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Global Ecol Biogeogr. 2018;1–11. wileyonlinelibrary.com/journal/geb | 1 © 2018 John Wiley & Sons Ltd Received: 13 February 2018 | Revised: 6 July 2018 | Accepted: 1 August 2018 DOI: 10.1111/geb.12825 ORIGINAL ARTICLE Homogenization of species composition and species association networks are decoupled Daijiang Li 1 | Timothée Poisot 2 | Donald M. Waller 3 | Benjamin Baiser 1 1 Department of Wildlife Ecology and Conservation, University of Florida, Gainesville, Florida 2 Département de Sciences Biologiques, Université de Montréal, Montréal, Québec, Canada 3 Department of Botany, University of Wisconsin‐Madison, Madison, Wisconsin Correspondence Daijiang Li, Department of Wildlife Ecology and Conservation, University of Florida, Gainesville, FL 32611. Email: [email protected] Funding information NSF, Grant/Award Number: ABI 1458034 and DEB 1046355 Abstract Aim: Ecological communities are composed of both species and the biotic relation‐ ships (interactions or spatial associations) among them. Biotic homogenization in spe‐ cies composition (i.e., increased site‐to‐site similarity) is recognized as a common consequence of global change, but less is known about how the similarity of species relationships changes over space and time. Does homogenization of species compo‐ sition lead to homogenization of species relationships or are the dynamics of species relationships decoupled from changes in species composition? Location: Wisconsin, USA. Time period: 1950–2012. Major taxa studied: Vascular plants. Methods: We used long‐term resurvey data to analyse changes in plant species as‐ sociation patterns between the 1950s and 2000s at 266 sites distributed among three community types in Wisconsin, USA. We used species associations (quantified via local co‐occurrence patterns) to represent one type of relationship among spe‐ cies. Species pairs that co‐occur more or less than expected by chance have positive or negative associations, respectively. We then measured beta diversity in both spe‐ cies composition and species association networks over time and space. Results: Shifts in species associations consistently exceeded the shifts observed in species composition. Less disturbed forests of northern Wisconsin have converged somewhat in species composition but little in species associations. In contrast, for‐ ests in central Wisconsin succeeding from pine barrens to closed‐canopy forests have strongly homogenized in both species composition and species associations. More fragmented forests in southern Wisconsin also tended to converge in species composition and in the species’ negative associations, but their positive associations diverged over the last half century. Species composition and associations are gener‐ ally affected by a similar set of environmental variables. Their relative importance, however, has changed over time. Main conclusions: Long‐term shifts in species relationships appear to be decoupled from shifts in species composition despite being affected by similar environmental variables. KEYWORDS beta diversity, long‐term changes, networks, species composition, species co‐occurrence, species interactions

Homogenization of species composition and species ... · L I ET A L. | 3 biotic homogenization in species composition (Li & Waller, 2015; Rogers, Rooney, Olson, & Waller, 2008; Rooney

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Page 1: Homogenization of species composition and species ... · L I ET A L. | 3 biotic homogenization in species composition (Li & Waller, 2015; Rogers, Rooney, Olson, & Waller, 2008; Rooney

Global Ecol Biogeogr 20181ndash11 wileyonlinelibrarycomjournalgeb emsp|emsp1copy 2018 John Wiley amp Sons Ltd

Received13February2018emsp |emsp Revised6July2018emsp |emsp Accepted1August2018DOI 101111geb12825

O R I G I N A L A R T I C L E

Homogenization of species composition and species association networks are decoupled

Daijiang Li1 emsp|emspTimotheacutee Poisot2 emsp|emspDonald M Waller3emsp|emspBenjamin Baiser1

1DepartmentofWildlifeEcologyandConservationUniversityofFloridaGainesvilleFlorida2DeacutepartementdeSciencesBiologiquesUniversiteacutedeMontreacutealMontreacutealQueacutebecCanada3DepartmentofBotanyUniversityofWisconsin‐MadisonMadisonWisconsin

CorrespondenceDaijiangLiDepartmentofWildlifeEcologyandConservationUniversityofFloridaGainesvilleFL32611Emaildaijiangleegmailcom

Funding informationNSFGrantAwardNumberABI1458034andDEB1046355

AbstractAimEcologicalcommunitiesarecomposedofbothspeciesandthebioticrelation‐ships(interactionsorspatialassociations)amongthemBiotichomogenizationinspe‐cies composition (ieincreased site‐to‐site similarity) is recognized as a commonconsequenceofglobalchangebutlessisknownabouthowthesimilarityofspeciesrelationshipschangesoverspaceandtimeDoeshomogenizationofspeciescompo‐sitionleadtohomogenizationofspeciesrelationshipsorarethedynamicsofspeciesrelationshipsdecoupledfromchangesinspeciescompositionLocationWisconsinUSATime period 1950ndash2012Major taxa studiedVascularplantsMethodsWeusedlong‐termresurveydatatoanalysechangesinplantspeciesas‐sociation patterns between the 1950s and 2000s at 266 sites distributed amongthreecommunitytypesinWisconsinUSAWeusedspeciesassociations(quantifiedvialocalco‐occurrencepatterns)torepresentonetypeofrelationshipamongspe‐ciesSpeciespairsthatco‐occurmoreorlessthanexpectedbychancehavepositiveornegativeassociationsrespectivelyWethenmeasuredbetadiversityinbothspe‐ciescompositionandspeciesassociationnetworksovertimeandspaceResultsShiftsinspeciesassociationsconsistentlyexceededtheshiftsobservedinspeciescompositionLessdisturbedforestsofnorthernWisconsinhaveconvergedsomewhatinspeciescompositionbutlittleinspeciesassociationsIncontrastfor‐ests in centralWisconsin succeeding from pine barrens to closed‐canopy forestshave stronglyhomogenized inboth species composition and species associationsMorefragmentedforestsinsouthernWisconsinalsotendedtoconvergeinspeciescompositionandinthespeciesrsquonegativeassociationsbuttheirpositiveassociationsdivergedoverthelasthalfcenturySpeciescompositionandassociationsaregener‐allyaffectedbyasimilarsetofenvironmentalvariablesTheirrelativeimportancehoweverhaschangedovertimeMain conclusionsLong‐termshiftsinspeciesrelationshipsappeartobedecoupledfromshiftsinspeciescompositiondespitebeingaffectedbysimilarenvironmentalvariables

K E Y W O R D S

betadiversitylong‐termchangesnetworksspeciescompositionspeciesco‐occurrencespeciesinteractions

2emsp |emsp emspensp Li et aL

1emsp |emspINTRODUC TION

Globalenvironmentalchanges includingshifts inclimate landuseandmanagement and species invasions are affecting many com‐munities and ecosystems (Sala et al 2000 Vitousek MooneyLubchencoampMelillo1997)andformingnovelecosystems(HobbsHiggs amp Harris 2009) One consequence of this human‐inducedbioticupheavalisbiotichomogenization(BH)theincreaseincom‐positional similarity of spatially distinct ecological assemblages(iedeclineinbetadiversityMcKinneyampLockwood1999OldenComteampGiam2018OldenampPoff2003)Biotichomogenizationhasbeendocumentedinseveralecosystemstaxonomicgroupsandspatial scales (egBaiserOldenRecordLockwoodampMcKinney2012 Li amp Waller 2015 Rooney Wiegmann Rogers amp Waller2004deSolaretal2015)Suchdeclinesinbetadiversitycanad‐verselyaffectecosystemfunctions(OldenPoffDouglasDouglasampFausch2004)byreducingecosystemservicesldquoinsurancerdquoeffects(LoreauMouquetampGonzalez2003)

Environmentalchangescanalsomodifyrelationshipsamongspe‐cies (egbiotic interactions spatial associations Blois ZarnetskeFitzpatrick amp Finnegan 2013 Tylianakis Didham Bascompte ampWardle 2008) Thismay result in new predatorndashprey interactions(RockwellGormezanoampKoons2011)intensifiedpredation(Harley2011)changesinplantphenologyleadingtopollinationmismatches(HeglandNielsenLaacutezaroBjerknesampTotland2009)andchangesinnon‐trophicrelationshipsamongspeciessuchasspeciesspatialassociation(LiampWaller2016MilazzoMirtoDomeniciampGristina2013)Speciesrelationshipsmayinfactbemoresensitiveandsus‐ceptible to environmental change than species richness or com‐position providing abetter indicatorof ecological change (PoisotGueacuteveneux‐Julien Fortin Gravel amp Legendre 2017 Tylianakis etal 2008) For example relationships between a host and its par‐asites in the tropics changed in response to habitat modificationwithout changes in species composition (Tylianakis TscharntkeampLewis2007) Species relationships alsoplay crucial roles inmain‐tainingbiodiversityandecosystem functionsatboth localand re‐gionalscales(BascompteJordanoampOlesen2006GotelliGravesampRahbek 2010HarveyGounandWardampAltermatt 2017) Asa resultmonitoring species compositionand species relationshipssimultaneouslymightprovideabetterunderstandingofhowglobalchange affects ecosystem structure and function (McCann 2007Valiente‐Banuetetal2015)

Recently there has been an upsurge of interest in species re‐lationships in the context of ecological networks (McCann 2007Morales‐Castilla Matias Gravel amp Arauacutejo 2015 Tylianakis ampMorris2017)This reflects important advances in the theoryandmethods of network analysis and its clear applicability to conser‐vationbiologyandrestorationecology(CummingBodinErnstsonampElmqvist 2010TylianakisampMorris 2017) Ecological networksarecomposedofnodesandlinkswherespeciesarenodesandtherelationships between them are links Ecological networks pro‐vide a useful conceptual framework for studying species relation‐ships and the complexity of biological systems However most

previous studies of species relationships have focused on spatialvariation innetworkstructures typicallyalongsomeenvironmen‐talgradient(egMokrossRyderCocircrtesWolfeampStouffer2014)nothow thesechangeover time (but seeCaraDonnaet al2017MacLeodGenungAscherampWinfree2016PetanidouKallimanisTzanopoulos Sgardelis amp Pantis 2008)Without long‐term base‐linedata it isdifficult tostudyhowspeciesrelationshipnetworksmayvaryovertime(LaliberteacuteampTylianakis2010PoisotStoufferampGravel2015)Howevergiventherapidchangeinabioticandbioticconditionsacrossecosystemsworldwide(Tylianakisetal2008)ex‐plorationofthetemporaldynamicsofspeciesrelationshipsisneces‐sarytoassessbiodiversityunderglobalchange

Plantndashplant interactions (egfacilitation competition) alongwith other factors such as environmental conditions form thefoundationofplantcommunityassemblyonwhichothertypesofinteractions (egtrophic interactions in foodwebs pollination in‐teractions hostndashparasite interactions) build Although plantndashplantinteractions are fundamental they have received less attentionthan other types of ecological interactions Part of the reason isthatalthoughmostothertypesofinteractionscanbedetectedbyobservations(egpollinationpredationparasitism)plantndashplantin‐teractionsaredifficulttoobserveandthusrequireexperimentstoquantifyConductinganadequatenumberofsuchexperimentssoonbecomes intractableas thenumberofpossible interactions scaleswiththesquareofthenumberofspecies

Given that performing factorial replicated experiments to de‐tecthowplantspeciesinteractisatime‐limitedprocessanalterna‐tiveistoexaminehowspeciesassociatespatiallySincetheseminalwork of Diamond (1975) species associations (ieco‐occurrence)are regularly used in community ecology and biogeography as aproxyforspeciesinteractions(CazellesArauacutejoMouquetampGravel2016Gotelli2000)Thishasstimulatedbothcontroversy(ConnorampSimberloff1979)andnewresearch(egGotelliampGraves1996)Previousstudieshavesuggestedthatbioticinteractionsarethemaindriver of local species associations (Morales‐Castilla et al 2015)speciesassociationatthelocalscaleispossibledespiteorbecauseof interactionswith theotherspecies in thecommunity thathavealsopassedtheenvironmental filtersConsequentlyweshouldbeabletoinfersomethingaboutinteractionsamongspeciesbasedonhowtheyco‐occur locally (ArauacutejoRozenfeldRahbekampMarquet2011Gotelli 2000Harris 2016) However other recent studieshave shown that species associationsarenot informative for spe‐cies interactions (at leastwith current statisticalmethodsBarnerCoblentz Hacker amp Menge 2018 Delalandre amp Montesinos‐Navarro2018FreilichWietersBroitmanMarquetampNavarrete2018)Herewerefertobothobservedpatternsofspeciesassoci‐ationsandbiotic interactionsbetweenspeciesunder theumbrellaterm ldquospecies relationshipsrdquo to avoid the assumption that associa‐tionsnecessarilyindicateinteractions

Tostudylong‐termchangesinplantndashplantspeciesassociationsweappliednetworkanalysistothreeforestplantcommunitytypesinWisconsinUSAsampledfirst in the1950sagain in the2000sAlthough most plant communities in Wisconsin have undergone

emspensp emsp | emsp3Li et aL

biotic homogenization in species composition (Li ampWaller 2015Rogers RooneyOlsonampWaller 2008 Rooney et al 2004) ho‐mogenizationpatternsofplantndashplant speciesassociations in thesecommunitiesareunknownOntheonehandhomogenizedspeciescompositionacrosslocalescouldacttohomogenizespeciesassocia‐tionsasthesamesetofcommonspeciesco‐occuracrossmostsitesOntheotherhandasthespeciesresponsibleforhomogenizingspe‐ciescompositionbecamewidespreadtheycouldformnovelassoci‐ationswithspeciesrestrictedtocertainlocalesThusdifferentiationofspeciesassociationscouldoccurdespitehomogenizationofspe‐ciescomposition

Hereweaskwhetherplantcommunitycompositionandpatternsof species associationhavechanged inparallel (iebothhomoge‐nizedordifferentiated)overthelast50+yearsWealsoaskwhetherthese two components of biodiversity were influenced by similarordifferentenvironmental variables inboth timeperiods Speciesassociationsmay be inherentlymore labile than species composi‐tion(Poisotetal2017)reflectingthelargenumberofassociationspresentamongspecies(withnspecieswehaven(n‐1)2possiblespeciesassociations)Thereforewedonotnecessarilyexpectbiotichomogenization in speciescomposition tobe reflected inchangesinspeciesassociationnetworksWealsohypothesize that speciescompositionandassociationsaredrivenbythesameenvironmentalfactorsgiventhefactthatassociationsarebuiltonspeciesidentitiesHoweverwedonotexpecttheseenvironmentalfactorstohavethesame effect over time given observed changes in environmentalconditions suchas climate across thesecommunities In sumwesought to demonstrate whether species associations and speciescompositionhavesimilarresponsestoglobalenvironmentalchange

2emsp |emspMETHODS

21emsp|emspVegetation data

Inthe1950sJohnCurtisandhisstudentsandcolleaguescanvassedthestateofWisconsintofindthebestremainingexamplesofnaturalvegetationthensampled1000+sitesanddiversecommunitytypes(Curtis1959)Theychoseonlysiteswithnoobviousdisturbancesand located all plots ge30m away from any edges Within eachsitetheyrecordedthepresenceandabsenceofallvascularplantsin each ofmany sampled1‐m2 quadrats The number of quadratssampledateachsitevariedbutwasusually20TheywerecarefultoarchivetheiroriginaldatainthePlantEcologyLaboratoryattheUniversity of WisconsinndashMadison (httpswwwbotanywisceduPELWallerAmatangeloJohnsonampRogers2012)Hereweusedatafromthreecommunitytypesresurveyedsince2000usingsimi‐lar methods (Supporting Information Appendix Figure S1) north‐ernuplandforests (NUF108sitesAmatangeloFultonRogersampWaller2011Rooneyetal2004)centralsandspinebarrensforests(CSP30sitesLiampWaller2015)andsouthernuplandforests(SUF128sitesRogersetal2008)These resurveyedsites showednoobvious signsof recentdisturbanceandwere located in relatively

intacthabitatsGiventhattheoriginalsiteswerenotpermanentlymarked theseareldquosemi‐permanentrdquoplotsTheresurveyssampledtwo to six times asmanyquadrats per site as theoriginal surveyAlltaxonomywascarefullysynchronizedbetweenperiodsToallowfair comparisonswithmatchedsamplingeffortwe randomlysub‐sampledthe2000ssurveydatausingthesamenumberofquadratsasused in the1950sCollectivelyweanalysed speciespresenceabsencedatafromgt5000quadratsdistributedamongthesame266sitesinthetwotimeperiods

22emsp|emspEnvironmental data

Weanalysedenvironmentalvariablestodetectdriversofplantcom‐position andassociationpatternsWeobtainedaveragedailypre‐cipitation andminimal temperature for all sites from aWisconsinclimate database covering 1950ndash2006 (Kucharik Serbin VavrusHopkinsampMotew2010)Thesedata arederived fromanexten‐sivenetworkofweatherstationsdistributedthroughoutthestateDownscaleddataweregeneratedviaspatial interpolationTorep‐resenteachperiodofsamplingweaveragedclimatevariablesovertwo5‐yearperiods1950ndash1954and2002ndash2006(cfAshGivnishampWaller2017LiampWaller2017)Thisaccountsforpotentiallagsinspeciesrsquo responsesand inter‐annualclimaticvariationWedohavecanopyshadedataforthecentralsandpinebarrensforestsinbothtimeperiods(LiampWaller2015)Howeversuchdatawerenotavail‐ableforothervegetationtypes

23emsp|emspPlant association networks

Within each vegetation type and time period we constructed aquadratbyspeciesmatrixwithrowsforeachquadrat(nestedwithinasite)andcolumnsforeachspeciesValuesinthecellsofthismatrixreflectthepresenceorabsence(10)ofthatspeciesinthatquadratWetreatthe1‐m2quadratasthesampleunitherebecauseplantsthat co‐occur at this scale aremost likely also to interactWe re‐movedspeciesoccupyingfewerthansixquadratsateachperiodtoexcluderarespeciesandfacilitatethedeterminationofcorespeciesco‐occurrencepairsWethenusedthisquadratbyspeciesmatrixtoinferspeciespairsthataremoreorlesslikelytoco‐occurwitheachotherincomparisontorandomexpectationsusingtwomethods

Ourfirstmethodisbasedonthetraditionalnullmodelapproachcommonly used to study species co‐occurrence patterns (Gotelli2000)We calculated the partialC‐score for each pair of speciesas(ciminusmij)(cjminusmij)whereci and cjarethenumberofquadratoccur‐rencesof species i and j and mij is thenumberof quadratswherebothspeciesoccurredWethenshuffledthecellsofthequadratbyspeciesmatrix5000timesusingthefixedndashfixedrandomizational‐gorithmWeappliedthisnullmodeltoeachsiteseparatelyandthenrestackedtheshuffleddataThisconstrainednullmodelmaintainsrowandcolumnsums(speciesrichnesswithineachquadratandspe‐ciesfrequencyacrossallquadrats)ofthematrixwhilealsoaccount‐ing for thehierarchical structureofourdataset Ineach iterationpartialC‐scores for all species pairswere computed generating a

4emsp |emsp emspensp Li et aL

nulldistributionfromthe5000randomizationsThiswasthenusedtojudgewhethertheobservedC‐scorereflectshigherorlowerco‐occurrence thanexpectedbychanceFormoredetails seeLiandWaller(2016)

A recent study concluded that this null model approach hasrelatively lowpowerto infer truespecies interactions fromco‐oc‐currence patterns and suggested using Markov networks instead(Harris 2016) Unfortunately current implementations ofMarkovnetworks are restricted to le20 species (Harris 2016) precludingtheir use with our dataset A second method with power similartoMarkov networks but extending to includemanymore speciesisgeneralizedlinearmodels(GLMsHarris2016)Weadoptedthisapproachandusedgeneralizedlinearmixedmodels(GLMMs)toac‐countforthehierarchicalstructureofourdatasetIntheseGLMMswefittedBayesianregularized logisticregressiontothepresenceabsenceofeachspecies (response)usingthepresenceabsenceofother speciesaspredictorsandsite identityas randomtermThismethod generates two regression coefficients and p‐values foreach species pairWe averaged these to estimate the strengthofspecies interactions (cfHarris2016)These twomethodsyieldedqualitativelysimilar resultsWetherefore reportonly results fromGLMMsinthemaintextbecausetheseoftenhadhigherstatisticalpowerForresultsfromtheC‐scorenullmodelseetheSupportingInformationAppendix

Withthelistofpositiveandnegativeassociationspeciespairswebuiltonepositiveassociationmetawebandonenegativeassoci‐ationmetawebforeachvegetationtypeandtimeperiodPositivenegativeassociationindicatesthatapairofspeciesco‐occurmorelessthanexpectedbychance (basedonconstrainednullmodelorGLMMs)Wethenbuiltpositiveandnegativeassociationnetworksforeachsitefromthesetwometawebsbysub‐settingthespeciesobserved at that site This assumes that species relationships be‐tweenspeciesdonotdifferacrosssitesofthesamevegetationtypeandtimeperiodyieldingmoreconservativeresultsToremovethisassumptiononecanalsobuildanassociationnetworkforeachsiteindependentlyHoweverwelackedthepowertodothisgiventhelimitednumberofquadrats(mostly20)persiteThereforetheasso‐ciationnetworksforeachsiteinouranalyseswerederivedfromthemetawebsinsteadofbeingbuiltindependently

24emsp|emspData analysis

241emsp|emspChanges in spatial beta diversity over time

We calculated pairwise beta diversity in both species composi‐tionandspeciesassociationnetworkswithineachvegetationtypeandtimeperiodusingthemethodsproposedbyLegendreandDeCaacuteceres(2013)Forpairwisebetadiversityofspeciescompositiontheinputisasitebyspeciesmatrixwithspeciesabundancesinthecellsforspeciesassociationpairwisebetadiversitytheinputisasitebyspeciespairs(non‐randompairsinferredviamethodsdescribedintheprevioussubsection)matrix Inthiswaywetreateachnon‐randomspeciespairasaldquospeciesrdquointraditionalcommunityecology

analyses(cfPoisotetal2017)Thisapproachallowsusdirectlytocomparepairwisebetadiversityforspeciescompositionwithbetadiversity for species associations because both are calculated thesamewayWecomparedpairwisebetadiversityofeachvegetationtypebetweenthe1950sandthe2000susingpairedrandomizationtestsLower(orhigher)betadiversityinthe2000ssuggestsbiotichomogenization(ordifferentiation)

GiventhenumberofsitesinNUF(108)andSUF(126)wehavealargenumberofpairwisebeta‐diversitymeasures(5778and7875respectively)Suchlargesamplesizesmakeitpossibletoobtainsta‐tisticallysignificantresultsthatmaynotbebiologicallysignificantThereforewe also tested changes in beta diversity for each veg‐etation type using a distance‐basedpermutational test for homo‐geneityofmultivariatedispersion(PERMDISPAndersonEllingsenamp McArdle 2006) This analysis used BrayndashCurtis distancesPERMDISPcalculatesthedistanceofeachsitefromthecentroidoftheordinationspaceandthentestswhetherthesedistancesaredif‐ferentacrossgroups(ie1950svs2000s)withpermutationtestsWealsouseresultsfromPERMDISPtovisualizespeciescompositionandassociationpatternsforeachvegetationtypeandtimeperiod

242emsp|emspWithin‐site changes over time

Tocompareratesofchangeinspeciescompositionandspeciesas‐sociationsovertimewecalculatedbetadiversitybetweenperiodswithineachsite(ieasiteinthe1950sversusthesamesiteinthe2000s)againusingthemethodofLegendreandDeCaacuteceres(2013)We then used a paired t‐test to examinewhether the beta‐diver‐sityvaluesthatreflectchangesinspeciesassociationssignificantlyexceedthosethat reflectchanges inspeciescomposition (ietestwhetherspeciesassociationschangedmorethanspeciescomposi‐tion)Toconfirmtheseresultswealsoappliedpermutationalmul‐tivariate analysis of variance (PERMANOVA Anderson 2001) tocompare changes in species composition and species associationsovertime

243emsp|emspEnvironmental drivers

Tounderstand environmental drivers for species composition andassociation networks we conducted distance‐based redundancyanalysis(RDA)foreachvegetationtypeandtimeperiodWetrans‐formedthespeciescompositionandassociationmatrixintodistancematriceswiththeHellingerindex(LegendreampLegendre2012)WeusedenvironmentalvariablesaspredictorsinRDAsToidentifythemostsignificantenvironmentalvariablesweusedforwardvariableselectionandAkaikeinformationcriterion‐basedstatisticsover999replicaterunsforeachmatrix(cfPoisotetal2017)Theorderofvariableselectionprovides insight intothe importanceofenviron‐mental variables with the earlier selected variables generally af‐fectingspeciescompositionortheassociationsmoreThisanalysisallowed us to studywhether species composition and associationareaffectedbysimilarsetsofenvironmentalvariablesinthesameway and how these relationships changed over time All analyses

emspensp emsp | emsp5Li et aL

were conducted in R v340 (RCore Team 2017)with the pack‐agevegan (Oksanenet al 2018) fornullmodels and thepackageMCMCglmm(Hadfield2010)forBayesianGLMMs

3emsp |emspRESULTS

Acrossallvegetationtypesmost(gt80)speciespairsco‐occurredrandomly at both time periods as inferred from the results usingBayesianGLMMs(Table1)Amongnon‐randomspeciespairsmorespeciespairsco‐occurrednegatively (7ndash95)thanpositively (45ndash67)acrossallvegetationtypesandtimeperiods(Table1)

In theNUF region speciescompositionpositive speciesasso‐ciationsandnegativespeciesassociationsallshowedsimilar levelsof dispersion in both time periods in ordination space (Figure 1SupportingInformationAppendixFigureS2)Thuslittlehomogeni‐zationoccurredThiswasconfirmedbyPERMDISPresults(permuta‐tiontestallpgt025Table2)Howeverpairwisesitebetadiversitycalculated with methods proposed by Legendre and De Caacuteceres(2013)suggestedhomogenizationinspeciescompositionandnega‐tiveassociationsbutdifferentiationinpositiveassociations(pairedrandomizationtestbothplt0001Table2)

In the CSP region both species composition and patterns ofpositive association converge in ordination space in the 2000swhencomparedwith the1950s (Figure1Supporting InformationAppendix Figure S2) This suggests that these sites experiencedhomogenization in both species composition and positive speciesassociationsIncontrastweobservednochangeinnegativeasso‐ciationsResults frompairedrandomizationtestsonpairwisebetadiversityandPERMDISP(Table2)confirmthisinterpretation

Sites intheSUFregionalsoshowedatendencytoconvergeinspecies composition and negative associations between periods(Figure1SupportingInformationAppendixFigureS2)Incontrastpositive associations tended to diverge These results were sup‐portedby theparallel analysesof pairwise sitebetadiversity andPERMDISP(exceptnegativeassociationsTable2)

Forallregionsshiftsinbetadiversityforthespeciesassociationnetworksexceededthoseforspeciescomposition(p=0001withineach site Figure 2) Thus it appears that species association net‐workshavechangedfasterthanspeciescompositionLargeturnover

inspeciesassociations(positiveornegative)mayreflectonlyslightchangesinspeciescomposition

Speciescompositionandspeciesassociationswerelargelyinflu‐encedbythesamesetofenvironmentalvariableswithineachvege‐tationtypeandeachtimeperiod(Table3)Forallsitesinthe1950sspeciescompositionandspeciesassociationnetworkswereaffectedbyalmostthesamesetofenvironmentalvariablesThispatternstillholds in the2000sbut less so for theCSP sitesMore intriguingthe importance of environmental variables on plant communitieshaschangedovertimeForexampleshadewasthemostimportantfortheCSPsitesinthe1950sbutdecreasedinimportancebythe2000s for species composition and positive associationsMinimaltemperaturewasthemostimportantvariablethatstronglyaffectedspeciescompositionandpositiveassociationsoftheSUFsitesinthe1950sbutbecamelessimportantbythe2000swhereasprecipita‐tiongainedimportance

4emsp |emspDISCUSSION

Few studies have quantified changes in both species compositionand species relationship networks over time (Burkle Myers ampBelote2016)Ittakesconsiderableefforttoconstructasingleinter‐actionnetworkletalonenetworksatmultiplesitesovertwoormoretimeperiodsWefoundonlytwoempiricalstudiesonhomogeniza‐tion of ecological networks Laliberteacute and Tylianakis (2010) foundthatdeforestationhomogenizedparasitoidndashhostnetworksintropi‐calareasAlthoughtheyhadtemporaldataofparasitoidndashhostnet‐works(monthlysamplesfor17months)theirmainconclusionwasderivedfromspatialcomparisonsamongdifferentland‐usecatego‐riesKehindeandSamways(2014)examinedbiotichomogenizationofinsectndashflowerinteractionsinvineyardsmanagedunderagri‐envi‐ronmentalschemesintheCapeFloristicRegionTheyfoundnoevi‐denceofhomogenizationforinteractionnetworkswhencomparingvineyardswithnaturalsites

Ourstudymaythusbethefirsttoexploretemporalchangesinbeta diversity of species relationship networks Using patterns ofspecies co‐occurrence to indicate species relationships and usingavaluablehigh‐resolution long‐termdatasetwewereabletoex‐amineparallelchangesinbothcommunitycompositionandspecies

TA B L E 1 emspSummaryofspeciesusedandspeciesassociationsforeachvegetationtypeandtimeperiod

Type DateSpeciesused(n)

Pairs(negativeassociation)[n()]

Pairs(positiveassociation)[n()]

Pairs(random)[n()] Totalpairs

NUF 1950s 146 741(7) 513(48) 9331(882) 10585

NUF 2000s 160 1120(88) 626(49) 10974(863) 12720

CSP 1950s 61 162(89) 104(57) 1564(855) 1830

CSP 2000s 55 125(84) 100(67) 1260(848) 1485

SUF 1950s 225 2001(79) 1127(45) 22072(876) 25200

SUF 2000s 186 1635(95) 857(5) 14713(855) 17205

AbbreviationsCSPcentralsandplainsNUFnorthernuplandforestsSUFsouthernuplandforests

6emsp |emsp emspensp Li et aL

associationnetworksWefoundthatspeciesassociationnetworkscanhomogenizedifferentiateor shownochange through time indifferentvegetationtypesregardlessofthehomogenizationdynam‐icsofspeciescompositionLong‐termchangesinspeciescomposi‐tionandspeciesassociationsthusappeartobedecoupled

IntheNUFofWisconsinplantcommunitieswererelativelysta‐ble intermsoftheirspeciescompositionandspeciesassociationsComparedwith other community types NUF has a lower humanpopulation less land‐use change and less habitat fragmentationInthepresentstudywefoundnooverallchangesinbetadiversityof speciescompositionandspeciesassociationswhen testedwithPERMDISPHoweverpairedrandomizationtestsonbetadiversitybetweensitepairssuggestedsignificanthomogenizationinspeciescomposition matching the conclusion (biotic impoverishment andhomogenization)reachedinapreviousstudyofasubsetofthesesites(Rooneyetal2004)Herewealsoobservedhomogenizationinthe

among‐sitediversityofnegativespeciesassociationsbutsignificantdifferentiationinpositivespeciesassociationsGiventhelargenum‐berofsites inNUF(108) theresultsofrandomizationtestsmightnotbebiologicallysignificantdespitetheirstatisticalsignificancesTheseresultssuggest thatshifts inspeciescompositionmightnotoccurinthesamedirectionasshiftsinspeciesrelationships

Plantcommunities in theCSPhistoricallywerefire‐maintainedpinebarrenswithopencanopiesHowevertheyaresucceedingintoclose‐canopyuplandforestsbecauseoffiresuppression(LiampWaller2015)Firesuppressionhasresultedinhomogenizationinbothspe‐ciescomposition(LiampWaller2015)andfunctionaltraitcomposition(LiampWaller2017)Thisprobablyreflectsdeclinesinhabitathetero‐geneitywithinthesecommunitiesInthe1950ssitesintheCSPhaddifferentcanopycoverageformingmosaicsofburnedandunburnedhabitatstosupportdifferentplantcommunitiesInthe2000show‐ever siteswere similar toeachother in their canopycoverowing

F I G U R E 1 emspDistancetothecentroidofordinationsofspeciescompositionandassociationsIncreasesinthedistancetothecentroidovertimeindicatedifferentiation(diff)Decreasesinthedistancetothecentroidovertimeindicatehomogenization(homog)p lt 005 plt001p lt 0001

no change

homog

homog

no change

homog

diff

no change

no change

no change

Species Composition Positive Associations Negative Associations

NU

FC

SPSU

F

1950s 2000s 1950s 2000s 1950s 2000s

02

04

06

08

02

04

06

08

02

04

06

08

Dis

tanc

e to

Cen

troid

emspensp emsp | emsp7Li et aL

to fire suppression and succession filtering out shade‐intolerantspecies(LiampWaller2017)andhomogenizingplantcommunities(LiampWaller2015)Giventheseecologicalchangesitisnotsurprisingtofindsignificanthomogenizationinbothspeciescompositionandpositivespeciesassociationsinthesecommunities

SitesintheSUFhavebeenaffectedbydevelopmentandland‐use changes more than any other plant community inWisconsin(Rogersetal2008)Currentlymostofthesesitesarefragmentedanddisturbedbynearbyanthropogenic activities including roadsdevelopmentandagriculturePreviousstudiessuggestthathabitatdegradationandfragmentationtendtohomogenizespeciescompo‐sitionbydecreasingspeciesdiversitywhichcanalsoreducenetworkcomplexityandstability(LaliberteacuteampTylianakis2010Mokrossetal2014Tylianakisetal2007)However the fact thathabitat frag‐mentationcan result ingreaterdifferences in interactionnetworkstructure(Bordesetal2015)suggeststhatnetworksimplification(fewer nodes andor edges) does not necessarily cause networkhomogenizationNetworkscandifferacrosssites if individualnet‐workscontainuniqueinteractionseveniftheyshowageneraltrendtowards simplification In theseSUFcommunities the importanceofspeciesdispersallimitationandstochasticfactorshasincreasedwhereastheimportanceofspeciesinteractionshasdecreasedovertime(LiampWaller2016)Itisthuslikelythatstochasticassemblypro‐cesses are formingnovel sets of interactions among species eventhoughspeciesdiversityhasdecreasedIndeedwefoundonaver‐age964significantpositivespeciespairspersiteinthe1950sbutonly603significantpositivepairspersiteinthe2000sindicatingthatassociationnetworksateachsitehavesimplifiedHoweverboththepairedrandomizationtestonpairwisebetadiversityofpositiveassociationnetworksandPERMDISPsuggestedthatpositiveasso‐ciationnetworks inthe2000shavedifferentiatedsincethe1950s(Table2)ThereforeintheSUFwefoundhomogenizationofspeciescompositionbutdifferentiationofspeciespositiveassociations

Although changes in species associations are occurring fasterthan changes in species composition and appear decoupled fromthembotharegenerallyaffectedbysimilarsetsofenvironmentalvariables (Table 3) For example positive species associations andcomposition at all siteswithin each time periodwere affected bythesamesetofenvironmentalvariablesHowevertheimportanceofenvironmentalvariablesforspeciesassociationsandcompositionhaschangedovertimefortheCSPandSUFSpeciesassociationsandcompositionintheCSPweremostaffectedbycanopyshadeinthe1950swithclimaticfactorsplayingnoroleforpositiveassociationsandspeciescompositionBy the2000sclimaticvariablesbecamemoreimportantthancanopyshadeThisreflectsthefactthatCSPforestswith closed canopies show little variation in canopy coverinthe2000sIntheSUFminimaltemperatureusedtobemoreim‐portantthanprecipitationforspeciescompositionandpositiveas‐sociationsthispatternreversedinthe2000sTheseresultssuggestthatspeciesassociationsandcompositionaregenerallyaffectedbya similar set of environmental variables As global environmentalchangesacceleratetherelative importanceofenvironmentalvari‐ablesmaychange further contributing to theemergenceofnovelTA

BLE

2emspHomogenizationinspeciescompositiondoesnotalwaysresultinthehomogenizationofspeciesassociationnetworks

Ave_1950(pairwise)

Ave_2000(pairwise)

Ave_1950(permdisp)

Ave_2000(permdisp)

Direction(pairwise)

Direction(permdisp)

NUF

SpeComp

059

50587

051

30

51homog

nochange

PosAssoc

0778

0785

0561

0566

diff

nochange

NegAssoc

089

10887

0636

0633

homog

nochange

CSP

SpeComp

0447

029

90418

0327

homog

homog

PosAssoc

0683

0442

0496

0314

homog

homog

NegAssoc

080

50806

0574

0575

nochange

nochange

SUF

SpeComp

0572

0546

0516

0497

homog

homog

PosAssoc

0736

0782

0527

0567

diff

diff

NegAssoc

0862

0841

0615

0603

homog

nochange

Not

eNumbersintheave_1950(pairwise)andave_2000(pairwise)columnsrepresentaveragepairwisebetadiversitybetweensiteswithinthesamevegetationtypeinthe1950sandthe2000srespec‐

tivelyNumbersintheave_1950(permdisp)andave_2000(permdisp)columnsrepresenttheaveragedistancetothegroupcentroidintheordinationsofsiteswithinthesamevegetationtypeinthe1950s

andthe2000srespectivelyThecolumndirection(pairwise)indicatesdirectionsofchangesinthepairwisesitebetadiversityovertimetestedwithpairedrandomizationtestsThecolumndirection

(permdisp)indicatesdirectionsofchangesinthedistancebetweensitesandtheordinationcentroidovertimetestedwithpermutationtestsAbbreviationsdiffdifferentiationhomoghomogenization

NegAssocnegativeassociationPosAssocpositiveassociationSpeCompspeciescompositionplt005plt001

p lt

000

1

8emsp |emsp emspensp Li et aL

Vegetationtype Date Variable Shade Precipitation Minimaltemperature

NUF 1950s SpeComp ndash 2 1

PosAssoc ndash 2 1

NegAssoc ndash 2 1

2000s SpeComp ndash 2 1

PosAssoc ndash 2 1

NegAssoc ndash 2 1

CSP 1950s SpeComp 1

PosAssoc 1

NegAssoc 1 2

2000s SpeComp 2 1

PosAssoc 3 1 2

NegAssoc 2 1

SUF 1950s SpeComp ndash 2 1

PosAssoc ndash 2 1

NegAssoc ndash 1 2

2000s SpeComp ndash 1 2

PosAssoc ndash 1 2

NegAssoc ndash 1 2

NoteNumbersaretheorderinwhichvariablesareselectedDash(ndash)meansthattheenvironmentalvariableisnotavailableBlankcellsmeanthatthesevariablesaredroppedoutAbbreviationsNegAssocnegativeassociationPosAssocpositiveassociationSpeCompspeciescomposition

TA B L E 3 emspSelectedenvironmentalvariablesforspeciescompositionandspeciesassociations

F I G U R E 2 emspBetadiversityofspeciescompositionandassociationofthesamesiteovertimeEachpointrepresentsthebetadiversityofthesamesitebetweenthe1950sandthe2000sBetadiversityofoneindicatesthatthespeciescompositionorspeciesassociationinthe1950sandthe2000sweretotallydifferentwhereasbetadiversityofzeroindicatesnochangesinasiteovertimeTurnoverinspeciesrelationshipsappearstobemuchgreaterthantheturnoverinspeciescomposition

NU

FC

SPSU

F

Species Composition Positive Association Negative Association

025

050

075

100

025

050

075

100

025

050

075

100

Beta

div

ersi

ty o

ver t

ime

at th

e sa

me

site

emspensp emsp | emsp9Li et aL

arraysofspeciesandconsequentspecies interactions (Bloisetal2013Milazzoetal2013)

Species association (co‐occurrence) patterns have commonlybeenusedtorepresentspeciesinteractionsbecauseitisintractabletoquantifyinteractionsamonghundredsofplantspeciesSpeciesassociations may give false‐positive (hypothesized links that donotexistintherealsystem)interactionsbetweenspeciesandmaynot detect all real interactions (Barner et al 2018DelalandreampMontesinos‐Navarro2018Freilichetal2018)Howeverourmaingoalistostudybroadpatternsofcommunitystructureanddynam‐ics rather than to pinpoint exact interactions between particularspeciespairsForthispurposespeciesspatialassociationnetworksareanecessaryandusefulproxy(Freilichetal2018)becausetheycanprovidevaluableinformationregardingthenetoutputofdirectandindirecteffectsamongmultipleplantspecies(ratherthanexactpairwise interactions Delalandre amp Montesinos‐Navarro 2018)Co‐occurrence networks may also serve to predict overall com‐munityresponsestodisturbance(TullochChadegravesampLindenmayer2018) To reduce thepotential for biaswe studied species asso‐ciation patterns at a fine spatial scale (1m2) and used statisticalmethods(BayesianGLMMs)thathaverelativelyhighpowerforde‐tecting species interactions (Harris 2016) Furthermoreweusedacommonnullmodelapproachand reported these results in theSupporting InformationAppendixGiven that bothmethods pro‐videquantitatively similar results and reach the sameconclusionour conclusion that changes in species associations and speciescompositionaredecoupledislikelytoberobustConsequentlyourresultsfromspeciesassociationnetworksmayalsoholdforspeciesinteractionnetworks

