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J Veg Sci 201930257ndash268 wileyonlinelibrarycomjournaljvs emsp|emsp257
Journal of Vegetation Science
copy 2018 International Association for Vegetation Science
Received25July2018emsp |emsp Revised29November2018emsp |emsp Accepted3December2018DOI101111jvs12708
R E S E A R C H A R T I C L E
Variation in compositional and structural components of community assemblage and its determinants
Jie Yao1 emsp|emspChunyu Zhang1emsp|emspMiquel De Caacuteceres23emsp|emspPierre Legendre4emsp|emspXiuhai Zhao1
1ResearchCenterofForestManagementEngineeringofStateForestryandGrasslandAdministrationBeijingForestryUniversityBeijingChina2ForestSciencesCentreofCatalonia(CTFC)SolsonaSpain3CenterforEcologicalResearchandForestryApplications(CREAF)CerdanyoladelVallegravesSpain4DeacutepartementdeSciencesBiologiquesUniversiteacutedeMontreacutealMontreacutealQuebecCanada
CorrespondenceXiuhaiZhaoResearchCenterofForestManagementEngineeringofStateForestryandGrasslandAdministrationBeijingForestryUniversityBeijingChinaEmailzhaoxhbjfueducn
Funding informationKeyProjectofNationalKeyResearchandDevelopmentPlan(2017YFC050400101)andProgramofNationalNaturalScienceFoundationofChina(31670643)
Co-ordinatingEditorStephenRoxburgh
AbstractQuestions WhataretheecologicalprocessesthatdeterminethespatialdistributionofspeciesandspeciesdiversityPartitioningbetadiversitycanprovidefundamentalinsights into the processes that determine the spatial variation of species assem-blages However studying beta diversity is conventionally based only on speciescompositiondataignoringthestructuralcomponentofcommunitiesStudy site TemperatemixedbroadleafndashconiferforestinJiaoheJilinProvincenorth-easternChinaMethods Wecharacterizedthevariationofcommunityassemblagesintermsofspe-ciescompositionsizestructureorconsideringbothcomponentsWethenemployedenvironmentalandspatialvariablesasexplanatoryfactorstopartitionthevariationinbothcompositionalandstructuralcomponentsofcommunityassemblageandas-sess the relative contributions of the niche and neutral processes to communityassemblyResults Thevaluesofoverallbetadiversity(BDstatistics)andtherelativecontribu-tion of individual sampling units to beta diversity (LCBD indices) depended onwhether thespeciescompositionsizestructureorbothtogetherhadbeentakenintoaccountThevalueofcompositionalndashstructuralbetadiversitywasthelargestfollowedbytraditionalcompositionalbetadiversitythesmallestwasthestructuralbetadiversityThesiteswithhighcontributionstobetadiversity(LCBDvalues)var-iedamongstructuralandcompositionalcomponentsTheexplanatorypoweroftheenvironmentalvariablesand thespatialvariablesalsovariedwidelywithdifferentcomponentsofacommunityThecombinationofenvironmentalandspatialvariablesexplainedthehighestproportionofvariation(438)inthecompositionalcompo-nentandexplainedthelowestproportionofvariation(254)inthestructuralcom-ponentofcommunityassemblageConclusion Both deterministic and stochastic processes are acting to determinecommunityassemblagesintermsofspeciescompositionandstructureinourtem-perateforestsiteOurstudyhighlightstheimportanceofconsideringthestructuralcomponentofforestcommunitiesinadditiontocompositionaldatawhenstudyingbetadiversity
K E Y WO RD S
betadiversitycommunityassemblagecumulativeabundanceprofilelocalcontributionstobetadiversitysizestructurespeciescompositionvariationpartitioning
258emsp |emsp emspenspJournal of Vegetation Science
YAO et Al
1emsp |emspINTRODUCTION
Understandingthemechanismsthatdeterminethespatialdistri-butionofspeciesandspeciesdiversityisacentralthemeinecol-ogy (Chave 2004 Chesson 2000 Hutchinson 1961 Ricklefs1990 Vellend 2017) Deterministic niche-based and stochasticneutral processes have beenwidely discussed as potential driv-ers of community assembly (Chesson 2000 HilleRisLambersAdler Harpole Levine ampMayfield 2012Hubbell 2001 2006MayfieldampLevine2010)butthefactorsunderlyingtherelativecontributionof the twoprocessesarestillunresolved (Legendreetal2009Punchi-Manageetal2014vanderPlasetal2015)Niche and neutral theories emphasize different mechanisms assources of species diversity Niche theory predicts that deter-ministicprocessessuchashabitatfilteringandcompetitionshapespeciesassemblagesNeutraltheoryincontrastassumesthatallspecies are essentially functionally equivalent (HilleRisLambersetal 2012Hubbell 20012006Keddy1992) andemphasizesthe importance of stochastic processes in community assemblysuchasrandombirthdeathdispersaleventsspeciationandsto-chasticextinction(Caswell1976Hubbell2001)Itisnowgener-allyacceptedthatboththedeterministicandstochasticprocessesarepotentiallyimportantdeterminantsofthespatialdistributionobserved in community assemblagesAt present however theirrelative importance in shapingdifferent componentsof commu-nityorganization(iethestructuralcompositionalorbothcom-ponentstogether)isnotclear(DeCaacuteceresetal2012Legendreetal2009Punchi-Manageetal2014)Inthepresentstudywedefinedtheldquocompositionalrdquotermasthespeciescompositiondata(egspeciesabundancevalues)Weconstrainedthedefinitionofldquostructuralrdquotorefertothediameteratbreastheightoftheindivid-ualtreesmakingupthecommunity
Thevariationinspeciescompositionobservedamongasetofsamplingunitswithinaregionisoftendescribedasbetadiversity(Whittaker19601972)Theinterestofcommunityecologistsforbetadiversitystemsnotonlyfromthefactthatitlinkslocal(iealphadiversity) and regionaldiversity (ie gammadiversity) (DeCaacuteceresetal2012)butalsobecauseitcanprovidefundamentalinsights into theprocesses thatdetermine the spatialpatternofspecies assemblages (Anderson etal 2011 Chase 2010 Kraftetal 2011 Legendre amp De Caacuteceres 2013Myers etal 2013)Beta diversity can bemeasured inmany different ways (KoleffGastonampLennon2003LegendreBorcardampPeres-Neto2005Legendre amp Legendre 2012 Legendre etal 2009) Beta diver-sityestimatesaremostoftenbasedonspeciescompositionaldata(egspeciesabundancevaluesorspecies incidence)whichtakethe formof a site-by-species datamatrixwith sites in rows andspecies abundances in columns Although species compositiondataarefundamentallyimportanttheyalonemaybeinsufficientfor describing community organization and may neglect othervaluable information to study community assembly processessuchasthestructuralcomponent(egthesizestructureofcon-stituentindividuals)ofacommunity(DeCaacuteceresLegendreampHe
2013FaithAustinBelbinampMargules1985Fangetal2012)The phenomenon of competition asymmetry emphasizes thatlarge individuals usually compete disproportionately with theirsmaller-sized neighbors (Weiner 1990) Big trees control moreabove- and below-ground resources (eg light and mineral nu-trients)thansmalltrees(SchwinningampWeiner1998)ThereforelargerindividualstendtohavegreaterimpactonthefunctionanddynamicsofforestecosystemsthansmallonesMoreovernaturalmulti-species communities may exhibit similar compositions butdifferinotherfeaturessuchasthesizestructureoftheirindividu-als(DeCaacuteceresetal2013)Thedistributionofindividualsizesisalsoan importantcomponenttorepresentandunderstandcom-munity assembly therefore using species abundances only (iethe compositional component) to describe forest beta diversitymay be an oversimplification of the spatial variation of commu-nities In order to get comprehensive insight into the processesthat determine the spatial pattern of species assemblages it isnecessarytoensurefirstthatwehavetheabilitytodescribebetadiversity inacomprehensivewayWhetherornotthestructuralcomponent shouldor couldbeconsideredaltogetherwithotherbeta diversity components has never been investigated and re-mainstobeexplored
In thisstudywegeneralizedtheconventionalapproachto thestudy of beta diversity by considering structural data in additiontocompositionaldataWefirstmeasurethespatialvariationofas-semblagesonthebasisofspeciescompositionandsizestructureofconstituentsWethenusetheenvironmentalandspatialvariablesas explanatory factors to partition the variation in compositionalandstructuralcomponentsofcommunityassemblageWespecifi-callyaddressthefollowingquestions(a)Canwetakeboththespe-ciescompositionalandsizestructuralcomponentsofacommunityintoaccountwhendescribingbetadiversity Isthereacorrelationbetween thesebetadiversity components (b)How is the assess-mentofthesebetadiversitycomponentsaffectedbythesizeofthesampling units (c)When considering both the compositional andstructural components together towhatextentarebetadiversityassessmentsaffectedbytherelativeimportanceaccordedtostruc-tural vs compositional differences (d)What is the relative contri-bution of the environmental and spatial variables to communityassemblyintermsofspeciescompositionsizestructureorconsid-eringbothcomponents
2emsp |emspMATERIAL AND METHODS
21emsp|emspStudy sites and data collection
Ourstudywascarriedout inatemperatemixedbroadleafndashconiferforestinJiaoheJilinProvincenortheasternChinaTheaveragehot-testmonthlytemperatureis217degCinJulyandthecoldestmonthisJanuarywithanaveragedaytemperatureof -186degCTheaverageannualprecipitationis6959mm(ZhangZhaoampGadow2014)Thesoilisabrownforestsoilwitharootabledepthrangingbetween20and100cm (ZhangZhaoZhaoampGadow2012)This studyuses
emspensp emsp | emsp259Journal of Vegetation Science
YAO et Al
datafroma30-ha(500mtimes600m)forestdynamicplot(43deg57928primendash43deg58214primeN127deg45287primendash127deg45790primeE)establishedinthesum-merof2010Theplot issituated inaprotectedold-growthforestina latestageof successionwith littlehumandisturbancedue toits remoteness fromresidential areas (YaoZhangZhangZhaoampGadow2016)
Allindividualswithadiameteratbreastheight(dbh)of1cmormoreintheplotwereidentifiedmeasuredandspatiallymappedin2010Atotalof49684individualtreesbelongingto20familiesand47speciesintheplotwereusedinthepresentstudyTheplotwasdividedinto120(50mtimes50m)750(20mtimes20m)and3000(10mtimes10m)subplotshereaftercalledquadratsTopographicandsoilvari-ableswerealsoavailable foreachquadratFour topographicvari-ables(altitudequadratconvexityslopeandaspect)werecalculatedforeachquadratfollowingtherecommendationofHarmsConditHubbellandFoster(2001)andYamakuraetal(1995)Eightsoilen-vironmentalandnutrientvariablesweremeasuredpHtheamountof organic matter and the total amounts as well as the availablenutrients of nitrogen (N) phosphorus (P) and potassium (K) (ggYanZhangWangZhaoampGadow2015)All laboratoryanalyseswereconductedfollowingtheproceduresrecommendedbytheSoilScienceSocietyofChina(1999)
22emsp|emspStatistical analyses
221emsp|emspCumulative abundance profiles
Theconceptofcumulativeabundanceprofile (CAP)developedbyDeCaacuteceresetal(2013)isdefinedasafunctionthattakestheval-uesofastructuralvariable (egheightdbhetc)as inputandre-turnsthecumulativeabundanceofindividualswhosevaluesofthestructuralvariableareequal toor largerthanthe inputvalueTheCAP framework generalizes traditional species abundance valuesand allows researchers to describe the structural component of acommunityInthepresentstudythestructuralvariablewasdiam-eteratbreastheight(dbh)AccordingtothischoicethevalueofCAPforagivendbhvalueisthecumulativeabundanceoftreeindividualsasbigasorbiggerthantheinputvalueFunctionCAPinfactreplacestheabundancevalueofadbhclassbythesumofabundancesinthisandlargerdbhclasses
222emsp|emspCommunity tables
Following theconventionalmethods speciescomposition tables(ie quadrats in rows species in column and the table contain-ing individual counts)wereassembled in this studywecall thistablethetraditional species composition matrix(YCOMP)InordertogeneralizeatraditionalspeciesabundancevalueanddescribethesizestructurecomponentofthecommunitytheCAPsconsider-ingspeciesidentitywerecalculatedtoobtainthespecies composi-tion combined with structural data matrix(YCOMPndashSTR)TheYCOMPndashSTR isamatrixwithasmanyrowsasplotrecordsandwherecolumnsareorganized inblocksandthereareasmanyblocksasspecies
andeachblockhasasmanycolumnsassizeclassesDisregardingspeciesidentityofthedifferentindividualsCAPswerealsocalcu-latedtoobtainthecommunity structural matrix (YSTR)TheYSTR is amatrixwithasmanyrowsasplotrecordsandasmanycolumnsas size classes
FunctionsldquostratifyvegdatardquoandldquoCAPrdquointhevegclustRpack-age(DeCaacuteceresFontampOliva2010)availableonCRAN(httpsCRANR-projectorgpackage=vegclust) were applied to calculatetheCAPsFunctionsldquostratifyvegdatardquoandldquoCAPrdquorequirediscretiz-ingthestructuralvariableandthenumberofsizebinsaffectstheimportanceaccordedtostructuraldifferencesThustherearede-cisions tobemadewhencreatingYSTR and YCOMPndashSTR particularlyhowwedefine thebinsof thestructuralvariables (egdbhbins)Inthisstudywetestedfrom1-cmbinsizeto15-cmbinsizetodis-cretizedbhintoclassesThat is1cmbinsleadtodbhclasses1ndash22ndash33ndash4andsoonwhereas5cmbinsleadtodbhclasses1ndash56ndash1010ndash15andsoonThesmallerthesizeofdbhbinthemorecolumnswillbeproducedineachblockinthetableYCOMPndashSTRindicatingthatmoreweightisaccordedtodifferencesinstructureandviceversaIfthebinsizewasbigenoughsothatthenumberofcolumnsineachblock in the tableYCOMPndashSTRwasonewewouldhave thatYCOMPndashSTR=YCOMPGenerallythelargerthesizeofdbhbinsthemoresimi-lar will YCOMP and YCOMPndashSTR be
223emsp|emspPairwise dissimilarity in terms of community composition and structure
Wecalculateddissimilaritymatrices between all pairs of quadratsusingthepercentagedifferenceindex(akaBrayndashCurtisdissimilar-ity)oncommunitymatricesYCOMPYSTRandYCOMPndashSTRtoobtainthe compositional dissimilarity matrix (DCOMP) the structural dissimilar-ity matrix (DSTR)andthe compositionalndashstructural dissimilarity matrix (DCOMPndashSTR) respectively In order to explore the pairwise covari-ation between the three kinds of dissimilarity assessments (ieDCOMP vs DSTRDCOMP vs DCOMPndashSTRandDSTR vs DCOMPndashSTR)wefirstcomputed principal coordinates of each dissimilarity matrix usingprincipalcoordinatesanalysis (PCoA) thencomparedtheresultingmatricesofprincipalcoordinateskeepingallaxesusingtheRVco-efficientWeexpectedthatDCOMPndashSTRwouldbecorrelatedtobothDCOMP and DSTRbutthestrengthofthecorrelationdoesdependonthechosensizeofdiameterbins(ieontheweightgiventostruc-turalvscompositionalinformation)
Function ldquovegdistrdquo with the dissimilarity index ldquobrayrdquo in theveganRpackage(Oksanenetal2018)wasusedtocalculatethedissimilarity matrices D Function ldquopcoardquo in the ape R package(ParadisClaudeampStrimmer2004)wasusedtocomputeprincipalcoordinates of eachdissimilaritymatrixD Thedissimilarities inD matricesweresquare-rootedbeforePCoAinordertomakethema-tricesEuclideanandpreventthegenerationofnegativeeigenvaluesandcomplexPCoAaxes (DeCaacuteceresetal2013)Function ldquocoef-fRVrdquo in the FactoMineR R package (Husson Josse LeampMazet2015)wasusedtocalculatetheRVcoefficientsbetweenthematri-cesofprincipalcoordinates
260emsp |emsp emspenspJournal of Vegetation Science
YAO et Al
224emsp|emspBeta diversity components (BDCOMP BDSTR and BDCOMPndashSTR)
Conventionallybetadiversity (abbreviatedBD) is assessed fromasite-by-speciesdatamatrixotherbasiccharacteristics(egsizeofindividuals)ofthecommunityareignoredInordertogeneral-izetheconceptoftraditionalbetadiversitytoCAPdataweap-pliedtheindexproposedbyLegendreetal (2005)andLegendreandDeCaacuteceres(2013)tocomputebetadiversityasthevarianceofthecommunitydataLegendreandDeCaacuteceres(2013)showedhow to compute the total variance of the community composi-tion datamatrix from a dissimilaritymatrixD The total sum ofsquaresSS(Y)canbeobtainedfromadissimilaritymatrixDusingEquation1(LegendreampDeCaacuteceres2013LegendreampLegendre2012) Dividing SS(Y) by (n - 1) produces the classical unbiasedestimateofthetotalvarianceofYcomputedfromauser-selectedEuclidean dissimilarity matrixD (ie Equation 2)We used thatapproach to calculate the traditional compositional beta diversity (BDCOMP) the structural beta diversity (BDSTR) and the composi-tionalndashstructural beta diversity(BDCOMPndashSTR)respectivelyusingthefollowingequations
D =(Dhi)isanntimesnsymmetricdissimilaritymatrix(eitherDCOMP
DSTRorDCOMPndashSTR) i and h representthesamplingunitsn is thenumberofthesamplingunits If thecalculationsstartwithaper-centagedifferenceDmatrixwhichisnon-Euclideanonecomputesthesquare-rootsoftheDvaluesintheDmatrixtomakeitEuclideanbeforeusingthetransformedDvaluesinEquations1and2
225emsp|emspLocal contributions to beta diversity in terms of community composition and structure
Legendre andDe Caacuteceres (2013) suggested that total beta diver-sity can be partitioned into Local Contributions toBetaDiversity(LCBDwhicharecomparative indicatorsoftheecologicalunique-nessofthesites)TheLocalContributionstoBetaDiversity(LCBDi)represent the relative contributionsof the samplingunit i to betadiversityLCBDi indicateshowexceptional thecompositionofsitei iswhencomparedtothecentroidofallpointswhichwouldrep-resent a theoretical site with the average species composition ofall the sampling units In the present study the LCBD representsthe degree of uniqueness of each sampling unit in terms of com-position andor structure of community assemblages LCBDi indi-cescanbecalculatedfromthedissimilaritymatricesD(LegendreampDeCaacuteceres2013)OnefirsttransformsthedistancematrixDintomatrixA =(ahi)=(ndash05D2
hi) then centers thematrix as proposedbyGower(1966)
where Iisanidentitymatrixofsizen1isavectorofones(oflengthn)and1primeisitstranspose(LegendreampLegendre2012)HereeachdiagonalelementofmatrixGistheSSivalues(iethesquareddis-tancetothecentroidoftheithsamplingunit)Hencethevectoroflocalcontributionsofthesitestobetadiversity(LCBDi)is
The LCBD indices are scaled to sum to 1 We used functionldquoLCBDcomprdquointheadespatialRpackage(Drayetal2018)avail-ableonCRAN(httpsCRANR-projectorgpackage=adespatial)tocalculatetheLCBDindices
Wecheckedwhetherthere isacorrelationbetweentheLCBDcoefficientscalculatedfromspeciescompositionsizestructureorusingthetwocomponentstogetherHencewecalculatedSpearmanrank correlations pairwise between the three typesof LCBDvec-tors (ieLCBDCOMPvsLCBDSTRLCBDCOMPvsLCBDCOMPndashSTRandLCBDSTRvsLCBDCOMPndashSTR)SincetheLCBDindicesindicatethede-greeofuniquenessof thesamplingunits in termsof their speciescompositionandorsizestructureweplottedtheLCBDvaluesonmapsof the30-haplotLargeLCBDvalues indicate thesites thathaveuniquespeciesassemblagesandsmallLCBDvaluesindicatethesites thathaveassemblagesthatareverysimilar to those inothersites Againwe expected LCBDCOMPndashSTR to be correlated to bothLCBDCOMP and LCBDSTR butwith the strength of the correlationdependingontheweightgiventostructuralvscompositionalinfor-mationWethusshowedthetwoextremecasesoftheLCBDmapaccordinga largestweighttothestructuralcomponentandcorre-spondinglythesmallestrelativeweighttothecompositionalcompo-nent(ie1-cmbinsize)andgivingthelargestrelativeweighttothecompositionalcomponent(ie15-cmbinsize)
226emsp|emspSets of explanatory variables environmental and spatial variables
Following Legendre etal (2009)we used altitude convexity andslope to construct third-degreepolynomial functions (ie yieldingninevariables)Themonomialswithexponentsallowthemodelingof nonlinear relationships between the topographic variables andthe response variablesWe calculated the aspect of a quadrat astheaverageangleofthefourtriangularplanesthatdeviatefromthenorthdirectionWe thusused the sin (aspect) and cos (aspect) inorder to include it in a linear regressionmodelWe thereforeob-tained11expandedtopographicvariablesWethencombinedthese11 expanded topographic variables with the eight soil variables(described insection21Studysitesanddatacollection) toobtainthe environmental variables data table (ie 19 variables) for eachquadratWe computed eigenfunctions of distance-basedMoranrsquoseigenvector maps (dbMEM also called Principal Coordinates ofNeighbour Matrices PCNM Borcard Legendre Avois-Jacquet amp
(1)SS(Y) =1
n
nminus1sum
h=1
nsum
i=h+1
D2hi
(2)BD = SS(Y)∕(nminus1)
(3)G =
(
Iminus11
n
)
A
(
Iminus11
n
)
(4)(LCBDi) = (SSi)∕SS(Y) = diag(G)∕SS(Y)
emspensp emsp | emsp261Journal of Vegetation Science
YAO et Al
Tuomisto2004LegendreampLegendre2012Legendreetal2009)acrossthe3000(10mtimes10m)750(20mtimes20m)and120(50mtimes50m)quadratsThedbMEMeigenfunctionswithpositiveeigenval-uesonlywereusedasspatialvariablesWeappliedforwardmodelselection(withpermutationtestsatthe5significanceleveloftheincrease in R2 ateachstep) toextract thesignificantenvironmentvariablesandeigenfunctionsofdbMEMusingthefunctionldquoforwardselrdquointhepackageadespatial(Drayetal2018)
227emsp|emspVariation partitioning of DCOMP DSTR and DCOMPndashSTR
Tocompare the influenceofniche-basedandspatialprocessesoncommunityassembly representedbycommunitycompositionsizestructure or the two components together distance-based re-dundancyanalysis (dbRDALegendreampAnderson1999Legendreamp Legendre 2012)was used to partition the variation of each ofthree community matrices (Borcard Legendre amp Drapeau 1992Legendre etal 2009 Peres-Neto Legendre Dray amp Borcard2006) Specificallyweused the two setsof explanatoryvariables(after forwardmodelselection) topartitionvariation in theprinci-palcoordinatetablesextractedfromDCOMPDSTRDCOMPndashSTRsepa-rately into fractions explained by the four different components(a)purehabitat (b)spatiallystructuredhabitat (c)purespaceand(d)undetermined (BorcardampLegendre1994Borcardetal1992DeCaacuteceresetal 2012Legendreetal 2009Myersetal 2013Punchi-Manage etal 2014) We hypothesized that the niche
processesareresponsiblefortheproportionofvariationexplainedbythepurehabitatandthespatially-structuredhabitatcomponents(a+b)(LaliberteacutePaquetteLegendreampBouchard2009Legendreetal2009)Whilewehypothesizedthattheproportionofvariationexplainedbythepurespatialcomponent(c)isrelatedtoindepend-ent biological processes (eg dispersal limitation competition fa-cilitationhistoricaleventsandJanzenndashConnelleffects)(LegendreampLegendre2012Legendreetal2009Punchi-Manageetal2014)Theundeterminedproportionofvariation(d)mayberelatedtosto-chastic processes or undefined non-spatially-structured biologicalor environmental variables (Dumbrell Nelson Helgason DythamampFitter2010)Thatallowedustoassesstherelativecontributionsoftheenvironmentalandspatialvariablestocommunityassemblyin termsof composition structureor taking the twocomponentstogetherAllanalyseswereperformedusingR(RCoreTeam2017)
3emsp |emspRESULTS
31emsp|emspPairwise dissimilarity in terms of community composition and structure
Wefound thatdissimilaritymatricescomputed fromspeciescom-position(DCOMP)sizestructure(DSTR)andconsideringbothcompo-nentstogether(DCOMPndashSTR)werecorrelatedHoweverthestrengthof the correlationdependedon the sizeofbinsused todiscretizethestructuralvariableandonthesizeof thequadrats (Figure1andashc) Overall the correlation between DCOMP vs DCOMPndashSTR was
F IGURE 1emspThecorrelationsbetweenthepairwisedissimilarityintermsofspeciescomposition(DCOMP)sizestructure(DSTR)andbothcomponentstogether(DCOMPndashSTR)ThecorrelationsofDCOMP vs DSTRDCOMP vs DCOMPndashSTRand DSTR vs DCOMPndashSTRvarywithdbhbinsatthescaleof(a)10mtimes10m(b)20mtimes20mand(c)50mtimes50mIngraphs(a)(b)and(c)thehorizontalreddottedlineshorizontalbluelong-dashlinesandhorizontalgreensolidlinesrepresentthemeanvaluesofRVcoefficientsof1ndash15cmdbhbinsofDCOMP vs DSTRDCOMP vs DCOMPndashSTRandDSTR vs DCOMPndashSTRrespectively(d)BoxplotsforRVcoefficientsofthethreepairwisedissimilaritycomparisons(aggregatedoverall1ndash15cmdbhbinsizes)foreachofthethreequadratsizes[Colourfigurecanbeviewedatwileyonlinelibrarycom]
262emsp |emsp emspenspJournal of Vegetation Science
YAO et Al
substantially stronger than that ofDCOMP vs DSTR andofDSTR vs DCOMPndashSTR
The correlation ofDCOMP vs DCOMPndashSTR increasedwith the in-crease of bin size Correspondingly the correlations of DSTR vs DCOMPndashSTR showed the opposite trend (Figure1andashc) As to the ef-fectofthesizeofthesamplingunitsthestrengthofcorrelationsin-creasedwiththequadratsize(Figure1d)exceptforthecorrelationbetweenDCOMP and DCOMPndashSTRwhichexhibitsnosignificantdiffer-encebetweenthe10mtimes10mand20mtimes20mquadrats(p = 023Figure1d)
32emsp|emspThe three components of beta diversity (BD) BDCOMP BDSTR and BDCOMPndashSTR
Thebetadiversity(BD)valueswerecloselyrelatedtowhetherthespecies composition size structure or both components togetherhad been taken into account Among these three components ofbetadiversityBDCOMPndashSTRwasgreatestcloselyfollowedbyBDCOMPandthesmallestwasBDSTR(Figure2)Sincethesizestructureofin-dividualswasnot consideredwhen calculatingBDCOMP this indexwasnotaffectedbythesizeofdbhbins(Figure2andashc)ThevaluesofBDCOMPndashSTRandBDSTRhoweverdecreasedslightlywithanincreaseofbinsizeWhenincreasingdbhbinsizethevaluesofBDCOMPndashSTR graduallyapproachedthevaluesofBDCOMP (Figure2andashc)BDalso
varied as a function of quadrat size (Figure2) values of BDCOMPBDSTRandBDCOMPndashSTR(afteraveragingacrossbinsizes)systemati-callydecreasedwithincreasingquadratsize(Figure2d)
33emsp|emspLocal contributions to beta diversity in terms of community composition and structure
LocalContributionstoBetaDiversitycalculatedusingspeciescom-positionsizestructureorbothcomponentswerecorrelatedAgainthe strengthof correlationsdependedon the sizeofdbhbins andon the size of quadrats (Figure3andashc) In the case of LCBDCOMP vs LCBDCOMPndashSTR the strength of the correlation increased with anincreaseofbinsizeCorrespondinglythecorrelationofLCBDSTR vs LCBDCOMPndashSTRshowedtheoppositetrend(Figure3andashc)Thecorrela-tionsofLCBDCOMPvsLCBDSTRandLCBDSTRvsLCBDCOMPndashSTR were significantly different for differentquadrat sizesA striking findingwasthatthestrengthofcorrelationswasweakeratthescaleof20mtimes20m than that at the scalesof10mtimes10mor50mtimes50m(Figure3d)HowevercorrelationsbetweenLCBDCOMPvsLCBDCOMPndashSTRwerenotsubstantiallyaffectedbythesizeofquadrats(Figure3d)
TheLCBDivaluesindicatetheithquadratsthatcontributemoreorlessthanthemeantobetadiversity(inotherwordstheithquad-ratswithhighorlowuniquenessofspeciesassemblages)TheresultsindicatedthatthesiteswithhighLCBDvalues(contributemorethan
F IGURE 2emspTheBetaDiversity(BD)intermsofspeciescomposition(BDCOMP)sizestructure(BDSTR)andbothcomponentstogether(BDCOMPndashSTR)ThevaluesofBDCOMPndashSTRandBDSTRvarywiththesizeofbinsofthestructuralvariable(dbhbinsizes=1ndash15cm)atthescaleof(a)10mtimes10m(b)20mtimes20mand(c)50mtimes50mThesizestructureofindividuals(iethedbh)isnotconsideredwhencalculatingtheBDCOMPthusthevaluesofBDCOMPwerenotaffectedbythebinsizeIngraphs(a)(b)and(c)thehorizontalbluelong-dashlinesandhorizontalgreensolidlinesrepresentthemeanvaluesofBDCOMPndashSTRandBDSTRacross1ndash15cmbinsizesrespectively(d)ValuesofBDCOMPBDSTRandBDCOMPndashSTR(afteraveragingacrossdbhbinsizes)varywiththesamplingunitsizes[Colourfigurecanbeviewedatwileyonlinelibrarycom]
emspensp emsp | emsp263Journal of Vegetation Science
YAO et Al
themeantobetadiversity)arevariedamongthreecomponentsofacommunity (Figure4)Specifically342(456)290(387)and331 (441)outof750quadratscontributedmorethanthemeanto beta diversity in term of species composition (ie LCBDCOMPFigure4a)sizestructure(ieLCBDSTRFigure4g)andbothcompo-nentstogether(ieLCBDCOMPndashSTRFigure4f)respectively
34emsp|emspVariation partitioning of matrices DCOMP DSTR and DCOMPndashSTR
Theexplanatorypoweroftheenvironmentalvariablesandthespa-tialvariablesvariedforthethreetypesofmatricesandwithquadratsizes (Table 1) The variation explained by the environmental vari-ables(a+b)andbythespatialvariables(b+c)increasedsystemati-callywith increasingscale (Table1)Averagingacrossquadratsizeshabitatandspacejointlyexplained438254and341ofthevariation in compositional component structural component andthe two components together of community assemblage respec-tivelyHoweverthecontributionofthepurehabitatcomponent (a)was negligible The combination of environmental and spatial vari-ablesexplained the lowestproportionofvariation in the structuralcomponentaloneandexplainedthehighestproportionofvariationinthecompositionalcomponentalone(Table1)Boththeenvironmen-talvariables(a+b)andthepurespatialvariables(c)explainedmore
variationinthecompositionalcomponentthanthatinthestructuralcomponentsofcommunityassemblageAdditionallyourfindingsin-dicatethattheunexplained(d)fractionsdominatedthevariancepar-titioningcomputedforthestructuralcomponentYstralone(Table1)
4emsp |emspDISCUSSION
Forest ecosystems can be characterized and evaluated in terms ofboththeirstructureandcomposition(Peet1992)Inpreviousstud-ies the compositional and structural components of a communityassemblagewereusuallyanalyzedseparately(egFangetal2012)Howeverthenatureofspeciesassemblagesindicatesthateitherspe-cies composition or size structure of constituent individuals alonemayoversimplifycommunityorganization (DeCaacuteceresetal2013)Changes in structure and compositionmay be onlyweakly related(egArsenaultampBradfield1995)thereforeassessmentofbothsi-multaneouslyisimportantwhenevaluatingcommunityassemblyInthepresentstudywegeneralizedtheconventionalapproachtocom-munityassemblagebyincorporatingstructuraldataofacommunityinadditiontocompositionaldatausingtheCAPframeworkToourknowledge this is the firstpaper that investigates inasinglestudythevariationinboththecompositionalandstructuralcomponentsofcommunityassemblagessimultaneouslyaswellasitsdeterminants
F IGURE 3emspThecorrelationsbetweentheLocalContributionstoBetaDiversity(LCBD)intermsofcommunitycomposition(LCBDCOMP)structure(LCBDSTR)andbothcomponentstogether(LCBDCOMPndashSTR)ThecorrelationsofLCBDCOMPvsLCBDSTRLCBDCOMP vsLCBDCOMPndashSTRandLCBDSTR vs LCBDCOMPndashSTRwiththesizeofbinsofthestructuralvariable(binsizes=1ndash15cm)atthescaleof(a)10mtimes10m(b)20mtimes20mand(c)50mtimes50mIngraphs(a)(b)and(c)thehorizontalreddottedlineshorizontalbluelong-dashlinesandhorizontalgreensolidlinesrepresentthemeanvaluesofSpearmanrsquosrankcorrelationcoefficientr across 1ndash15 cm binsizeofLCBDCOMPvsLCBDSTRLCBDCOMPvsLCBDCOMPndashSTRLCBDSTR vs LCBDCOMPndashSTRrespectively(d)BoxplotsfortheSpearmanrsquosrankcorrelationcoefficientrbetweenthepairwiseofthethreekindsofLCBDof1ndash15cmbinsizesatdifferentquadratsizes[Colourfigurecanbeviewedatwileyonlinelibrarycom]
264emsp |emsp emspenspJournal of Vegetation Science
YAO et Al
