Geographic scale and disturbance influence intraspecific trait ... · KUMORDZ ET AL.Functional...

Functional Ecology 2019001ndash14 wileyonlinelibrarycomjournalfec emsp|emsp1copy 2019 The Authors Functional Ecology copy 2019 British Ecological Society

Received4May2018emsp |emsp Accepted17June2019DOI 1011111365-243513402

R E S E A R C H A R T I C L E

Geographic scale and disturbance influence intraspecific trait variability in leaves and roots of North American understorey plants

Bright B Kumordzi1emsp| Isabelle Aubin2emsp| Franccediloise Cardou23 emsp| Bill Shipley3 emsp| Cyrille Violle4emsp| Jill Johnstone5emsp| Madhur Anand6emsp| Andreacute Arsenault7 emsp| F Wayne Bell8emsp| Yves Bergeron9 emsp| Isabelle Boulangeat10emsp| Maxime Brousseau11emsp| Louis De Grandpreacute12emsp| Sylvain Delagrange13emsp| Nicole J Fenton9emsp| Dominique Gravel3emsp| S Ellen Macdonald14 emsp| Benoit Hamel2emsp| Morgane Higelin9emsp| Franccedilois Heacutebert15emsp| Nathalie Isabel12 emsp| Azim Mallik16emsp| Anne CS McIntosh17 emsp| Jennie R McLaren18 emsp| Christian Messier1319emsp| Dave Morris20 emsp| Nelson Thiffault121 emsp| Jean‐Pierre Tremblay11 emsp| Alison D Munson1

1CentredrsquoeacutetudedelaforecirctDeacutepartementdessciencesduboisetdelaforecirctUniversiteacuteLavalQueacutebecQCCanada2GreatLakesForestryCentreCanadianForestServiceNaturalResourcesCanadaSaultSteMarieONCanada3DeacutepartementdebiologieUniversiteacutedeSherbrookeSherbrookeQCCanada4CEFEUMR5175CNRSndashUniversiteacutedeMontpellierndashUniversiteacutePaul‐ValeacuteryMontpellierndashEPHEMontpellierFrance5DepartmentofBiologyUniversityofSaskatchewanSaskatoonSKCanada6SchoolofEnvironmentalSciencesUniversityofGuelphGuelphONCanada7AtlanticForestryCentreCanadianForestServiceandSchoolofScienceandtheEnvironmentMemorialUniversityofNewfoundlandCornerBrookNLCanada8OntarioForestResearchInstituteOntarioMinistryofNaturalResourcesandForestrySaultSteMarieONCanada9InstitutderecherchesurlesforecirctsUniversiteacuteduQueacutebecenAbitibi‐TeacutemiscamingueRouyn‐NorandaQCCanada10IrsteaURLESSEMUniversiteacuteGrenobleAlpesSt‐Martin‐dHegraveresFrance11DeacutepartementdebiologieandCentredeacutetudedelaforecirctUniversiteacuteLavalQueacutebecQCCanada12LaurentianForestryCentreCanadianForestServiceNaturalResourcesCanadaQueacutebecQCCanada13InstitutdesSciencesdelaForecirctTempeacutereacuteeUniversiteacuteduQueacutebecenOutaouaisRiponQCCanada14DepartmentofRenewableResourcesUniversityofAlbertaEdmontonABCanada15DirectiondelarechercheforestiegravereMinistegraveredesForecirctsdelaFauneetdesParcsQueacutebecQCCanada16DepartmentofBiologyLakeheadUniversityThunderBayONCanada17UniversityofAlbertaAugustanaCampusCamroseABCanada18DepartmentofBiologicalSciencesUniversityofTexasatElPasoElPasoTXUSA19CentredEacutetudedelaForecirctUniversiteacuteduQueacutebecagraveMontreacutealMontreacutealQCCanada20CentreforNorthernForestEcosystemResearchOntarioMinistryofNaturalResourcesandForestryThunderBayONCanadaand21Canadian WoodFibreCentreNaturalResourcesCanadaQueacutebecQCCanada

CorrespondenceIsabelleAubinEmailisabelleaubincanadaca

Funding informationEuropeanResearchCouncil(ERC)GrantAwardNumberERC‐StG‐2014‐639706‐CONSTRAINTSFondsderechercheduQueacutebecndashNatureetTechnologies(FRQNT)teamgranttoADMIABSLDNTYBNaturalResourcesCanadaCanadianForestServiceForestChangeInitiativeNaturalSciencesandEngineeringResearchCouncil(NSERC)DiscoverygrantstoindividualresearchersADMMAJJSEMCM

HandlingEditorEllenDorrepaal

Abstract1 Consideringintraspecifictraitvariability(ITV)inecologicalstudieshasimprovedourunderstandingof speciespersistenceandcoexistenceTheseadvancesarebasedonthegrowingnumberofleafITVstudiesoverlocalgradientsbutlogisti-calconstraintshavepreventedasolidexaminationofITVinroottraitsoratscalesreflectingspeciesrsquogeographicranges

2 We compared themagnitude of ITV in above‐ and below‐groundplant organsacrossthreespatialscales(biophysicalregionlocalityandplot)Wefocusedonsixunderstoreyspecies(fourherbsandtwoshrubs)thatoccurbothindisturbedandundisturbedhabitatsacrossborealandtemperateCanadianforestsWeaimedtodocumentITVstructureoverbroadecologicalandgeographicalscalesbyasking(a)What is thebreadthof ITVacrossspecies range‐scale (b)Whatproportion

2emsp |emsp emspenspFunctional Ecology KUMORDZI et al

1emsp |emspINTRODUC TION

Interactionsbetweengeneticmake‐upandanindividualsenviron-mentexpressedastraitvariabilityareatthecoreoftodaysmostpressing questions in macroecology More specifically variabilityin plant traits can contributemuch to our understanding of plantperformance and fitness across environmental gradients (Keddy1992 Violle et al 2012) Although less frequently characterizedthanbetween‐speciesvariability(AlbertThuillerYoccozSoudantetal2010LeBagousse‐PinguetBelloVandewalleLepsampSykes2014GarnierNavasampGrigulis2015) intraspecific trait variabil-ity (ITV) that is traitvariabilityamong individualsofasinglespe-cies is increasinglybeing recognizedasamajor factor for speciescoexistence and persistence in a changing environment (Butler etal2017Shipleyetal2016Violleetal2012)ByformallytakingITVintoaccountcommunityecologistshaveimprovedbothdetec-tionof community assemblymechanisms (LeBagousse‐Pinguetetal 2014 JungViolleMondyHoffmannampMuller 2010 Siefert2012)andpredictionofglobal change impactsonecosystempro-cesses(JacksonPeltzerampWardle2013WardleBardgettWalkerampBonner2009)

ThereisnowgoodevidencethatthegeneralassumptionthatITVislowerthaninterspecificvariabilitydoesnotholdtrueinallsituations(Kazakouetal2014KicheninWardlePeltzerMorseampFreschet2013 Kumordzi Nilsson Gundale amp Wardle 2014) The crucialquestionthatemergesisthereforewhenandwhyisITVmoreim-portantPreviousstudieshavesuggestedthatITVisamechanismbywhichplantspeciesrespondtolocalspatialresourceheterogeneity(ValladaresGianoliampGoacutemez2007)andisrelatedtoenvironmentalvariationacrossthespeciesrsquorange(Helsenetal2017)Intraspecifictraitvariabilitymaybeparticularlyimportantinlowdiversityecosys-temswherereducedcompetitioncouldallowindividualsofthesamespecies tooccupy a larger trait space (FreschetBellingham LyverBonner ampWardle 2013 SilvertownampCharlesworth 2009 Violleetal2012)Forspecieswithwidespreadgeographicaldistributions(FajardoampPiper2011Sidesetal2014)greater ITVcouldrepre-sentbetteradaptationtoawiderangeofenvironmentalconditions(Albert Grassein Schurr Vieilledent amp Violle 2011 Sides et al2014Vasseuretal2018)Thespatial variance partitioning hypothesis predictsthatITVwillsaturatewithincreasingspatialscale(Albertetal2011)andthereforealargeproportionofthevariabilityshouldbeobservedatthelocalscale(Burtonetal2017)

ofITViscapturedatdifferentspatialscalesparticularlywhenlocalscaledistur-bancesareconsideredand(c)Isthevariancestructureconsistentbetweenanalo-gousleafandroottraitsandbetweenmorphologicalandchemicaltraits

3 Following standardizedmethodswe sampled818populations across79 forestplotssimultaneously includingdisturbedandundisturbedstandsspanningfourbiophysicalregions(~5200km)Traitsmeasuredincludedspecificleafarea(SLA)specificrootlength(SRL)andleafandrootnutrientconcentrations(NPKMgCa)We used variance decomposition techniques to characterize ITV structureacrossscales