Anassumptionmadeinthisstudyisthatspeciesassociationswithin each vegetation type and timeperiod remain consistentacross sites In reality associations between species can varythroughspaceandtime(Poisotetal2015)Giventhatwelackedthedatatoanalysehowspeciesassociationsmayhavedifferedover siteswepooleddataacross sites togain insights into theaverage nature of species associationswithin each communityThismakesourresultsconservativebecauseaccountingforvari‐ation inspeciesassociationsoversitescouldshowonlygreatervariationinnetworkstructurestrengtheningourconclusionthattemporal changes in species associations and composition aredecoupled

Our results suggest that species relationshipsmay not be ex‐periencingageneraltrendtowardshomogenizationbecausenovelrelationships may be forming in response to rapid global changeThisraisesimportantquestionsabouthowsuchchangesinspeciesrelationshipsmightaffectcommunitystabilityecosystemservicesandspeciesco‐evolutionStudiesofbetadiversity inspecies rela‐tionshipsremainintheirinfancy(Burkleetal2016)Giventheim‐portanceofspeciesrelationshipsandtheirpotentialunpredictablerelationshipwithspeciescompositionfutureempiricalandtheoret‐icalresearchthatinvestigatespatternscausesandconsequencesofchangesinbetadiversityofrelationshipnetworksareneeded

5emsp |emspBIOSKETCH

Daijiang Liisapost‐doctoralresearcherattheDepartmentofWildlifeEcologyampConservationUniversityofFloridaHisresearchinterestscovercommunityecologyfunctionalandphylogeneticdiversitybi‐ologicalinvasionsglobalchangebiologyandecologicalmodelling

DATA ACCE SSIBILIT Y

The data used in this study have been deposited to figshare(httpsfigsharecoms5a98a69a66f22644361e) with httpsdoiorg106084m9figshare6771938

ORCID

Daijiang Li httporcidorg0000‐0002‐0925‐3421

Timotheacutee Poisot httporcidorg0000‐0002‐0735‐5184

Benjamin Baiser httporcidorg0000‐0002‐3573‐1183

R E FE R E N C E S

AmatangeloKLFultonMRRogersDAampWallerDM (2011)Convergingforestcommunitycompositionalonganedaphicgradi‐ent threatens landscape‐level diversityDiversity and Distributions17201ndash213httpsdoiorg101111j1472‐4642201000730x

AndersonMJ(2001)Anewmethodfornon‐parametricmultivariateanalysisofvarianceAustral Ecology2632ndash46

AndersonMJEllingsenKEampMcArdleBH (2006)MultivariatedispersionasameasureofbetadiversityEcology Letters9683ndash693httpsdoiorg101111j1461‐0248200600926x

Arauacutejo M B Rozenfeld A Rahbek C amp Marquet P A (2011)Using species co‐occurrence networks to assess the im‐pacts of climate change Ecography 34 897ndash908 httpsdoiorg101111j1600‐0587201106919x

AshJDGivnishTJampWallerDM(2017)Trackinglagsinhistori‐calplantspeciesrsquoshiftsinrelationtoregionalclimatechangeGlobal Change Biology231305ndash1315httpsdoiorg101111gcb13429

BaiserBOlden JDRecordSLockwoodJLampMcKinneyML(2012) Pattern and process of biotic homogenization in the newPangaeaProceedings of the Royal Society B Biological Sciences2794772ndash4777

Barner A K Coblentz K E Hacker S D amp Menge B A (2018)Fundamentalcontradictionsamongobservationalandexperimentalestimatesofnon‐trophicspeciesinteractionsEcology99557ndash566httpsdoiorg101002ecy2133

Bascompte J JordanoPampOlesen JM (2006)Asymmetriccoevo‐lutionarynetworksfacilitatebiodiversitymaintenanceScience312431ndash433httpsdoiorg101126science1123412

Blois J L Zarnetske P L FitzpatrickM C amp Finnegan S (2013)ClimatechangeandthepastpresentandfutureofbioticinteractionsScience341499ndash504httpsdoiorg101126science1237184

BordesFMorandSPilosofSClaudeJKrasnovBRCossonJ‐Fhellip Blasdell K (2015) Habitat fragmentation alters the propertiesofahostndashparasitenetworkRodentsand theirhelminths inSouth‐East Asia Journal of Animal Ecology 84 1253ndash1263 httpsdoiorg1011111365‐265612368

BurkleLAMyersJAampBeloteRT (2016)Thebeta‐diversityofspecies interactions Untangling the drivers of geographic vari‐ation in plantndashpollinator diversity and function across scales

10emsp |emsp emspensp Li et aL

American Journal of Botany103118ndash128httpsdoiorg103732ajb1500079

CaraDonna P J Petry W K Brennan R M Cunningham J LBronstein J LWaserNMamp SandersN J (2017) InteractionrewiringandtherapidturnoverofplantndashpollinatornetworksEcology Letters20385ndash394httpsdoiorg101111ele12740

CazellesKArauacutejoMBMouquetNampGravelD(2016)Atheoryforspeciesco‐occurrenceininteractionnetworksTheoretical Ecology939ndash48httpsdoiorg101007s12080‐015‐0281‐9

ConnorEFampSimberloffD(1979)Theassemblyofspeciescommu‐nitiesChanceorcompetitionEcology601132ndash1140httpsdoiorg1023071936961

CummingGSBodinOumlErnstsonHampElmqvistT(2010)Networkanalysis in conservation biogeography Challenges and oppor‐tunities Diversity and Distributions 16 414ndash425 httpsdoiorg101111j1472‐4642201000651x

CurtisJT(1959)The vegetation of Wisconsin An ordination of plant com-munitiesMadisonWIUniversityofWisconsinPress

de Solar R R C Barlow J Ferreira J Berenguer E Lees A CThompsonJRhellipGardnerTA(2015)Howpervasiveisbioticho‐mogenizationinhuman‐modifiedtropicalforestlandscapesEcology Letters181108ndash1118httpsdoiorg101111ele12494

DelalandreLampMontesinos‐NavarroA(2018)Canco‐occurrencenet‐works predict plant‐plant interactions in a semi‐arid gypsum com‐munityPerspectives in Plant Ecology Evolution and Systematics3136ndash43httpsdoiorg101016jppees201801001

Diamond JM (1975) Assembly of species communitiesEcology and Evolution of Communities342ndash444

FreilichMAWietersEBroitmanBMarquetPAampNavarreteSA(2018)Speciesco‐occurrencenetworksCantheyrevealtrophicandnon‐trophicinteractionsinecologicalcommunitiesEcology99690ndash699httpsdoiorg101002ecy2142

Gotelli N J (2000) Null model analysis of species co‐oc‐currence patterns Ecology 81 2606ndash2621 httpsdoiorg1018900012‐9658(2000)081[2606NMAOSC]20CO2

GotelliNJampGravesGR(1996)Null models in ecologyWashingtonDCSmithsonianInstitution

GotelliN JGravesGRampRahbekC (2010)Macroecological sig‐nalsofspeciesinteractionsintheDanishavifaunaProceedings of the National Academy of Sciences of the USA1075030ndash5035httpsdoiorg101073pnas0914089107

Hadfield JD (2010)MCMCmethods formulti‐responsegeneralizedlinearmixedmodelsTheMCMCglmmRpackageJournal of Statistical Software331ndash22

Harley C D (2011) Climate change keystone predation and biodi‐versity loss Science 334 1124ndash1127 httpsdoiorg101126science1210199

Harris D J (2016) Inferring species interactions from co‐occurrencedata with Markov networks Ecology 97 3308ndash3314 httpsdoiorg101002ecy1605

Harvey E Gounand I Ward C L amp Altermatt F (2017) Bridgingecology and conservation From ecological networks to ecosys‐tem function Journal of Applied Ecology 54 371ndash379 httpsdoiorg1011111365‐266412769

Hegland S J Nielsen A Laacutezaro A Bjerknes A‐L amp TotlandOslash (2009) How does climate warming affect plant‐pollina‐tor interactions Ecology Letters 12 184ndash195 httpsdoiorg101111j1461‐0248200801269x

Hobbs R J Higgs E amp Harris J A (2009) Novel ecosystemsImplicationsforconservationandrestorationTrends in Ecology and Evolution24599ndash605httpsdoiorg101016jtree200905012

Kehinde T amp Samways M J (2014) Effects of vineyard manage‐ment on biotic homogenization of insectndashflower interaction net‐works in the cape floristic region biodiversity hotspot Journal of Insect Conservation 18 469ndash477 httpsdoiorg101007s10841‐014‐9659‐z

Kucharik C J Serbin S P Vavrus S Hopkins E J amp MotewM M (2010) Patterns of climate change across Wisconsinfrom 1950 to 2006 Physical Geography 31 1ndash28 httpsdoiorg1027470272‐36463111

LaliberteacuteEampTylianakisJM(2010)Deforestationhomogenizestrop‐ical parasitoidndashhost networks Ecology 91 1740ndash1747 httpsdoiorg10189009‐13281

LegendrePampDeCaacuteceresM(2013)BetadiversityasthevarianceofcommunitydataDissimilaritycoefficientsandpartitioningEcology Letters16951ndash963httpsdoiorg101111ele12141

LegendrePampLegendreLF(2012)Numerical ecologyAmsterdamTheNetherlandsElsevier

LiDampWallerDM(2015)DriversofobservedbiotichomogenizationinpinebarrensofcentralWisconsinEcology961030ndash1041httpsdoiorg10189014‐08931

LiDampWallerDM (2016)Long‐termshifts inthepatternsandun‐derlyingprocessesofplantassociationsinWisconsinforestsGlobal Ecology and Biogeography 25 516ndash526 httpsdoiorg101111geb12432

LiDampWallerDM(2017)Fireexclusionandclimatechangeinteracttoaffect long‐termchanges in the functional compositionofplantcommunitiesDiversity and Distributions 23 496ndash506 httpsdoiorg101111ddi12542

LoreauMMouquetNampGonzalezA(2003)Biodiversityasspatialinsurance inheterogeneous landscapesProceedings of the National Academy of Sciences of the USA 100 12765ndash12770 httpsdoiorg101073pnas2235465100

MacLeod M Genung M A Ascher J S amp Winfree R (2016)Measuring partner choice in plantndashpollinator networks Using nullmodels to separate rewiring and fidelity from chanceEcology972925ndash2931httpsdoiorg101002ecy1574

McCannK(2007)ProtectingbiostructureNature44629ndash29httpsdoiorg101038446029a

McKinneyMLampLockwoodJL(1999)BiotichomogenizationAfewwinners replacingmany losers in the nextmass extinctionTrends in Ecology and Evolution 14 450ndash453 httpsdoiorg101016S0169‐5347(99)01679‐1

Milazzo M Mirto S Domenici P amp Gristina M (2013) Climatechange exacerbates interspecific interactions in sympatriccoastal fishes Journal of Animal Ecology 82 468ndash477 httpsdoiorg101111j1365‐2656201202034x

MokrossKRyderTBCocircrtesMCWolfe JDampStoufferPC(2014) Decay of interspecific avian flock networks along a dis‐turbance gradient in Amazonia Proceedings of the Royal Society B Biological Sciences28120132599

Morales‐Castilla IMatiasM G Gravel D amp ArauacutejoM B (2015)Inferring biotic interactions from proxies Trends in Ecology and Evolution30347ndash356httpsdoiorg101016jtree201503014

OksanenJBlanchetFGFriendlyMKindtRLegendrePMcGlinnDhellipWagnerH(2018)Vegan Community ecology packageRpack‐ageversion25‐2httpsCRANR‐projectorgpackage=vegan

OldenJDComteLampGiamX(2018)TheHomogoceneAresearchprospectusforthestudyofbiotichomogenisationNeoBiota3723httpsdoiorg103897neobiota3722552

OldenJDampPoffNL (2003)Towardamechanisticunderstandingand prediction of biotic homogenization The American Naturalist162442ndash460httpsdoiorg101086378212

OldenJDPoffNLDouglasMRDouglasMEampFauschKD(2004)Ecologicalandevolutionaryconsequencesofbiotichomog‐enization Trends in Ecology and Evolution 19 18ndash24 httpsdoiorg101016jtree200309010

PetanidouTKallimanisASTzanopoulosJSgardelisSPampPantisJD(2008)Long‐termobservationofapollinationnetworkFluctuationinspeciesandinteractionsrelativeinvarianceofnetworkstructureand implicationsforestimatesofspecializationEcology Letters11564ndash575httpsdoiorg101111j1461‐0248200801170x

emspensp emsp | emsp11Li et aL

Poisot T Gueacuteveneux‐Julien C FortinM‐J Gravel D amp LegendreP (2017)Hostsparasitesandtheir interactionsrespondtodiffer‐entclimaticvariablesGlobal Ecology and Biogeography26942ndash951httpsdoiorg101111geb12602

PoisotTStoufferDBampGravelD(2015)BeyondspeciesWhyeco‐logicalinteractionnetworksvarythroughspaceandtimeOikos124243ndash251httpsdoiorg101111oik01719

RCoreTeam(2017)R A language and environment for statistical comput-ingViennaAustriaRFoundationforStatisticalComputing

RockwellRFGormezanoLJampKoonsDN(2011)TrophicmatchesandmismatchesCanpolarbearsreducetheabundanceofnestingsnowgeese inwesternHudsonBayOikos120696ndash709httpsdoiorg101111j1600‐0706201018837x

RogersDARooneyTPOlsonDampWallerDM(2008)ShiftsinsouthernWisconsin forest canopy and understory richness com‐position and heterogeneity Ecology 89 2482ndash2492 httpsdoiorg10189007‐11291

RooneyTPWiegmannSMRogersDAampWallerDM (2004)BioticimpoverishmentandhomogenizationinunfragmentedforestunderstorycommunitiesConservation Biology18787ndash798httpsdoiorg101111j1523‐1739200400515x

SalaOEChapinFSArmestoJJBerlowEBloomfieldJDirzoRhellipLeemansR(2000)Globalbiodiversityscenariosfortheyear2100 Science2871770ndash1774

TullochAIChadegravesIampLindenmayerDB(2018)Speciesco‐occur‐renceanalysispredictsmanagementoutcomesformultiplethreatsNature Ecology amp Evolution 2 465ndash474 httpsdoiorg101038s41559‐017‐0457‐3

Tylianakis J M Didham R K Bascompte J amp Wardle D A(2008) Global change and species interactions in terres‐trial ecosystems Ecology Letters 11 1351ndash1363 httpsdoiorg101111j1461‐0248200801250x

Tylianakis J M amp Morris R J (2017) Ecological networksacross environmental gradients Annual Review of Ecology

Evolution and Systematics 48 25ndash48 httpsdoiorg101146annurev‐ecolsys‐110316‐022821

Tylianakis JM Tscharntke Tamp LewisO T (2007)Habitatmodifi‐cation alters the structure of tropical hostndashparasitoid food websNature445202ndash205httpsdoiorg101038nature05429

Valiente‐BanuetAAizenMAAlcaacutentaraJMArroyoJCocucciAGalettiMhellipJordanoP(2015)BeyondspecieslossTheextinctionofecologicalinteractionsinachangingworldFunctional Ecology29299ndash307httpsdoiorg1011111365‐243512356

Vitousek PMMooneyHA Lubchenco JampMelillo JM (1997)Human domination of earthrsquos ecosystems Science 277 494ndash499httpsdoiorg101126science2775325494

Waller DM Amatangelo K L Johnson S amp Rogers D A (2012)Wisconsinvegetationdatabasendashplantcommunitysurveyandresur‐veydatafromtheWisconsinplantecologylaboratoryBiodiversity amp Ecology4255ndash264httpsdoiorg107809b‐e00082

SUPPORTING INFORMATION

Additional supporting information may be found online in theSupportingInformationsectionattheendofthearticle

How to cite this articleLiDPoisotTWallerDMBaiserBHomogenizationofspeciescompositionandspeciesassociationnetworksaredecoupledGlobal Ecol Biogeogr 2018001ndash11 httpsdoiorg101111geb12825

Page 2: Homogenization of species composition and species ... · L I ET A L. | 3 biotic homogenization in species composition (Li & Waller, 2015; Rogers, Rooney, Olson, & Waller, 2008; Rooney

2emsp |emsp emspensp Li et aL

1emsp |emspINTRODUC TION

Globalenvironmentalchanges includingshifts inclimate landuseandmanagement and species invasions are affecting many com‐munities and ecosystems (Sala et al 2000 Vitousek MooneyLubchencoampMelillo1997)andformingnovelecosystems(HobbsHiggs amp Harris 2009) One consequence of this human‐inducedbioticupheavalisbiotichomogenization(BH)theincreaseincom‐positional similarity of spatially distinct ecological assemblages(iedeclineinbetadiversityMcKinneyampLockwood1999OldenComteampGiam2018OldenampPoff2003)Biotichomogenizationhasbeendocumentedinseveralecosystemstaxonomicgroupsandspatial scales (egBaiserOldenRecordLockwoodampMcKinney2012 Li amp Waller 2015 Rooney Wiegmann Rogers amp Waller2004deSolaretal2015)Suchdeclinesinbetadiversitycanad‐verselyaffectecosystemfunctions(OldenPoffDouglasDouglasampFausch2004)byreducingecosystemservicesldquoinsurancerdquoeffects(LoreauMouquetampGonzalez2003)

Environmentalchangescanalsomodifyrelationshipsamongspe‐cies (egbiotic interactions spatial associations Blois ZarnetskeFitzpatrick amp Finnegan 2013 Tylianakis Didham Bascompte ampWardle 2008) Thismay result in new predatorndashprey interactions(RockwellGormezanoampKoons2011)intensifiedpredation(Harley2011)changesinplantphenologyleadingtopollinationmismatches(HeglandNielsenLaacutezaroBjerknesampTotland2009)andchangesinnon‐trophicrelationshipsamongspeciessuchasspeciesspatialassociation(LiampWaller2016MilazzoMirtoDomeniciampGristina2013)Speciesrelationshipsmayinfactbemoresensitiveandsus‐ceptible to environmental change than species richness or com‐position providing abetter indicatorof ecological change (PoisotGueacuteveneux‐Julien Fortin Gravel amp Legendre 2017 Tylianakis etal 2008) For example relationships between a host and its par‐asites in the tropics changed in response to habitat modificationwithout changes in species composition (Tylianakis TscharntkeampLewis2007) Species relationships alsoplay crucial roles inmain‐tainingbiodiversityandecosystem functionsatboth localand re‐gionalscales(BascompteJordanoampOlesen2006GotelliGravesampRahbek 2010HarveyGounandWardampAltermatt 2017) Asa resultmonitoring species compositionand species relationshipssimultaneouslymightprovideabetterunderstandingofhowglobalchange affects ecosystem structure and function (McCann 2007Valiente‐Banuetetal2015)

Recently there has been an upsurge of interest in species re‐lationships in the context of ecological networks (McCann 2007Morales‐Castilla Matias Gravel amp Arauacutejo 2015 Tylianakis ampMorris2017)This reflects important advances in the theoryandmethods of network analysis and its clear applicability to conser‐vationbiologyandrestorationecology(CummingBodinErnstsonampElmqvist 2010TylianakisampMorris 2017) Ecological networksarecomposedofnodesandlinkswherespeciesarenodesandtherelationships between them are links Ecological networks pro‐vide a useful conceptual framework for studying species relation‐ships and the complexity of biological systems However most

previous studies of species relationships have focused on spatialvariation innetworkstructures typicallyalongsomeenvironmen‐talgradient(egMokrossRyderCocircrtesWolfeampStouffer2014)nothow thesechangeover time (but seeCaraDonnaet al2017MacLeodGenungAscherampWinfree2016PetanidouKallimanisTzanopoulos Sgardelis amp Pantis 2008)Without long‐term base‐linedata it isdifficult tostudyhowspeciesrelationshipnetworksmayvaryovertime(LaliberteacuteampTylianakis2010PoisotStoufferampGravel2015)Howevergiventherapidchangeinabioticandbioticconditionsacrossecosystemsworldwide(Tylianakisetal2008)ex‐plorationofthetemporaldynamicsofspeciesrelationshipsisneces‐sarytoassessbiodiversityunderglobalchange

Plantndashplant interactions (egfacilitation competition) alongwith other factors such as environmental conditions form thefoundationofplantcommunityassemblyonwhichothertypesofinteractions (egtrophic interactions in foodwebs pollination in‐teractions hostndashparasite interactions) build Although plantndashplantinteractions are fundamental they have received less attentionthan other types of ecological interactions Part of the reason isthatalthoughmostothertypesofinteractionscanbedetectedbyobservations(egpollinationpredationparasitism)plantndashplantin‐teractionsaredifficulttoobserveandthusrequireexperimentstoquantifyConductinganadequatenumberofsuchexperimentssoonbecomes intractableas thenumberofpossible interactions scaleswiththesquareofthenumberofspecies

Given that performing factorial replicated experiments to de‐tecthowplantspeciesinteractisatime‐limitedprocessanalterna‐tiveistoexaminehowspeciesassociatespatiallySincetheseminalwork of Diamond (1975) species associations (ieco‐occurrence)are regularly used in community ecology and biogeography as aproxyforspeciesinteractions(CazellesArauacutejoMouquetampGravel2016Gotelli2000)Thishasstimulatedbothcontroversy(ConnorampSimberloff1979)andnewresearch(egGotelliampGraves1996)Previousstudieshavesuggestedthatbioticinteractionsarethemaindriver of local species associations (Morales‐Castilla et al 2015)speciesassociationatthelocalscaleispossibledespiteorbecauseof interactionswith theotherspecies in thecommunity thathavealsopassedtheenvironmental filtersConsequentlyweshouldbeabletoinfersomethingaboutinteractionsamongspeciesbasedonhowtheyco‐occur locally (ArauacutejoRozenfeldRahbekampMarquet2011Gotelli 2000Harris 2016) However other recent studieshave shown that species associationsarenot informative for spe‐cies interactions (at leastwith current statisticalmethodsBarnerCoblentz Hacker amp Menge 2018 Delalandre amp Montesinos‐Navarro2018FreilichWietersBroitmanMarquetampNavarrete2018)Herewerefertobothobservedpatternsofspeciesassoci‐ationsandbiotic interactionsbetweenspeciesunder theumbrellaterm ldquospecies relationshipsrdquo to avoid the assumption that associa‐tionsnecessarilyindicateinteractions

Tostudylong‐termchangesinplantndashplantspeciesassociationsweappliednetworkanalysistothreeforestplantcommunitytypesinWisconsinUSAsampledfirst in the1950sagain in the2000sAlthough most plant communities in Wisconsin have undergone

emspensp emsp | emsp3Li et aL

biotic homogenization in species composition (Li ampWaller 2015Rogers RooneyOlsonampWaller 2008 Rooney et al 2004) ho‐mogenizationpatternsofplantndashplant speciesassociations in thesecommunitiesareunknownOntheonehandhomogenizedspeciescompositionacrosslocalescouldacttohomogenizespeciesassocia‐tionsasthesamesetofcommonspeciesco‐occuracrossmostsitesOntheotherhandasthespeciesresponsibleforhomogenizingspe‐ciescompositionbecamewidespreadtheycouldformnovelassoci‐ationswithspeciesrestrictedtocertainlocalesThusdifferentiationofspeciesassociationscouldoccurdespitehomogenizationofspe‐ciescomposition

Hereweaskwhetherplantcommunitycompositionandpatternsof species associationhavechanged inparallel (iebothhomoge‐nizedordifferentiated)overthelast50+yearsWealsoaskwhetherthese two components of biodiversity were influenced by similarordifferentenvironmental variables inboth timeperiods Speciesassociationsmay be inherentlymore labile than species composi‐tion(Poisotetal2017)reflectingthelargenumberofassociationspresentamongspecies(withnspecieswehaven(n‐1)2possiblespeciesassociations)Thereforewedonotnecessarilyexpectbiotichomogenization in speciescomposition tobe reflected inchangesinspeciesassociationnetworksWealsohypothesize that speciescompositionandassociationsaredrivenbythesameenvironmentalfactorsgiventhefactthatassociationsarebuiltonspeciesidentitiesHoweverwedonotexpecttheseenvironmentalfactorstohavethesame effect over time given observed changes in environmentalconditions suchas climate across thesecommunities In sumwesought to demonstrate whether species associations and speciescompositionhavesimilarresponsestoglobalenvironmentalchange

2emsp |emspMETHODS

21emsp|emspVegetation data

Inthe1950sJohnCurtisandhisstudentsandcolleaguescanvassedthestateofWisconsintofindthebestremainingexamplesofnaturalvegetationthensampled1000+sitesanddiversecommunitytypes(Curtis1959)Theychoseonlysiteswithnoobviousdisturbancesand located all plots ge30m away from any edges Within eachsitetheyrecordedthepresenceandabsenceofallvascularplantsin each ofmany sampled1‐m2 quadrats The number of quadratssampledateachsitevariedbutwasusually20TheywerecarefultoarchivetheiroriginaldatainthePlantEcologyLaboratoryattheUniversity of WisconsinndashMadison (httpswwwbotanywisceduPELWallerAmatangeloJohnsonampRogers2012)Hereweusedatafromthreecommunitytypesresurveyedsince2000usingsimi‐lar methods (Supporting Information Appendix Figure S1) north‐ernuplandforests (NUF108sitesAmatangeloFultonRogersampWaller2011Rooneyetal2004)centralsandspinebarrensforests(CSP30sitesLiampWaller2015)andsouthernuplandforests(SUF128sitesRogersetal2008)These resurveyedsites showednoobvious signsof recentdisturbanceandwere located in relatively

intacthabitatsGiventhattheoriginalsiteswerenotpermanentlymarked theseareldquosemi‐permanentrdquoplotsTheresurveyssampledtwo to six times asmanyquadrats per site as theoriginal surveyAlltaxonomywascarefullysynchronizedbetweenperiodsToallowfair comparisonswithmatchedsamplingeffortwe randomlysub‐sampledthe2000ssurveydatausingthesamenumberofquadratsasused in the1950sCollectivelyweanalysed speciespresenceabsencedatafromgt5000quadratsdistributedamongthesame266sitesinthetwotimeperiods

22emsp|emspEnvironmental data

Weanalysedenvironmentalvariablestodetectdriversofplantcom‐position andassociationpatternsWeobtainedaveragedailypre‐cipitation andminimal temperature for all sites from aWisconsinclimate database covering 1950ndash2006 (Kucharik Serbin VavrusHopkinsampMotew2010)Thesedata arederived fromanexten‐sivenetworkofweatherstationsdistributedthroughoutthestateDownscaleddataweregeneratedviaspatial interpolationTorep‐resenteachperiodofsamplingweaveragedclimatevariablesovertwo5‐yearperiods1950ndash1954and2002ndash2006(cfAshGivnishampWaller2017LiampWaller2017)Thisaccountsforpotentiallagsinspeciesrsquo responsesand inter‐annualclimaticvariationWedohavecanopyshadedataforthecentralsandpinebarrensforestsinbothtimeperiods(LiampWaller2015)Howeversuchdatawerenotavail‐ableforothervegetationtypes

23emsp|emspPlant association networks

Within each vegetation type and time period we constructed aquadratbyspeciesmatrixwithrowsforeachquadrat(nestedwithinasite)andcolumnsforeachspeciesValuesinthecellsofthismatrixreflectthepresenceorabsence(10)ofthatspeciesinthatquadratWetreatthe1‐m2quadratasthesampleunitherebecauseplantsthat co‐occur at this scale aremost likely also to interactWe re‐movedspeciesoccupyingfewerthansixquadratsateachperiodtoexcluderarespeciesandfacilitatethedeterminationofcorespeciesco‐occurrencepairsWethenusedthisquadratbyspeciesmatrixtoinferspeciespairsthataremoreorlesslikelytoco‐occurwitheachotherincomparisontorandomexpectationsusingtwomethods

Ourfirstmethodisbasedonthetraditionalnullmodelapproachcommonly used to study species co‐occurrence patterns (Gotelli2000)We calculated the partialC‐score for each pair of speciesas(ciminusmij)(cjminusmij)whereci and cjarethenumberofquadratoccur‐rencesof species i and j and mij is thenumberof quadratswherebothspeciesoccurredWethenshuffledthecellsofthequadratbyspeciesmatrix5000timesusingthefixedndashfixedrandomizational‐gorithmWeappliedthisnullmodeltoeachsiteseparatelyandthenrestackedtheshuffleddataThisconstrainednullmodelmaintainsrowandcolumnsums(speciesrichnesswithineachquadratandspe‐ciesfrequencyacrossallquadrats)ofthematrixwhilealsoaccount‐ing for thehierarchical structureofourdataset Ineach iterationpartialC‐scores for all species pairswere computed generating a

4emsp |emsp emspensp Li et aL

nulldistributionfromthe5000randomizationsThiswasthenusedtojudgewhethertheobservedC‐scorereflectshigherorlowerco‐occurrence thanexpectedbychanceFormoredetails seeLiandWaller(2016)

A recent study concluded that this null model approach hasrelatively lowpowerto infer truespecies interactions fromco‐oc‐currence patterns and suggested using Markov networks instead(Harris 2016) Unfortunately current implementations ofMarkovnetworks are restricted to le20 species (Harris 2016) precludingtheir use with our dataset A second method with power similartoMarkov networks but extending to includemanymore speciesisgeneralizedlinearmodels(GLMsHarris2016)Weadoptedthisapproachandusedgeneralizedlinearmixedmodels(GLMMs)toac‐countforthehierarchicalstructureofourdatasetIntheseGLMMswefittedBayesianregularized logisticregressiontothepresenceabsenceofeachspecies (response)usingthepresenceabsenceofother speciesaspredictorsandsite identityas randomtermThismethod generates two regression coefficients and p‐values foreach species pairWe averaged these to estimate the strengthofspecies interactions (cfHarris2016)These twomethodsyieldedqualitativelysimilar resultsWetherefore reportonly results fromGLMMsinthemaintextbecausetheseoftenhadhigherstatisticalpowerForresultsfromtheC‐scorenullmodelseetheSupportingInformationAppendix

Withthelistofpositiveandnegativeassociationspeciespairswebuiltonepositiveassociationmetawebandonenegativeassoci‐ationmetawebforeachvegetationtypeandtimeperiodPositivenegativeassociationindicatesthatapairofspeciesco‐occurmorelessthanexpectedbychance (basedonconstrainednullmodelorGLMMs)Wethenbuiltpositiveandnegativeassociationnetworksforeachsitefromthesetwometawebsbysub‐settingthespeciesobserved at that site This assumes that species relationships be‐tweenspeciesdonotdifferacrosssitesofthesamevegetationtypeandtimeperiodyieldingmoreconservativeresultsToremovethisassumptiononecanalsobuildanassociationnetworkforeachsiteindependentlyHoweverwelackedthepowertodothisgiventhelimitednumberofquadrats(mostly20)persiteThereforetheasso‐ciationnetworksforeachsiteinouranalyseswerederivedfromthemetawebsinsteadofbeingbuiltindependently

24emsp|emspData analysis

241emsp|emspChanges in spatial beta diversity over time

We calculated pairwise beta diversity in both species composi‐tionandspeciesassociationnetworkswithineachvegetationtypeandtimeperiodusingthemethodsproposedbyLegendreandDeCaacuteceres(2013)Forpairwisebetadiversityofspeciescompositiontheinputisasitebyspeciesmatrixwithspeciesabundancesinthecellsforspeciesassociationpairwisebetadiversitytheinputisasitebyspeciespairs(non‐randompairsinferredviamethodsdescribedintheprevioussubsection)matrix Inthiswaywetreateachnon‐randomspeciespairasaldquospeciesrdquointraditionalcommunityecology

analyses(cfPoisotetal2017)Thisapproachallowsusdirectlytocomparepairwisebetadiversityforspeciescompositionwithbetadiversity for species associations because both are calculated thesamewayWecomparedpairwisebetadiversityofeachvegetationtypebetweenthe1950sandthe2000susingpairedrandomizationtestsLower(orhigher)betadiversityinthe2000ssuggestsbiotichomogenization(ordifferentiation)

GiventhenumberofsitesinNUF(108)andSUF(126)wehavealargenumberofpairwisebeta‐diversitymeasures(5778and7875respectively)Suchlargesamplesizesmakeitpossibletoobtainsta‐tisticallysignificantresultsthatmaynotbebiologicallysignificantThereforewe also tested changes in beta diversity for each veg‐etation type using a distance‐basedpermutational test for homo‐geneityofmultivariatedispersion(PERMDISPAndersonEllingsenamp McArdle 2006) This analysis used BrayndashCurtis distancesPERMDISPcalculatesthedistanceofeachsitefromthecentroidoftheordinationspaceandthentestswhetherthesedistancesaredif‐ferentacrossgroups(ie1950svs2000s)withpermutationtestsWealsouseresultsfromPERMDISPtovisualizespeciescompositionandassociationpatternsforeachvegetationtypeandtimeperiod

242emsp|emspWithin‐site changes over time

Tocompareratesofchangeinspeciescompositionandspeciesas‐sociationsovertimewecalculatedbetadiversitybetweenperiodswithineachsite(ieasiteinthe1950sversusthesamesiteinthe2000s)againusingthemethodofLegendreandDeCaacuteceres(2013)We then used a paired t‐test to examinewhether the beta‐diver‐sityvaluesthatreflectchangesinspeciesassociationssignificantlyexceedthosethat reflectchanges inspeciescomposition (ietestwhetherspeciesassociationschangedmorethanspeciescomposi‐tion)Toconfirmtheseresultswealsoappliedpermutationalmul‐tivariate analysis of variance (PERMANOVA Anderson 2001) tocompare changes in species composition and species associationsovertime

243emsp|emspEnvironmental drivers

Tounderstand environmental drivers for species composition andassociation networks we conducted distance‐based redundancyanalysis(RDA)foreachvegetationtypeandtimeperiodWetrans‐formedthespeciescompositionandassociationmatrixintodistancematriceswiththeHellingerindex(LegendreampLegendre2012)WeusedenvironmentalvariablesaspredictorsinRDAsToidentifythemostsignificantenvironmentalvariablesweusedforwardvariableselectionandAkaikeinformationcriterion‐basedstatisticsover999replicaterunsforeachmatrix(cfPoisotetal2017)Theorderofvariableselectionprovides insight intothe importanceofenviron‐mental variables with the earlier selected variables generally af‐fectingspeciescompositionortheassociationsmoreThisanalysisallowed us to studywhether species composition and associationareaffectedbysimilarsetsofenvironmentalvariablesinthesameway and how these relationships changed over time All analyses

emspensp emsp | emsp5Li et aL

were conducted in R v340 (RCore Team 2017)with the pack‐agevegan (Oksanenet al 2018) fornullmodels and thepackageMCMCglmm(Hadfield2010)forBayesianGLMMs

3emsp |emspRESULTS

Acrossallvegetationtypesmost(gt80)speciespairsco‐occurredrandomly at both time periods as inferred from the results usingBayesianGLMMs(Table1)Amongnon‐randomspeciespairsmorespeciespairsco‐occurrednegatively (7ndash95)thanpositively (45ndash67)acrossallvegetationtypesandtimeperiods(Table1)

In theNUF region speciescompositionpositive speciesasso‐ciationsandnegativespeciesassociationsallshowedsimilar levelsof dispersion in both time periods in ordination space (Figure 1SupportingInformationAppendixFigureS2)Thuslittlehomogeni‐zationoccurredThiswasconfirmedbyPERMDISPresults(permuta‐tiontestallpgt025Table2)Howeverpairwisesitebetadiversitycalculated with methods proposed by Legendre and De Caacuteceres(2013)suggestedhomogenizationinspeciescompositionandnega‐tiveassociationsbutdifferentiationinpositiveassociations(pairedrandomizationtestbothplt0001Table2)

In the CSP region both species composition and patterns ofpositive association converge in ordination space in the 2000swhencomparedwith the1950s (Figure1Supporting InformationAppendix Figure S2) This suggests that these sites experiencedhomogenization in both species composition and positive speciesassociationsIncontrastweobservednochangeinnegativeasso‐ciationsResults frompairedrandomizationtestsonpairwisebetadiversityandPERMDISP(Table2)confirmthisinterpretation

Sites intheSUFregionalsoshowedatendencytoconvergeinspecies composition and negative associations between periods(Figure1SupportingInformationAppendixFigureS2)Incontrastpositive associations tended to diverge These results were sup‐portedby theparallel analysesof pairwise sitebetadiversity andPERMDISP(exceptnegativeassociationsTable2)

Forallregionsshiftsinbetadiversityforthespeciesassociationnetworksexceededthoseforspeciescomposition(p=0001withineach site Figure 2) Thus it appears that species association net‐workshavechangedfasterthanspeciescompositionLargeturnover

inspeciesassociations(positiveornegative)mayreflectonlyslightchangesinspeciescomposition

Speciescompositionandspeciesassociationswerelargelyinflu‐encedbythesamesetofenvironmentalvariableswithineachvege‐tationtypeandeachtimeperiod(Table3)Forallsitesinthe1950sspeciescompositionandspeciesassociationnetworkswereaffectedbyalmostthesamesetofenvironmentalvariablesThispatternstillholds in the2000sbut less so for theCSP sitesMore intriguingthe importance of environmental variables on plant communitieshaschangedovertimeForexampleshadewasthemostimportantfortheCSPsitesinthe1950sbutdecreasedinimportancebythe2000s for species composition and positive associationsMinimaltemperaturewasthemostimportantvariablethatstronglyaffectedspeciescompositionandpositiveassociationsoftheSUFsitesinthe1950sbutbecamelessimportantbythe2000swhereasprecipita‐tiongainedimportance

4emsp |emspDISCUSSION

Few studies have quantified changes in both species compositionand species relationship networks over time (Burkle Myers ampBelote2016)Ittakesconsiderableefforttoconstructasingleinter‐actionnetworkletalonenetworksatmultiplesitesovertwoormoretimeperiodsWefoundonlytwoempiricalstudiesonhomogeniza‐tion of ecological networks Laliberteacute and Tylianakis (2010) foundthatdeforestationhomogenizedparasitoidndashhostnetworksintropi‐calareasAlthoughtheyhadtemporaldataofparasitoidndashhostnet‐works(monthlysamplesfor17months)theirmainconclusionwasderivedfromspatialcomparisonsamongdifferentland‐usecatego‐riesKehindeandSamways(2014)examinedbiotichomogenizationofinsectndashflowerinteractionsinvineyardsmanagedunderagri‐envi‐ronmentalschemesintheCapeFloristicRegionTheyfoundnoevi‐denceofhomogenizationforinteractionnetworkswhencomparingvineyardswithnaturalsites

Ourstudymaythusbethefirsttoexploretemporalchangesinbeta diversity of species relationship networks Using patterns ofspecies co‐occurrence to indicate species relationships and usingavaluablehigh‐resolution long‐termdatasetwewereabletoex‐amineparallelchangesinbothcommunitycompositionandspecies

TA B L E 1 emspSummaryofspeciesusedandspeciesassociationsforeachvegetationtypeandtimeperiod

Type DateSpeciesused(n)

Pairs(negativeassociation)[n()]

Pairs(positiveassociation)[n()]

Pairs(random)[n()] Totalpairs

NUF 1950s 146 741(7) 513(48) 9331(882) 10585

NUF 2000s 160 1120(88) 626(49) 10974(863) 12720

CSP 1950s 61 162(89) 104(57) 1564(855) 1830

CSP 2000s 55 125(84) 100(67) 1260(848) 1485

SUF 1950s 225 2001(79) 1127(45) 22072(876) 25200

SUF 2000s 186 1635(95) 857(5) 14713(855) 17205

AbbreviationsCSPcentralsandplainsNUFnorthernuplandforestsSUFsouthernuplandforests

6emsp |emsp emspensp Li et aL

associationnetworksWefoundthatspeciesassociationnetworkscanhomogenizedifferentiateor shownochange through time indifferentvegetationtypesregardlessofthehomogenizationdynam‐icsofspeciescompositionLong‐termchangesinspeciescomposi‐tionandspeciesassociationsthusappeartobedecoupled

IntheNUFofWisconsinplantcommunitieswererelativelysta‐ble intermsoftheirspeciescompositionandspeciesassociationsComparedwith other community types NUF has a lower humanpopulation less land‐use change and less habitat fragmentationInthepresentstudywefoundnooverallchangesinbetadiversityof speciescompositionandspeciesassociationswhen testedwithPERMDISPHoweverpairedrandomizationtestsonbetadiversitybetweensitepairssuggestedsignificanthomogenizationinspeciescomposition matching the conclusion (biotic impoverishment andhomogenization)reachedinapreviousstudyofasubsetofthesesites(Rooneyetal2004)Herewealsoobservedhomogenizationinthe

among‐sitediversityofnegativespeciesassociationsbutsignificantdifferentiationinpositivespeciesassociationsGiventhelargenum‐berofsites inNUF(108) theresultsofrandomizationtestsmightnotbebiologicallysignificantdespitetheirstatisticalsignificancesTheseresultssuggest thatshifts inspeciescompositionmightnotoccurinthesamedirectionasshiftsinspeciesrelationships