We found thatbothoverall betadiversity (BD) and the rela-tive contribution of sampling units to beta diversity (LCBD) de-pended on whether the species composition size structure orbothcomponentstogetherhadbeentakenintoaccountBetadi-versity partitioning indicated that the explanatory power of the
environmental and the spatial variables also varied widely withdifferentcomponentsofacommunityOur resultshighlight thatconsideringboth species compositional and size structural com-ponentsmaybeamorecomprehensivewaytodescribethecom-munityorganization
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41emsp|emspStructural and compositional components of forest variation
The framework of CAP allowed us to incorporate the distribu-tionof individualtreesize intotheanalysisofcommunityassem-blage thusmaking it possible toquantify the spatial variationofcommunitystructurebetadiversityEvensosuchstructuralbetadiversitycanbequantified independentlyor incombinationwithspecies composition TheBDCOMPndashSTR is the largest among thesethreecomponentsofbetadiversity indicating thatapplyingspe-ciescompositionaloneorsizestructurealonetoassessthebetadi-versitymayunderestimatethevariationofassemblages(Figure2)ThevaluesofBDCOMPareclosertotheBDCOMPndashSTRvaluesthanthatofBDSTR(theBDSTRvaluesarerelativelysmallFigure2)ThusasfarasourCAPframework isconcerned it seemsmoreappropri-atetoquantifybetadiversityusingthespeciescomposition indi-viduallythanusingthesizestructureindividuallyNeverthelessifstructureprovidesindependentinformationandisdeemedimpor-tantoneshouldincorporateitinBDassessmentAsbetadiversityindiceswerecalculatedfromdissimilaritymatrices thestructuralcomponent of beta diversity depended on the weight given to
structural vs compositional informationwhencalculatingdissimi-larity(Figure2andashc)Thelargerthebinsizes(iethesmallerweightgiventospeciesstructuralinformation)thecloserBDCOMPndashSTR val-uesapproachedthevaluesofBDCOMP(Figure2andashc)Ifthebinsizesare big enough theBDCOMPndashSTR value and theBDCOMP value are expected to converge at a certain size of dbh binNeverthelessconsideringthenecessityofcomprehensiveassessmentofbetadi-versityweadvocateforsmallbinsizesastheyprovidemoreinde-pendentstructuralinformationFinallyitisimportanttonotethatthisforestplotincludes47differenttreespecieswhichresultsinastrongrelativeweightofthecompositionalcomponentofBDCOMPndashSTRwhenusingtheCAPframeworkRepeatingourstudyinforestswith lower species richness or in this forest but using a coarsercompositional resolution (eg at the family level)would result inlargerrelativeweightofthestructuralcomponent
42emsp|emspLocal contributions to beta diversity in terms of community composition and structure
EcologicallyLCBDindicesonlyrepresentthedegreeofuniquenessofthesamplingunitsintermsofcommunitycomposition(Legendre
F IGURE 4emspMapsof30-ha(500mtimes600m)plotshowingthelocalcontributionstobetadiversity(LCBD)intermsofcommunitycompositionandstructurefor750quadrats(20mtimes20m)ThesolidcirclesrepresentthevaluesofLCBDiforeachithquadrat(i =[1750])(a)ThemapofLCBDsonlyintermsofspeciescompositionNotethatthesizestructureofindividuals(iedbh)isnotconsideredwhencalculatingtheLCBDCOMPthusthevaluesofLCBDCOMPwerenotaffectedbythesizeofthebinsofthestructuralvariable(b)ndash(e)ThetwoextremecasesoftheLCBDmap(b)and(c)givingthemostweighttothestructuralcomponentandcorrespondinglytheleastweighttothecompositionalcomponent(ie1-cmbinsize)and(d)and(e)givingthemostweighttothecompositionalcomponentandcorrespondinglytheleastweighttothestructuralcomponent(ie15-cmbinsize)(f)and(g)MapsofLCBDsafteraveragingacrossdbhbinsizesSizeofthecirclesisproportionaltotheLCBDivaluesTheblackandgreysolidcirclesrepresentthesiteswithLCBDvalueshigherandlowerthanthemeanrespectively
TABLE 1emspVariationpartitioningresultsforthreetypesofmatricesatdifferentscalesofquadratsThepartitioningisbasedonadjustedR2 statisticsasrecommendedbyPeres-Netoetal(2006)
Quadrat sizes (a) (b) (c) (d) (a + b) (b + c) (a + b + c)
YCOMP
10mtimes10m 00044 00796 01361 07799 00840 02157 02201
20mtimes20m 00028 01783 02862 05327 01811 04645 04673
50mtimes50m 00050 02995 03229 03726 03045 06224 06274
YSTR
10mtimes10m 00123 00131 00296 09450 00254 00427 00550
20mtimes20m 00013 00907 01652 07428 00920 02560 02572
50mtimes50m 00029 02300 02163 05509 02328 04463 04492
YCOMPndashSTR
10mtimes10m 00055 00564 00932 08449 00619 01496 01551
20mtimes20m 00028 01576 02559 05837 01604 04135 04163
50mtimes50m 00013 02543 01948 05496 02556 04492 04504
Fractions(a)ndash(d)(adjustedR2statistics)(a)variationexplainedbytheenvironmentalvariablesaftercontrollingforthespatialstructure(b)variationexplainedbythespatiallystructuredenvironmentalvariables(c)spatiallystructuredvariationexplainedbypurespaceaftercontrollingforenviron-mentalvariation(d)residualvariationEnvironmentalvariablesusedtocomputefraction(a+b)dbMEMeigenfunctionsweretheexplanatoryvaria-blesusedtocomputefraction(b+c)Only5-cm-diameterclasses(iebinsize=5cm)asthestructuralvariablewereusedtocalculatetheYSTR and YCOMPndashSTR
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YAO et Al
amp De Caacuteceres 2013) However natural communities may exhibitsimilarspeciescompositionsbutdifferinotherfeaturessuchasthesizestructureof individuals Inthepresentstudyweassessedthedegreeofuniquenessofthequadratsintermsnotonlyoftheirspe-ciescompositionbutalsooftheirsizestructureandbyusingbothcomponentstogetherThedegreeofuniquenessofquadratsintermsofcommunitycompositionindividuallyhadaveryweakcorrelationwithuniqueness in termsof size structure individually (LCBDCOMP vsLCBDSTRFigure3) indicating that sites that areunique in spe-cies composition are not necessarily unique in size structure andvice versa Additionally we found that the spatial distribution ofsiteswithhighLCBDvaluesisdifferentforthetwocomponentsofacommunitywith siteswithhighstructuraluniquenessoccurringinsmallforestpatches(Figure4)Alltheseresultsreinforcetheideathatconsideringbothspeciescompositionalandsizestructuralcom-ponentsmaybeamorecomprehensivewaytodescribethecommu-nityorganizationHoweverifweacceptthefactthatsitesthatareuniqueintermsofsizestructurearetheresultofgapdynamics(seebelow) the non-zero correlation between LCBDCOMP vs LCBDSTR mayindicatethatforestgapsmaybecolonizedbyspeciesthatmaylaterbesuppressedastheforestgrowssothatrecentforestgapshaveadifferentspeciescompositionthanclosedforeststructures(Comitaetal2009)
43emsp|emspPartitioning the structural and compositional components of beta diversity
About344ofthevariationincommunityassemblagewasdeter-minedbyenvironmentalandspatialvariablesdependingonthescale(quadratsize)andonwhichcomponentsofcommunityassemblage(ie compositional component structural component and takingbothcomponents together)were taken intoaccountThispropor-tion isslightly lowerthanthevaluesfound instudiesbyLegendreetal (2009)andPunchi-Manageetal (2014)Areasonforthisre-sult is thatwe incorporateddifferencesboth insizestructureandspeciescomposition intocommunityassemblagesratherthanonlyusingtheconventionalspeciescompositiondataWhenthespeciescomposition and size structure of the constituent individuals areincorporatedintothecommunityatthesametimemorevariationwilloccurincommunityassemblagesInourstudyhabitat(a+b)ex-plainedmorevariationinthecompositionalcomponent(190)thaninthestructuralcomponent(117)ofthecommunityassemblagesBetadiversitypartitioningindicatedthatthevariationinthestruc-turalcomponentislessdictatedbyenvironmentthanvariationinthecompositional componentWe here hypothesize that canopy gapdynamicswillbethepotentialdriversofstructuralvariationWinterinourstudyareaiscoldandlongwithalongsnowfallperiodThesnowfallperiodlastsforhalfayearandthesnowcoverthicknessinmountainousareasreaches40ndash50cmWehypothesizethatpulsesofmoderate-severity disturbancesmay be caused by snowstormsin our site In the absence of stand-replacing disturbances forestcanopiesareopenedperiodicallybythedeathofsinglebigtreesorsmallgroupsofadulttreescreatingcanopygapsSnowstormsmay
havealteredforeststructurebyselectivelyremovinglargercanopytrees Environmental selection of individuals shapes compositionbydeterminingthefitnessof individualswhereasstructuralvaria-tionmayhavesomerelationshipwithenvironmentalconditions(ielargertreesinsiteswherelargersizesaresupportedforenergyorwateravailability)butingeneralisthereflectionofdifferentstagesaroundgapdynamicsPreviousstudiesareconsistentwithourfind-ingsFraverandWhite(2005)forinstancefoundthattherepeatedmoderate-severity disturbances (iewindstorms) causeddramaticstructural changes they caused no significant change in speciescomposition
Becausetherelativeimportanceofbothnicheandneutralthe-oryinstructuringcommunitiesvarieswithspatialscale(Legendreetal 2009 Punchi-Manage etal 2014) we conducted scale-dependentanalyses InsharpcontrasttothefindingbyLegendreetal(2009)forabroad-leavedforestinChinawefoundthattheproportionofundeterminedvariation incompositionalandstruc-turalcomponentsofcommunityassemblageswasveryhighatfinespatialscales(upto945forthestructuralcomponent780forthecompositionalcomponentand844forbothcomponentsto-gether)butdecreasedsystematicallywith increasingspatial scale(up to a minimum of 373 for compositional component at the50-mscale)TheseresultsareinlinewiththefindingsbyPunchi-Manageetal(2014)inaSriLankandipterocarpforestandbyDeCaacuteceresetal(2012)inacomparisonofseveralforestsOntheonehandthehighproportionofunexplainedvariationmayberelatedtounmeasuredandnotspatially-structuredbiologicalorenviron-mentalvariablesXuetal(2016)showedthatthesoilnutrientsintheupper(0ndash10cmconsideredinourstudy)andlowersoillayers(10ndash20cm)andtheheavymetalelements(CuNiCdAsPbZnMoCrMnandMg)inthesoilshowastrongcorrelationwiththespeciesspatialdistributionsatJiaoheThismaypartlyexplainwhythepureenvironmentalvariable(a)explainedsuchlittlevariationinthecommunityassemblagesAnotherexplanationforthehighpro-portionofunexplainedvariationisthatitmaybeduetostochasticprocesseswhich related to theneutral theoryassuming that thedynamicsofpopulationsareprimarilydrivenbyecologicaldriftanddispersal(Legendreetal2009)Ontheotherhandtheproportionofundeterminedvariationincompositionalandstructuralcompo-nents of community assemblages decreased systematically withincreasingspatialscaleThismayindicatethatcommunityassem-blageishighlystochasticintermsofspeciescompositionandtreesizedistributionatfinescales (ie10-mscale)butthisfinescalestochasticitytendstosmoothoutatthe50-mscalewheremoreconsistent habitat-driven species assemblages emerged Whenvariance partitioning is conducted on the structural componentalonetheunexplained(d)fractionisdominantWhiletheinfluenceofenvironmental factorsonsizestructuremaybe less importantthan for thecompositionalcomponent theeffectof localdistur-bances (eg appearanceof canopygaps resulting frommortalityof largetrees)results inrandomspatialpatternsofquadratswithrather different structure contributing to a large unexplainedfraction
emspensp emsp | emsp267Journal of Vegetation Science
YAO et Al
5emsp |emspCONCLUSIONS
SpeciescompositionandsizestructurearethetwoessentialfeaturesofacommunityOnlyoneofthemindividuallymaybeinsufficienttodescribetheorganizationoftreespeciesassemblagesDefiningandquantifyingbetadiversityusingthespeciescompositionalonemaybesufficienttheninmanyoccasionsNeverthelessspeciescompo-sition is justonedimensionofbiodiversity variation in size struc-tureisalsoimportantIncorporatingstructuraldatainbetadiversityassessmentsallowsecologiststomakeuseofvaluableinformationcollectedduringfieldsurveysIfitisavailablethereisnoreasontoignorethewealthofinformationaboutsizestructurewhencompar-ingspeciesassemblagesOurstudyhighlightstheneedtoincorpo-ratethestructuraldataofacommunityinadditiontocompositionaldatawhenquantifyingandanalyzingbetadiversityFinallyourre-sults suggest thatbothdeterministicandstochasticprocessesarerelevantdeterminantsofcompositionalandstructuralcomponentsof communityassemblages inour temperate forestNeverthelesstheseprocessesarescale-andorresolution-dependent
ACKNOWLEDGEMENTS
WewouldliketothankHeHuaijiangDingShengjianNiRuiqiangandZuoQiangandseveralothersforassistingwiththefielddatacollectionAuthorsaregratefultotheJiaoheManagementBureauof the Forest Experimental Zone for permission to undertake thefieldworkWealsothankthreeanonymousreviewersforprovidingthevaluablecomments
CONFLICTS OF INTEREST
Theauthorsdeclarenocompetingfinancialinterests
DATA ACCESSIBILITY
DataownershipbelongstoBeijingForestryUniversitywhosestaffconductedtheanalysesandwrotethemanuscripthttpwwwbjfueducn
ORCID
Jie Yao httpsorcidorg0000-0002-8606-8158
REFERENCES
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ArsenaultAampBradfieldGE (1995)Structuralndashcompositionalvaria-tioninthreeage-classesoftemperaterainforestsinsoutherncoastalBritishColumbiaCanadian Journal of Botany7354ndash64httpsdoiorg101139b95-007
Borcard D amp Legendre P (1994) Environmental control and spatialstructureinecologicalcommunitiesanexampleusingoribatidmites(Acari Oribatei) Environmental and Ecological Statistics 1 37ndash61httpsdoiorg101007BF00714196
Borcard D Legendre P Avois-Jacquet C amp Tuomisto H (2004)DissectingthespatialstructureofecologicaldataatmultiplescalesEcology851826ndash1832httpsdoiorg10189003-3111
BorcardDLegendrePampDrapeauP(1992)PartiallingoutthespatialcomponentofecologicalvariationEcology731045ndash1055httpsdoiorg1023071940179
Caswell H (1976) Community structure a neutral model anal-ysis Ecological Monographs 46 327ndash354 httpsdoiorg1023071942257
ChaseJM(2010)Stochasticcommunityassemblycauseshigherbiodi-versityinmoreproductiveenvironmentsScience3281388ndash1391httpsdoiorg101126science1187820
ChaveJ(2004)NeutraltheoryandcommunityecologyEcology Letters7241ndash253httpsdoiorg101111j1461-0248200300566x
Chesson P (2000) Mechanisms of maintenance of species diversityAnnual Review of Ecology and Systematics31343ndash366httpsdoiorg101146annurevecolsys311343
ComitaLSUriarteMThompsonJJonckheereICanhamCDampZimmermanJK(2009)Abioticandbioticdriversofseedlingsur-vival inahurricane-impacted tropical forestJournal of Ecology971346ndash1359httpsdoiorg101111j1365-2745200901551x
DeCaacuteceresMFontXampOlivaF(2010)Themanagementofvegeta-tionclassificationswithfuzzyclusteringJournal of Vegetation Science211138ndash1151httpsdoiorg101111j1654-1103201001211x
De Caacuteceres M Legendre P amp He F (2013) Dissimilarity mea-surements and the size structure of ecological communitiesMethods in Ecology and Evolution 4 1167ndash1177 httpsdoiorg1011112041-210X12116
De Caacuteceres M Legendre P Valencia R Cao M Chang L-W Chuyong G hellip He F (2012) The variation of tree betadiversity across a global network of forest plots Global Ecology and Biogeography 21 1191ndash1202 httpsdoiorg101111j1466-8238201200770x
DraySBaumanDBlanchetGBorcardDClappeSGuenardGhellipWagnerHH(2018)adespatial Multivariate multiscale spatial analy-sis R package version 03-2RetrievedfromhttpsCRANR-projectorgpackage=adespatial
Dumbrell A J NelsonM Helgason T Dytham C amp Fitter A H(2010)Relativerolesofnicheandneutralprocesses instructuringa soil microbial community ISME Journal 4 337ndash345 httpsdoiorg101038ismej2009122
FaithDAustinMBelbinLampMargulesC (1985)Numericalclas-sification of profile attributes in environmental studies Journal of Environmental Management2073ndash85
Fang J Shen Z Tang ZWang XWang Z Feng J hellip Zheng C(2012) Forest community survey and the structural character-istics of forests in China Ecography 35 1059ndash1071 httpsdoiorg101111j1600-0587201300161x
FraverSampWhiteAS(2005)Disturbancedynamicsofold-growthPicea rubens forests of northern Maine Journal of Vegetation Science 16 597ndash610 httpsdoiorg101111j1654-11032005tb02401x
Gower J C (1966) Some distance properties of latent root and vec-tormethodsusedinmultivariateanalysisBiometrika53325ndash338httpsdoiorg101093biomet533-4325
Harms K E Condit R Hubbell S P amp Foster R B (2001)Habitat associations of trees and shrubs in a 50-ha neotrop-ical forest plot Journal of Ecology 89 947ndash959 httpsdoiorg101111j1365-2745200100615x
HilleRisLambers J Adler P B Harpole W S Levine J M ampMayfield M M (2012) Rethinking community assembly
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through the lens of coexistence theory Annual Review of Ecology Evolution and Systematics 43 227ndash249 httpsdoiorg101146annurev-ecolsys-110411-160411
HubbellSP(Ed)(2001)The unified theory of biodiversity and biogeogra-phyPrincetonNJPrincetonUniversityPress
Hubbell S P (2006) Neutral theory and the evolution of eco-logical equivalence Ecology 87 1387ndash1398 httpsdoiorg1018900012-9658(2006)87[1387NTATEO]20CO2
HussonFJosseJLeSampMazetJ(2015)FactoMineR Multivariate exploratory data analysis and data mining Version 1314 RetrievedfromhttpsCRANR-projectorgpackage=FactoMineR
Hutchinson G E (1961) The paradox of the plankton American Naturalist95137ndash145httpsdoiorg101086282171
KeddyPA(1992)Assemblyandresponserulestwogoalsforpredic-tive community ecology Journal of Vegetation Science3 157ndash164httpsdoiorg1023073235676
KoleffPGastonKJampLennonJJ(2003)MeasuringbetadiversityforpresencendashabsencedataJournal of Animal Ecology72367ndash382httpsdoiorg101046j1365-2656200300710x
KraftN JBComita L SChase JM SandersN J SwensonNGCrist TOhellipMyers JA (2011)Disentangling thedriversofβdiversityalong latitudinalandelevationalgradientsScience3331755ndash1758httpsdoiorg101126science1208584
LaliberteacuteEPaquetteALegendrePampBouchardA(2009)Assessingthescale-specificimportanceofnichesandotherspatialprocessesonbetadiversityacasestudyfromatemperateforestOecologia159377ndash388httpsdoiorg101007s00442-008-1214-8
Legendre P amp Anderson M J (1999) Distance-based redundancyanalysis testing multispecies responses in multifactorial ecolog-ical experiments Ecological Monographs 69 1ndash24 httpsdoiorg1018900012-9615(1999)069[0001DBRATM]20CO2
Legendre P Borcard D amp Peres-Neto P R (2005) Analyzing betadiversity partitioning the spatial variation of community com-position data Ecological Monographs 75 435ndash450 httpsdoiorg10189005-0549
LegendrePampDeCaacuteceresM(2013)BetadiversityasthevarianceofcommunitydatadissimilaritycoefficientsandpartitioningEcology Letters16951ndash963httpsdoiorg101111ele12141
LegendrePampLegendreL (2012)Numerical ecology Vol 24 (3rded)AmsterdamTheNetherlandsElsevierScienceBV
LegendrePMiXRenHMaKYuMSun I-FampHeF (2009)Partitioning beta diversity in a subtropical broad-leaved forest ofChina Ecology90663ndash674httpsdoiorg10189007-18801
MayfieldMMampLevineJM(2010)Opposingeffectsofcompetitiveex-clusiononthephylogeneticstructureofcommunitiesEcology Letters131085ndash1093httpsdoiorg101111j1461-0248201001509x
MyersJAChaseJMJimeacutenezIJoslashrgensenPMAraujo-MurakamiAPaniagua-ZambranaNampSeidelR(2013)Beta-diversityintem-perateandtropicalforestsreflectsdissimilarmechanismsofcommu-nityassemblyEcology Letters16151ndash157httpsdoiorg101111ele12021
OksanenJBlanchetFGFriendlyMKindtRLegendrePMcGlinnDhellipWagnerH(2018)vegan Community ecology package Version 25-2Retrievedfromhttpscranr-projectorgpackage=vegan
Paradis EClaude JampStrimmerK (2004)APEAnalysesof phylo-genetics and evolution inR languageBioinformatics20 289ndash290httpsdoiorg101093bioinformaticsbtg412
PeetRK (1992)Community structureand function InDCGlenn-LewinRKPeetampTTVeblen(Eds)Plant succession theory and prediction(pp103ndash140)NewYorkNYChapmanampHall
Peres-NetoPRLegendrePDraySampBorcardD(2006)Variationpartitioningofspeciesdatamatricesestimationandcomparisonof
fractionsEcology872614ndash2625httpsdoiorg1018900012-9658(2006)87[2614VPOSDM]20CO2
Punchi-Manage R Wiegand T Wiegand K Getzin S SavitriGunatillekeCV ampNimalGunatilleke IAUN(2014)EffectofspatialprocessesandtopographyonstructuringspeciesassemblagesinaSriLankandipterocarpforestEcology95376ndash386httpsdoiorg10189012-21021
RCoreTeam (2017)R A language and environment for statistical com-puting Vienna Austria R Foundation for Statistical ComputingRetrievedfromhttpswwwR-projectorg
Ricklefs R E (1990) Seabird life histories and the marine environ-mentsomespeculationsColonial Waterbirds13(1)1ndash6httpsdoiorg1023071521414
SchwinningSampWeinerJ(1998)MechanismsdeterminingthedegreeofsizeasymmetryincompetitionamongplantsOecologia113447ndash455httpsdoiorg101007s004420050397
SoilScienceSocietyofChina(Ed)(1999)Soil agricultural chemical analy-sis procedureBeijingChinaChineseAgriculturalSciencePress
van der Plas F Janzen T Ordonez A FokkemaW Reinders JEtienneRSampOlffH(2015)Anewmodelingapproachestimatesthe relative importance of different community assembly pro-cesses Ecology961502ndash1515httpsdoiorg10189014-04541
VellendM(Ed)(2017)The theory of ecological communitiesPrincetonNJPrincetonUniversityPresshttpsdoiorg1015159781400883790
Weiner J (1990) Asymmetric competition in plant popula-tions Trends in Ecology and Evolution 5 360ndash364 httpsdoiorg1010160169-5347(90)90095-U
WhittakerRH (1960)VegetationoftheSiskiyoumountainsOregonand California Ecological Monographs 30 279ndash338 httpsdoiorg1023071943563
WhittakerRH(1972)EvolutionandmeasurementofspeciesdiversityTaxon21213ndash251httpsdoiorg1023071218190
XuWHaoMWangJZhangCZhaoXampvonGadowK(2016)Soilelementsinfluencingcommunitystructureinanold-growthfor-est innortheasternChinaForests7159httpsdoiorg103390f7080159
YamakuraTKanzakiMItohAOhkuboTOginoKChaiEOKhellipAshtonPS(1995)Topographyofalarge-scaleresearchplotes-tablishedwithinatropicalrainforestatLambirSarawakTropics541ndash56httpsdoiorg103759tropics541
YanYZhangCWangYZhaoXampvonGadowK(2015)Driversofseedlingsurvivalinatemperateforestandtheirrelativeimportanceat threestagesofsuccessionEcology and Evolution54287ndash4299httpsdoiorg101002ece31688
YaoJZhangXZhangCZhaoXampvonGadowK(2016)EffectsofdensitydependenceinatemperateforestinnortheasternChinaScientific Reports632844httpsdoiorg101038srep32844
ZhangCZhaoXampvonGadowK(2014)Analyzingselectiveharvestevents inthree largeforestobservationalstudies inNorthEasternChina Forest Ecology and Management 316 100ndash109 httpsdoiorg101016jforeco201307018
ZhangCZhaoYZhaoXampvonGadowK (2012)Species-habitatassociations inanorthern temperate forest inChinaSilva Fennica46501ndash519
How to cite this articleYaoJZhangCDeCaacuteceresMLegendrePZhaoXVariationincompositionalandstructuralcomponentsofcommunityassemblageanditsdeterminantsJ Veg Sci 201930257ndash268 httpsdoiorg101111jvs12708
258emsp |emsp emspenspJournal of Vegetation Science
YAO et Al
1emsp |emspINTRODUCTION
Understandingthemechanismsthatdeterminethespatialdistri-butionofspeciesandspeciesdiversityisacentralthemeinecol-ogy (Chave 2004 Chesson 2000 Hutchinson 1961 Ricklefs1990 Vellend 2017) Deterministic niche-based and stochasticneutral processes have beenwidely discussed as potential driv-ers of community assembly (Chesson 2000 HilleRisLambersAdler Harpole Levine ampMayfield 2012Hubbell 2001 2006MayfieldampLevine2010)butthefactorsunderlyingtherelativecontributionof the twoprocessesarestillunresolved (Legendreetal2009Punchi-Manageetal2014vanderPlasetal2015)Niche and neutral theories emphasize different mechanisms assources of species diversity Niche theory predicts that deter-ministicprocessessuchashabitatfilteringandcompetitionshapespeciesassemblagesNeutraltheoryincontrastassumesthatallspecies are essentially functionally equivalent (HilleRisLambersetal 2012Hubbell 20012006Keddy1992) andemphasizesthe importance of stochastic processes in community assemblysuchasrandombirthdeathdispersaleventsspeciationandsto-chasticextinction(Caswell1976Hubbell2001)Itisnowgener-allyacceptedthatboththedeterministicandstochasticprocessesarepotentiallyimportantdeterminantsofthespatialdistributionobserved in community assemblagesAt present however theirrelative importance in shapingdifferent componentsof commu-nityorganization(iethestructuralcompositionalorbothcom-ponentstogether)isnotclear(DeCaacuteceresetal2012Legendreetal2009Punchi-Manageetal2014)Inthepresentstudywedefinedtheldquocompositionalrdquotermasthespeciescompositiondata(egspeciesabundancevalues)Weconstrainedthedefinitionofldquostructuralrdquotorefertothediameteratbreastheightoftheindivid-ualtreesmakingupthecommunity
Thevariationinspeciescompositionobservedamongasetofsamplingunitswithinaregionisoftendescribedasbetadiversity(Whittaker19601972)Theinterestofcommunityecologistsforbetadiversitystemsnotonlyfromthefactthatitlinkslocal(iealphadiversity) and regionaldiversity (ie gammadiversity) (DeCaacuteceresetal2012)butalsobecauseitcanprovidefundamentalinsights into theprocesses thatdetermine the spatialpatternofspecies assemblages (Anderson etal 2011 Chase 2010 Kraftetal 2011 Legendre amp De Caacuteceres 2013Myers etal 2013)Beta diversity can bemeasured inmany different ways (KoleffGastonampLennon2003LegendreBorcardampPeres-Neto2005Legendre amp Legendre 2012 Legendre etal 2009) Beta diver-sityestimatesaremostoftenbasedonspeciescompositionaldata(egspeciesabundancevaluesorspecies incidence)whichtakethe formof a site-by-species datamatrixwith sites in rows andspecies abundances in columns Although species compositiondataarefundamentallyimportanttheyalonemaybeinsufficientfor describing community organization and may neglect othervaluable information to study community assembly processessuchasthestructuralcomponent(egthesizestructureofcon-stituentindividuals)ofacommunity(DeCaacuteceresLegendreampHe
2013FaithAustinBelbinampMargules1985Fangetal2012)The phenomenon of competition asymmetry emphasizes thatlarge individuals usually compete disproportionately with theirsmaller-sized neighbors (Weiner 1990) Big trees control moreabove- and below-ground resources (eg light and mineral nu-trients)thansmalltrees(SchwinningampWeiner1998)ThereforelargerindividualstendtohavegreaterimpactonthefunctionanddynamicsofforestecosystemsthansmallonesMoreovernaturalmulti-species communities may exhibit similar compositions butdifferinotherfeaturessuchasthesizestructureoftheirindividu-als(DeCaacuteceresetal2013)Thedistributionofindividualsizesisalsoan importantcomponenttorepresentandunderstandcom-munity assembly therefore using species abundances only (iethe compositional component) to describe forest beta diversitymay be an oversimplification of the spatial variation of commu-nities In order to get comprehensive insight into the processesthat determine the spatial pattern of species assemblages it isnecessarytoensurefirstthatwehavetheabilitytodescribebetadiversity inacomprehensivewayWhetherornotthestructuralcomponent shouldor couldbeconsideredaltogetherwithotherbeta diversity components has never been investigated and re-mainstobeexplored
In thisstudywegeneralizedtheconventionalapproachto thestudy of beta diversity by considering structural data in additiontocompositionaldataWefirstmeasurethespatialvariationofas-semblagesonthebasisofspeciescompositionandsizestructureofconstituentsWethenusetheenvironmentalandspatialvariablesas explanatory factors to partition the variation in compositionalandstructuralcomponentsofcommunityassemblageWespecifi-callyaddressthefollowingquestions(a)Canwetakeboththespe-ciescompositionalandsizestructuralcomponentsofacommunityintoaccountwhendescribingbetadiversity Isthereacorrelationbetween thesebetadiversity components (b)How is the assess-mentofthesebetadiversitycomponentsaffectedbythesizeofthesampling units (c)When considering both the compositional andstructural components together towhatextentarebetadiversityassessmentsaffectedbytherelativeimportanceaccordedtostruc-tural vs compositional differences (d)What is the relative contri-bution of the environmental and spatial variables to communityassemblyintermsofspeciescompositionsizestructureorconsid-eringbothcomponents
2emsp |emspMATERIAL AND METHODS
21emsp|emspStudy sites and data collection
Ourstudywascarriedout inatemperatemixedbroadleafndashconiferforestinJiaoheJilinProvincenortheasternChinaTheaveragehot-testmonthlytemperatureis217degCinJulyandthecoldestmonthisJanuarywithanaveragedaytemperatureof -186degCTheaverageannualprecipitationis6959mm(ZhangZhaoampGadow2014)Thesoilisabrownforestsoilwitharootabledepthrangingbetween20and100cm (ZhangZhaoZhaoampGadow2012)This studyuses
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YAO et Al
datafroma30-ha(500mtimes600m)forestdynamicplot(43deg57928primendash43deg58214primeN127deg45287primendash127deg45790primeE)establishedinthesum-merof2010Theplot issituated inaprotectedold-growthforestina latestageof successionwith littlehumandisturbancedue toits remoteness fromresidential areas (YaoZhangZhangZhaoampGadow2016)
Allindividualswithadiameteratbreastheight(dbh)of1cmormoreintheplotwereidentifiedmeasuredandspatiallymappedin2010Atotalof49684individualtreesbelongingto20familiesand47speciesintheplotwereusedinthepresentstudyTheplotwasdividedinto120(50mtimes50m)750(20mtimes20m)and3000(10mtimes10m)subplotshereaftercalledquadratsTopographicandsoilvari-ableswerealsoavailable foreachquadratFour topographicvari-ables(altitudequadratconvexityslopeandaspect)werecalculatedforeachquadratfollowingtherecommendationofHarmsConditHubbellandFoster(2001)andYamakuraetal(1995)Eightsoilen-vironmentalandnutrientvariablesweremeasuredpHtheamountof organic matter and the total amounts as well as the availablenutrients of nitrogen (N) phosphorus (P) and potassium (K) (ggYanZhangWangZhaoampGadow2015)All laboratoryanalyseswereconductedfollowingtheproceduresrecommendedbytheSoilScienceSocietyofChina(1999)
22emsp|emspStatistical analyses
221emsp|emspCumulative abundance profiles
Theconceptofcumulativeabundanceprofile (CAP)developedbyDeCaacuteceresetal(2013)isdefinedasafunctionthattakestheval-uesofastructuralvariable (egheightdbhetc)as inputandre-turnsthecumulativeabundanceofindividualswhosevaluesofthestructuralvariableareequal toor largerthanthe inputvalueTheCAP framework generalizes traditional species abundance valuesand allows researchers to describe the structural component of acommunityInthepresentstudythestructuralvariablewasdiam-eteratbreastheight(dbh)AccordingtothischoicethevalueofCAPforagivendbhvalueisthecumulativeabundanceoftreeindividualsasbigasorbiggerthantheinputvalueFunctionCAPinfactreplacestheabundancevalueofadbhclassbythesumofabundancesinthisandlargerdbhclasses
222emsp|emspCommunity tables