4 OurresultsshowthatanimportantproportionofITVoccurredatthelocalscalewhensamplingincludedcontrastingenvironmentalconditionsresultingfromlocaldisturbanceAcertainproportionofthevariabilityinbothleafandroottraitsre-mainedunaccountedforbythethreesamplingscalesincludedinthedesign(36onaverage)withthelargestamountforSRL(54)Substantialdifferencesinmag-nitudeof ITVwerefoundamongthesixspeciesandbetweenanalogoustraitssuggestingthattraitdistributionwasinfluencedbyspeciesstrategyandreflectstheextentofunderstoreyenvironmentheterogeneity

5 Even for species with broad geographical distributions a large proportion ofwithin‐speciestraitvariabilitycanbecapturedbysamplinglocallyacrossecologi-calgradientsThishaspracticalimplicationsforsamplingdesignandtraitselectionforbothlocalstudiesandcontinental‐scalemodelling

K E Y W O R D S

functionalbiogeographyintraspecifictraitvariabilityleaftraitplantfunctionaltraitroottraitspecificleafareaspecificrootlengthtissuenutrientconcentration

emspensp emsp | emsp3Functional EcologyKUMORDZI et al

Environmental variations can create strong selective forcesand impact trait variability both within and among plant organs(FreschetSwartampCornelissen2015Reichetal1999)InNorthAmericanborealandtemperateforestsnaturalandanthropogenicdisturbances suchas firepestoutbreakswind‐throwand loggingare commondisturbances that candrastically alter the availabilityanddistributionof above‐ andbelow‐ground resources (Venier etal 2014) This disturbance‐driven small‐scale heterogeneity isnested within continental‐wide climatic gradients of precipitationand temperature Spanning over 5200 km longitudinally meanannual precipitation in Canada can be as low as 300 mm in theWest‐Central Boreal Forest and up to 1800mm in some regionsof Eastern Canada (Canadian National Vegetation Classification2015)Someunderstoreyplantspecieshaveremarkableadaptationto thesemulti‐scale environmental variations such that they dis-playbothavastgeographical(spatial)extent(TableS2FigureS1inSupporting Information)andabroadecological range (ie suitableenvironmentalgradient) ITVcouldexplaintheirwideextentbut itmayalsocontributetothemaintenanceoffitnessinfluctuatingun-derstoreyenvironmentalconditionsatlocalscales(AubinMessierampKneeshaw2005BartemucciMessierampCanham2006NeufeldampYoung2003)

Despite theecological importanceofdisturbance in these for-ests(BonanampShugart1989Venieretal2014)relativelylittleisknownabouthowdisturbancesinfluencethemagnitudeofleafandrootITVStandardtraitmeasurementprotocolsweredevelopedtoaddress ecological questions involving interspecific comparisonssince these protocols recommend selecting mature plants in fulllightandwithoutphysicaldamage (egPeacuterez‐Harguindeguyetal2013)intraspecificvariationislikelyunderestimatedThisispartic-ularlythecaseforforestplantsthatthriveinboththeunderstoreyandopenpost‐disturbance standsConsideredas commonwithintheir distributions these understorey herbs and shrubs have gar-nered less attention than rare economically valuable or invasivespeciesSpanningbothwidespatial(distance)andecologicalgradi-ents thesespeciesareexpected tohaveahighmagnitudeof ITV(Sidesetal2014)Theirubiquitymakesthemparticularlysuitedtoaddressquestionsabouttheecological importanceofITVforspe-ciespersistence

AnimportantquestioniswhetherITVvariesamongplantorgansTheorysuggeststhatplantsallocateinternalresourcesdifferentiallyamongorganstomaximizecaptureofthemostlimitingresource(egFreschet et al 2013) For instance in low‐light conditions plantsshouldallocatesignificantlymoreresourcestoleavesthantorootsBecauseplant response to environmental stimuli is determined atthewhole‐plant level (Freschet et al 2015 Kang Chang Yan ampWang2014)severalauthorshavesuggestedthattraitco‐variationshouldbe constant across spatial scales (Liuet al 2010Reichetal1999)Ifthisholdstruevariationinleaftraitscouldbeusedasproxies for theharder tomeasureanalogous root traitsHoweverrecent evidence fromempirical studies shows that trait variabilitycanbedecoupledamongorgansandacrossspecies(Freschetetal2013KumordziGundaleNilssonampWardle2016)withdifferent

patternsemergingatdifferentecological(MessierMcGillEnquistampLechowicz2016)orspatialscales(Kangetal2014)ForexampleLiuetal(2010)demonstratedgreatervariabilityinleaftraitsthaninanalogousroottraitsatbroadspatialscalesInthesecoldnutrient‐limitedborealsoilswemightexpectgreatervariabilityofSRLandrootnutrientsatthelargestscalesincechangesinsoilmineralogyandhencepHandnutrient availabilitymaybemost important atthisscale(BoiffinAubinampMunson2015)Withinplantorgans(egleaves) nutrient concentrations were found to exhibit higher ITVthanmorphologicaltraits(Kazakouetal2014)

IntheoryITVshouldbeestimatedbysystematicsamplingofin-dividualsacrossaspeciesrsquogeographicandorecologicalrange(Albertetal2011AlbertThuillerYoccozSoudantetal2010)Howeverthisisbothimpracticalandunrealisticinmostcases(Baralotoetal2010)Studies interested in ITVhavethereforemainly focusedonintensive local‐scalesamplingmeasuringseveral individualsgrow-ing in contrasting environmental conditions (eg Albert ThuillerYoccozDouzetetal2010Messieretal2016)Facedwithlogis-ticalconstraints large‐scalestudieshavereliedprimarilyonmeta‐analyses focusing insteadon the relative contributionof leaf ITVtowithin‐ and among‐community trait variance (eg Siefert et al2015)Gapfillingapproacheshavetypicallybeenusedtoovercomepartialcoverage (Butleretal2017)Despitethenotableprogressthat has beenmade in quantifying ITV few studies have tackledrange‐scaleestimatesofITVThislatterknowledgeisnecessaryforarobustapplicationofatrait‐basedapproachtoanswercontinen-tal‐andglobal‐scalequestionsregardingclimatechangeadaptation(Aubinetal2016ViolleReichPacalaEnquistampKattge2014)Itis also important for local‐scale studies sincewithout range‐wideITV estimates trait values estimated from localmeasurements ordatabanksremainwithoutcontextFinallyknowledgeofITVatdif-ferent spatial andecological scales couldprovideguidanceon thescaleatwhichthemajorityofITViscapturedreflectingthepoten-tialeffectofITVonecosystemfunction

Inthepresentstudyweinvestigatethemagnitudeofintraspe-cificvariability in leafandroottraitsacrossdifferentspatialandecological scales for six ubiquitous understoreyherb and shrubspecies that occur both in disturbed and undisturbed habitatsacross boreal and temperate Canadian forests The two shrubscanbeconsideredmoreconservativespecieswhilethefourherbslessconservativebutallareadaptedto lessfertilesoils (Larsen1980)Toachieve this sizeable samplinggoalweadoptedacol-laborativeapproachcollatingtheeffortsof23fieldteamsacrossCanada (Co‐VITAS project) Strategically focusing on traits thatcould reliably be sampled by several field teams independentlywealsochosetraitsrelatedtotheleafand(potentially)rooteco-nomicsspectrum(Weemstraetal2016Wrightetal2004)Thetraitsselectedareamongthemostplastic(Siefertetal2015)andshould respond todisturbance (SLA to light after canopydistur-banceandSRLtochangesinnutrientsassociatedwithabioticgra-dientsofsoilfertilitythatchangeoverlargescalesbutalsowithdisturbanceBoiffinetal2015)Plantnutrition(leafandrootNPandcationbases)inacidicborealsoilsishighlyrelatedtosoilpH


whichalsovarieswithlarge‐scalechangesinsoilmineralogyandwithsoildisturbanceespecially fire (ThiffaultBeacutelangerPareacuteampMunson2007)

ThisstudywasdesignedtodocumentITVstructureoverwidegeographical (spatial) and ecological scales by sampling speciesthroughout their range and under different disturbance condi-tionsMore specifically we address the following questions (a)What isthebreadthof ITVacrossspeciesrangesandhowdoesit differ among speciesWe would expect the breadth to varywithspeciesstrategyandfunctionaltype(higherITVacrossspe-cies ranges for herbs due to constraints on more conservativewoodyplantsMaireetal2013)(b)WhatproportionofITVcanbecaptured locallyAhigherproportionof ITVshouldbefoundat smaller scales (Albert et al 2011)Disturbance that removesthecanopyshouldincreasethisproportionatsmallerscalessinceunderstoreyspeciesareparticularlysensitivetoalteredlightandsoilconditionsTheinclusionofadisturbancegradientaddseco-logicaldistancebetween samples to capturea largerproportionofITVwithinashortspatialgradientand(c)Isthevariancestruc-tureacrossscalesconsistentbetweenmorphologicalandchemicaltraitsandbetweenanalogousleafandroottraitsBasedonpre-viousstudieswewouldexpecthigherITVforchemicalcomparedtomorphologicaltraits(Siefertetal2015)Leavesandrootsmayshowsimilarvariancestructuresamongscalesbuttheirresponseto disturbance‐related changes in light and soil resources couldcausedifferences in theproportionofvarianceexplainedat thelocalscaleSincelightavailabilityvariesconsiderablybetweendis-turbedandundisturbedplotswewouldexpecthigher variationforleafthanroottraitsattheplotscaleForroottraitsweexpectahigherproportionofthevarianceexplainedatalargerscalere-latedtochangesinsoilmineralogy