Plantcommunities in theCSPhistoricallywerefire‐maintainedpinebarrenswithopencanopiesHowevertheyaresucceedingintoclose‐canopyuplandforestsbecauseoffiresuppression(LiampWaller2015)Firesuppressionhasresultedinhomogenizationinbothspe‐ciescomposition(LiampWaller2015)andfunctionaltraitcomposition(LiampWaller2017)Thisprobablyreflectsdeclinesinhabitathetero‐geneitywithinthesecommunitiesInthe1950ssitesintheCSPhaddifferentcanopycoverageformingmosaicsofburnedandunburnedhabitatstosupportdifferentplantcommunitiesInthe2000show‐ever siteswere similar toeachother in their canopycoverowing

F I G U R E 1 emspDistancetothecentroidofordinationsofspeciescompositionandassociationsIncreasesinthedistancetothecentroidovertimeindicatedifferentiation(diff)Decreasesinthedistancetothecentroidovertimeindicatehomogenization(homog)p lt 005 plt001p lt 0001

no change

homog

homog

no change

homog

diff

no change

no change

no change

Species Composition Positive Associations Negative Associations

NU

FC

SPSU

F

1950s 2000s 1950s 2000s 1950s 2000s

02

04

06

08

02

04

06

08

02

04

06

08

Dis

tanc

e to

Cen

troid

emspensp emsp | emsp7Li et aL

to fire suppression and succession filtering out shade‐intolerantspecies(LiampWaller2017)andhomogenizingplantcommunities(LiampWaller2015)Giventheseecologicalchangesitisnotsurprisingtofindsignificanthomogenizationinbothspeciescompositionandpositivespeciesassociationsinthesecommunities

SitesintheSUFhavebeenaffectedbydevelopmentandland‐use changes more than any other plant community inWisconsin(Rogersetal2008)Currentlymostofthesesitesarefragmentedanddisturbedbynearbyanthropogenic activities including roadsdevelopmentandagriculturePreviousstudiessuggestthathabitatdegradationandfragmentationtendtohomogenizespeciescompo‐sitionbydecreasingspeciesdiversitywhichcanalsoreducenetworkcomplexityandstability(LaliberteacuteampTylianakis2010Mokrossetal2014Tylianakisetal2007)However the fact thathabitat frag‐mentationcan result ingreaterdifferences in interactionnetworkstructure(Bordesetal2015)suggeststhatnetworksimplification(fewer nodes andor edges) does not necessarily cause networkhomogenizationNetworkscandifferacrosssites if individualnet‐workscontainuniqueinteractionseveniftheyshowageneraltrendtowards simplification In theseSUFcommunities the importanceofspeciesdispersallimitationandstochasticfactorshasincreasedwhereastheimportanceofspeciesinteractionshasdecreasedovertime(LiampWaller2016)Itisthuslikelythatstochasticassemblypro‐cesses are formingnovel sets of interactions among species eventhoughspeciesdiversityhasdecreasedIndeedwefoundonaver‐age964significantpositivespeciespairspersiteinthe1950sbutonly603significantpositivepairspersiteinthe2000sindicatingthatassociationnetworksateachsitehavesimplifiedHoweverboththepairedrandomizationtestonpairwisebetadiversityofpositiveassociationnetworksandPERMDISPsuggestedthatpositiveasso‐ciationnetworks inthe2000shavedifferentiatedsincethe1950s(Table2)ThereforeintheSUFwefoundhomogenizationofspeciescompositionbutdifferentiationofspeciespositiveassociations

Although changes in species associations are occurring fasterthan changes in species composition and appear decoupled fromthembotharegenerallyaffectedbysimilarsetsofenvironmentalvariables (Table 3) For example positive species associations andcomposition at all siteswithin each time periodwere affected bythesamesetofenvironmentalvariablesHowevertheimportanceofenvironmentalvariablesforspeciesassociationsandcompositionhaschangedovertimefortheCSPandSUFSpeciesassociationsandcompositionintheCSPweremostaffectedbycanopyshadeinthe1950swithclimaticfactorsplayingnoroleforpositiveassociationsandspeciescompositionBy the2000sclimaticvariablesbecamemoreimportantthancanopyshadeThisreflectsthefactthatCSPforestswith closed canopies show little variation in canopy coverinthe2000sIntheSUFminimaltemperatureusedtobemoreim‐portantthanprecipitationforspeciescompositionandpositiveas‐sociationsthispatternreversedinthe2000sTheseresultssuggestthatspeciesassociationsandcompositionaregenerallyaffectedbya similar set of environmental variables As global environmentalchangesacceleratetherelative importanceofenvironmentalvari‐ablesmaychange further contributing to theemergenceofnovelTA

BLE

2emspHomogenizationinspeciescompositiondoesnotalwaysresultinthehomogenizationofspeciesassociationnetworks

Ave_1950(pairwise)

Ave_2000(pairwise)

Ave_1950(permdisp)

Ave_2000(permdisp)

Direction(pairwise)

Direction(permdisp)

NUF

SpeComp

059

50587

051

30

51homog

nochange

PosAssoc

0778

0785

0561

0566

diff

nochange

NegAssoc

089

10887

0636

0633

homog

nochange

CSP

SpeComp

0447

029

90418

0327

homog

homog

PosAssoc

0683

0442

0496

0314

homog

homog

NegAssoc

080

50806

0574

0575

nochange

nochange

SUF

SpeComp

0572

0546

0516

0497

homog

homog

PosAssoc

0736

0782

0527

0567

diff

diff

NegAssoc

0862

0841

0615

0603

homog

nochange

Not

eNumbersintheave_1950(pairwise)andave_2000(pairwise)columnsrepresentaveragepairwisebetadiversitybetweensiteswithinthesamevegetationtypeinthe1950sandthe2000srespec‐

tivelyNumbersintheave_1950(permdisp)andave_2000(permdisp)columnsrepresenttheaveragedistancetothegroupcentroidintheordinationsofsiteswithinthesamevegetationtypeinthe1950s

andthe2000srespectivelyThecolumndirection(pairwise)indicatesdirectionsofchangesinthepairwisesitebetadiversityovertimetestedwithpairedrandomizationtestsThecolumndirection

(permdisp)indicatesdirectionsofchangesinthedistancebetweensitesandtheordinationcentroidovertimetestedwithpermutationtestsAbbreviationsdiffdifferentiationhomoghomogenization

NegAssocnegativeassociationPosAssocpositiveassociationSpeCompspeciescompositionplt005plt001

p lt

000

1

8emsp |emsp emspensp Li et aL

Vegetationtype Date Variable Shade Precipitation Minimaltemperature

NUF 1950s SpeComp ndash 2 1

PosAssoc ndash 2 1

NegAssoc ndash 2 1

2000s SpeComp ndash 2 1

PosAssoc ndash 2 1

NegAssoc ndash 2 1

CSP 1950s SpeComp 1

PosAssoc 1

NegAssoc 1 2

2000s SpeComp 2 1

PosAssoc 3 1 2

NegAssoc 2 1

SUF 1950s SpeComp ndash 2 1

PosAssoc ndash 2 1

NegAssoc ndash 1 2

2000s SpeComp ndash 1 2

PosAssoc ndash 1 2

NegAssoc ndash 1 2

NoteNumbersaretheorderinwhichvariablesareselectedDash(ndash)meansthattheenvironmentalvariableisnotavailableBlankcellsmeanthatthesevariablesaredroppedoutAbbreviationsNegAssocnegativeassociationPosAssocpositiveassociationSpeCompspeciescomposition

TA B L E 3 emspSelectedenvironmentalvariablesforspeciescompositionandspeciesassociations

F I G U R E 2 emspBetadiversityofspeciescompositionandassociationofthesamesiteovertimeEachpointrepresentsthebetadiversityofthesamesitebetweenthe1950sandthe2000sBetadiversityofoneindicatesthatthespeciescompositionorspeciesassociationinthe1950sandthe2000sweretotallydifferentwhereasbetadiversityofzeroindicatesnochangesinasiteovertimeTurnoverinspeciesrelationshipsappearstobemuchgreaterthantheturnoverinspeciescomposition

NU

FC

SPSU

F

Species Composition Positive Association Negative Association

025

050

075

100

025

050

075

100

025

050

075

100

Beta

div

ersi

ty o

ver t

ime

at th

e sa

me

site

emspensp emsp | emsp9Li et aL

arraysofspeciesandconsequentspecies interactions (Bloisetal2013Milazzoetal2013)

Species association (co‐occurrence) patterns have commonlybeenusedtorepresentspeciesinteractionsbecauseitisintractabletoquantifyinteractionsamonghundredsofplantspeciesSpeciesassociations may give false‐positive (hypothesized links that donotexistintherealsystem)interactionsbetweenspeciesandmaynot detect all real interactions (Barner et al 2018DelalandreampMontesinos‐Navarro2018Freilichetal2018)Howeverourmaingoalistostudybroadpatternsofcommunitystructureanddynam‐ics rather than to pinpoint exact interactions between particularspeciespairsForthispurposespeciesspatialassociationnetworksareanecessaryandusefulproxy(Freilichetal2018)becausetheycanprovidevaluableinformationregardingthenetoutputofdirectandindirecteffectsamongmultipleplantspecies(ratherthanexactpairwise interactions Delalandre amp Montesinos‐Navarro 2018)Co‐occurrence networks may also serve to predict overall com‐munityresponsestodisturbance(TullochChadegravesampLindenmayer2018) To reduce thepotential for biaswe studied species asso‐ciation patterns at a fine spatial scale (1m2) and used statisticalmethods(BayesianGLMMs)thathaverelativelyhighpowerforde‐tecting species interactions (Harris 2016) Furthermoreweusedacommonnullmodelapproachand reported these results in theSupporting InformationAppendixGiven that bothmethods pro‐videquantitatively similar results and reach the sameconclusionour conclusion that changes in species associations and speciescompositionaredecoupledislikelytoberobustConsequentlyourresultsfromspeciesassociationnetworksmayalsoholdforspeciesinteractionnetworks

Anassumptionmadeinthisstudyisthatspeciesassociationswithin each vegetation type and timeperiod remain consistentacross sites In reality associations between species can varythroughspaceandtime(Poisotetal2015)Giventhatwelackedthedatatoanalysehowspeciesassociationsmayhavedifferedover siteswepooleddataacross sites togain insights into theaverage nature of species associationswithin each communityThismakesourresultsconservativebecauseaccountingforvari‐ation inspeciesassociationsoversitescouldshowonlygreatervariationinnetworkstructurestrengtheningourconclusionthattemporal changes in species associations and composition aredecoupled

Our results suggest that species relationshipsmay not be ex‐periencingageneraltrendtowardshomogenizationbecausenovelrelationships may be forming in response to rapid global changeThisraisesimportantquestionsabouthowsuchchangesinspeciesrelationshipsmightaffectcommunitystabilityecosystemservicesandspeciesco‐evolutionStudiesofbetadiversity inspecies rela‐tionshipsremainintheirinfancy(Burkleetal2016)Giventheim‐portanceofspeciesrelationshipsandtheirpotentialunpredictablerelationshipwithspeciescompositionfutureempiricalandtheoret‐icalresearchthatinvestigatespatternscausesandconsequencesofchangesinbetadiversityofrelationshipnetworksareneeded

5emsp |emspBIOSKETCH

Daijiang Liisapost‐doctoralresearcherattheDepartmentofWildlifeEcologyampConservationUniversityofFloridaHisresearchinterestscovercommunityecologyfunctionalandphylogeneticdiversitybi‐ologicalinvasionsglobalchangebiologyandecologicalmodelling

DATA ACCE SSIBILIT Y

The data used in this study have been deposited to figshare(httpsfigsharecoms5a98a69a66f22644361e) with httpsdoiorg106084m9figshare6771938

ORCID

Daijiang Li httporcidorg0000‐0002‐0925‐3421

Timotheacutee Poisot httporcidorg0000‐0002‐0735‐5184

Benjamin Baiser httporcidorg0000‐0002‐3573‐1183

R E FE R E N C E S

AmatangeloKLFultonMRRogersDAampWallerDM (2011)Convergingforestcommunitycompositionalonganedaphicgradi‐ent threatens landscape‐level diversityDiversity and Distributions17201ndash213httpsdoiorg101111j1472‐4642201000730x

AndersonMJ(2001)Anewmethodfornon‐parametricmultivariateanalysisofvarianceAustral Ecology2632ndash46

AndersonMJEllingsenKEampMcArdleBH (2006)MultivariatedispersionasameasureofbetadiversityEcology Letters9683ndash693httpsdoiorg101111j1461‐0248200600926x

Arauacutejo M B Rozenfeld A Rahbek C amp Marquet P A (2011)Using species co‐occurrence networks to assess the im‐pacts of climate change Ecography 34 897ndash908 httpsdoiorg101111j1600‐0587201106919x

AshJDGivnishTJampWallerDM(2017)Trackinglagsinhistori‐calplantspeciesrsquoshiftsinrelationtoregionalclimatechangeGlobal Change Biology231305ndash1315httpsdoiorg101111gcb13429

BaiserBOlden JDRecordSLockwoodJLampMcKinneyML(2012) Pattern and process of biotic homogenization in the newPangaeaProceedings of the Royal Society B Biological Sciences2794772ndash4777

Barner A K Coblentz K E Hacker S D amp Menge B A (2018)Fundamentalcontradictionsamongobservationalandexperimentalestimatesofnon‐trophicspeciesinteractionsEcology99557ndash566httpsdoiorg101002ecy2133

Bascompte J JordanoPampOlesen JM (2006)Asymmetriccoevo‐lutionarynetworksfacilitatebiodiversitymaintenanceScience312431ndash433httpsdoiorg101126science1123412

Blois J L Zarnetske P L FitzpatrickM C amp Finnegan S (2013)ClimatechangeandthepastpresentandfutureofbioticinteractionsScience341499ndash504httpsdoiorg101126science1237184

BordesFMorandSPilosofSClaudeJKrasnovBRCossonJ‐Fhellip Blasdell K (2015) Habitat fragmentation alters the propertiesofahostndashparasitenetworkRodentsand theirhelminths inSouth‐East Asia Journal of Animal Ecology 84 1253ndash1263 httpsdoiorg1011111365‐265612368

BurkleLAMyersJAampBeloteRT (2016)Thebeta‐diversityofspecies interactions Untangling the drivers of geographic vari‐ation in plantndashpollinator diversity and function across scales

10emsp |emsp emspensp Li et aL

American Journal of Botany103118ndash128httpsdoiorg103732ajb1500079

CaraDonna P J Petry W K Brennan R M Cunningham J LBronstein J LWaserNMamp SandersN J (2017) InteractionrewiringandtherapidturnoverofplantndashpollinatornetworksEcology Letters20385ndash394httpsdoiorg101111ele12740

CazellesKArauacutejoMBMouquetNampGravelD(2016)Atheoryforspeciesco‐occurrenceininteractionnetworksTheoretical Ecology939ndash48httpsdoiorg101007s12080‐015‐0281‐9

ConnorEFampSimberloffD(1979)Theassemblyofspeciescommu‐nitiesChanceorcompetitionEcology601132ndash1140httpsdoiorg1023071936961

CummingGSBodinOumlErnstsonHampElmqvistT(2010)Networkanalysis in conservation biogeography Challenges and oppor‐tunities Diversity and Distributions 16 414ndash425 httpsdoiorg101111j1472‐4642201000651x

CurtisJT(1959)The vegetation of Wisconsin An ordination of plant com-munitiesMadisonWIUniversityofWisconsinPress

de Solar R R C Barlow J Ferreira J Berenguer E Lees A CThompsonJRhellipGardnerTA(2015)Howpervasiveisbioticho‐mogenizationinhuman‐modifiedtropicalforestlandscapesEcology Letters181108ndash1118httpsdoiorg101111ele12494

DelalandreLampMontesinos‐NavarroA(2018)Canco‐occurrencenet‐works predict plant‐plant interactions in a semi‐arid gypsum com‐munityPerspectives in Plant Ecology Evolution and Systematics3136ndash43httpsdoiorg101016jppees201801001

Diamond JM (1975) Assembly of species communitiesEcology and Evolution of Communities342ndash444

FreilichMAWietersEBroitmanBMarquetPAampNavarreteSA(2018)Speciesco‐occurrencenetworksCantheyrevealtrophicandnon‐trophicinteractionsinecologicalcommunitiesEcology99690ndash699httpsdoiorg101002ecy2142

Gotelli N J (2000) Null model analysis of species co‐oc‐currence patterns Ecology 81 2606ndash2621 httpsdoiorg1018900012‐9658(2000)081[2606NMAOSC]20CO2

GotelliNJampGravesGR(1996)Null models in ecologyWashingtonDCSmithsonianInstitution

GotelliN JGravesGRampRahbekC (2010)Macroecological sig‐nalsofspeciesinteractionsintheDanishavifaunaProceedings of the National Academy of Sciences of the USA1075030ndash5035httpsdoiorg101073pnas0914089107

Hadfield JD (2010)MCMCmethods formulti‐responsegeneralizedlinearmixedmodelsTheMCMCglmmRpackageJournal of Statistical Software331ndash22

Harley C D (2011) Climate change keystone predation and biodi‐versity loss Science 334 1124ndash1127 httpsdoiorg101126science1210199

Harris D J (2016) Inferring species interactions from co‐occurrencedata with Markov networks Ecology 97 3308ndash3314 httpsdoiorg101002ecy1605

Harvey E Gounand I Ward C L amp Altermatt F (2017) Bridgingecology and conservation From ecological networks to ecosys‐tem function Journal of Applied Ecology 54 371ndash379 httpsdoiorg1011111365‐266412769

Hegland S J Nielsen A Laacutezaro A Bjerknes A‐L amp TotlandOslash (2009) How does climate warming affect plant‐pollina‐tor interactions Ecology Letters 12 184ndash195 httpsdoiorg101111j1461‐0248200801269x

Hobbs R J Higgs E amp Harris J A (2009) Novel ecosystemsImplicationsforconservationandrestorationTrends in Ecology and Evolution24599ndash605httpsdoiorg101016jtree200905012

Kehinde T amp Samways M J (2014) Effects of vineyard manage‐ment on biotic homogenization of insectndashflower interaction net‐works in the cape floristic region biodiversity hotspot Journal of Insect Conservation 18 469ndash477 httpsdoiorg101007s10841‐014‐9659‐z

Kucharik C J Serbin S P Vavrus S Hopkins E J amp MotewM M (2010) Patterns of climate change across Wisconsinfrom 1950 to 2006 Physical Geography 31 1ndash28 httpsdoiorg1027470272‐36463111

LaliberteacuteEampTylianakisJM(2010)Deforestationhomogenizestrop‐ical parasitoidndashhost networks Ecology 91 1740ndash1747 httpsdoiorg10189009‐13281

LegendrePampDeCaacuteceresM(2013)BetadiversityasthevarianceofcommunitydataDissimilaritycoefficientsandpartitioningEcology Letters16951ndash963httpsdoiorg101111ele12141

LegendrePampLegendreLF(2012)Numerical ecologyAmsterdamTheNetherlandsElsevier

LiDampWallerDM(2015)DriversofobservedbiotichomogenizationinpinebarrensofcentralWisconsinEcology961030ndash1041httpsdoiorg10189014‐08931

LiDampWallerDM (2016)Long‐termshifts inthepatternsandun‐derlyingprocessesofplantassociationsinWisconsinforestsGlobal Ecology and Biogeography 25 516ndash526 httpsdoiorg101111geb12432

LiDampWallerDM(2017)Fireexclusionandclimatechangeinteracttoaffect long‐termchanges in the functional compositionofplantcommunitiesDiversity and Distributions 23 496ndash506 httpsdoiorg101111ddi12542

LoreauMMouquetNampGonzalezA(2003)Biodiversityasspatialinsurance inheterogeneous landscapesProceedings of the National Academy of Sciences of the USA 100 12765ndash12770 httpsdoiorg101073pnas2235465100

MacLeod M Genung M A Ascher J S amp Winfree R (2016)Measuring partner choice in plantndashpollinator networks Using nullmodels to separate rewiring and fidelity from chanceEcology972925ndash2931httpsdoiorg101002ecy1574

McCannK(2007)ProtectingbiostructureNature44629ndash29httpsdoiorg101038446029a

McKinneyMLampLockwoodJL(1999)BiotichomogenizationAfewwinners replacingmany losers in the nextmass extinctionTrends in Ecology and Evolution 14 450ndash453 httpsdoiorg101016S0169‐5347(99)01679‐1

Milazzo M Mirto S Domenici P amp Gristina M (2013) Climatechange exacerbates interspecific interactions in sympatriccoastal fishes Journal of Animal Ecology 82 468ndash477 httpsdoiorg101111j1365‐2656201202034x

MokrossKRyderTBCocircrtesMCWolfe JDampStoufferPC(2014) Decay of interspecific avian flock networks along a dis‐turbance gradient in Amazonia Proceedings of the Royal Society B Biological Sciences28120132599

Morales‐Castilla IMatiasM G Gravel D amp ArauacutejoM B (2015)Inferring biotic interactions from proxies Trends in Ecology and Evolution30347ndash356httpsdoiorg101016jtree201503014

OksanenJBlanchetFGFriendlyMKindtRLegendrePMcGlinnDhellipWagnerH(2018)Vegan Community ecology packageRpack‐ageversion25‐2httpsCRANR‐projectorgpackage=vegan

OldenJDComteLampGiamX(2018)TheHomogoceneAresearchprospectusforthestudyofbiotichomogenisationNeoBiota3723httpsdoiorg103897neobiota3722552

OldenJDampPoffNL (2003)Towardamechanisticunderstandingand prediction of biotic homogenization The American Naturalist162442ndash460httpsdoiorg101086378212

OldenJDPoffNLDouglasMRDouglasMEampFauschKD(2004)Ecologicalandevolutionaryconsequencesofbiotichomog‐enization Trends in Ecology and Evolution 19 18ndash24 httpsdoiorg101016jtree200309010

PetanidouTKallimanisASTzanopoulosJSgardelisSPampPantisJD(2008)Long‐termobservationofapollinationnetworkFluctuationinspeciesandinteractionsrelativeinvarianceofnetworkstructureand implicationsforestimatesofspecializationEcology Letters11564ndash575httpsdoiorg101111j1461‐0248200801170x

emspensp emsp | emsp11Li et aL

Poisot T Gueacuteveneux‐Julien C FortinM‐J Gravel D amp LegendreP (2017)Hostsparasitesandtheir interactionsrespondtodiffer‐entclimaticvariablesGlobal Ecology and Biogeography26942ndash951httpsdoiorg101111geb12602

PoisotTStoufferDBampGravelD(2015)BeyondspeciesWhyeco‐logicalinteractionnetworksvarythroughspaceandtimeOikos124243ndash251httpsdoiorg101111oik01719

RCoreTeam(2017)R A language and environment for statistical comput-ingViennaAustriaRFoundationforStatisticalComputing

RockwellRFGormezanoLJampKoonsDN(2011)TrophicmatchesandmismatchesCanpolarbearsreducetheabundanceofnestingsnowgeese inwesternHudsonBayOikos120696ndash709httpsdoiorg101111j1600‐0706201018837x

RogersDARooneyTPOlsonDampWallerDM(2008)ShiftsinsouthernWisconsin forest canopy and understory richness com‐position and heterogeneity Ecology 89 2482ndash2492 httpsdoiorg10189007‐11291

RooneyTPWiegmannSMRogersDAampWallerDM (2004)BioticimpoverishmentandhomogenizationinunfragmentedforestunderstorycommunitiesConservation Biology18787ndash798httpsdoiorg101111j1523‐1739200400515x

SalaOEChapinFSArmestoJJBerlowEBloomfieldJDirzoRhellipLeemansR(2000)Globalbiodiversityscenariosfortheyear2100 Science2871770ndash1774

TullochAIChadegravesIampLindenmayerDB(2018)Speciesco‐occur‐renceanalysispredictsmanagementoutcomesformultiplethreatsNature Ecology amp Evolution 2 465ndash474 httpsdoiorg101038s41559‐017‐0457‐3

Tylianakis J M Didham R K Bascompte J amp Wardle D A(2008) Global change and species interactions in terres‐trial ecosystems Ecology Letters 11 1351ndash1363 httpsdoiorg101111j1461‐0248200801250x

Tylianakis J M amp Morris R J (2017) Ecological networksacross environmental gradients Annual Review of Ecology

Evolution and Systematics 48 25ndash48 httpsdoiorg101146annurev‐ecolsys‐110316‐022821

Tylianakis JM Tscharntke Tamp LewisO T (2007)Habitatmodifi‐cation alters the structure of tropical hostndashparasitoid food websNature445202ndash205httpsdoiorg101038nature05429

Valiente‐BanuetAAizenMAAlcaacutentaraJMArroyoJCocucciAGalettiMhellipJordanoP(2015)BeyondspecieslossTheextinctionofecologicalinteractionsinachangingworldFunctional Ecology29299ndash307httpsdoiorg1011111365‐243512356

Vitousek PMMooneyHA Lubchenco JampMelillo JM (1997)Human domination of earthrsquos ecosystems Science 277 494ndash499httpsdoiorg101126science2775325494

Waller DM Amatangelo K L Johnson S amp Rogers D A (2012)Wisconsinvegetationdatabasendashplantcommunitysurveyandresur‐veydatafromtheWisconsinplantecologylaboratoryBiodiversity amp Ecology4255ndash264httpsdoiorg107809b‐e00082

SUPPORTING INFORMATION

Additional supporting information may be found online in theSupportingInformationsectionattheendofthearticle

How to cite this articleLiDPoisotTWallerDMBaiserBHomogenizationofspeciescompositionandspeciesassociationnetworksaredecoupledGlobal Ecol Biogeogr 2018001ndash11 httpsdoiorg101111geb12825

Page 3: Homogenization of species composition and species ... · L I ET A L. | 3 biotic homogenization in species composition (Li & Waller, 2015; Rogers, Rooney, Olson, & Waller, 2008; Rooney

emspensp emsp | emsp3Li et aL

biotic homogenization in species composition (Li ampWaller 2015Rogers RooneyOlsonampWaller 2008 Rooney et al 2004) ho‐mogenizationpatternsofplantndashplant speciesassociations in thesecommunitiesareunknownOntheonehandhomogenizedspeciescompositionacrosslocalescouldacttohomogenizespeciesassocia‐tionsasthesamesetofcommonspeciesco‐occuracrossmostsitesOntheotherhandasthespeciesresponsibleforhomogenizingspe‐ciescompositionbecamewidespreadtheycouldformnovelassoci‐ationswithspeciesrestrictedtocertainlocalesThusdifferentiationofspeciesassociationscouldoccurdespitehomogenizationofspe‐ciescomposition

Hereweaskwhetherplantcommunitycompositionandpatternsof species associationhavechanged inparallel (iebothhomoge‐nizedordifferentiated)overthelast50+yearsWealsoaskwhetherthese two components of biodiversity were influenced by similarordifferentenvironmental variables inboth timeperiods Speciesassociationsmay be inherentlymore labile than species composi‐tion(Poisotetal2017)reflectingthelargenumberofassociationspresentamongspecies(withnspecieswehaven(n‐1)2possiblespeciesassociations)Thereforewedonotnecessarilyexpectbiotichomogenization in speciescomposition tobe reflected inchangesinspeciesassociationnetworksWealsohypothesize that speciescompositionandassociationsaredrivenbythesameenvironmentalfactorsgiventhefactthatassociationsarebuiltonspeciesidentitiesHoweverwedonotexpecttheseenvironmentalfactorstohavethesame effect over time given observed changes in environmentalconditions suchas climate across thesecommunities In sumwesought to demonstrate whether species associations and speciescompositionhavesimilarresponsestoglobalenvironmentalchange

2emsp |emspMETHODS

21emsp|emspVegetation data

Inthe1950sJohnCurtisandhisstudentsandcolleaguescanvassedthestateofWisconsintofindthebestremainingexamplesofnaturalvegetationthensampled1000+sitesanddiversecommunitytypes(Curtis1959)Theychoseonlysiteswithnoobviousdisturbancesand located all plots ge30m away from any edges Within eachsitetheyrecordedthepresenceandabsenceofallvascularplantsin each ofmany sampled1‐m2 quadrats The number of quadratssampledateachsitevariedbutwasusually20TheywerecarefultoarchivetheiroriginaldatainthePlantEcologyLaboratoryattheUniversity of WisconsinndashMadison (httpswwwbotanywisceduPELWallerAmatangeloJohnsonampRogers2012)Hereweusedatafromthreecommunitytypesresurveyedsince2000usingsimi‐lar methods (Supporting Information Appendix Figure S1) north‐ernuplandforests (NUF108sitesAmatangeloFultonRogersampWaller2011Rooneyetal2004)centralsandspinebarrensforests(CSP30sitesLiampWaller2015)andsouthernuplandforests(SUF128sitesRogersetal2008)These resurveyedsites showednoobvious signsof recentdisturbanceandwere located in relatively

intacthabitatsGiventhattheoriginalsiteswerenotpermanentlymarked theseareldquosemi‐permanentrdquoplotsTheresurveyssampledtwo to six times asmanyquadrats per site as theoriginal surveyAlltaxonomywascarefullysynchronizedbetweenperiodsToallowfair comparisonswithmatchedsamplingeffortwe randomlysub‐sampledthe2000ssurveydatausingthesamenumberofquadratsasused in the1950sCollectivelyweanalysed speciespresenceabsencedatafromgt5000quadratsdistributedamongthesame266sitesinthetwotimeperiods

22emsp|emspEnvironmental data

Weanalysedenvironmentalvariablestodetectdriversofplantcom‐position andassociationpatternsWeobtainedaveragedailypre‐cipitation andminimal temperature for all sites from aWisconsinclimate database covering 1950ndash2006 (Kucharik Serbin VavrusHopkinsampMotew2010)Thesedata arederived fromanexten‐sivenetworkofweatherstationsdistributedthroughoutthestateDownscaleddataweregeneratedviaspatial interpolationTorep‐resenteachperiodofsamplingweaveragedclimatevariablesovertwo5‐yearperiods1950ndash1954and2002ndash2006(cfAshGivnishampWaller2017LiampWaller2017)Thisaccountsforpotentiallagsinspeciesrsquo responsesand inter‐annualclimaticvariationWedohavecanopyshadedataforthecentralsandpinebarrensforestsinbothtimeperiods(LiampWaller2015)Howeversuchdatawerenotavail‐ableforothervegetationtypes

23emsp|emspPlant association networks

Within each vegetation type and time period we constructed aquadratbyspeciesmatrixwithrowsforeachquadrat(nestedwithinasite)andcolumnsforeachspeciesValuesinthecellsofthismatrixreflectthepresenceorabsence(10)ofthatspeciesinthatquadratWetreatthe1‐m2quadratasthesampleunitherebecauseplantsthat co‐occur at this scale aremost likely also to interactWe re‐movedspeciesoccupyingfewerthansixquadratsateachperiodtoexcluderarespeciesandfacilitatethedeterminationofcorespeciesco‐occurrencepairsWethenusedthisquadratbyspeciesmatrixtoinferspeciespairsthataremoreorlesslikelytoco‐occurwitheachotherincomparisontorandomexpectationsusingtwomethods

Ourfirstmethodisbasedonthetraditionalnullmodelapproachcommonly used to study species co‐occurrence patterns (Gotelli2000)We calculated the partialC‐score for each pair of speciesas(ciminusmij)(cjminusmij)whereci and cjarethenumberofquadratoccur‐rencesof species i and j and mij is thenumberof quadratswherebothspeciesoccurredWethenshuffledthecellsofthequadratbyspeciesmatrix5000timesusingthefixedndashfixedrandomizational‐gorithmWeappliedthisnullmodeltoeachsiteseparatelyandthenrestackedtheshuffleddataThisconstrainednullmodelmaintainsrowandcolumnsums(speciesrichnesswithineachquadratandspe‐ciesfrequencyacrossallquadrats)ofthematrixwhilealsoaccount‐ing for thehierarchical structureofourdataset Ineach iterationpartialC‐scores for all species pairswere computed generating a

4emsp |emsp emspensp Li et aL

nulldistributionfromthe5000randomizationsThiswasthenusedtojudgewhethertheobservedC‐scorereflectshigherorlowerco‐occurrence thanexpectedbychanceFormoredetails seeLiandWaller(2016)

A recent study concluded that this null model approach hasrelatively lowpowerto infer truespecies interactions fromco‐oc‐currence patterns and suggested using Markov networks instead(Harris 2016) Unfortunately current implementations ofMarkovnetworks are restricted to le20 species (Harris 2016) precludingtheir use with our dataset A second method with power similartoMarkov networks but extending to includemanymore speciesisgeneralizedlinearmodels(GLMsHarris2016)Weadoptedthisapproachandusedgeneralizedlinearmixedmodels(GLMMs)toac‐countforthehierarchicalstructureofourdatasetIntheseGLMMswefittedBayesianregularized logisticregressiontothepresenceabsenceofeachspecies (response)usingthepresenceabsenceofother speciesaspredictorsandsite identityas randomtermThismethod generates two regression coefficients and p‐values foreach species pairWe averaged these to estimate the strengthofspecies interactions (cfHarris2016)These twomethodsyieldedqualitativelysimilar resultsWetherefore reportonly results fromGLMMsinthemaintextbecausetheseoftenhadhigherstatisticalpowerForresultsfromtheC‐scorenullmodelseetheSupportingInformationAppendix

Withthelistofpositiveandnegativeassociationspeciespairswebuiltonepositiveassociationmetawebandonenegativeassoci‐ationmetawebforeachvegetationtypeandtimeperiodPositivenegativeassociationindicatesthatapairofspeciesco‐occurmorelessthanexpectedbychance (basedonconstrainednullmodelorGLMMs)Wethenbuiltpositiveandnegativeassociationnetworksforeachsitefromthesetwometawebsbysub‐settingthespeciesobserved at that site This assumes that species relationships be‐tweenspeciesdonotdifferacrosssitesofthesamevegetationtypeandtimeperiodyieldingmoreconservativeresultsToremovethisassumptiononecanalsobuildanassociationnetworkforeachsiteindependentlyHoweverwelackedthepowertodothisgiventhelimitednumberofquadrats(mostly20)persiteThereforetheasso‐ciationnetworksforeachsiteinouranalyseswerederivedfromthemetawebsinsteadofbeingbuiltindependently

24emsp|emspData analysis

241emsp|emspChanges in spatial beta diversity over time

We calculated pairwise beta diversity in both species composi‐tionandspeciesassociationnetworkswithineachvegetationtypeandtimeperiodusingthemethodsproposedbyLegendreandDeCaacuteceres(2013)Forpairwisebetadiversityofspeciescompositiontheinputisasitebyspeciesmatrixwithspeciesabundancesinthecellsforspeciesassociationpairwisebetadiversitytheinputisasitebyspeciespairs(non‐randompairsinferredviamethodsdescribedintheprevioussubsection)matrix Inthiswaywetreateachnon‐randomspeciespairasaldquospeciesrdquointraditionalcommunityecology

analyses(cfPoisotetal2017)Thisapproachallowsusdirectlytocomparepairwisebetadiversityforspeciescompositionwithbetadiversity for species associations because both are calculated thesamewayWecomparedpairwisebetadiversityofeachvegetationtypebetweenthe1950sandthe2000susingpairedrandomizationtestsLower(orhigher)betadiversityinthe2000ssuggestsbiotichomogenization(ordifferentiation)

GiventhenumberofsitesinNUF(108)andSUF(126)wehavealargenumberofpairwisebeta‐diversitymeasures(5778and7875respectively)Suchlargesamplesizesmakeitpossibletoobtainsta‐tisticallysignificantresultsthatmaynotbebiologicallysignificantThereforewe also tested changes in beta diversity for each veg‐etation type using a distance‐basedpermutational test for homo‐geneityofmultivariatedispersion(PERMDISPAndersonEllingsenamp McArdle 2006) This analysis used BrayndashCurtis distancesPERMDISPcalculatesthedistanceofeachsitefromthecentroidoftheordinationspaceandthentestswhetherthesedistancesaredif‐ferentacrossgroups(ie1950svs2000s)withpermutationtestsWealsouseresultsfromPERMDISPtovisualizespeciescompositionandassociationpatternsforeachvegetationtypeandtimeperiod

242emsp|emspWithin‐site changes over time

Tocompareratesofchangeinspeciescompositionandspeciesas‐sociationsovertimewecalculatedbetadiversitybetweenperiodswithineachsite(ieasiteinthe1950sversusthesamesiteinthe2000s)againusingthemethodofLegendreandDeCaacuteceres(2013)We then used a paired t‐test to examinewhether the beta‐diver‐sityvaluesthatreflectchangesinspeciesassociationssignificantlyexceedthosethat reflectchanges inspeciescomposition (ietestwhetherspeciesassociationschangedmorethanspeciescomposi‐tion)Toconfirmtheseresultswealsoappliedpermutationalmul‐tivariate analysis of variance (PERMANOVA Anderson 2001) tocompare changes in species composition and species associationsovertime

243emsp|emspEnvironmental drivers

Tounderstand environmental drivers for species composition andassociation networks we conducted distance‐based redundancyanalysis(RDA)foreachvegetationtypeandtimeperiodWetrans‐formedthespeciescompositionandassociationmatrixintodistancematriceswiththeHellingerindex(LegendreampLegendre2012)WeusedenvironmentalvariablesaspredictorsinRDAsToidentifythemostsignificantenvironmentalvariablesweusedforwardvariableselectionandAkaikeinformationcriterion‐basedstatisticsover999replicaterunsforeachmatrix(cfPoisotetal2017)Theorderofvariableselectionprovides insight intothe importanceofenviron‐mental variables with the earlier selected variables generally af‐fectingspeciescompositionortheassociationsmoreThisanalysisallowed us to studywhether species composition and associationareaffectedbysimilarsetsofenvironmentalvariablesinthesameway and how these relationships changed over time All analyses

emspensp emsp | emsp5Li et aL

were conducted in R v340 (RCore Team 2017)with the pack‐agevegan (Oksanenet al 2018) fornullmodels and thepackageMCMCglmm(Hadfield2010)forBayesianGLMMs

3emsp |emspRESULTS

Acrossallvegetationtypesmost(gt80)speciespairsco‐occurredrandomly at both time periods as inferred from the results usingBayesianGLMMs(Table1)Amongnon‐randomspeciespairsmorespeciespairsco‐occurrednegatively (7ndash95)thanpositively (45ndash67)acrossallvegetationtypesandtimeperiods(Table1)

In theNUF region speciescompositionpositive speciesasso‐ciationsandnegativespeciesassociationsallshowedsimilar levelsof dispersion in both time periods in ordination space (Figure 1SupportingInformationAppendixFigureS2)Thuslittlehomogeni‐zationoccurredThiswasconfirmedbyPERMDISPresults(permuta‐tiontestallpgt025Table2)Howeverpairwisesitebetadiversitycalculated with methods proposed by Legendre and De Caacuteceres(2013)suggestedhomogenizationinspeciescompositionandnega‐tiveassociationsbutdifferentiationinpositiveassociations(pairedrandomizationtestbothplt0001Table2)

In the CSP region both species composition and patterns ofpositive association converge in ordination space in the 2000swhencomparedwith the1950s (Figure1Supporting InformationAppendix Figure S2) This suggests that these sites experiencedhomogenization in both species composition and positive speciesassociationsIncontrastweobservednochangeinnegativeasso‐ciationsResults frompairedrandomizationtestsonpairwisebetadiversityandPERMDISP(Table2)confirmthisinterpretation

Sites intheSUFregionalsoshowedatendencytoconvergeinspecies composition and negative associations between periods(Figure1SupportingInformationAppendixFigureS2)Incontrastpositive associations tended to diverge These results were sup‐portedby theparallel analysesof pairwise sitebetadiversity andPERMDISP(exceptnegativeassociationsTable2)

Forallregionsshiftsinbetadiversityforthespeciesassociationnetworksexceededthoseforspeciescomposition(p=0001withineach site Figure 2) Thus it appears that species association net‐workshavechangedfasterthanspeciescompositionLargeturnover

inspeciesassociations(positiveornegative)mayreflectonlyslightchangesinspeciescomposition