Following theconventionalmethods speciescomposition tables(ie quadrats in rows species in column and the table contain-ing individual counts)wereassembled in this studywecall thistablethetraditional species composition matrix(YCOMP)InordertogeneralizeatraditionalspeciesabundancevalueanddescribethesizestructurecomponentofthecommunitytheCAPsconsider-ingspeciesidentitywerecalculatedtoobtainthespecies composi-tion combined with structural data matrix(YCOMPndashSTR)TheYCOMPndashSTR isamatrixwithasmanyrowsasplotrecordsandwherecolumnsareorganized inblocksandthereareasmanyblocksasspecies
andeachblockhasasmanycolumnsassizeclassesDisregardingspeciesidentityofthedifferentindividualsCAPswerealsocalcu-latedtoobtainthecommunity structural matrix (YSTR)TheYSTR is amatrixwithasmanyrowsasplotrecordsandasmanycolumnsas size classes
FunctionsldquostratifyvegdatardquoandldquoCAPrdquointhevegclustRpack-age(DeCaacuteceresFontampOliva2010)availableonCRAN(httpsCRANR-projectorgpackage=vegclust) were applied to calculatetheCAPsFunctionsldquostratifyvegdatardquoandldquoCAPrdquorequirediscretiz-ingthestructuralvariableandthenumberofsizebinsaffectstheimportanceaccordedtostructuraldifferencesThustherearede-cisions tobemadewhencreatingYSTR and YCOMPndashSTR particularlyhowwedefine thebinsof thestructuralvariables (egdbhbins)Inthisstudywetestedfrom1-cmbinsizeto15-cmbinsizetodis-cretizedbhintoclassesThat is1cmbinsleadtodbhclasses1ndash22ndash33ndash4andsoonwhereas5cmbinsleadtodbhclasses1ndash56ndash1010ndash15andsoonThesmallerthesizeofdbhbinthemorecolumnswillbeproducedineachblockinthetableYCOMPndashSTRindicatingthatmoreweightisaccordedtodifferencesinstructureandviceversaIfthebinsizewasbigenoughsothatthenumberofcolumnsineachblock in the tableYCOMPndashSTRwasonewewouldhave thatYCOMPndashSTR=YCOMPGenerallythelargerthesizeofdbhbinsthemoresimi-lar will YCOMP and YCOMPndashSTR be
223emsp|emspPairwise dissimilarity in terms of community composition and structure
Wecalculateddissimilaritymatrices between all pairs of quadratsusingthepercentagedifferenceindex(akaBrayndashCurtisdissimilar-ity)oncommunitymatricesYCOMPYSTRandYCOMPndashSTRtoobtainthe compositional dissimilarity matrix (DCOMP) the structural dissimilar-ity matrix (DSTR)andthe compositionalndashstructural dissimilarity matrix (DCOMPndashSTR) respectively In order to explore the pairwise covari-ation between the three kinds of dissimilarity assessments (ieDCOMP vs DSTRDCOMP vs DCOMPndashSTRandDSTR vs DCOMPndashSTR)wefirstcomputed principal coordinates of each dissimilarity matrix usingprincipalcoordinatesanalysis (PCoA) thencomparedtheresultingmatricesofprincipalcoordinateskeepingallaxesusingtheRVco-efficientWeexpectedthatDCOMPndashSTRwouldbecorrelatedtobothDCOMP and DSTRbutthestrengthofthecorrelationdoesdependonthechosensizeofdiameterbins(ieontheweightgiventostruc-turalvscompositionalinformation)
Function ldquovegdistrdquo with the dissimilarity index ldquobrayrdquo in theveganRpackage(Oksanenetal2018)wasusedtocalculatethedissimilarity matrices D Function ldquopcoardquo in the ape R package(ParadisClaudeampStrimmer2004)wasusedtocomputeprincipalcoordinates of eachdissimilaritymatrixD Thedissimilarities inD matricesweresquare-rootedbeforePCoAinordertomakethema-tricesEuclideanandpreventthegenerationofnegativeeigenvaluesandcomplexPCoAaxes (DeCaacuteceresetal2013)Function ldquocoef-fRVrdquo in the FactoMineR R package (Husson Josse LeampMazet2015)wasusedtocalculatetheRVcoefficientsbetweenthematri-cesofprincipalcoordinates
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224emsp|emspBeta diversity components (BDCOMP BDSTR and BDCOMPndashSTR)
Conventionallybetadiversity (abbreviatedBD) is assessed fromasite-by-speciesdatamatrixotherbasiccharacteristics(egsizeofindividuals)ofthecommunityareignoredInordertogeneral-izetheconceptoftraditionalbetadiversitytoCAPdataweap-pliedtheindexproposedbyLegendreetal (2005)andLegendreandDeCaacuteceres(2013)tocomputebetadiversityasthevarianceofthecommunitydataLegendreandDeCaacuteceres(2013)showedhow to compute the total variance of the community composi-tion datamatrix from a dissimilaritymatrixD The total sum ofsquaresSS(Y)canbeobtainedfromadissimilaritymatrixDusingEquation1(LegendreampDeCaacuteceres2013LegendreampLegendre2012) Dividing SS(Y) by (n - 1) produces the classical unbiasedestimateofthetotalvarianceofYcomputedfromauser-selectedEuclidean dissimilarity matrixD (ie Equation 2)We used thatapproach to calculate the traditional compositional beta diversity (BDCOMP) the structural beta diversity (BDSTR) and the composi-tionalndashstructural beta diversity(BDCOMPndashSTR)respectivelyusingthefollowingequations
D =(Dhi)isanntimesnsymmetricdissimilaritymatrix(eitherDCOMP
DSTRorDCOMPndashSTR) i and h representthesamplingunitsn is thenumberofthesamplingunits If thecalculationsstartwithaper-centagedifferenceDmatrixwhichisnon-Euclideanonecomputesthesquare-rootsoftheDvaluesintheDmatrixtomakeitEuclideanbeforeusingthetransformedDvaluesinEquations1and2
225emsp|emspLocal contributions to beta diversity in terms of community composition and structure
Legendre andDe Caacuteceres (2013) suggested that total beta diver-sity can be partitioned into Local Contributions toBetaDiversity(LCBDwhicharecomparative indicatorsoftheecologicalunique-nessofthesites)TheLocalContributionstoBetaDiversity(LCBDi)represent the relative contributionsof the samplingunit i to betadiversityLCBDi indicateshowexceptional thecompositionofsitei iswhencomparedtothecentroidofallpointswhichwouldrep-resent a theoretical site with the average species composition ofall the sampling units In the present study the LCBD representsthe degree of uniqueness of each sampling unit in terms of com-position andor structure of community assemblages LCBDi indi-cescanbecalculatedfromthedissimilaritymatricesD(LegendreampDeCaacuteceres2013)OnefirsttransformsthedistancematrixDintomatrixA =(ahi)=(ndash05D2
hi) then centers thematrix as proposedbyGower(1966)
where Iisanidentitymatrixofsizen1isavectorofones(oflengthn)and1primeisitstranspose(LegendreampLegendre2012)HereeachdiagonalelementofmatrixGistheSSivalues(iethesquareddis-tancetothecentroidoftheithsamplingunit)Hencethevectoroflocalcontributionsofthesitestobetadiversity(LCBDi)is
The LCBD indices are scaled to sum to 1 We used functionldquoLCBDcomprdquointheadespatialRpackage(Drayetal2018)avail-ableonCRAN(httpsCRANR-projectorgpackage=adespatial)tocalculatetheLCBDindices
Wecheckedwhetherthere isacorrelationbetweentheLCBDcoefficientscalculatedfromspeciescompositionsizestructureorusingthetwocomponentstogetherHencewecalculatedSpearmanrank correlations pairwise between the three typesof LCBDvec-tors (ieLCBDCOMPvsLCBDSTRLCBDCOMPvsLCBDCOMPndashSTRandLCBDSTRvsLCBDCOMPndashSTR)SincetheLCBDindicesindicatethede-greeofuniquenessof thesamplingunits in termsof their speciescompositionandorsizestructureweplottedtheLCBDvaluesonmapsof the30-haplotLargeLCBDvalues indicate thesites thathaveuniquespeciesassemblagesandsmallLCBDvaluesindicatethesites thathaveassemblagesthatareverysimilar to those inothersites Againwe expected LCBDCOMPndashSTR to be correlated to bothLCBDCOMP and LCBDSTR butwith the strength of the correlationdependingontheweightgiventostructuralvscompositionalinfor-mationWethusshowedthetwoextremecasesoftheLCBDmapaccordinga largestweighttothestructuralcomponentandcorre-spondinglythesmallestrelativeweighttothecompositionalcompo-nent(ie1-cmbinsize)andgivingthelargestrelativeweighttothecompositionalcomponent(ie15-cmbinsize)
226emsp|emspSets of explanatory variables environmental and spatial variables
Following Legendre etal (2009)we used altitude convexity andslope to construct third-degreepolynomial functions (ie yieldingninevariables)Themonomialswithexponentsallowthemodelingof nonlinear relationships between the topographic variables andthe response variablesWe calculated the aspect of a quadrat astheaverageangleofthefourtriangularplanesthatdeviatefromthenorthdirectionWe thusused the sin (aspect) and cos (aspect) inorder to include it in a linear regressionmodelWe thereforeob-tained11expandedtopographicvariablesWethencombinedthese11 expanded topographic variables with the eight soil variables(described insection21Studysitesanddatacollection) toobtainthe environmental variables data table (ie 19 variables) for eachquadratWe computed eigenfunctions of distance-basedMoranrsquoseigenvector maps (dbMEM also called Principal Coordinates ofNeighbour Matrices PCNM Borcard Legendre Avois-Jacquet amp
(1)SS(Y) =1
n
nminus1sum
h=1
nsum
i=h+1
D2hi
(2)BD = SS(Y)∕(nminus1)
(3)G =
(
Iminus11
n
)
A
(
Iminus11
n
)
(4)(LCBDi) = (SSi)∕SS(Y) = diag(G)∕SS(Y)
emspensp emsp | emsp261Journal of Vegetation Science
YAO et Al
Tuomisto2004LegendreampLegendre2012Legendreetal2009)acrossthe3000(10mtimes10m)750(20mtimes20m)and120(50mtimes50m)quadratsThedbMEMeigenfunctionswithpositiveeigenval-uesonlywereusedasspatialvariablesWeappliedforwardmodelselection(withpermutationtestsatthe5significanceleveloftheincrease in R2 ateachstep) toextract thesignificantenvironmentvariablesandeigenfunctionsofdbMEMusingthefunctionldquoforwardselrdquointhepackageadespatial(Drayetal2018)
227emsp|emspVariation partitioning of DCOMP DSTR and DCOMPndashSTR
Tocompare the influenceofniche-basedandspatialprocessesoncommunityassembly representedbycommunitycompositionsizestructure or the two components together distance-based re-dundancyanalysis (dbRDALegendreampAnderson1999Legendreamp Legendre 2012)was used to partition the variation of each ofthree community matrices (Borcard Legendre amp Drapeau 1992Legendre etal 2009 Peres-Neto Legendre Dray amp Borcard2006) Specificallyweused the two setsof explanatoryvariables(after forwardmodelselection) topartitionvariation in theprinci-palcoordinatetablesextractedfromDCOMPDSTRDCOMPndashSTRsepa-rately into fractions explained by the four different components(a)purehabitat (b)spatiallystructuredhabitat (c)purespaceand(d)undetermined (BorcardampLegendre1994Borcardetal1992DeCaacuteceresetal 2012Legendreetal 2009Myersetal 2013Punchi-Manage etal 2014) We hypothesized that the niche
processesareresponsiblefortheproportionofvariationexplainedbythepurehabitatandthespatially-structuredhabitatcomponents(a+b)(LaliberteacutePaquetteLegendreampBouchard2009Legendreetal2009)Whilewehypothesizedthattheproportionofvariationexplainedbythepurespatialcomponent(c)isrelatedtoindepend-ent biological processes (eg dispersal limitation competition fa-cilitationhistoricaleventsandJanzenndashConnelleffects)(LegendreampLegendre2012Legendreetal2009Punchi-Manageetal2014)Theundeterminedproportionofvariation(d)mayberelatedtosto-chastic processes or undefined non-spatially-structured biologicalor environmental variables (Dumbrell Nelson Helgason DythamampFitter2010)Thatallowedustoassesstherelativecontributionsoftheenvironmentalandspatialvariablestocommunityassemblyin termsof composition structureor taking the twocomponentstogetherAllanalyseswereperformedusingR(RCoreTeam2017)
3emsp |emspRESULTS
31emsp|emspPairwise dissimilarity in terms of community composition and structure
Wefound thatdissimilaritymatricescomputed fromspeciescom-position(DCOMP)sizestructure(DSTR)andconsideringbothcompo-nentstogether(DCOMPndashSTR)werecorrelatedHoweverthestrengthof the correlationdependedon the sizeofbinsused todiscretizethestructuralvariableandonthesizeof thequadrats (Figure1andashc) Overall the correlation between DCOMP vs DCOMPndashSTR was
F IGURE 1emspThecorrelationsbetweenthepairwisedissimilarityintermsofspeciescomposition(DCOMP)sizestructure(DSTR)andbothcomponentstogether(DCOMPndashSTR)ThecorrelationsofDCOMP vs DSTRDCOMP vs DCOMPndashSTRand DSTR vs DCOMPndashSTRvarywithdbhbinsatthescaleof(a)10mtimes10m(b)20mtimes20mand(c)50mtimes50mIngraphs(a)(b)and(c)thehorizontalreddottedlineshorizontalbluelong-dashlinesandhorizontalgreensolidlinesrepresentthemeanvaluesofRVcoefficientsof1ndash15cmdbhbinsofDCOMP vs DSTRDCOMP vs DCOMPndashSTRandDSTR vs DCOMPndashSTRrespectively(d)BoxplotsforRVcoefficientsofthethreepairwisedissimilaritycomparisons(aggregatedoverall1ndash15cmdbhbinsizes)foreachofthethreequadratsizes[Colourfigurecanbeviewedatwileyonlinelibrarycom]
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YAO et Al
substantially stronger than that ofDCOMP vs DSTR andofDSTR vs DCOMPndashSTR
The correlation ofDCOMP vs DCOMPndashSTR increasedwith the in-crease of bin size Correspondingly the correlations of DSTR vs DCOMPndashSTR showed the opposite trend (Figure1andashc) As to the ef-fectofthesizeofthesamplingunitsthestrengthofcorrelationsin-creasedwiththequadratsize(Figure1d)exceptforthecorrelationbetweenDCOMP and DCOMPndashSTRwhichexhibitsnosignificantdiffer-encebetweenthe10mtimes10mand20mtimes20mquadrats(p = 023Figure1d)
32emsp|emspThe three components of beta diversity (BD) BDCOMP BDSTR and BDCOMPndashSTR
Thebetadiversity(BD)valueswerecloselyrelatedtowhetherthespecies composition size structure or both components togetherhad been taken into account Among these three components ofbetadiversityBDCOMPndashSTRwasgreatestcloselyfollowedbyBDCOMPandthesmallestwasBDSTR(Figure2)Sincethesizestructureofin-dividualswasnot consideredwhen calculatingBDCOMP this indexwasnotaffectedbythesizeofdbhbins(Figure2andashc)ThevaluesofBDCOMPndashSTRandBDSTRhoweverdecreasedslightlywithanincreaseofbinsizeWhenincreasingdbhbinsizethevaluesofBDCOMPndashSTR graduallyapproachedthevaluesofBDCOMP (Figure2andashc)BDalso
varied as a function of quadrat size (Figure2) values of BDCOMPBDSTRandBDCOMPndashSTR(afteraveragingacrossbinsizes)systemati-callydecreasedwithincreasingquadratsize(Figure2d)
33emsp|emspLocal contributions to beta diversity in terms of community composition and structure
LocalContributionstoBetaDiversitycalculatedusingspeciescom-positionsizestructureorbothcomponentswerecorrelatedAgainthe strengthof correlationsdependedon the sizeofdbhbins andon the size of quadrats (Figure3andashc) In the case of LCBDCOMP vs LCBDCOMPndashSTR the strength of the correlation increased with anincreaseofbinsizeCorrespondinglythecorrelationofLCBDSTR vs LCBDCOMPndashSTRshowedtheoppositetrend(Figure3andashc)Thecorrela-tionsofLCBDCOMPvsLCBDSTRandLCBDSTRvsLCBDCOMPndashSTR were significantly different for differentquadrat sizesA striking findingwasthatthestrengthofcorrelationswasweakeratthescaleof20mtimes20m than that at the scalesof10mtimes10mor50mtimes50m(Figure3d)HowevercorrelationsbetweenLCBDCOMPvsLCBDCOMPndashSTRwerenotsubstantiallyaffectedbythesizeofquadrats(Figure3d)
TheLCBDivaluesindicatetheithquadratsthatcontributemoreorlessthanthemeantobetadiversity(inotherwordstheithquad-ratswithhighorlowuniquenessofspeciesassemblages)TheresultsindicatedthatthesiteswithhighLCBDvalues(contributemorethan
F IGURE 2emspTheBetaDiversity(BD)intermsofspeciescomposition(BDCOMP)sizestructure(BDSTR)andbothcomponentstogether(BDCOMPndashSTR)ThevaluesofBDCOMPndashSTRandBDSTRvarywiththesizeofbinsofthestructuralvariable(dbhbinsizes=1ndash15cm)atthescaleof(a)10mtimes10m(b)20mtimes20mand(c)50mtimes50mThesizestructureofindividuals(iethedbh)isnotconsideredwhencalculatingtheBDCOMPthusthevaluesofBDCOMPwerenotaffectedbythebinsizeIngraphs(a)(b)and(c)thehorizontalbluelong-dashlinesandhorizontalgreensolidlinesrepresentthemeanvaluesofBDCOMPndashSTRandBDSTRacross1ndash15cmbinsizesrespectively(d)ValuesofBDCOMPBDSTRandBDCOMPndashSTR(afteraveragingacrossdbhbinsizes)varywiththesamplingunitsizes[Colourfigurecanbeviewedatwileyonlinelibrarycom]
emspensp emsp | emsp263Journal of Vegetation Science
YAO et Al
themeantobetadiversity)arevariedamongthreecomponentsofacommunity (Figure4)Specifically342(456)290(387)and331 (441)outof750quadratscontributedmorethanthemeanto beta diversity in term of species composition (ie LCBDCOMPFigure4a)sizestructure(ieLCBDSTRFigure4g)andbothcompo-nentstogether(ieLCBDCOMPndashSTRFigure4f)respectively
34emsp|emspVariation partitioning of matrices DCOMP DSTR and DCOMPndashSTR
Theexplanatorypoweroftheenvironmentalvariablesandthespa-tialvariablesvariedforthethreetypesofmatricesandwithquadratsizes (Table 1) The variation explained by the environmental vari-ables(a+b)andbythespatialvariables(b+c)increasedsystemati-callywith increasingscale (Table1)Averagingacrossquadratsizeshabitatandspacejointlyexplained438254and341ofthevariation in compositional component structural component andthe two components together of community assemblage respec-tivelyHoweverthecontributionofthepurehabitatcomponent (a)was negligible The combination of environmental and spatial vari-ablesexplained the lowestproportionofvariation in the structuralcomponentaloneandexplainedthehighestproportionofvariationinthecompositionalcomponentalone(Table1)Boththeenvironmen-talvariables(a+b)andthepurespatialvariables(c)explainedmore
variationinthecompositionalcomponentthanthatinthestructuralcomponentsofcommunityassemblageAdditionallyourfindingsin-dicatethattheunexplained(d)fractionsdominatedthevariancepar-titioningcomputedforthestructuralcomponentYstralone(Table1)
4emsp |emspDISCUSSION
Forest ecosystems can be characterized and evaluated in terms ofboththeirstructureandcomposition(Peet1992)Inpreviousstud-ies the compositional and structural components of a communityassemblagewereusuallyanalyzedseparately(egFangetal2012)Howeverthenatureofspeciesassemblagesindicatesthateitherspe-cies composition or size structure of constituent individuals alonemayoversimplifycommunityorganization (DeCaacuteceresetal2013)Changes in structure and compositionmay be onlyweakly related(egArsenaultampBradfield1995)thereforeassessmentofbothsi-multaneouslyisimportantwhenevaluatingcommunityassemblyInthepresentstudywegeneralizedtheconventionalapproachtocom-munityassemblagebyincorporatingstructuraldataofacommunityinadditiontocompositionaldatausingtheCAPframeworkToourknowledge this is the firstpaper that investigates inasinglestudythevariationinboththecompositionalandstructuralcomponentsofcommunityassemblagessimultaneouslyaswellasitsdeterminants
F IGURE 3emspThecorrelationsbetweentheLocalContributionstoBetaDiversity(LCBD)intermsofcommunitycomposition(LCBDCOMP)structure(LCBDSTR)andbothcomponentstogether(LCBDCOMPndashSTR)ThecorrelationsofLCBDCOMPvsLCBDSTRLCBDCOMP vsLCBDCOMPndashSTRandLCBDSTR vs LCBDCOMPndashSTRwiththesizeofbinsofthestructuralvariable(binsizes=1ndash15cm)atthescaleof(a)10mtimes10m(b)20mtimes20mand(c)50mtimes50mIngraphs(a)(b)and(c)thehorizontalreddottedlineshorizontalbluelong-dashlinesandhorizontalgreensolidlinesrepresentthemeanvaluesofSpearmanrsquosrankcorrelationcoefficientr across 1ndash15 cm binsizeofLCBDCOMPvsLCBDSTRLCBDCOMPvsLCBDCOMPndashSTRLCBDSTR vs LCBDCOMPndashSTRrespectively(d)BoxplotsfortheSpearmanrsquosrankcorrelationcoefficientrbetweenthepairwiseofthethreekindsofLCBDof1ndash15cmbinsizesatdifferentquadratsizes[Colourfigurecanbeviewedatwileyonlinelibrarycom]
264emsp |emsp emspenspJournal of Vegetation Science
YAO et Al
We found thatbothoverall betadiversity (BD) and the rela-tive contribution of sampling units to beta diversity (LCBD) de-pended on whether the species composition size structure orbothcomponentstogetherhadbeentakenintoaccountBetadi-versity partitioning indicated that the explanatory power of the
environmental and the spatial variables also varied widely withdifferentcomponentsofacommunityOur resultshighlight thatconsideringboth species compositional and size structural com-ponentsmaybeamorecomprehensivewaytodescribethecom-munityorganization
emspensp emsp | emsp265Journal of Vegetation Science
YAO et Al
41emsp|emspStructural and compositional components of forest variation
The framework of CAP allowed us to incorporate the distribu-tionof individualtreesize intotheanalysisofcommunityassem-blage thusmaking it possible toquantify the spatial variationofcommunitystructurebetadiversityEvensosuchstructuralbetadiversitycanbequantified independentlyor incombinationwithspecies composition TheBDCOMPndashSTR is the largest among thesethreecomponentsofbetadiversity indicating thatapplyingspe-ciescompositionaloneorsizestructurealonetoassessthebetadi-versitymayunderestimatethevariationofassemblages(Figure2)ThevaluesofBDCOMPareclosertotheBDCOMPndashSTRvaluesthanthatofBDSTR(theBDSTRvaluesarerelativelysmallFigure2)ThusasfarasourCAPframework isconcerned it seemsmoreappropri-atetoquantifybetadiversityusingthespeciescomposition indi-viduallythanusingthesizestructureindividuallyNeverthelessifstructureprovidesindependentinformationandisdeemedimpor-tantoneshouldincorporateitinBDassessmentAsbetadiversityindiceswerecalculatedfromdissimilaritymatrices thestructuralcomponent of beta diversity depended on the weight given to
structural vs compositional informationwhencalculatingdissimi-larity(Figure2andashc)Thelargerthebinsizes(iethesmallerweightgiventospeciesstructuralinformation)thecloserBDCOMPndashSTR val-uesapproachedthevaluesofBDCOMP(Figure2andashc)Ifthebinsizesare big enough theBDCOMPndashSTR value and theBDCOMP value are expected to converge at a certain size of dbh binNeverthelessconsideringthenecessityofcomprehensiveassessmentofbetadi-versityweadvocateforsmallbinsizesastheyprovidemoreinde-pendentstructuralinformationFinallyitisimportanttonotethatthisforestplotincludes47differenttreespecieswhichresultsinastrongrelativeweightofthecompositionalcomponentofBDCOMPndashSTRwhenusingtheCAPframeworkRepeatingourstudyinforestswith lower species richness or in this forest but using a coarsercompositional resolution (eg at the family level)would result inlargerrelativeweightofthestructuralcomponent
42emsp|emspLocal contributions to beta diversity in terms of community composition and structure
EcologicallyLCBDindicesonlyrepresentthedegreeofuniquenessofthesamplingunitsintermsofcommunitycomposition(Legendre
F IGURE 4emspMapsof30-ha(500mtimes600m)plotshowingthelocalcontributionstobetadiversity(LCBD)intermsofcommunitycompositionandstructurefor750quadrats(20mtimes20m)ThesolidcirclesrepresentthevaluesofLCBDiforeachithquadrat(i =[1750])(a)ThemapofLCBDsonlyintermsofspeciescompositionNotethatthesizestructureofindividuals(iedbh)isnotconsideredwhencalculatingtheLCBDCOMPthusthevaluesofLCBDCOMPwerenotaffectedbythesizeofthebinsofthestructuralvariable(b)ndash(e)ThetwoextremecasesoftheLCBDmap(b)and(c)givingthemostweighttothestructuralcomponentandcorrespondinglytheleastweighttothecompositionalcomponent(ie1-cmbinsize)and(d)and(e)givingthemostweighttothecompositionalcomponentandcorrespondinglytheleastweighttothestructuralcomponent(ie15-cmbinsize)(f)and(g)MapsofLCBDsafteraveragingacrossdbhbinsizesSizeofthecirclesisproportionaltotheLCBDivaluesTheblackandgreysolidcirclesrepresentthesiteswithLCBDvalueshigherandlowerthanthemeanrespectively
TABLE 1emspVariationpartitioningresultsforthreetypesofmatricesatdifferentscalesofquadratsThepartitioningisbasedonadjustedR2 statisticsasrecommendedbyPeres-Netoetal(2006)
Quadrat sizes (a) (b) (c) (d) (a + b) (b + c) (a + b + c)
YCOMP
10mtimes10m 00044 00796 01361 07799 00840 02157 02201
20mtimes20m 00028 01783 02862 05327 01811 04645 04673
50mtimes50m 00050 02995 03229 03726 03045 06224 06274
YSTR
10mtimes10m 00123 00131 00296 09450 00254 00427 00550
20mtimes20m 00013 00907 01652 07428 00920 02560 02572
50mtimes50m 00029 02300 02163 05509 02328 04463 04492
YCOMPndashSTR
10mtimes10m 00055 00564 00932 08449 00619 01496 01551
20mtimes20m 00028 01576 02559 05837 01604 04135 04163
50mtimes50m 00013 02543 01948 05496 02556 04492 04504
Fractions(a)ndash(d)(adjustedR2statistics)(a)variationexplainedbytheenvironmentalvariablesaftercontrollingforthespatialstructure(b)variationexplainedbythespatiallystructuredenvironmentalvariables(c)spatiallystructuredvariationexplainedbypurespaceaftercontrollingforenviron-mentalvariation(d)residualvariationEnvironmentalvariablesusedtocomputefraction(a+b)dbMEMeigenfunctionsweretheexplanatoryvaria-blesusedtocomputefraction(b+c)Only5-cm-diameterclasses(iebinsize=5cm)asthestructuralvariablewereusedtocalculatetheYSTR and YCOMPndashSTR
266emsp |emsp emspenspJournal of Vegetation Science
YAO et Al
amp De Caacuteceres 2013) However natural communities may exhibitsimilarspeciescompositionsbutdifferinotherfeaturessuchasthesizestructureof individuals Inthepresentstudyweassessedthedegreeofuniquenessofthequadratsintermsnotonlyoftheirspe-ciescompositionbutalsooftheirsizestructureandbyusingbothcomponentstogetherThedegreeofuniquenessofquadratsintermsofcommunitycompositionindividuallyhadaveryweakcorrelationwithuniqueness in termsof size structure individually (LCBDCOMP vsLCBDSTRFigure3) indicating that sites that areunique in spe-cies composition are not necessarily unique in size structure andvice versa Additionally we found that the spatial distribution ofsiteswithhighLCBDvaluesisdifferentforthetwocomponentsofacommunitywith siteswithhighstructuraluniquenessoccurringinsmallforestpatches(Figure4)Alltheseresultsreinforcetheideathatconsideringbothspeciescompositionalandsizestructuralcom-ponentsmaybeamorecomprehensivewaytodescribethecommu-nityorganizationHoweverifweacceptthefactthatsitesthatareuniqueintermsofsizestructurearetheresultofgapdynamics(seebelow) the non-zero correlation between LCBDCOMP vs LCBDSTR mayindicatethatforestgapsmaybecolonizedbyspeciesthatmaylaterbesuppressedastheforestgrowssothatrecentforestgapshaveadifferentspeciescompositionthanclosedforeststructures(Comitaetal2009)
43emsp|emspPartitioning the structural and compositional components of beta diversity
About344ofthevariationincommunityassemblagewasdeter-minedbyenvironmentalandspatialvariablesdependingonthescale(quadratsize)andonwhichcomponentsofcommunityassemblage(ie compositional component structural component and takingbothcomponents together)were taken intoaccountThispropor-tion isslightly lowerthanthevaluesfound instudiesbyLegendreetal (2009)andPunchi-Manageetal (2014)Areasonforthisre-sult is thatwe incorporateddifferencesboth insizestructureandspeciescomposition intocommunityassemblagesratherthanonlyusingtheconventionalspeciescompositiondataWhenthespeciescomposition and size structure of the constituent individuals areincorporatedintothecommunityatthesametimemorevariationwilloccurincommunityassemblagesInourstudyhabitat(a+b)ex-plainedmorevariationinthecompositionalcomponent(190)thaninthestructuralcomponent(117)ofthecommunityassemblagesBetadiversitypartitioningindicatedthatthevariationinthestruc-turalcomponentislessdictatedbyenvironmentthanvariationinthecompositional componentWe here hypothesize that canopy gapdynamicswillbethepotentialdriversofstructuralvariationWinterinourstudyareaiscoldandlongwithalongsnowfallperiodThesnowfallperiodlastsforhalfayearandthesnowcoverthicknessinmountainousareasreaches40ndash50cmWehypothesizethatpulsesofmoderate-severity disturbancesmay be caused by snowstormsin our site In the absence of stand-replacing disturbances forestcanopiesareopenedperiodicallybythedeathofsinglebigtreesorsmallgroupsofadulttreescreatingcanopygapsSnowstormsmay
havealteredforeststructurebyselectivelyremovinglargercanopytrees Environmental selection of individuals shapes compositionbydeterminingthefitnessof individualswhereasstructuralvaria-tionmayhavesomerelationshipwithenvironmentalconditions(ielargertreesinsiteswherelargersizesaresupportedforenergyorwateravailability)butingeneralisthereflectionofdifferentstagesaroundgapdynamicsPreviousstudiesareconsistentwithourfind-ingsFraverandWhite(2005)forinstancefoundthattherepeatedmoderate-severity disturbances (iewindstorms) causeddramaticstructural changes they caused no significant change in speciescomposition
Becausetherelativeimportanceofbothnicheandneutralthe-oryinstructuringcommunitiesvarieswithspatialscale(Legendreetal 2009 Punchi-Manage etal 2014) we conducted scale-dependentanalyses InsharpcontrasttothefindingbyLegendreetal(2009)forabroad-leavedforestinChinawefoundthattheproportionofundeterminedvariation incompositionalandstruc-turalcomponentsofcommunityassemblageswasveryhighatfinespatialscales(upto945forthestructuralcomponent780forthecompositionalcomponentand844forbothcomponentsto-gether)butdecreasedsystematicallywith increasingspatial scale(up to a minimum of 373 for compositional component at the50-mscale)TheseresultsareinlinewiththefindingsbyPunchi-Manageetal(2014)inaSriLankandipterocarpforestandbyDeCaacuteceresetal(2012)inacomparisonofseveralforestsOntheonehandthehighproportionofunexplainedvariationmayberelatedtounmeasuredandnotspatially-structuredbiologicalorenviron-mentalvariablesXuetal(2016)showedthatthesoilnutrientsintheupper(0ndash10cmconsideredinourstudy)andlowersoillayers(10ndash20cm)andtheheavymetalelements(CuNiCdAsPbZnMoCrMnandMg)inthesoilshowastrongcorrelationwiththespeciesspatialdistributionsatJiaoheThismaypartlyexplainwhythepureenvironmentalvariable(a)explainedsuchlittlevariationinthecommunityassemblagesAnotherexplanationforthehighpro-portionofunexplainedvariationisthatitmaybeduetostochasticprocesseswhich related to theneutral theoryassuming that thedynamicsofpopulationsareprimarilydrivenbyecologicaldriftanddispersal(Legendreetal2009)Ontheotherhandtheproportionofundeterminedvariationincompositionalandstructuralcompo-nents of community assemblages decreased systematically withincreasingspatialscaleThismayindicatethatcommunityassem-blageishighlystochasticintermsofspeciescompositionandtreesizedistributionatfinescales (ie10-mscale)butthisfinescalestochasticitytendstosmoothoutatthe50-mscalewheremoreconsistent habitat-driven species assemblages emerged Whenvariance partitioning is conducted on the structural componentalonetheunexplained(d)fractionisdominantWhiletheinfluenceofenvironmental factorsonsizestructuremaybe less importantthan for thecompositionalcomponent theeffectof localdistur-bances (eg appearanceof canopygaps resulting frommortalityof largetrees)results inrandomspatialpatternsofquadratswithrather different structure contributing to a large unexplainedfraction
emspensp emsp | emsp267Journal of Vegetation Science
YAO et Al
5emsp |emspCONCLUSIONS