2emsp |emspMATERIAL S AND METHODS

21emsp|emspStudy area

Thestudywasconductedby23teamsaspartoftheCo‐VITASpro-ject(TableS1)followingastandardizedprotocoltocharacterize79plotsacrosstheborealandtemperateforestsofCanada(Figure1)Chosenlocationsweremostoftenpre‐existingstudysitesforwhichcollaboratorshadreadyaccessandknowledge(TableS1)Locationswereselected to reflect thepredominantcontinentalclimaticgra-dientacrossCanadaandtocapturealargeextentofeachspeciesrsquorange(FigureS1)

TheCanadiancontinentalgradientischaracterizedbyaneastndashwestdecreaseinmeansummerrainfallOfourstudylocationsthehighestaveragesummerrainfall(JulyndashAugust)valuesoccurinQuebec(ForecirctMontmorency144mm1971ndash2000McKenneyetal2011)andthelowestinnorthernAlbertaandtheYukon(both63mm1971ndash2000McKenneyetal2011)PredictablymeansummertemperatureacrossCanadatendstodecreasewithlatitudeandthelowestmeansummertemperature (mean of JulyndashAugust) of 134degC was recorded at theYukonlocation(KluaneMcKenneyetal2011)andthehighestmeansummertemperatureof244degCatMontSaint‐HilaireQuebec

22emsp|emspSampling design and data collection

Plantpopulationsweresampledbetween10and25July2014fol-lowinganestedhierarchicaldesign (Figure1)Our79studyplotsreflectingbothdisturbedandundisturbedconditionswerenestedwithin32 localitiesdistributedacrossfourbiophysical regionsandspanning5200km(Figure1)Wedefinedthesamplinghierarchyasfollows(fromsmallesttolargest)

F I G U R E 1 emspSpatial‐scalehierarchyandnomenclatureusedinthestudyOverall818populations(5m2)weresampledacross79plots(2500m2)withandwithoutdisturbancewhichwerenestedwithin32localitiesinfourbiophysicalregionsofCanadaScalePopulationswerelocated50to100mapartandwerepooledattheplotlevelforanalysisDistancebetweendisturbedandundisturbedplotswasbetween250mand10kmTheshortestdistancebetweenlocalitiesinthesamebiophysicalregionwas26kmLocalitiesweredistributedacrossfourbiophysicalregionsandspanning5200kmMapadaptedfromtheCanadianNationalVegetationClassification(CanadianNationalVegetationClassification2015)

Plot~2500m 2

Population5 m2

LocalityDistance across plots

~250 m - 10 km

Disturbed

Undisturbed

0 500 1000 1500 2000250 Kilometres

Biophysical Regions

Other

LocalitiesOntario amp Quebec Mixed ForestWest-Central North American Boreal Forest amp Woodland

Eastern North American Boreal ForestEastern Subboreal Forest


(i) PlotAnareaofapproximately2500m2wherepopulationsofthe targetspeciesweresampledTheplot is located inoneofthe two following categories reflecting the local disturbanceregime ldquoUndisturbedrdquo mature closed canopy forest with nosignofrecentdisturbanceor inarecently(lessthan20years)ldquoDisturbedrdquo forest affected by canopy removal and varyingsoildisruption (firewind‐throw insectoutbreak treeharvestsmelterdeposition)

(ii) LocalityAgeographic locationcharacterizedbyhomogeneousclimateregimeandsoilconditionsencompassingdisturbedandundisturbed plots These typically reflected each field teamsstudyareaLocalitiesincludedatleastoneplotanduptofourwhichwereseparatedbydistancesofupto10km

(iii)Biophysical regionAregionallydistinctvegetationzonereflectingdifferencesinclimateregimesoilconditionsandforestcompo-sitionabundanceandordominanceThisreferstotheldquomacro‐grouprdquoleveloftheCanadianNationalVegetationClassificationSystem (Canadian National Vegetation Classification 2015httpcnvc‐cnvcca)Biophysicalregionsincluded3to16locali-tieseach

Selectedsiteshadgenerallyflatterrainwithslopesnotexceeding5andcontainedasmanytargetspeciesaspossibleTheresultingsam-plingdesignissummarizedinTableS1

23emsp|emspTarget species and functional trait measurements

We focused on six common understorey plant species that occurin temperate and boreal forests ofNorthAmerica (Tables S1 andS2 Figure S1) These included two low shrubs Vaccinium angus‐tifolium (Ericaceae) and Kalmia angustifolia (Ericaceae) and fourherbsMaianthemum canadense (Asparagaceae)Cornus canadensis (Cornaceae)Trientalis borealis(Lysimachia borealisPrimulaceae)andAralia nudicaulis(Araliaceae)Theshrubscouldbeconsideredtohaveamoreconservativestrategy(slow‐growing)incontrasttotheher-baceousspeciesInparticularAraliaisfoundinhigherfertilityenvi-ronmentscomparedtotheotherthreeherbs

Foreachtargetspeciespresentinaplotthreepopulations(ierametsandorindividualplantslocatedwithinahomogeneous~5‐m2area)wereselectedapproximately50mapartForeachpopula-tionwepooledcollectedleafmaterialfrom3to5individualsFullyexpandedcurrent‐year leaveswerecollected insufficientquantitytoproduce2gofdryweightmaterial(10ndash30leavesgroundthrougha 20‐mesh screen using aWileymill) Leaf area of freshmaterialwascapturedbyindividualfieldteamsbeforedryingusingscannersorcamerasAll leafsampleswereshippedtoGreatLakesForestryCentre(SaultSte‐Marie)forgrindingNutrientanalyseswerecarriedoutatUniversiteacuteLaval(Queacutebec)andatMinistegraveredesForecirctsdelaFauneetdesParcs(Queacutebec)

Similarlyforeachpopulationtheentirerootsystemwasgentlyextractedfor3ndash5matureindividualsmakingsuretoincludeatleast10 absorbing fine roots The sampleswere stored fresh in sealed

plasticbagswithamoistpapertowelforprocessinginthelaboratoryFreshrootswereshippedininsulatedcontainerstocentrallabora-toriesforrapidstandardizedprocessingCornus and Maianthemum roots to Universiteacute duQueacutebec en Abitibi‐Teacutemiscamingue (Rouyn‐Noranda)andtheotherspeciestoUniversiteacuteLaval(QueacutebecCity)

Atotalof818targetspeciespopulationsweresampled(TablesS4andS5)Foreachpopulationweestimatedthespecificleafarea(SLA) as the ratio of the leaf area to dryweight (cm2g) and spe-cificrootlength(SRL)astheratioofrootlengthtodrymassoffineroots(mg)WemeasuredSRLonabsorptivefinerootsthatisthemost distal fine rootswith healthy terminal root cap (Cornelissenetal2003)GroundleafsampleswerepooledbypopulationwhilegroundroottissuehadtobepooledattheplotlevelduetothesmallsizeoffinerootedspeciesSubsamplesforeachleafandrootsampleweredigestedinH2O2Se(Lowther1980)todeterminetheconcen-trationsofnitrogen(N)phosphorus(P)potassium(K)calcium(Ca)andmagnesium(Mg)FollowingdigestionconcentrationofNinthedigestwasmeasuredbyspectrophotometry(FIAstarTecator)Pbyinductivelycoupledplasmaanalysesandcationsthroughatomicab-sorption(Optima4300DVofPerkin‐Elmer)Theleafandrootmor-phologicaltraitdatawereaveragedwithinplotforconsistencywithnutrientroottraits(ieonevalueperplotforeachspeciestrait)

24emsp|emspStatistical analyses

All statistical analyses were performed in r (version 311 RDevelopment Core Team 2014) on data averaged per plot FirsttoexaminethebreadthofITVacrosseachspeciesrsquosampledrange(question1)we computeddensity plots showing the relative fre-quencyofmorphological (SLAandSRL)andchemical ([N] [P] [K][Ca][Mg])leafandroottraitvaluesforeachofthesixspecies(gg-plot2packageWickham2009)Foreachspeciesandtraitwecom-putedITVasthecoefficientofvariation(CVtrait)whichisestimatedasthestandarddeviationofeachdistributiondividedbythemeaninordertoquantifytheextentoftraitvariabilityacrosstheentirespeciesrsquodistributionsampledThisprovidesavisualcomparisonofthe trait variability for different species and traitsWewere alsointerested inassessing thepercentageof range‐wide ITVthatcanbecapturedlocallywhensamplingacrossthedisturbancegradient(question2)Foreachspeciesandtraittheaverageandthemaxi-mumITVobservedbetweenplotsfromasamelocalityweredividedbytheITVmeasuredacrossthespeciesrsquosampledrange