Speciescompositionandspeciesassociationswerelargelyinflu‐encedbythesamesetofenvironmentalvariableswithineachvege‐tationtypeandeachtimeperiod(Table3)Forallsitesinthe1950sspeciescompositionandspeciesassociationnetworkswereaffectedbyalmostthesamesetofenvironmentalvariablesThispatternstillholds in the2000sbut less so for theCSP sitesMore intriguingthe importance of environmental variables on plant communitieshaschangedovertimeForexampleshadewasthemostimportantfortheCSPsitesinthe1950sbutdecreasedinimportancebythe2000s for species composition and positive associationsMinimaltemperaturewasthemostimportantvariablethatstronglyaffectedspeciescompositionandpositiveassociationsoftheSUFsitesinthe1950sbutbecamelessimportantbythe2000swhereasprecipita‐tiongainedimportance

4emsp |emspDISCUSSION

Few studies have quantified changes in both species compositionand species relationship networks over time (Burkle Myers ampBelote2016)Ittakesconsiderableefforttoconstructasingleinter‐actionnetworkletalonenetworksatmultiplesitesovertwoormoretimeperiodsWefoundonlytwoempiricalstudiesonhomogeniza‐tion of ecological networks Laliberteacute and Tylianakis (2010) foundthatdeforestationhomogenizedparasitoidndashhostnetworksintropi‐calareasAlthoughtheyhadtemporaldataofparasitoidndashhostnet‐works(monthlysamplesfor17months)theirmainconclusionwasderivedfromspatialcomparisonsamongdifferentland‐usecatego‐riesKehindeandSamways(2014)examinedbiotichomogenizationofinsectndashflowerinteractionsinvineyardsmanagedunderagri‐envi‐ronmentalschemesintheCapeFloristicRegionTheyfoundnoevi‐denceofhomogenizationforinteractionnetworkswhencomparingvineyardswithnaturalsites

Ourstudymaythusbethefirsttoexploretemporalchangesinbeta diversity of species relationship networks Using patterns ofspecies co‐occurrence to indicate species relationships and usingavaluablehigh‐resolution long‐termdatasetwewereabletoex‐amineparallelchangesinbothcommunitycompositionandspecies

TA B L E 1 emspSummaryofspeciesusedandspeciesassociationsforeachvegetationtypeandtimeperiod

Type DateSpeciesused(n)

Pairs(negativeassociation)[n()]

Pairs(positiveassociation)[n()]

Pairs(random)[n()] Totalpairs

NUF 1950s 146 741(7) 513(48) 9331(882) 10585

NUF 2000s 160 1120(88) 626(49) 10974(863) 12720

CSP 1950s 61 162(89) 104(57) 1564(855) 1830

CSP 2000s 55 125(84) 100(67) 1260(848) 1485

SUF 1950s 225 2001(79) 1127(45) 22072(876) 25200

SUF 2000s 186 1635(95) 857(5) 14713(855) 17205

AbbreviationsCSPcentralsandplainsNUFnorthernuplandforestsSUFsouthernuplandforests

6emsp |emsp emspensp Li et aL

associationnetworksWefoundthatspeciesassociationnetworkscanhomogenizedifferentiateor shownochange through time indifferentvegetationtypesregardlessofthehomogenizationdynam‐icsofspeciescompositionLong‐termchangesinspeciescomposi‐tionandspeciesassociationsthusappeartobedecoupled

IntheNUFofWisconsinplantcommunitieswererelativelysta‐ble intermsoftheirspeciescompositionandspeciesassociationsComparedwith other community types NUF has a lower humanpopulation less land‐use change and less habitat fragmentationInthepresentstudywefoundnooverallchangesinbetadiversityof speciescompositionandspeciesassociationswhen testedwithPERMDISPHoweverpairedrandomizationtestsonbetadiversitybetweensitepairssuggestedsignificanthomogenizationinspeciescomposition matching the conclusion (biotic impoverishment andhomogenization)reachedinapreviousstudyofasubsetofthesesites(Rooneyetal2004)Herewealsoobservedhomogenizationinthe

among‐sitediversityofnegativespeciesassociationsbutsignificantdifferentiationinpositivespeciesassociationsGiventhelargenum‐berofsites inNUF(108) theresultsofrandomizationtestsmightnotbebiologicallysignificantdespitetheirstatisticalsignificancesTheseresultssuggest thatshifts inspeciescompositionmightnotoccurinthesamedirectionasshiftsinspeciesrelationships

Plantcommunities in theCSPhistoricallywerefire‐maintainedpinebarrenswithopencanopiesHowevertheyaresucceedingintoclose‐canopyuplandforestsbecauseoffiresuppression(LiampWaller2015)Firesuppressionhasresultedinhomogenizationinbothspe‐ciescomposition(LiampWaller2015)andfunctionaltraitcomposition(LiampWaller2017)Thisprobablyreflectsdeclinesinhabitathetero‐geneitywithinthesecommunitiesInthe1950ssitesintheCSPhaddifferentcanopycoverageformingmosaicsofburnedandunburnedhabitatstosupportdifferentplantcommunitiesInthe2000show‐ever siteswere similar toeachother in their canopycoverowing

F I G U R E 1 emspDistancetothecentroidofordinationsofspeciescompositionandassociationsIncreasesinthedistancetothecentroidovertimeindicatedifferentiation(diff)Decreasesinthedistancetothecentroidovertimeindicatehomogenization(homog)p lt 005 plt001p lt 0001

no change

homog

homog

no change

homog

diff

no change

no change

no change

Species Composition Positive Associations Negative Associations

NU

FC

SPSU

F

1950s 2000s 1950s 2000s 1950s 2000s

02

04

06

08

02

04

06

08

02

04

06

08

Dis

tanc

e to

Cen

troid

emspensp emsp | emsp7Li et aL

to fire suppression and succession filtering out shade‐intolerantspecies(LiampWaller2017)andhomogenizingplantcommunities(LiampWaller2015)Giventheseecologicalchangesitisnotsurprisingtofindsignificanthomogenizationinbothspeciescompositionandpositivespeciesassociationsinthesecommunities

SitesintheSUFhavebeenaffectedbydevelopmentandland‐use changes more than any other plant community inWisconsin(Rogersetal2008)Currentlymostofthesesitesarefragmentedanddisturbedbynearbyanthropogenic activities including roadsdevelopmentandagriculturePreviousstudiessuggestthathabitatdegradationandfragmentationtendtohomogenizespeciescompo‐sitionbydecreasingspeciesdiversitywhichcanalsoreducenetworkcomplexityandstability(LaliberteacuteampTylianakis2010Mokrossetal2014Tylianakisetal2007)However the fact thathabitat frag‐mentationcan result ingreaterdifferences in interactionnetworkstructure(Bordesetal2015)suggeststhatnetworksimplification(fewer nodes andor edges) does not necessarily cause networkhomogenizationNetworkscandifferacrosssites if individualnet‐workscontainuniqueinteractionseveniftheyshowageneraltrendtowards simplification In theseSUFcommunities the importanceofspeciesdispersallimitationandstochasticfactorshasincreasedwhereastheimportanceofspeciesinteractionshasdecreasedovertime(LiampWaller2016)Itisthuslikelythatstochasticassemblypro‐cesses are formingnovel sets of interactions among species eventhoughspeciesdiversityhasdecreasedIndeedwefoundonaver‐age964significantpositivespeciespairspersiteinthe1950sbutonly603significantpositivepairspersiteinthe2000sindicatingthatassociationnetworksateachsitehavesimplifiedHoweverboththepairedrandomizationtestonpairwisebetadiversityofpositiveassociationnetworksandPERMDISPsuggestedthatpositiveasso‐ciationnetworks inthe2000shavedifferentiatedsincethe1950s(Table2)ThereforeintheSUFwefoundhomogenizationofspeciescompositionbutdifferentiationofspeciespositiveassociations

Although changes in species associations are occurring fasterthan changes in species composition and appear decoupled fromthembotharegenerallyaffectedbysimilarsetsofenvironmentalvariables (Table 3) For example positive species associations andcomposition at all siteswithin each time periodwere affected bythesamesetofenvironmentalvariablesHowevertheimportanceofenvironmentalvariablesforspeciesassociationsandcompositionhaschangedovertimefortheCSPandSUFSpeciesassociationsandcompositionintheCSPweremostaffectedbycanopyshadeinthe1950swithclimaticfactorsplayingnoroleforpositiveassociationsandspeciescompositionBy the2000sclimaticvariablesbecamemoreimportantthancanopyshadeThisreflectsthefactthatCSPforestswith closed canopies show little variation in canopy coverinthe2000sIntheSUFminimaltemperatureusedtobemoreim‐portantthanprecipitationforspeciescompositionandpositiveas‐sociationsthispatternreversedinthe2000sTheseresultssuggestthatspeciesassociationsandcompositionaregenerallyaffectedbya similar set of environmental variables As global environmentalchangesacceleratetherelative importanceofenvironmentalvari‐ablesmaychange further contributing to theemergenceofnovelTA

BLE

2emspHomogenizationinspeciescompositiondoesnotalwaysresultinthehomogenizationofspeciesassociationnetworks

Ave_1950(pairwise)

Ave_2000(pairwise)

Ave_1950(permdisp)

Ave_2000(permdisp)

Direction(pairwise)

Direction(permdisp)

NUF

SpeComp

059

50587

051

30

51homog

nochange

PosAssoc

0778

0785

0561

0566

diff

nochange

NegAssoc

089

10887

0636

0633

homog

nochange

CSP

SpeComp

0447

029

90418

0327

homog

homog

PosAssoc

0683

0442

0496

0314

homog

homog

NegAssoc

080

50806

0574

0575

nochange

nochange

SUF

SpeComp

0572

0546

0516

0497

homog

homog

PosAssoc

0736

0782

0527

0567

diff

diff

NegAssoc

0862

0841

0615

0603

homog

nochange

Not

eNumbersintheave_1950(pairwise)andave_2000(pairwise)columnsrepresentaveragepairwisebetadiversitybetweensiteswithinthesamevegetationtypeinthe1950sandthe2000srespec‐

tivelyNumbersintheave_1950(permdisp)andave_2000(permdisp)columnsrepresenttheaveragedistancetothegroupcentroidintheordinationsofsiteswithinthesamevegetationtypeinthe1950s

andthe2000srespectivelyThecolumndirection(pairwise)indicatesdirectionsofchangesinthepairwisesitebetadiversityovertimetestedwithpairedrandomizationtestsThecolumndirection

(permdisp)indicatesdirectionsofchangesinthedistancebetweensitesandtheordinationcentroidovertimetestedwithpermutationtestsAbbreviationsdiffdifferentiationhomoghomogenization

NegAssocnegativeassociationPosAssocpositiveassociationSpeCompspeciescompositionplt005plt001

p lt

000

1

8emsp |emsp emspensp Li et aL

Vegetationtype Date Variable Shade Precipitation Minimaltemperature

NUF 1950s SpeComp ndash 2 1

PosAssoc ndash 2 1

NegAssoc ndash 2 1

2000s SpeComp ndash 2 1

PosAssoc ndash 2 1

NegAssoc ndash 2 1

CSP 1950s SpeComp 1

PosAssoc 1

NegAssoc 1 2

2000s SpeComp 2 1

PosAssoc 3 1 2

NegAssoc 2 1

SUF 1950s SpeComp ndash 2 1

PosAssoc ndash 2 1

NegAssoc ndash 1 2

2000s SpeComp ndash 1 2

PosAssoc ndash 1 2

NegAssoc ndash 1 2

NoteNumbersaretheorderinwhichvariablesareselectedDash(ndash)meansthattheenvironmentalvariableisnotavailableBlankcellsmeanthatthesevariablesaredroppedoutAbbreviationsNegAssocnegativeassociationPosAssocpositiveassociationSpeCompspeciescomposition

TA B L E 3 emspSelectedenvironmentalvariablesforspeciescompositionandspeciesassociations

F I G U R E 2 emspBetadiversityofspeciescompositionandassociationofthesamesiteovertimeEachpointrepresentsthebetadiversityofthesamesitebetweenthe1950sandthe2000sBetadiversityofoneindicatesthatthespeciescompositionorspeciesassociationinthe1950sandthe2000sweretotallydifferentwhereasbetadiversityofzeroindicatesnochangesinasiteovertimeTurnoverinspeciesrelationshipsappearstobemuchgreaterthantheturnoverinspeciescomposition

NU

FC

SPSU

F

Species Composition Positive Association Negative Association

025

050

075

100

025

050

075

100

025

050

075

100

Beta

div

ersi

ty o

ver t

ime

at th

e sa

me

site

emspensp emsp | emsp9Li et aL

arraysofspeciesandconsequentspecies interactions (Bloisetal2013Milazzoetal2013)

Species association (co‐occurrence) patterns have commonlybeenusedtorepresentspeciesinteractionsbecauseitisintractabletoquantifyinteractionsamonghundredsofplantspeciesSpeciesassociations may give false‐positive (hypothesized links that donotexistintherealsystem)interactionsbetweenspeciesandmaynot detect all real interactions (Barner et al 2018DelalandreampMontesinos‐Navarro2018Freilichetal2018)Howeverourmaingoalistostudybroadpatternsofcommunitystructureanddynam‐ics rather than to pinpoint exact interactions between particularspeciespairsForthispurposespeciesspatialassociationnetworksareanecessaryandusefulproxy(Freilichetal2018)becausetheycanprovidevaluableinformationregardingthenetoutputofdirectandindirecteffectsamongmultipleplantspecies(ratherthanexactpairwise interactions Delalandre amp Montesinos‐Navarro 2018)Co‐occurrence networks may also serve to predict overall com‐munityresponsestodisturbance(TullochChadegravesampLindenmayer2018) To reduce thepotential for biaswe studied species asso‐ciation patterns at a fine spatial scale (1m2) and used statisticalmethods(BayesianGLMMs)thathaverelativelyhighpowerforde‐tecting species interactions (Harris 2016) Furthermoreweusedacommonnullmodelapproachand reported these results in theSupporting InformationAppendixGiven that bothmethods pro‐videquantitatively similar results and reach the sameconclusionour conclusion that changes in species associations and speciescompositionaredecoupledislikelytoberobustConsequentlyourresultsfromspeciesassociationnetworksmayalsoholdforspeciesinteractionnetworks

Anassumptionmadeinthisstudyisthatspeciesassociationswithin each vegetation type and timeperiod remain consistentacross sites In reality associations between species can varythroughspaceandtime(Poisotetal2015)Giventhatwelackedthedatatoanalysehowspeciesassociationsmayhavedifferedover siteswepooleddataacross sites togain insights into theaverage nature of species associationswithin each communityThismakesourresultsconservativebecauseaccountingforvari‐ation inspeciesassociationsoversitescouldshowonlygreatervariationinnetworkstructurestrengtheningourconclusionthattemporal changes in species associations and composition aredecoupled

Our results suggest that species relationshipsmay not be ex‐periencingageneraltrendtowardshomogenizationbecausenovelrelationships may be forming in response to rapid global changeThisraisesimportantquestionsabouthowsuchchangesinspeciesrelationshipsmightaffectcommunitystabilityecosystemservicesandspeciesco‐evolutionStudiesofbetadiversity inspecies rela‐tionshipsremainintheirinfancy(Burkleetal2016)Giventheim‐portanceofspeciesrelationshipsandtheirpotentialunpredictablerelationshipwithspeciescompositionfutureempiricalandtheoret‐icalresearchthatinvestigatespatternscausesandconsequencesofchangesinbetadiversityofrelationshipnetworksareneeded

5emsp |emspBIOSKETCH

Daijiang Liisapost‐doctoralresearcherattheDepartmentofWildlifeEcologyampConservationUniversityofFloridaHisresearchinterestscovercommunityecologyfunctionalandphylogeneticdiversitybi‐ologicalinvasionsglobalchangebiologyandecologicalmodelling

DATA ACCE SSIBILIT Y

The data used in this study have been deposited to figshare(httpsfigsharecoms5a98a69a66f22644361e) with httpsdoiorg106084m9figshare6771938

ORCID

Daijiang Li httporcidorg0000‐0002‐0925‐3421

Timotheacutee Poisot httporcidorg0000‐0002‐0735‐5184

Benjamin Baiser httporcidorg0000‐0002‐3573‐1183

R E FE R E N C E S

AmatangeloKLFultonMRRogersDAampWallerDM (2011)Convergingforestcommunitycompositionalonganedaphicgradi‐ent threatens landscape‐level diversityDiversity and Distributions17201ndash213httpsdoiorg101111j1472‐4642201000730x

AndersonMJ(2001)Anewmethodfornon‐parametricmultivariateanalysisofvarianceAustral Ecology2632ndash46

AndersonMJEllingsenKEampMcArdleBH (2006)MultivariatedispersionasameasureofbetadiversityEcology Letters9683ndash693httpsdoiorg101111j1461‐0248200600926x

Arauacutejo M B Rozenfeld A Rahbek C amp Marquet P A (2011)Using species co‐occurrence networks to assess the im‐pacts of climate change Ecography 34 897ndash908 httpsdoiorg101111j1600‐0587201106919x

AshJDGivnishTJampWallerDM(2017)Trackinglagsinhistori‐calplantspeciesrsquoshiftsinrelationtoregionalclimatechangeGlobal Change Biology231305ndash1315httpsdoiorg101111gcb13429

BaiserBOlden JDRecordSLockwoodJLampMcKinneyML(2012) Pattern and process of biotic homogenization in the newPangaeaProceedings of the Royal Society B Biological Sciences2794772ndash4777

Barner A K Coblentz K E Hacker S D amp Menge B A (2018)Fundamentalcontradictionsamongobservationalandexperimentalestimatesofnon‐trophicspeciesinteractionsEcology99557ndash566httpsdoiorg101002ecy2133

Bascompte J JordanoPampOlesen JM (2006)Asymmetriccoevo‐lutionarynetworksfacilitatebiodiversitymaintenanceScience312431ndash433httpsdoiorg101126science1123412

Blois J L Zarnetske P L FitzpatrickM C amp Finnegan S (2013)ClimatechangeandthepastpresentandfutureofbioticinteractionsScience341499ndash504httpsdoiorg101126science1237184

BordesFMorandSPilosofSClaudeJKrasnovBRCossonJ‐Fhellip Blasdell K (2015) Habitat fragmentation alters the propertiesofahostndashparasitenetworkRodentsand theirhelminths inSouth‐East Asia Journal of Animal Ecology 84 1253ndash1263 httpsdoiorg1011111365‐265612368

BurkleLAMyersJAampBeloteRT (2016)Thebeta‐diversityofspecies interactions Untangling the drivers of geographic vari‐ation in plantndashpollinator diversity and function across scales

10emsp |emsp emspensp Li et aL

American Journal of Botany103118ndash128httpsdoiorg103732ajb1500079

CaraDonna P J Petry W K Brennan R M Cunningham J LBronstein J LWaserNMamp SandersN J (2017) InteractionrewiringandtherapidturnoverofplantndashpollinatornetworksEcology Letters20385ndash394httpsdoiorg101111ele12740

CazellesKArauacutejoMBMouquetNampGravelD(2016)Atheoryforspeciesco‐occurrenceininteractionnetworksTheoretical Ecology939ndash48httpsdoiorg101007s12080‐015‐0281‐9

ConnorEFampSimberloffD(1979)Theassemblyofspeciescommu‐nitiesChanceorcompetitionEcology601132ndash1140httpsdoiorg1023071936961

CummingGSBodinOumlErnstsonHampElmqvistT(2010)Networkanalysis in conservation biogeography Challenges and oppor‐tunities Diversity and Distributions 16 414ndash425 httpsdoiorg101111j1472‐4642201000651x

CurtisJT(1959)The vegetation of Wisconsin An ordination of plant com-munitiesMadisonWIUniversityofWisconsinPress

de Solar R R C Barlow J Ferreira J Berenguer E Lees A CThompsonJRhellipGardnerTA(2015)Howpervasiveisbioticho‐mogenizationinhuman‐modifiedtropicalforestlandscapesEcology Letters181108ndash1118httpsdoiorg101111ele12494

DelalandreLampMontesinos‐NavarroA(2018)Canco‐occurrencenet‐works predict plant‐plant interactions in a semi‐arid gypsum com‐munityPerspectives in Plant Ecology Evolution and Systematics3136ndash43httpsdoiorg101016jppees201801001

Diamond JM (1975) Assembly of species communitiesEcology and Evolution of Communities342ndash444

FreilichMAWietersEBroitmanBMarquetPAampNavarreteSA(2018)Speciesco‐occurrencenetworksCantheyrevealtrophicandnon‐trophicinteractionsinecologicalcommunitiesEcology99690ndash699httpsdoiorg101002ecy2142

Gotelli N J (2000) Null model analysis of species co‐oc‐currence patterns Ecology 81 2606ndash2621 httpsdoiorg1018900012‐9658(2000)081[2606NMAOSC]20CO2

GotelliNJampGravesGR(1996)Null models in ecologyWashingtonDCSmithsonianInstitution

GotelliN JGravesGRampRahbekC (2010)Macroecological sig‐nalsofspeciesinteractionsintheDanishavifaunaProceedings of the National Academy of Sciences of the USA1075030ndash5035httpsdoiorg101073pnas0914089107

Hadfield JD (2010)MCMCmethods formulti‐responsegeneralizedlinearmixedmodelsTheMCMCglmmRpackageJournal of Statistical Software331ndash22

Harley C D (2011) Climate change keystone predation and biodi‐versity loss Science 334 1124ndash1127 httpsdoiorg101126science1210199

Harris D J (2016) Inferring species interactions from co‐occurrencedata with Markov networks Ecology 97 3308ndash3314 httpsdoiorg101002ecy1605

Harvey E Gounand I Ward C L amp Altermatt F (2017) Bridgingecology and conservation From ecological networks to ecosys‐tem function Journal of Applied Ecology 54 371ndash379 httpsdoiorg1011111365‐266412769

Hegland S J Nielsen A Laacutezaro A Bjerknes A‐L amp TotlandOslash (2009) How does climate warming affect plant‐pollina‐tor interactions Ecology Letters 12 184ndash195 httpsdoiorg101111j1461‐0248200801269x

Hobbs R J Higgs E amp Harris J A (2009) Novel ecosystemsImplicationsforconservationandrestorationTrends in Ecology and Evolution24599ndash605httpsdoiorg101016jtree200905012

Kehinde T amp Samways M J (2014) Effects of vineyard manage‐ment on biotic homogenization of insectndashflower interaction net‐works in the cape floristic region biodiversity hotspot Journal of Insect Conservation 18 469ndash477 httpsdoiorg101007s10841‐014‐9659‐z

Kucharik C J Serbin S P Vavrus S Hopkins E J amp MotewM M (2010) Patterns of climate change across Wisconsinfrom 1950 to 2006 Physical Geography 31 1ndash28 httpsdoiorg1027470272‐36463111

LaliberteacuteEampTylianakisJM(2010)Deforestationhomogenizestrop‐ical parasitoidndashhost networks Ecology 91 1740ndash1747 httpsdoiorg10189009‐13281

LegendrePampDeCaacuteceresM(2013)BetadiversityasthevarianceofcommunitydataDissimilaritycoefficientsandpartitioningEcology Letters16951ndash963httpsdoiorg101111ele12141

LegendrePampLegendreLF(2012)Numerical ecologyAmsterdamTheNetherlandsElsevier

LiDampWallerDM(2015)DriversofobservedbiotichomogenizationinpinebarrensofcentralWisconsinEcology961030ndash1041httpsdoiorg10189014‐08931

LiDampWallerDM (2016)Long‐termshifts inthepatternsandun‐derlyingprocessesofplantassociationsinWisconsinforestsGlobal Ecology and Biogeography 25 516ndash526 httpsdoiorg101111geb12432

LiDampWallerDM(2017)Fireexclusionandclimatechangeinteracttoaffect long‐termchanges in the functional compositionofplantcommunitiesDiversity and Distributions 23 496ndash506 httpsdoiorg101111ddi12542

LoreauMMouquetNampGonzalezA(2003)Biodiversityasspatialinsurance inheterogeneous landscapesProceedings of the National Academy of Sciences of the USA 100 12765ndash12770 httpsdoiorg101073pnas2235465100

MacLeod M Genung M A Ascher J S amp Winfree R (2016)Measuring partner choice in plantndashpollinator networks Using nullmodels to separate rewiring and fidelity from chanceEcology972925ndash2931httpsdoiorg101002ecy1574

McCannK(2007)ProtectingbiostructureNature44629ndash29httpsdoiorg101038446029a

McKinneyMLampLockwoodJL(1999)BiotichomogenizationAfewwinners replacingmany losers in the nextmass extinctionTrends in Ecology and Evolution 14 450ndash453 httpsdoiorg101016S0169‐5347(99)01679‐1

Milazzo M Mirto S Domenici P amp Gristina M (2013) Climatechange exacerbates interspecific interactions in sympatriccoastal fishes Journal of Animal Ecology 82 468ndash477 httpsdoiorg101111j1365‐2656201202034x

MokrossKRyderTBCocircrtesMCWolfe JDampStoufferPC(2014) Decay of interspecific avian flock networks along a dis‐turbance gradient in Amazonia Proceedings of the Royal Society B Biological Sciences28120132599

Morales‐Castilla IMatiasM G Gravel D amp ArauacutejoM B (2015)Inferring biotic interactions from proxies Trends in Ecology and Evolution30347ndash356httpsdoiorg101016jtree201503014

OksanenJBlanchetFGFriendlyMKindtRLegendrePMcGlinnDhellipWagnerH(2018)Vegan Community ecology packageRpack‐ageversion25‐2httpsCRANR‐projectorgpackage=vegan

OldenJDComteLampGiamX(2018)TheHomogoceneAresearchprospectusforthestudyofbiotichomogenisationNeoBiota3723httpsdoiorg103897neobiota3722552

OldenJDampPoffNL (2003)Towardamechanisticunderstandingand prediction of biotic homogenization The American Naturalist162442ndash460httpsdoiorg101086378212

OldenJDPoffNLDouglasMRDouglasMEampFauschKD(2004)Ecologicalandevolutionaryconsequencesofbiotichomog‐enization Trends in Ecology and Evolution 19 18ndash24 httpsdoiorg101016jtree200309010

PetanidouTKallimanisASTzanopoulosJSgardelisSPampPantisJD(2008)Long‐termobservationofapollinationnetworkFluctuationinspeciesandinteractionsrelativeinvarianceofnetworkstructureand implicationsforestimatesofspecializationEcology Letters11564ndash575httpsdoiorg101111j1461‐0248200801170x

emspensp emsp | emsp11Li et aL

Poisot T Gueacuteveneux‐Julien C FortinM‐J Gravel D amp LegendreP (2017)Hostsparasitesandtheir interactionsrespondtodiffer‐entclimaticvariablesGlobal Ecology and Biogeography26942ndash951httpsdoiorg101111geb12602

PoisotTStoufferDBampGravelD(2015)BeyondspeciesWhyeco‐logicalinteractionnetworksvarythroughspaceandtimeOikos124243ndash251httpsdoiorg101111oik01719

RCoreTeam(2017)R A language and environment for statistical comput-ingViennaAustriaRFoundationforStatisticalComputing

RockwellRFGormezanoLJampKoonsDN(2011)TrophicmatchesandmismatchesCanpolarbearsreducetheabundanceofnestingsnowgeese inwesternHudsonBayOikos120696ndash709httpsdoiorg101111j1600‐0706201018837x

RogersDARooneyTPOlsonDampWallerDM(2008)ShiftsinsouthernWisconsin forest canopy and understory richness com‐position and heterogeneity Ecology 89 2482ndash2492 httpsdoiorg10189007‐11291

RooneyTPWiegmannSMRogersDAampWallerDM (2004)BioticimpoverishmentandhomogenizationinunfragmentedforestunderstorycommunitiesConservation Biology18787ndash798httpsdoiorg101111j1523‐1739200400515x

SalaOEChapinFSArmestoJJBerlowEBloomfieldJDirzoRhellipLeemansR(2000)Globalbiodiversityscenariosfortheyear2100 Science2871770ndash1774

TullochAIChadegravesIampLindenmayerDB(2018)Speciesco‐occur‐renceanalysispredictsmanagementoutcomesformultiplethreatsNature Ecology amp Evolution 2 465ndash474 httpsdoiorg101038s41559‐017‐0457‐3

Tylianakis J M Didham R K Bascompte J amp Wardle D A(2008) Global change and species interactions in terres‐trial ecosystems Ecology Letters 11 1351ndash1363 httpsdoiorg101111j1461‐0248200801250x

Tylianakis J M amp Morris R J (2017) Ecological networksacross environmental gradients Annual Review of Ecology

Evolution and Systematics 48 25ndash48 httpsdoiorg101146annurev‐ecolsys‐110316‐022821

Tylianakis JM Tscharntke Tamp LewisO T (2007)Habitatmodifi‐cation alters the structure of tropical hostndashparasitoid food websNature445202ndash205httpsdoiorg101038nature05429

Valiente‐BanuetAAizenMAAlcaacutentaraJMArroyoJCocucciAGalettiMhellipJordanoP(2015)BeyondspecieslossTheextinctionofecologicalinteractionsinachangingworldFunctional Ecology29299ndash307httpsdoiorg1011111365‐243512356

Vitousek PMMooneyHA Lubchenco JampMelillo JM (1997)Human domination of earthrsquos ecosystems Science 277 494ndash499httpsdoiorg101126science2775325494

Waller DM Amatangelo K L Johnson S amp Rogers D A (2012)Wisconsinvegetationdatabasendashplantcommunitysurveyandresur‐veydatafromtheWisconsinplantecologylaboratoryBiodiversity amp Ecology4255ndash264httpsdoiorg107809b‐e00082

SUPPORTING INFORMATION

Additional supporting information may be found online in theSupportingInformationsectionattheendofthearticle

How to cite this articleLiDPoisotTWallerDMBaiserBHomogenizationofspeciescompositionandspeciesassociationnetworksaredecoupledGlobal Ecol Biogeogr 2018001ndash11 httpsdoiorg101111geb12825

Page 4: Homogenization of species composition and species ... · L I ET A L. | 3 biotic homogenization in species composition (Li & Waller, 2015; Rogers, Rooney, Olson, & Waller, 2008; Rooney

4emsp |emsp emspensp Li et aL

nulldistributionfromthe5000randomizationsThiswasthenusedtojudgewhethertheobservedC‐scorereflectshigherorlowerco‐occurrence thanexpectedbychanceFormoredetails seeLiandWaller(2016)

A recent study concluded that this null model approach hasrelatively lowpowerto infer truespecies interactions fromco‐oc‐currence patterns and suggested using Markov networks instead(Harris 2016) Unfortunately current implementations ofMarkovnetworks are restricted to le20 species (Harris 2016) precludingtheir use with our dataset A second method with power similartoMarkov networks but extending to includemanymore speciesisgeneralizedlinearmodels(GLMsHarris2016)Weadoptedthisapproachandusedgeneralizedlinearmixedmodels(GLMMs)toac‐countforthehierarchicalstructureofourdatasetIntheseGLMMswefittedBayesianregularized logisticregressiontothepresenceabsenceofeachspecies (response)usingthepresenceabsenceofother speciesaspredictorsandsite identityas randomtermThismethod generates two regression coefficients and p‐values foreach species pairWe averaged these to estimate the strengthofspecies interactions (cfHarris2016)These twomethodsyieldedqualitativelysimilar resultsWetherefore reportonly results fromGLMMsinthemaintextbecausetheseoftenhadhigherstatisticalpowerForresultsfromtheC‐scorenullmodelseetheSupportingInformationAppendix

Withthelistofpositiveandnegativeassociationspeciespairswebuiltonepositiveassociationmetawebandonenegativeassoci‐ationmetawebforeachvegetationtypeandtimeperiodPositivenegativeassociationindicatesthatapairofspeciesco‐occurmorelessthanexpectedbychance (basedonconstrainednullmodelorGLMMs)Wethenbuiltpositiveandnegativeassociationnetworksforeachsitefromthesetwometawebsbysub‐settingthespeciesobserved at that site This assumes that species relationships be‐tweenspeciesdonotdifferacrosssitesofthesamevegetationtypeandtimeperiodyieldingmoreconservativeresultsToremovethisassumptiononecanalsobuildanassociationnetworkforeachsiteindependentlyHoweverwelackedthepowertodothisgiventhelimitednumberofquadrats(mostly20)persiteThereforetheasso‐ciationnetworksforeachsiteinouranalyseswerederivedfromthemetawebsinsteadofbeingbuiltindependently

24emsp|emspData analysis

241emsp|emspChanges in spatial beta diversity over time

We calculated pairwise beta diversity in both species composi‐tionandspeciesassociationnetworkswithineachvegetationtypeandtimeperiodusingthemethodsproposedbyLegendreandDeCaacuteceres(2013)Forpairwisebetadiversityofspeciescompositiontheinputisasitebyspeciesmatrixwithspeciesabundancesinthecellsforspeciesassociationpairwisebetadiversitytheinputisasitebyspeciespairs(non‐randompairsinferredviamethodsdescribedintheprevioussubsection)matrix Inthiswaywetreateachnon‐randomspeciespairasaldquospeciesrdquointraditionalcommunityecology

analyses(cfPoisotetal2017)Thisapproachallowsusdirectlytocomparepairwisebetadiversityforspeciescompositionwithbetadiversity for species associations because both are calculated thesamewayWecomparedpairwisebetadiversityofeachvegetationtypebetweenthe1950sandthe2000susingpairedrandomizationtestsLower(orhigher)betadiversityinthe2000ssuggestsbiotichomogenization(ordifferentiation)

GiventhenumberofsitesinNUF(108)andSUF(126)wehavealargenumberofpairwisebeta‐diversitymeasures(5778and7875respectively)Suchlargesamplesizesmakeitpossibletoobtainsta‐tisticallysignificantresultsthatmaynotbebiologicallysignificantThereforewe also tested changes in beta diversity for each veg‐etation type using a distance‐basedpermutational test for homo‐geneityofmultivariatedispersion(PERMDISPAndersonEllingsenamp McArdle 2006) This analysis used BrayndashCurtis distancesPERMDISPcalculatesthedistanceofeachsitefromthecentroidoftheordinationspaceandthentestswhetherthesedistancesaredif‐ferentacrossgroups(ie1950svs2000s)withpermutationtestsWealsouseresultsfromPERMDISPtovisualizespeciescompositionandassociationpatternsforeachvegetationtypeandtimeperiod

242emsp|emspWithin‐site changes over time

Tocompareratesofchangeinspeciescompositionandspeciesas‐sociationsovertimewecalculatedbetadiversitybetweenperiodswithineachsite(ieasiteinthe1950sversusthesamesiteinthe2000s)againusingthemethodofLegendreandDeCaacuteceres(2013)We then used a paired t‐test to examinewhether the beta‐diver‐sityvaluesthatreflectchangesinspeciesassociationssignificantlyexceedthosethat reflectchanges inspeciescomposition (ietestwhetherspeciesassociationschangedmorethanspeciescomposi‐tion)Toconfirmtheseresultswealsoappliedpermutationalmul‐tivariate analysis of variance (PERMANOVA Anderson 2001) tocompare changes in species composition and species associationsovertime

243emsp|emspEnvironmental drivers

Tounderstand environmental drivers for species composition andassociation networks we conducted distance‐based redundancyanalysis(RDA)foreachvegetationtypeandtimeperiodWetrans‐formedthespeciescompositionandassociationmatrixintodistancematriceswiththeHellingerindex(LegendreampLegendre2012)WeusedenvironmentalvariablesaspredictorsinRDAsToidentifythemostsignificantenvironmentalvariablesweusedforwardvariableselectionandAkaikeinformationcriterion‐basedstatisticsover999replicaterunsforeachmatrix(cfPoisotetal2017)Theorderofvariableselectionprovides insight intothe importanceofenviron‐mental variables with the earlier selected variables generally af‐fectingspeciescompositionortheassociationsmoreThisanalysisallowed us to studywhether species composition and associationareaffectedbysimilarsetsofenvironmentalvariablesinthesameway and how these relationships changed over time All analyses

emspensp emsp | emsp5Li et aL

were conducted in R v340 (RCore Team 2017)with the pack‐agevegan (Oksanenet al 2018) fornullmodels and thepackageMCMCglmm(Hadfield2010)forBayesianGLMMs

3emsp |emspRESULTS

Acrossallvegetationtypesmost(gt80)speciespairsco‐occurredrandomly at both time periods as inferred from the results usingBayesianGLMMs(Table1)Amongnon‐randomspeciespairsmorespeciespairsco‐occurrednegatively (7ndash95)thanpositively (45ndash67)acrossallvegetationtypesandtimeperiods(Table1)

In theNUF region speciescompositionpositive speciesasso‐ciationsandnegativespeciesassociationsallshowedsimilar levelsof dispersion in both time periods in ordination space (Figure 1SupportingInformationAppendixFigureS2)Thuslittlehomogeni‐zationoccurredThiswasconfirmedbyPERMDISPresults(permuta‐tiontestallpgt025Table2)Howeverpairwisesitebetadiversitycalculated with methods proposed by Legendre and De Caacuteceres(2013)suggestedhomogenizationinspeciescompositionandnega‐tiveassociationsbutdifferentiationinpositiveassociations(pairedrandomizationtestbothplt0001Table2)

In the CSP region both species composition and patterns ofpositive association converge in ordination space in the 2000swhencomparedwith the1950s (Figure1Supporting InformationAppendix Figure S2) This suggests that these sites experiencedhomogenization in both species composition and positive speciesassociationsIncontrastweobservednochangeinnegativeasso‐ciationsResults frompairedrandomizationtestsonpairwisebetadiversityandPERMDISP(Table2)confirmthisinterpretation

Sites intheSUFregionalsoshowedatendencytoconvergeinspecies composition and negative associations between periods(Figure1SupportingInformationAppendixFigureS2)Incontrastpositive associations tended to diverge These results were sup‐portedby theparallel analysesof pairwise sitebetadiversity andPERMDISP(exceptnegativeassociationsTable2)

Forallregionsshiftsinbetadiversityforthespeciesassociationnetworksexceededthoseforspeciescomposition(p=0001withineach site Figure 2) Thus it appears that species association net‐workshavechangedfasterthanspeciescompositionLargeturnover

inspeciesassociations(positiveornegative)mayreflectonlyslightchangesinspeciescomposition

Speciescompositionandspeciesassociationswerelargelyinflu‐encedbythesamesetofenvironmentalvariableswithineachvege‐tationtypeandeachtimeperiod(Table3)Forallsitesinthe1950sspeciescompositionandspeciesassociationnetworkswereaffectedbyalmostthesamesetofenvironmentalvariablesThispatternstillholds in the2000sbut less so for theCSP sitesMore intriguingthe importance of environmental variables on plant communitieshaschangedovertimeForexampleshadewasthemostimportantfortheCSPsitesinthe1950sbutdecreasedinimportancebythe2000s for species composition and positive associationsMinimaltemperaturewasthemostimportantvariablethatstronglyaffectedspeciescompositionandpositiveassociationsoftheSUFsitesinthe1950sbutbecamelessimportantbythe2000swhereasprecipita‐tiongainedimportance

4emsp |emspDISCUSSION

Few studies have quantified changes in both species compositionand species relationship networks over time (Burkle Myers ampBelote2016)Ittakesconsiderableefforttoconstructasingleinter‐actionnetworkletalonenetworksatmultiplesitesovertwoormoretimeperiodsWefoundonlytwoempiricalstudiesonhomogeniza‐tion of ecological networks Laliberteacute and Tylianakis (2010) foundthatdeforestationhomogenizedparasitoidndashhostnetworksintropi‐calareasAlthoughtheyhadtemporaldataofparasitoidndashhostnet‐works(monthlysamplesfor17months)theirmainconclusionwasderivedfromspatialcomparisonsamongdifferentland‐usecatego‐riesKehindeandSamways(2014)examinedbiotichomogenizationofinsectndashflowerinteractionsinvineyardsmanagedunderagri‐envi‐ronmentalschemesintheCapeFloristicRegionTheyfoundnoevi‐denceofhomogenizationforinteractionnetworkswhencomparingvineyardswithnaturalsites

Ourstudymaythusbethefirsttoexploretemporalchangesinbeta diversity of species relationship networks Using patterns ofspecies co‐occurrence to indicate species relationships and usingavaluablehigh‐resolution long‐termdatasetwewereabletoex‐amineparallelchangesinbothcommunitycompositionandspecies

TA B L E 1 emspSummaryofspeciesusedandspeciesassociationsforeachvegetationtypeandtimeperiod

Type DateSpeciesused(n)

Pairs(negativeassociation)[n()]

Pairs(positiveassociation)[n()]

Pairs(random)[n()] Totalpairs

NUF 1950s 146 741(7) 513(48) 9331(882) 10585

NUF 2000s 160 1120(88) 626(49) 10974(863) 12720

CSP 1950s 61 162(89) 104(57) 1564(855) 1830

CSP 2000s 55 125(84) 100(67) 1260(848) 1485

SUF 1950s 225 2001(79) 1127(45) 22072(876) 25200

SUF 2000s 186 1635(95) 857(5) 14713(855) 17205

AbbreviationsCSPcentralsandplainsNUFnorthernuplandforestsSUFsouthernuplandforests