SpeciescompositionandsizestructurearethetwoessentialfeaturesofacommunityOnlyoneofthemindividuallymaybeinsufficienttodescribetheorganizationoftreespeciesassemblagesDefiningandquantifyingbetadiversityusingthespeciescompositionalonemaybesufficienttheninmanyoccasionsNeverthelessspeciescompo-sition is justonedimensionofbiodiversity variation in size struc-tureisalsoimportantIncorporatingstructuraldatainbetadiversityassessmentsallowsecologiststomakeuseofvaluableinformationcollectedduringfieldsurveysIfitisavailablethereisnoreasontoignorethewealthofinformationaboutsizestructurewhencompar-ingspeciesassemblagesOurstudyhighlightstheneedtoincorpo-ratethestructuraldataofacommunityinadditiontocompositionaldatawhenquantifyingandanalyzingbetadiversityFinallyourre-sults suggest thatbothdeterministicandstochasticprocessesarerelevantdeterminantsofcompositionalandstructuralcomponentsof communityassemblages inour temperate forestNeverthelesstheseprocessesarescale-andorresolution-dependent
ACKNOWLEDGEMENTS
WewouldliketothankHeHuaijiangDingShengjianNiRuiqiangandZuoQiangandseveralothersforassistingwiththefielddatacollectionAuthorsaregratefultotheJiaoheManagementBureauof the Forest Experimental Zone for permission to undertake thefieldworkWealsothankthreeanonymousreviewersforprovidingthevaluablecomments
CONFLICTS OF INTEREST
Theauthorsdeclarenocompetingfinancialinterests
DATA ACCESSIBILITY
DataownershipbelongstoBeijingForestryUniversitywhosestaffconductedtheanalysesandwrotethemanuscripthttpwwwbjfueducn
ORCID
Jie Yao httpsorcidorg0000-0002-8606-8158
REFERENCES
Anderson M J Crist T O Chase J M Vellend M InouyeB D Freestone A L hellip Swenson N G (2011) Navigatingthe multiple meanings of β diversity a roadmap for the prac-ticing ecologist Ecology Letters 14 19ndash28 httpsdoiorg101111j1461-0248201001552x
ArsenaultAampBradfieldGE (1995)Structuralndashcompositionalvaria-tioninthreeage-classesoftemperaterainforestsinsoutherncoastalBritishColumbiaCanadian Journal of Botany7354ndash64httpsdoiorg101139b95-007
Borcard D amp Legendre P (1994) Environmental control and spatialstructureinecologicalcommunitiesanexampleusingoribatidmites(Acari Oribatei) Environmental and Ecological Statistics 1 37ndash61httpsdoiorg101007BF00714196
Borcard D Legendre P Avois-Jacquet C amp Tuomisto H (2004)DissectingthespatialstructureofecologicaldataatmultiplescalesEcology851826ndash1832httpsdoiorg10189003-3111
BorcardDLegendrePampDrapeauP(1992)PartiallingoutthespatialcomponentofecologicalvariationEcology731045ndash1055httpsdoiorg1023071940179
Caswell H (1976) Community structure a neutral model anal-ysis Ecological Monographs 46 327ndash354 httpsdoiorg1023071942257
ChaseJM(2010)Stochasticcommunityassemblycauseshigherbiodi-versityinmoreproductiveenvironmentsScience3281388ndash1391httpsdoiorg101126science1187820
ChaveJ(2004)NeutraltheoryandcommunityecologyEcology Letters7241ndash253httpsdoiorg101111j1461-0248200300566x
Chesson P (2000) Mechanisms of maintenance of species diversityAnnual Review of Ecology and Systematics31343ndash366httpsdoiorg101146annurevecolsys311343
ComitaLSUriarteMThompsonJJonckheereICanhamCDampZimmermanJK(2009)Abioticandbioticdriversofseedlingsur-vival inahurricane-impacted tropical forestJournal of Ecology971346ndash1359httpsdoiorg101111j1365-2745200901551x
DeCaacuteceresMFontXampOlivaF(2010)Themanagementofvegeta-tionclassificationswithfuzzyclusteringJournal of Vegetation Science211138ndash1151httpsdoiorg101111j1654-1103201001211x
De Caacuteceres M Legendre P amp He F (2013) Dissimilarity mea-surements and the size structure of ecological communitiesMethods in Ecology and Evolution 4 1167ndash1177 httpsdoiorg1011112041-210X12116
De Caacuteceres M Legendre P Valencia R Cao M Chang L-W Chuyong G hellip He F (2012) The variation of tree betadiversity across a global network of forest plots Global Ecology and Biogeography 21 1191ndash1202 httpsdoiorg101111j1466-8238201200770x
DraySBaumanDBlanchetGBorcardDClappeSGuenardGhellipWagnerHH(2018)adespatial Multivariate multiscale spatial analy-sis R package version 03-2RetrievedfromhttpsCRANR-projectorgpackage=adespatial
Dumbrell A J NelsonM Helgason T Dytham C amp Fitter A H(2010)Relativerolesofnicheandneutralprocesses instructuringa soil microbial community ISME Journal 4 337ndash345 httpsdoiorg101038ismej2009122
FaithDAustinMBelbinLampMargulesC (1985)Numericalclas-sification of profile attributes in environmental studies Journal of Environmental Management2073ndash85
Fang J Shen Z Tang ZWang XWang Z Feng J hellip Zheng C(2012) Forest community survey and the structural character-istics of forests in China Ecography 35 1059ndash1071 httpsdoiorg101111j1600-0587201300161x
FraverSampWhiteAS(2005)Disturbancedynamicsofold-growthPicea rubens forests of northern Maine Journal of Vegetation Science 16 597ndash610 httpsdoiorg101111j1654-11032005tb02401x
Gower J C (1966) Some distance properties of latent root and vec-tormethodsusedinmultivariateanalysisBiometrika53325ndash338httpsdoiorg101093biomet533-4325
Harms K E Condit R Hubbell S P amp Foster R B (2001)Habitat associations of trees and shrubs in a 50-ha neotrop-ical forest plot Journal of Ecology 89 947ndash959 httpsdoiorg101111j1365-2745200100615x
HilleRisLambers J Adler P B Harpole W S Levine J M ampMayfield M M (2012) Rethinking community assembly
268emsp |emsp emspenspJournal of Vegetation Science
YAO et Al
through the lens of coexistence theory Annual Review of Ecology Evolution and Systematics 43 227ndash249 httpsdoiorg101146annurev-ecolsys-110411-160411
HubbellSP(Ed)(2001)The unified theory of biodiversity and biogeogra-phyPrincetonNJPrincetonUniversityPress
Hubbell S P (2006) Neutral theory and the evolution of eco-logical equivalence Ecology 87 1387ndash1398 httpsdoiorg1018900012-9658(2006)87[1387NTATEO]20CO2
HussonFJosseJLeSampMazetJ(2015)FactoMineR Multivariate exploratory data analysis and data mining Version 1314 RetrievedfromhttpsCRANR-projectorgpackage=FactoMineR
Hutchinson G E (1961) The paradox of the plankton American Naturalist95137ndash145httpsdoiorg101086282171
KeddyPA(1992)Assemblyandresponserulestwogoalsforpredic-tive community ecology Journal of Vegetation Science3 157ndash164httpsdoiorg1023073235676
KoleffPGastonKJampLennonJJ(2003)MeasuringbetadiversityforpresencendashabsencedataJournal of Animal Ecology72367ndash382httpsdoiorg101046j1365-2656200300710x
KraftN JBComita L SChase JM SandersN J SwensonNGCrist TOhellipMyers JA (2011)Disentangling thedriversofβdiversityalong latitudinalandelevationalgradientsScience3331755ndash1758httpsdoiorg101126science1208584
LaliberteacuteEPaquetteALegendrePampBouchardA(2009)Assessingthescale-specificimportanceofnichesandotherspatialprocessesonbetadiversityacasestudyfromatemperateforestOecologia159377ndash388httpsdoiorg101007s00442-008-1214-8
Legendre P amp Anderson M J (1999) Distance-based redundancyanalysis testing multispecies responses in multifactorial ecolog-ical experiments Ecological Monographs 69 1ndash24 httpsdoiorg1018900012-9615(1999)069[0001DBRATM]20CO2
Legendre P Borcard D amp Peres-Neto P R (2005) Analyzing betadiversity partitioning the spatial variation of community com-position data Ecological Monographs 75 435ndash450 httpsdoiorg10189005-0549
LegendrePampDeCaacuteceresM(2013)BetadiversityasthevarianceofcommunitydatadissimilaritycoefficientsandpartitioningEcology Letters16951ndash963httpsdoiorg101111ele12141
LegendrePampLegendreL (2012)Numerical ecology Vol 24 (3rded)AmsterdamTheNetherlandsElsevierScienceBV
LegendrePMiXRenHMaKYuMSun I-FampHeF (2009)Partitioning beta diversity in a subtropical broad-leaved forest ofChina Ecology90663ndash674httpsdoiorg10189007-18801
MayfieldMMampLevineJM(2010)Opposingeffectsofcompetitiveex-clusiononthephylogeneticstructureofcommunitiesEcology Letters131085ndash1093httpsdoiorg101111j1461-0248201001509x
MyersJAChaseJMJimeacutenezIJoslashrgensenPMAraujo-MurakamiAPaniagua-ZambranaNampSeidelR(2013)Beta-diversityintem-perateandtropicalforestsreflectsdissimilarmechanismsofcommu-nityassemblyEcology Letters16151ndash157httpsdoiorg101111ele12021
OksanenJBlanchetFGFriendlyMKindtRLegendrePMcGlinnDhellipWagnerH(2018)vegan Community ecology package Version 25-2Retrievedfromhttpscranr-projectorgpackage=vegan
Paradis EClaude JampStrimmerK (2004)APEAnalysesof phylo-genetics and evolution inR languageBioinformatics20 289ndash290httpsdoiorg101093bioinformaticsbtg412
PeetRK (1992)Community structureand function InDCGlenn-LewinRKPeetampTTVeblen(Eds)Plant succession theory and prediction(pp103ndash140)NewYorkNYChapmanampHall
Peres-NetoPRLegendrePDraySampBorcardD(2006)Variationpartitioningofspeciesdatamatricesestimationandcomparisonof
fractionsEcology872614ndash2625httpsdoiorg1018900012-9658(2006)87[2614VPOSDM]20CO2
Punchi-Manage R Wiegand T Wiegand K Getzin S SavitriGunatillekeCV ampNimalGunatilleke IAUN(2014)EffectofspatialprocessesandtopographyonstructuringspeciesassemblagesinaSriLankandipterocarpforestEcology95376ndash386httpsdoiorg10189012-21021
RCoreTeam (2017)R A language and environment for statistical com-puting Vienna Austria R Foundation for Statistical ComputingRetrievedfromhttpswwwR-projectorg
Ricklefs R E (1990) Seabird life histories and the marine environ-mentsomespeculationsColonial Waterbirds13(1)1ndash6httpsdoiorg1023071521414
SchwinningSampWeinerJ(1998)MechanismsdeterminingthedegreeofsizeasymmetryincompetitionamongplantsOecologia113447ndash455httpsdoiorg101007s004420050397
SoilScienceSocietyofChina(Ed)(1999)Soil agricultural chemical analy-sis procedureBeijingChinaChineseAgriculturalSciencePress
van der Plas F Janzen T Ordonez A FokkemaW Reinders JEtienneRSampOlffH(2015)Anewmodelingapproachestimatesthe relative importance of different community assembly pro-cesses Ecology961502ndash1515httpsdoiorg10189014-04541
VellendM(Ed)(2017)The theory of ecological communitiesPrincetonNJPrincetonUniversityPresshttpsdoiorg1015159781400883790
Weiner J (1990) Asymmetric competition in plant popula-tions Trends in Ecology and Evolution 5 360ndash364 httpsdoiorg1010160169-5347(90)90095-U
WhittakerRH (1960)VegetationoftheSiskiyoumountainsOregonand California Ecological Monographs 30 279ndash338 httpsdoiorg1023071943563
WhittakerRH(1972)EvolutionandmeasurementofspeciesdiversityTaxon21213ndash251httpsdoiorg1023071218190
XuWHaoMWangJZhangCZhaoXampvonGadowK(2016)Soilelementsinfluencingcommunitystructureinanold-growthfor-est innortheasternChinaForests7159httpsdoiorg103390f7080159
YamakuraTKanzakiMItohAOhkuboTOginoKChaiEOKhellipAshtonPS(1995)Topographyofalarge-scaleresearchplotes-tablishedwithinatropicalrainforestatLambirSarawakTropics541ndash56httpsdoiorg103759tropics541
YanYZhangCWangYZhaoXampvonGadowK(2015)Driversofseedlingsurvivalinatemperateforestandtheirrelativeimportanceat threestagesofsuccessionEcology and Evolution54287ndash4299httpsdoiorg101002ece31688
YaoJZhangXZhangCZhaoXampvonGadowK(2016)EffectsofdensitydependenceinatemperateforestinnortheasternChinaScientific Reports632844httpsdoiorg101038srep32844
ZhangCZhaoXampvonGadowK(2014)Analyzingselectiveharvestevents inthree largeforestobservationalstudies inNorthEasternChina Forest Ecology and Management 316 100ndash109 httpsdoiorg101016jforeco201307018
ZhangCZhaoYZhaoXampvonGadowK (2012)Species-habitatassociations inanorthern temperate forest inChinaSilva Fennica46501ndash519
How to cite this articleYaoJZhangCDeCaacuteceresMLegendrePZhaoXVariationincompositionalandstructuralcomponentsofcommunityassemblageanditsdeterminantsJ Veg Sci 201930257ndash268 httpsdoiorg101111jvs12708
emspensp emsp | emsp259Journal of Vegetation Science
YAO et Al
datafroma30-ha(500mtimes600m)forestdynamicplot(43deg57928primendash43deg58214primeN127deg45287primendash127deg45790primeE)establishedinthesum-merof2010Theplot issituated inaprotectedold-growthforestina latestageof successionwith littlehumandisturbancedue toits remoteness fromresidential areas (YaoZhangZhangZhaoampGadow2016)
Allindividualswithadiameteratbreastheight(dbh)of1cmormoreintheplotwereidentifiedmeasuredandspatiallymappedin2010Atotalof49684individualtreesbelongingto20familiesand47speciesintheplotwereusedinthepresentstudyTheplotwasdividedinto120(50mtimes50m)750(20mtimes20m)and3000(10mtimes10m)subplotshereaftercalledquadratsTopographicandsoilvari-ableswerealsoavailable foreachquadratFour topographicvari-ables(altitudequadratconvexityslopeandaspect)werecalculatedforeachquadratfollowingtherecommendationofHarmsConditHubbellandFoster(2001)andYamakuraetal(1995)Eightsoilen-vironmentalandnutrientvariablesweremeasuredpHtheamountof organic matter and the total amounts as well as the availablenutrients of nitrogen (N) phosphorus (P) and potassium (K) (ggYanZhangWangZhaoampGadow2015)All laboratoryanalyseswereconductedfollowingtheproceduresrecommendedbytheSoilScienceSocietyofChina(1999)
22emsp|emspStatistical analyses
221emsp|emspCumulative abundance profiles
Theconceptofcumulativeabundanceprofile (CAP)developedbyDeCaacuteceresetal(2013)isdefinedasafunctionthattakestheval-uesofastructuralvariable (egheightdbhetc)as inputandre-turnsthecumulativeabundanceofindividualswhosevaluesofthestructuralvariableareequal toor largerthanthe inputvalueTheCAP framework generalizes traditional species abundance valuesand allows researchers to describe the structural component of acommunityInthepresentstudythestructuralvariablewasdiam-eteratbreastheight(dbh)AccordingtothischoicethevalueofCAPforagivendbhvalueisthecumulativeabundanceoftreeindividualsasbigasorbiggerthantheinputvalueFunctionCAPinfactreplacestheabundancevalueofadbhclassbythesumofabundancesinthisandlargerdbhclasses
222emsp|emspCommunity tables
Following theconventionalmethods speciescomposition tables(ie quadrats in rows species in column and the table contain-ing individual counts)wereassembled in this studywecall thistablethetraditional species composition matrix(YCOMP)InordertogeneralizeatraditionalspeciesabundancevalueanddescribethesizestructurecomponentofthecommunitytheCAPsconsider-ingspeciesidentitywerecalculatedtoobtainthespecies composi-tion combined with structural data matrix(YCOMPndashSTR)TheYCOMPndashSTR isamatrixwithasmanyrowsasplotrecordsandwherecolumnsareorganized inblocksandthereareasmanyblocksasspecies
andeachblockhasasmanycolumnsassizeclassesDisregardingspeciesidentityofthedifferentindividualsCAPswerealsocalcu-latedtoobtainthecommunity structural matrix (YSTR)TheYSTR is amatrixwithasmanyrowsasplotrecordsandasmanycolumnsas size classes
FunctionsldquostratifyvegdatardquoandldquoCAPrdquointhevegclustRpack-age(DeCaacuteceresFontampOliva2010)availableonCRAN(httpsCRANR-projectorgpackage=vegclust) were applied to calculatetheCAPsFunctionsldquostratifyvegdatardquoandldquoCAPrdquorequirediscretiz-ingthestructuralvariableandthenumberofsizebinsaffectstheimportanceaccordedtostructuraldifferencesThustherearede-cisions tobemadewhencreatingYSTR and YCOMPndashSTR particularlyhowwedefine thebinsof thestructuralvariables (egdbhbins)Inthisstudywetestedfrom1-cmbinsizeto15-cmbinsizetodis-cretizedbhintoclassesThat is1cmbinsleadtodbhclasses1ndash22ndash33ndash4andsoonwhereas5cmbinsleadtodbhclasses1ndash56ndash1010ndash15andsoonThesmallerthesizeofdbhbinthemorecolumnswillbeproducedineachblockinthetableYCOMPndashSTRindicatingthatmoreweightisaccordedtodifferencesinstructureandviceversaIfthebinsizewasbigenoughsothatthenumberofcolumnsineachblock in the tableYCOMPndashSTRwasonewewouldhave thatYCOMPndashSTR=YCOMPGenerallythelargerthesizeofdbhbinsthemoresimi-lar will YCOMP and YCOMPndashSTR be
223emsp|emspPairwise dissimilarity in terms of community composition and structure
Wecalculateddissimilaritymatrices between all pairs of quadratsusingthepercentagedifferenceindex(akaBrayndashCurtisdissimilar-ity)oncommunitymatricesYCOMPYSTRandYCOMPndashSTRtoobtainthe compositional dissimilarity matrix (DCOMP) the structural dissimilar-ity matrix (DSTR)andthe compositionalndashstructural dissimilarity matrix (DCOMPndashSTR) respectively In order to explore the pairwise covari-ation between the three kinds of dissimilarity assessments (ieDCOMP vs DSTRDCOMP vs DCOMPndashSTRandDSTR vs DCOMPndashSTR)wefirstcomputed principal coordinates of each dissimilarity matrix usingprincipalcoordinatesanalysis (PCoA) thencomparedtheresultingmatricesofprincipalcoordinateskeepingallaxesusingtheRVco-efficientWeexpectedthatDCOMPndashSTRwouldbecorrelatedtobothDCOMP and DSTRbutthestrengthofthecorrelationdoesdependonthechosensizeofdiameterbins(ieontheweightgiventostruc-turalvscompositionalinformation)
Function ldquovegdistrdquo with the dissimilarity index ldquobrayrdquo in theveganRpackage(Oksanenetal2018)wasusedtocalculatethedissimilarity matrices D Function ldquopcoardquo in the ape R package(ParadisClaudeampStrimmer2004)wasusedtocomputeprincipalcoordinates of eachdissimilaritymatrixD Thedissimilarities inD matricesweresquare-rootedbeforePCoAinordertomakethema-tricesEuclideanandpreventthegenerationofnegativeeigenvaluesandcomplexPCoAaxes (DeCaacuteceresetal2013)Function ldquocoef-fRVrdquo in the FactoMineR R package (Husson Josse LeampMazet2015)wasusedtocalculatetheRVcoefficientsbetweenthematri-cesofprincipalcoordinates
260emsp |emsp emspenspJournal of Vegetation Science
YAO et Al
224emsp|emspBeta diversity components (BDCOMP BDSTR and BDCOMPndashSTR)
Conventionallybetadiversity (abbreviatedBD) is assessed fromasite-by-speciesdatamatrixotherbasiccharacteristics(egsizeofindividuals)ofthecommunityareignoredInordertogeneral-izetheconceptoftraditionalbetadiversitytoCAPdataweap-pliedtheindexproposedbyLegendreetal (2005)andLegendreandDeCaacuteceres(2013)tocomputebetadiversityasthevarianceofthecommunitydataLegendreandDeCaacuteceres(2013)showedhow to compute the total variance of the community composi-tion datamatrix from a dissimilaritymatrixD The total sum ofsquaresSS(Y)canbeobtainedfromadissimilaritymatrixDusingEquation1(LegendreampDeCaacuteceres2013LegendreampLegendre2012) Dividing SS(Y) by (n - 1) produces the classical unbiasedestimateofthetotalvarianceofYcomputedfromauser-selectedEuclidean dissimilarity matrixD (ie Equation 2)We used thatapproach to calculate the traditional compositional beta diversity (BDCOMP) the structural beta diversity (BDSTR) and the composi-tionalndashstructural beta diversity(BDCOMPndashSTR)respectivelyusingthefollowingequations
D =(Dhi)isanntimesnsymmetricdissimilaritymatrix(eitherDCOMP
DSTRorDCOMPndashSTR) i and h representthesamplingunitsn is thenumberofthesamplingunits If thecalculationsstartwithaper-centagedifferenceDmatrixwhichisnon-Euclideanonecomputesthesquare-rootsoftheDvaluesintheDmatrixtomakeitEuclideanbeforeusingthetransformedDvaluesinEquations1and2
225emsp|emspLocal contributions to beta diversity in terms of community composition and structure
Legendre andDe Caacuteceres (2013) suggested that total beta diver-sity can be partitioned into Local Contributions toBetaDiversity(LCBDwhicharecomparative indicatorsoftheecologicalunique-nessofthesites)TheLocalContributionstoBetaDiversity(LCBDi)represent the relative contributionsof the samplingunit i to betadiversityLCBDi indicateshowexceptional thecompositionofsitei iswhencomparedtothecentroidofallpointswhichwouldrep-resent a theoretical site with the average species composition ofall the sampling units In the present study the LCBD representsthe degree of uniqueness of each sampling unit in terms of com-position andor structure of community assemblages LCBDi indi-cescanbecalculatedfromthedissimilaritymatricesD(LegendreampDeCaacuteceres2013)OnefirsttransformsthedistancematrixDintomatrixA =(ahi)=(ndash05D2
hi) then centers thematrix as proposedbyGower(1966)
where Iisanidentitymatrixofsizen1isavectorofones(oflengthn)and1primeisitstranspose(LegendreampLegendre2012)HereeachdiagonalelementofmatrixGistheSSivalues(iethesquareddis-tancetothecentroidoftheithsamplingunit)Hencethevectoroflocalcontributionsofthesitestobetadiversity(LCBDi)is
The LCBD indices are scaled to sum to 1 We used functionldquoLCBDcomprdquointheadespatialRpackage(Drayetal2018)avail-ableonCRAN(httpsCRANR-projectorgpackage=adespatial)tocalculatetheLCBDindices
Wecheckedwhetherthere isacorrelationbetweentheLCBDcoefficientscalculatedfromspeciescompositionsizestructureorusingthetwocomponentstogetherHencewecalculatedSpearmanrank correlations pairwise between the three typesof LCBDvec-tors (ieLCBDCOMPvsLCBDSTRLCBDCOMPvsLCBDCOMPndashSTRandLCBDSTRvsLCBDCOMPndashSTR)SincetheLCBDindicesindicatethede-greeofuniquenessof thesamplingunits in termsof their speciescompositionandorsizestructureweplottedtheLCBDvaluesonmapsof the30-haplotLargeLCBDvalues indicate thesites thathaveuniquespeciesassemblagesandsmallLCBDvaluesindicatethesites thathaveassemblagesthatareverysimilar to those inothersites Againwe expected LCBDCOMPndashSTR to be correlated to bothLCBDCOMP and LCBDSTR butwith the strength of the correlationdependingontheweightgiventostructuralvscompositionalinfor-mationWethusshowedthetwoextremecasesoftheLCBDmapaccordinga largestweighttothestructuralcomponentandcorre-spondinglythesmallestrelativeweighttothecompositionalcompo-nent(ie1-cmbinsize)andgivingthelargestrelativeweighttothecompositionalcomponent(ie15-cmbinsize)
226emsp|emspSets of explanatory variables environmental and spatial variables
Following Legendre etal (2009)we used altitude convexity andslope to construct third-degreepolynomial functions (ie yieldingninevariables)Themonomialswithexponentsallowthemodelingof nonlinear relationships between the topographic variables andthe response variablesWe calculated the aspect of a quadrat astheaverageangleofthefourtriangularplanesthatdeviatefromthenorthdirectionWe thusused the sin (aspect) and cos (aspect) inorder to include it in a linear regressionmodelWe thereforeob-tained11expandedtopographicvariablesWethencombinedthese11 expanded topographic variables with the eight soil variables(described insection21Studysitesanddatacollection) toobtainthe environmental variables data table (ie 19 variables) for eachquadratWe computed eigenfunctions of distance-basedMoranrsquoseigenvector maps (dbMEM also called Principal Coordinates ofNeighbour Matrices PCNM Borcard Legendre Avois-Jacquet amp
(1)SS(Y) =1
n
nminus1sum
h=1
nsum
i=h+1
D2hi
(2)BD = SS(Y)∕(nminus1)
(3)G =
(
Iminus11
n
)
A
(
Iminus11
n
)
(4)(LCBDi) = (SSi)∕SS(Y) = diag(G)∕SS(Y)
emspensp emsp | emsp261Journal of Vegetation Science
YAO et Al
Tuomisto2004LegendreampLegendre2012Legendreetal2009)acrossthe3000(10mtimes10m)750(20mtimes20m)and120(50mtimes50m)quadratsThedbMEMeigenfunctionswithpositiveeigenval-uesonlywereusedasspatialvariablesWeappliedforwardmodelselection(withpermutationtestsatthe5significanceleveloftheincrease in R2 ateachstep) toextract thesignificantenvironmentvariablesandeigenfunctionsofdbMEMusingthefunctionldquoforwardselrdquointhepackageadespatial(Drayetal2018)
227emsp|emspVariation partitioning of DCOMP DSTR and DCOMPndashSTR
Tocompare the influenceofniche-basedandspatialprocessesoncommunityassembly representedbycommunitycompositionsizestructure or the two components together distance-based re-dundancyanalysis (dbRDALegendreampAnderson1999Legendreamp Legendre 2012)was used to partition the variation of each ofthree community matrices (Borcard Legendre amp Drapeau 1992Legendre etal 2009 Peres-Neto Legendre Dray amp Borcard2006) Specificallyweused the two setsof explanatoryvariables(after forwardmodelselection) topartitionvariation in theprinci-palcoordinatetablesextractedfromDCOMPDSTRDCOMPndashSTRsepa-rately into fractions explained by the four different components(a)purehabitat (b)spatiallystructuredhabitat (c)purespaceand(d)undetermined (BorcardampLegendre1994Borcardetal1992DeCaacuteceresetal 2012Legendreetal 2009Myersetal 2013Punchi-Manage etal 2014) We hypothesized that the niche
processesareresponsiblefortheproportionofvariationexplainedbythepurehabitatandthespatially-structuredhabitatcomponents(a+b)(LaliberteacutePaquetteLegendreampBouchard2009Legendreetal2009)Whilewehypothesizedthattheproportionofvariationexplainedbythepurespatialcomponent(c)isrelatedtoindepend-ent biological processes (eg dispersal limitation competition fa-cilitationhistoricaleventsandJanzenndashConnelleffects)(LegendreampLegendre2012Legendreetal2009Punchi-Manageetal2014)Theundeterminedproportionofvariation(d)mayberelatedtosto-chastic processes or undefined non-spatially-structured biologicalor environmental variables (Dumbrell Nelson Helgason DythamampFitter2010)Thatallowedustoassesstherelativecontributionsoftheenvironmentalandspatialvariablestocommunityassemblyin termsof composition structureor taking the twocomponentstogetherAllanalyseswereperformedusingR(RCoreTeam2017)
3emsp |emspRESULTS
31emsp|emspPairwise dissimilarity in terms of community composition and structure
Wefound thatdissimilaritymatricescomputed fromspeciescom-position(DCOMP)sizestructure(DSTR)andconsideringbothcompo-nentstogether(DCOMPndashSTR)werecorrelatedHoweverthestrengthof the correlationdependedon the sizeofbinsused todiscretizethestructuralvariableandonthesizeof thequadrats (Figure1andashc) Overall the correlation between DCOMP vs DCOMPndashSTR was
F IGURE 1emspThecorrelationsbetweenthepairwisedissimilarityintermsofspeciescomposition(DCOMP)sizestructure(DSTR)andbothcomponentstogether(DCOMPndashSTR)ThecorrelationsofDCOMP vs DSTRDCOMP vs DCOMPndashSTRand DSTR vs DCOMPndashSTRvarywithdbhbinsatthescaleof(a)10mtimes10m(b)20mtimes20mand(c)50mtimes50mIngraphs(a)(b)and(c)thehorizontalreddottedlineshorizontalbluelong-dashlinesandhorizontalgreensolidlinesrepresentthemeanvaluesofRVcoefficientsof1ndash15cmdbhbinsofDCOMP vs DSTRDCOMP vs DCOMPndashSTRandDSTR vs DCOMPndashSTRrespectively(d)BoxplotsforRVcoefficientsofthethreepairwisedissimilaritycomparisons(aggregatedoverall1ndash15cmdbhbinsizes)foreachofthethreequadratsizes[Colourfigurecanbeviewedatwileyonlinelibrarycom]
262emsp |emsp emspenspJournal of Vegetation Science
YAO et Al
substantially stronger than that ofDCOMP vs DSTR andofDSTR vs DCOMPndashSTR
The correlation ofDCOMP vs DCOMPndashSTR increasedwith the in-crease of bin size Correspondingly the correlations of DSTR vs DCOMPndashSTR showed the opposite trend (Figure1andashc) As to the ef-fectofthesizeofthesamplingunitsthestrengthofcorrelationsin-creasedwiththequadratsize(Figure1d)exceptforthecorrelationbetweenDCOMP and DCOMPndashSTRwhichexhibitsnosignificantdiffer-encebetweenthe10mtimes10mand20mtimes20mquadrats(p = 023Figure1d)
32emsp|emspThe three components of beta diversity (BD) BDCOMP BDSTR and BDCOMPndashSTR
Thebetadiversity(BD)valueswerecloselyrelatedtowhetherthespecies composition size structure or both components togetherhad been taken into account Among these three components ofbetadiversityBDCOMPndashSTRwasgreatestcloselyfollowedbyBDCOMPandthesmallestwasBDSTR(Figure2)Sincethesizestructureofin-dividualswasnot consideredwhen calculatingBDCOMP this indexwasnotaffectedbythesizeofdbhbins(Figure2andashc)ThevaluesofBDCOMPndashSTRandBDSTRhoweverdecreasedslightlywithanincreaseofbinsizeWhenincreasingdbhbinsizethevaluesofBDCOMPndashSTR graduallyapproachedthevaluesofBDCOMP (Figure2andashc)BDalso
varied as a function of quadrat size (Figure2) values of BDCOMPBDSTRandBDCOMPndashSTR(afteraveragingacrossbinsizes)systemati-callydecreasedwithincreasingquadratsize(Figure2d)
33emsp|emspLocal contributions to beta diversity in terms of community composition and structure
LocalContributionstoBetaDiversitycalculatedusingspeciescom-positionsizestructureorbothcomponentswerecorrelatedAgainthe strengthof correlationsdependedon the sizeofdbhbins andon the size of quadrats (Figure3andashc) In the case of LCBDCOMP vs LCBDCOMPndashSTR the strength of the correlation increased with anincreaseofbinsizeCorrespondinglythecorrelationofLCBDSTR vs LCBDCOMPndashSTRshowedtheoppositetrend(Figure3andashc)Thecorrela-tionsofLCBDCOMPvsLCBDSTRandLCBDSTRvsLCBDCOMPndashSTR were significantly different for differentquadrat sizesA striking findingwasthatthestrengthofcorrelationswasweakeratthescaleof20mtimes20m than that at the scalesof10mtimes10mor50mtimes50m(Figure3d)HowevercorrelationsbetweenLCBDCOMPvsLCBDCOMPndashSTRwerenotsubstantiallyaffectedbythesizeofquadrats(Figure3d)
TheLCBDivaluesindicatetheithquadratsthatcontributemoreorlessthanthemeantobetadiversity(inotherwordstheithquad-ratswithhighorlowuniquenessofspeciesassemblages)TheresultsindicatedthatthesiteswithhighLCBDvalues(contributemorethan
F IGURE 2emspTheBetaDiversity(BD)intermsofspeciescomposition(BDCOMP)sizestructure(BDSTR)andbothcomponentstogether(BDCOMPndashSTR)ThevaluesofBDCOMPndashSTRandBDSTRvarywiththesizeofbinsofthestructuralvariable(dbhbinsizes=1ndash15cm)atthescaleof(a)10mtimes10m(b)20mtimes20mand(c)50mtimes50mThesizestructureofindividuals(iethedbh)isnotconsideredwhencalculatingtheBDCOMPthusthevaluesofBDCOMPwerenotaffectedbythebinsizeIngraphs(a)(b)and(c)thehorizontalbluelong-dashlinesandhorizontalgreensolidlinesrepresentthemeanvaluesofBDCOMPndashSTRandBDSTRacross1ndash15cmbinsizesrespectively(d)ValuesofBDCOMPBDSTRandBDCOMPndashSTR(afteraveragingacrossdbhbinsizes)varywiththesamplingunitsizes[Colourfigurecanbeviewedatwileyonlinelibrarycom]
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themeantobetadiversity)arevariedamongthreecomponentsofacommunity (Figure4)Specifically342(456)290(387)and331 (441)outof750quadratscontributedmorethanthemeanto beta diversity in term of species composition (ie LCBDCOMPFigure4a)sizestructure(ieLCBDSTRFigure4g)andbothcompo-nentstogether(ieLCBDCOMPndashSTRFigure4f)respectively
34emsp|emspVariation partitioning of matrices DCOMP DSTR and DCOMPndashSTR
Theexplanatorypoweroftheenvironmentalvariablesandthespa-tialvariablesvariedforthethreetypesofmatricesandwithquadratsizes (Table 1) The variation explained by the environmental vari-ables(a+b)andbythespatialvariables(b+c)increasedsystemati-callywith increasingscale (Table1)Averagingacrossquadratsizeshabitatandspacejointlyexplained438254and341ofthevariation in compositional component structural component andthe two components together of community assemblage respec-tivelyHoweverthecontributionofthepurehabitatcomponent (a)was negligible The combination of environmental and spatial vari-ablesexplained the lowestproportionofvariation in the structuralcomponentaloneandexplainedthehighestproportionofvariationinthecompositionalcomponentalone(Table1)Boththeenvironmen-talvariables(a+b)andthepurespatialvariables(c)explainedmore
variationinthecompositionalcomponentthanthatinthestructuralcomponentsofcommunityassemblageAdditionallyourfindingsin-dicatethattheunexplained(d)fractionsdominatedthevariancepar-titioningcomputedforthestructuralcomponentYstralone(Table1)
