.,K.‐J.C.,P.G.,D.H.,V.J.K.,G.M., F.P.,D.S.,C.V. andM.W. contributeddata for thismanuscript.M.P. helpedwith data handling.G.v.d.T. calculatedSpeciesTemperatureIndices.A.J.v.S.principallyconductedsta‐tisticalanalyses,withinputfromT.T.,R.H.A.v.G.andM.F.W.T.T.led the writing with significant input from R.H.A.v.G., M.F.W.,A.J.v.S.andG.D.K.Allauthorshavereviewedthemanuscript.
SUPPORTING INFORMATION
Additional supporting information may be found online in theSupportingInformationsectionattheendofthearticle.
How to cite this article:TermaatT,vanStrienAJ,vanGrunsvenRHA,etal.DistributiontrendsofEuropeandragonfliesunderclimatechange.Divers Distrib. 2019;00:1–15. https://doi.org/10.1111/ddi.12913