6emsp |emsp emspensp Li et aL

associationnetworksWefoundthatspeciesassociationnetworkscanhomogenizedifferentiateor shownochange through time indifferentvegetationtypesregardlessofthehomogenizationdynam‐icsofspeciescompositionLong‐termchangesinspeciescomposi‐tionandspeciesassociationsthusappeartobedecoupled

IntheNUFofWisconsinplantcommunitieswererelativelysta‐ble intermsoftheirspeciescompositionandspeciesassociationsComparedwith other community types NUF has a lower humanpopulation less land‐use change and less habitat fragmentationInthepresentstudywefoundnooverallchangesinbetadiversityof speciescompositionandspeciesassociationswhen testedwithPERMDISPHoweverpairedrandomizationtestsonbetadiversitybetweensitepairssuggestedsignificanthomogenizationinspeciescomposition matching the conclusion (biotic impoverishment andhomogenization)reachedinapreviousstudyofasubsetofthesesites(Rooneyetal2004)Herewealsoobservedhomogenizationinthe

among‐sitediversityofnegativespeciesassociationsbutsignificantdifferentiationinpositivespeciesassociationsGiventhelargenum‐berofsites inNUF(108) theresultsofrandomizationtestsmightnotbebiologicallysignificantdespitetheirstatisticalsignificancesTheseresultssuggest thatshifts inspeciescompositionmightnotoccurinthesamedirectionasshiftsinspeciesrelationships

Plantcommunities in theCSPhistoricallywerefire‐maintainedpinebarrenswithopencanopiesHowevertheyaresucceedingintoclose‐canopyuplandforestsbecauseoffiresuppression(LiampWaller2015)Firesuppressionhasresultedinhomogenizationinbothspe‐ciescomposition(LiampWaller2015)andfunctionaltraitcomposition(LiampWaller2017)Thisprobablyreflectsdeclinesinhabitathetero‐geneitywithinthesecommunitiesInthe1950ssitesintheCSPhaddifferentcanopycoverageformingmosaicsofburnedandunburnedhabitatstosupportdifferentplantcommunitiesInthe2000show‐ever siteswere similar toeachother in their canopycoverowing

F I G U R E 1 emspDistancetothecentroidofordinationsofspeciescompositionandassociationsIncreasesinthedistancetothecentroidovertimeindicatedifferentiation(diff)Decreasesinthedistancetothecentroidovertimeindicatehomogenization(homog)p lt 005 plt001p lt 0001

no change

homog

homog

no change

homog

diff

no change

no change

no change

Species Composition Positive Associations Negative Associations

NU

FC

SPSU

F

1950s 2000s 1950s 2000s 1950s 2000s

02

04

06

08

02

04

06

08

02

04

06

08

Dis

tanc

e to

Cen

troid

emspensp emsp | emsp7Li et aL

to fire suppression and succession filtering out shade‐intolerantspecies(LiampWaller2017)andhomogenizingplantcommunities(LiampWaller2015)Giventheseecologicalchangesitisnotsurprisingtofindsignificanthomogenizationinbothspeciescompositionandpositivespeciesassociationsinthesecommunities

SitesintheSUFhavebeenaffectedbydevelopmentandland‐use changes more than any other plant community inWisconsin(Rogersetal2008)Currentlymostofthesesitesarefragmentedanddisturbedbynearbyanthropogenic activities including roadsdevelopmentandagriculturePreviousstudiessuggestthathabitatdegradationandfragmentationtendtohomogenizespeciescompo‐sitionbydecreasingspeciesdiversitywhichcanalsoreducenetworkcomplexityandstability(LaliberteacuteampTylianakis2010Mokrossetal2014Tylianakisetal2007)However the fact thathabitat frag‐mentationcan result ingreaterdifferences in interactionnetworkstructure(Bordesetal2015)suggeststhatnetworksimplification(fewer nodes andor edges) does not necessarily cause networkhomogenizationNetworkscandifferacrosssites if individualnet‐workscontainuniqueinteractionseveniftheyshowageneraltrendtowards simplification In theseSUFcommunities the importanceofspeciesdispersallimitationandstochasticfactorshasincreasedwhereastheimportanceofspeciesinteractionshasdecreasedovertime(LiampWaller2016)Itisthuslikelythatstochasticassemblypro‐cesses are formingnovel sets of interactions among species eventhoughspeciesdiversityhasdecreasedIndeedwefoundonaver‐age964significantpositivespeciespairspersiteinthe1950sbutonly603significantpositivepairspersiteinthe2000sindicatingthatassociationnetworksateachsitehavesimplifiedHoweverboththepairedrandomizationtestonpairwisebetadiversityofpositiveassociationnetworksandPERMDISPsuggestedthatpositiveasso‐ciationnetworks inthe2000shavedifferentiatedsincethe1950s(Table2)ThereforeintheSUFwefoundhomogenizationofspeciescompositionbutdifferentiationofspeciespositiveassociations

Although changes in species associations are occurring fasterthan changes in species composition and appear decoupled fromthembotharegenerallyaffectedbysimilarsetsofenvironmentalvariables (Table 3) For example positive species associations andcomposition at all siteswithin each time periodwere affected bythesamesetofenvironmentalvariablesHowevertheimportanceofenvironmentalvariablesforspeciesassociationsandcompositionhaschangedovertimefortheCSPandSUFSpeciesassociationsandcompositionintheCSPweremostaffectedbycanopyshadeinthe1950swithclimaticfactorsplayingnoroleforpositiveassociationsandspeciescompositionBy the2000sclimaticvariablesbecamemoreimportantthancanopyshadeThisreflectsthefactthatCSPforestswith closed canopies show little variation in canopy coverinthe2000sIntheSUFminimaltemperatureusedtobemoreim‐portantthanprecipitationforspeciescompositionandpositiveas‐sociationsthispatternreversedinthe2000sTheseresultssuggestthatspeciesassociationsandcompositionaregenerallyaffectedbya similar set of environmental variables As global environmentalchangesacceleratetherelative importanceofenvironmentalvari‐ablesmaychange further contributing to theemergenceofnovelTA

BLE

2emspHomogenizationinspeciescompositiondoesnotalwaysresultinthehomogenizationofspeciesassociationnetworks

Ave_1950(pairwise)

Ave_2000(pairwise)

Ave_1950(permdisp)

Ave_2000(permdisp)

Direction(pairwise)

Direction(permdisp)

NUF

SpeComp

059

50587

051

30

51homog

nochange

PosAssoc

0778

0785

0561

0566

diff

nochange

NegAssoc

089

10887

0636

0633

homog

nochange

CSP

SpeComp

0447

029

90418

0327

homog

homog

PosAssoc

0683

0442

0496

0314

homog

homog

NegAssoc

080

50806

0574

0575

nochange

nochange

SUF

SpeComp

0572

0546

0516

0497

homog

homog

PosAssoc

0736

0782

0527

0567

diff

diff

NegAssoc

0862

0841

0615

0603

homog

nochange

Not

eNumbersintheave_1950(pairwise)andave_2000(pairwise)columnsrepresentaveragepairwisebetadiversitybetweensiteswithinthesamevegetationtypeinthe1950sandthe2000srespec‐

tivelyNumbersintheave_1950(permdisp)andave_2000(permdisp)columnsrepresenttheaveragedistancetothegroupcentroidintheordinationsofsiteswithinthesamevegetationtypeinthe1950s

andthe2000srespectivelyThecolumndirection(pairwise)indicatesdirectionsofchangesinthepairwisesitebetadiversityovertimetestedwithpairedrandomizationtestsThecolumndirection

(permdisp)indicatesdirectionsofchangesinthedistancebetweensitesandtheordinationcentroidovertimetestedwithpermutationtestsAbbreviationsdiffdifferentiationhomoghomogenization

NegAssocnegativeassociationPosAssocpositiveassociationSpeCompspeciescompositionplt005plt001

p lt

000

1

8emsp |emsp emspensp Li et aL

Vegetationtype Date Variable Shade Precipitation Minimaltemperature

NUF 1950s SpeComp ndash 2 1

PosAssoc ndash 2 1

NegAssoc ndash 2 1

2000s SpeComp ndash 2 1

PosAssoc ndash 2 1

NegAssoc ndash 2 1

CSP 1950s SpeComp 1

PosAssoc 1

NegAssoc 1 2

2000s SpeComp 2 1

PosAssoc 3 1 2

NegAssoc 2 1

SUF 1950s SpeComp ndash 2 1

PosAssoc ndash 2 1

NegAssoc ndash 1 2

2000s SpeComp ndash 1 2

PosAssoc ndash 1 2

NegAssoc ndash 1 2

NoteNumbersaretheorderinwhichvariablesareselectedDash(ndash)meansthattheenvironmentalvariableisnotavailableBlankcellsmeanthatthesevariablesaredroppedoutAbbreviationsNegAssocnegativeassociationPosAssocpositiveassociationSpeCompspeciescomposition

TA B L E 3 emspSelectedenvironmentalvariablesforspeciescompositionandspeciesassociations

F I G U R E 2 emspBetadiversityofspeciescompositionandassociationofthesamesiteovertimeEachpointrepresentsthebetadiversityofthesamesitebetweenthe1950sandthe2000sBetadiversityofoneindicatesthatthespeciescompositionorspeciesassociationinthe1950sandthe2000sweretotallydifferentwhereasbetadiversityofzeroindicatesnochangesinasiteovertimeTurnoverinspeciesrelationshipsappearstobemuchgreaterthantheturnoverinspeciescomposition

NU

FC

SPSU

F

Species Composition Positive Association Negative Association

025

050

075

100

025

050

075

100

025

050

075

100

Beta

div

ersi

ty o

ver t

ime

at th

e sa

me

site

emspensp emsp | emsp9Li et aL

arraysofspeciesandconsequentspecies interactions (Bloisetal2013Milazzoetal2013)

Species association (co‐occurrence) patterns have commonlybeenusedtorepresentspeciesinteractionsbecauseitisintractabletoquantifyinteractionsamonghundredsofplantspeciesSpeciesassociations may give false‐positive (hypothesized links that donotexistintherealsystem)interactionsbetweenspeciesandmaynot detect all real interactions (Barner et al 2018DelalandreampMontesinos‐Navarro2018Freilichetal2018)Howeverourmaingoalistostudybroadpatternsofcommunitystructureanddynam‐ics rather than to pinpoint exact interactions between particularspeciespairsForthispurposespeciesspatialassociationnetworksareanecessaryandusefulproxy(Freilichetal2018)becausetheycanprovidevaluableinformationregardingthenetoutputofdirectandindirecteffectsamongmultipleplantspecies(ratherthanexactpairwise interactions Delalandre amp Montesinos‐Navarro 2018)Co‐occurrence networks may also serve to predict overall com‐munityresponsestodisturbance(TullochChadegravesampLindenmayer2018) To reduce thepotential for biaswe studied species asso‐ciation patterns at a fine spatial scale (1m2) and used statisticalmethods(BayesianGLMMs)thathaverelativelyhighpowerforde‐tecting species interactions (Harris 2016) Furthermoreweusedacommonnullmodelapproachand reported these results in theSupporting InformationAppendixGiven that bothmethods pro‐videquantitatively similar results and reach the sameconclusionour conclusion that changes in species associations and speciescompositionaredecoupledislikelytoberobustConsequentlyourresultsfromspeciesassociationnetworksmayalsoholdforspeciesinteractionnetworks

Anassumptionmadeinthisstudyisthatspeciesassociationswithin each vegetation type and timeperiod remain consistentacross sites In reality associations between species can varythroughspaceandtime(Poisotetal2015)Giventhatwelackedthedatatoanalysehowspeciesassociationsmayhavedifferedover siteswepooleddataacross sites togain insights into theaverage nature of species associationswithin each communityThismakesourresultsconservativebecauseaccountingforvari‐ation inspeciesassociationsoversitescouldshowonlygreatervariationinnetworkstructurestrengtheningourconclusionthattemporal changes in species associations and composition aredecoupled

Our results suggest that species relationshipsmay not be ex‐periencingageneraltrendtowardshomogenizationbecausenovelrelationships may be forming in response to rapid global changeThisraisesimportantquestionsabouthowsuchchangesinspeciesrelationshipsmightaffectcommunitystabilityecosystemservicesandspeciesco‐evolutionStudiesofbetadiversity inspecies rela‐tionshipsremainintheirinfancy(Burkleetal2016)Giventheim‐portanceofspeciesrelationshipsandtheirpotentialunpredictablerelationshipwithspeciescompositionfutureempiricalandtheoret‐icalresearchthatinvestigatespatternscausesandconsequencesofchangesinbetadiversityofrelationshipnetworksareneeded

5emsp |emspBIOSKETCH

Daijiang Liisapost‐doctoralresearcherattheDepartmentofWildlifeEcologyampConservationUniversityofFloridaHisresearchinterestscovercommunityecologyfunctionalandphylogeneticdiversitybi‐ologicalinvasionsglobalchangebiologyandecologicalmodelling

DATA ACCE SSIBILIT Y

The data used in this study have been deposited to figshare(httpsfigsharecoms5a98a69a66f22644361e) with httpsdoiorg106084m9figshare6771938

ORCID

Daijiang Li httporcidorg0000‐0002‐0925‐3421

Timotheacutee Poisot httporcidorg0000‐0002‐0735‐5184

Benjamin Baiser httporcidorg0000‐0002‐3573‐1183

R E FE R E N C E S

AmatangeloKLFultonMRRogersDAampWallerDM (2011)Convergingforestcommunitycompositionalonganedaphicgradi‐ent threatens landscape‐level diversityDiversity and Distributions17201ndash213httpsdoiorg101111j1472‐4642201000730x

AndersonMJ(2001)Anewmethodfornon‐parametricmultivariateanalysisofvarianceAustral Ecology2632ndash46

AndersonMJEllingsenKEampMcArdleBH (2006)MultivariatedispersionasameasureofbetadiversityEcology Letters9683ndash693httpsdoiorg101111j1461‐0248200600926x

Arauacutejo M B Rozenfeld A Rahbek C amp Marquet P A (2011)Using species co‐occurrence networks to assess the im‐pacts of climate change Ecography 34 897ndash908 httpsdoiorg101111j1600‐0587201106919x

AshJDGivnishTJampWallerDM(2017)Trackinglagsinhistori‐calplantspeciesrsquoshiftsinrelationtoregionalclimatechangeGlobal Change Biology231305ndash1315httpsdoiorg101111gcb13429

BaiserBOlden JDRecordSLockwoodJLampMcKinneyML(2012) Pattern and process of biotic homogenization in the newPangaeaProceedings of the Royal Society B Biological Sciences2794772ndash4777

Barner A K Coblentz K E Hacker S D amp Menge B A (2018)Fundamentalcontradictionsamongobservationalandexperimentalestimatesofnon‐trophicspeciesinteractionsEcology99557ndash566httpsdoiorg101002ecy2133

Bascompte J JordanoPampOlesen JM (2006)Asymmetriccoevo‐lutionarynetworksfacilitatebiodiversitymaintenanceScience312431ndash433httpsdoiorg101126science1123412

Blois J L Zarnetske P L FitzpatrickM C amp Finnegan S (2013)ClimatechangeandthepastpresentandfutureofbioticinteractionsScience341499ndash504httpsdoiorg101126science1237184

BordesFMorandSPilosofSClaudeJKrasnovBRCossonJ‐Fhellip Blasdell K (2015) Habitat fragmentation alters the propertiesofahostndashparasitenetworkRodentsand theirhelminths inSouth‐East Asia Journal of Animal Ecology 84 1253ndash1263 httpsdoiorg1011111365‐265612368

BurkleLAMyersJAampBeloteRT (2016)Thebeta‐diversityofspecies interactions Untangling the drivers of geographic vari‐ation in plantndashpollinator diversity and function across scales

10emsp |emsp emspensp Li et aL

American Journal of Botany103118ndash128httpsdoiorg103732ajb1500079

CaraDonna P J Petry W K Brennan R M Cunningham J LBronstein J LWaserNMamp SandersN J (2017) InteractionrewiringandtherapidturnoverofplantndashpollinatornetworksEcology Letters20385ndash394httpsdoiorg101111ele12740

CazellesKArauacutejoMBMouquetNampGravelD(2016)Atheoryforspeciesco‐occurrenceininteractionnetworksTheoretical Ecology939ndash48httpsdoiorg101007s12080‐015‐0281‐9

ConnorEFampSimberloffD(1979)Theassemblyofspeciescommu‐nitiesChanceorcompetitionEcology601132ndash1140httpsdoiorg1023071936961

CummingGSBodinOumlErnstsonHampElmqvistT(2010)Networkanalysis in conservation biogeography Challenges and oppor‐tunities Diversity and Distributions 16 414ndash425 httpsdoiorg101111j1472‐4642201000651x

CurtisJT(1959)The vegetation of Wisconsin An ordination of plant com-munitiesMadisonWIUniversityofWisconsinPress

de Solar R R C Barlow J Ferreira J Berenguer E Lees A CThompsonJRhellipGardnerTA(2015)Howpervasiveisbioticho‐mogenizationinhuman‐modifiedtropicalforestlandscapesEcology Letters181108ndash1118httpsdoiorg101111ele12494

DelalandreLampMontesinos‐NavarroA(2018)Canco‐occurrencenet‐works predict plant‐plant interactions in a semi‐arid gypsum com‐munityPerspectives in Plant Ecology Evolution and Systematics3136ndash43httpsdoiorg101016jppees201801001

Diamond JM (1975) Assembly of species communitiesEcology and Evolution of Communities342ndash444

FreilichMAWietersEBroitmanBMarquetPAampNavarreteSA(2018)Speciesco‐occurrencenetworksCantheyrevealtrophicandnon‐trophicinteractionsinecologicalcommunitiesEcology99690ndash699httpsdoiorg101002ecy2142

Gotelli N J (2000) Null model analysis of species co‐oc‐currence patterns Ecology 81 2606ndash2621 httpsdoiorg1018900012‐9658(2000)081[2606NMAOSC]20CO2

GotelliNJampGravesGR(1996)Null models in ecologyWashingtonDCSmithsonianInstitution

GotelliN JGravesGRampRahbekC (2010)Macroecological sig‐nalsofspeciesinteractionsintheDanishavifaunaProceedings of the National Academy of Sciences of the USA1075030ndash5035httpsdoiorg101073pnas0914089107

Hadfield JD (2010)MCMCmethods formulti‐responsegeneralizedlinearmixedmodelsTheMCMCglmmRpackageJournal of Statistical Software331ndash22

Harley C D (2011) Climate change keystone predation and biodi‐versity loss Science 334 1124ndash1127 httpsdoiorg101126science1210199

Harris D J (2016) Inferring species interactions from co‐occurrencedata with Markov networks Ecology 97 3308ndash3314 httpsdoiorg101002ecy1605

Harvey E Gounand I Ward C L amp Altermatt F (2017) Bridgingecology and conservation From ecological networks to ecosys‐tem function Journal of Applied Ecology 54 371ndash379 httpsdoiorg1011111365‐266412769

Hegland S J Nielsen A Laacutezaro A Bjerknes A‐L amp TotlandOslash (2009) How does climate warming affect plant‐pollina‐tor interactions Ecology Letters 12 184ndash195 httpsdoiorg101111j1461‐0248200801269x

Hobbs R J Higgs E amp Harris J A (2009) Novel ecosystemsImplicationsforconservationandrestorationTrends in Ecology and Evolution24599ndash605httpsdoiorg101016jtree200905012

Kehinde T amp Samways M J (2014) Effects of vineyard manage‐ment on biotic homogenization of insectndashflower interaction net‐works in the cape floristic region biodiversity hotspot Journal of Insect Conservation 18 469ndash477 httpsdoiorg101007s10841‐014‐9659‐z

Kucharik C J Serbin S P Vavrus S Hopkins E J amp MotewM M (2010) Patterns of climate change across Wisconsinfrom 1950 to 2006 Physical Geography 31 1ndash28 httpsdoiorg1027470272‐36463111

LaliberteacuteEampTylianakisJM(2010)Deforestationhomogenizestrop‐ical parasitoidndashhost networks Ecology 91 1740ndash1747 httpsdoiorg10189009‐13281

LegendrePampDeCaacuteceresM(2013)BetadiversityasthevarianceofcommunitydataDissimilaritycoefficientsandpartitioningEcology Letters16951ndash963httpsdoiorg101111ele12141

LegendrePampLegendreLF(2012)Numerical ecologyAmsterdamTheNetherlandsElsevier

LiDampWallerDM(2015)DriversofobservedbiotichomogenizationinpinebarrensofcentralWisconsinEcology961030ndash1041httpsdoiorg10189014‐08931

LiDampWallerDM (2016)Long‐termshifts inthepatternsandun‐derlyingprocessesofplantassociationsinWisconsinforestsGlobal Ecology and Biogeography 25 516ndash526 httpsdoiorg101111geb12432

LiDampWallerDM(2017)Fireexclusionandclimatechangeinteracttoaffect long‐termchanges in the functional compositionofplantcommunitiesDiversity and Distributions 23 496ndash506 httpsdoiorg101111ddi12542

LoreauMMouquetNampGonzalezA(2003)Biodiversityasspatialinsurance inheterogeneous landscapesProceedings of the National Academy of Sciences of the USA 100 12765ndash12770 httpsdoiorg101073pnas2235465100

MacLeod M Genung M A Ascher J S amp Winfree R (2016)Measuring partner choice in plantndashpollinator networks Using nullmodels to separate rewiring and fidelity from chanceEcology972925ndash2931httpsdoiorg101002ecy1574

McCannK(2007)ProtectingbiostructureNature44629ndash29httpsdoiorg101038446029a

McKinneyMLampLockwoodJL(1999)BiotichomogenizationAfewwinners replacingmany losers in the nextmass extinctionTrends in Ecology and Evolution 14 450ndash453 httpsdoiorg101016S0169‐5347(99)01679‐1

Milazzo M Mirto S Domenici P amp Gristina M (2013) Climatechange exacerbates interspecific interactions in sympatriccoastal fishes Journal of Animal Ecology 82 468ndash477 httpsdoiorg101111j1365‐2656201202034x

MokrossKRyderTBCocircrtesMCWolfe JDampStoufferPC(2014) Decay of interspecific avian flock networks along a dis‐turbance gradient in Amazonia Proceedings of the Royal Society B Biological Sciences28120132599

Morales‐Castilla IMatiasM G Gravel D amp ArauacutejoM B (2015)Inferring biotic interactions from proxies Trends in Ecology and Evolution30347ndash356httpsdoiorg101016jtree201503014

OksanenJBlanchetFGFriendlyMKindtRLegendrePMcGlinnDhellipWagnerH(2018)Vegan Community ecology packageRpack‐ageversion25‐2httpsCRANR‐projectorgpackage=vegan

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OldenJDampPoffNL (2003)Towardamechanisticunderstandingand prediction of biotic homogenization The American Naturalist162442ndash460httpsdoiorg101086378212

OldenJDPoffNLDouglasMRDouglasMEampFauschKD(2004)Ecologicalandevolutionaryconsequencesofbiotichomog‐enization Trends in Ecology and Evolution 19 18ndash24 httpsdoiorg101016jtree200309010

PetanidouTKallimanisASTzanopoulosJSgardelisSPampPantisJD(2008)Long‐termobservationofapollinationnetworkFluctuationinspeciesandinteractionsrelativeinvarianceofnetworkstructureand implicationsforestimatesofspecializationEcology Letters11564ndash575httpsdoiorg101111j1461‐0248200801170x

emspensp emsp | emsp11Li et aL

Poisot T Gueacuteveneux‐Julien C FortinM‐J Gravel D amp LegendreP (2017)Hostsparasitesandtheir interactionsrespondtodiffer‐entclimaticvariablesGlobal Ecology and Biogeography26942ndash951httpsdoiorg101111geb12602

PoisotTStoufferDBampGravelD(2015)BeyondspeciesWhyeco‐logicalinteractionnetworksvarythroughspaceandtimeOikos124243ndash251httpsdoiorg101111oik01719

RCoreTeam(2017)R A language and environment for statistical comput-ingViennaAustriaRFoundationforStatisticalComputing

RockwellRFGormezanoLJampKoonsDN(2011)TrophicmatchesandmismatchesCanpolarbearsreducetheabundanceofnestingsnowgeese inwesternHudsonBayOikos120696ndash709httpsdoiorg101111j1600‐0706201018837x

RogersDARooneyTPOlsonDampWallerDM(2008)ShiftsinsouthernWisconsin forest canopy and understory richness com‐position and heterogeneity Ecology 89 2482ndash2492 httpsdoiorg10189007‐11291

RooneyTPWiegmannSMRogersDAampWallerDM (2004)BioticimpoverishmentandhomogenizationinunfragmentedforestunderstorycommunitiesConservation Biology18787ndash798httpsdoiorg101111j1523‐1739200400515x

SalaOEChapinFSArmestoJJBerlowEBloomfieldJDirzoRhellipLeemansR(2000)Globalbiodiversityscenariosfortheyear2100 Science2871770ndash1774

TullochAIChadegravesIampLindenmayerDB(2018)Speciesco‐occur‐renceanalysispredictsmanagementoutcomesformultiplethreatsNature Ecology amp Evolution 2 465ndash474 httpsdoiorg101038s41559‐017‐0457‐3

Tylianakis J M Didham R K Bascompte J amp Wardle D A(2008) Global change and species interactions in terres‐trial ecosystems Ecology Letters 11 1351ndash1363 httpsdoiorg101111j1461‐0248200801250x

Tylianakis J M amp Morris R J (2017) Ecological networksacross environmental gradients Annual Review of Ecology

Evolution and Systematics 48 25ndash48 httpsdoiorg101146annurev‐ecolsys‐110316‐022821

Tylianakis JM Tscharntke Tamp LewisO T (2007)Habitatmodifi‐cation alters the structure of tropical hostndashparasitoid food websNature445202ndash205httpsdoiorg101038nature05429

Valiente‐BanuetAAizenMAAlcaacutentaraJMArroyoJCocucciAGalettiMhellipJordanoP(2015)BeyondspecieslossTheextinctionofecologicalinteractionsinachangingworldFunctional Ecology29299ndash307httpsdoiorg1011111365‐243512356

Vitousek PMMooneyHA Lubchenco JampMelillo JM (1997)Human domination of earthrsquos ecosystems Science 277 494ndash499httpsdoiorg101126science2775325494

Waller DM Amatangelo K L Johnson S amp Rogers D A (2012)Wisconsinvegetationdatabasendashplantcommunitysurveyandresur‐veydatafromtheWisconsinplantecologylaboratoryBiodiversity amp Ecology4255ndash264httpsdoiorg107809b‐e00082

SUPPORTING INFORMATION

Additional supporting information may be found online in theSupportingInformationsectionattheendofthearticle

How to cite this articleLiDPoisotTWallerDMBaiserBHomogenizationofspeciescompositionandspeciesassociationnetworksaredecoupledGlobal Ecol Biogeogr 2018001ndash11 httpsdoiorg101111geb12825

Page 5: Homogenization of species composition and species ... · L I ET A L. | 3 biotic homogenization in species composition (Li & Waller, 2015; Rogers, Rooney, Olson, & Waller, 2008; Rooney

emspensp emsp | emsp5Li et aL

were conducted in R v340 (RCore Team 2017)with the pack‐agevegan (Oksanenet al 2018) fornullmodels and thepackageMCMCglmm(Hadfield2010)forBayesianGLMMs

3emsp |emspRESULTS

Acrossallvegetationtypesmost(gt80)speciespairsco‐occurredrandomly at both time periods as inferred from the results usingBayesianGLMMs(Table1)Amongnon‐randomspeciespairsmorespeciespairsco‐occurrednegatively (7ndash95)thanpositively (45ndash67)acrossallvegetationtypesandtimeperiods(Table1)

In theNUF region speciescompositionpositive speciesasso‐ciationsandnegativespeciesassociationsallshowedsimilar levelsof dispersion in both time periods in ordination space (Figure 1SupportingInformationAppendixFigureS2)Thuslittlehomogeni‐zationoccurredThiswasconfirmedbyPERMDISPresults(permuta‐tiontestallpgt025Table2)Howeverpairwisesitebetadiversitycalculated with methods proposed by Legendre and De Caacuteceres(2013)suggestedhomogenizationinspeciescompositionandnega‐tiveassociationsbutdifferentiationinpositiveassociations(pairedrandomizationtestbothplt0001Table2)

In the CSP region both species composition and patterns ofpositive association converge in ordination space in the 2000swhencomparedwith the1950s (Figure1Supporting InformationAppendix Figure S2) This suggests that these sites experiencedhomogenization in both species composition and positive speciesassociationsIncontrastweobservednochangeinnegativeasso‐ciationsResults frompairedrandomizationtestsonpairwisebetadiversityandPERMDISP(Table2)confirmthisinterpretation

Sites intheSUFregionalsoshowedatendencytoconvergeinspecies composition and negative associations between periods(Figure1SupportingInformationAppendixFigureS2)Incontrastpositive associations tended to diverge These results were sup‐portedby theparallel analysesof pairwise sitebetadiversity andPERMDISP(exceptnegativeassociationsTable2)

Forallregionsshiftsinbetadiversityforthespeciesassociationnetworksexceededthoseforspeciescomposition(p=0001withineach site Figure 2) Thus it appears that species association net‐workshavechangedfasterthanspeciescompositionLargeturnover

inspeciesassociations(positiveornegative)mayreflectonlyslightchangesinspeciescomposition

Speciescompositionandspeciesassociationswerelargelyinflu‐encedbythesamesetofenvironmentalvariableswithineachvege‐tationtypeandeachtimeperiod(Table3)Forallsitesinthe1950sspeciescompositionandspeciesassociationnetworkswereaffectedbyalmostthesamesetofenvironmentalvariablesThispatternstillholds in the2000sbut less so for theCSP sitesMore intriguingthe importance of environmental variables on plant communitieshaschangedovertimeForexampleshadewasthemostimportantfortheCSPsitesinthe1950sbutdecreasedinimportancebythe2000s for species composition and positive associationsMinimaltemperaturewasthemostimportantvariablethatstronglyaffectedspeciescompositionandpositiveassociationsoftheSUFsitesinthe1950sbutbecamelessimportantbythe2000swhereasprecipita‐tiongainedimportance

4emsp |emspDISCUSSION

Few studies have quantified changes in both species compositionand species relationship networks over time (Burkle Myers ampBelote2016)Ittakesconsiderableefforttoconstructasingleinter‐actionnetworkletalonenetworksatmultiplesitesovertwoormoretimeperiodsWefoundonlytwoempiricalstudiesonhomogeniza‐tion of ecological networks Laliberteacute and Tylianakis (2010) foundthatdeforestationhomogenizedparasitoidndashhostnetworksintropi‐calareasAlthoughtheyhadtemporaldataofparasitoidndashhostnet‐works(monthlysamplesfor17months)theirmainconclusionwasderivedfromspatialcomparisonsamongdifferentland‐usecatego‐riesKehindeandSamways(2014)examinedbiotichomogenizationofinsectndashflowerinteractionsinvineyardsmanagedunderagri‐envi‐ronmentalschemesintheCapeFloristicRegionTheyfoundnoevi‐denceofhomogenizationforinteractionnetworkswhencomparingvineyardswithnaturalsites

Ourstudymaythusbethefirsttoexploretemporalchangesinbeta diversity of species relationship networks Using patterns ofspecies co‐occurrence to indicate species relationships and usingavaluablehigh‐resolution long‐termdatasetwewereabletoex‐amineparallelchangesinbothcommunitycompositionandspecies

TA B L E 1 emspSummaryofspeciesusedandspeciesassociationsforeachvegetationtypeandtimeperiod

Type DateSpeciesused(n)

Pairs(negativeassociation)[n()]

Pairs(positiveassociation)[n()]

Pairs(random)[n()] Totalpairs

NUF 1950s 146 741(7) 513(48) 9331(882) 10585

NUF 2000s 160 1120(88) 626(49) 10974(863) 12720

CSP 1950s 61 162(89) 104(57) 1564(855) 1830

CSP 2000s 55 125(84) 100(67) 1260(848) 1485

SUF 1950s 225 2001(79) 1127(45) 22072(876) 25200

SUF 2000s 186 1635(95) 857(5) 14713(855) 17205

AbbreviationsCSPcentralsandplainsNUFnorthernuplandforestsSUFsouthernuplandforests

6emsp |emsp emspensp Li et aL

associationnetworksWefoundthatspeciesassociationnetworkscanhomogenizedifferentiateor shownochange through time indifferentvegetationtypesregardlessofthehomogenizationdynam‐icsofspeciescompositionLong‐termchangesinspeciescomposi‐tionandspeciesassociationsthusappeartobedecoupled

IntheNUFofWisconsinplantcommunitieswererelativelysta‐ble intermsoftheirspeciescompositionandspeciesassociationsComparedwith other community types NUF has a lower humanpopulation less land‐use change and less habitat fragmentationInthepresentstudywefoundnooverallchangesinbetadiversityof speciescompositionandspeciesassociationswhen testedwithPERMDISPHoweverpairedrandomizationtestsonbetadiversitybetweensitepairssuggestedsignificanthomogenizationinspeciescomposition matching the conclusion (biotic impoverishment andhomogenization)reachedinapreviousstudyofasubsetofthesesites(Rooneyetal2004)Herewealsoobservedhomogenizationinthe

among‐sitediversityofnegativespeciesassociationsbutsignificantdifferentiationinpositivespeciesassociationsGiventhelargenum‐berofsites inNUF(108) theresultsofrandomizationtestsmightnotbebiologicallysignificantdespitetheirstatisticalsignificancesTheseresultssuggest thatshifts inspeciescompositionmightnotoccurinthesamedirectionasshiftsinspeciesrelationships

Plantcommunities in theCSPhistoricallywerefire‐maintainedpinebarrenswithopencanopiesHowevertheyaresucceedingintoclose‐canopyuplandforestsbecauseoffiresuppression(LiampWaller2015)Firesuppressionhasresultedinhomogenizationinbothspe‐ciescomposition(LiampWaller2015)andfunctionaltraitcomposition(LiampWaller2017)Thisprobablyreflectsdeclinesinhabitathetero‐geneitywithinthesecommunitiesInthe1950ssitesintheCSPhaddifferentcanopycoverageformingmosaicsofburnedandunburnedhabitatstosupportdifferentplantcommunitiesInthe2000show‐ever siteswere similar toeachother in their canopycoverowing

F I G U R E 1 emspDistancetothecentroidofordinationsofspeciescompositionandassociationsIncreasesinthedistancetothecentroidovertimeindicatedifferentiation(diff)Decreasesinthedistancetothecentroidovertimeindicatehomogenization(homog)p lt 005 plt001p lt 0001

no change

homog

homog

no change

homog

diff

no change

no change

no change

Species Composition Positive Associations Negative Associations

NU

FC

SPSU

F

1950s 2000s 1950s 2000s 1950s 2000s

02

04

06

08

02

04

06

08

02

04

06

08

Dis

tanc

e to

Cen

troid

emspensp emsp | emsp7Li et aL

to fire suppression and succession filtering out shade‐intolerantspecies(LiampWaller2017)andhomogenizingplantcommunities(LiampWaller2015)Giventheseecologicalchangesitisnotsurprisingtofindsignificanthomogenizationinbothspeciescompositionandpositivespeciesassociationsinthesecommunities

SitesintheSUFhavebeenaffectedbydevelopmentandland‐use changes more than any other plant community inWisconsin(Rogersetal2008)Currentlymostofthesesitesarefragmentedanddisturbedbynearbyanthropogenic activities including roadsdevelopmentandagriculturePreviousstudiessuggestthathabitatdegradationandfragmentationtendtohomogenizespeciescompo‐sitionbydecreasingspeciesdiversitywhichcanalsoreducenetworkcomplexityandstability(LaliberteacuteampTylianakis2010Mokrossetal2014Tylianakisetal2007)However the fact thathabitat frag‐mentationcan result ingreaterdifferences in interactionnetworkstructure(Bordesetal2015)suggeststhatnetworksimplification(fewer nodes andor edges) does not necessarily cause networkhomogenizationNetworkscandifferacrosssites if individualnet‐workscontainuniqueinteractionseveniftheyshowageneraltrendtowards simplification In theseSUFcommunities the importanceofspeciesdispersallimitationandstochasticfactorshasincreasedwhereastheimportanceofspeciesinteractionshasdecreasedovertime(LiampWaller2016)Itisthuslikelythatstochasticassemblypro‐cesses are formingnovel sets of interactions among species eventhoughspeciesdiversityhasdecreasedIndeedwefoundonaver‐age964significantpositivespeciespairspersiteinthe1950sbutonly603significantpositivepairspersiteinthe2000sindicatingthatassociationnetworksateachsitehavesimplifiedHoweverboththepairedrandomizationtestonpairwisebetadiversityofpositiveassociationnetworksandPERMDISPsuggestedthatpositiveasso‐ciationnetworks inthe2000shavedifferentiatedsincethe1950s(Table2)ThereforeintheSUFwefoundhomogenizationofspeciescompositionbutdifferentiationofspeciespositiveassociations

Although changes in species associations are occurring fasterthan changes in species composition and appear decoupled fromthembotharegenerallyaffectedbysimilarsetsofenvironmentalvariables (Table 3) For example positive species associations andcomposition at all siteswithin each time periodwere affected bythesamesetofenvironmentalvariablesHowevertheimportanceofenvironmentalvariablesforspeciesassociationsandcompositionhaschangedovertimefortheCSPandSUFSpeciesassociationsandcompositionintheCSPweremostaffectedbycanopyshadeinthe1950swithclimaticfactorsplayingnoroleforpositiveassociationsandspeciescompositionBy the2000sclimaticvariablesbecamemoreimportantthancanopyshadeThisreflectsthefactthatCSPforestswith closed canopies show little variation in canopy coverinthe2000sIntheSUFminimaltemperatureusedtobemoreim‐portantthanprecipitationforspeciescompositionandpositiveas‐sociationsthispatternreversedinthe2000sTheseresultssuggestthatspeciesassociationsandcompositionaregenerallyaffectedbya similar set of environmental variables As global environmentalchangesacceleratetherelative importanceofenvironmentalvari‐ablesmaychange further contributing to theemergenceofnovelTA

BLE

2emspHomogenizationinspeciescompositiondoesnotalwaysresultinthehomogenizationofspeciesassociationnetworks

Ave_1950(pairwise)

Ave_2000(pairwise)

Ave_1950(permdisp)

Ave_2000(permdisp)

Direction(pairwise)

Direction(permdisp)

NUF

SpeComp

059

50587

051

30

51homog

nochange

PosAssoc

0778

0785

0561

0566

diff

nochange

NegAssoc

089

10887

0636

0633

homog

nochange

CSP

SpeComp

0447

029

90418

0327

homog

homog

PosAssoc

0683

0442

0496

0314

homog

homog

NegAssoc

080

50806

0574

0575

nochange

nochange

SUF

SpeComp

0572

0546

0516

0497

homog

homog

PosAssoc

0736

0782

0527

0567

diff

diff

NegAssoc

0862

0841

0615

0603

homog

nochange

Not

eNumbersintheave_1950(pairwise)andave_2000(pairwise)columnsrepresentaveragepairwisebetadiversitybetweensiteswithinthesamevegetationtypeinthe1950sandthe2000srespec‐

tivelyNumbersintheave_1950(permdisp)andave_2000(permdisp)columnsrepresenttheaveragedistancetothegroupcentroidintheordinationsofsiteswithinthesamevegetationtypeinthe1950s

andthe2000srespectivelyThecolumndirection(pairwise)indicatesdirectionsofchangesinthepairwisesitebetadiversityovertimetestedwithpairedrandomizationtestsThecolumndirection

(permdisp)indicatesdirectionsofchangesinthedistancebetweensitesandtheordinationcentroidovertimetestedwithpermutationtestsAbbreviationsdiffdifferentiationhomoghomogenization

NegAssocnegativeassociationPosAssocpositiveassociationSpeCompspeciescompositionplt005plt001

p lt

000

1

8emsp |emsp emspensp Li et aL

Vegetationtype Date Variable Shade Precipitation Minimaltemperature

NUF 1950s SpeComp ndash 2 1

PosAssoc ndash 2 1

NegAssoc ndash 2 1

2000s SpeComp ndash 2 1

PosAssoc ndash 2 1

NegAssoc ndash 2 1

CSP 1950s SpeComp 1

PosAssoc 1

NegAssoc 1 2

2000s SpeComp 2 1

PosAssoc 3 1 2

NegAssoc 2 1

SUF 1950s SpeComp ndash 2 1

PosAssoc ndash 2 1

NegAssoc ndash 1 2

2000s SpeComp ndash 1 2

PosAssoc ndash 1 2

NegAssoc ndash 1 2

NoteNumbersaretheorderinwhichvariablesareselectedDash(ndash)meansthattheenvironmentalvariableisnotavailableBlankcellsmeanthatthesevariablesaredroppedoutAbbreviationsNegAssocnegativeassociationPosAssocpositiveassociationSpeCompspeciescomposition