We explored how the variance structure differs between leafand root traits and between morphological and chemical traits(question 3) Thiswas done for each species individually becauseofthestronginteractiveeffectofspeciesandtraitonITV(resultsnotshown)Foreachspeciesandtraitthevariancestructureacrosssamplingscaleswasdeterminedusingamixedmodellingtechnique(lme4packageBatesetal2015)Using traitvaluesas responsevariables our model included all three sampling scales as nestedrandomvariablesbiophysicalregion(iecomparisonamongregion)locality (iecomparisonamong localities)andplot (iecomparisonbetweendisturbedandundisturbedplots)Foreachtraitwethen


decomposedandquantifiedthevarianceacrosssamplingscalesandexpresseditasapercentageofthetotalvarianceexplainedbyran-domcomponentsyieldingthevariancestructureacrossscales

Theseanalyseswereconductedwithconsiderationfortheun-balancednatureofourstudydesign(GelmanampHill2007)Weac-knowledge that varianceestimates for sampling scaleswith lowerreplication are less accurate than those for scales with higherreplication

3emsp |emspRESULTS

Thestudiedspecieshadquitedifferenttraitdistributionsasdemon-stratedbytheirdensityplots(Figure2)withcleardifferencesamongspeciesinthemeanthemodeandthebreadthoftheirtraitdistribu-tionSomespeciessuchasV angustifoliumtendedtohavenarrowtraitdistributionswhileothersdisplayedagenerallywidebreadthof trait values (eg T borealis) The relative position of the meantraitvaluesamongspecies (x‐axisFigure2)wasconsistentacrosstraitsForexampletheshrubsKalmia angustifolia and V angustifo‐lium generally exhibited lowermean trait values and trait breadththantheherbsA nudicaulis and T borealis(Figure2)Ingeneralthetwoshrubsshowedlowermeanandbreadthforleafandroottissue

bases(CaKMg)comparedtotheherbsDistributionsaregenerallyrelativelyflatfortissueKandforleafPandMgforherbaceousspe-ciesThispatternismuchlessevidentforNwherethedistributionisrelativelyconstantacrossspecies(exceptAraliacharacterizedbyhighermeanN)Densityplotsshowedthattraitdistributionbreadthwithin specieswas largelyconsistent forboth leafand root traitsalthoughroottraitstendedtovarylessthanleaftraits(Figure2)

We observed differences in the coefficient of variation foranalogous traits (similar traits measured on leaves and rootsFigure3)ForallspeciestheCVofSRLwasgreaterthantheCVforSLAbutforC canadensistheyweresimilarFormostspeciesNandPwerecharacterizedbyhighervariabilityinrootscomparedto leaves thiswasnot thecase forbasecationsCaMgandKwhichshowednogeneralpatternamongspeciesTheCVof leafNwasconsistentlylowerforallspecieswhencomparedtoothertraits(Figure3)

Itwaspossible to capturea substantialproportionof the traitvariation locally when sampling both disturbed and undisturbedplotsMaximumrange‐wide ITVcaptured locallyvaried from32to100 (61on average for all traits and species Table S3)Onaverage22of the range‐wide ITVwasobservedbetweenplotsofagivenlocalityAlargerproportionofleaftraitvariationtendedtobecapturedlocallyincomparisonwithroots(ANOVAp0052)

F I G U R E 2 emspRelativefrequencyofmeasuredrootandleaftraitsofsixstudyspeciesdistributedacrossCanadianborealandtemperateforestsSLAspecificleafareaSRLspecificrootlengthNnitrogenPphosphorusKpotassiumCacalciumMgmagnesiumconcentrations


Thevariancestructurerevealeddifferencesintheproportionofvarianceexplainedbythedifferentsamplingscalesamongspeciesandacrosstraits(Figure4)Figure5showstheaveragecumulativeproportionof trait varianceexplainedateach scaleWeobservedacleardecreaseintheproportionofexplainedITVwithincreasingspatial scale (Figure 5) which confirms that overall a substantialamountofITVcanbecapturedattheplotscalewhensamplingbothdisturbedandundisturbedplotswithinalocality

TheproportionofITVcapturedateachscaledifferedforrootandleaftraits(Figures4and5)Forleaftraitsdifferencesamongplotscapturedonaverage10to49ofthetotal ITV(Figure5)while extending sampling to includemultiple localities addedanadditional18to54tothetotalproportionofITVexplainedforan average species Large‐scale sampling among biophysical re-gionscapturedanadditional3to18ofleaftraitvariabilityForchemicalroottraitswiththeexceptionofCasamplingattheplotlevelexplained23to45ofthetotalproportionofchemicalroottraitvariancewhileextendingsamplingamonglocalitiesaddedanadditional19to30Samplingthesechemicalroottraitsatalargescaleexplainedanadditional3 to10of varianceForCaonly4ofvarianceoccurredat theplot levelwhile samplingamongmultiplelocalitiesaddedanadditional45Samplingamongbio-physical regionsaddedanother3variancecaptured (Figure5)

ForSRL13ofvarianceoccurredattheplotlevelanadditional28wascapturedamongmultiplelocalitiesandsamplingamongregionsonlyaddedanadditional3TherelativelylowamountofITVexplainedatthebiophysicalregionscale(amongregions)wasgenerallyconsistentformostspecieswithsomeexceptionssuchasV angustifoliumrootPandleafCaandA nudicaulisleaftraits(Figure4)

Wefoundstrongcontrasts intherelativecontributionofsam-pling scale for analogous above‐ and below‐ground traits For in-stance leafCaandSLAhadthelowestproportionofvariancenotaccountedforbyourmodel(onaverage18and24respectively)andSRLthehighest(54Figure5)Similarly85ofSLAvariancefor V angustifoliumoccurredamongplotswhileSRLvarianceforthisspecieswasverylowatthatscale(4Figure4)

4emsp |emspDISCUSSION

41emsp|emspMagnitude of ITV for different species

ThemagnitudeofITVisexpectedtoreflecttheextentofenviron-mentalheterogeneity (Valladareset al 2007) and should indicatethe relative contribution of environmental drivers to phenotypicvariation (Messier et al 2016) We report range‐scale estimates

F I G U R E 3 emspCoefficientofvariationofanalogousmorphologicalandchemicaltraitsforeachofthesixstudyspeciesestimatedforsamplesfromacrossthegeographicalrangeofthespeciesSLAspecificleafareaSRLspecificrootlengthNnitrogenPphosphorusKpotassiumCacalciumMgmagnesiumconcentrations


of root and leaf ITV for six North American understorey specieswithwidegeographicalandecologicaldistributions(Figure2)Suchrange‐scaleestimatesareextremelyrareespeciallyforroottraitsand it is the first time that ITV estimates are reported forNorthAmerican understorey ubiquitous speciesDifferent trait distribu-tionsareevidentamongthesixspecieshighlightingimportantdif-ferencesinmagnitudeofITV(Figure2)Themostconsistentpattern(andlowerCVFigure3)amongspecieswasnotedforleafNandtoalesserextentSLAthiscouldberelatedtotheleafeconomicsspec-trumA nudicaulisthemostnutrient‐demandingspecies(associatedwithfertilesites)demonstratesawidercurvefor leafNandSLAand a highermean leafN The two shrub species show generallynarrowerbreadthandlowermeansformosttraitsespeciallytissuebasecationsperhapsrelatedtotheirpreferenceforlowfertilityen-vironments(ThiffaultTitusampMunson2004)StrategiesthendohavesomeimpactontraitprobabilitydistributionsIngeneralSRLhasahigherCVthanothertraits(Figure3)thismayreflectthehet-erogeneouscharacterofsoils in termsofmineralogy textureanddrainage(Weemstraetal2016)

42emsp|emspPartitioning of ITV at three scales

FormosttraitswefoundalowproportionofITVcapturedatlargespatial scales (ie among biophysical regions Figure 4) We ob-servedthatthegreatestproportionofITVoccurredlocallyamongpopulations from contrasting environments (ie in disturbed and

undisturbed plots) and among localities from a given biophysicalregion These results are in accordance with the spatial variancepartitioninghypothesis(Albertetal2011)whichpredictsthatITVshould saturatewith increasing scale aswell aswith studies thatnotedahighproportionofvarianceexplainedlocally(egMoreiraTavsanogluampPausas2012LajoieampVellend2015Messieretal2016)NorthAmericanborealandtemperateforestunderstoriesaretheresultofenvironmentalgradientsoperatingatdifferentscalesincluding continental climatic gradients and local heterogeneitydriven by anthropogenic and natural disturbance regimes (BonanampShugart1989SchulteampMladenoff2005)Inparticularcanopyremovalafteradisturbancesuchasfireorharvestingcausesmajorshiftsinunderstoreyenvironmentalconditionsnotablylightavaila-bilitytemperatureandsoilmoistureregime(NeufeldampYoung2003RossFlanaganampRoi1986Venieretal2014)Theimportantcon-tributionofdisturbancetothe ITVof thesesixubiquitousspeciesunderlinestheiradaptationtodisturbance‐proneenvironments