4emsp |emspDISCUSSION
Forest ecosystems can be characterized and evaluated in terms ofboththeirstructureandcomposition(Peet1992)Inpreviousstud-ies the compositional and structural components of a communityassemblagewereusuallyanalyzedseparately(egFangetal2012)Howeverthenatureofspeciesassemblagesindicatesthateitherspe-cies composition or size structure of constituent individuals alonemayoversimplifycommunityorganization (DeCaacuteceresetal2013)Changes in structure and compositionmay be onlyweakly related(egArsenaultampBradfield1995)thereforeassessmentofbothsi-multaneouslyisimportantwhenevaluatingcommunityassemblyInthepresentstudywegeneralizedtheconventionalapproachtocom-munityassemblagebyincorporatingstructuraldataofacommunityinadditiontocompositionaldatausingtheCAPframeworkToourknowledge this is the firstpaper that investigates inasinglestudythevariationinboththecompositionalandstructuralcomponentsofcommunityassemblagessimultaneouslyaswellasitsdeterminants
F IGURE 3emspThecorrelationsbetweentheLocalContributionstoBetaDiversity(LCBD)intermsofcommunitycomposition(LCBDCOMP)structure(LCBDSTR)andbothcomponentstogether(LCBDCOMPndashSTR)ThecorrelationsofLCBDCOMPvsLCBDSTRLCBDCOMP vsLCBDCOMPndashSTRandLCBDSTR vs LCBDCOMPndashSTRwiththesizeofbinsofthestructuralvariable(binsizes=1ndash15cm)atthescaleof(a)10mtimes10m(b)20mtimes20mand(c)50mtimes50mIngraphs(a)(b)and(c)thehorizontalreddottedlineshorizontalbluelong-dashlinesandhorizontalgreensolidlinesrepresentthemeanvaluesofSpearmanrsquosrankcorrelationcoefficientr across 1ndash15 cm binsizeofLCBDCOMPvsLCBDSTRLCBDCOMPvsLCBDCOMPndashSTRLCBDSTR vs LCBDCOMPndashSTRrespectively(d)BoxplotsfortheSpearmanrsquosrankcorrelationcoefficientrbetweenthepairwiseofthethreekindsofLCBDof1ndash15cmbinsizesatdifferentquadratsizes[Colourfigurecanbeviewedatwileyonlinelibrarycom]
264emsp |emsp emspenspJournal of Vegetation Science
YAO et Al
We found thatbothoverall betadiversity (BD) and the rela-tive contribution of sampling units to beta diversity (LCBD) de-pended on whether the species composition size structure orbothcomponentstogetherhadbeentakenintoaccountBetadi-versity partitioning indicated that the explanatory power of the
environmental and the spatial variables also varied widely withdifferentcomponentsofacommunityOur resultshighlight thatconsideringboth species compositional and size structural com-ponentsmaybeamorecomprehensivewaytodescribethecom-munityorganization
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YAO et Al
41emsp|emspStructural and compositional components of forest variation
The framework of CAP allowed us to incorporate the distribu-tionof individualtreesize intotheanalysisofcommunityassem-blage thusmaking it possible toquantify the spatial variationofcommunitystructurebetadiversityEvensosuchstructuralbetadiversitycanbequantified independentlyor incombinationwithspecies composition TheBDCOMPndashSTR is the largest among thesethreecomponentsofbetadiversity indicating thatapplyingspe-ciescompositionaloneorsizestructurealonetoassessthebetadi-versitymayunderestimatethevariationofassemblages(Figure2)ThevaluesofBDCOMPareclosertotheBDCOMPndashSTRvaluesthanthatofBDSTR(theBDSTRvaluesarerelativelysmallFigure2)ThusasfarasourCAPframework isconcerned it seemsmoreappropri-atetoquantifybetadiversityusingthespeciescomposition indi-viduallythanusingthesizestructureindividuallyNeverthelessifstructureprovidesindependentinformationandisdeemedimpor-tantoneshouldincorporateitinBDassessmentAsbetadiversityindiceswerecalculatedfromdissimilaritymatrices thestructuralcomponent of beta diversity depended on the weight given to
structural vs compositional informationwhencalculatingdissimi-larity(Figure2andashc)Thelargerthebinsizes(iethesmallerweightgiventospeciesstructuralinformation)thecloserBDCOMPndashSTR val-uesapproachedthevaluesofBDCOMP(Figure2andashc)Ifthebinsizesare big enough theBDCOMPndashSTR value and theBDCOMP value are expected to converge at a certain size of dbh binNeverthelessconsideringthenecessityofcomprehensiveassessmentofbetadi-versityweadvocateforsmallbinsizesastheyprovidemoreinde-pendentstructuralinformationFinallyitisimportanttonotethatthisforestplotincludes47differenttreespecieswhichresultsinastrongrelativeweightofthecompositionalcomponentofBDCOMPndashSTRwhenusingtheCAPframeworkRepeatingourstudyinforestswith lower species richness or in this forest but using a coarsercompositional resolution (eg at the family level)would result inlargerrelativeweightofthestructuralcomponent
42emsp|emspLocal contributions to beta diversity in terms of community composition and structure
EcologicallyLCBDindicesonlyrepresentthedegreeofuniquenessofthesamplingunitsintermsofcommunitycomposition(Legendre
F IGURE 4emspMapsof30-ha(500mtimes600m)plotshowingthelocalcontributionstobetadiversity(LCBD)intermsofcommunitycompositionandstructurefor750quadrats(20mtimes20m)ThesolidcirclesrepresentthevaluesofLCBDiforeachithquadrat(i =[1750])(a)ThemapofLCBDsonlyintermsofspeciescompositionNotethatthesizestructureofindividuals(iedbh)isnotconsideredwhencalculatingtheLCBDCOMPthusthevaluesofLCBDCOMPwerenotaffectedbythesizeofthebinsofthestructuralvariable(b)ndash(e)ThetwoextremecasesoftheLCBDmap(b)and(c)givingthemostweighttothestructuralcomponentandcorrespondinglytheleastweighttothecompositionalcomponent(ie1-cmbinsize)and(d)and(e)givingthemostweighttothecompositionalcomponentandcorrespondinglytheleastweighttothestructuralcomponent(ie15-cmbinsize)(f)and(g)MapsofLCBDsafteraveragingacrossdbhbinsizesSizeofthecirclesisproportionaltotheLCBDivaluesTheblackandgreysolidcirclesrepresentthesiteswithLCBDvalueshigherandlowerthanthemeanrespectively
TABLE 1emspVariationpartitioningresultsforthreetypesofmatricesatdifferentscalesofquadratsThepartitioningisbasedonadjustedR2 statisticsasrecommendedbyPeres-Netoetal(2006)
Quadrat sizes (a) (b) (c) (d) (a + b) (b + c) (a + b + c)
YCOMP
10mtimes10m 00044 00796 01361 07799 00840 02157 02201
20mtimes20m 00028 01783 02862 05327 01811 04645 04673
50mtimes50m 00050 02995 03229 03726 03045 06224 06274
YSTR
10mtimes10m 00123 00131 00296 09450 00254 00427 00550
20mtimes20m 00013 00907 01652 07428 00920 02560 02572
50mtimes50m 00029 02300 02163 05509 02328 04463 04492
YCOMPndashSTR
10mtimes10m 00055 00564 00932 08449 00619 01496 01551
20mtimes20m 00028 01576 02559 05837 01604 04135 04163
50mtimes50m 00013 02543 01948 05496 02556 04492 04504
Fractions(a)ndash(d)(adjustedR2statistics)(a)variationexplainedbytheenvironmentalvariablesaftercontrollingforthespatialstructure(b)variationexplainedbythespatiallystructuredenvironmentalvariables(c)spatiallystructuredvariationexplainedbypurespaceaftercontrollingforenviron-mentalvariation(d)residualvariationEnvironmentalvariablesusedtocomputefraction(a+b)dbMEMeigenfunctionsweretheexplanatoryvaria-blesusedtocomputefraction(b+c)Only5-cm-diameterclasses(iebinsize=5cm)asthestructuralvariablewereusedtocalculatetheYSTR and YCOMPndashSTR
266emsp |emsp emspenspJournal of Vegetation Science
YAO et Al
amp De Caacuteceres 2013) However natural communities may exhibitsimilarspeciescompositionsbutdifferinotherfeaturessuchasthesizestructureof individuals Inthepresentstudyweassessedthedegreeofuniquenessofthequadratsintermsnotonlyoftheirspe-ciescompositionbutalsooftheirsizestructureandbyusingbothcomponentstogetherThedegreeofuniquenessofquadratsintermsofcommunitycompositionindividuallyhadaveryweakcorrelationwithuniqueness in termsof size structure individually (LCBDCOMP vsLCBDSTRFigure3) indicating that sites that areunique in spe-cies composition are not necessarily unique in size structure andvice versa Additionally we found that the spatial distribution ofsiteswithhighLCBDvaluesisdifferentforthetwocomponentsofacommunitywith siteswithhighstructuraluniquenessoccurringinsmallforestpatches(Figure4)Alltheseresultsreinforcetheideathatconsideringbothspeciescompositionalandsizestructuralcom-ponentsmaybeamorecomprehensivewaytodescribethecommu-nityorganizationHoweverifweacceptthefactthatsitesthatareuniqueintermsofsizestructurearetheresultofgapdynamics(seebelow) the non-zero correlation between LCBDCOMP vs LCBDSTR mayindicatethatforestgapsmaybecolonizedbyspeciesthatmaylaterbesuppressedastheforestgrowssothatrecentforestgapshaveadifferentspeciescompositionthanclosedforeststructures(Comitaetal2009)
43emsp|emspPartitioning the structural and compositional components of beta diversity
About344ofthevariationincommunityassemblagewasdeter-minedbyenvironmentalandspatialvariablesdependingonthescale(quadratsize)andonwhichcomponentsofcommunityassemblage(ie compositional component structural component and takingbothcomponents together)were taken intoaccountThispropor-tion isslightly lowerthanthevaluesfound instudiesbyLegendreetal (2009)andPunchi-Manageetal (2014)Areasonforthisre-sult is thatwe incorporateddifferencesboth insizestructureandspeciescomposition intocommunityassemblagesratherthanonlyusingtheconventionalspeciescompositiondataWhenthespeciescomposition and size structure of the constituent individuals areincorporatedintothecommunityatthesametimemorevariationwilloccurincommunityassemblagesInourstudyhabitat(a+b)ex-plainedmorevariationinthecompositionalcomponent(190)thaninthestructuralcomponent(117)ofthecommunityassemblagesBetadiversitypartitioningindicatedthatthevariationinthestruc-turalcomponentislessdictatedbyenvironmentthanvariationinthecompositional componentWe here hypothesize that canopy gapdynamicswillbethepotentialdriversofstructuralvariationWinterinourstudyareaiscoldandlongwithalongsnowfallperiodThesnowfallperiodlastsforhalfayearandthesnowcoverthicknessinmountainousareasreaches40ndash50cmWehypothesizethatpulsesofmoderate-severity disturbancesmay be caused by snowstormsin our site In the absence of stand-replacing disturbances forestcanopiesareopenedperiodicallybythedeathofsinglebigtreesorsmallgroupsofadulttreescreatingcanopygapsSnowstormsmay
havealteredforeststructurebyselectivelyremovinglargercanopytrees Environmental selection of individuals shapes compositionbydeterminingthefitnessof individualswhereasstructuralvaria-tionmayhavesomerelationshipwithenvironmentalconditions(ielargertreesinsiteswherelargersizesaresupportedforenergyorwateravailability)butingeneralisthereflectionofdifferentstagesaroundgapdynamicsPreviousstudiesareconsistentwithourfind-ingsFraverandWhite(2005)forinstancefoundthattherepeatedmoderate-severity disturbances (iewindstorms) causeddramaticstructural changes they caused no significant change in speciescomposition
Becausetherelativeimportanceofbothnicheandneutralthe-oryinstructuringcommunitiesvarieswithspatialscale(Legendreetal 2009 Punchi-Manage etal 2014) we conducted scale-dependentanalyses InsharpcontrasttothefindingbyLegendreetal(2009)forabroad-leavedforestinChinawefoundthattheproportionofundeterminedvariation incompositionalandstruc-turalcomponentsofcommunityassemblageswasveryhighatfinespatialscales(upto945forthestructuralcomponent780forthecompositionalcomponentand844forbothcomponentsto-gether)butdecreasedsystematicallywith increasingspatial scale(up to a minimum of 373 for compositional component at the50-mscale)TheseresultsareinlinewiththefindingsbyPunchi-Manageetal(2014)inaSriLankandipterocarpforestandbyDeCaacuteceresetal(2012)inacomparisonofseveralforestsOntheonehandthehighproportionofunexplainedvariationmayberelatedtounmeasuredandnotspatially-structuredbiologicalorenviron-mentalvariablesXuetal(2016)showedthatthesoilnutrientsintheupper(0ndash10cmconsideredinourstudy)andlowersoillayers(10ndash20cm)andtheheavymetalelements(CuNiCdAsPbZnMoCrMnandMg)inthesoilshowastrongcorrelationwiththespeciesspatialdistributionsatJiaoheThismaypartlyexplainwhythepureenvironmentalvariable(a)explainedsuchlittlevariationinthecommunityassemblagesAnotherexplanationforthehighpro-portionofunexplainedvariationisthatitmaybeduetostochasticprocesseswhich related to theneutral theoryassuming that thedynamicsofpopulationsareprimarilydrivenbyecologicaldriftanddispersal(Legendreetal2009)Ontheotherhandtheproportionofundeterminedvariationincompositionalandstructuralcompo-nents of community assemblages decreased systematically withincreasingspatialscaleThismayindicatethatcommunityassem-blageishighlystochasticintermsofspeciescompositionandtreesizedistributionatfinescales (ie10-mscale)butthisfinescalestochasticitytendstosmoothoutatthe50-mscalewheremoreconsistent habitat-driven species assemblages emerged Whenvariance partitioning is conducted on the structural componentalonetheunexplained(d)fractionisdominantWhiletheinfluenceofenvironmental factorsonsizestructuremaybe less importantthan for thecompositionalcomponent theeffectof localdistur-bances (eg appearanceof canopygaps resulting frommortalityof largetrees)results inrandomspatialpatternsofquadratswithrather different structure contributing to a large unexplainedfraction
emspensp emsp | emsp267Journal of Vegetation Science
YAO et Al
5emsp |emspCONCLUSIONS
SpeciescompositionandsizestructurearethetwoessentialfeaturesofacommunityOnlyoneofthemindividuallymaybeinsufficienttodescribetheorganizationoftreespeciesassemblagesDefiningandquantifyingbetadiversityusingthespeciescompositionalonemaybesufficienttheninmanyoccasionsNeverthelessspeciescompo-sition is justonedimensionofbiodiversity variation in size struc-tureisalsoimportantIncorporatingstructuraldatainbetadiversityassessmentsallowsecologiststomakeuseofvaluableinformationcollectedduringfieldsurveysIfitisavailablethereisnoreasontoignorethewealthofinformationaboutsizestructurewhencompar-ingspeciesassemblagesOurstudyhighlightstheneedtoincorpo-ratethestructuraldataofacommunityinadditiontocompositionaldatawhenquantifyingandanalyzingbetadiversityFinallyourre-sults suggest thatbothdeterministicandstochasticprocessesarerelevantdeterminantsofcompositionalandstructuralcomponentsof communityassemblages inour temperate forestNeverthelesstheseprocessesarescale-andorresolution-dependent
ACKNOWLEDGEMENTS
WewouldliketothankHeHuaijiangDingShengjianNiRuiqiangandZuoQiangandseveralothersforassistingwiththefielddatacollectionAuthorsaregratefultotheJiaoheManagementBureauof the Forest Experimental Zone for permission to undertake thefieldworkWealsothankthreeanonymousreviewersforprovidingthevaluablecomments
CONFLICTS OF INTEREST
Theauthorsdeclarenocompetingfinancialinterests
DATA ACCESSIBILITY
DataownershipbelongstoBeijingForestryUniversitywhosestaffconductedtheanalysesandwrotethemanuscripthttpwwwbjfueducn
ORCID
Jie Yao httpsorcidorg0000-0002-8606-8158
REFERENCES
Anderson M J Crist T O Chase J M Vellend M InouyeB D Freestone A L hellip Swenson N G (2011) Navigatingthe multiple meanings of β diversity a roadmap for the prac-ticing ecologist Ecology Letters 14 19ndash28 httpsdoiorg101111j1461-0248201001552x
ArsenaultAampBradfieldGE (1995)Structuralndashcompositionalvaria-tioninthreeage-classesoftemperaterainforestsinsoutherncoastalBritishColumbiaCanadian Journal of Botany7354ndash64httpsdoiorg101139b95-007
Borcard D amp Legendre P (1994) Environmental control and spatialstructureinecologicalcommunitiesanexampleusingoribatidmites(Acari Oribatei) Environmental and Ecological Statistics 1 37ndash61httpsdoiorg101007BF00714196
Borcard D Legendre P Avois-Jacquet C amp Tuomisto H (2004)DissectingthespatialstructureofecologicaldataatmultiplescalesEcology851826ndash1832httpsdoiorg10189003-3111
BorcardDLegendrePampDrapeauP(1992)PartiallingoutthespatialcomponentofecologicalvariationEcology731045ndash1055httpsdoiorg1023071940179
Caswell H (1976) Community structure a neutral model anal-ysis Ecological Monographs 46 327ndash354 httpsdoiorg1023071942257
ChaseJM(2010)Stochasticcommunityassemblycauseshigherbiodi-versityinmoreproductiveenvironmentsScience3281388ndash1391httpsdoiorg101126science1187820
ChaveJ(2004)NeutraltheoryandcommunityecologyEcology Letters7241ndash253httpsdoiorg101111j1461-0248200300566x
Chesson P (2000) Mechanisms of maintenance of species diversityAnnual Review of Ecology and Systematics31343ndash366httpsdoiorg101146annurevecolsys311343
ComitaLSUriarteMThompsonJJonckheereICanhamCDampZimmermanJK(2009)Abioticandbioticdriversofseedlingsur-vival inahurricane-impacted tropical forestJournal of Ecology971346ndash1359httpsdoiorg101111j1365-2745200901551x
DeCaacuteceresMFontXampOlivaF(2010)Themanagementofvegeta-tionclassificationswithfuzzyclusteringJournal of Vegetation Science211138ndash1151httpsdoiorg101111j1654-1103201001211x
De Caacuteceres M Legendre P amp He F (2013) Dissimilarity mea-surements and the size structure of ecological communitiesMethods in Ecology and Evolution 4 1167ndash1177 httpsdoiorg1011112041-210X12116
De Caacuteceres M Legendre P Valencia R Cao M Chang L-W Chuyong G hellip He F (2012) The variation of tree betadiversity across a global network of forest plots Global Ecology and Biogeography 21 1191ndash1202 httpsdoiorg101111j1466-8238201200770x
DraySBaumanDBlanchetGBorcardDClappeSGuenardGhellipWagnerHH(2018)adespatial Multivariate multiscale spatial analy-sis R package version 03-2RetrievedfromhttpsCRANR-projectorgpackage=adespatial
Dumbrell A J NelsonM Helgason T Dytham C amp Fitter A H(2010)Relativerolesofnicheandneutralprocesses instructuringa soil microbial community ISME Journal 4 337ndash345 httpsdoiorg101038ismej2009122
FaithDAustinMBelbinLampMargulesC (1985)Numericalclas-sification of profile attributes in environmental studies Journal of Environmental Management2073ndash85
Fang J Shen Z Tang ZWang XWang Z Feng J hellip Zheng C(2012) Forest community survey and the structural character-istics of forests in China Ecography 35 1059ndash1071 httpsdoiorg101111j1600-0587201300161x
FraverSampWhiteAS(2005)Disturbancedynamicsofold-growthPicea rubens forests of northern Maine Journal of Vegetation Science 16 597ndash610 httpsdoiorg101111j1654-11032005tb02401x
Gower J C (1966) Some distance properties of latent root and vec-tormethodsusedinmultivariateanalysisBiometrika53325ndash338httpsdoiorg101093biomet533-4325
Harms K E Condit R Hubbell S P amp Foster R B (2001)Habitat associations of trees and shrubs in a 50-ha neotrop-ical forest plot Journal of Ecology 89 947ndash959 httpsdoiorg101111j1365-2745200100615x
HilleRisLambers J Adler P B Harpole W S Levine J M ampMayfield M M (2012) Rethinking community assembly
268emsp |emsp emspenspJournal of Vegetation Science
YAO et Al
through the lens of coexistence theory Annual Review of Ecology Evolution and Systematics 43 227ndash249 httpsdoiorg101146annurev-ecolsys-110411-160411
HubbellSP(Ed)(2001)The unified theory of biodiversity and biogeogra-phyPrincetonNJPrincetonUniversityPress
Hubbell S P (2006) Neutral theory and the evolution of eco-logical equivalence Ecology 87 1387ndash1398 httpsdoiorg1018900012-9658(2006)87[1387NTATEO]20CO2
HussonFJosseJLeSampMazetJ(2015)FactoMineR Multivariate exploratory data analysis and data mining Version 1314 RetrievedfromhttpsCRANR-projectorgpackage=FactoMineR
Hutchinson G E (1961) The paradox of the plankton American Naturalist95137ndash145httpsdoiorg101086282171
KeddyPA(1992)Assemblyandresponserulestwogoalsforpredic-tive community ecology Journal of Vegetation Science3 157ndash164httpsdoiorg1023073235676
KoleffPGastonKJampLennonJJ(2003)MeasuringbetadiversityforpresencendashabsencedataJournal of Animal Ecology72367ndash382httpsdoiorg101046j1365-2656200300710x
KraftN JBComita L SChase JM SandersN J SwensonNGCrist TOhellipMyers JA (2011)Disentangling thedriversofβdiversityalong latitudinalandelevationalgradientsScience3331755ndash1758httpsdoiorg101126science1208584
LaliberteacuteEPaquetteALegendrePampBouchardA(2009)Assessingthescale-specificimportanceofnichesandotherspatialprocessesonbetadiversityacasestudyfromatemperateforestOecologia159377ndash388httpsdoiorg101007s00442-008-1214-8
Legendre P amp Anderson M J (1999) Distance-based redundancyanalysis testing multispecies responses in multifactorial ecolog-ical experiments Ecological Monographs 69 1ndash24 httpsdoiorg1018900012-9615(1999)069[0001DBRATM]20CO2
Legendre P Borcard D amp Peres-Neto P R (2005) Analyzing betadiversity partitioning the spatial variation of community com-position data Ecological Monographs 75 435ndash450 httpsdoiorg10189005-0549
LegendrePampDeCaacuteceresM(2013)BetadiversityasthevarianceofcommunitydatadissimilaritycoefficientsandpartitioningEcology Letters16951ndash963httpsdoiorg101111ele12141
LegendrePampLegendreL (2012)Numerical ecology Vol 24 (3rded)AmsterdamTheNetherlandsElsevierScienceBV
LegendrePMiXRenHMaKYuMSun I-FampHeF (2009)Partitioning beta diversity in a subtropical broad-leaved forest ofChina Ecology90663ndash674httpsdoiorg10189007-18801
MayfieldMMampLevineJM(2010)Opposingeffectsofcompetitiveex-clusiononthephylogeneticstructureofcommunitiesEcology Letters131085ndash1093httpsdoiorg101111j1461-0248201001509x
MyersJAChaseJMJimeacutenezIJoslashrgensenPMAraujo-MurakamiAPaniagua-ZambranaNampSeidelR(2013)Beta-diversityintem-perateandtropicalforestsreflectsdissimilarmechanismsofcommu-nityassemblyEcology Letters16151ndash157httpsdoiorg101111ele12021
OksanenJBlanchetFGFriendlyMKindtRLegendrePMcGlinnDhellipWagnerH(2018)vegan Community ecology package Version 25-2Retrievedfromhttpscranr-projectorgpackage=vegan
Paradis EClaude JampStrimmerK (2004)APEAnalysesof phylo-genetics and evolution inR languageBioinformatics20 289ndash290httpsdoiorg101093bioinformaticsbtg412
PeetRK (1992)Community structureand function InDCGlenn-LewinRKPeetampTTVeblen(Eds)Plant succession theory and prediction(pp103ndash140)NewYorkNYChapmanampHall
Peres-NetoPRLegendrePDraySampBorcardD(2006)Variationpartitioningofspeciesdatamatricesestimationandcomparisonof
fractionsEcology872614ndash2625httpsdoiorg1018900012-9658(2006)87[2614VPOSDM]20CO2
Punchi-Manage R Wiegand T Wiegand K Getzin S SavitriGunatillekeCV ampNimalGunatilleke IAUN(2014)EffectofspatialprocessesandtopographyonstructuringspeciesassemblagesinaSriLankandipterocarpforestEcology95376ndash386httpsdoiorg10189012-21021
RCoreTeam (2017)R A language and environment for statistical com-puting Vienna Austria R Foundation for Statistical ComputingRetrievedfromhttpswwwR-projectorg
Ricklefs R E (1990) Seabird life histories and the marine environ-mentsomespeculationsColonial Waterbirds13(1)1ndash6httpsdoiorg1023071521414
SchwinningSampWeinerJ(1998)MechanismsdeterminingthedegreeofsizeasymmetryincompetitionamongplantsOecologia113447ndash455httpsdoiorg101007s004420050397
SoilScienceSocietyofChina(Ed)(1999)Soil agricultural chemical analy-sis procedureBeijingChinaChineseAgriculturalSciencePress
van der Plas F Janzen T Ordonez A FokkemaW Reinders JEtienneRSampOlffH(2015)Anewmodelingapproachestimatesthe relative importance of different community assembly pro-cesses Ecology961502ndash1515httpsdoiorg10189014-04541
VellendM(Ed)(2017)The theory of ecological communitiesPrincetonNJPrincetonUniversityPresshttpsdoiorg1015159781400883790
Weiner J (1990) Asymmetric competition in plant popula-tions Trends in Ecology and Evolution 5 360ndash364 httpsdoiorg1010160169-5347(90)90095-U
WhittakerRH (1960)VegetationoftheSiskiyoumountainsOregonand California Ecological Monographs 30 279ndash338 httpsdoiorg1023071943563
WhittakerRH(1972)EvolutionandmeasurementofspeciesdiversityTaxon21213ndash251httpsdoiorg1023071218190
XuWHaoMWangJZhangCZhaoXampvonGadowK(2016)Soilelementsinfluencingcommunitystructureinanold-growthfor-est innortheasternChinaForests7159httpsdoiorg103390f7080159
YamakuraTKanzakiMItohAOhkuboTOginoKChaiEOKhellipAshtonPS(1995)Topographyofalarge-scaleresearchplotes-tablishedwithinatropicalrainforestatLambirSarawakTropics541ndash56httpsdoiorg103759tropics541
YanYZhangCWangYZhaoXampvonGadowK(2015)Driversofseedlingsurvivalinatemperateforestandtheirrelativeimportanceat threestagesofsuccessionEcology and Evolution54287ndash4299httpsdoiorg101002ece31688
YaoJZhangXZhangCZhaoXampvonGadowK(2016)EffectsofdensitydependenceinatemperateforestinnortheasternChinaScientific Reports632844httpsdoiorg101038srep32844
ZhangCZhaoXampvonGadowK(2014)Analyzingselectiveharvestevents inthree largeforestobservationalstudies inNorthEasternChina Forest Ecology and Management 316 100ndash109 httpsdoiorg101016jforeco201307018
ZhangCZhaoYZhaoXampvonGadowK (2012)Species-habitatassociations inanorthern temperate forest inChinaSilva Fennica46501ndash519
How to cite this articleYaoJZhangCDeCaacuteceresMLegendrePZhaoXVariationincompositionalandstructuralcomponentsofcommunityassemblageanditsdeterminantsJ Veg Sci 201930257ndash268 httpsdoiorg101111jvs12708
260emsp |emsp emspenspJournal of Vegetation Science
YAO et Al
224emsp|emspBeta diversity components (BDCOMP BDSTR and BDCOMPndashSTR)
Conventionallybetadiversity (abbreviatedBD) is assessed fromasite-by-speciesdatamatrixotherbasiccharacteristics(egsizeofindividuals)ofthecommunityareignoredInordertogeneral-izetheconceptoftraditionalbetadiversitytoCAPdataweap-pliedtheindexproposedbyLegendreetal (2005)andLegendreandDeCaacuteceres(2013)tocomputebetadiversityasthevarianceofthecommunitydataLegendreandDeCaacuteceres(2013)showedhow to compute the total variance of the community composi-tion datamatrix from a dissimilaritymatrixD The total sum ofsquaresSS(Y)canbeobtainedfromadissimilaritymatrixDusingEquation1(LegendreampDeCaacuteceres2013LegendreampLegendre2012) Dividing SS(Y) by (n - 1) produces the classical unbiasedestimateofthetotalvarianceofYcomputedfromauser-selectedEuclidean dissimilarity matrixD (ie Equation 2)We used thatapproach to calculate the traditional compositional beta diversity (BDCOMP) the structural beta diversity (BDSTR) and the composi-tionalndashstructural beta diversity(BDCOMPndashSTR)respectivelyusingthefollowingequations
D =(Dhi)isanntimesnsymmetricdissimilaritymatrix(eitherDCOMP
DSTRorDCOMPndashSTR) i and h representthesamplingunitsn is thenumberofthesamplingunits If thecalculationsstartwithaper-centagedifferenceDmatrixwhichisnon-Euclideanonecomputesthesquare-rootsoftheDvaluesintheDmatrixtomakeitEuclideanbeforeusingthetransformedDvaluesinEquations1and2
225emsp|emspLocal contributions to beta diversity in terms of community composition and structure
Legendre andDe Caacuteceres (2013) suggested that total beta diver-sity can be partitioned into Local Contributions toBetaDiversity(LCBDwhicharecomparative indicatorsoftheecologicalunique-nessofthesites)TheLocalContributionstoBetaDiversity(LCBDi)represent the relative contributionsof the samplingunit i to betadiversityLCBDi indicateshowexceptional thecompositionofsitei iswhencomparedtothecentroidofallpointswhichwouldrep-resent a theoretical site with the average species composition ofall the sampling units In the present study the LCBD representsthe degree of uniqueness of each sampling unit in terms of com-position andor structure of community assemblages LCBDi indi-cescanbecalculatedfromthedissimilaritymatricesD(LegendreampDeCaacuteceres2013)OnefirsttransformsthedistancematrixDintomatrixA =(ahi)=(ndash05D2
hi) then centers thematrix as proposedbyGower(1966)
where Iisanidentitymatrixofsizen1isavectorofones(oflengthn)and1primeisitstranspose(LegendreampLegendre2012)HereeachdiagonalelementofmatrixGistheSSivalues(iethesquareddis-tancetothecentroidoftheithsamplingunit)Hencethevectoroflocalcontributionsofthesitestobetadiversity(LCBDi)is
The LCBD indices are scaled to sum to 1 We used functionldquoLCBDcomprdquointheadespatialRpackage(Drayetal2018)avail-ableonCRAN(httpsCRANR-projectorgpackage=adespatial)tocalculatetheLCBDindices
Wecheckedwhetherthere isacorrelationbetweentheLCBDcoefficientscalculatedfromspeciescompositionsizestructureorusingthetwocomponentstogetherHencewecalculatedSpearmanrank correlations pairwise between the three typesof LCBDvec-tors (ieLCBDCOMPvsLCBDSTRLCBDCOMPvsLCBDCOMPndashSTRandLCBDSTRvsLCBDCOMPndashSTR)SincetheLCBDindicesindicatethede-greeofuniquenessof thesamplingunits in termsof their speciescompositionandorsizestructureweplottedtheLCBDvaluesonmapsof the30-haplotLargeLCBDvalues indicate thesites thathaveuniquespeciesassemblagesandsmallLCBDvaluesindicatethesites thathaveassemblagesthatareverysimilar to those inothersites Againwe expected LCBDCOMPndashSTR to be correlated to bothLCBDCOMP and LCBDSTR butwith the strength of the correlationdependingontheweightgiventostructuralvscompositionalinfor-mationWethusshowedthetwoextremecasesoftheLCBDmapaccordinga largestweighttothestructuralcomponentandcorre-spondinglythesmallestrelativeweighttothecompositionalcompo-nent(ie1-cmbinsize)andgivingthelargestrelativeweighttothecompositionalcomponent(ie15-cmbinsize)
226emsp|emspSets of explanatory variables environmental and spatial variables
Following Legendre etal (2009)we used altitude convexity andslope to construct third-degreepolynomial functions (ie yieldingninevariables)Themonomialswithexponentsallowthemodelingof nonlinear relationships between the topographic variables andthe response variablesWe calculated the aspect of a quadrat astheaverageangleofthefourtriangularplanesthatdeviatefromthenorthdirectionWe thusused the sin (aspect) and cos (aspect) inorder to include it in a linear regressionmodelWe thereforeob-tained11expandedtopographicvariablesWethencombinedthese11 expanded topographic variables with the eight soil variables(described insection21Studysitesanddatacollection) toobtainthe environmental variables data table (ie 19 variables) for eachquadratWe computed eigenfunctions of distance-basedMoranrsquoseigenvector maps (dbMEM also called Principal Coordinates ofNeighbour Matrices PCNM Borcard Legendre Avois-Jacquet amp
(1)SS(Y) =1
n
nminus1sum
h=1
nsum
i=h+1
D2hi
(2)BD = SS(Y)∕(nminus1)
(3)G =
(
Iminus11
n
)
A
(
Iminus11
n
)
(4)(LCBDi) = (SSi)∕SS(Y) = diag(G)∕SS(Y)
emspensp emsp | emsp261Journal of Vegetation Science
YAO et Al
Tuomisto2004LegendreampLegendre2012Legendreetal2009)acrossthe3000(10mtimes10m)750(20mtimes20m)and120(50mtimes50m)quadratsThedbMEMeigenfunctionswithpositiveeigenval-uesonlywereusedasspatialvariablesWeappliedforwardmodelselection(withpermutationtestsatthe5significanceleveloftheincrease in R2 ateachstep) toextract thesignificantenvironmentvariablesandeigenfunctionsofdbMEMusingthefunctionldquoforwardselrdquointhepackageadespatial(Drayetal2018)
227emsp|emspVariation partitioning of DCOMP DSTR and DCOMPndashSTR