TA B L E 3 emspSelectedenvironmentalvariablesforspeciescompositionandspeciesassociations

F I G U R E 2 emspBetadiversityofspeciescompositionandassociationofthesamesiteovertimeEachpointrepresentsthebetadiversityofthesamesitebetweenthe1950sandthe2000sBetadiversityofoneindicatesthatthespeciescompositionorspeciesassociationinthe1950sandthe2000sweretotallydifferentwhereasbetadiversityofzeroindicatesnochangesinasiteovertimeTurnoverinspeciesrelationshipsappearstobemuchgreaterthantheturnoverinspeciescomposition

NU

FC

SPSU

F

Species Composition Positive Association Negative Association

025

050

075

100

025

050

075

100

025

050

075

100

Beta

div

ersi

ty o

ver t

ime

at th

e sa

me

site

emspensp emsp | emsp9Li et aL

arraysofspeciesandconsequentspecies interactions (Bloisetal2013Milazzoetal2013)

Species association (co‐occurrence) patterns have commonlybeenusedtorepresentspeciesinteractionsbecauseitisintractabletoquantifyinteractionsamonghundredsofplantspeciesSpeciesassociations may give false‐positive (hypothesized links that donotexistintherealsystem)interactionsbetweenspeciesandmaynot detect all real interactions (Barner et al 2018DelalandreampMontesinos‐Navarro2018Freilichetal2018)Howeverourmaingoalistostudybroadpatternsofcommunitystructureanddynam‐ics rather than to pinpoint exact interactions between particularspeciespairsForthispurposespeciesspatialassociationnetworksareanecessaryandusefulproxy(Freilichetal2018)becausetheycanprovidevaluableinformationregardingthenetoutputofdirectandindirecteffectsamongmultipleplantspecies(ratherthanexactpairwise interactions Delalandre amp Montesinos‐Navarro 2018)Co‐occurrence networks may also serve to predict overall com‐munityresponsestodisturbance(TullochChadegravesampLindenmayer2018) To reduce thepotential for biaswe studied species asso‐ciation patterns at a fine spatial scale (1m2) and used statisticalmethods(BayesianGLMMs)thathaverelativelyhighpowerforde‐tecting species interactions (Harris 2016) Furthermoreweusedacommonnullmodelapproachand reported these results in theSupporting InformationAppendixGiven that bothmethods pro‐videquantitatively similar results and reach the sameconclusionour conclusion that changes in species associations and speciescompositionaredecoupledislikelytoberobustConsequentlyourresultsfromspeciesassociationnetworksmayalsoholdforspeciesinteractionnetworks

Anassumptionmadeinthisstudyisthatspeciesassociationswithin each vegetation type and timeperiod remain consistentacross sites In reality associations between species can varythroughspaceandtime(Poisotetal2015)Giventhatwelackedthedatatoanalysehowspeciesassociationsmayhavedifferedover siteswepooleddataacross sites togain insights into theaverage nature of species associationswithin each communityThismakesourresultsconservativebecauseaccountingforvari‐ation inspeciesassociationsoversitescouldshowonlygreatervariationinnetworkstructurestrengtheningourconclusionthattemporal changes in species associations and composition aredecoupled

Our results suggest that species relationshipsmay not be ex‐periencingageneraltrendtowardshomogenizationbecausenovelrelationships may be forming in response to rapid global changeThisraisesimportantquestionsabouthowsuchchangesinspeciesrelationshipsmightaffectcommunitystabilityecosystemservicesandspeciesco‐evolutionStudiesofbetadiversity inspecies rela‐tionshipsremainintheirinfancy(Burkleetal2016)Giventheim‐portanceofspeciesrelationshipsandtheirpotentialunpredictablerelationshipwithspeciescompositionfutureempiricalandtheoret‐icalresearchthatinvestigatespatternscausesandconsequencesofchangesinbetadiversityofrelationshipnetworksareneeded

5emsp |emspBIOSKETCH

Daijiang Liisapost‐doctoralresearcherattheDepartmentofWildlifeEcologyampConservationUniversityofFloridaHisresearchinterestscovercommunityecologyfunctionalandphylogeneticdiversitybi‐ologicalinvasionsglobalchangebiologyandecologicalmodelling

DATA ACCE SSIBILIT Y

The data used in this study have been deposited to figshare(httpsfigsharecoms5a98a69a66f22644361e) with httpsdoiorg106084m9figshare6771938

ORCID

Daijiang Li httporcidorg0000‐0002‐0925‐3421

Timotheacutee Poisot httporcidorg0000‐0002‐0735‐5184

Benjamin Baiser httporcidorg0000‐0002‐3573‐1183

R E FE R E N C E S

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AndersonMJ(2001)Anewmethodfornon‐parametricmultivariateanalysisofvarianceAustral Ecology2632ndash46

AndersonMJEllingsenKEampMcArdleBH (2006)MultivariatedispersionasameasureofbetadiversityEcology Letters9683ndash693httpsdoiorg101111j1461‐0248200600926x

Arauacutejo M B Rozenfeld A Rahbek C amp Marquet P A (2011)Using species co‐occurrence networks to assess the im‐pacts of climate change Ecography 34 897ndash908 httpsdoiorg101111j1600‐0587201106919x

AshJDGivnishTJampWallerDM(2017)Trackinglagsinhistori‐calplantspeciesrsquoshiftsinrelationtoregionalclimatechangeGlobal Change Biology231305ndash1315httpsdoiorg101111gcb13429

BaiserBOlden JDRecordSLockwoodJLampMcKinneyML(2012) Pattern and process of biotic homogenization in the newPangaeaProceedings of the Royal Society B Biological Sciences2794772ndash4777

Barner A K Coblentz K E Hacker S D amp Menge B A (2018)Fundamentalcontradictionsamongobservationalandexperimentalestimatesofnon‐trophicspeciesinteractionsEcology99557ndash566httpsdoiorg101002ecy2133

Bascompte J JordanoPampOlesen JM (2006)Asymmetriccoevo‐lutionarynetworksfacilitatebiodiversitymaintenanceScience312431ndash433httpsdoiorg101126science1123412

Blois J L Zarnetske P L FitzpatrickM C amp Finnegan S (2013)ClimatechangeandthepastpresentandfutureofbioticinteractionsScience341499ndash504httpsdoiorg101126science1237184

BordesFMorandSPilosofSClaudeJKrasnovBRCossonJ‐Fhellip Blasdell K (2015) Habitat fragmentation alters the propertiesofahostndashparasitenetworkRodentsand theirhelminths inSouth‐East Asia Journal of Animal Ecology 84 1253ndash1263 httpsdoiorg1011111365‐265612368

BurkleLAMyersJAampBeloteRT (2016)Thebeta‐diversityofspecies interactions Untangling the drivers of geographic vari‐ation in plantndashpollinator diversity and function across scales

10emsp |emsp emspensp Li et aL

American Journal of Botany103118ndash128httpsdoiorg103732ajb1500079

CaraDonna P J Petry W K Brennan R M Cunningham J LBronstein J LWaserNMamp SandersN J (2017) InteractionrewiringandtherapidturnoverofplantndashpollinatornetworksEcology Letters20385ndash394httpsdoiorg101111ele12740

CazellesKArauacutejoMBMouquetNampGravelD(2016)Atheoryforspeciesco‐occurrenceininteractionnetworksTheoretical Ecology939ndash48httpsdoiorg101007s12080‐015‐0281‐9

ConnorEFampSimberloffD(1979)Theassemblyofspeciescommu‐nitiesChanceorcompetitionEcology601132ndash1140httpsdoiorg1023071936961

CummingGSBodinOumlErnstsonHampElmqvistT(2010)Networkanalysis in conservation biogeography Challenges and oppor‐tunities Diversity and Distributions 16 414ndash425 httpsdoiorg101111j1472‐4642201000651x

CurtisJT(1959)The vegetation of Wisconsin An ordination of plant com-munitiesMadisonWIUniversityofWisconsinPress

de Solar R R C Barlow J Ferreira J Berenguer E Lees A CThompsonJRhellipGardnerTA(2015)Howpervasiveisbioticho‐mogenizationinhuman‐modifiedtropicalforestlandscapesEcology Letters181108ndash1118httpsdoiorg101111ele12494

DelalandreLampMontesinos‐NavarroA(2018)Canco‐occurrencenet‐works predict plant‐plant interactions in a semi‐arid gypsum com‐munityPerspectives in Plant Ecology Evolution and Systematics3136ndash43httpsdoiorg101016jppees201801001

Diamond JM (1975) Assembly of species communitiesEcology and Evolution of Communities342ndash444

FreilichMAWietersEBroitmanBMarquetPAampNavarreteSA(2018)Speciesco‐occurrencenetworksCantheyrevealtrophicandnon‐trophicinteractionsinecologicalcommunitiesEcology99690ndash699httpsdoiorg101002ecy2142

Gotelli N J (2000) Null model analysis of species co‐oc‐currence patterns Ecology 81 2606ndash2621 httpsdoiorg1018900012‐9658(2000)081[2606NMAOSC]20CO2

GotelliNJampGravesGR(1996)Null models in ecologyWashingtonDCSmithsonianInstitution

GotelliN JGravesGRampRahbekC (2010)Macroecological sig‐nalsofspeciesinteractionsintheDanishavifaunaProceedings of the National Academy of Sciences of the USA1075030ndash5035httpsdoiorg101073pnas0914089107

Hadfield JD (2010)MCMCmethods formulti‐responsegeneralizedlinearmixedmodelsTheMCMCglmmRpackageJournal of Statistical Software331ndash22

Harley C D (2011) Climate change keystone predation and biodi‐versity loss Science 334 1124ndash1127 httpsdoiorg101126science1210199

Harris D J (2016) Inferring species interactions from co‐occurrencedata with Markov networks Ecology 97 3308ndash3314 httpsdoiorg101002ecy1605

Harvey E Gounand I Ward C L amp Altermatt F (2017) Bridgingecology and conservation From ecological networks to ecosys‐tem function Journal of Applied Ecology 54 371ndash379 httpsdoiorg1011111365‐266412769

Hegland S J Nielsen A Laacutezaro A Bjerknes A‐L amp TotlandOslash (2009) How does climate warming affect plant‐pollina‐tor interactions Ecology Letters 12 184ndash195 httpsdoiorg101111j1461‐0248200801269x

Hobbs R J Higgs E amp Harris J A (2009) Novel ecosystemsImplicationsforconservationandrestorationTrends in Ecology and Evolution24599ndash605httpsdoiorg101016jtree200905012

Kehinde T amp Samways M J (2014) Effects of vineyard manage‐ment on biotic homogenization of insectndashflower interaction net‐works in the cape floristic region biodiversity hotspot Journal of Insect Conservation 18 469ndash477 httpsdoiorg101007s10841‐014‐9659‐z

Kucharik C J Serbin S P Vavrus S Hopkins E J amp MotewM M (2010) Patterns of climate change across Wisconsinfrom 1950 to 2006 Physical Geography 31 1ndash28 httpsdoiorg1027470272‐36463111

LaliberteacuteEampTylianakisJM(2010)Deforestationhomogenizestrop‐ical parasitoidndashhost networks Ecology 91 1740ndash1747 httpsdoiorg10189009‐13281

LegendrePampDeCaacuteceresM(2013)BetadiversityasthevarianceofcommunitydataDissimilaritycoefficientsandpartitioningEcology Letters16951ndash963httpsdoiorg101111ele12141

LegendrePampLegendreLF(2012)Numerical ecologyAmsterdamTheNetherlandsElsevier

LiDampWallerDM(2015)DriversofobservedbiotichomogenizationinpinebarrensofcentralWisconsinEcology961030ndash1041httpsdoiorg10189014‐08931

LiDampWallerDM (2016)Long‐termshifts inthepatternsandun‐derlyingprocessesofplantassociationsinWisconsinforestsGlobal Ecology and Biogeography 25 516ndash526 httpsdoiorg101111geb12432

LiDampWallerDM(2017)Fireexclusionandclimatechangeinteracttoaffect long‐termchanges in the functional compositionofplantcommunitiesDiversity and Distributions 23 496ndash506 httpsdoiorg101111ddi12542

LoreauMMouquetNampGonzalezA(2003)Biodiversityasspatialinsurance inheterogeneous landscapesProceedings of the National Academy of Sciences of the USA 100 12765ndash12770 httpsdoiorg101073pnas2235465100

MacLeod M Genung M A Ascher J S amp Winfree R (2016)Measuring partner choice in plantndashpollinator networks Using nullmodels to separate rewiring and fidelity from chanceEcology972925ndash2931httpsdoiorg101002ecy1574

McCannK(2007)ProtectingbiostructureNature44629ndash29httpsdoiorg101038446029a

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Milazzo M Mirto S Domenici P amp Gristina M (2013) Climatechange exacerbates interspecific interactions in sympatriccoastal fishes Journal of Animal Ecology 82 468ndash477 httpsdoiorg101111j1365‐2656201202034x

MokrossKRyderTBCocircrtesMCWolfe JDampStoufferPC(2014) Decay of interspecific avian flock networks along a dis‐turbance gradient in Amazonia Proceedings of the Royal Society B Biological Sciences28120132599

Morales‐Castilla IMatiasM G Gravel D amp ArauacutejoM B (2015)Inferring biotic interactions from proxies Trends in Ecology and Evolution30347ndash356httpsdoiorg101016jtree201503014

OksanenJBlanchetFGFriendlyMKindtRLegendrePMcGlinnDhellipWagnerH(2018)Vegan Community ecology packageRpack‐ageversion25‐2httpsCRANR‐projectorgpackage=vegan

OldenJDComteLampGiamX(2018)TheHomogoceneAresearchprospectusforthestudyofbiotichomogenisationNeoBiota3723httpsdoiorg103897neobiota3722552

OldenJDampPoffNL (2003)Towardamechanisticunderstandingand prediction of biotic homogenization The American Naturalist162442ndash460httpsdoiorg101086378212

OldenJDPoffNLDouglasMRDouglasMEampFauschKD(2004)Ecologicalandevolutionaryconsequencesofbiotichomog‐enization Trends in Ecology and Evolution 19 18ndash24 httpsdoiorg101016jtree200309010

PetanidouTKallimanisASTzanopoulosJSgardelisSPampPantisJD(2008)Long‐termobservationofapollinationnetworkFluctuationinspeciesandinteractionsrelativeinvarianceofnetworkstructureand implicationsforestimatesofspecializationEcology Letters11564ndash575httpsdoiorg101111j1461‐0248200801170x

emspensp emsp | emsp11Li et aL

Poisot T Gueacuteveneux‐Julien C FortinM‐J Gravel D amp LegendreP (2017)Hostsparasitesandtheir interactionsrespondtodiffer‐entclimaticvariablesGlobal Ecology and Biogeography26942ndash951httpsdoiorg101111geb12602

PoisotTStoufferDBampGravelD(2015)BeyondspeciesWhyeco‐logicalinteractionnetworksvarythroughspaceandtimeOikos124243ndash251httpsdoiorg101111oik01719

RCoreTeam(2017)R A language and environment for statistical comput-ingViennaAustriaRFoundationforStatisticalComputing

RockwellRFGormezanoLJampKoonsDN(2011)TrophicmatchesandmismatchesCanpolarbearsreducetheabundanceofnestingsnowgeese inwesternHudsonBayOikos120696ndash709httpsdoiorg101111j1600‐0706201018837x

RogersDARooneyTPOlsonDampWallerDM(2008)ShiftsinsouthernWisconsin forest canopy and understory richness com‐position and heterogeneity Ecology 89 2482ndash2492 httpsdoiorg10189007‐11291

RooneyTPWiegmannSMRogersDAampWallerDM (2004)BioticimpoverishmentandhomogenizationinunfragmentedforestunderstorycommunitiesConservation Biology18787ndash798httpsdoiorg101111j1523‐1739200400515x

SalaOEChapinFSArmestoJJBerlowEBloomfieldJDirzoRhellipLeemansR(2000)Globalbiodiversityscenariosfortheyear2100 Science2871770ndash1774

TullochAIChadegravesIampLindenmayerDB(2018)Speciesco‐occur‐renceanalysispredictsmanagementoutcomesformultiplethreatsNature Ecology amp Evolution 2 465ndash474 httpsdoiorg101038s41559‐017‐0457‐3

Tylianakis J M Didham R K Bascompte J amp Wardle D A(2008) Global change and species interactions in terres‐trial ecosystems Ecology Letters 11 1351ndash1363 httpsdoiorg101111j1461‐0248200801250x

Tylianakis J M amp Morris R J (2017) Ecological networksacross environmental gradients Annual Review of Ecology

Evolution and Systematics 48 25ndash48 httpsdoiorg101146annurev‐ecolsys‐110316‐022821

Tylianakis JM Tscharntke Tamp LewisO T (2007)Habitatmodifi‐cation alters the structure of tropical hostndashparasitoid food websNature445202ndash205httpsdoiorg101038nature05429

Valiente‐BanuetAAizenMAAlcaacutentaraJMArroyoJCocucciAGalettiMhellipJordanoP(2015)BeyondspecieslossTheextinctionofecologicalinteractionsinachangingworldFunctional Ecology29299ndash307httpsdoiorg1011111365‐243512356

Vitousek PMMooneyHA Lubchenco JampMelillo JM (1997)Human domination of earthrsquos ecosystems Science 277 494ndash499httpsdoiorg101126science2775325494

Waller DM Amatangelo K L Johnson S amp Rogers D A (2012)Wisconsinvegetationdatabasendashplantcommunitysurveyandresur‐veydatafromtheWisconsinplantecologylaboratoryBiodiversity amp Ecology4255ndash264httpsdoiorg107809b‐e00082

SUPPORTING INFORMATION

Additional supporting information may be found online in theSupportingInformationsectionattheendofthearticle

How to cite this articleLiDPoisotTWallerDMBaiserBHomogenizationofspeciescompositionandspeciesassociationnetworksaredecoupledGlobal Ecol Biogeogr 2018001ndash11 httpsdoiorg101111geb12825

Page 6: Homogenization of species composition and species ... · L I ET A L. | 3 biotic homogenization in species composition (Li & Waller, 2015; Rogers, Rooney, Olson, & Waller, 2008; Rooney

6emsp |emsp emspensp Li et aL

associationnetworksWefoundthatspeciesassociationnetworkscanhomogenizedifferentiateor shownochange through time indifferentvegetationtypesregardlessofthehomogenizationdynam‐icsofspeciescompositionLong‐termchangesinspeciescomposi‐tionandspeciesassociationsthusappeartobedecoupled

IntheNUFofWisconsinplantcommunitieswererelativelysta‐ble intermsoftheirspeciescompositionandspeciesassociationsComparedwith other community types NUF has a lower humanpopulation less land‐use change and less habitat fragmentationInthepresentstudywefoundnooverallchangesinbetadiversityof speciescompositionandspeciesassociationswhen testedwithPERMDISPHoweverpairedrandomizationtestsonbetadiversitybetweensitepairssuggestedsignificanthomogenizationinspeciescomposition matching the conclusion (biotic impoverishment andhomogenization)reachedinapreviousstudyofasubsetofthesesites(Rooneyetal2004)Herewealsoobservedhomogenizationinthe

among‐sitediversityofnegativespeciesassociationsbutsignificantdifferentiationinpositivespeciesassociationsGiventhelargenum‐berofsites inNUF(108) theresultsofrandomizationtestsmightnotbebiologicallysignificantdespitetheirstatisticalsignificancesTheseresultssuggest thatshifts inspeciescompositionmightnotoccurinthesamedirectionasshiftsinspeciesrelationships

Plantcommunities in theCSPhistoricallywerefire‐maintainedpinebarrenswithopencanopiesHowevertheyaresucceedingintoclose‐canopyuplandforestsbecauseoffiresuppression(LiampWaller2015)Firesuppressionhasresultedinhomogenizationinbothspe‐ciescomposition(LiampWaller2015)andfunctionaltraitcomposition(LiampWaller2017)Thisprobablyreflectsdeclinesinhabitathetero‐geneitywithinthesecommunitiesInthe1950ssitesintheCSPhaddifferentcanopycoverageformingmosaicsofburnedandunburnedhabitatstosupportdifferentplantcommunitiesInthe2000show‐ever siteswere similar toeachother in their canopycoverowing

F I G U R E 1 emspDistancetothecentroidofordinationsofspeciescompositionandassociationsIncreasesinthedistancetothecentroidovertimeindicatedifferentiation(diff)Decreasesinthedistancetothecentroidovertimeindicatehomogenization(homog)p lt 005 plt001p lt 0001

no change

homog

homog

no change

homog

diff

no change

no change

no change

Species Composition Positive Associations Negative Associations

NU

FC

SPSU

F

1950s 2000s 1950s 2000s 1950s 2000s

02

04

06

08

02

04

06

08

02

04

06

08

Dis

tanc

e to

Cen

troid

emspensp emsp | emsp7Li et aL

to fire suppression and succession filtering out shade‐intolerantspecies(LiampWaller2017)andhomogenizingplantcommunities(LiampWaller2015)Giventheseecologicalchangesitisnotsurprisingtofindsignificanthomogenizationinbothspeciescompositionandpositivespeciesassociationsinthesecommunities

SitesintheSUFhavebeenaffectedbydevelopmentandland‐use changes more than any other plant community inWisconsin(Rogersetal2008)Currentlymostofthesesitesarefragmentedanddisturbedbynearbyanthropogenic activities including roadsdevelopmentandagriculturePreviousstudiessuggestthathabitatdegradationandfragmentationtendtohomogenizespeciescompo‐sitionbydecreasingspeciesdiversitywhichcanalsoreducenetworkcomplexityandstability(LaliberteacuteampTylianakis2010Mokrossetal2014Tylianakisetal2007)However the fact thathabitat frag‐mentationcan result ingreaterdifferences in interactionnetworkstructure(Bordesetal2015)suggeststhatnetworksimplification(fewer nodes andor edges) does not necessarily cause networkhomogenizationNetworkscandifferacrosssites if individualnet‐workscontainuniqueinteractionseveniftheyshowageneraltrendtowards simplification In theseSUFcommunities the importanceofspeciesdispersallimitationandstochasticfactorshasincreasedwhereastheimportanceofspeciesinteractionshasdecreasedovertime(LiampWaller2016)Itisthuslikelythatstochasticassemblypro‐cesses are formingnovel sets of interactions among species eventhoughspeciesdiversityhasdecreasedIndeedwefoundonaver‐age964significantpositivespeciespairspersiteinthe1950sbutonly603significantpositivepairspersiteinthe2000sindicatingthatassociationnetworksateachsitehavesimplifiedHoweverboththepairedrandomizationtestonpairwisebetadiversityofpositiveassociationnetworksandPERMDISPsuggestedthatpositiveasso‐ciationnetworks inthe2000shavedifferentiatedsincethe1950s(Table2)ThereforeintheSUFwefoundhomogenizationofspeciescompositionbutdifferentiationofspeciespositiveassociations

Although changes in species associations are occurring fasterthan changes in species composition and appear decoupled fromthembotharegenerallyaffectedbysimilarsetsofenvironmentalvariables (Table 3) For example positive species associations andcomposition at all siteswithin each time periodwere affected bythesamesetofenvironmentalvariablesHowevertheimportanceofenvironmentalvariablesforspeciesassociationsandcompositionhaschangedovertimefortheCSPandSUFSpeciesassociationsandcompositionintheCSPweremostaffectedbycanopyshadeinthe1950swithclimaticfactorsplayingnoroleforpositiveassociationsandspeciescompositionBy the2000sclimaticvariablesbecamemoreimportantthancanopyshadeThisreflectsthefactthatCSPforestswith closed canopies show little variation in canopy coverinthe2000sIntheSUFminimaltemperatureusedtobemoreim‐portantthanprecipitationforspeciescompositionandpositiveas‐sociationsthispatternreversedinthe2000sTheseresultssuggestthatspeciesassociationsandcompositionaregenerallyaffectedbya similar set of environmental variables As global environmentalchangesacceleratetherelative importanceofenvironmentalvari‐ablesmaychange further contributing to theemergenceofnovelTA

BLE

2emspHomogenizationinspeciescompositiondoesnotalwaysresultinthehomogenizationofspeciesassociationnetworks

Ave_1950(pairwise)

Ave_2000(pairwise)

Ave_1950(permdisp)

Ave_2000(permdisp)

Direction(pairwise)

Direction(permdisp)

NUF

SpeComp

059

50587

051

30

51homog

nochange

PosAssoc

0778

0785

0561

0566

diff

nochange

NegAssoc

089

10887

0636

0633

homog

nochange

CSP

SpeComp

0447

029

90418

0327

homog

homog

PosAssoc

0683

0442

0496

0314

homog

homog

NegAssoc

080

50806

0574

0575

nochange

nochange

SUF

SpeComp

0572

0546

0516

0497

homog

homog

PosAssoc

0736

0782

0527

0567

diff

diff

NegAssoc

0862

0841

0615

0603

homog

nochange

Not

eNumbersintheave_1950(pairwise)andave_2000(pairwise)columnsrepresentaveragepairwisebetadiversitybetweensiteswithinthesamevegetationtypeinthe1950sandthe2000srespec‐

tivelyNumbersintheave_1950(permdisp)andave_2000(permdisp)columnsrepresenttheaveragedistancetothegroupcentroidintheordinationsofsiteswithinthesamevegetationtypeinthe1950s

andthe2000srespectivelyThecolumndirection(pairwise)indicatesdirectionsofchangesinthepairwisesitebetadiversityovertimetestedwithpairedrandomizationtestsThecolumndirection

(permdisp)indicatesdirectionsofchangesinthedistancebetweensitesandtheordinationcentroidovertimetestedwithpermutationtestsAbbreviationsdiffdifferentiationhomoghomogenization

NegAssocnegativeassociationPosAssocpositiveassociationSpeCompspeciescompositionplt005plt001

p lt

000

1

8emsp |emsp emspensp Li et aL

Vegetationtype Date Variable Shade Precipitation Minimaltemperature

NUF 1950s SpeComp ndash 2 1

PosAssoc ndash 2 1

NegAssoc ndash 2 1

2000s SpeComp ndash 2 1

PosAssoc ndash 2 1

NegAssoc ndash 2 1

CSP 1950s SpeComp 1

PosAssoc 1

NegAssoc 1 2

2000s SpeComp 2 1

PosAssoc 3 1 2

NegAssoc 2 1

SUF 1950s SpeComp ndash 2 1

PosAssoc ndash 2 1

NegAssoc ndash 1 2

2000s SpeComp ndash 1 2

PosAssoc ndash 1 2

NegAssoc ndash 1 2

NoteNumbersaretheorderinwhichvariablesareselectedDash(ndash)meansthattheenvironmentalvariableisnotavailableBlankcellsmeanthatthesevariablesaredroppedoutAbbreviationsNegAssocnegativeassociationPosAssocpositiveassociationSpeCompspeciescomposition

TA B L E 3 emspSelectedenvironmentalvariablesforspeciescompositionandspeciesassociations

F I G U R E 2 emspBetadiversityofspeciescompositionandassociationofthesamesiteovertimeEachpointrepresentsthebetadiversityofthesamesitebetweenthe1950sandthe2000sBetadiversityofoneindicatesthatthespeciescompositionorspeciesassociationinthe1950sandthe2000sweretotallydifferentwhereasbetadiversityofzeroindicatesnochangesinasiteovertimeTurnoverinspeciesrelationshipsappearstobemuchgreaterthantheturnoverinspeciescomposition

NU

FC

SPSU

F

Species Composition Positive Association Negative Association

025

050

075

100

025

050

075

100

025

050

075

100

Beta

div

ersi

ty o

ver t

ime

at th

e sa

me

site

emspensp emsp | emsp9Li et aL

arraysofspeciesandconsequentspecies interactions (Bloisetal2013Milazzoetal2013)

Species association (co‐occurrence) patterns have commonlybeenusedtorepresentspeciesinteractionsbecauseitisintractabletoquantifyinteractionsamonghundredsofplantspeciesSpeciesassociations may give false‐positive (hypothesized links that donotexistintherealsystem)interactionsbetweenspeciesandmaynot detect all real interactions (Barner et al 2018DelalandreampMontesinos‐Navarro2018Freilichetal2018)Howeverourmaingoalistostudybroadpatternsofcommunitystructureanddynam‐ics rather than to pinpoint exact interactions between particularspeciespairsForthispurposespeciesspatialassociationnetworksareanecessaryandusefulproxy(Freilichetal2018)becausetheycanprovidevaluableinformationregardingthenetoutputofdirectandindirecteffectsamongmultipleplantspecies(ratherthanexactpairwise interactions Delalandre amp Montesinos‐Navarro 2018)Co‐occurrence networks may also serve to predict overall com‐munityresponsestodisturbance(TullochChadegravesampLindenmayer2018) To reduce thepotential for biaswe studied species asso‐ciation patterns at a fine spatial scale (1m2) and used statisticalmethods(BayesianGLMMs)thathaverelativelyhighpowerforde‐tecting species interactions (Harris 2016) Furthermoreweusedacommonnullmodelapproachand reported these results in theSupporting InformationAppendixGiven that bothmethods pro‐videquantitatively similar results and reach the sameconclusionour conclusion that changes in species associations and speciescompositionaredecoupledislikelytoberobustConsequentlyourresultsfromspeciesassociationnetworksmayalsoholdforspeciesinteractionnetworks

Anassumptionmadeinthisstudyisthatspeciesassociationswithin each vegetation type and timeperiod remain consistentacross sites In reality associations between species can varythroughspaceandtime(Poisotetal2015)Giventhatwelackedthedatatoanalysehowspeciesassociationsmayhavedifferedover siteswepooleddataacross sites togain insights into theaverage nature of species associationswithin each communityThismakesourresultsconservativebecauseaccountingforvari‐ation inspeciesassociationsoversitescouldshowonlygreatervariationinnetworkstructurestrengtheningourconclusionthattemporal changes in species associations and composition aredecoupled

Our results suggest that species relationshipsmay not be ex‐periencingageneraltrendtowardshomogenizationbecausenovelrelationships may be forming in response to rapid global changeThisraisesimportantquestionsabouthowsuchchangesinspeciesrelationshipsmightaffectcommunitystabilityecosystemservicesandspeciesco‐evolutionStudiesofbetadiversity inspecies rela‐tionshipsremainintheirinfancy(Burkleetal2016)Giventheim‐portanceofspeciesrelationshipsandtheirpotentialunpredictablerelationshipwithspeciescompositionfutureempiricalandtheoret‐icalresearchthatinvestigatespatternscausesandconsequencesofchangesinbetadiversityofrelationshipnetworksareneeded

5emsp |emspBIOSKETCH

Daijiang Liisapost‐doctoralresearcherattheDepartmentofWildlifeEcologyampConservationUniversityofFloridaHisresearchinterestscovercommunityecologyfunctionalandphylogeneticdiversitybi‐ologicalinvasionsglobalchangebiologyandecologicalmodelling

DATA ACCE SSIBILIT Y

The data used in this study have been deposited to figshare(httpsfigsharecoms5a98a69a66f22644361e) with httpsdoiorg106084m9figshare6771938

ORCID

Daijiang Li httporcidorg0000‐0002‐0925‐3421

Timotheacutee Poisot httporcidorg0000‐0002‐0735‐5184

Benjamin Baiser httporcidorg0000‐0002‐3573‐1183

R E FE R E N C E S

AmatangeloKLFultonMRRogersDAampWallerDM (2011)Convergingforestcommunitycompositionalonganedaphicgradi‐ent threatens landscape‐level diversityDiversity and Distributions17201ndash213httpsdoiorg101111j1472‐4642201000730x

AndersonMJ(2001)Anewmethodfornon‐parametricmultivariateanalysisofvarianceAustral Ecology2632ndash46

AndersonMJEllingsenKEampMcArdleBH (2006)MultivariatedispersionasameasureofbetadiversityEcology Letters9683ndash693httpsdoiorg101111j1461‐0248200600926x

Arauacutejo M B Rozenfeld A Rahbek C amp Marquet P A (2011)Using species co‐occurrence networks to assess the im‐pacts of climate change Ecography 34 897ndash908 httpsdoiorg101111j1600‐0587201106919x

AshJDGivnishTJampWallerDM(2017)Trackinglagsinhistori‐calplantspeciesrsquoshiftsinrelationtoregionalclimatechangeGlobal Change Biology231305ndash1315httpsdoiorg101111gcb13429

BaiserBOlden JDRecordSLockwoodJLampMcKinneyML(2012) Pattern and process of biotic homogenization in the newPangaeaProceedings of the Royal Society B Biological Sciences2794772ndash4777

Barner A K Coblentz K E Hacker S D amp Menge B A (2018)Fundamentalcontradictionsamongobservationalandexperimentalestimatesofnon‐trophicspeciesinteractionsEcology99557ndash566httpsdoiorg101002ecy2133

Bascompte J JordanoPampOlesen JM (2006)Asymmetriccoevo‐lutionarynetworksfacilitatebiodiversitymaintenanceScience312431ndash433httpsdoiorg101126science1123412

Blois J L Zarnetske P L FitzpatrickM C amp Finnegan S (2013)ClimatechangeandthepastpresentandfutureofbioticinteractionsScience341499ndash504httpsdoiorg101126science1237184

BordesFMorandSPilosofSClaudeJKrasnovBRCossonJ‐Fhellip Blasdell K (2015) Habitat fragmentation alters the propertiesofahostndashparasitenetworkRodentsand theirhelminths inSouth‐East Asia Journal of Animal Ecology 84 1253ndash1263 httpsdoiorg1011111365‐265612368

BurkleLAMyersJAampBeloteRT (2016)Thebeta‐diversityofspecies interactions Untangling the drivers of geographic vari‐ation in plantndashpollinator diversity and function across scales

10emsp |emsp emspensp Li et aL

American Journal of Botany103118ndash128httpsdoiorg103732ajb1500079

CaraDonna P J Petry W K Brennan R M Cunningham J LBronstein J LWaserNMamp SandersN J (2017) InteractionrewiringandtherapidturnoverofplantndashpollinatornetworksEcology Letters20385ndash394httpsdoiorg101111ele12740

CazellesKArauacutejoMBMouquetNampGravelD(2016)Atheoryforspeciesco‐occurrenceininteractionnetworksTheoretical Ecology939ndash48httpsdoiorg101007s12080‐015‐0281‐9

ConnorEFampSimberloffD(1979)Theassemblyofspeciescommu‐nitiesChanceorcompetitionEcology601132ndash1140httpsdoiorg1023071936961

CummingGSBodinOumlErnstsonHampElmqvistT(2010)Networkanalysis in conservation biogeography Challenges and oppor‐tunities Diversity and Distributions 16 414ndash425 httpsdoiorg101111j1472‐4642201000651x

CurtisJT(1959)The vegetation of Wisconsin An ordination of plant com-munitiesMadisonWIUniversityofWisconsinPress

de Solar R R C Barlow J Ferreira J Berenguer E Lees A CThompsonJRhellipGardnerTA(2015)Howpervasiveisbioticho‐mogenizationinhuman‐modifiedtropicalforestlandscapesEcology Letters181108ndash1118httpsdoiorg101111ele12494

DelalandreLampMontesinos‐NavarroA(2018)Canco‐occurrencenet‐works predict plant‐plant interactions in a semi‐arid gypsum com‐munityPerspectives in Plant Ecology Evolution and Systematics3136ndash43httpsdoiorg101016jppees201801001

Diamond JM (1975) Assembly of species communitiesEcology and Evolution of Communities342ndash444

FreilichMAWietersEBroitmanBMarquetPAampNavarreteSA(2018)Speciesco‐occurrencenetworksCantheyrevealtrophicandnon‐trophicinteractionsinecologicalcommunitiesEcology99690ndash699httpsdoiorg101002ecy2142

Gotelli N J (2000) Null model analysis of species co‐oc‐currence patterns Ecology 81 2606ndash2621 httpsdoiorg1018900012‐9658(2000)081[2606NMAOSC]20CO2

GotelliNJampGravesGR(1996)Null models in ecologyWashingtonDCSmithsonianInstitution

GotelliN JGravesGRampRahbekC (2010)Macroecological sig‐nalsofspeciesinteractionsintheDanishavifaunaProceedings of the National Academy of Sciences of the USA1075030ndash5035httpsdoiorg101073pnas0914089107

Hadfield JD (2010)MCMCmethods formulti‐responsegeneralizedlinearmixedmodelsTheMCMCglmmRpackageJournal of Statistical Software331ndash22

Harley C D (2011) Climate change keystone predation and biodi‐versity loss Science 334 1124ndash1127 httpsdoiorg101126science1210199

Harris D J (2016) Inferring species interactions from co‐occurrencedata with Markov networks Ecology 97 3308ndash3314 httpsdoiorg101002ecy1605

Harvey E Gounand I Ward C L amp Altermatt F (2017) Bridgingecology and conservation From ecological networks to ecosys‐tem function Journal of Applied Ecology 54 371ndash379 httpsdoiorg1011111365‐266412769

Hegland S J Nielsen A Laacutezaro A Bjerknes A‐L amp TotlandOslash (2009) How does climate warming affect plant‐pollina‐tor interactions Ecology Letters 12 184ndash195 httpsdoiorg101111j1461‐0248200801269x

Hobbs R J Higgs E amp Harris J A (2009) Novel ecosystemsImplicationsforconservationandrestorationTrends in Ecology and Evolution24599ndash605httpsdoiorg101016jtree200905012

Kehinde T amp Samways M J (2014) Effects of vineyard manage‐ment on biotic homogenization of insectndashflower interaction net‐works in the cape floristic region biodiversity hotspot Journal of Insect Conservation 18 469ndash477 httpsdoiorg101007s10841‐014‐9659‐z

Kucharik C J Serbin S P Vavrus S Hopkins E J amp MotewM M (2010) Patterns of climate change across Wisconsinfrom 1950 to 2006 Physical Geography 31 1ndash28 httpsdoiorg1027470272‐36463111

LaliberteacuteEampTylianakisJM(2010)Deforestationhomogenizestrop‐ical parasitoidndashhost networks Ecology 91 1740ndash1747 httpsdoiorg10189009‐13281

LegendrePampDeCaacuteceresM(2013)BetadiversityasthevarianceofcommunitydataDissimilaritycoefficientsandpartitioningEcology Letters16951ndash963httpsdoiorg101111ele12141

LegendrePampLegendreLF(2012)Numerical ecologyAmsterdamTheNetherlandsElsevier

LiDampWallerDM(2015)DriversofobservedbiotichomogenizationinpinebarrensofcentralWisconsinEcology961030ndash1041httpsdoiorg10189014‐08931

LiDampWallerDM (2016)Long‐termshifts inthepatternsandun‐derlyingprocessesofplantassociationsinWisconsinforestsGlobal Ecology and Biogeography 25 516ndash526 httpsdoiorg101111geb12432

LiDampWallerDM(2017)Fireexclusionandclimatechangeinteracttoaffect long‐termchanges in the functional compositionofplantcommunitiesDiversity and Distributions 23 496ndash506 httpsdoiorg101111ddi12542

LoreauMMouquetNampGonzalezA(2003)Biodiversityasspatialinsurance inheterogeneous landscapesProceedings of the National Academy of Sciences of the USA 100 12765ndash12770 httpsdoiorg101073pnas2235465100

MacLeod M Genung M A Ascher J S amp Winfree R (2016)Measuring partner choice in plantndashpollinator networks Using nullmodels to separate rewiring and fidelity from chanceEcology972925ndash2931httpsdoiorg101002ecy1574

McCannK(2007)ProtectingbiostructureNature44629ndash29httpsdoiorg101038446029a

McKinneyMLampLockwoodJL(1999)BiotichomogenizationAfewwinners replacingmany losers in the nextmass extinctionTrends in Ecology and Evolution 14 450ndash453 httpsdoiorg101016S0169‐5347(99)01679‐1

Milazzo M Mirto S Domenici P amp Gristina M (2013) Climatechange exacerbates interspecific interactions in sympatriccoastal fishes Journal of Animal Ecology 82 468ndash477 httpsdoiorg101111j1365‐2656201202034x

MokrossKRyderTBCocircrtesMCWolfe JDampStoufferPC(2014) Decay of interspecific avian flock networks along a dis‐turbance gradient in Amazonia Proceedings of the Royal Society B Biological Sciences28120132599

Morales‐Castilla IMatiasM G Gravel D amp ArauacutejoM B (2015)Inferring biotic interactions from proxies Trends in Ecology and Evolution30347ndash356httpsdoiorg101016jtree201503014

OksanenJBlanchetFGFriendlyMKindtRLegendrePMcGlinnDhellipWagnerH(2018)Vegan Community ecology packageRpack‐ageversion25‐2httpsCRANR‐projectorgpackage=vegan