Although therewere clear differences in ITV response acrossspatialscalesnogeneraltrendemergedamongspeciesEachspe-cies demonstrated quite different partitioningwith no similaritiesamong species according to strategy nor differences betweenherbsandshrubs this latterobservationsupporting theresultsofthemeta‐analysesbySiefertetal (2015)ThegreatestproportionoftraitvarianceexplainedforthetwomostcommonherbspeciesT borealis and C canadensis tendedtobecaptured innutrientsatthelocalityscaleindicatingabroadadaptabilitytoheterogeneous

F I G U R E 4 emspSummaryofvariancedecompositionanalysesshowingtherelativecontributionofthethreesamplingscalestovariabilityinmorphologicalandchemicaltraitsmeasuredonleafandroottissuesforsixstudyspeciesSLAspecificleafareaSRLspecificrootlengthNnitrogenPphosphorusKpotassiumCacalciumMgmagnesiumconcentrations


soilnutrientconditions(Figure4)AhighproportionofSLAvariancewasalsocapturedatthelocalityscaleforC canadensisThiswouldseemtoindicateawideabove‐groundplasticityandadaptationtodifferent light conditions createdbydisturbanceThe lowest vari-anceatthelocalityscalewasnotedforleaftraitsofV angustifoliuma conservative speciesFor this species a largeproportionof leaftraitvariancewascapturedattheplotscale(iebetweendisturbedandundisturbedplots)

AmongleaftraitsSLAwhichisknowntovarystronglywithlightandtemperatureandmoderatelywithnutrientavailability(PoorterNiinemetsPoorterWrightampVillar2009)showedthehighestpro-portionofexplainedvarianceattheplotscale(Figure5)MostofthevariationinSLAwascapturedamongplotsreflectingdifferencesinlightavailabilityandmuchlessvariationwasaccountedforbysam-plingfromseverallocalitiesorfromdifferentbiophysicalregionsIncontrast a very lowproportion of leaf and rootCawas capturedamongplotsbutasubstantialproportionwascapturedwhensam-plingamonglocalitiesperhapsrelatedtosoilmineralogy

While our results indicate ITV saturationwith increasing spa-tialscaleaspredictedbyAlbertetal(2011)theyalsohighlighttheimportanceofadequatelycoveringtheentirespeciesniche in ITVassessmentsOurresultsclearlyshowthe importanceofsamplingacrosscontrastingenvironmentalconditionsinordertocapturethefullextentandmagnitudeofITVforspecieswithabroadecologicalrangeWebuildonthemodelpredictionofAlbertetal (2011)by

accountingforspeciesrsquorangesizesandproposethatITVcanincreasewithspatialscaleuntilthefullbreadthofaspeciesrsquoecologicalnicheis covered (including the full rangeofenvironmental conditions inwhichitcanmaintainnon‐nullfitness)ITVcanthenbeexpectedtotaperoffatthegeographicalscalewheregeneticvariationbecomesthemaindriverofphenotypicvariability(Vasseuretal2018)Itisimportanttonotethatourstudydesigndoesnotallowustodiscrim-inatebetweenpurelyspatialscale(iethephysicaldistancebetweensamples)andecologicalscale(iethedistancebetweensamplesintermsof theunderlyingenvironmentalgradient)at the local levelThe drivers of disturbance‐related ITV and continental‐scale ITVmaybedifferentandindependentofeachother

Alargeproportionofthevariabilityinleaftraitsremainedunac-countedforbythethreesamplingscalesincludedinthedesign(31on average Figure 5) In a study investigating ITV structure fromplotleveldowntotheleaflevelMessieretal(2016)accountedfor49oftheSLAvarianceand33oftheleafNvarianceatecologicalscaleslowerthanoursamplingdesign(individualsamplingstrataandleafscales)Thiswasattributedtovariationsinleafverticalpositionunderstoreylightheterogeneityandindividualphenotype(Messieretal2016)Residualvarianceinourstudythereforecouldpoten-tiallybeattributabletoleavesindividualsandpopulationssampledTheproportionofvariability in root traitsunaccounted forbyourthreesamplingscaleswassimilartothatforleaftraits(40onav-erageFigure5)withtheexceptionofSRLforwhichtheproportion

F I G U R E 5 emspAveragemagnitudeofintraspecifictraitvariabilityinleaf(toppanel)androottraits(bottompanel)forthesixstudyspeciesobservedacrossdifferentsamplingscalesSLAspecificleafareaSRLspecificrootlengthNnitrogenPphosphorusKpotassiumCacalciumMgmagnesiumconcentrations


washigher(54)Thehighvarianceunaccountedforbyourstudydesignunderscoresthenecessityofsamplingtraitsatsmallereco-logicalscales(egindividualsandleavesorroots)

SeveralstudieshaveemphasizedtheneedtoadequatelycaptureITV tobetterunderstand its contribution to large‐scaleecologicalprocesses(LeBagousse‐Pinguetetal2015Siefert2012Violleetal 2012)Obviously documenting ITV for specieswith extendedgeographical distributions involves amajor logistical commitmentHoweverourfindingssuggestthatalargeproportionofITV(aver-aging22oftherange‐wideITVTableS3) isdrivenbyecologicalgradientsthatarefoundovershortdistances (disturbedvsundis-turbed)while a smallerpartof ITV is the resultof environmentalgradientsspanningoverlargegeographicalextents(egclimateandsoil type)Therefore localmeasuresof ITVmaybeadequateesti-mates of speciesrsquo ITVwhen broad ecological gradients are locallyavailableHoweverdependingonstudyobjectivesquantifyingthegreatestproportionofITVmaybeinsufficient(Albertetal2011)ForinstanceevensmallamountsofITVcapturedatlargescalesmaybeimportantforbiome‐scalesensitivityanalysesorclimatechangeadaptationstudies(Anderegg2015Aubinetal2018)

43emsp|emspCorrespondence between above‐ and below‐ground ITV

Inanswertothethirdquestionweaddressedwhetherthevariancestructure across spatial scaleswas consistent between analogousleafandroottraitsandbetweenmorphologicalandchemicaltraitsChemical traits showed lower variation than morphological traits(Figure3)HoweverSLAandSRLareconsideredtobeamongthemostplasticmorphologicaltraits(AugerampShipley2013Siefertetal2015)Siefertetal(2015)alsofoundSLAmorevariablethanleafnutrientsCovarianceinleafandroottraitshasbeenobservedacrossspeciesinseveralstudies(Reichetal19992003WestobyFalsterMolesVeskampWright2002)howeverwedidnotobservethisco-varianceinoursixunderstoreyspeciesTheleafeconomicspectrum(Wrightetal2004)waswellexpressedinourdatasetwithmoreacquisitivespecies(T borealis and Maianthemum canadense)havingahigherSLAandleafNconcentrationthanthemoreconservativespecies(Kalmia angustifolia and V angustifoliumFigure2)Howeverwedidnotfindany indicationofananalogouscoordination intheroots(iearooteconomicspectrumRoumetetal2016Weemstraetal2016)

OurresultssuggestthatthemagnitudeofITVpresent inplanttraits depends on the specific plant organ Distinct organ‐levelITVmaynotbesurprisingas leavesandrootsplaydifferentrolesinplant resourceacquisitionandconservationstrategiesandmayconsequentlyresponddifferentlytodriversofphenotypicvariability(Freschetetal2013Kumordzietal2014Messieretal2016)Moreimportantlytheyarealsoexposedtovastlydifferentenviron-mentswhere local‐scale disturbances havedifferent implicationsDisturbances resulting in canopy removal modify soil conditionsincludingincreasedsoiltemperaturemicrobialactivityandnutrientavailability (Venieretal2014)suchchangescoulddrivetheroot

trait variability observed among plots Some of the unaccountedvarianceinroottraitsmayalsobeattributabletotheinherentdif-ficultyofmeasuringrootstheimprecisioninSRLmeasurementforthefinelyrootedspecies(egKalmia angustifolia and V angustifolium)mayinpartexplaintheirlargeCV(Figure3)andhighproportionofvariabilityunaccountedforbythethreesamplingscales(Figure4)HoweverMaianthemum canadenseaspecieswithmuchthickerfinerootsalsohadalowexplainedSRLvariance(Figure4)suggestinganimportantroleforprocessesoccurringatsmallerscales(egnutrientavailability) that differentially affect the individuals (supported byunpublisheddataMunsonandCorrales)

Chemicaltraitsweremoreconsistentlystructuredacrossspatialscales (Figure5) indicatingacovarianceamongchemical rootandleaf traits on average despite variability among species (Figure 4FigureS2) Incomparisonwithleaftraits ITVinrootsremainsun-derexplored(BardgettMommerampDeVries2014)dueinlargeparttotherelativedifficultyinobtainingandprocessinglargenumbersofsamples(howeverseetheroottraitdatabankFREDIversenetal2017)Likeleaftraitsroottraitsmayalsoindicatedifferentaxesofplantecologicalstrategiesbutseveralstudiesnowpointtowardsamulti‐dimensional interpretationofbelow‐groundtraits (Kramer‐Walteretal2016Weemstraetal2016)wheresometraitsmayrespondincoordinationwithabove‐ground(suchasroottissueden-sityinthecaseoftrees)whileotherssuchasSRLmaynot