Tocompare the influenceofniche-basedandspatialprocessesoncommunityassembly representedbycommunitycompositionsizestructure or the two components together distance-based re-dundancyanalysis (dbRDALegendreampAnderson1999Legendreamp Legendre 2012)was used to partition the variation of each ofthree community matrices (Borcard Legendre amp Drapeau 1992Legendre etal 2009 Peres-Neto Legendre Dray amp Borcard2006) Specificallyweused the two setsof explanatoryvariables(after forwardmodelselection) topartitionvariation in theprinci-palcoordinatetablesextractedfromDCOMPDSTRDCOMPndashSTRsepa-rately into fractions explained by the four different components(a)purehabitat (b)spatiallystructuredhabitat (c)purespaceand(d)undetermined (BorcardampLegendre1994Borcardetal1992DeCaacuteceresetal 2012Legendreetal 2009Myersetal 2013Punchi-Manage etal 2014) We hypothesized that the niche
processesareresponsiblefortheproportionofvariationexplainedbythepurehabitatandthespatially-structuredhabitatcomponents(a+b)(LaliberteacutePaquetteLegendreampBouchard2009Legendreetal2009)Whilewehypothesizedthattheproportionofvariationexplainedbythepurespatialcomponent(c)isrelatedtoindepend-ent biological processes (eg dispersal limitation competition fa-cilitationhistoricaleventsandJanzenndashConnelleffects)(LegendreampLegendre2012Legendreetal2009Punchi-Manageetal2014)Theundeterminedproportionofvariation(d)mayberelatedtosto-chastic processes or undefined non-spatially-structured biologicalor environmental variables (Dumbrell Nelson Helgason DythamampFitter2010)Thatallowedustoassesstherelativecontributionsoftheenvironmentalandspatialvariablestocommunityassemblyin termsof composition structureor taking the twocomponentstogetherAllanalyseswereperformedusingR(RCoreTeam2017)
3emsp |emspRESULTS
31emsp|emspPairwise dissimilarity in terms of community composition and structure
Wefound thatdissimilaritymatricescomputed fromspeciescom-position(DCOMP)sizestructure(DSTR)andconsideringbothcompo-nentstogether(DCOMPndashSTR)werecorrelatedHoweverthestrengthof the correlationdependedon the sizeofbinsused todiscretizethestructuralvariableandonthesizeof thequadrats (Figure1andashc) Overall the correlation between DCOMP vs DCOMPndashSTR was
F IGURE 1emspThecorrelationsbetweenthepairwisedissimilarityintermsofspeciescomposition(DCOMP)sizestructure(DSTR)andbothcomponentstogether(DCOMPndashSTR)ThecorrelationsofDCOMP vs DSTRDCOMP vs DCOMPndashSTRand DSTR vs DCOMPndashSTRvarywithdbhbinsatthescaleof(a)10mtimes10m(b)20mtimes20mand(c)50mtimes50mIngraphs(a)(b)and(c)thehorizontalreddottedlineshorizontalbluelong-dashlinesandhorizontalgreensolidlinesrepresentthemeanvaluesofRVcoefficientsof1ndash15cmdbhbinsofDCOMP vs DSTRDCOMP vs DCOMPndashSTRandDSTR vs DCOMPndashSTRrespectively(d)BoxplotsforRVcoefficientsofthethreepairwisedissimilaritycomparisons(aggregatedoverall1ndash15cmdbhbinsizes)foreachofthethreequadratsizes[Colourfigurecanbeviewedatwileyonlinelibrarycom]
262emsp |emsp emspenspJournal of Vegetation Science
YAO et Al
substantially stronger than that ofDCOMP vs DSTR andofDSTR vs DCOMPndashSTR
The correlation ofDCOMP vs DCOMPndashSTR increasedwith the in-crease of bin size Correspondingly the correlations of DSTR vs DCOMPndashSTR showed the opposite trend (Figure1andashc) As to the ef-fectofthesizeofthesamplingunitsthestrengthofcorrelationsin-creasedwiththequadratsize(Figure1d)exceptforthecorrelationbetweenDCOMP and DCOMPndashSTRwhichexhibitsnosignificantdiffer-encebetweenthe10mtimes10mand20mtimes20mquadrats(p = 023Figure1d)
32emsp|emspThe three components of beta diversity (BD) BDCOMP BDSTR and BDCOMPndashSTR
Thebetadiversity(BD)valueswerecloselyrelatedtowhetherthespecies composition size structure or both components togetherhad been taken into account Among these three components ofbetadiversityBDCOMPndashSTRwasgreatestcloselyfollowedbyBDCOMPandthesmallestwasBDSTR(Figure2)Sincethesizestructureofin-dividualswasnot consideredwhen calculatingBDCOMP this indexwasnotaffectedbythesizeofdbhbins(Figure2andashc)ThevaluesofBDCOMPndashSTRandBDSTRhoweverdecreasedslightlywithanincreaseofbinsizeWhenincreasingdbhbinsizethevaluesofBDCOMPndashSTR graduallyapproachedthevaluesofBDCOMP (Figure2andashc)BDalso
varied as a function of quadrat size (Figure2) values of BDCOMPBDSTRandBDCOMPndashSTR(afteraveragingacrossbinsizes)systemati-callydecreasedwithincreasingquadratsize(Figure2d)
33emsp|emspLocal contributions to beta diversity in terms of community composition and structure
LocalContributionstoBetaDiversitycalculatedusingspeciescom-positionsizestructureorbothcomponentswerecorrelatedAgainthe strengthof correlationsdependedon the sizeofdbhbins andon the size of quadrats (Figure3andashc) In the case of LCBDCOMP vs LCBDCOMPndashSTR the strength of the correlation increased with anincreaseofbinsizeCorrespondinglythecorrelationofLCBDSTR vs LCBDCOMPndashSTRshowedtheoppositetrend(Figure3andashc)Thecorrela-tionsofLCBDCOMPvsLCBDSTRandLCBDSTRvsLCBDCOMPndashSTR were significantly different for differentquadrat sizesA striking findingwasthatthestrengthofcorrelationswasweakeratthescaleof20mtimes20m than that at the scalesof10mtimes10mor50mtimes50m(Figure3d)HowevercorrelationsbetweenLCBDCOMPvsLCBDCOMPndashSTRwerenotsubstantiallyaffectedbythesizeofquadrats(Figure3d)
TheLCBDivaluesindicatetheithquadratsthatcontributemoreorlessthanthemeantobetadiversity(inotherwordstheithquad-ratswithhighorlowuniquenessofspeciesassemblages)TheresultsindicatedthatthesiteswithhighLCBDvalues(contributemorethan
F IGURE 2emspTheBetaDiversity(BD)intermsofspeciescomposition(BDCOMP)sizestructure(BDSTR)andbothcomponentstogether(BDCOMPndashSTR)ThevaluesofBDCOMPndashSTRandBDSTRvarywiththesizeofbinsofthestructuralvariable(dbhbinsizes=1ndash15cm)atthescaleof(a)10mtimes10m(b)20mtimes20mand(c)50mtimes50mThesizestructureofindividuals(iethedbh)isnotconsideredwhencalculatingtheBDCOMPthusthevaluesofBDCOMPwerenotaffectedbythebinsizeIngraphs(a)(b)and(c)thehorizontalbluelong-dashlinesandhorizontalgreensolidlinesrepresentthemeanvaluesofBDCOMPndashSTRandBDSTRacross1ndash15cmbinsizesrespectively(d)ValuesofBDCOMPBDSTRandBDCOMPndashSTR(afteraveragingacrossdbhbinsizes)varywiththesamplingunitsizes[Colourfigurecanbeviewedatwileyonlinelibrarycom]
emspensp emsp | emsp263Journal of Vegetation Science
YAO et Al
themeantobetadiversity)arevariedamongthreecomponentsofacommunity (Figure4)Specifically342(456)290(387)and331 (441)outof750quadratscontributedmorethanthemeanto beta diversity in term of species composition (ie LCBDCOMPFigure4a)sizestructure(ieLCBDSTRFigure4g)andbothcompo-nentstogether(ieLCBDCOMPndashSTRFigure4f)respectively
34emsp|emspVariation partitioning of matrices DCOMP DSTR and DCOMPndashSTR
Theexplanatorypoweroftheenvironmentalvariablesandthespa-tialvariablesvariedforthethreetypesofmatricesandwithquadratsizes (Table 1) The variation explained by the environmental vari-ables(a+b)andbythespatialvariables(b+c)increasedsystemati-callywith increasingscale (Table1)Averagingacrossquadratsizeshabitatandspacejointlyexplained438254and341ofthevariation in compositional component structural component andthe two components together of community assemblage respec-tivelyHoweverthecontributionofthepurehabitatcomponent (a)was negligible The combination of environmental and spatial vari-ablesexplained the lowestproportionofvariation in the structuralcomponentaloneandexplainedthehighestproportionofvariationinthecompositionalcomponentalone(Table1)Boththeenvironmen-talvariables(a+b)andthepurespatialvariables(c)explainedmore
variationinthecompositionalcomponentthanthatinthestructuralcomponentsofcommunityassemblageAdditionallyourfindingsin-dicatethattheunexplained(d)fractionsdominatedthevariancepar-titioningcomputedforthestructuralcomponentYstralone(Table1)
4emsp |emspDISCUSSION
Forest ecosystems can be characterized and evaluated in terms ofboththeirstructureandcomposition(Peet1992)Inpreviousstud-ies the compositional and structural components of a communityassemblagewereusuallyanalyzedseparately(egFangetal2012)Howeverthenatureofspeciesassemblagesindicatesthateitherspe-cies composition or size structure of constituent individuals alonemayoversimplifycommunityorganization (DeCaacuteceresetal2013)Changes in structure and compositionmay be onlyweakly related(egArsenaultampBradfield1995)thereforeassessmentofbothsi-multaneouslyisimportantwhenevaluatingcommunityassemblyInthepresentstudywegeneralizedtheconventionalapproachtocom-munityassemblagebyincorporatingstructuraldataofacommunityinadditiontocompositionaldatausingtheCAPframeworkToourknowledge this is the firstpaper that investigates inasinglestudythevariationinboththecompositionalandstructuralcomponentsofcommunityassemblagessimultaneouslyaswellasitsdeterminants
F IGURE 3emspThecorrelationsbetweentheLocalContributionstoBetaDiversity(LCBD)intermsofcommunitycomposition(LCBDCOMP)structure(LCBDSTR)andbothcomponentstogether(LCBDCOMPndashSTR)ThecorrelationsofLCBDCOMPvsLCBDSTRLCBDCOMP vsLCBDCOMPndashSTRandLCBDSTR vs LCBDCOMPndashSTRwiththesizeofbinsofthestructuralvariable(binsizes=1ndash15cm)atthescaleof(a)10mtimes10m(b)20mtimes20mand(c)50mtimes50mIngraphs(a)(b)and(c)thehorizontalreddottedlineshorizontalbluelong-dashlinesandhorizontalgreensolidlinesrepresentthemeanvaluesofSpearmanrsquosrankcorrelationcoefficientr across 1ndash15 cm binsizeofLCBDCOMPvsLCBDSTRLCBDCOMPvsLCBDCOMPndashSTRLCBDSTR vs LCBDCOMPndashSTRrespectively(d)BoxplotsfortheSpearmanrsquosrankcorrelationcoefficientrbetweenthepairwiseofthethreekindsofLCBDof1ndash15cmbinsizesatdifferentquadratsizes[Colourfigurecanbeviewedatwileyonlinelibrarycom]
264emsp |emsp emspenspJournal of Vegetation Science
YAO et Al
We found thatbothoverall betadiversity (BD) and the rela-tive contribution of sampling units to beta diversity (LCBD) de-pended on whether the species composition size structure orbothcomponentstogetherhadbeentakenintoaccountBetadi-versity partitioning indicated that the explanatory power of the
environmental and the spatial variables also varied widely withdifferentcomponentsofacommunityOur resultshighlight thatconsideringboth species compositional and size structural com-ponentsmaybeamorecomprehensivewaytodescribethecom-munityorganization
emspensp emsp | emsp265Journal of Vegetation Science
YAO et Al
41emsp|emspStructural and compositional components of forest variation
The framework of CAP allowed us to incorporate the distribu-tionof individualtreesize intotheanalysisofcommunityassem-blage thusmaking it possible toquantify the spatial variationofcommunitystructurebetadiversityEvensosuchstructuralbetadiversitycanbequantified independentlyor incombinationwithspecies composition TheBDCOMPndashSTR is the largest among thesethreecomponentsofbetadiversity indicating thatapplyingspe-ciescompositionaloneorsizestructurealonetoassessthebetadi-versitymayunderestimatethevariationofassemblages(Figure2)ThevaluesofBDCOMPareclosertotheBDCOMPndashSTRvaluesthanthatofBDSTR(theBDSTRvaluesarerelativelysmallFigure2)ThusasfarasourCAPframework isconcerned it seemsmoreappropri-atetoquantifybetadiversityusingthespeciescomposition indi-viduallythanusingthesizestructureindividuallyNeverthelessifstructureprovidesindependentinformationandisdeemedimpor-tantoneshouldincorporateitinBDassessmentAsbetadiversityindiceswerecalculatedfromdissimilaritymatrices thestructuralcomponent of beta diversity depended on the weight given to
structural vs compositional informationwhencalculatingdissimi-larity(Figure2andashc)Thelargerthebinsizes(iethesmallerweightgiventospeciesstructuralinformation)thecloserBDCOMPndashSTR val-uesapproachedthevaluesofBDCOMP(Figure2andashc)Ifthebinsizesare big enough theBDCOMPndashSTR value and theBDCOMP value are expected to converge at a certain size of dbh binNeverthelessconsideringthenecessityofcomprehensiveassessmentofbetadi-versityweadvocateforsmallbinsizesastheyprovidemoreinde-pendentstructuralinformationFinallyitisimportanttonotethatthisforestplotincludes47differenttreespecieswhichresultsinastrongrelativeweightofthecompositionalcomponentofBDCOMPndashSTRwhenusingtheCAPframeworkRepeatingourstudyinforestswith lower species richness or in this forest but using a coarsercompositional resolution (eg at the family level)would result inlargerrelativeweightofthestructuralcomponent
42emsp|emspLocal contributions to beta diversity in terms of community composition and structure
EcologicallyLCBDindicesonlyrepresentthedegreeofuniquenessofthesamplingunitsintermsofcommunitycomposition(Legendre
F IGURE 4emspMapsof30-ha(500mtimes600m)plotshowingthelocalcontributionstobetadiversity(LCBD)intermsofcommunitycompositionandstructurefor750quadrats(20mtimes20m)ThesolidcirclesrepresentthevaluesofLCBDiforeachithquadrat(i =[1750])(a)ThemapofLCBDsonlyintermsofspeciescompositionNotethatthesizestructureofindividuals(iedbh)isnotconsideredwhencalculatingtheLCBDCOMPthusthevaluesofLCBDCOMPwerenotaffectedbythesizeofthebinsofthestructuralvariable(b)ndash(e)ThetwoextremecasesoftheLCBDmap(b)and(c)givingthemostweighttothestructuralcomponentandcorrespondinglytheleastweighttothecompositionalcomponent(ie1-cmbinsize)and(d)and(e)givingthemostweighttothecompositionalcomponentandcorrespondinglytheleastweighttothestructuralcomponent(ie15-cmbinsize)(f)and(g)MapsofLCBDsafteraveragingacrossdbhbinsizesSizeofthecirclesisproportionaltotheLCBDivaluesTheblackandgreysolidcirclesrepresentthesiteswithLCBDvalueshigherandlowerthanthemeanrespectively
TABLE 1emspVariationpartitioningresultsforthreetypesofmatricesatdifferentscalesofquadratsThepartitioningisbasedonadjustedR2 statisticsasrecommendedbyPeres-Netoetal(2006)
Quadrat sizes (a) (b) (c) (d) (a + b) (b + c) (a + b + c)
YCOMP
10mtimes10m 00044 00796 01361 07799 00840 02157 02201
20mtimes20m 00028 01783 02862 05327 01811 04645 04673
50mtimes50m 00050 02995 03229 03726 03045 06224 06274
YSTR
10mtimes10m 00123 00131 00296 09450 00254 00427 00550
20mtimes20m 00013 00907 01652 07428 00920 02560 02572
50mtimes50m 00029 02300 02163 05509 02328 04463 04492
YCOMPndashSTR
10mtimes10m 00055 00564 00932 08449 00619 01496 01551
20mtimes20m 00028 01576 02559 05837 01604 04135 04163
50mtimes50m 00013 02543 01948 05496 02556 04492 04504
Fractions(a)ndash(d)(adjustedR2statistics)(a)variationexplainedbytheenvironmentalvariablesaftercontrollingforthespatialstructure(b)variationexplainedbythespatiallystructuredenvironmentalvariables(c)spatiallystructuredvariationexplainedbypurespaceaftercontrollingforenviron-mentalvariation(d)residualvariationEnvironmentalvariablesusedtocomputefraction(a+b)dbMEMeigenfunctionsweretheexplanatoryvaria-blesusedtocomputefraction(b+c)Only5-cm-diameterclasses(iebinsize=5cm)asthestructuralvariablewereusedtocalculatetheYSTR and YCOMPndashSTR
266emsp |emsp emspenspJournal of Vegetation Science
YAO et Al
amp De Caacuteceres 2013) However natural communities may exhibitsimilarspeciescompositionsbutdifferinotherfeaturessuchasthesizestructureof individuals Inthepresentstudyweassessedthedegreeofuniquenessofthequadratsintermsnotonlyoftheirspe-ciescompositionbutalsooftheirsizestructureandbyusingbothcomponentstogetherThedegreeofuniquenessofquadratsintermsofcommunitycompositionindividuallyhadaveryweakcorrelationwithuniqueness in termsof size structure individually (LCBDCOMP vsLCBDSTRFigure3) indicating that sites that areunique in spe-cies composition are not necessarily unique in size structure andvice versa Additionally we found that the spatial distribution ofsiteswithhighLCBDvaluesisdifferentforthetwocomponentsofacommunitywith siteswithhighstructuraluniquenessoccurringinsmallforestpatches(Figure4)Alltheseresultsreinforcetheideathatconsideringbothspeciescompositionalandsizestructuralcom-ponentsmaybeamorecomprehensivewaytodescribethecommu-nityorganizationHoweverifweacceptthefactthatsitesthatareuniqueintermsofsizestructurearetheresultofgapdynamics(seebelow) the non-zero correlation between LCBDCOMP vs LCBDSTR mayindicatethatforestgapsmaybecolonizedbyspeciesthatmaylaterbesuppressedastheforestgrowssothatrecentforestgapshaveadifferentspeciescompositionthanclosedforeststructures(Comitaetal2009)
43emsp|emspPartitioning the structural and compositional components of beta diversity
About344ofthevariationincommunityassemblagewasdeter-minedbyenvironmentalandspatialvariablesdependingonthescale(quadratsize)andonwhichcomponentsofcommunityassemblage(ie compositional component structural component and takingbothcomponents together)were taken intoaccountThispropor-tion isslightly lowerthanthevaluesfound instudiesbyLegendreetal (2009)andPunchi-Manageetal (2014)Areasonforthisre-sult is thatwe incorporateddifferencesboth insizestructureandspeciescomposition intocommunityassemblagesratherthanonlyusingtheconventionalspeciescompositiondataWhenthespeciescomposition and size structure of the constituent individuals areincorporatedintothecommunityatthesametimemorevariationwilloccurincommunityassemblagesInourstudyhabitat(a+b)ex-plainedmorevariationinthecompositionalcomponent(190)thaninthestructuralcomponent(117)ofthecommunityassemblagesBetadiversitypartitioningindicatedthatthevariationinthestruc-turalcomponentislessdictatedbyenvironmentthanvariationinthecompositional componentWe here hypothesize that canopy gapdynamicswillbethepotentialdriversofstructuralvariationWinterinourstudyareaiscoldandlongwithalongsnowfallperiodThesnowfallperiodlastsforhalfayearandthesnowcoverthicknessinmountainousareasreaches40ndash50cmWehypothesizethatpulsesofmoderate-severity disturbancesmay be caused by snowstormsin our site In the absence of stand-replacing disturbances forestcanopiesareopenedperiodicallybythedeathofsinglebigtreesorsmallgroupsofadulttreescreatingcanopygapsSnowstormsmay
havealteredforeststructurebyselectivelyremovinglargercanopytrees Environmental selection of individuals shapes compositionbydeterminingthefitnessof individualswhereasstructuralvaria-tionmayhavesomerelationshipwithenvironmentalconditions(ielargertreesinsiteswherelargersizesaresupportedforenergyorwateravailability)butingeneralisthereflectionofdifferentstagesaroundgapdynamicsPreviousstudiesareconsistentwithourfind-ingsFraverandWhite(2005)forinstancefoundthattherepeatedmoderate-severity disturbances (iewindstorms) causeddramaticstructural changes they caused no significant change in speciescomposition
Becausetherelativeimportanceofbothnicheandneutralthe-oryinstructuringcommunitiesvarieswithspatialscale(Legendreetal 2009 Punchi-Manage etal 2014) we conducted scale-dependentanalyses InsharpcontrasttothefindingbyLegendreetal(2009)forabroad-leavedforestinChinawefoundthattheproportionofundeterminedvariation incompositionalandstruc-turalcomponentsofcommunityassemblageswasveryhighatfinespatialscales(upto945forthestructuralcomponent780forthecompositionalcomponentand844forbothcomponentsto-gether)butdecreasedsystematicallywith increasingspatial scale(up to a minimum of 373 for compositional component at the50-mscale)TheseresultsareinlinewiththefindingsbyPunchi-Manageetal(2014)inaSriLankandipterocarpforestandbyDeCaacuteceresetal(2012)inacomparisonofseveralforestsOntheonehandthehighproportionofunexplainedvariationmayberelatedtounmeasuredandnotspatially-structuredbiologicalorenviron-mentalvariablesXuetal(2016)showedthatthesoilnutrientsintheupper(0ndash10cmconsideredinourstudy)andlowersoillayers(10ndash20cm)andtheheavymetalelements(CuNiCdAsPbZnMoCrMnandMg)inthesoilshowastrongcorrelationwiththespeciesspatialdistributionsatJiaoheThismaypartlyexplainwhythepureenvironmentalvariable(a)explainedsuchlittlevariationinthecommunityassemblagesAnotherexplanationforthehighpro-portionofunexplainedvariationisthatitmaybeduetostochasticprocesseswhich related to theneutral theoryassuming that thedynamicsofpopulationsareprimarilydrivenbyecologicaldriftanddispersal(Legendreetal2009)Ontheotherhandtheproportionofundeterminedvariationincompositionalandstructuralcompo-nents of community assemblages decreased systematically withincreasingspatialscaleThismayindicatethatcommunityassem-blageishighlystochasticintermsofspeciescompositionandtreesizedistributionatfinescales (ie10-mscale)butthisfinescalestochasticitytendstosmoothoutatthe50-mscalewheremoreconsistent habitat-driven species assemblages emerged Whenvariance partitioning is conducted on the structural componentalonetheunexplained(d)fractionisdominantWhiletheinfluenceofenvironmental factorsonsizestructuremaybe less importantthan for thecompositionalcomponent theeffectof localdistur-bances (eg appearanceof canopygaps resulting frommortalityof largetrees)results inrandomspatialpatternsofquadratswithrather different structure contributing to a large unexplainedfraction
emspensp emsp | emsp267Journal of Vegetation Science
YAO et Al
5emsp |emspCONCLUSIONS
SpeciescompositionandsizestructurearethetwoessentialfeaturesofacommunityOnlyoneofthemindividuallymaybeinsufficienttodescribetheorganizationoftreespeciesassemblagesDefiningandquantifyingbetadiversityusingthespeciescompositionalonemaybesufficienttheninmanyoccasionsNeverthelessspeciescompo-sition is justonedimensionofbiodiversity variation in size struc-tureisalsoimportantIncorporatingstructuraldatainbetadiversityassessmentsallowsecologiststomakeuseofvaluableinformationcollectedduringfieldsurveysIfitisavailablethereisnoreasontoignorethewealthofinformationaboutsizestructurewhencompar-ingspeciesassemblagesOurstudyhighlightstheneedtoincorpo-ratethestructuraldataofacommunityinadditiontocompositionaldatawhenquantifyingandanalyzingbetadiversityFinallyourre-sults suggest thatbothdeterministicandstochasticprocessesarerelevantdeterminantsofcompositionalandstructuralcomponentsof communityassemblages inour temperate forestNeverthelesstheseprocessesarescale-andorresolution-dependent
ACKNOWLEDGEMENTS
WewouldliketothankHeHuaijiangDingShengjianNiRuiqiangandZuoQiangandseveralothersforassistingwiththefielddatacollectionAuthorsaregratefultotheJiaoheManagementBureauof the Forest Experimental Zone for permission to undertake thefieldworkWealsothankthreeanonymousreviewersforprovidingthevaluablecomments
CONFLICTS OF INTEREST
Theauthorsdeclarenocompetingfinancialinterests
DATA ACCESSIBILITY
DataownershipbelongstoBeijingForestryUniversitywhosestaffconductedtheanalysesandwrotethemanuscripthttpwwwbjfueducn
ORCID
Jie Yao httpsorcidorg0000-0002-8606-8158
REFERENCES
Anderson M J Crist T O Chase J M Vellend M InouyeB D Freestone A L hellip Swenson N G (2011) Navigatingthe multiple meanings of β diversity a roadmap for the prac-ticing ecologist Ecology Letters 14 19ndash28 httpsdoiorg101111j1461-0248201001552x
ArsenaultAampBradfieldGE (1995)Structuralndashcompositionalvaria-tioninthreeage-classesoftemperaterainforestsinsoutherncoastalBritishColumbiaCanadian Journal of Botany7354ndash64httpsdoiorg101139b95-007
Borcard D amp Legendre P (1994) Environmental control and spatialstructureinecologicalcommunitiesanexampleusingoribatidmites(Acari Oribatei) Environmental and Ecological Statistics 1 37ndash61httpsdoiorg101007BF00714196
Borcard D Legendre P Avois-Jacquet C amp Tuomisto H (2004)DissectingthespatialstructureofecologicaldataatmultiplescalesEcology851826ndash1832httpsdoiorg10189003-3111
BorcardDLegendrePampDrapeauP(1992)PartiallingoutthespatialcomponentofecologicalvariationEcology731045ndash1055httpsdoiorg1023071940179
Caswell H (1976) Community structure a neutral model anal-ysis Ecological Monographs 46 327ndash354 httpsdoiorg1023071942257
ChaseJM(2010)Stochasticcommunityassemblycauseshigherbiodi-versityinmoreproductiveenvironmentsScience3281388ndash1391httpsdoiorg101126science1187820
ChaveJ(2004)NeutraltheoryandcommunityecologyEcology Letters7241ndash253httpsdoiorg101111j1461-0248200300566x
Chesson P (2000) Mechanisms of maintenance of species diversityAnnual Review of Ecology and Systematics31343ndash366httpsdoiorg101146annurevecolsys311343
ComitaLSUriarteMThompsonJJonckheereICanhamCDampZimmermanJK(2009)Abioticandbioticdriversofseedlingsur-vival inahurricane-impacted tropical forestJournal of Ecology971346ndash1359httpsdoiorg101111j1365-2745200901551x
DeCaacuteceresMFontXampOlivaF(2010)Themanagementofvegeta-tionclassificationswithfuzzyclusteringJournal of Vegetation Science211138ndash1151httpsdoiorg101111j1654-1103201001211x
De Caacuteceres M Legendre P amp He F (2013) Dissimilarity mea-surements and the size structure of ecological communitiesMethods in Ecology and Evolution 4 1167ndash1177 httpsdoiorg1011112041-210X12116
De Caacuteceres M Legendre P Valencia R Cao M Chang L-W Chuyong G hellip He F (2012) The variation of tree betadiversity across a global network of forest plots Global Ecology and Biogeography 21 1191ndash1202 httpsdoiorg101111j1466-8238201200770x
DraySBaumanDBlanchetGBorcardDClappeSGuenardGhellipWagnerHH(2018)adespatial Multivariate multiscale spatial analy-sis R package version 03-2RetrievedfromhttpsCRANR-projectorgpackage=adespatial
Dumbrell A J NelsonM Helgason T Dytham C amp Fitter A H(2010)Relativerolesofnicheandneutralprocesses instructuringa soil microbial community ISME Journal 4 337ndash345 httpsdoiorg101038ismej2009122
FaithDAustinMBelbinLampMargulesC (1985)Numericalclas-sification of profile attributes in environmental studies Journal of Environmental Management2073ndash85
Fang J Shen Z Tang ZWang XWang Z Feng J hellip Zheng C(2012) Forest community survey and the structural character-istics of forests in China Ecography 35 1059ndash1071 httpsdoiorg101111j1600-0587201300161x
FraverSampWhiteAS(2005)Disturbancedynamicsofold-growthPicea rubens forests of northern Maine Journal of Vegetation Science 16 597ndash610 httpsdoiorg101111j1654-11032005tb02401x
Gower J C (1966) Some distance properties of latent root and vec-tormethodsusedinmultivariateanalysisBiometrika53325ndash338httpsdoiorg101093biomet533-4325
Harms K E Condit R Hubbell S P amp Foster R B (2001)Habitat associations of trees and shrubs in a 50-ha neotrop-ical forest plot Journal of Ecology 89 947ndash959 httpsdoiorg101111j1365-2745200100615x
HilleRisLambers J Adler P B Harpole W S Levine J M ampMayfield M M (2012) Rethinking community assembly
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YAO et Al
through the lens of coexistence theory Annual Review of Ecology Evolution and Systematics 43 227ndash249 httpsdoiorg101146annurev-ecolsys-110411-160411
HubbellSP(Ed)(2001)The unified theory of biodiversity and biogeogra-phyPrincetonNJPrincetonUniversityPress
Hubbell S P (2006) Neutral theory and the evolution of eco-logical equivalence Ecology 87 1387ndash1398 httpsdoiorg1018900012-9658(2006)87[1387NTATEO]20CO2
HussonFJosseJLeSampMazetJ(2015)FactoMineR Multivariate exploratory data analysis and data mining Version 1314 RetrievedfromhttpsCRANR-projectorgpackage=FactoMineR
Hutchinson G E (1961) The paradox of the plankton American Naturalist95137ndash145httpsdoiorg101086282171
KeddyPA(1992)Assemblyandresponserulestwogoalsforpredic-tive community ecology Journal of Vegetation Science3 157ndash164httpsdoiorg1023073235676
KoleffPGastonKJampLennonJJ(2003)MeasuringbetadiversityforpresencendashabsencedataJournal of Animal Ecology72367ndash382httpsdoiorg101046j1365-2656200300710x
KraftN JBComita L SChase JM SandersN J SwensonNGCrist TOhellipMyers JA (2011)Disentangling thedriversofβdiversityalong latitudinalandelevationalgradientsScience3331755ndash1758httpsdoiorg101126science1208584
LaliberteacuteEPaquetteALegendrePampBouchardA(2009)Assessingthescale-specificimportanceofnichesandotherspatialprocessesonbetadiversityacasestudyfromatemperateforestOecologia159377ndash388httpsdoiorg101007s00442-008-1214-8
Legendre P amp Anderson M J (1999) Distance-based redundancyanalysis testing multispecies responses in multifactorial ecolog-ical experiments Ecological Monographs 69 1ndash24 httpsdoiorg1018900012-9615(1999)069[0001DBRATM]20CO2
Legendre P Borcard D amp Peres-Neto P R (2005) Analyzing betadiversity partitioning the spatial variation of community com-position data Ecological Monographs 75 435ndash450 httpsdoiorg10189005-0549
LegendrePampDeCaacuteceresM(2013)BetadiversityasthevarianceofcommunitydatadissimilaritycoefficientsandpartitioningEcology Letters16951ndash963httpsdoiorg101111ele12141
LegendrePampLegendreL (2012)Numerical ecology Vol 24 (3rded)AmsterdamTheNetherlandsElsevierScienceBV
LegendrePMiXRenHMaKYuMSun I-FampHeF (2009)Partitioning beta diversity in a subtropical broad-leaved forest ofChina Ecology90663ndash674httpsdoiorg10189007-18801
MayfieldMMampLevineJM(2010)Opposingeffectsofcompetitiveex-clusiononthephylogeneticstructureofcommunitiesEcology Letters131085ndash1093httpsdoiorg101111j1461-0248201001509x
MyersJAChaseJMJimeacutenezIJoslashrgensenPMAraujo-MurakamiAPaniagua-ZambranaNampSeidelR(2013)Beta-diversityintem-perateandtropicalforestsreflectsdissimilarmechanismsofcommu-nityassemblyEcology Letters16151ndash157httpsdoiorg101111ele12021
OksanenJBlanchetFGFriendlyMKindtRLegendrePMcGlinnDhellipWagnerH(2018)vegan Community ecology package Version 25-2Retrievedfromhttpscranr-projectorgpackage=vegan
Paradis EClaude JampStrimmerK (2004)APEAnalysesof phylo-genetics and evolution inR languageBioinformatics20 289ndash290httpsdoiorg101093bioinformaticsbtg412
PeetRK (1992)Community structureand function InDCGlenn-LewinRKPeetampTTVeblen(Eds)Plant succession theory and prediction(pp103ndash140)NewYorkNYChapmanampHall
Peres-NetoPRLegendrePDraySampBorcardD(2006)Variationpartitioningofspeciesdatamatricesestimationandcomparisonof
fractionsEcology872614ndash2625httpsdoiorg1018900012-9658(2006)87[2614VPOSDM]20CO2
Punchi-Manage R Wiegand T Wiegand K Getzin S SavitriGunatillekeCV ampNimalGunatilleke IAUN(2014)EffectofspatialprocessesandtopographyonstructuringspeciesassemblagesinaSriLankandipterocarpforestEcology95376ndash386httpsdoiorg10189012-21021
RCoreTeam (2017)R A language and environment for statistical com-puting Vienna Austria R Foundation for Statistical ComputingRetrievedfromhttpswwwR-projectorg
Ricklefs R E (1990) Seabird life histories and the marine environ-mentsomespeculationsColonial Waterbirds13(1)1ndash6httpsdoiorg1023071521414
SchwinningSampWeinerJ(1998)MechanismsdeterminingthedegreeofsizeasymmetryincompetitionamongplantsOecologia113447ndash455httpsdoiorg101007s004420050397
SoilScienceSocietyofChina(Ed)(1999)Soil agricultural chemical analy-sis procedureBeijingChinaChineseAgriculturalSciencePress