OldenJDComteLampGiamX(2018)TheHomogoceneAresearchprospectusforthestudyofbiotichomogenisationNeoBiota3723httpsdoiorg103897neobiota3722552

OldenJDampPoffNL (2003)Towardamechanisticunderstandingand prediction of biotic homogenization The American Naturalist162442ndash460httpsdoiorg101086378212

OldenJDPoffNLDouglasMRDouglasMEampFauschKD(2004)Ecologicalandevolutionaryconsequencesofbiotichomog‐enization Trends in Ecology and Evolution 19 18ndash24 httpsdoiorg101016jtree200309010

PetanidouTKallimanisASTzanopoulosJSgardelisSPampPantisJD(2008)Long‐termobservationofapollinationnetworkFluctuationinspeciesandinteractionsrelativeinvarianceofnetworkstructureand implicationsforestimatesofspecializationEcology Letters11564ndash575httpsdoiorg101111j1461‐0248200801170x

emspensp emsp | emsp11Li et aL

Poisot T Gueacuteveneux‐Julien C FortinM‐J Gravel D amp LegendreP (2017)Hostsparasitesandtheir interactionsrespondtodiffer‐entclimaticvariablesGlobal Ecology and Biogeography26942ndash951httpsdoiorg101111geb12602

PoisotTStoufferDBampGravelD(2015)BeyondspeciesWhyeco‐logicalinteractionnetworksvarythroughspaceandtimeOikos124243ndash251httpsdoiorg101111oik01719

RCoreTeam(2017)R A language and environment for statistical comput-ingViennaAustriaRFoundationforStatisticalComputing

RockwellRFGormezanoLJampKoonsDN(2011)TrophicmatchesandmismatchesCanpolarbearsreducetheabundanceofnestingsnowgeese inwesternHudsonBayOikos120696ndash709httpsdoiorg101111j1600‐0706201018837x

RogersDARooneyTPOlsonDampWallerDM(2008)ShiftsinsouthernWisconsin forest canopy and understory richness com‐position and heterogeneity Ecology 89 2482ndash2492 httpsdoiorg10189007‐11291

RooneyTPWiegmannSMRogersDAampWallerDM (2004)BioticimpoverishmentandhomogenizationinunfragmentedforestunderstorycommunitiesConservation Biology18787ndash798httpsdoiorg101111j1523‐1739200400515x

SalaOEChapinFSArmestoJJBerlowEBloomfieldJDirzoRhellipLeemansR(2000)Globalbiodiversityscenariosfortheyear2100 Science2871770ndash1774

TullochAIChadegravesIampLindenmayerDB(2018)Speciesco‐occur‐renceanalysispredictsmanagementoutcomesformultiplethreatsNature Ecology amp Evolution 2 465ndash474 httpsdoiorg101038s41559‐017‐0457‐3

Tylianakis J M Didham R K Bascompte J amp Wardle D A(2008) Global change and species interactions in terres‐trial ecosystems Ecology Letters 11 1351ndash1363 httpsdoiorg101111j1461‐0248200801250x

Tylianakis J M amp Morris R J (2017) Ecological networksacross environmental gradients Annual Review of Ecology

Evolution and Systematics 48 25ndash48 httpsdoiorg101146annurev‐ecolsys‐110316‐022821

Tylianakis JM Tscharntke Tamp LewisO T (2007)Habitatmodifi‐cation alters the structure of tropical hostndashparasitoid food websNature445202ndash205httpsdoiorg101038nature05429

Valiente‐BanuetAAizenMAAlcaacutentaraJMArroyoJCocucciAGalettiMhellipJordanoP(2015)BeyondspecieslossTheextinctionofecologicalinteractionsinachangingworldFunctional Ecology29299ndash307httpsdoiorg1011111365‐243512356

Vitousek PMMooneyHA Lubchenco JampMelillo JM (1997)Human domination of earthrsquos ecosystems Science 277 494ndash499httpsdoiorg101126science2775325494

Waller DM Amatangelo K L Johnson S amp Rogers D A (2012)Wisconsinvegetationdatabasendashplantcommunitysurveyandresur‐veydatafromtheWisconsinplantecologylaboratoryBiodiversity amp Ecology4255ndash264httpsdoiorg107809b‐e00082

SUPPORTING INFORMATION

Additional supporting information may be found online in theSupportingInformationsectionattheendofthearticle

How to cite this articleLiDPoisotTWallerDMBaiserBHomogenizationofspeciescompositionandspeciesassociationnetworksaredecoupledGlobal Ecol Biogeogr 2018001ndash11 httpsdoiorg101111geb12825

Page 7: Homogenization of species composition and species ... · L I ET A L. | 3 biotic homogenization in species composition (Li & Waller, 2015; Rogers, Rooney, Olson, & Waller, 2008; Rooney

emspensp emsp | emsp7Li et aL

to fire suppression and succession filtering out shade‐intolerantspecies(LiampWaller2017)andhomogenizingplantcommunities(LiampWaller2015)Giventheseecologicalchangesitisnotsurprisingtofindsignificanthomogenizationinbothspeciescompositionandpositivespeciesassociationsinthesecommunities

SitesintheSUFhavebeenaffectedbydevelopmentandland‐use changes more than any other plant community inWisconsin(Rogersetal2008)Currentlymostofthesesitesarefragmentedanddisturbedbynearbyanthropogenic activities including roadsdevelopmentandagriculturePreviousstudiessuggestthathabitatdegradationandfragmentationtendtohomogenizespeciescompo‐sitionbydecreasingspeciesdiversitywhichcanalsoreducenetworkcomplexityandstability(LaliberteacuteampTylianakis2010Mokrossetal2014Tylianakisetal2007)However the fact thathabitat frag‐mentationcan result ingreaterdifferences in interactionnetworkstructure(Bordesetal2015)suggeststhatnetworksimplification(fewer nodes andor edges) does not necessarily cause networkhomogenizationNetworkscandifferacrosssites if individualnet‐workscontainuniqueinteractionseveniftheyshowageneraltrendtowards simplification In theseSUFcommunities the importanceofspeciesdispersallimitationandstochasticfactorshasincreasedwhereastheimportanceofspeciesinteractionshasdecreasedovertime(LiampWaller2016)Itisthuslikelythatstochasticassemblypro‐cesses are formingnovel sets of interactions among species eventhoughspeciesdiversityhasdecreasedIndeedwefoundonaver‐age964significantpositivespeciespairspersiteinthe1950sbutonly603significantpositivepairspersiteinthe2000sindicatingthatassociationnetworksateachsitehavesimplifiedHoweverboththepairedrandomizationtestonpairwisebetadiversityofpositiveassociationnetworksandPERMDISPsuggestedthatpositiveasso‐ciationnetworks inthe2000shavedifferentiatedsincethe1950s(Table2)ThereforeintheSUFwefoundhomogenizationofspeciescompositionbutdifferentiationofspeciespositiveassociations

Although changes in species associations are occurring fasterthan changes in species composition and appear decoupled fromthembotharegenerallyaffectedbysimilarsetsofenvironmentalvariables (Table 3) For example positive species associations andcomposition at all siteswithin each time periodwere affected bythesamesetofenvironmentalvariablesHowevertheimportanceofenvironmentalvariablesforspeciesassociationsandcompositionhaschangedovertimefortheCSPandSUFSpeciesassociationsandcompositionintheCSPweremostaffectedbycanopyshadeinthe1950swithclimaticfactorsplayingnoroleforpositiveassociationsandspeciescompositionBy the2000sclimaticvariablesbecamemoreimportantthancanopyshadeThisreflectsthefactthatCSPforestswith closed canopies show little variation in canopy coverinthe2000sIntheSUFminimaltemperatureusedtobemoreim‐portantthanprecipitationforspeciescompositionandpositiveas‐sociationsthispatternreversedinthe2000sTheseresultssuggestthatspeciesassociationsandcompositionaregenerallyaffectedbya similar set of environmental variables As global environmentalchangesacceleratetherelative importanceofenvironmentalvari‐ablesmaychange further contributing to theemergenceofnovelTA

BLE

2emspHomogenizationinspeciescompositiondoesnotalwaysresultinthehomogenizationofspeciesassociationnetworks

Ave_1950(pairwise)

Ave_2000(pairwise)

Ave_1950(permdisp)

Ave_2000(permdisp)

Direction(pairwise)

Direction(permdisp)

NUF

SpeComp

059

50587

051

30

51homog

nochange

PosAssoc

0778

0785

0561

0566

diff

nochange

NegAssoc

089

10887

0636

0633

homog

nochange

CSP

SpeComp

0447

029

90418

0327

homog

homog

PosAssoc

0683

0442

0496

0314

homog

homog

NegAssoc

080

50806

0574

0575

nochange

nochange

SUF

SpeComp

0572

0546

0516

0497

homog

homog

PosAssoc

0736

0782

0527

0567

diff

diff

NegAssoc

0862

0841

0615

0603

homog

nochange

Not

eNumbersintheave_1950(pairwise)andave_2000(pairwise)columnsrepresentaveragepairwisebetadiversitybetweensiteswithinthesamevegetationtypeinthe1950sandthe2000srespec‐

tivelyNumbersintheave_1950(permdisp)andave_2000(permdisp)columnsrepresenttheaveragedistancetothegroupcentroidintheordinationsofsiteswithinthesamevegetationtypeinthe1950s

andthe2000srespectivelyThecolumndirection(pairwise)indicatesdirectionsofchangesinthepairwisesitebetadiversityovertimetestedwithpairedrandomizationtestsThecolumndirection

(permdisp)indicatesdirectionsofchangesinthedistancebetweensitesandtheordinationcentroidovertimetestedwithpermutationtestsAbbreviationsdiffdifferentiationhomoghomogenization

NegAssocnegativeassociationPosAssocpositiveassociationSpeCompspeciescompositionplt005plt001

p lt

000

1

8emsp |emsp emspensp Li et aL

Vegetationtype Date Variable Shade Precipitation Minimaltemperature

NUF 1950s SpeComp ndash 2 1

PosAssoc ndash 2 1

NegAssoc ndash 2 1

2000s SpeComp ndash 2 1

PosAssoc ndash 2 1

NegAssoc ndash 2 1

CSP 1950s SpeComp 1

PosAssoc 1

NegAssoc 1 2

2000s SpeComp 2 1

PosAssoc 3 1 2

NegAssoc 2 1

SUF 1950s SpeComp ndash 2 1

PosAssoc ndash 2 1

NegAssoc ndash 1 2

2000s SpeComp ndash 1 2

PosAssoc ndash 1 2

NegAssoc ndash 1 2

NoteNumbersaretheorderinwhichvariablesareselectedDash(ndash)meansthattheenvironmentalvariableisnotavailableBlankcellsmeanthatthesevariablesaredroppedoutAbbreviationsNegAssocnegativeassociationPosAssocpositiveassociationSpeCompspeciescomposition

TA B L E 3 emspSelectedenvironmentalvariablesforspeciescompositionandspeciesassociations

F I G U R E 2 emspBetadiversityofspeciescompositionandassociationofthesamesiteovertimeEachpointrepresentsthebetadiversityofthesamesitebetweenthe1950sandthe2000sBetadiversityofoneindicatesthatthespeciescompositionorspeciesassociationinthe1950sandthe2000sweretotallydifferentwhereasbetadiversityofzeroindicatesnochangesinasiteovertimeTurnoverinspeciesrelationshipsappearstobemuchgreaterthantheturnoverinspeciescomposition

NU

FC

SPSU

F

Species Composition Positive Association Negative Association

025

050

075

100

025

050

075

100

025

050

075

100

Beta

div

ersi

ty o

ver t

ime

at th

e sa

me

site

emspensp emsp | emsp9Li et aL

arraysofspeciesandconsequentspecies interactions (Bloisetal2013Milazzoetal2013)

Species association (co‐occurrence) patterns have commonlybeenusedtorepresentspeciesinteractionsbecauseitisintractabletoquantifyinteractionsamonghundredsofplantspeciesSpeciesassociations may give false‐positive (hypothesized links that donotexistintherealsystem)interactionsbetweenspeciesandmaynot detect all real interactions (Barner et al 2018DelalandreampMontesinos‐Navarro2018Freilichetal2018)Howeverourmaingoalistostudybroadpatternsofcommunitystructureanddynam‐ics rather than to pinpoint exact interactions between particularspeciespairsForthispurposespeciesspatialassociationnetworksareanecessaryandusefulproxy(Freilichetal2018)becausetheycanprovidevaluableinformationregardingthenetoutputofdirectandindirecteffectsamongmultipleplantspecies(ratherthanexactpairwise interactions Delalandre amp Montesinos‐Navarro 2018)Co‐occurrence networks may also serve to predict overall com‐munityresponsestodisturbance(TullochChadegravesampLindenmayer2018) To reduce thepotential for biaswe studied species asso‐ciation patterns at a fine spatial scale (1m2) and used statisticalmethods(BayesianGLMMs)thathaverelativelyhighpowerforde‐tecting species interactions (Harris 2016) Furthermoreweusedacommonnullmodelapproachand reported these results in theSupporting InformationAppendixGiven that bothmethods pro‐videquantitatively similar results and reach the sameconclusionour conclusion that changes in species associations and speciescompositionaredecoupledislikelytoberobustConsequentlyourresultsfromspeciesassociationnetworksmayalsoholdforspeciesinteractionnetworks

Anassumptionmadeinthisstudyisthatspeciesassociationswithin each vegetation type and timeperiod remain consistentacross sites In reality associations between species can varythroughspaceandtime(Poisotetal2015)Giventhatwelackedthedatatoanalysehowspeciesassociationsmayhavedifferedover siteswepooleddataacross sites togain insights into theaverage nature of species associationswithin each communityThismakesourresultsconservativebecauseaccountingforvari‐ation inspeciesassociationsoversitescouldshowonlygreatervariationinnetworkstructurestrengtheningourconclusionthattemporal changes in species associations and composition aredecoupled

Our results suggest that species relationshipsmay not be ex‐periencingageneraltrendtowardshomogenizationbecausenovelrelationships may be forming in response to rapid global changeThisraisesimportantquestionsabouthowsuchchangesinspeciesrelationshipsmightaffectcommunitystabilityecosystemservicesandspeciesco‐evolutionStudiesofbetadiversity inspecies rela‐tionshipsremainintheirinfancy(Burkleetal2016)Giventheim‐portanceofspeciesrelationshipsandtheirpotentialunpredictablerelationshipwithspeciescompositionfutureempiricalandtheoret‐icalresearchthatinvestigatespatternscausesandconsequencesofchangesinbetadiversityofrelationshipnetworksareneeded

5emsp |emspBIOSKETCH

Daijiang Liisapost‐doctoralresearcherattheDepartmentofWildlifeEcologyampConservationUniversityofFloridaHisresearchinterestscovercommunityecologyfunctionalandphylogeneticdiversitybi‐ologicalinvasionsglobalchangebiologyandecologicalmodelling

DATA ACCE SSIBILIT Y

The data used in this study have been deposited to figshare(httpsfigsharecoms5a98a69a66f22644361e) with httpsdoiorg106084m9figshare6771938

ORCID

Daijiang Li httporcidorg0000‐0002‐0925‐3421

Timotheacutee Poisot httporcidorg0000‐0002‐0735‐5184

Benjamin Baiser httporcidorg0000‐0002‐3573‐1183

R E FE R E N C E S

AmatangeloKLFultonMRRogersDAampWallerDM (2011)Convergingforestcommunitycompositionalonganedaphicgradi‐ent threatens landscape‐level diversityDiversity and Distributions17201ndash213httpsdoiorg101111j1472‐4642201000730x

AndersonMJ(2001)Anewmethodfornon‐parametricmultivariateanalysisofvarianceAustral Ecology2632ndash46

AndersonMJEllingsenKEampMcArdleBH (2006)MultivariatedispersionasameasureofbetadiversityEcology Letters9683ndash693httpsdoiorg101111j1461‐0248200600926x

Arauacutejo M B Rozenfeld A Rahbek C amp Marquet P A (2011)Using species co‐occurrence networks to assess the im‐pacts of climate change Ecography 34 897ndash908 httpsdoiorg101111j1600‐0587201106919x

AshJDGivnishTJampWallerDM(2017)Trackinglagsinhistori‐calplantspeciesrsquoshiftsinrelationtoregionalclimatechangeGlobal Change Biology231305ndash1315httpsdoiorg101111gcb13429

BaiserBOlden JDRecordSLockwoodJLampMcKinneyML(2012) Pattern and process of biotic homogenization in the newPangaeaProceedings of the Royal Society B Biological Sciences2794772ndash4777

Barner A K Coblentz K E Hacker S D amp Menge B A (2018)Fundamentalcontradictionsamongobservationalandexperimentalestimatesofnon‐trophicspeciesinteractionsEcology99557ndash566httpsdoiorg101002ecy2133

Bascompte J JordanoPampOlesen JM (2006)Asymmetriccoevo‐lutionarynetworksfacilitatebiodiversitymaintenanceScience312431ndash433httpsdoiorg101126science1123412

Blois J L Zarnetske P L FitzpatrickM C amp Finnegan S (2013)ClimatechangeandthepastpresentandfutureofbioticinteractionsScience341499ndash504httpsdoiorg101126science1237184

BordesFMorandSPilosofSClaudeJKrasnovBRCossonJ‐Fhellip Blasdell K (2015) Habitat fragmentation alters the propertiesofahostndashparasitenetworkRodentsand theirhelminths inSouth‐East Asia Journal of Animal Ecology 84 1253ndash1263 httpsdoiorg1011111365‐265612368

BurkleLAMyersJAampBeloteRT (2016)Thebeta‐diversityofspecies interactions Untangling the drivers of geographic vari‐ation in plantndashpollinator diversity and function across scales

10emsp |emsp emspensp Li et aL

American Journal of Botany103118ndash128httpsdoiorg103732ajb1500079

CaraDonna P J Petry W K Brennan R M Cunningham J LBronstein J LWaserNMamp SandersN J (2017) InteractionrewiringandtherapidturnoverofplantndashpollinatornetworksEcology Letters20385ndash394httpsdoiorg101111ele12740

CazellesKArauacutejoMBMouquetNampGravelD(2016)Atheoryforspeciesco‐occurrenceininteractionnetworksTheoretical Ecology939ndash48httpsdoiorg101007s12080‐015‐0281‐9

ConnorEFampSimberloffD(1979)Theassemblyofspeciescommu‐nitiesChanceorcompetitionEcology601132ndash1140httpsdoiorg1023071936961

CummingGSBodinOumlErnstsonHampElmqvistT(2010)Networkanalysis in conservation biogeography Challenges and oppor‐tunities Diversity and Distributions 16 414ndash425 httpsdoiorg101111j1472‐4642201000651x

CurtisJT(1959)The vegetation of Wisconsin An ordination of plant com-munitiesMadisonWIUniversityofWisconsinPress

de Solar R R C Barlow J Ferreira J Berenguer E Lees A CThompsonJRhellipGardnerTA(2015)Howpervasiveisbioticho‐mogenizationinhuman‐modifiedtropicalforestlandscapesEcology Letters181108ndash1118httpsdoiorg101111ele12494

DelalandreLampMontesinos‐NavarroA(2018)Canco‐occurrencenet‐works predict plant‐plant interactions in a semi‐arid gypsum com‐munityPerspectives in Plant Ecology Evolution and Systematics3136ndash43httpsdoiorg101016jppees201801001

Diamond JM (1975) Assembly of species communitiesEcology and Evolution of Communities342ndash444

FreilichMAWietersEBroitmanBMarquetPAampNavarreteSA(2018)Speciesco‐occurrencenetworksCantheyrevealtrophicandnon‐trophicinteractionsinecologicalcommunitiesEcology99690ndash699httpsdoiorg101002ecy2142

Gotelli N J (2000) Null model analysis of species co‐oc‐currence patterns Ecology 81 2606ndash2621 httpsdoiorg1018900012‐9658(2000)081[2606NMAOSC]20CO2

GotelliNJampGravesGR(1996)Null models in ecologyWashingtonDCSmithsonianInstitution

GotelliN JGravesGRampRahbekC (2010)Macroecological sig‐nalsofspeciesinteractionsintheDanishavifaunaProceedings of the National Academy of Sciences of the USA1075030ndash5035httpsdoiorg101073pnas0914089107

Hadfield JD (2010)MCMCmethods formulti‐responsegeneralizedlinearmixedmodelsTheMCMCglmmRpackageJournal of Statistical Software331ndash22

Harley C D (2011) Climate change keystone predation and biodi‐versity loss Science 334 1124ndash1127 httpsdoiorg101126science1210199

Harris D J (2016) Inferring species interactions from co‐occurrencedata with Markov networks Ecology 97 3308ndash3314 httpsdoiorg101002ecy1605

Harvey E Gounand I Ward C L amp Altermatt F (2017) Bridgingecology and conservation From ecological networks to ecosys‐tem function Journal of Applied Ecology 54 371ndash379 httpsdoiorg1011111365‐266412769

Hegland S J Nielsen A Laacutezaro A Bjerknes A‐L amp TotlandOslash (2009) How does climate warming affect plant‐pollina‐tor interactions Ecology Letters 12 184ndash195 httpsdoiorg101111j1461‐0248200801269x

Hobbs R J Higgs E amp Harris J A (2009) Novel ecosystemsImplicationsforconservationandrestorationTrends in Ecology and Evolution24599ndash605httpsdoiorg101016jtree200905012

Kehinde T amp Samways M J (2014) Effects of vineyard manage‐ment on biotic homogenization of insectndashflower interaction net‐works in the cape floristic region biodiversity hotspot Journal of Insect Conservation 18 469ndash477 httpsdoiorg101007s10841‐014‐9659‐z

Kucharik C J Serbin S P Vavrus S Hopkins E J amp MotewM M (2010) Patterns of climate change across Wisconsinfrom 1950 to 2006 Physical Geography 31 1ndash28 httpsdoiorg1027470272‐36463111

LaliberteacuteEampTylianakisJM(2010)Deforestationhomogenizestrop‐ical parasitoidndashhost networks Ecology 91 1740ndash1747 httpsdoiorg10189009‐13281

LegendrePampDeCaacuteceresM(2013)BetadiversityasthevarianceofcommunitydataDissimilaritycoefficientsandpartitioningEcology Letters16951ndash963httpsdoiorg101111ele12141

LegendrePampLegendreLF(2012)Numerical ecologyAmsterdamTheNetherlandsElsevier

LiDampWallerDM(2015)DriversofobservedbiotichomogenizationinpinebarrensofcentralWisconsinEcology961030ndash1041httpsdoiorg10189014‐08931

LiDampWallerDM (2016)Long‐termshifts inthepatternsandun‐derlyingprocessesofplantassociationsinWisconsinforestsGlobal Ecology and Biogeography 25 516ndash526 httpsdoiorg101111geb12432

LiDampWallerDM(2017)Fireexclusionandclimatechangeinteracttoaffect long‐termchanges in the functional compositionofplantcommunitiesDiversity and Distributions 23 496ndash506 httpsdoiorg101111ddi12542

LoreauMMouquetNampGonzalezA(2003)Biodiversityasspatialinsurance inheterogeneous landscapesProceedings of the National Academy of Sciences of the USA 100 12765ndash12770 httpsdoiorg101073pnas2235465100

MacLeod M Genung M A Ascher J S amp Winfree R (2016)Measuring partner choice in plantndashpollinator networks Using nullmodels to separate rewiring and fidelity from chanceEcology972925ndash2931httpsdoiorg101002ecy1574

McCannK(2007)ProtectingbiostructureNature44629ndash29httpsdoiorg101038446029a

McKinneyMLampLockwoodJL(1999)BiotichomogenizationAfewwinners replacingmany losers in the nextmass extinctionTrends in Ecology and Evolution 14 450ndash453 httpsdoiorg101016S0169‐5347(99)01679‐1

Milazzo M Mirto S Domenici P amp Gristina M (2013) Climatechange exacerbates interspecific interactions in sympatriccoastal fishes Journal of Animal Ecology 82 468ndash477 httpsdoiorg101111j1365‐2656201202034x

MokrossKRyderTBCocircrtesMCWolfe JDampStoufferPC(2014) Decay of interspecific avian flock networks along a dis‐turbance gradient in Amazonia Proceedings of the Royal Society B Biological Sciences28120132599

Morales‐Castilla IMatiasM G Gravel D amp ArauacutejoM B (2015)Inferring biotic interactions from proxies Trends in Ecology and Evolution30347ndash356httpsdoiorg101016jtree201503014

OksanenJBlanchetFGFriendlyMKindtRLegendrePMcGlinnDhellipWagnerH(2018)Vegan Community ecology packageRpack‐ageversion25‐2httpsCRANR‐projectorgpackage=vegan

OldenJDComteLampGiamX(2018)TheHomogoceneAresearchprospectusforthestudyofbiotichomogenisationNeoBiota3723httpsdoiorg103897neobiota3722552

OldenJDampPoffNL (2003)Towardamechanisticunderstandingand prediction of biotic homogenization The American Naturalist162442ndash460httpsdoiorg101086378212

OldenJDPoffNLDouglasMRDouglasMEampFauschKD(2004)Ecologicalandevolutionaryconsequencesofbiotichomog‐enization Trends in Ecology and Evolution 19 18ndash24 httpsdoiorg101016jtree200309010

PetanidouTKallimanisASTzanopoulosJSgardelisSPampPantisJD(2008)Long‐termobservationofapollinationnetworkFluctuationinspeciesandinteractionsrelativeinvarianceofnetworkstructureand implicationsforestimatesofspecializationEcology Letters11564ndash575httpsdoiorg101111j1461‐0248200801170x

emspensp emsp | emsp11Li et aL

Poisot T Gueacuteveneux‐Julien C FortinM‐J Gravel D amp LegendreP (2017)Hostsparasitesandtheir interactionsrespondtodiffer‐entclimaticvariablesGlobal Ecology and Biogeography26942ndash951httpsdoiorg101111geb12602

PoisotTStoufferDBampGravelD(2015)BeyondspeciesWhyeco‐logicalinteractionnetworksvarythroughspaceandtimeOikos124243ndash251httpsdoiorg101111oik01719

RCoreTeam(2017)R A language and environment for statistical comput-ingViennaAustriaRFoundationforStatisticalComputing

RockwellRFGormezanoLJampKoonsDN(2011)TrophicmatchesandmismatchesCanpolarbearsreducetheabundanceofnestingsnowgeese inwesternHudsonBayOikos120696ndash709httpsdoiorg101111j1600‐0706201018837x

RogersDARooneyTPOlsonDampWallerDM(2008)ShiftsinsouthernWisconsin forest canopy and understory richness com‐position and heterogeneity Ecology 89 2482ndash2492 httpsdoiorg10189007‐11291

RooneyTPWiegmannSMRogersDAampWallerDM (2004)BioticimpoverishmentandhomogenizationinunfragmentedforestunderstorycommunitiesConservation Biology18787ndash798httpsdoiorg101111j1523‐1739200400515x

SalaOEChapinFSArmestoJJBerlowEBloomfieldJDirzoRhellipLeemansR(2000)Globalbiodiversityscenariosfortheyear2100 Science2871770ndash1774

TullochAIChadegravesIampLindenmayerDB(2018)Speciesco‐occur‐renceanalysispredictsmanagementoutcomesformultiplethreatsNature Ecology amp Evolution 2 465ndash474 httpsdoiorg101038s41559‐017‐0457‐3

Tylianakis J M Didham R K Bascompte J amp Wardle D A(2008) Global change and species interactions in terres‐trial ecosystems Ecology Letters 11 1351ndash1363 httpsdoiorg101111j1461‐0248200801250x

Tylianakis J M amp Morris R J (2017) Ecological networksacross environmental gradients Annual Review of Ecology

Evolution and Systematics 48 25ndash48 httpsdoiorg101146annurev‐ecolsys‐110316‐022821

Tylianakis JM Tscharntke Tamp LewisO T (2007)Habitatmodifi‐cation alters the structure of tropical hostndashparasitoid food websNature445202ndash205httpsdoiorg101038nature05429

Valiente‐BanuetAAizenMAAlcaacutentaraJMArroyoJCocucciAGalettiMhellipJordanoP(2015)BeyondspecieslossTheextinctionofecologicalinteractionsinachangingworldFunctional Ecology29299ndash307httpsdoiorg1011111365‐243512356

Vitousek PMMooneyHA Lubchenco JampMelillo JM (1997)Human domination of earthrsquos ecosystems Science 277 494ndash499httpsdoiorg101126science2775325494

Waller DM Amatangelo K L Johnson S amp Rogers D A (2012)Wisconsinvegetationdatabasendashplantcommunitysurveyandresur‐veydatafromtheWisconsinplantecologylaboratoryBiodiversity amp Ecology4255ndash264httpsdoiorg107809b‐e00082

SUPPORTING INFORMATION

Additional supporting information may be found online in theSupportingInformationsectionattheendofthearticle

How to cite this articleLiDPoisotTWallerDMBaiserBHomogenizationofspeciescompositionandspeciesassociationnetworksaredecoupledGlobal Ecol Biogeogr 2018001ndash11 httpsdoiorg101111geb12825

Page 8: Homogenization of species composition and species ... · L I ET A L. | 3 biotic homogenization in species composition (Li & Waller, 2015; Rogers, Rooney, Olson, & Waller, 2008; Rooney

8emsp |emsp emspensp Li et aL

Vegetationtype Date Variable Shade Precipitation Minimaltemperature

NUF 1950s SpeComp ndash 2 1

PosAssoc ndash 2 1

NegAssoc ndash 2 1

2000s SpeComp ndash 2 1

PosAssoc ndash 2 1

NegAssoc ndash 2 1

CSP 1950s SpeComp 1

PosAssoc 1

NegAssoc 1 2

2000s SpeComp 2 1

PosAssoc 3 1 2

NegAssoc 2 1

SUF 1950s SpeComp ndash 2 1

PosAssoc ndash 2 1

NegAssoc ndash 1 2

2000s SpeComp ndash 1 2

PosAssoc ndash 1 2

NegAssoc ndash 1 2

NoteNumbersaretheorderinwhichvariablesareselectedDash(ndash)meansthattheenvironmentalvariableisnotavailableBlankcellsmeanthatthesevariablesaredroppedoutAbbreviationsNegAssocnegativeassociationPosAssocpositiveassociationSpeCompspeciescomposition

TA B L E 3 emspSelectedenvironmentalvariablesforspeciescompositionandspeciesassociations

F I G U R E 2 emspBetadiversityofspeciescompositionandassociationofthesamesiteovertimeEachpointrepresentsthebetadiversityofthesamesitebetweenthe1950sandthe2000sBetadiversityofoneindicatesthatthespeciescompositionorspeciesassociationinthe1950sandthe2000sweretotallydifferentwhereasbetadiversityofzeroindicatesnochangesinasiteovertimeTurnoverinspeciesrelationshipsappearstobemuchgreaterthantheturnoverinspeciescomposition

NU

FC

SPSU

F

Species Composition Positive Association Negative Association

025

050

075

100

025

050

075

100

025

050

075

100

Beta

div

ersi

ty o

ver t

ime

at th

e sa

me

site

emspensp emsp | emsp9Li et aL

arraysofspeciesandconsequentspecies interactions (Bloisetal2013Milazzoetal2013)

Species association (co‐occurrence) patterns have commonlybeenusedtorepresentspeciesinteractionsbecauseitisintractabletoquantifyinteractionsamonghundredsofplantspeciesSpeciesassociations may give false‐positive (hypothesized links that donotexistintherealsystem)interactionsbetweenspeciesandmaynot detect all real interactions (Barner et al 2018DelalandreampMontesinos‐Navarro2018Freilichetal2018)Howeverourmaingoalistostudybroadpatternsofcommunitystructureanddynam‐ics rather than to pinpoint exact interactions between particularspeciespairsForthispurposespeciesspatialassociationnetworksareanecessaryandusefulproxy(Freilichetal2018)becausetheycanprovidevaluableinformationregardingthenetoutputofdirectandindirecteffectsamongmultipleplantspecies(ratherthanexactpairwise interactions Delalandre amp Montesinos‐Navarro 2018)Co‐occurrence networks may also serve to predict overall com‐munityresponsestodisturbance(TullochChadegravesampLindenmayer2018) To reduce thepotential for biaswe studied species asso‐ciation patterns at a fine spatial scale (1m2) and used statisticalmethods(BayesianGLMMs)thathaverelativelyhighpowerforde‐tecting species interactions (Harris 2016) Furthermoreweusedacommonnullmodelapproachand reported these results in theSupporting InformationAppendixGiven that bothmethods pro‐videquantitatively similar results and reach the sameconclusionour conclusion that changes in species associations and speciescompositionaredecoupledislikelytoberobustConsequentlyourresultsfromspeciesassociationnetworksmayalsoholdforspeciesinteractionnetworks

Anassumptionmadeinthisstudyisthatspeciesassociationswithin each vegetation type and timeperiod remain consistentacross sites In reality associations between species can varythroughspaceandtime(Poisotetal2015)Giventhatwelackedthedatatoanalysehowspeciesassociationsmayhavedifferedover siteswepooleddataacross sites togain insights into theaverage nature of species associationswithin each communityThismakesourresultsconservativebecauseaccountingforvari‐ation inspeciesassociationsoversitescouldshowonlygreatervariationinnetworkstructurestrengtheningourconclusionthattemporal changes in species associations and composition aredecoupled

Our results suggest that species relationshipsmay not be ex‐periencingageneraltrendtowardshomogenizationbecausenovelrelationships may be forming in response to rapid global changeThisraisesimportantquestionsabouthowsuchchangesinspeciesrelationshipsmightaffectcommunitystabilityecosystemservicesandspeciesco‐evolutionStudiesofbetadiversity inspecies rela‐tionshipsremainintheirinfancy(Burkleetal2016)Giventheim‐portanceofspeciesrelationshipsandtheirpotentialunpredictablerelationshipwithspeciescompositionfutureempiricalandtheoret‐icalresearchthatinvestigatespatternscausesandconsequencesofchangesinbetadiversityofrelationshipnetworksareneeded

5emsp |emspBIOSKETCH

Daijiang Liisapost‐doctoralresearcherattheDepartmentofWildlifeEcologyampConservationUniversityofFloridaHisresearchinterestscovercommunityecologyfunctionalandphylogeneticdiversitybi‐ologicalinvasionsglobalchangebiologyandecologicalmodelling

DATA ACCE SSIBILIT Y

The data used in this study have been deposited to figshare(httpsfigsharecoms5a98a69a66f22644361e) with httpsdoiorg106084m9figshare6771938

ORCID

Daijiang Li httporcidorg0000‐0002‐0925‐3421

Timotheacutee Poisot httporcidorg0000‐0002‐0735‐5184

Benjamin Baiser httporcidorg0000‐0002‐3573‐1183

R E FE R E N C E S

AmatangeloKLFultonMRRogersDAampWallerDM (2011)Convergingforestcommunitycompositionalonganedaphicgradi‐ent threatens landscape‐level diversityDiversity and Distributions17201ndash213httpsdoiorg101111j1472‐4642201000730x

AndersonMJ(2001)Anewmethodfornon‐parametricmultivariateanalysisofvarianceAustral Ecology2632ndash46

AndersonMJEllingsenKEampMcArdleBH (2006)MultivariatedispersionasameasureofbetadiversityEcology Letters9683ndash693httpsdoiorg101111j1461‐0248200600926x

Arauacutejo M B Rozenfeld A Rahbek C amp Marquet P A (2011)Using species co‐occurrence networks to assess the im‐pacts of climate change Ecography 34 897ndash908 httpsdoiorg101111j1600‐0587201106919x

AshJDGivnishTJampWallerDM(2017)Trackinglagsinhistori‐calplantspeciesrsquoshiftsinrelationtoregionalclimatechangeGlobal Change Biology231305ndash1315httpsdoiorg101111gcb13429

BaiserBOlden JDRecordSLockwoodJLampMcKinneyML(2012) Pattern and process of biotic homogenization in the newPangaeaProceedings of the Royal Society B Biological Sciences2794772ndash4777

Barner A K Coblentz K E Hacker S D amp Menge B A (2018)Fundamentalcontradictionsamongobservationalandexperimentalestimatesofnon‐trophicspeciesinteractionsEcology99557ndash566httpsdoiorg101002ecy2133

Bascompte J JordanoPampOlesen JM (2006)Asymmetriccoevo‐lutionarynetworksfacilitatebiodiversitymaintenanceScience312431ndash433httpsdoiorg101126science1123412

Blois J L Zarnetske P L FitzpatrickM C amp Finnegan S (2013)ClimatechangeandthepastpresentandfutureofbioticinteractionsScience341499ndash504httpsdoiorg101126science1237184

BordesFMorandSPilosofSClaudeJKrasnovBRCossonJ‐Fhellip Blasdell K (2015) Habitat fragmentation alters the propertiesofahostndashparasitenetworkRodentsand theirhelminths inSouth‐East Asia Journal of Animal Ecology 84 1253ndash1263 httpsdoiorg1011111365‐265612368

BurkleLAMyersJAampBeloteRT (2016)Thebeta‐diversityofspecies interactions Untangling the drivers of geographic vari‐ation in plantndashpollinator diversity and function across scales

10emsp |emsp emspensp Li et aL

American Journal of Botany103118ndash128httpsdoiorg103732ajb1500079

CaraDonna P J Petry W K Brennan R M Cunningham J LBronstein J LWaserNMamp SandersN J (2017) InteractionrewiringandtherapidturnoverofplantndashpollinatornetworksEcology Letters20385ndash394httpsdoiorg101111ele12740

CazellesKArauacutejoMBMouquetNampGravelD(2016)Atheoryforspeciesco‐occurrenceininteractionnetworksTheoretical Ecology939ndash48httpsdoiorg101007s12080‐015‐0281‐9

ConnorEFampSimberloffD(1979)Theassemblyofspeciescommu‐nitiesChanceorcompetitionEcology601132ndash1140httpsdoiorg1023071936961

CummingGSBodinOumlErnstsonHampElmqvistT(2010)Networkanalysis in conservation biogeography Challenges and oppor‐tunities Diversity and Distributions 16 414ndash425 httpsdoiorg101111j1472‐4642201000651x

CurtisJT(1959)The vegetation of Wisconsin An ordination of plant com-munitiesMadisonWIUniversityofWisconsinPress

de Solar R R C Barlow J Ferreira J Berenguer E Lees A CThompsonJRhellipGardnerTA(2015)Howpervasiveisbioticho‐mogenizationinhuman‐modifiedtropicalforestlandscapesEcology Letters181108ndash1118httpsdoiorg101111ele12494

DelalandreLampMontesinos‐NavarroA(2018)Canco‐occurrencenet‐works predict plant‐plant interactions in a semi‐arid gypsum com‐munityPerspectives in Plant Ecology Evolution and Systematics3136ndash43httpsdoiorg101016jppees201801001

Diamond JM (1975) Assembly of species communitiesEcology and Evolution of Communities342ndash444

FreilichMAWietersEBroitmanBMarquetPAampNavarreteSA(2018)Speciesco‐occurrencenetworksCantheyrevealtrophicandnon‐trophicinteractionsinecologicalcommunitiesEcology99690ndash699httpsdoiorg101002ecy2142

Gotelli N J (2000) Null model analysis of species co‐oc‐currence patterns Ecology 81 2606ndash2621 httpsdoiorg1018900012‐9658(2000)081[2606NMAOSC]20CO2

GotelliNJampGravesGR(1996)Null models in ecologyWashingtonDCSmithsonianInstitution

GotelliN JGravesGRampRahbekC (2010)Macroecological sig‐nalsofspeciesinteractionsintheDanishavifaunaProceedings of the National Academy of Sciences of the USA1075030ndash5035httpsdoiorg101073pnas0914089107

Hadfield JD (2010)MCMCmethods formulti‐responsegeneralizedlinearmixedmodelsTheMCMCglmmRpackageJournal of Statistical Software331ndash22

Harley C D (2011) Climate change keystone predation and biodi‐versity loss Science 334 1124ndash1127 httpsdoiorg101126science1210199

Harris D J (2016) Inferring species interactions from co‐occurrencedata with Markov networks Ecology 97 3308ndash3314 httpsdoiorg101002ecy1605

Harvey E Gounand I Ward C L amp Altermatt F (2017) Bridgingecology and conservation From ecological networks to ecosys‐tem function Journal of Applied Ecology 54 371ndash379 httpsdoiorg1011111365‐266412769

Hegland S J Nielsen A Laacutezaro A Bjerknes A‐L amp TotlandOslash (2009) How does climate warming affect plant‐pollina‐tor interactions Ecology Letters 12 184ndash195 httpsdoiorg101111j1461‐0248200801269x

Hobbs R J Higgs E amp Harris J A (2009) Novel ecosystemsImplicationsforconservationandrestorationTrends in Ecology and Evolution24599ndash605httpsdoiorg101016jtree200905012