44emsp|emspITV and predictive ecology

Traitsare increasinglybeing incorporated intomacro‐scalestudiesandusedtomakepredictionsaboutfuturecommunitycomposition(Laughlinetal2012Sudingetal2008)notablywithinthetheo-retical corpus of functional biogeography (Violle et al 2014)Weobserveddifferencesinrange‐wideITVevenamongoursmallgroupofubiquitousspeciesEachspecieswascharacterizedbydifferentpartitioningofvarianceacrossscalesandbetweenanalogoustraitsOurresultshighlightspecies‐specificidiosyncrasiesthatmightarisewhen inferring ecological processes from traits measured on dif-ferentplantorgans(Shipleyetal2016Violleetal2007)under-scoringtheneedforresearchonstrategies(egViolleetal2007Wardleetal2009Garnieretal2015Kumordzietal2016)aswellastheneedforsynthesistoidentifysuitesoftraitsthatarere-latedtoparticularecosystemprocesses (Aubinetal2016Peacuterez‐Harguindeguyetal2013)

Our results signify that there is more than one strategy toachieveaubiquitouspresenceinforestunderstoreyplantcommuni-tiesSpeciescanbeeffectivecolonizersabletoestablishoverawiderangeofenvironmentalconditionsortheycanmaintaintheirpres-enceintheunderstoreythroughvegetativeregenerationandahighlevelofplasticityinresponsetocanopyopening(Aubinetal2005GilliamampRoberts2003Rowe1983)orperhapsbothThesediffer-entstrategiesamongspeciescoulddirectlyinfluencetheabilityofentirecommunitiestoadaptorshiftunderclimatechangeldquoWinnerrdquospeciesunderclimatechangemayconsequentlynotonlybespeciesthatdisplaytraitsweexpecttobefavouredbutmayalsobethose


possessinglargeITVBynecessityourstudyfocusedonlyonasmallgroupof speciesbutgreater ITV inmoreacquisitive specieswar-rantsfurtherresearch

ACKNOWLEDG EMENTS

This work stemmed from the lsquoCo‐VITAS Understorey plants assentinelsofchanges inecosystemfunctionprojectandworkinggroupinitiatedin2014Wewouldliketothankallthefieldassis-tantsthatparticipatedinthesamplingWearealsoindebtedtothestaff from the Laboratoirede chimieorganique and inorganiqueoftheMinistegraveredesForecirctsdelaFauneetdesParcsduQueacutebecUniversiteacuteLavalUniversiteacuteduQueacutebecenAbitibi‐TemiscamingueandtheCanadianForestServicefor laboratoryanalysesThankstoparticipantsoftheCo‐VITASworkshopheldinFebruary2017wheretheideasforthispaperwerediscussedtheworkshopwassupported by the Canadian Institute of Ecology and Evolution(CIEE) Canadarsquos national synthesis centre Thanks toD Lesieur(CEF) fordatabasedevelopmentand toKBaldwin foraccess tothe CNVC classification data Thanks also to S Gautier‐Ethierand K Good for coordinating the laboratorymeasurementsMCoyeafordatamanagementSRoyer‐TardifforproofreadingthefinalmanuscriptandVHamelforgraphicalsupportThankstoLBoisvert‐Marsh for data management manuscript revision andgraphicalandstatisticalsupportThisworkwassupportedbyanFRQNT(FondsderechercheduQueacutebecmdashNatureetTechnologies)team grant (toADM IA BS LDNT and YB) the ForestChange Initiative (Canadian Forest Service Natural ResourcesCanada) and NSERC Discovery grants to individual research-ers (ADMMA JJ SEM andCM) CVwas supported bythe European Research Council (ERC) Starting Grant ProjectlsquoEcophysiologicalandbiophysicalconstraintsondomesticationincropplants(GrantERC‐StG‐2014‐639706‐CONSTRAINTS)

AUTHORSrsquo CONTRIBUTIONS

IAFCandADMdesignedmethodologyIABSJJFCMAAAWBYBIBMBLdGSDNFDGSEMBHMHFHNIAMAM JMCMDMNT JPTandADMcol-lectedthedataBBKIABSandADMconceivedtheideasandanalysedthedataBBKIAFCCVandADMledthewritingofthemanuscriptAllauthorscontributedcriticallytothedraftsandgavefinalapprovalforpublication

DATA AVAIL ABILIT Y S TATEMENT

DatadepositedintheDryadDigitalRepositoryhttpdoi105061dryad434gv5p(Kumordzietal2019)

ORCID

Franccediloise Cardou httpsorcidorg0000‐0002‐6527‐9212

Bill Shipley httpsorcidorg0000‐0002‐7026‐3880

Andreacute Arsenault httpsorcidorg0000‐0001‐8165‐7183

Yves Bergeron httpsorcidorg0000‐0003‐3707‐3687

S Ellen Macdonald httpsorcidorg0000‐0003‐1750‐1779

Nathalie Isabel httpsorcidorg0000‐0001‐8621‐9801

Anne CS McIntosh httpsorcidorg0000‐0002‐7802‐2205

Jennie R McLaren httpsorcidorg0000‐0003‐2004‐4783

Dave Morris httpsorcidorg0000‐0002‐5739‐0594

Nelson Thiffault httpsorcidorg0000‐0003‐2017‐6890

Jean‐Pierre Tremblay httpsorcidorg0000‐0003‐0978‐529X

Alison D Munson httpsorcidorg0000‐0001‐6013‐7998

R E FE R E N C E S

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Albert C H Thuiller W Yoccoz N G Douzet R Aubert S ampLavorel S (2010) A multi‐trait approach reveals the structureand the relative importance of intra‐ vs interspecific variabilityin plant traits Functional Ecology 24(6) 1192ndash1201 httpsdoiorg101111j1365‐2435201001727x

Albert C H Thuiller W Yoccoz N G Soudant A Boucher FSacconePampLavorelS(2010)IntraspecificfunctionalvariabilityExtentstructureandsourcesofvariationJournal of Ecology98(3)604ndash613httpsdoiorg101111j1365‐2745201001651x

AndereggW R L (2015) Spatial and temporal variation in plant hy-draulictraitsandtheirrelevanceforclimatechangeimpactsonvege-tationNew Phytologist205(3)1008ndash1014httpsdoiorg101111nph12907

AubinIBoisvert‐MarshLKebliHMcKenneyDPedlarJLawrenceK hellip Ste‐Marie C (2018) Tree vulnerability to climate changeImproving exposure‐based assessments using traits as indicatorsof sensitivity Ecosphere 9(2) e02108 httpsdoiorg101002ecs22108

AubinIMessierCampKneeshawD(2005)PopulationstructureandgrowthacclimationofmountainmaplealongasuccessionalgradientinthesouthernborealforestEcoscience12(4)540ndash548httpsdoiorg102980i1195‐6860‐12‐4‐5401

AubinIMunsonADCardouFBurtonPJIsabelNPedlarJHhellipMcKenneyD(2016)TraitstostaytraitstomoveAreviewoffunc-tional traits to assess sensitivity and adaptive capacity of temper-ateandborealtreestoclimatechangeEnvironmental Reviews24(2)164ndash186httpsdoiorg101139er‐2015‐0072

AugerSampShipleyB(2013)Inter‐specificandintra‐specifictraitvari-ationalongshortenvironmentalgradientsinanold‐growthtemper-ateforestJournal of Vegetation Science24(3)419ndash428httpsdoiorg101111j1654‐1103201201473x

Baraloto C Timothy Paine C E Patintildeo S BonalDHeacuterault B ampChaveJ(2010)Functionaltraitvariationandsamplingstrategiesinspecies‐richplant communitiesFunctional Ecology24(1)208ndash216httpsdoiorg101111j1365‐2435200901600x

Bardgett R D Mommer L amp De Vries F T (2014) Going under-ground Root traits as drivers of ecosystem processes Trends in Ecology amp Evolution 29(12) 692ndash699 httpsdoiorg101016jtree201410006


Bartemucci PMessier C amp Canham C D (2006) Overstory influ-encesonlightattenuationpatternsandunderstoryplantcommunitydiversity and composition in southern boreal forests of QuebecCanadian Journal of Forest Research36(9) 2065ndash2079 httpsdoiorg101139x06‐088

Bates D Maechler M Bolker B Walker S Christensen R H BSingmannHhellipBolkerB(2015)Package lsquolme4rsquo

BoiffinJAubinIampMunsonAD(2015)Ecologicalcontrolsonpost‐firevegetationassemblyatmultiplespatialscales ineasternNorthAmerican boreal forests Journal of Vegetation Science26(2) 360ndash372httpsdoiorg101111jvs12245

BonanGBampShugartHH(1989)EnvironmentalfactorsandecologicalprocessesinborealforestsAnnual Review of Ecology and Systematics20(1)1ndash28httpsdoiorg101146annureves20110189000245