van der Plas F Janzen T Ordonez A FokkemaW Reinders JEtienneRSampOlffH(2015)Anewmodelingapproachestimatesthe relative importance of different community assembly pro-cesses Ecology961502ndash1515httpsdoiorg10189014-04541
VellendM(Ed)(2017)The theory of ecological communitiesPrincetonNJPrincetonUniversityPresshttpsdoiorg1015159781400883790
Weiner J (1990) Asymmetric competition in plant popula-tions Trends in Ecology and Evolution 5 360ndash364 httpsdoiorg1010160169-5347(90)90095-U
WhittakerRH (1960)VegetationoftheSiskiyoumountainsOregonand California Ecological Monographs 30 279ndash338 httpsdoiorg1023071943563
WhittakerRH(1972)EvolutionandmeasurementofspeciesdiversityTaxon21213ndash251httpsdoiorg1023071218190
XuWHaoMWangJZhangCZhaoXampvonGadowK(2016)Soilelementsinfluencingcommunitystructureinanold-growthfor-est innortheasternChinaForests7159httpsdoiorg103390f7080159
YamakuraTKanzakiMItohAOhkuboTOginoKChaiEOKhellipAshtonPS(1995)Topographyofalarge-scaleresearchplotes-tablishedwithinatropicalrainforestatLambirSarawakTropics541ndash56httpsdoiorg103759tropics541
YanYZhangCWangYZhaoXampvonGadowK(2015)Driversofseedlingsurvivalinatemperateforestandtheirrelativeimportanceat threestagesofsuccessionEcology and Evolution54287ndash4299httpsdoiorg101002ece31688
YaoJZhangXZhangCZhaoXampvonGadowK(2016)EffectsofdensitydependenceinatemperateforestinnortheasternChinaScientific Reports632844httpsdoiorg101038srep32844
ZhangCZhaoXampvonGadowK(2014)Analyzingselectiveharvestevents inthree largeforestobservationalstudies inNorthEasternChina Forest Ecology and Management 316 100ndash109 httpsdoiorg101016jforeco201307018
ZhangCZhaoYZhaoXampvonGadowK (2012)Species-habitatassociations inanorthern temperate forest inChinaSilva Fennica46501ndash519
How to cite this articleYaoJZhangCDeCaacuteceresMLegendrePZhaoXVariationincompositionalandstructuralcomponentsofcommunityassemblageanditsdeterminantsJ Veg Sci 201930257ndash268 httpsdoiorg101111jvs12708
emspensp emsp | emsp261Journal of Vegetation Science
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Tuomisto2004LegendreampLegendre2012Legendreetal2009)acrossthe3000(10mtimes10m)750(20mtimes20m)and120(50mtimes50m)quadratsThedbMEMeigenfunctionswithpositiveeigenval-uesonlywereusedasspatialvariablesWeappliedforwardmodelselection(withpermutationtestsatthe5significanceleveloftheincrease in R2 ateachstep) toextract thesignificantenvironmentvariablesandeigenfunctionsofdbMEMusingthefunctionldquoforwardselrdquointhepackageadespatial(Drayetal2018)
227emsp|emspVariation partitioning of DCOMP DSTR and DCOMPndashSTR
Tocompare the influenceofniche-basedandspatialprocessesoncommunityassembly representedbycommunitycompositionsizestructure or the two components together distance-based re-dundancyanalysis (dbRDALegendreampAnderson1999Legendreamp Legendre 2012)was used to partition the variation of each ofthree community matrices (Borcard Legendre amp Drapeau 1992Legendre etal 2009 Peres-Neto Legendre Dray amp Borcard2006) Specificallyweused the two setsof explanatoryvariables(after forwardmodelselection) topartitionvariation in theprinci-palcoordinatetablesextractedfromDCOMPDSTRDCOMPndashSTRsepa-rately into fractions explained by the four different components(a)purehabitat (b)spatiallystructuredhabitat (c)purespaceand(d)undetermined (BorcardampLegendre1994Borcardetal1992DeCaacuteceresetal 2012Legendreetal 2009Myersetal 2013Punchi-Manage etal 2014) We hypothesized that the niche
processesareresponsiblefortheproportionofvariationexplainedbythepurehabitatandthespatially-structuredhabitatcomponents(a+b)(LaliberteacutePaquetteLegendreampBouchard2009Legendreetal2009)Whilewehypothesizedthattheproportionofvariationexplainedbythepurespatialcomponent(c)isrelatedtoindepend-ent biological processes (eg dispersal limitation competition fa-cilitationhistoricaleventsandJanzenndashConnelleffects)(LegendreampLegendre2012Legendreetal2009Punchi-Manageetal2014)Theundeterminedproportionofvariation(d)mayberelatedtosto-chastic processes or undefined non-spatially-structured biologicalor environmental variables (Dumbrell Nelson Helgason DythamampFitter2010)Thatallowedustoassesstherelativecontributionsoftheenvironmentalandspatialvariablestocommunityassemblyin termsof composition structureor taking the twocomponentstogetherAllanalyseswereperformedusingR(RCoreTeam2017)
3emsp |emspRESULTS
31emsp|emspPairwise dissimilarity in terms of community composition and structure
Wefound thatdissimilaritymatricescomputed fromspeciescom-position(DCOMP)sizestructure(DSTR)andconsideringbothcompo-nentstogether(DCOMPndashSTR)werecorrelatedHoweverthestrengthof the correlationdependedon the sizeofbinsused todiscretizethestructuralvariableandonthesizeof thequadrats (Figure1andashc) Overall the correlation between DCOMP vs DCOMPndashSTR was
F IGURE 1emspThecorrelationsbetweenthepairwisedissimilarityintermsofspeciescomposition(DCOMP)sizestructure(DSTR)andbothcomponentstogether(DCOMPndashSTR)ThecorrelationsofDCOMP vs DSTRDCOMP vs DCOMPndashSTRand DSTR vs DCOMPndashSTRvarywithdbhbinsatthescaleof(a)10mtimes10m(b)20mtimes20mand(c)50mtimes50mIngraphs(a)(b)and(c)thehorizontalreddottedlineshorizontalbluelong-dashlinesandhorizontalgreensolidlinesrepresentthemeanvaluesofRVcoefficientsof1ndash15cmdbhbinsofDCOMP vs DSTRDCOMP vs DCOMPndashSTRandDSTR vs DCOMPndashSTRrespectively(d)BoxplotsforRVcoefficientsofthethreepairwisedissimilaritycomparisons(aggregatedoverall1ndash15cmdbhbinsizes)foreachofthethreequadratsizes[Colourfigurecanbeviewedatwileyonlinelibrarycom]
262emsp |emsp emspenspJournal of Vegetation Science
YAO et Al
substantially stronger than that ofDCOMP vs DSTR andofDSTR vs DCOMPndashSTR
The correlation ofDCOMP vs DCOMPndashSTR increasedwith the in-crease of bin size Correspondingly the correlations of DSTR vs DCOMPndashSTR showed the opposite trend (Figure1andashc) As to the ef-fectofthesizeofthesamplingunitsthestrengthofcorrelationsin-creasedwiththequadratsize(Figure1d)exceptforthecorrelationbetweenDCOMP and DCOMPndashSTRwhichexhibitsnosignificantdiffer-encebetweenthe10mtimes10mand20mtimes20mquadrats(p = 023Figure1d)
32emsp|emspThe three components of beta diversity (BD) BDCOMP BDSTR and BDCOMPndashSTR
Thebetadiversity(BD)valueswerecloselyrelatedtowhetherthespecies composition size structure or both components togetherhad been taken into account Among these three components ofbetadiversityBDCOMPndashSTRwasgreatestcloselyfollowedbyBDCOMPandthesmallestwasBDSTR(Figure2)Sincethesizestructureofin-dividualswasnot consideredwhen calculatingBDCOMP this indexwasnotaffectedbythesizeofdbhbins(Figure2andashc)ThevaluesofBDCOMPndashSTRandBDSTRhoweverdecreasedslightlywithanincreaseofbinsizeWhenincreasingdbhbinsizethevaluesofBDCOMPndashSTR graduallyapproachedthevaluesofBDCOMP (Figure2andashc)BDalso
varied as a function of quadrat size (Figure2) values of BDCOMPBDSTRandBDCOMPndashSTR(afteraveragingacrossbinsizes)systemati-callydecreasedwithincreasingquadratsize(Figure2d)
33emsp|emspLocal contributions to beta diversity in terms of community composition and structure
LocalContributionstoBetaDiversitycalculatedusingspeciescom-positionsizestructureorbothcomponentswerecorrelatedAgainthe strengthof correlationsdependedon the sizeofdbhbins andon the size of quadrats (Figure3andashc) In the case of LCBDCOMP vs LCBDCOMPndashSTR the strength of the correlation increased with anincreaseofbinsizeCorrespondinglythecorrelationofLCBDSTR vs LCBDCOMPndashSTRshowedtheoppositetrend(Figure3andashc)Thecorrela-tionsofLCBDCOMPvsLCBDSTRandLCBDSTRvsLCBDCOMPndashSTR were significantly different for differentquadrat sizesA striking findingwasthatthestrengthofcorrelationswasweakeratthescaleof20mtimes20m than that at the scalesof10mtimes10mor50mtimes50m(Figure3d)HowevercorrelationsbetweenLCBDCOMPvsLCBDCOMPndashSTRwerenotsubstantiallyaffectedbythesizeofquadrats(Figure3d)
TheLCBDivaluesindicatetheithquadratsthatcontributemoreorlessthanthemeantobetadiversity(inotherwordstheithquad-ratswithhighorlowuniquenessofspeciesassemblages)TheresultsindicatedthatthesiteswithhighLCBDvalues(contributemorethan
F IGURE 2emspTheBetaDiversity(BD)intermsofspeciescomposition(BDCOMP)sizestructure(BDSTR)andbothcomponentstogether(BDCOMPndashSTR)ThevaluesofBDCOMPndashSTRandBDSTRvarywiththesizeofbinsofthestructuralvariable(dbhbinsizes=1ndash15cm)atthescaleof(a)10mtimes10m(b)20mtimes20mand(c)50mtimes50mThesizestructureofindividuals(iethedbh)isnotconsideredwhencalculatingtheBDCOMPthusthevaluesofBDCOMPwerenotaffectedbythebinsizeIngraphs(a)(b)and(c)thehorizontalbluelong-dashlinesandhorizontalgreensolidlinesrepresentthemeanvaluesofBDCOMPndashSTRandBDSTRacross1ndash15cmbinsizesrespectively(d)ValuesofBDCOMPBDSTRandBDCOMPndashSTR(afteraveragingacrossdbhbinsizes)varywiththesamplingunitsizes[Colourfigurecanbeviewedatwileyonlinelibrarycom]
emspensp emsp | emsp263Journal of Vegetation Science
YAO et Al
themeantobetadiversity)arevariedamongthreecomponentsofacommunity (Figure4)Specifically342(456)290(387)and331 (441)outof750quadratscontributedmorethanthemeanto beta diversity in term of species composition (ie LCBDCOMPFigure4a)sizestructure(ieLCBDSTRFigure4g)andbothcompo-nentstogether(ieLCBDCOMPndashSTRFigure4f)respectively
34emsp|emspVariation partitioning of matrices DCOMP DSTR and DCOMPndashSTR
Theexplanatorypoweroftheenvironmentalvariablesandthespa-tialvariablesvariedforthethreetypesofmatricesandwithquadratsizes (Table 1) The variation explained by the environmental vari-ables(a+b)andbythespatialvariables(b+c)increasedsystemati-callywith increasingscale (Table1)Averagingacrossquadratsizeshabitatandspacejointlyexplained438254and341ofthevariation in compositional component structural component andthe two components together of community assemblage respec-tivelyHoweverthecontributionofthepurehabitatcomponent (a)was negligible The combination of environmental and spatial vari-ablesexplained the lowestproportionofvariation in the structuralcomponentaloneandexplainedthehighestproportionofvariationinthecompositionalcomponentalone(Table1)Boththeenvironmen-talvariables(a+b)andthepurespatialvariables(c)explainedmore
variationinthecompositionalcomponentthanthatinthestructuralcomponentsofcommunityassemblageAdditionallyourfindingsin-dicatethattheunexplained(d)fractionsdominatedthevariancepar-titioningcomputedforthestructuralcomponentYstralone(Table1)
4emsp |emspDISCUSSION
Forest ecosystems can be characterized and evaluated in terms ofboththeirstructureandcomposition(Peet1992)Inpreviousstud-ies the compositional and structural components of a communityassemblagewereusuallyanalyzedseparately(egFangetal2012)Howeverthenatureofspeciesassemblagesindicatesthateitherspe-cies composition or size structure of constituent individuals alonemayoversimplifycommunityorganization (DeCaacuteceresetal2013)Changes in structure and compositionmay be onlyweakly related(egArsenaultampBradfield1995)thereforeassessmentofbothsi-multaneouslyisimportantwhenevaluatingcommunityassemblyInthepresentstudywegeneralizedtheconventionalapproachtocom-munityassemblagebyincorporatingstructuraldataofacommunityinadditiontocompositionaldatausingtheCAPframeworkToourknowledge this is the firstpaper that investigates inasinglestudythevariationinboththecompositionalandstructuralcomponentsofcommunityassemblagessimultaneouslyaswellasitsdeterminants
F IGURE 3emspThecorrelationsbetweentheLocalContributionstoBetaDiversity(LCBD)intermsofcommunitycomposition(LCBDCOMP)structure(LCBDSTR)andbothcomponentstogether(LCBDCOMPndashSTR)ThecorrelationsofLCBDCOMPvsLCBDSTRLCBDCOMP vsLCBDCOMPndashSTRandLCBDSTR vs LCBDCOMPndashSTRwiththesizeofbinsofthestructuralvariable(binsizes=1ndash15cm)atthescaleof(a)10mtimes10m(b)20mtimes20mand(c)50mtimes50mIngraphs(a)(b)and(c)thehorizontalreddottedlineshorizontalbluelong-dashlinesandhorizontalgreensolidlinesrepresentthemeanvaluesofSpearmanrsquosrankcorrelationcoefficientr across 1ndash15 cm binsizeofLCBDCOMPvsLCBDSTRLCBDCOMPvsLCBDCOMPndashSTRLCBDSTR vs LCBDCOMPndashSTRrespectively(d)BoxplotsfortheSpearmanrsquosrankcorrelationcoefficientrbetweenthepairwiseofthethreekindsofLCBDof1ndash15cmbinsizesatdifferentquadratsizes[Colourfigurecanbeviewedatwileyonlinelibrarycom]
264emsp |emsp emspenspJournal of Vegetation Science
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We found thatbothoverall betadiversity (BD) and the rela-tive contribution of sampling units to beta diversity (LCBD) de-pended on whether the species composition size structure orbothcomponentstogetherhadbeentakenintoaccountBetadi-versity partitioning indicated that the explanatory power of the
environmental and the spatial variables also varied widely withdifferentcomponentsofacommunityOur resultshighlight thatconsideringboth species compositional and size structural com-ponentsmaybeamorecomprehensivewaytodescribethecom-munityorganization
emspensp emsp | emsp265Journal of Vegetation Science
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41emsp|emspStructural and compositional components of forest variation
The framework of CAP allowed us to incorporate the distribu-tionof individualtreesize intotheanalysisofcommunityassem-blage thusmaking it possible toquantify the spatial variationofcommunitystructurebetadiversityEvensosuchstructuralbetadiversitycanbequantified independentlyor incombinationwithspecies composition TheBDCOMPndashSTR is the largest among thesethreecomponentsofbetadiversity indicating thatapplyingspe-ciescompositionaloneorsizestructurealonetoassessthebetadi-versitymayunderestimatethevariationofassemblages(Figure2)ThevaluesofBDCOMPareclosertotheBDCOMPndashSTRvaluesthanthatofBDSTR(theBDSTRvaluesarerelativelysmallFigure2)ThusasfarasourCAPframework isconcerned it seemsmoreappropri-atetoquantifybetadiversityusingthespeciescomposition indi-viduallythanusingthesizestructureindividuallyNeverthelessifstructureprovidesindependentinformationandisdeemedimpor-tantoneshouldincorporateitinBDassessmentAsbetadiversityindiceswerecalculatedfromdissimilaritymatrices thestructuralcomponent of beta diversity depended on the weight given to
structural vs compositional informationwhencalculatingdissimi-larity(Figure2andashc)Thelargerthebinsizes(iethesmallerweightgiventospeciesstructuralinformation)thecloserBDCOMPndashSTR val-uesapproachedthevaluesofBDCOMP(Figure2andashc)Ifthebinsizesare big enough theBDCOMPndashSTR value and theBDCOMP value are expected to converge at a certain size of dbh binNeverthelessconsideringthenecessityofcomprehensiveassessmentofbetadi-versityweadvocateforsmallbinsizesastheyprovidemoreinde-pendentstructuralinformationFinallyitisimportanttonotethatthisforestplotincludes47differenttreespecieswhichresultsinastrongrelativeweightofthecompositionalcomponentofBDCOMPndashSTRwhenusingtheCAPframeworkRepeatingourstudyinforestswith lower species richness or in this forest but using a coarsercompositional resolution (eg at the family level)would result inlargerrelativeweightofthestructuralcomponent
42emsp|emspLocal contributions to beta diversity in terms of community composition and structure
EcologicallyLCBDindicesonlyrepresentthedegreeofuniquenessofthesamplingunitsintermsofcommunitycomposition(Legendre
F IGURE 4emspMapsof30-ha(500mtimes600m)plotshowingthelocalcontributionstobetadiversity(LCBD)intermsofcommunitycompositionandstructurefor750quadrats(20mtimes20m)ThesolidcirclesrepresentthevaluesofLCBDiforeachithquadrat(i =[1750])(a)ThemapofLCBDsonlyintermsofspeciescompositionNotethatthesizestructureofindividuals(iedbh)isnotconsideredwhencalculatingtheLCBDCOMPthusthevaluesofLCBDCOMPwerenotaffectedbythesizeofthebinsofthestructuralvariable(b)ndash(e)ThetwoextremecasesoftheLCBDmap(b)and(c)givingthemostweighttothestructuralcomponentandcorrespondinglytheleastweighttothecompositionalcomponent(ie1-cmbinsize)and(d)and(e)givingthemostweighttothecompositionalcomponentandcorrespondinglytheleastweighttothestructuralcomponent(ie15-cmbinsize)(f)and(g)MapsofLCBDsafteraveragingacrossdbhbinsizesSizeofthecirclesisproportionaltotheLCBDivaluesTheblackandgreysolidcirclesrepresentthesiteswithLCBDvalueshigherandlowerthanthemeanrespectively
TABLE 1emspVariationpartitioningresultsforthreetypesofmatricesatdifferentscalesofquadratsThepartitioningisbasedonadjustedR2 statisticsasrecommendedbyPeres-Netoetal(2006)
Quadrat sizes (a) (b) (c) (d) (a + b) (b + c) (a + b + c)
YCOMP
10mtimes10m 00044 00796 01361 07799 00840 02157 02201
20mtimes20m 00028 01783 02862 05327 01811 04645 04673
50mtimes50m 00050 02995 03229 03726 03045 06224 06274
YSTR
10mtimes10m 00123 00131 00296 09450 00254 00427 00550
20mtimes20m 00013 00907 01652 07428 00920 02560 02572
50mtimes50m 00029 02300 02163 05509 02328 04463 04492
YCOMPndashSTR
10mtimes10m 00055 00564 00932 08449 00619 01496 01551
20mtimes20m 00028 01576 02559 05837 01604 04135 04163
50mtimes50m 00013 02543 01948 05496 02556 04492 04504
Fractions(a)ndash(d)(adjustedR2statistics)(a)variationexplainedbytheenvironmentalvariablesaftercontrollingforthespatialstructure(b)variationexplainedbythespatiallystructuredenvironmentalvariables(c)spatiallystructuredvariationexplainedbypurespaceaftercontrollingforenviron-mentalvariation(d)residualvariationEnvironmentalvariablesusedtocomputefraction(a+b)dbMEMeigenfunctionsweretheexplanatoryvaria-blesusedtocomputefraction(b+c)Only5-cm-diameterclasses(iebinsize=5cm)asthestructuralvariablewereusedtocalculatetheYSTR and YCOMPndashSTR
266emsp |emsp emspenspJournal of Vegetation Science
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amp De Caacuteceres 2013) However natural communities may exhibitsimilarspeciescompositionsbutdifferinotherfeaturessuchasthesizestructureof individuals Inthepresentstudyweassessedthedegreeofuniquenessofthequadratsintermsnotonlyoftheirspe-ciescompositionbutalsooftheirsizestructureandbyusingbothcomponentstogetherThedegreeofuniquenessofquadratsintermsofcommunitycompositionindividuallyhadaveryweakcorrelationwithuniqueness in termsof size structure individually (LCBDCOMP vsLCBDSTRFigure3) indicating that sites that areunique in spe-cies composition are not necessarily unique in size structure andvice versa Additionally we found that the spatial distribution ofsiteswithhighLCBDvaluesisdifferentforthetwocomponentsofacommunitywith siteswithhighstructuraluniquenessoccurringinsmallforestpatches(Figure4)Alltheseresultsreinforcetheideathatconsideringbothspeciescompositionalandsizestructuralcom-ponentsmaybeamorecomprehensivewaytodescribethecommu-nityorganizationHoweverifweacceptthefactthatsitesthatareuniqueintermsofsizestructurearetheresultofgapdynamics(seebelow) the non-zero correlation between LCBDCOMP vs LCBDSTR mayindicatethatforestgapsmaybecolonizedbyspeciesthatmaylaterbesuppressedastheforestgrowssothatrecentforestgapshaveadifferentspeciescompositionthanclosedforeststructures(Comitaetal2009)
43emsp|emspPartitioning the structural and compositional components of beta diversity
About344ofthevariationincommunityassemblagewasdeter-minedbyenvironmentalandspatialvariablesdependingonthescale(quadratsize)andonwhichcomponentsofcommunityassemblage(ie compositional component structural component and takingbothcomponents together)were taken intoaccountThispropor-tion isslightly lowerthanthevaluesfound instudiesbyLegendreetal (2009)andPunchi-Manageetal (2014)Areasonforthisre-sult is thatwe incorporateddifferencesboth insizestructureandspeciescomposition intocommunityassemblagesratherthanonlyusingtheconventionalspeciescompositiondataWhenthespeciescomposition and size structure of the constituent individuals areincorporatedintothecommunityatthesametimemorevariationwilloccurincommunityassemblagesInourstudyhabitat(a+b)ex-plainedmorevariationinthecompositionalcomponent(190)thaninthestructuralcomponent(117)ofthecommunityassemblagesBetadiversitypartitioningindicatedthatthevariationinthestruc-turalcomponentislessdictatedbyenvironmentthanvariationinthecompositional componentWe here hypothesize that canopy gapdynamicswillbethepotentialdriversofstructuralvariationWinterinourstudyareaiscoldandlongwithalongsnowfallperiodThesnowfallperiodlastsforhalfayearandthesnowcoverthicknessinmountainousareasreaches40ndash50cmWehypothesizethatpulsesofmoderate-severity disturbancesmay be caused by snowstormsin our site In the absence of stand-replacing disturbances forestcanopiesareopenedperiodicallybythedeathofsinglebigtreesorsmallgroupsofadulttreescreatingcanopygapsSnowstormsmay
havealteredforeststructurebyselectivelyremovinglargercanopytrees Environmental selection of individuals shapes compositionbydeterminingthefitnessof individualswhereasstructuralvaria-tionmayhavesomerelationshipwithenvironmentalconditions(ielargertreesinsiteswherelargersizesaresupportedforenergyorwateravailability)butingeneralisthereflectionofdifferentstagesaroundgapdynamicsPreviousstudiesareconsistentwithourfind-ingsFraverandWhite(2005)forinstancefoundthattherepeatedmoderate-severity disturbances (iewindstorms) causeddramaticstructural changes they caused no significant change in speciescomposition
Becausetherelativeimportanceofbothnicheandneutralthe-oryinstructuringcommunitiesvarieswithspatialscale(Legendreetal 2009 Punchi-Manage etal 2014) we conducted scale-dependentanalyses InsharpcontrasttothefindingbyLegendreetal(2009)forabroad-leavedforestinChinawefoundthattheproportionofundeterminedvariation incompositionalandstruc-turalcomponentsofcommunityassemblageswasveryhighatfinespatialscales(upto945forthestructuralcomponent780forthecompositionalcomponentand844forbothcomponentsto-gether)butdecreasedsystematicallywith increasingspatial scale(up to a minimum of 373 for compositional component at the50-mscale)TheseresultsareinlinewiththefindingsbyPunchi-Manageetal(2014)inaSriLankandipterocarpforestandbyDeCaacuteceresetal(2012)inacomparisonofseveralforestsOntheonehandthehighproportionofunexplainedvariationmayberelatedtounmeasuredandnotspatially-structuredbiologicalorenviron-mentalvariablesXuetal(2016)showedthatthesoilnutrientsintheupper(0ndash10cmconsideredinourstudy)andlowersoillayers(10ndash20cm)andtheheavymetalelements(CuNiCdAsPbZnMoCrMnandMg)inthesoilshowastrongcorrelationwiththespeciesspatialdistributionsatJiaoheThismaypartlyexplainwhythepureenvironmentalvariable(a)explainedsuchlittlevariationinthecommunityassemblagesAnotherexplanationforthehighpro-portionofunexplainedvariationisthatitmaybeduetostochasticprocesseswhich related to theneutral theoryassuming that thedynamicsofpopulationsareprimarilydrivenbyecologicaldriftanddispersal(Legendreetal2009)Ontheotherhandtheproportionofundeterminedvariationincompositionalandstructuralcompo-nents of community assemblages decreased systematically withincreasingspatialscaleThismayindicatethatcommunityassem-blageishighlystochasticintermsofspeciescompositionandtreesizedistributionatfinescales (ie10-mscale)butthisfinescalestochasticitytendstosmoothoutatthe50-mscalewheremoreconsistent habitat-driven species assemblages emerged Whenvariance partitioning is conducted on the structural componentalonetheunexplained(d)fractionisdominantWhiletheinfluenceofenvironmental factorsonsizestructuremaybe less importantthan for thecompositionalcomponent theeffectof localdistur-bances (eg appearanceof canopygaps resulting frommortalityof largetrees)results inrandomspatialpatternsofquadratswithrather different structure contributing to a large unexplainedfraction
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YAO et Al
5emsp |emspCONCLUSIONS
SpeciescompositionandsizestructurearethetwoessentialfeaturesofacommunityOnlyoneofthemindividuallymaybeinsufficienttodescribetheorganizationoftreespeciesassemblagesDefiningandquantifyingbetadiversityusingthespeciescompositionalonemaybesufficienttheninmanyoccasionsNeverthelessspeciescompo-sition is justonedimensionofbiodiversity variation in size struc-tureisalsoimportantIncorporatingstructuraldatainbetadiversityassessmentsallowsecologiststomakeuseofvaluableinformationcollectedduringfieldsurveysIfitisavailablethereisnoreasontoignorethewealthofinformationaboutsizestructurewhencompar-ingspeciesassemblagesOurstudyhighlightstheneedtoincorpo-ratethestructuraldataofacommunityinadditiontocompositionaldatawhenquantifyingandanalyzingbetadiversityFinallyourre-sults suggest thatbothdeterministicandstochasticprocessesarerelevantdeterminantsofcompositionalandstructuralcomponentsof communityassemblages inour temperate forestNeverthelesstheseprocessesarescale-andorresolution-dependent
ACKNOWLEDGEMENTS
WewouldliketothankHeHuaijiangDingShengjianNiRuiqiangandZuoQiangandseveralothersforassistingwiththefielddatacollectionAuthorsaregratefultotheJiaoheManagementBureauof the Forest Experimental Zone for permission to undertake thefieldworkWealsothankthreeanonymousreviewersforprovidingthevaluablecomments
CONFLICTS OF INTEREST
Theauthorsdeclarenocompetingfinancialinterests
DATA ACCESSIBILITY
DataownershipbelongstoBeijingForestryUniversitywhosestaffconductedtheanalysesandwrotethemanuscripthttpwwwbjfueducn
ORCID
Jie Yao httpsorcidorg0000-0002-8606-8158
REFERENCES
Anderson M J Crist T O Chase J M Vellend M InouyeB D Freestone A L hellip Swenson N G (2011) Navigatingthe multiple meanings of β diversity a roadmap for the prac-ticing ecologist Ecology Letters 14 19ndash28 httpsdoiorg101111j1461-0248201001552x
ArsenaultAampBradfieldGE (1995)Structuralndashcompositionalvaria-tioninthreeage-classesoftemperaterainforestsinsoutherncoastalBritishColumbiaCanadian Journal of Botany7354ndash64httpsdoiorg101139b95-007
Borcard D amp Legendre P (1994) Environmental control and spatialstructureinecologicalcommunitiesanexampleusingoribatidmites(Acari Oribatei) Environmental and Ecological Statistics 1 37ndash61httpsdoiorg101007BF00714196
Borcard D Legendre P Avois-Jacquet C amp Tuomisto H (2004)DissectingthespatialstructureofecologicaldataatmultiplescalesEcology851826ndash1832httpsdoiorg10189003-3111
BorcardDLegendrePampDrapeauP(1992)PartiallingoutthespatialcomponentofecologicalvariationEcology731045ndash1055httpsdoiorg1023071940179
Caswell H (1976) Community structure a neutral model anal-ysis Ecological Monographs 46 327ndash354 httpsdoiorg1023071942257
ChaseJM(2010)Stochasticcommunityassemblycauseshigherbiodi-versityinmoreproductiveenvironmentsScience3281388ndash1391httpsdoiorg101126science1187820
ChaveJ(2004)NeutraltheoryandcommunityecologyEcology Letters7241ndash253httpsdoiorg101111j1461-0248200300566x
Chesson P (2000) Mechanisms of maintenance of species diversityAnnual Review of Ecology and Systematics31343ndash366httpsdoiorg101146annurevecolsys311343
ComitaLSUriarteMThompsonJJonckheereICanhamCDampZimmermanJK(2009)Abioticandbioticdriversofseedlingsur-vival inahurricane-impacted tropical forestJournal of Ecology971346ndash1359httpsdoiorg101111j1365-2745200901551x
DeCaacuteceresMFontXampOlivaF(2010)Themanagementofvegeta-tionclassificationswithfuzzyclusteringJournal of Vegetation Science211138ndash1151httpsdoiorg101111j1654-1103201001211x
De Caacuteceres M Legendre P amp He F (2013) Dissimilarity mea-surements and the size structure of ecological communitiesMethods in Ecology and Evolution 4 1167ndash1177 httpsdoiorg1011112041-210X12116
De Caacuteceres M Legendre P Valencia R Cao M Chang L-W Chuyong G hellip He F (2012) The variation of tree betadiversity across a global network of forest plots Global Ecology and Biogeography 21 1191ndash1202 httpsdoiorg101111j1466-8238201200770x
DraySBaumanDBlanchetGBorcardDClappeSGuenardGhellipWagnerHH(2018)adespatial Multivariate multiscale spatial analy-sis R package version 03-2RetrievedfromhttpsCRANR-projectorgpackage=adespatial
Dumbrell A J NelsonM Helgason T Dytham C amp Fitter A H(2010)Relativerolesofnicheandneutralprocesses instructuringa soil microbial community ISME Journal 4 337ndash345 httpsdoiorg101038ismej2009122
FaithDAustinMBelbinLampMargulesC (1985)Numericalclas-sification of profile attributes in environmental studies Journal of Environmental Management2073ndash85
Fang J Shen Z Tang ZWang XWang Z Feng J hellip Zheng C(2012) Forest community survey and the structural character-istics of forests in China Ecography 35 1059ndash1071 httpsdoiorg101111j1600-0587201300161x
FraverSampWhiteAS(2005)Disturbancedynamicsofold-growthPicea rubens forests of northern Maine Journal of Vegetation Science 16 597ndash610 httpsdoiorg101111j1654-11032005tb02401x
Gower J C (1966) Some distance properties of latent root and vec-tormethodsusedinmultivariateanalysisBiometrika53325ndash338httpsdoiorg101093biomet533-4325
Harms K E Condit R Hubbell S P amp Foster R B (2001)Habitat associations of trees and shrubs in a 50-ha neotrop-ical forest plot Journal of Ecology 89 947ndash959 httpsdoiorg101111j1365-2745200100615x
HilleRisLambers J Adler P B Harpole W S Levine J M ampMayfield M M (2012) Rethinking community assembly
268emsp |emsp emspenspJournal of Vegetation Science
YAO et Al
through the lens of coexistence theory Annual Review of Ecology Evolution and Systematics 43 227ndash249 httpsdoiorg101146annurev-ecolsys-110411-160411
HubbellSP(Ed)(2001)The unified theory of biodiversity and biogeogra-phyPrincetonNJPrincetonUniversityPress
Hubbell S P (2006) Neutral theory and the evolution of eco-logical equivalence Ecology 87 1387ndash1398 httpsdoiorg1018900012-9658(2006)87[1387NTATEO]20CO2
HussonFJosseJLeSampMazetJ(2015)FactoMineR Multivariate exploratory data analysis and data mining Version 1314 RetrievedfromhttpsCRANR-projectorgpackage=FactoMineR
Hutchinson G E (1961) The paradox of the plankton American Naturalist95137ndash145httpsdoiorg101086282171
KeddyPA(1992)Assemblyandresponserulestwogoalsforpredic-tive community ecology Journal of Vegetation Science3 157ndash164httpsdoiorg1023073235676
KoleffPGastonKJampLennonJJ(2003)MeasuringbetadiversityforpresencendashabsencedataJournal of Animal Ecology72367ndash382httpsdoiorg101046j1365-2656200300710x
KraftN JBComita L SChase JM SandersN J SwensonNGCrist TOhellipMyers JA (2011)Disentangling thedriversofβdiversityalong latitudinalandelevationalgradientsScience3331755ndash1758httpsdoiorg101126science1208584
LaliberteacuteEPaquetteALegendrePampBouchardA(2009)Assessingthescale-specificimportanceofnichesandotherspatialprocessesonbetadiversityacasestudyfromatemperateforestOecologia159377ndash388httpsdoiorg101007s00442-008-1214-8