Kehinde T amp Samways M J (2014) Effects of vineyard manage‐ment on biotic homogenization of insectndashflower interaction net‐works in the cape floristic region biodiversity hotspot Journal of Insect Conservation 18 469ndash477 httpsdoiorg101007s10841‐014‐9659‐z

Kucharik C J Serbin S P Vavrus S Hopkins E J amp MotewM M (2010) Patterns of climate change across Wisconsinfrom 1950 to 2006 Physical Geography 31 1ndash28 httpsdoiorg1027470272‐36463111

LaliberteacuteEampTylianakisJM(2010)Deforestationhomogenizestrop‐ical parasitoidndashhost networks Ecology 91 1740ndash1747 httpsdoiorg10189009‐13281

LegendrePampDeCaacuteceresM(2013)BetadiversityasthevarianceofcommunitydataDissimilaritycoefficientsandpartitioningEcology Letters16951ndash963httpsdoiorg101111ele12141

LegendrePampLegendreLF(2012)Numerical ecologyAmsterdamTheNetherlandsElsevier

LiDampWallerDM(2015)DriversofobservedbiotichomogenizationinpinebarrensofcentralWisconsinEcology961030ndash1041httpsdoiorg10189014‐08931

LiDampWallerDM (2016)Long‐termshifts inthepatternsandun‐derlyingprocessesofplantassociationsinWisconsinforestsGlobal Ecology and Biogeography 25 516ndash526 httpsdoiorg101111geb12432

LiDampWallerDM(2017)Fireexclusionandclimatechangeinteracttoaffect long‐termchanges in the functional compositionofplantcommunitiesDiversity and Distributions 23 496ndash506 httpsdoiorg101111ddi12542

LoreauMMouquetNampGonzalezA(2003)Biodiversityasspatialinsurance inheterogeneous landscapesProceedings of the National Academy of Sciences of the USA 100 12765ndash12770 httpsdoiorg101073pnas2235465100

MacLeod M Genung M A Ascher J S amp Winfree R (2016)Measuring partner choice in plantndashpollinator networks Using nullmodels to separate rewiring and fidelity from chanceEcology972925ndash2931httpsdoiorg101002ecy1574

McCannK(2007)ProtectingbiostructureNature44629ndash29httpsdoiorg101038446029a

McKinneyMLampLockwoodJL(1999)BiotichomogenizationAfewwinners replacingmany losers in the nextmass extinctionTrends in Ecology and Evolution 14 450ndash453 httpsdoiorg101016S0169‐5347(99)01679‐1

Milazzo M Mirto S Domenici P amp Gristina M (2013) Climatechange exacerbates interspecific interactions in sympatriccoastal fishes Journal of Animal Ecology 82 468ndash477 httpsdoiorg101111j1365‐2656201202034x

MokrossKRyderTBCocircrtesMCWolfe JDampStoufferPC(2014) Decay of interspecific avian flock networks along a dis‐turbance gradient in Amazonia Proceedings of the Royal Society B Biological Sciences28120132599

Morales‐Castilla IMatiasM G Gravel D amp ArauacutejoM B (2015)Inferring biotic interactions from proxies Trends in Ecology and Evolution30347ndash356httpsdoiorg101016jtree201503014

OksanenJBlanchetFGFriendlyMKindtRLegendrePMcGlinnDhellipWagnerH(2018)Vegan Community ecology packageRpack‐ageversion25‐2httpsCRANR‐projectorgpackage=vegan

OldenJDComteLampGiamX(2018)TheHomogoceneAresearchprospectusforthestudyofbiotichomogenisationNeoBiota3723httpsdoiorg103897neobiota3722552

OldenJDampPoffNL (2003)Towardamechanisticunderstandingand prediction of biotic homogenization The American Naturalist162442ndash460httpsdoiorg101086378212

OldenJDPoffNLDouglasMRDouglasMEampFauschKD(2004)Ecologicalandevolutionaryconsequencesofbiotichomog‐enization Trends in Ecology and Evolution 19 18ndash24 httpsdoiorg101016jtree200309010

PetanidouTKallimanisASTzanopoulosJSgardelisSPampPantisJD(2008)Long‐termobservationofapollinationnetworkFluctuationinspeciesandinteractionsrelativeinvarianceofnetworkstructureand implicationsforestimatesofspecializationEcology Letters11564ndash575httpsdoiorg101111j1461‐0248200801170x

emspensp emsp | emsp11Li et aL

Poisot T Gueacuteveneux‐Julien C FortinM‐J Gravel D amp LegendreP (2017)Hostsparasitesandtheir interactionsrespondtodiffer‐entclimaticvariablesGlobal Ecology and Biogeography26942ndash951httpsdoiorg101111geb12602

PoisotTStoufferDBampGravelD(2015)BeyondspeciesWhyeco‐logicalinteractionnetworksvarythroughspaceandtimeOikos124243ndash251httpsdoiorg101111oik01719

RCoreTeam(2017)R A language and environment for statistical comput-ingViennaAustriaRFoundationforStatisticalComputing

RockwellRFGormezanoLJampKoonsDN(2011)TrophicmatchesandmismatchesCanpolarbearsreducetheabundanceofnestingsnowgeese inwesternHudsonBayOikos120696ndash709httpsdoiorg101111j1600‐0706201018837x

RogersDARooneyTPOlsonDampWallerDM(2008)ShiftsinsouthernWisconsin forest canopy and understory richness com‐position and heterogeneity Ecology 89 2482ndash2492 httpsdoiorg10189007‐11291

RooneyTPWiegmannSMRogersDAampWallerDM (2004)BioticimpoverishmentandhomogenizationinunfragmentedforestunderstorycommunitiesConservation Biology18787ndash798httpsdoiorg101111j1523‐1739200400515x

SalaOEChapinFSArmestoJJBerlowEBloomfieldJDirzoRhellipLeemansR(2000)Globalbiodiversityscenariosfortheyear2100 Science2871770ndash1774

TullochAIChadegravesIampLindenmayerDB(2018)Speciesco‐occur‐renceanalysispredictsmanagementoutcomesformultiplethreatsNature Ecology amp Evolution 2 465ndash474 httpsdoiorg101038s41559‐017‐0457‐3

Tylianakis J M Didham R K Bascompte J amp Wardle D A(2008) Global change and species interactions in terres‐trial ecosystems Ecology Letters 11 1351ndash1363 httpsdoiorg101111j1461‐0248200801250x

Tylianakis J M amp Morris R J (2017) Ecological networksacross environmental gradients Annual Review of Ecology

Evolution and Systematics 48 25ndash48 httpsdoiorg101146annurev‐ecolsys‐110316‐022821

Tylianakis JM Tscharntke Tamp LewisO T (2007)Habitatmodifi‐cation alters the structure of tropical hostndashparasitoid food websNature445202ndash205httpsdoiorg101038nature05429

Valiente‐BanuetAAizenMAAlcaacutentaraJMArroyoJCocucciAGalettiMhellipJordanoP(2015)BeyondspecieslossTheextinctionofecologicalinteractionsinachangingworldFunctional Ecology29299ndash307httpsdoiorg1011111365‐243512356

Vitousek PMMooneyHA Lubchenco JampMelillo JM (1997)Human domination of earthrsquos ecosystems Science 277 494ndash499httpsdoiorg101126science2775325494

Waller DM Amatangelo K L Johnson S amp Rogers D A (2012)Wisconsinvegetationdatabasendashplantcommunitysurveyandresur‐veydatafromtheWisconsinplantecologylaboratoryBiodiversity amp Ecology4255ndash264httpsdoiorg107809b‐e00082

SUPPORTING INFORMATION

Additional supporting information may be found online in theSupportingInformationsectionattheendofthearticle

How to cite this articleLiDPoisotTWallerDMBaiserBHomogenizationofspeciescompositionandspeciesassociationnetworksaredecoupledGlobal Ecol Biogeogr 2018001ndash11 httpsdoiorg101111geb12825

Page 9: Homogenization of species composition and species ... · L I ET A L. | 3 biotic homogenization in species composition (Li & Waller, 2015; Rogers, Rooney, Olson, & Waller, 2008; Rooney

emspensp emsp | emsp9Li et aL

arraysofspeciesandconsequentspecies interactions (Bloisetal2013Milazzoetal2013)

Species association (co‐occurrence) patterns have commonlybeenusedtorepresentspeciesinteractionsbecauseitisintractabletoquantifyinteractionsamonghundredsofplantspeciesSpeciesassociations may give false‐positive (hypothesized links that donotexistintherealsystem)interactionsbetweenspeciesandmaynot detect all real interactions (Barner et al 2018DelalandreampMontesinos‐Navarro2018Freilichetal2018)Howeverourmaingoalistostudybroadpatternsofcommunitystructureanddynam‐ics rather than to pinpoint exact interactions between particularspeciespairsForthispurposespeciesspatialassociationnetworksareanecessaryandusefulproxy(Freilichetal2018)becausetheycanprovidevaluableinformationregardingthenetoutputofdirectandindirecteffectsamongmultipleplantspecies(ratherthanexactpairwise interactions Delalandre amp Montesinos‐Navarro 2018)Co‐occurrence networks may also serve to predict overall com‐munityresponsestodisturbance(TullochChadegravesampLindenmayer2018) To reduce thepotential for biaswe studied species asso‐ciation patterns at a fine spatial scale (1m2) and used statisticalmethods(BayesianGLMMs)thathaverelativelyhighpowerforde‐tecting species interactions (Harris 2016) Furthermoreweusedacommonnullmodelapproachand reported these results in theSupporting InformationAppendixGiven that bothmethods pro‐videquantitatively similar results and reach the sameconclusionour conclusion that changes in species associations and speciescompositionaredecoupledislikelytoberobustConsequentlyourresultsfromspeciesassociationnetworksmayalsoholdforspeciesinteractionnetworks

Anassumptionmadeinthisstudyisthatspeciesassociationswithin each vegetation type and timeperiod remain consistentacross sites In reality associations between species can varythroughspaceandtime(Poisotetal2015)Giventhatwelackedthedatatoanalysehowspeciesassociationsmayhavedifferedover siteswepooleddataacross sites togain insights into theaverage nature of species associationswithin each communityThismakesourresultsconservativebecauseaccountingforvari‐ation inspeciesassociationsoversitescouldshowonlygreatervariationinnetworkstructurestrengtheningourconclusionthattemporal changes in species associations and composition aredecoupled

Our results suggest that species relationshipsmay not be ex‐periencingageneraltrendtowardshomogenizationbecausenovelrelationships may be forming in response to rapid global changeThisraisesimportantquestionsabouthowsuchchangesinspeciesrelationshipsmightaffectcommunitystabilityecosystemservicesandspeciesco‐evolutionStudiesofbetadiversity inspecies rela‐tionshipsremainintheirinfancy(Burkleetal2016)Giventheim‐portanceofspeciesrelationshipsandtheirpotentialunpredictablerelationshipwithspeciescompositionfutureempiricalandtheoret‐icalresearchthatinvestigatespatternscausesandconsequencesofchangesinbetadiversityofrelationshipnetworksareneeded

5emsp |emspBIOSKETCH

Daijiang Liisapost‐doctoralresearcherattheDepartmentofWildlifeEcologyampConservationUniversityofFloridaHisresearchinterestscovercommunityecologyfunctionalandphylogeneticdiversitybi‐ologicalinvasionsglobalchangebiologyandecologicalmodelling

DATA ACCE SSIBILIT Y

The data used in this study have been deposited to figshare(httpsfigsharecoms5a98a69a66f22644361e) with httpsdoiorg106084m9figshare6771938

ORCID

Daijiang Li httporcidorg0000‐0002‐0925‐3421

Timotheacutee Poisot httporcidorg0000‐0002‐0735‐5184

Benjamin Baiser httporcidorg0000‐0002‐3573‐1183

R E FE R E N C E S

AmatangeloKLFultonMRRogersDAampWallerDM (2011)Convergingforestcommunitycompositionalonganedaphicgradi‐ent threatens landscape‐level diversityDiversity and Distributions17201ndash213httpsdoiorg101111j1472‐4642201000730x

AndersonMJ(2001)Anewmethodfornon‐parametricmultivariateanalysisofvarianceAustral Ecology2632ndash46

AndersonMJEllingsenKEampMcArdleBH (2006)MultivariatedispersionasameasureofbetadiversityEcology Letters9683ndash693httpsdoiorg101111j1461‐0248200600926x

Arauacutejo M B Rozenfeld A Rahbek C amp Marquet P A (2011)Using species co‐occurrence networks to assess the im‐pacts of climate change Ecography 34 897ndash908 httpsdoiorg101111j1600‐0587201106919x

AshJDGivnishTJampWallerDM(2017)Trackinglagsinhistori‐calplantspeciesrsquoshiftsinrelationtoregionalclimatechangeGlobal Change Biology231305ndash1315httpsdoiorg101111gcb13429

BaiserBOlden JDRecordSLockwoodJLampMcKinneyML(2012) Pattern and process of biotic homogenization in the newPangaeaProceedings of the Royal Society B Biological Sciences2794772ndash4777

Barner A K Coblentz K E Hacker S D amp Menge B A (2018)Fundamentalcontradictionsamongobservationalandexperimentalestimatesofnon‐trophicspeciesinteractionsEcology99557ndash566httpsdoiorg101002ecy2133

Bascompte J JordanoPampOlesen JM (2006)Asymmetriccoevo‐lutionarynetworksfacilitatebiodiversitymaintenanceScience312431ndash433httpsdoiorg101126science1123412

Blois J L Zarnetske P L FitzpatrickM C amp Finnegan S (2013)ClimatechangeandthepastpresentandfutureofbioticinteractionsScience341499ndash504httpsdoiorg101126science1237184

BordesFMorandSPilosofSClaudeJKrasnovBRCossonJ‐Fhellip Blasdell K (2015) Habitat fragmentation alters the propertiesofahostndashparasitenetworkRodentsand theirhelminths inSouth‐East Asia Journal of Animal Ecology 84 1253ndash1263 httpsdoiorg1011111365‐265612368

BurkleLAMyersJAampBeloteRT (2016)Thebeta‐diversityofspecies interactions Untangling the drivers of geographic vari‐ation in plantndashpollinator diversity and function across scales

10emsp |emsp emspensp Li et aL

American Journal of Botany103118ndash128httpsdoiorg103732ajb1500079

CaraDonna P J Petry W K Brennan R M Cunningham J LBronstein J LWaserNMamp SandersN J (2017) InteractionrewiringandtherapidturnoverofplantndashpollinatornetworksEcology Letters20385ndash394httpsdoiorg101111ele12740

CazellesKArauacutejoMBMouquetNampGravelD(2016)Atheoryforspeciesco‐occurrenceininteractionnetworksTheoretical Ecology939ndash48httpsdoiorg101007s12080‐015‐0281‐9

ConnorEFampSimberloffD(1979)Theassemblyofspeciescommu‐nitiesChanceorcompetitionEcology601132ndash1140httpsdoiorg1023071936961

CummingGSBodinOumlErnstsonHampElmqvistT(2010)Networkanalysis in conservation biogeography Challenges and oppor‐tunities Diversity and Distributions 16 414ndash425 httpsdoiorg101111j1472‐4642201000651x

CurtisJT(1959)The vegetation of Wisconsin An ordination of plant com-munitiesMadisonWIUniversityofWisconsinPress

de Solar R R C Barlow J Ferreira J Berenguer E Lees A CThompsonJRhellipGardnerTA(2015)Howpervasiveisbioticho‐mogenizationinhuman‐modifiedtropicalforestlandscapesEcology Letters181108ndash1118httpsdoiorg101111ele12494

DelalandreLampMontesinos‐NavarroA(2018)Canco‐occurrencenet‐works predict plant‐plant interactions in a semi‐arid gypsum com‐munityPerspectives in Plant Ecology Evolution and Systematics3136ndash43httpsdoiorg101016jppees201801001

Diamond JM (1975) Assembly of species communitiesEcology and Evolution of Communities342ndash444

FreilichMAWietersEBroitmanBMarquetPAampNavarreteSA(2018)Speciesco‐occurrencenetworksCantheyrevealtrophicandnon‐trophicinteractionsinecologicalcommunitiesEcology99690ndash699httpsdoiorg101002ecy2142

Gotelli N J (2000) Null model analysis of species co‐oc‐currence patterns Ecology 81 2606ndash2621 httpsdoiorg1018900012‐9658(2000)081[2606NMAOSC]20CO2

GotelliNJampGravesGR(1996)Null models in ecologyWashingtonDCSmithsonianInstitution

GotelliN JGravesGRampRahbekC (2010)Macroecological sig‐nalsofspeciesinteractionsintheDanishavifaunaProceedings of the National Academy of Sciences of the USA1075030ndash5035httpsdoiorg101073pnas0914089107

Hadfield JD (2010)MCMCmethods formulti‐responsegeneralizedlinearmixedmodelsTheMCMCglmmRpackageJournal of Statistical Software331ndash22

Harley C D (2011) Climate change keystone predation and biodi‐versity loss Science 334 1124ndash1127 httpsdoiorg101126science1210199

Harris D J (2016) Inferring species interactions from co‐occurrencedata with Markov networks Ecology 97 3308ndash3314 httpsdoiorg101002ecy1605

Harvey E Gounand I Ward C L amp Altermatt F (2017) Bridgingecology and conservation From ecological networks to ecosys‐tem function Journal of Applied Ecology 54 371ndash379 httpsdoiorg1011111365‐266412769

Hegland S J Nielsen A Laacutezaro A Bjerknes A‐L amp TotlandOslash (2009) How does climate warming affect plant‐pollina‐tor interactions Ecology Letters 12 184ndash195 httpsdoiorg101111j1461‐0248200801269x

Hobbs R J Higgs E amp Harris J A (2009) Novel ecosystemsImplicationsforconservationandrestorationTrends in Ecology and Evolution24599ndash605httpsdoiorg101016jtree200905012

Kehinde T amp Samways M J (2014) Effects of vineyard manage‐ment on biotic homogenization of insectndashflower interaction net‐works in the cape floristic region biodiversity hotspot Journal of Insect Conservation 18 469ndash477 httpsdoiorg101007s10841‐014‐9659‐z

Kucharik C J Serbin S P Vavrus S Hopkins E J amp MotewM M (2010) Patterns of climate change across Wisconsinfrom 1950 to 2006 Physical Geography 31 1ndash28 httpsdoiorg1027470272‐36463111

LaliberteacuteEampTylianakisJM(2010)Deforestationhomogenizestrop‐ical parasitoidndashhost networks Ecology 91 1740ndash1747 httpsdoiorg10189009‐13281

LegendrePampDeCaacuteceresM(2013)BetadiversityasthevarianceofcommunitydataDissimilaritycoefficientsandpartitioningEcology Letters16951ndash963httpsdoiorg101111ele12141

LegendrePampLegendreLF(2012)Numerical ecologyAmsterdamTheNetherlandsElsevier

LiDampWallerDM(2015)DriversofobservedbiotichomogenizationinpinebarrensofcentralWisconsinEcology961030ndash1041httpsdoiorg10189014‐08931

LiDampWallerDM (2016)Long‐termshifts inthepatternsandun‐derlyingprocessesofplantassociationsinWisconsinforestsGlobal Ecology and Biogeography 25 516ndash526 httpsdoiorg101111geb12432

LiDampWallerDM(2017)Fireexclusionandclimatechangeinteracttoaffect long‐termchanges in the functional compositionofplantcommunitiesDiversity and Distributions 23 496ndash506 httpsdoiorg101111ddi12542

LoreauMMouquetNampGonzalezA(2003)Biodiversityasspatialinsurance inheterogeneous landscapesProceedings of the National Academy of Sciences of the USA 100 12765ndash12770 httpsdoiorg101073pnas2235465100

MacLeod M Genung M A Ascher J S amp Winfree R (2016)Measuring partner choice in plantndashpollinator networks Using nullmodels to separate rewiring and fidelity from chanceEcology972925ndash2931httpsdoiorg101002ecy1574

McCannK(2007)ProtectingbiostructureNature44629ndash29httpsdoiorg101038446029a

McKinneyMLampLockwoodJL(1999)BiotichomogenizationAfewwinners replacingmany losers in the nextmass extinctionTrends in Ecology and Evolution 14 450ndash453 httpsdoiorg101016S0169‐5347(99)01679‐1

Milazzo M Mirto S Domenici P amp Gristina M (2013) Climatechange exacerbates interspecific interactions in sympatriccoastal fishes Journal of Animal Ecology 82 468ndash477 httpsdoiorg101111j1365‐2656201202034x

MokrossKRyderTBCocircrtesMCWolfe JDampStoufferPC(2014) Decay of interspecific avian flock networks along a dis‐turbance gradient in Amazonia Proceedings of the Royal Society B Biological Sciences28120132599

Morales‐Castilla IMatiasM G Gravel D amp ArauacutejoM B (2015)Inferring biotic interactions from proxies Trends in Ecology and Evolution30347ndash356httpsdoiorg101016jtree201503014

OksanenJBlanchetFGFriendlyMKindtRLegendrePMcGlinnDhellipWagnerH(2018)Vegan Community ecology packageRpack‐ageversion25‐2httpsCRANR‐projectorgpackage=vegan

OldenJDComteLampGiamX(2018)TheHomogoceneAresearchprospectusforthestudyofbiotichomogenisationNeoBiota3723httpsdoiorg103897neobiota3722552

OldenJDampPoffNL (2003)Towardamechanisticunderstandingand prediction of biotic homogenization The American Naturalist162442ndash460httpsdoiorg101086378212

OldenJDPoffNLDouglasMRDouglasMEampFauschKD(2004)Ecologicalandevolutionaryconsequencesofbiotichomog‐enization Trends in Ecology and Evolution 19 18ndash24 httpsdoiorg101016jtree200309010

PetanidouTKallimanisASTzanopoulosJSgardelisSPampPantisJD(2008)Long‐termobservationofapollinationnetworkFluctuationinspeciesandinteractionsrelativeinvarianceofnetworkstructureand implicationsforestimatesofspecializationEcology Letters11564ndash575httpsdoiorg101111j1461‐0248200801170x

emspensp emsp | emsp11Li et aL

Poisot T Gueacuteveneux‐Julien C FortinM‐J Gravel D amp LegendreP (2017)Hostsparasitesandtheir interactionsrespondtodiffer‐entclimaticvariablesGlobal Ecology and Biogeography26942ndash951httpsdoiorg101111geb12602

PoisotTStoufferDBampGravelD(2015)BeyondspeciesWhyeco‐logicalinteractionnetworksvarythroughspaceandtimeOikos124243ndash251httpsdoiorg101111oik01719

RCoreTeam(2017)R A language and environment for statistical comput-ingViennaAustriaRFoundationforStatisticalComputing

RockwellRFGormezanoLJampKoonsDN(2011)TrophicmatchesandmismatchesCanpolarbearsreducetheabundanceofnestingsnowgeese inwesternHudsonBayOikos120696ndash709httpsdoiorg101111j1600‐0706201018837x

RogersDARooneyTPOlsonDampWallerDM(2008)ShiftsinsouthernWisconsin forest canopy and understory richness com‐position and heterogeneity Ecology 89 2482ndash2492 httpsdoiorg10189007‐11291

RooneyTPWiegmannSMRogersDAampWallerDM (2004)BioticimpoverishmentandhomogenizationinunfragmentedforestunderstorycommunitiesConservation Biology18787ndash798httpsdoiorg101111j1523‐1739200400515x

SalaOEChapinFSArmestoJJBerlowEBloomfieldJDirzoRhellipLeemansR(2000)Globalbiodiversityscenariosfortheyear2100 Science2871770ndash1774

TullochAIChadegravesIampLindenmayerDB(2018)Speciesco‐occur‐renceanalysispredictsmanagementoutcomesformultiplethreatsNature Ecology amp Evolution 2 465ndash474 httpsdoiorg101038s41559‐017‐0457‐3

Tylianakis J M Didham R K Bascompte J amp Wardle D A(2008) Global change and species interactions in terres‐trial ecosystems Ecology Letters 11 1351ndash1363 httpsdoiorg101111j1461‐0248200801250x

Tylianakis J M amp Morris R J (2017) Ecological networksacross environmental gradients Annual Review of Ecology

Evolution and Systematics 48 25ndash48 httpsdoiorg101146annurev‐ecolsys‐110316‐022821

Tylianakis JM Tscharntke Tamp LewisO T (2007)Habitatmodifi‐cation alters the structure of tropical hostndashparasitoid food websNature445202ndash205httpsdoiorg101038nature05429

Valiente‐BanuetAAizenMAAlcaacutentaraJMArroyoJCocucciAGalettiMhellipJordanoP(2015)BeyondspecieslossTheextinctionofecologicalinteractionsinachangingworldFunctional Ecology29299ndash307httpsdoiorg1011111365‐243512356

Vitousek PMMooneyHA Lubchenco JampMelillo JM (1997)Human domination of earthrsquos ecosystems Science 277 494ndash499httpsdoiorg101126science2775325494

Waller DM Amatangelo K L Johnson S amp Rogers D A (2012)Wisconsinvegetationdatabasendashplantcommunitysurveyandresur‐veydatafromtheWisconsinplantecologylaboratoryBiodiversity amp Ecology4255ndash264httpsdoiorg107809b‐e00082

SUPPORTING INFORMATION

Additional supporting information may be found online in theSupportingInformationsectionattheendofthearticle

How to cite this articleLiDPoisotTWallerDMBaiserBHomogenizationofspeciescompositionandspeciesassociationnetworksaredecoupledGlobal Ecol Biogeogr 2018001ndash11 httpsdoiorg101111geb12825

Page 10: Homogenization of species composition and species ... · L I ET A L. | 3 biotic homogenization in species composition (Li & Waller, 2015; Rogers, Rooney, Olson, & Waller, 2008; Rooney

10emsp |emsp emspensp Li et aL

American Journal of Botany103118ndash128httpsdoiorg103732ajb1500079

CaraDonna P J Petry W K Brennan R M Cunningham J LBronstein J LWaserNMamp SandersN J (2017) InteractionrewiringandtherapidturnoverofplantndashpollinatornetworksEcology Letters20385ndash394httpsdoiorg101111ele12740

CazellesKArauacutejoMBMouquetNampGravelD(2016)Atheoryforspeciesco‐occurrenceininteractionnetworksTheoretical Ecology939ndash48httpsdoiorg101007s12080‐015‐0281‐9

ConnorEFampSimberloffD(1979)Theassemblyofspeciescommu‐nitiesChanceorcompetitionEcology601132ndash1140httpsdoiorg1023071936961

CummingGSBodinOumlErnstsonHampElmqvistT(2010)Networkanalysis in conservation biogeography Challenges and oppor‐tunities Diversity and Distributions 16 414ndash425 httpsdoiorg101111j1472‐4642201000651x

CurtisJT(1959)The vegetation of Wisconsin An ordination of plant com-munitiesMadisonWIUniversityofWisconsinPress

de Solar R R C Barlow J Ferreira J Berenguer E Lees A CThompsonJRhellipGardnerTA(2015)Howpervasiveisbioticho‐mogenizationinhuman‐modifiedtropicalforestlandscapesEcology Letters181108ndash1118httpsdoiorg101111ele12494

DelalandreLampMontesinos‐NavarroA(2018)Canco‐occurrencenet‐works predict plant‐plant interactions in a semi‐arid gypsum com‐munityPerspectives in Plant Ecology Evolution and Systematics3136ndash43httpsdoiorg101016jppees201801001

Diamond JM (1975) Assembly of species communitiesEcology and Evolution of Communities342ndash444

FreilichMAWietersEBroitmanBMarquetPAampNavarreteSA(2018)Speciesco‐occurrencenetworksCantheyrevealtrophicandnon‐trophicinteractionsinecologicalcommunitiesEcology99690ndash699httpsdoiorg101002ecy2142

Gotelli N J (2000) Null model analysis of species co‐oc‐currence patterns Ecology 81 2606ndash2621 httpsdoiorg1018900012‐9658(2000)081[2606NMAOSC]20CO2

GotelliNJampGravesGR(1996)Null models in ecologyWashingtonDCSmithsonianInstitution

GotelliN JGravesGRampRahbekC (2010)Macroecological sig‐nalsofspeciesinteractionsintheDanishavifaunaProceedings of the National Academy of Sciences of the USA1075030ndash5035httpsdoiorg101073pnas0914089107

Hadfield JD (2010)MCMCmethods formulti‐responsegeneralizedlinearmixedmodelsTheMCMCglmmRpackageJournal of Statistical Software331ndash22

Harley C D (2011) Climate change keystone predation and biodi‐versity loss Science 334 1124ndash1127 httpsdoiorg101126science1210199

Harris D J (2016) Inferring species interactions from co‐occurrencedata with Markov networks Ecology 97 3308ndash3314 httpsdoiorg101002ecy1605

Harvey E Gounand I Ward C L amp Altermatt F (2017) Bridgingecology and conservation From ecological networks to ecosys‐tem function Journal of Applied Ecology 54 371ndash379 httpsdoiorg1011111365‐266412769

Hegland S J Nielsen A Laacutezaro A Bjerknes A‐L amp TotlandOslash (2009) How does climate warming affect plant‐pollina‐tor interactions Ecology Letters 12 184ndash195 httpsdoiorg101111j1461‐0248200801269x

Hobbs R J Higgs E amp Harris J A (2009) Novel ecosystemsImplicationsforconservationandrestorationTrends in Ecology and Evolution24599ndash605httpsdoiorg101016jtree200905012

Kehinde T amp Samways M J (2014) Effects of vineyard manage‐ment on biotic homogenization of insectndashflower interaction net‐works in the cape floristic region biodiversity hotspot Journal of Insect Conservation 18 469ndash477 httpsdoiorg101007s10841‐014‐9659‐z

Kucharik C J Serbin S P Vavrus S Hopkins E J amp MotewM M (2010) Patterns of climate change across Wisconsinfrom 1950 to 2006 Physical Geography 31 1ndash28 httpsdoiorg1027470272‐36463111

LaliberteacuteEampTylianakisJM(2010)Deforestationhomogenizestrop‐ical parasitoidndashhost networks Ecology 91 1740ndash1747 httpsdoiorg10189009‐13281

LegendrePampDeCaacuteceresM(2013)BetadiversityasthevarianceofcommunitydataDissimilaritycoefficientsandpartitioningEcology Letters16951ndash963httpsdoiorg101111ele12141

LegendrePampLegendreLF(2012)Numerical ecologyAmsterdamTheNetherlandsElsevier

LiDampWallerDM(2015)DriversofobservedbiotichomogenizationinpinebarrensofcentralWisconsinEcology961030ndash1041httpsdoiorg10189014‐08931

LiDampWallerDM (2016)Long‐termshifts inthepatternsandun‐derlyingprocessesofplantassociationsinWisconsinforestsGlobal Ecology and Biogeography 25 516ndash526 httpsdoiorg101111geb12432

LiDampWallerDM(2017)Fireexclusionandclimatechangeinteracttoaffect long‐termchanges in the functional compositionofplantcommunitiesDiversity and Distributions 23 496ndash506 httpsdoiorg101111ddi12542

LoreauMMouquetNampGonzalezA(2003)Biodiversityasspatialinsurance inheterogeneous landscapesProceedings of the National Academy of Sciences of the USA 100 12765ndash12770 httpsdoiorg101073pnas2235465100

MacLeod M Genung M A Ascher J S amp Winfree R (2016)Measuring partner choice in plantndashpollinator networks Using nullmodels to separate rewiring and fidelity from chanceEcology972925ndash2931httpsdoiorg101002ecy1574

McCannK(2007)ProtectingbiostructureNature44629ndash29httpsdoiorg101038446029a

McKinneyMLampLockwoodJL(1999)BiotichomogenizationAfewwinners replacingmany losers in the nextmass extinctionTrends in Ecology and Evolution 14 450ndash453 httpsdoiorg101016S0169‐5347(99)01679‐1

Milazzo M Mirto S Domenici P amp Gristina M (2013) Climatechange exacerbates interspecific interactions in sympatriccoastal fishes Journal of Animal Ecology 82 468ndash477 httpsdoiorg101111j1365‐2656201202034x

MokrossKRyderTBCocircrtesMCWolfe JDampStoufferPC(2014) Decay of interspecific avian flock networks along a dis‐turbance gradient in Amazonia Proceedings of the Royal Society B Biological Sciences28120132599

Morales‐Castilla IMatiasM G Gravel D amp ArauacutejoM B (2015)Inferring biotic interactions from proxies Trends in Ecology and Evolution30347ndash356httpsdoiorg101016jtree201503014

OksanenJBlanchetFGFriendlyMKindtRLegendrePMcGlinnDhellipWagnerH(2018)Vegan Community ecology packageRpack‐ageversion25‐2httpsCRANR‐projectorgpackage=vegan

OldenJDComteLampGiamX(2018)TheHomogoceneAresearchprospectusforthestudyofbiotichomogenisationNeoBiota3723httpsdoiorg103897neobiota3722552

OldenJDampPoffNL (2003)Towardamechanisticunderstandingand prediction of biotic homogenization The American Naturalist162442ndash460httpsdoiorg101086378212

OldenJDPoffNLDouglasMRDouglasMEampFauschKD(2004)Ecologicalandevolutionaryconsequencesofbiotichomog‐enization Trends in Ecology and Evolution 19 18ndash24 httpsdoiorg101016jtree200309010

PetanidouTKallimanisASTzanopoulosJSgardelisSPampPantisJD(2008)Long‐termobservationofapollinationnetworkFluctuationinspeciesandinteractionsrelativeinvarianceofnetworkstructureand implicationsforestimatesofspecializationEcology Letters11564ndash575httpsdoiorg101111j1461‐0248200801170x

emspensp emsp | emsp11Li et aL

Poisot T Gueacuteveneux‐Julien C FortinM‐J Gravel D amp LegendreP (2017)Hostsparasitesandtheir interactionsrespondtodiffer‐entclimaticvariablesGlobal Ecology and Biogeography26942ndash951httpsdoiorg101111geb12602

PoisotTStoufferDBampGravelD(2015)BeyondspeciesWhyeco‐logicalinteractionnetworksvarythroughspaceandtimeOikos124243ndash251httpsdoiorg101111oik01719

RCoreTeam(2017)R A language and environment for statistical comput-ingViennaAustriaRFoundationforStatisticalComputing

RockwellRFGormezanoLJampKoonsDN(2011)TrophicmatchesandmismatchesCanpolarbearsreducetheabundanceofnestingsnowgeese inwesternHudsonBayOikos120696ndash709httpsdoiorg101111j1600‐0706201018837x

RogersDARooneyTPOlsonDampWallerDM(2008)ShiftsinsouthernWisconsin forest canopy and understory richness com‐position and heterogeneity Ecology 89 2482ndash2492 httpsdoiorg10189007‐11291

RooneyTPWiegmannSMRogersDAampWallerDM (2004)BioticimpoverishmentandhomogenizationinunfragmentedforestunderstorycommunitiesConservation Biology18787ndash798httpsdoiorg101111j1523‐1739200400515x

SalaOEChapinFSArmestoJJBerlowEBloomfieldJDirzoRhellipLeemansR(2000)Globalbiodiversityscenariosfortheyear2100 Science2871770ndash1774

TullochAIChadegravesIampLindenmayerDB(2018)Speciesco‐occur‐renceanalysispredictsmanagementoutcomesformultiplethreatsNature Ecology amp Evolution 2 465ndash474 httpsdoiorg101038s41559‐017‐0457‐3

Tylianakis J M Didham R K Bascompte J amp Wardle D A(2008) Global change and species interactions in terres‐trial ecosystems Ecology Letters 11 1351ndash1363 httpsdoiorg101111j1461‐0248200801250x

Tylianakis J M amp Morris R J (2017) Ecological networksacross environmental gradients Annual Review of Ecology

Evolution and Systematics 48 25ndash48 httpsdoiorg101146annurev‐ecolsys‐110316‐022821

Tylianakis JM Tscharntke Tamp LewisO T (2007)Habitatmodifi‐cation alters the structure of tropical hostndashparasitoid food websNature445202ndash205httpsdoiorg101038nature05429

Valiente‐BanuetAAizenMAAlcaacutentaraJMArroyoJCocucciAGalettiMhellipJordanoP(2015)BeyondspecieslossTheextinctionofecologicalinteractionsinachangingworldFunctional Ecology29299ndash307httpsdoiorg1011111365‐243512356

Vitousek PMMooneyHA Lubchenco JampMelillo JM (1997)Human domination of earthrsquos ecosystems Science 277 494ndash499httpsdoiorg101126science2775325494

Waller DM Amatangelo K L Johnson S amp Rogers D A (2012)Wisconsinvegetationdatabasendashplantcommunitysurveyandresur‐veydatafromtheWisconsinplantecologylaboratoryBiodiversity amp Ecology4255ndash264httpsdoiorg107809b‐e00082

SUPPORTING INFORMATION

Additional supporting information may be found online in theSupportingInformationsectionattheendofthearticle

How to cite this articleLiDPoisotTWallerDMBaiserBHomogenizationofspeciescompositionandspeciesassociationnetworksaredecoupledGlobal Ecol Biogeogr 2018001ndash11 httpsdoiorg101111geb12825

Page 11: Homogenization of species composition and species ... · L I ET A L. | 3 biotic homogenization in species composition (Li & Waller, 2015; Rogers, Rooney, Olson, & Waller, 2008; Rooney

emspensp emsp | emsp11Li et aL

Poisot T Gueacuteveneux‐Julien C FortinM‐J Gravel D amp LegendreP (2017)Hostsparasitesandtheir interactionsrespondtodiffer‐entclimaticvariablesGlobal Ecology and Biogeography26942ndash951httpsdoiorg101111geb12602

PoisotTStoufferDBampGravelD(2015)BeyondspeciesWhyeco‐logicalinteractionnetworksvarythroughspaceandtimeOikos124243ndash251httpsdoiorg101111oik01719

RCoreTeam(2017)R A language and environment for statistical comput-ingViennaAustriaRFoundationforStatisticalComputing

RockwellRFGormezanoLJampKoonsDN(2011)TrophicmatchesandmismatchesCanpolarbearsreducetheabundanceofnestingsnowgeese inwesternHudsonBayOikos120696ndash709httpsdoiorg101111j1600‐0706201018837x

RogersDARooneyTPOlsonDampWallerDM(2008)ShiftsinsouthernWisconsin forest canopy and understory richness com‐position and heterogeneity Ecology 89 2482ndash2492 httpsdoiorg10189007‐11291

RooneyTPWiegmannSMRogersDAampWallerDM (2004)BioticimpoverishmentandhomogenizationinunfragmentedforestunderstorycommunitiesConservation Biology18787ndash798httpsdoiorg101111j1523‐1739200400515x

SalaOEChapinFSArmestoJJBerlowEBloomfieldJDirzoRhellipLeemansR(2000)Globalbiodiversityscenariosfortheyear2100 Science2871770ndash1774

TullochAIChadegravesIampLindenmayerDB(2018)Speciesco‐occur‐renceanalysispredictsmanagementoutcomesformultiplethreatsNature Ecology amp Evolution 2 465ndash474 httpsdoiorg101038s41559‐017‐0457‐3

Tylianakis J M Didham R K Bascompte J amp Wardle D A(2008) Global change and species interactions in terres‐trial ecosystems Ecology Letters 11 1351ndash1363 httpsdoiorg101111j1461‐0248200801250x

Tylianakis J M amp Morris R J (2017) Ecological networksacross environmental gradients Annual Review of Ecology

Evolution and Systematics 48 25ndash48 httpsdoiorg101146annurev‐ecolsys‐110316‐022821

Tylianakis JM Tscharntke Tamp LewisO T (2007)Habitatmodifi‐cation alters the structure of tropical hostndashparasitoid food websNature445202ndash205httpsdoiorg101038nature05429

Valiente‐BanuetAAizenMAAlcaacutentaraJMArroyoJCocucciAGalettiMhellipJordanoP(2015)BeyondspecieslossTheextinctionofecologicalinteractionsinachangingworldFunctional Ecology29299ndash307httpsdoiorg1011111365‐243512356

Vitousek PMMooneyHA Lubchenco JampMelillo JM (1997)Human domination of earthrsquos ecosystems Science 277 494ndash499httpsdoiorg101126science2775325494

Waller DM Amatangelo K L Johnson S amp Rogers D A (2012)Wisconsinvegetationdatabasendashplantcommunitysurveyandresur‐veydatafromtheWisconsinplantecologylaboratoryBiodiversity amp Ecology4255ndash264httpsdoiorg107809b‐e00082

SUPPORTING INFORMATION

Additional supporting information may be found online in theSupportingInformationsectionattheendofthearticle

How to cite this articleLiDPoisotTWallerDMBaiserBHomogenizationofspeciescompositionandspeciesassociationnetworksaredecoupledGlobal Ecol Biogeogr 2018001ndash11 httpsdoiorg101111geb12825


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