BurtonJIPerakisSSMcKenzieSCLawrenceCEPuettmannKJampTjoelkerM(2017)IntraspecificvariabilityandreactionnormsofforestunderstoreyplantspeciestraitsFunctional Ecology31(10)1881ndash1893httpsdoiorg1011111365‐243512898

Butler E E Datta A Flores‐Moreno H Chen MWythers K RFazayeliFhellipReichPB(2017)Mappinglocalandglobalvariabil-ity in plant trait distributionsProceedings of the National Academy of Sciences 114(51) E10937ndashE10946 httpsdoiorg101073pnas1708984114

CanadianNationalVegetationClassification (2015)Vegetation zones of Canada [map]Draft version31 [July2015ndashunderdevelopment]Scale15000000SaultSteMarieONNaturalResourcesCanadaCanadianForestService

Cornelissen J H C Lavorel S Garnier E Diacuteaz S Buchmann NGurvichD Ehellip PoorterH (2003) A handbook of protocols forstandardised and easy measurement of plant functional traitsworldwide Australian Journal of Botany51(4)335ndash380httpsdoiorg101071BT02124

Fajardo A amp Piper F I (2011) Intraspecific trait variation and co-variation in a widespread tree species (Nothofagus pumilio) insouthern Chile New Phytologist 189(1) 259ndash271 httpsdoiorg101111j1469‐8137201003468x

FreschetGTBellinghamPJLyverPOBBonnerKIampWardleDA(2013)Plasticityinabove‐andbelowgroundresourceacquisi-tiontraits inresponsetosingleandmultipleenvironmentalfactorsinthreetreespeciesEcology and Evolution3(4)1065ndash1078httpsdoiorg101002ece3520

FreschetGTSwartEMampCornelissenJH(2015)Integratedplantphenotypic responses to contrasting above‐and below‐ground re-sourcesKeyrolesofspecificleafareaandrootmassfractionNew Phytologist206(4)1247ndash1260httpsdoiorg101111nph13352

GarnierENavasM‐LampGrigulisK(2015)Plant functional diversity Organism traits community structure and ecosystem propertiesNewYorkNYOxfordUniversityPress

GelmanAampHillJ(2007)Data analysis using regression and multilevelhierarchical modelsCambridgeNYCambridgeUniversityPress

GilliamFSampRobertsMR (2003)The herbaceous layer in forests of eastern North AmericaNewYorkNYOxfordUniversityPress

HelsenKAcharyaKPBrunetJCousinsSAODecocqGHermyMhellipGraaeBJ (2017)Bioticandabioticdriversof intraspecifictrait variation within plant populations of three herbaceous plantspeciesalongalatitudinalgradientBMC Ecology17(1)38httpsdoiorg101186s12898‐017‐0151‐y

Iversen C M McCormack M L Powell A S Blackwood C BFreschet G T Kattge J hellip Violle C (2017) A global Fine‐RootEcology Database to address below‐ground challenges in plantecology New Phytologist 215(1) 15ndash26 httpsdoiorg101111nph14486

JacksonBGPeltzerDAampWardleDA(2013)Thewithin‐speciesleafeconomicspectrumdoesnotpredictleaflitterdecomposabilityat

eitherthewithin‐speciesorwholecommunitylevelsJournal of Ecology101(6)1409ndash1419httpsdoiorg1011111365‐274512155

Jung V Violle C Mondy C Hoffmann L amp Muller S (2010)Intraspecific variability and trait‐based community as-sembly Journal of Ecology 98(5) 1134ndash1140 httpsdoiorg101111j1365‐2745201001687x

KangMChangSXYanERampWangXH (2014)Traitvariabil-ity differs between leaf andwood tissues across ecological scalesinsubtropicalforestsJournal of Vegetation Science25(3)703ndash714httpsdoiorg101111jvs12118

KazakouEViolleCRoumetCNavasM‐LVileDKattge JampGarnierE(2014)Aretrait‐basedspeciesrankingsconsistentacrossdatasetsandspatialscalesJournal of Vegetation Science25(1)235ndash247httpsdoiorg101111jvs12066

KeddyPA(1992)AssemblyandresponserulesTwogoalsforpredic-tivecommunityecologyJournal of Vegetation Science3(2)157ndash164httpsdoiorg1023073235676

Kichenin EWardle D A Peltzer D A Morse CW amp FreschetG T (2013) Contrasting effects of plant inter‐and intraspecificvariation on community‐level trait measures along an environ-mental gradient Functional Ecology 27(5) 1254ndash1261 httpsdoiorg1011111365‐243512116

Kramer‐Walter K R Bellingham P J Millar T R Smissen R DRichardsonSJampLaughlinDC(2016)Roottraitsaremultidimen-sionalSpecificroot lengthis independentfromroottissuedensityandtheplanteconomicspectrumJournal of Ecology104(5)1299ndash1310httpsdoiorg1011111365‐274512562

KumordziBBAubin ICardouFShipleyBViolleC JohnstoneJhellipMunsonAD(2019)DatafromGeographicscaleanddistur-bance influence intraspecific traitvariability in leavesand rootsofNorthAmericanunderstoreyplantsDryad Digital Repositoryhttpsdoiorg105061dryad434gv5p

KumordziBBGundaleMJNilssonM‐CampWardleDA(2016)Shiftsinabovegroundbiomassallocationpatternsofdominantshrubspecies across a strong environmental gradient PLoS ONE 11(6)e0157136httpsdoiorg101371journalpone0157136

KumordziBBNilssonM‐CGundaleMJampWardleDA(2014)Changesinlocal‐scaleintraspecifictraitvariabilityofdominantspe-ciesacrosscontrastingislandecosystemsEcosphere5(3)1ndash17httpsdoiorg101890ES13‐003391

Lajoie G amp Vellend M (2015) Understanding context dependencein the contribution of intraspecific variation to community traitndashenvironment matching Ecology 96(11) 2912ndash2922 httpsdoiorg10189015‐01561

LarsenJA(1980)The boreal ecosystemNewYorkAcademicPressLaughlinDC JoshiCBodegomPMBastowZAFuleacutePZamp

FukamiT (2012)Apredictivemodelofcommunityassembly thatincorporates intraspecific trait variation Ecology Letters 15(11)1291ndash1299httpsdoiorg101111j1461‐0248201201852x

LeBagousse‐PinguetYBelloFVandewalleMLepsJampSykesMT(2014)Speciesrichnessoflimestonegrasslandsincreaseswithtraitoverlap Evidence fromwithin‐and between‐species functional di-versitypartitioningJournal of Ecology102(2)466ndash474httpsdoiorg1011111365‐274512201

Le Bagousse‐Pinguet Y Boumlrger L Quero J‐L Garciacutea‐Goacutemez MSorianoSMaestreFTampGrossN(2015)Traitsofneighbouringplantsandspacelimitationdetermineintraspecifictraitvariabilityinsemi‐aridshrublandsJournal of Ecology103(6)1647ndash1657httpsdoiorg1011111365‐274512480

Liu G Freschet G T Pan X Cornelissen J H C Li Y ampDong M (2010) Coordinated variation in leaf and root traitsacross multiple spatial scales in Chinese semi‐arid and aridecosystems New Phytologist 188(2) 543ndash553 httpsdoiorg101111j1469‐8137201003388x


LowtherJR (1980)UseofasinglesulphuricacidndashHydrogenperox-idedigestfortheanalysisofPinus radiataneedlesCommunications in Soil Science and Plant Analysis 11(2) 175ndash188 httpsdoiorg10108000103628009367026

MaireVGrossNHillDMartinRWirthCWrightIJampSoussanaJ‐F (2013) Disentangling coordination among functional traitsusinganindividual‐centredmodel Impactonplantperformanceatintra‐andinter‐specificlevelsPLoS ONE8(10)e77372httpsdoiorg101371journalpone0077372

McKenneyDWHutchinsonMFPapadopolPLawrenceKPedlarJ Campbell K hellip Owen T (2011) Customized spatial climatemodelsforNorthAmericaBulletin of the American Meteorological Society92(12)1611ndash1622httpsdoiorg1011752011BAMS31321

MessierJMcGillBJEnquistBJampLechowiczMJ (2016)Traitvariation and integration across scales Is the leaf economic spec-trumpresentatlocalscalesEcography40(6)685ndash697httpsdoiorg101111ecog02006

MoreiraBTavsanogluCcedilampPausasJG(2012)LocalversusregionalintraspecificvariabilityinregenerationtraitsOecologia168(3)671ndash677httpsdoiorg101007s00442‐011‐2127‐5

NeufeldHSampYoungDR(2003)Ecophysiologyoftheherbaceouslayer intemperatedeciduousforests InFGilliamampMRRoberts(Eds)The herbaceous layer in forests of North America (pp 38ndash90)NewYorkNYOxfordUniversityPress

Peacuterez‐Harguindeguy N Diacuteaz S Garnier E Lavorel S Poorter HJaureguiberryPhellipCornelissenJHC(2013)Newhandbookforstandardised measurement of plant functional traits worldwideAustralian Journal of Botany61(3)167ndash234httpsdoiorg101071BT12225

PoorterHNiinemetsUumlPoorter LWright I JampVillarR (2009)Causesandconsequencesofvariationinleafmassperarea(LMA)A meta‐analysis New Phytologist 182(3) 565ndash588 httpsdoiorg101111j1469‐8137200902830x

R Development Core Team (2014) R A language and environment for statistical computing Vienna Austria R Foundation for StatisticalComputing

ReichPB EllsworthD SWaltersMBVose JMGreshamCVolinJCampBowmanWD(1999)Generalityofleaftraitrelation-shipsAtestacrosssixbiomesEcology80(6)1955ndash1969httpsdoiorg1018900012‐9658(1999)080[1955GOLTRA]20CO2

ReichPBWright I JCavender‐Bares JCraine JMOleksyn JWestobyMampWaltersMB(2003)Theevolutionofplantfunc-tionalvariationTraitsspectraandstrategiesInternational Journal of Plant Sciences164(S3)S143ndashS164httpsdoiorg101086374368

RossM S Flanagan L B amp Roi GH L (1986) Seasonal and suc-cessionalchangesinlightqualityandquantityintheunderstoryofborealforestecosystemsCanadian Journal of Botany64(11)2792ndash2799httpsdoiorg101139b86‐373

RoumetCBirousteMPicon‐CochardCGhestemMOsmanNVrignon‐Brenas S hellip Stokes A (2016) Root structurendashfunctionrelationshipsin74speciesEvidenceofarooteconomicsspectrumrelatedtocarboneconomyNew Phytologist210(3)815ndash826httpsdoiorg101111nph13828

RoweJS(1983)Conceptsoffireeffectsonplantindividualsandspe-ciesInRWeinampDMaclean(Eds)The role of fire in northern circum‐polar ecosystems(pp431ndash473)ChichesterNYJohnWileyampSonspublishedonbehalfoftheScientificCommitteeonProblemsoftheEnvironmentoftheInternationalCouncilofScientificUnions

SchulteLAampMladenoffDJ(2005)SeverewindandfireregimesinnorthernforestsHistoricalvariabilityattheregionalscaleEcology86(2)431ndash445httpsdoiorg10189003‐4065

Shipley B De Bello F Cornelissen J H C Laliberteacute E LaughlinDCampReichPB (2016)Reinforcing loosefoundationstones in

trait‐based plant ecologyOecologia 180(4) 923ndash931 httpsdoiorg101007s00442‐016‐3549‐x

SidesCBEnquistB JEbersole J J SmithMNHendersonAN amp Sloat L L (2014) Revisiting Darwinrsquos hypothesis DoesgreaterintraspecificvariabilityincreasespeciesrsquoecologicalbreadthAmerican Journal of Botany101(1)56ndash62httpsdoiorg103732ajb1300284

SiefertA (2012) Incorporating intraspecificvariation intestsof trait‐basedcommunityassemblyOecologia170(3)767ndash775httpsdoiorg101007s00442‐012‐2351‐7

SiefertAViolleCChalmandrierLAlbertCHTaudiereAFajardoA hellipWardle D A (2015) A global meta‐analysis of the relativeextentof intraspecific trait variation inplant communitiesEcology Letters18(12)1406ndash1419httpsdoiorg101111ele12508

SilvertownJampCharlesworthD(2009)Introduction to plant population biology (4th ed)MaldenMAOxfordUKCarlton JohnWileyampSons

Suding KN Lavorel S Chapin F S Cornelissen J H C Diacuteaz SGarnier E hellip Navas M‐L (2008) Scaling environmental changethrough the community‐level A trait‐based response‐and‐effectframeworkforplantsGlobal Change Biology14(5)1125ndash1140httpsdoiorg101111j1365‐2486200801557x

ThiffaultEBeacutelangerNPareacuteDampMunsonA (2007)Howdo for-estharvestingmethodscomparewithwildfireAcasestudyofsoilchemistryand treenutrition in theboreal forestCanadian Journal of Forest Research371658ndash1668httpsdoiorg101139X07‐031

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SUPPORTING INFORMATION

Additional supporting information may be found online in theSupportingInformationsectionattheendofthearticle

How to cite this articleKumordziBBAubinICardouFetalGeographicscaleanddisturbanceinfluenceintraspecifictraitvariabilityinleavesandrootsofNorthAmericanunderstoreyplantsFunct Ecol 2019001ndash14 httpsdoiorg1011111365‐243513402


1emsp |emspINTRODUC TION

Interactionsbetweengeneticmake‐upandanindividualsenviron-mentexpressedastraitvariabilityareatthecoreoftodaysmostpressing questions in macroecology More specifically variabilityin plant traits can contributemuch to our understanding of plantperformance and fitness across environmental gradients (Keddy1992 Violle et al 2012) Although less frequently characterizedthanbetween‐speciesvariability(AlbertThuillerYoccozSoudantetal2010LeBagousse‐PinguetBelloVandewalleLepsampSykes2014GarnierNavasampGrigulis2015) intraspecific trait variabil-ity (ITV) that is traitvariabilityamong individualsofasinglespe-cies is increasinglybeing recognizedasamajor factor for speciescoexistence and persistence in a changing environment (Butler etal2017Shipleyetal2016Violleetal2012)ByformallytakingITVintoaccountcommunityecologistshaveimprovedbothdetec-tionof community assemblymechanisms (LeBagousse‐Pinguetetal 2014 JungViolleMondyHoffmannampMuller 2010 Siefert2012)andpredictionofglobal change impactsonecosystempro-cesses(JacksonPeltzerampWardle2013WardleBardgettWalkerampBonner2009)

ThereisnowgoodevidencethatthegeneralassumptionthatITVislowerthaninterspecificvariabilitydoesnotholdtrueinallsituations(Kazakouetal2014KicheninWardlePeltzerMorseampFreschet2013 Kumordzi Nilsson Gundale amp Wardle 2014) The crucialquestionthatemergesisthereforewhenandwhyisITVmoreim-portantPreviousstudieshavesuggestedthatITVisamechanismbywhichplantspeciesrespondtolocalspatialresourceheterogeneity(ValladaresGianoliampGoacutemez2007)andisrelatedtoenvironmentalvariationacrossthespeciesrsquorange(Helsenetal2017)Intraspecifictraitvariabilitymaybeparticularlyimportantinlowdiversityecosys-temswherereducedcompetitioncouldallowindividualsofthesamespecies tooccupy a larger trait space (FreschetBellingham LyverBonner ampWardle 2013 SilvertownampCharlesworth 2009 Violleetal2012)Forspecieswithwidespreadgeographicaldistributions(FajardoampPiper2011Sidesetal2014)greater ITVcouldrepre-sentbetteradaptationtoawiderangeofenvironmentalconditions(Albert Grassein Schurr Vieilledent amp Violle 2011 Sides et al2014Vasseuretal2018)Thespatial variance partitioning hypothesis predictsthatITVwillsaturatewithincreasingspatialscale(Albertetal2011)andthereforealargeproportionofthevariabilityshouldbeobservedatthelocalscale(Burtonetal2017)

ofITViscapturedatdifferentspatialscalesparticularlywhenlocalscaledistur-bancesareconsideredand(c)Isthevariancestructureconsistentbetweenanalo-gousleafandroottraitsandbetweenmorphologicalandchemicaltraits

3 Following standardizedmethodswe sampled818populations across79 forestplotssimultaneously includingdisturbedandundisturbedstandsspanningfourbiophysicalregions(~5200km)Traitsmeasuredincludedspecificleafarea(SLA)specificrootlength(SRL)andleafandrootnutrientconcentrations(NPKMgCa)We used variance decomposition techniques to characterize ITV structureacrossscales

4 OurresultsshowthatanimportantproportionofITVoccurredatthelocalscalewhensamplingincludedcontrastingenvironmentalconditionsresultingfromlocaldisturbanceAcertainproportionofthevariabilityinbothleafandroottraitsre-mainedunaccountedforbythethreesamplingscalesincludedinthedesign(36onaverage)withthelargestamountforSRL(54)Substantialdifferencesinmag-nitudeof ITVwerefoundamongthesixspeciesandbetweenanalogoustraitssuggestingthattraitdistributionwasinfluencedbyspeciesstrategyandreflectstheextentofunderstoreyenvironmentheterogeneity

5 Even for species with broad geographical distributions a large proportion ofwithin‐speciestraitvariabilitycanbecapturedbysamplinglocallyacrossecologi-calgradientsThishaspracticalimplicationsforsamplingdesignandtraitselectionforbothlocalstudiesandcontinental‐scalemodelling

K E Y W O R D S

functionalbiogeographyintraspecifictraitvariabilityleaftraitplantfunctionaltraitroottraitspecificleafareaspecificrootlengthtissuenutrientconcentration


















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0 500 1000 1500 2000250 Kilometres

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3emsp |emspRESULTS










































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Geographic scale and disturbance influence intraspecific trait ... · KUMORDZ ET AL.Functional...

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