Legendre P amp Anderson M J (1999) Distance-based redundancyanalysis testing multispecies responses in multifactorial ecolog-ical experiments Ecological Monographs 69 1ndash24 httpsdoiorg1018900012-9615(1999)069[0001DBRATM]20CO2
Legendre P Borcard D amp Peres-Neto P R (2005) Analyzing betadiversity partitioning the spatial variation of community com-position data Ecological Monographs 75 435ndash450 httpsdoiorg10189005-0549
LegendrePampDeCaacuteceresM(2013)BetadiversityasthevarianceofcommunitydatadissimilaritycoefficientsandpartitioningEcology Letters16951ndash963httpsdoiorg101111ele12141
LegendrePampLegendreL (2012)Numerical ecology Vol 24 (3rded)AmsterdamTheNetherlandsElsevierScienceBV
LegendrePMiXRenHMaKYuMSun I-FampHeF (2009)Partitioning beta diversity in a subtropical broad-leaved forest ofChina Ecology90663ndash674httpsdoiorg10189007-18801
MayfieldMMampLevineJM(2010)Opposingeffectsofcompetitiveex-clusiononthephylogeneticstructureofcommunitiesEcology Letters131085ndash1093httpsdoiorg101111j1461-0248201001509x
MyersJAChaseJMJimeacutenezIJoslashrgensenPMAraujo-MurakamiAPaniagua-ZambranaNampSeidelR(2013)Beta-diversityintem-perateandtropicalforestsreflectsdissimilarmechanismsofcommu-nityassemblyEcology Letters16151ndash157httpsdoiorg101111ele12021
OksanenJBlanchetFGFriendlyMKindtRLegendrePMcGlinnDhellipWagnerH(2018)vegan Community ecology package Version 25-2Retrievedfromhttpscranr-projectorgpackage=vegan
Paradis EClaude JampStrimmerK (2004)APEAnalysesof phylo-genetics and evolution inR languageBioinformatics20 289ndash290httpsdoiorg101093bioinformaticsbtg412
PeetRK (1992)Community structureand function InDCGlenn-LewinRKPeetampTTVeblen(Eds)Plant succession theory and prediction(pp103ndash140)NewYorkNYChapmanampHall
Peres-NetoPRLegendrePDraySampBorcardD(2006)Variationpartitioningofspeciesdatamatricesestimationandcomparisonof
fractionsEcology872614ndash2625httpsdoiorg1018900012-9658(2006)87[2614VPOSDM]20CO2
Punchi-Manage R Wiegand T Wiegand K Getzin S SavitriGunatillekeCV ampNimalGunatilleke IAUN(2014)EffectofspatialprocessesandtopographyonstructuringspeciesassemblagesinaSriLankandipterocarpforestEcology95376ndash386httpsdoiorg10189012-21021
RCoreTeam (2017)R A language and environment for statistical com-puting Vienna Austria R Foundation for Statistical ComputingRetrievedfromhttpswwwR-projectorg
Ricklefs R E (1990) Seabird life histories and the marine environ-mentsomespeculationsColonial Waterbirds13(1)1ndash6httpsdoiorg1023071521414
SchwinningSampWeinerJ(1998)MechanismsdeterminingthedegreeofsizeasymmetryincompetitionamongplantsOecologia113447ndash455httpsdoiorg101007s004420050397
SoilScienceSocietyofChina(Ed)(1999)Soil agricultural chemical analy-sis procedureBeijingChinaChineseAgriculturalSciencePress
van der Plas F Janzen T Ordonez A FokkemaW Reinders JEtienneRSampOlffH(2015)Anewmodelingapproachestimatesthe relative importance of different community assembly pro-cesses Ecology961502ndash1515httpsdoiorg10189014-04541
VellendM(Ed)(2017)The theory of ecological communitiesPrincetonNJPrincetonUniversityPresshttpsdoiorg1015159781400883790
Weiner J (1990) Asymmetric competition in plant popula-tions Trends in Ecology and Evolution 5 360ndash364 httpsdoiorg1010160169-5347(90)90095-U
WhittakerRH (1960)VegetationoftheSiskiyoumountainsOregonand California Ecological Monographs 30 279ndash338 httpsdoiorg1023071943563
WhittakerRH(1972)EvolutionandmeasurementofspeciesdiversityTaxon21213ndash251httpsdoiorg1023071218190
XuWHaoMWangJZhangCZhaoXampvonGadowK(2016)Soilelementsinfluencingcommunitystructureinanold-growthfor-est innortheasternChinaForests7159httpsdoiorg103390f7080159
YamakuraTKanzakiMItohAOhkuboTOginoKChaiEOKhellipAshtonPS(1995)Topographyofalarge-scaleresearchplotes-tablishedwithinatropicalrainforestatLambirSarawakTropics541ndash56httpsdoiorg103759tropics541
YanYZhangCWangYZhaoXampvonGadowK(2015)Driversofseedlingsurvivalinatemperateforestandtheirrelativeimportanceat threestagesofsuccessionEcology and Evolution54287ndash4299httpsdoiorg101002ece31688
YaoJZhangXZhangCZhaoXampvonGadowK(2016)EffectsofdensitydependenceinatemperateforestinnortheasternChinaScientific Reports632844httpsdoiorg101038srep32844
ZhangCZhaoXampvonGadowK(2014)Analyzingselectiveharvestevents inthree largeforestobservationalstudies inNorthEasternChina Forest Ecology and Management 316 100ndash109 httpsdoiorg101016jforeco201307018
ZhangCZhaoYZhaoXampvonGadowK (2012)Species-habitatassociations inanorthern temperate forest inChinaSilva Fennica46501ndash519
How to cite this articleYaoJZhangCDeCaacuteceresMLegendrePZhaoXVariationincompositionalandstructuralcomponentsofcommunityassemblageanditsdeterminantsJ Veg Sci 201930257ndash268 httpsdoiorg101111jvs12708
262emsp |emsp emspenspJournal of Vegetation Science
YAO et Al
substantially stronger than that ofDCOMP vs DSTR andofDSTR vs DCOMPndashSTR
The correlation ofDCOMP vs DCOMPndashSTR increasedwith the in-crease of bin size Correspondingly the correlations of DSTR vs DCOMPndashSTR showed the opposite trend (Figure1andashc) As to the ef-fectofthesizeofthesamplingunitsthestrengthofcorrelationsin-creasedwiththequadratsize(Figure1d)exceptforthecorrelationbetweenDCOMP and DCOMPndashSTRwhichexhibitsnosignificantdiffer-encebetweenthe10mtimes10mand20mtimes20mquadrats(p = 023Figure1d)
32emsp|emspThe three components of beta diversity (BD) BDCOMP BDSTR and BDCOMPndashSTR
Thebetadiversity(BD)valueswerecloselyrelatedtowhetherthespecies composition size structure or both components togetherhad been taken into account Among these three components ofbetadiversityBDCOMPndashSTRwasgreatestcloselyfollowedbyBDCOMPandthesmallestwasBDSTR(Figure2)Sincethesizestructureofin-dividualswasnot consideredwhen calculatingBDCOMP this indexwasnotaffectedbythesizeofdbhbins(Figure2andashc)ThevaluesofBDCOMPndashSTRandBDSTRhoweverdecreasedslightlywithanincreaseofbinsizeWhenincreasingdbhbinsizethevaluesofBDCOMPndashSTR graduallyapproachedthevaluesofBDCOMP (Figure2andashc)BDalso
varied as a function of quadrat size (Figure2) values of BDCOMPBDSTRandBDCOMPndashSTR(afteraveragingacrossbinsizes)systemati-callydecreasedwithincreasingquadratsize(Figure2d)
33emsp|emspLocal contributions to beta diversity in terms of community composition and structure
LocalContributionstoBetaDiversitycalculatedusingspeciescom-positionsizestructureorbothcomponentswerecorrelatedAgainthe strengthof correlationsdependedon the sizeofdbhbins andon the size of quadrats (Figure3andashc) In the case of LCBDCOMP vs LCBDCOMPndashSTR the strength of the correlation increased with anincreaseofbinsizeCorrespondinglythecorrelationofLCBDSTR vs LCBDCOMPndashSTRshowedtheoppositetrend(Figure3andashc)Thecorrela-tionsofLCBDCOMPvsLCBDSTRandLCBDSTRvsLCBDCOMPndashSTR were significantly different for differentquadrat sizesA striking findingwasthatthestrengthofcorrelationswasweakeratthescaleof20mtimes20m than that at the scalesof10mtimes10mor50mtimes50m(Figure3d)HowevercorrelationsbetweenLCBDCOMPvsLCBDCOMPndashSTRwerenotsubstantiallyaffectedbythesizeofquadrats(Figure3d)
TheLCBDivaluesindicatetheithquadratsthatcontributemoreorlessthanthemeantobetadiversity(inotherwordstheithquad-ratswithhighorlowuniquenessofspeciesassemblages)TheresultsindicatedthatthesiteswithhighLCBDvalues(contributemorethan
F IGURE 2emspTheBetaDiversity(BD)intermsofspeciescomposition(BDCOMP)sizestructure(BDSTR)andbothcomponentstogether(BDCOMPndashSTR)ThevaluesofBDCOMPndashSTRandBDSTRvarywiththesizeofbinsofthestructuralvariable(dbhbinsizes=1ndash15cm)atthescaleof(a)10mtimes10m(b)20mtimes20mand(c)50mtimes50mThesizestructureofindividuals(iethedbh)isnotconsideredwhencalculatingtheBDCOMPthusthevaluesofBDCOMPwerenotaffectedbythebinsizeIngraphs(a)(b)and(c)thehorizontalbluelong-dashlinesandhorizontalgreensolidlinesrepresentthemeanvaluesofBDCOMPndashSTRandBDSTRacross1ndash15cmbinsizesrespectively(d)ValuesofBDCOMPBDSTRandBDCOMPndashSTR(afteraveragingacrossdbhbinsizes)varywiththesamplingunitsizes[Colourfigurecanbeviewedatwileyonlinelibrarycom]
emspensp emsp | emsp263Journal of Vegetation Science
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themeantobetadiversity)arevariedamongthreecomponentsofacommunity (Figure4)Specifically342(456)290(387)and331 (441)outof750quadratscontributedmorethanthemeanto beta diversity in term of species composition (ie LCBDCOMPFigure4a)sizestructure(ieLCBDSTRFigure4g)andbothcompo-nentstogether(ieLCBDCOMPndashSTRFigure4f)respectively
34emsp|emspVariation partitioning of matrices DCOMP DSTR and DCOMPndashSTR
Theexplanatorypoweroftheenvironmentalvariablesandthespa-tialvariablesvariedforthethreetypesofmatricesandwithquadratsizes (Table 1) The variation explained by the environmental vari-ables(a+b)andbythespatialvariables(b+c)increasedsystemati-callywith increasingscale (Table1)Averagingacrossquadratsizeshabitatandspacejointlyexplained438254and341ofthevariation in compositional component structural component andthe two components together of community assemblage respec-tivelyHoweverthecontributionofthepurehabitatcomponent (a)was negligible The combination of environmental and spatial vari-ablesexplained the lowestproportionofvariation in the structuralcomponentaloneandexplainedthehighestproportionofvariationinthecompositionalcomponentalone(Table1)Boththeenvironmen-talvariables(a+b)andthepurespatialvariables(c)explainedmore
variationinthecompositionalcomponentthanthatinthestructuralcomponentsofcommunityassemblageAdditionallyourfindingsin-dicatethattheunexplained(d)fractionsdominatedthevariancepar-titioningcomputedforthestructuralcomponentYstralone(Table1)
4emsp |emspDISCUSSION
Forest ecosystems can be characterized and evaluated in terms ofboththeirstructureandcomposition(Peet1992)Inpreviousstud-ies the compositional and structural components of a communityassemblagewereusuallyanalyzedseparately(egFangetal2012)Howeverthenatureofspeciesassemblagesindicatesthateitherspe-cies composition or size structure of constituent individuals alonemayoversimplifycommunityorganization (DeCaacuteceresetal2013)Changes in structure and compositionmay be onlyweakly related(egArsenaultampBradfield1995)thereforeassessmentofbothsi-multaneouslyisimportantwhenevaluatingcommunityassemblyInthepresentstudywegeneralizedtheconventionalapproachtocom-munityassemblagebyincorporatingstructuraldataofacommunityinadditiontocompositionaldatausingtheCAPframeworkToourknowledge this is the firstpaper that investigates inasinglestudythevariationinboththecompositionalandstructuralcomponentsofcommunityassemblagessimultaneouslyaswellasitsdeterminants
F IGURE 3emspThecorrelationsbetweentheLocalContributionstoBetaDiversity(LCBD)intermsofcommunitycomposition(LCBDCOMP)structure(LCBDSTR)andbothcomponentstogether(LCBDCOMPndashSTR)ThecorrelationsofLCBDCOMPvsLCBDSTRLCBDCOMP vsLCBDCOMPndashSTRandLCBDSTR vs LCBDCOMPndashSTRwiththesizeofbinsofthestructuralvariable(binsizes=1ndash15cm)atthescaleof(a)10mtimes10m(b)20mtimes20mand(c)50mtimes50mIngraphs(a)(b)and(c)thehorizontalreddottedlineshorizontalbluelong-dashlinesandhorizontalgreensolidlinesrepresentthemeanvaluesofSpearmanrsquosrankcorrelationcoefficientr across 1ndash15 cm binsizeofLCBDCOMPvsLCBDSTRLCBDCOMPvsLCBDCOMPndashSTRLCBDSTR vs LCBDCOMPndashSTRrespectively(d)BoxplotsfortheSpearmanrsquosrankcorrelationcoefficientrbetweenthepairwiseofthethreekindsofLCBDof1ndash15cmbinsizesatdifferentquadratsizes[Colourfigurecanbeviewedatwileyonlinelibrarycom]
264emsp |emsp emspenspJournal of Vegetation Science
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We found thatbothoverall betadiversity (BD) and the rela-tive contribution of sampling units to beta diversity (LCBD) de-pended on whether the species composition size structure orbothcomponentstogetherhadbeentakenintoaccountBetadi-versity partitioning indicated that the explanatory power of the
environmental and the spatial variables also varied widely withdifferentcomponentsofacommunityOur resultshighlight thatconsideringboth species compositional and size structural com-ponentsmaybeamorecomprehensivewaytodescribethecom-munityorganization
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41emsp|emspStructural and compositional components of forest variation
The framework of CAP allowed us to incorporate the distribu-tionof individualtreesize intotheanalysisofcommunityassem-blage thusmaking it possible toquantify the spatial variationofcommunitystructurebetadiversityEvensosuchstructuralbetadiversitycanbequantified independentlyor incombinationwithspecies composition TheBDCOMPndashSTR is the largest among thesethreecomponentsofbetadiversity indicating thatapplyingspe-ciescompositionaloneorsizestructurealonetoassessthebetadi-versitymayunderestimatethevariationofassemblages(Figure2)ThevaluesofBDCOMPareclosertotheBDCOMPndashSTRvaluesthanthatofBDSTR(theBDSTRvaluesarerelativelysmallFigure2)ThusasfarasourCAPframework isconcerned it seemsmoreappropri-atetoquantifybetadiversityusingthespeciescomposition indi-viduallythanusingthesizestructureindividuallyNeverthelessifstructureprovidesindependentinformationandisdeemedimpor-tantoneshouldincorporateitinBDassessmentAsbetadiversityindiceswerecalculatedfromdissimilaritymatrices thestructuralcomponent of beta diversity depended on the weight given to
structural vs compositional informationwhencalculatingdissimi-larity(Figure2andashc)Thelargerthebinsizes(iethesmallerweightgiventospeciesstructuralinformation)thecloserBDCOMPndashSTR val-uesapproachedthevaluesofBDCOMP(Figure2andashc)Ifthebinsizesare big enough theBDCOMPndashSTR value and theBDCOMP value are expected to converge at a certain size of dbh binNeverthelessconsideringthenecessityofcomprehensiveassessmentofbetadi-versityweadvocateforsmallbinsizesastheyprovidemoreinde-pendentstructuralinformationFinallyitisimportanttonotethatthisforestplotincludes47differenttreespecieswhichresultsinastrongrelativeweightofthecompositionalcomponentofBDCOMPndashSTRwhenusingtheCAPframeworkRepeatingourstudyinforestswith lower species richness or in this forest but using a coarsercompositional resolution (eg at the family level)would result inlargerrelativeweightofthestructuralcomponent
42emsp|emspLocal contributions to beta diversity in terms of community composition and structure
EcologicallyLCBDindicesonlyrepresentthedegreeofuniquenessofthesamplingunitsintermsofcommunitycomposition(Legendre
F IGURE 4emspMapsof30-ha(500mtimes600m)plotshowingthelocalcontributionstobetadiversity(LCBD)intermsofcommunitycompositionandstructurefor750quadrats(20mtimes20m)ThesolidcirclesrepresentthevaluesofLCBDiforeachithquadrat(i =[1750])(a)ThemapofLCBDsonlyintermsofspeciescompositionNotethatthesizestructureofindividuals(iedbh)isnotconsideredwhencalculatingtheLCBDCOMPthusthevaluesofLCBDCOMPwerenotaffectedbythesizeofthebinsofthestructuralvariable(b)ndash(e)ThetwoextremecasesoftheLCBDmap(b)and(c)givingthemostweighttothestructuralcomponentandcorrespondinglytheleastweighttothecompositionalcomponent(ie1-cmbinsize)and(d)and(e)givingthemostweighttothecompositionalcomponentandcorrespondinglytheleastweighttothestructuralcomponent(ie15-cmbinsize)(f)and(g)MapsofLCBDsafteraveragingacrossdbhbinsizesSizeofthecirclesisproportionaltotheLCBDivaluesTheblackandgreysolidcirclesrepresentthesiteswithLCBDvalueshigherandlowerthanthemeanrespectively
TABLE 1emspVariationpartitioningresultsforthreetypesofmatricesatdifferentscalesofquadratsThepartitioningisbasedonadjustedR2 statisticsasrecommendedbyPeres-Netoetal(2006)
Quadrat sizes (a) (b) (c) (d) (a + b) (b + c) (a + b + c)
YCOMP
10mtimes10m 00044 00796 01361 07799 00840 02157 02201
20mtimes20m 00028 01783 02862 05327 01811 04645 04673
50mtimes50m 00050 02995 03229 03726 03045 06224 06274
YSTR
10mtimes10m 00123 00131 00296 09450 00254 00427 00550
20mtimes20m 00013 00907 01652 07428 00920 02560 02572
50mtimes50m 00029 02300 02163 05509 02328 04463 04492
YCOMPndashSTR
10mtimes10m 00055 00564 00932 08449 00619 01496 01551
20mtimes20m 00028 01576 02559 05837 01604 04135 04163
50mtimes50m 00013 02543 01948 05496 02556 04492 04504
Fractions(a)ndash(d)(adjustedR2statistics)(a)variationexplainedbytheenvironmentalvariablesaftercontrollingforthespatialstructure(b)variationexplainedbythespatiallystructuredenvironmentalvariables(c)spatiallystructuredvariationexplainedbypurespaceaftercontrollingforenviron-mentalvariation(d)residualvariationEnvironmentalvariablesusedtocomputefraction(a+b)dbMEMeigenfunctionsweretheexplanatoryvaria-blesusedtocomputefraction(b+c)Only5-cm-diameterclasses(iebinsize=5cm)asthestructuralvariablewereusedtocalculatetheYSTR and YCOMPndashSTR
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YAO et Al
amp De Caacuteceres 2013) However natural communities may exhibitsimilarspeciescompositionsbutdifferinotherfeaturessuchasthesizestructureof individuals Inthepresentstudyweassessedthedegreeofuniquenessofthequadratsintermsnotonlyoftheirspe-ciescompositionbutalsooftheirsizestructureandbyusingbothcomponentstogetherThedegreeofuniquenessofquadratsintermsofcommunitycompositionindividuallyhadaveryweakcorrelationwithuniqueness in termsof size structure individually (LCBDCOMP vsLCBDSTRFigure3) indicating that sites that areunique in spe-cies composition are not necessarily unique in size structure andvice versa Additionally we found that the spatial distribution ofsiteswithhighLCBDvaluesisdifferentforthetwocomponentsofacommunitywith siteswithhighstructuraluniquenessoccurringinsmallforestpatches(Figure4)Alltheseresultsreinforcetheideathatconsideringbothspeciescompositionalandsizestructuralcom-ponentsmaybeamorecomprehensivewaytodescribethecommu-nityorganizationHoweverifweacceptthefactthatsitesthatareuniqueintermsofsizestructurearetheresultofgapdynamics(seebelow) the non-zero correlation between LCBDCOMP vs LCBDSTR mayindicatethatforestgapsmaybecolonizedbyspeciesthatmaylaterbesuppressedastheforestgrowssothatrecentforestgapshaveadifferentspeciescompositionthanclosedforeststructures(Comitaetal2009)
43emsp|emspPartitioning the structural and compositional components of beta diversity
About344ofthevariationincommunityassemblagewasdeter-minedbyenvironmentalandspatialvariablesdependingonthescale(quadratsize)andonwhichcomponentsofcommunityassemblage(ie compositional component structural component and takingbothcomponents together)were taken intoaccountThispropor-tion isslightly lowerthanthevaluesfound instudiesbyLegendreetal (2009)andPunchi-Manageetal (2014)Areasonforthisre-sult is thatwe incorporateddifferencesboth insizestructureandspeciescomposition intocommunityassemblagesratherthanonlyusingtheconventionalspeciescompositiondataWhenthespeciescomposition and size structure of the constituent individuals areincorporatedintothecommunityatthesametimemorevariationwilloccurincommunityassemblagesInourstudyhabitat(a+b)ex-plainedmorevariationinthecompositionalcomponent(190)thaninthestructuralcomponent(117)ofthecommunityassemblagesBetadiversitypartitioningindicatedthatthevariationinthestruc-turalcomponentislessdictatedbyenvironmentthanvariationinthecompositional componentWe here hypothesize that canopy gapdynamicswillbethepotentialdriversofstructuralvariationWinterinourstudyareaiscoldandlongwithalongsnowfallperiodThesnowfallperiodlastsforhalfayearandthesnowcoverthicknessinmountainousareasreaches40ndash50cmWehypothesizethatpulsesofmoderate-severity disturbancesmay be caused by snowstormsin our site In the absence of stand-replacing disturbances forestcanopiesareopenedperiodicallybythedeathofsinglebigtreesorsmallgroupsofadulttreescreatingcanopygapsSnowstormsmay
havealteredforeststructurebyselectivelyremovinglargercanopytrees Environmental selection of individuals shapes compositionbydeterminingthefitnessof individualswhereasstructuralvaria-tionmayhavesomerelationshipwithenvironmentalconditions(ielargertreesinsiteswherelargersizesaresupportedforenergyorwateravailability)butingeneralisthereflectionofdifferentstagesaroundgapdynamicsPreviousstudiesareconsistentwithourfind-ingsFraverandWhite(2005)forinstancefoundthattherepeatedmoderate-severity disturbances (iewindstorms) causeddramaticstructural changes they caused no significant change in speciescomposition
Becausetherelativeimportanceofbothnicheandneutralthe-oryinstructuringcommunitiesvarieswithspatialscale(Legendreetal 2009 Punchi-Manage etal 2014) we conducted scale-dependentanalyses InsharpcontrasttothefindingbyLegendreetal(2009)forabroad-leavedforestinChinawefoundthattheproportionofundeterminedvariation incompositionalandstruc-turalcomponentsofcommunityassemblageswasveryhighatfinespatialscales(upto945forthestructuralcomponent780forthecompositionalcomponentand844forbothcomponentsto-gether)butdecreasedsystematicallywith increasingspatial scale(up to a minimum of 373 for compositional component at the50-mscale)TheseresultsareinlinewiththefindingsbyPunchi-Manageetal(2014)inaSriLankandipterocarpforestandbyDeCaacuteceresetal(2012)inacomparisonofseveralforestsOntheonehandthehighproportionofunexplainedvariationmayberelatedtounmeasuredandnotspatially-structuredbiologicalorenviron-mentalvariablesXuetal(2016)showedthatthesoilnutrientsintheupper(0ndash10cmconsideredinourstudy)andlowersoillayers(10ndash20cm)andtheheavymetalelements(CuNiCdAsPbZnMoCrMnandMg)inthesoilshowastrongcorrelationwiththespeciesspatialdistributionsatJiaoheThismaypartlyexplainwhythepureenvironmentalvariable(a)explainedsuchlittlevariationinthecommunityassemblagesAnotherexplanationforthehighpro-portionofunexplainedvariationisthatitmaybeduetostochasticprocesseswhich related to theneutral theoryassuming that thedynamicsofpopulationsareprimarilydrivenbyecologicaldriftanddispersal(Legendreetal2009)Ontheotherhandtheproportionofundeterminedvariationincompositionalandstructuralcompo-nents of community assemblages decreased systematically withincreasingspatialscaleThismayindicatethatcommunityassem-blageishighlystochasticintermsofspeciescompositionandtreesizedistributionatfinescales (ie10-mscale)butthisfinescalestochasticitytendstosmoothoutatthe50-mscalewheremoreconsistent habitat-driven species assemblages emerged Whenvariance partitioning is conducted on the structural componentalonetheunexplained(d)fractionisdominantWhiletheinfluenceofenvironmental factorsonsizestructuremaybe less importantthan for thecompositionalcomponent theeffectof localdistur-bances (eg appearanceof canopygaps resulting frommortalityof largetrees)results inrandomspatialpatternsofquadratswithrather different structure contributing to a large unexplainedfraction
emspensp emsp | emsp267Journal of Vegetation Science
YAO et Al
5emsp |emspCONCLUSIONS
SpeciescompositionandsizestructurearethetwoessentialfeaturesofacommunityOnlyoneofthemindividuallymaybeinsufficienttodescribetheorganizationoftreespeciesassemblagesDefiningandquantifyingbetadiversityusingthespeciescompositionalonemaybesufficienttheninmanyoccasionsNeverthelessspeciescompo-sition is justonedimensionofbiodiversity variation in size struc-tureisalsoimportantIncorporatingstructuraldatainbetadiversityassessmentsallowsecologiststomakeuseofvaluableinformationcollectedduringfieldsurveysIfitisavailablethereisnoreasontoignorethewealthofinformationaboutsizestructurewhencompar-ingspeciesassemblagesOurstudyhighlightstheneedtoincorpo-ratethestructuraldataofacommunityinadditiontocompositionaldatawhenquantifyingandanalyzingbetadiversityFinallyourre-sults suggest thatbothdeterministicandstochasticprocessesarerelevantdeterminantsofcompositionalandstructuralcomponentsof communityassemblages inour temperate forestNeverthelesstheseprocessesarescale-andorresolution-dependent
ACKNOWLEDGEMENTS
WewouldliketothankHeHuaijiangDingShengjianNiRuiqiangandZuoQiangandseveralothersforassistingwiththefielddatacollectionAuthorsaregratefultotheJiaoheManagementBureauof the Forest Experimental Zone for permission to undertake thefieldworkWealsothankthreeanonymousreviewersforprovidingthevaluablecomments
CONFLICTS OF INTEREST
Theauthorsdeclarenocompetingfinancialinterests
DATA ACCESSIBILITY
DataownershipbelongstoBeijingForestryUniversitywhosestaffconductedtheanalysesandwrotethemanuscripthttpwwwbjfueducn
ORCID
Jie Yao httpsorcidorg0000-0002-8606-8158
REFERENCES
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ArsenaultAampBradfieldGE (1995)Structuralndashcompositionalvaria-tioninthreeage-classesoftemperaterainforestsinsoutherncoastalBritishColumbiaCanadian Journal of Botany7354ndash64httpsdoiorg101139b95-007
Borcard D amp Legendre P (1994) Environmental control and spatialstructureinecologicalcommunitiesanexampleusingoribatidmites(Acari Oribatei) Environmental and Ecological Statistics 1 37ndash61httpsdoiorg101007BF00714196
Borcard D Legendre P Avois-Jacquet C amp Tuomisto H (2004)DissectingthespatialstructureofecologicaldataatmultiplescalesEcology851826ndash1832httpsdoiorg10189003-3111
BorcardDLegendrePampDrapeauP(1992)PartiallingoutthespatialcomponentofecologicalvariationEcology731045ndash1055httpsdoiorg1023071940179
Caswell H (1976) Community structure a neutral model anal-ysis Ecological Monographs 46 327ndash354 httpsdoiorg1023071942257
ChaseJM(2010)Stochasticcommunityassemblycauseshigherbiodi-versityinmoreproductiveenvironmentsScience3281388ndash1391httpsdoiorg101126science1187820
ChaveJ(2004)NeutraltheoryandcommunityecologyEcology Letters7241ndash253httpsdoiorg101111j1461-0248200300566x
Chesson P (2000) Mechanisms of maintenance of species diversityAnnual Review of Ecology and Systematics31343ndash366httpsdoiorg101146annurevecolsys311343
ComitaLSUriarteMThompsonJJonckheereICanhamCDampZimmermanJK(2009)Abioticandbioticdriversofseedlingsur-vival inahurricane-impacted tropical forestJournal of Ecology971346ndash1359httpsdoiorg101111j1365-2745200901551x
DeCaacuteceresMFontXampOlivaF(2010)Themanagementofvegeta-tionclassificationswithfuzzyclusteringJournal of Vegetation Science211138ndash1151httpsdoiorg101111j1654-1103201001211x
De Caacuteceres M Legendre P amp He F (2013) Dissimilarity mea-surements and the size structure of ecological communitiesMethods in Ecology and Evolution 4 1167ndash1177 httpsdoiorg1011112041-210X12116
De Caacuteceres M Legendre P Valencia R Cao M Chang L-W Chuyong G hellip He F (2012) The variation of tree betadiversity across a global network of forest plots Global Ecology and Biogeography 21 1191ndash1202 httpsdoiorg101111j1466-8238201200770x
DraySBaumanDBlanchetGBorcardDClappeSGuenardGhellipWagnerHH(2018)adespatial Multivariate multiscale spatial analy-sis R package version 03-2RetrievedfromhttpsCRANR-projectorgpackage=adespatial
Dumbrell A J NelsonM Helgason T Dytham C amp Fitter A H(2010)Relativerolesofnicheandneutralprocesses instructuringa soil microbial community ISME Journal 4 337ndash345 httpsdoiorg101038ismej2009122
FaithDAustinMBelbinLampMargulesC (1985)Numericalclas-sification of profile attributes in environmental studies Journal of Environmental Management2073ndash85
Fang J Shen Z Tang ZWang XWang Z Feng J hellip Zheng C(2012) Forest community survey and the structural character-istics of forests in China Ecography 35 1059ndash1071 httpsdoiorg101111j1600-0587201300161x
FraverSampWhiteAS(2005)Disturbancedynamicsofold-growthPicea rubens forests of northern Maine Journal of Vegetation Science 16 597ndash610 httpsdoiorg101111j1654-11032005tb02401x
Gower J C (1966) Some distance properties of latent root and vec-tormethodsusedinmultivariateanalysisBiometrika53325ndash338httpsdoiorg101093biomet533-4325
Harms K E Condit R Hubbell S P amp Foster R B (2001)Habitat associations of trees and shrubs in a 50-ha neotrop-ical forest plot Journal of Ecology 89 947ndash959 httpsdoiorg101111j1365-2745200100615x
HilleRisLambers J Adler P B Harpole W S Levine J M ampMayfield M M (2012) Rethinking community assembly
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through the lens of coexistence theory Annual Review of Ecology Evolution and Systematics 43 227ndash249 httpsdoiorg101146annurev-ecolsys-110411-160411
HubbellSP(Ed)(2001)The unified theory of biodiversity and biogeogra-phyPrincetonNJPrincetonUniversityPress
Hubbell S P (2006) Neutral theory and the evolution of eco-logical equivalence Ecology 87 1387ndash1398 httpsdoiorg1018900012-9658(2006)87[1387NTATEO]20CO2
HussonFJosseJLeSampMazetJ(2015)FactoMineR Multivariate exploratory data analysis and data mining Version 1314 RetrievedfromhttpsCRANR-projectorgpackage=FactoMineR
Hutchinson G E (1961) The paradox of the plankton American Naturalist95137ndash145httpsdoiorg101086282171
KeddyPA(1992)Assemblyandresponserulestwogoalsforpredic-tive community ecology Journal of Vegetation Science3 157ndash164httpsdoiorg1023073235676
KoleffPGastonKJampLennonJJ(2003)MeasuringbetadiversityforpresencendashabsencedataJournal of Animal Ecology72367ndash382httpsdoiorg101046j1365-2656200300710x
KraftN JBComita L SChase JM SandersN J SwensonNGCrist TOhellipMyers JA (2011)Disentangling thedriversofβdiversityalong latitudinalandelevationalgradientsScience3331755ndash1758httpsdoiorg101126science1208584
LaliberteacuteEPaquetteALegendrePampBouchardA(2009)Assessingthescale-specificimportanceofnichesandotherspatialprocessesonbetadiversityacasestudyfromatemperateforestOecologia159377ndash388httpsdoiorg101007s00442-008-1214-8
Legendre P amp Anderson M J (1999) Distance-based redundancyanalysis testing multispecies responses in multifactorial ecolog-ical experiments Ecological Monographs 69 1ndash24 httpsdoiorg1018900012-9615(1999)069[0001DBRATM]20CO2
Legendre P Borcard D amp Peres-Neto P R (2005) Analyzing betadiversity partitioning the spatial variation of community com-position data Ecological Monographs 75 435ndash450 httpsdoiorg10189005-0549
LegendrePampDeCaacuteceresM(2013)BetadiversityasthevarianceofcommunitydatadissimilaritycoefficientsandpartitioningEcology Letters16951ndash963httpsdoiorg101111ele12141
LegendrePampLegendreL (2012)Numerical ecology Vol 24 (3rded)AmsterdamTheNetherlandsElsevierScienceBV
LegendrePMiXRenHMaKYuMSun I-FampHeF (2009)Partitioning beta diversity in a subtropical broad-leaved forest ofChina Ecology90663ndash674httpsdoiorg10189007-18801
MayfieldMMampLevineJM(2010)Opposingeffectsofcompetitiveex-clusiononthephylogeneticstructureofcommunitiesEcology Letters131085ndash1093httpsdoiorg101111j1461-0248201001509x
MyersJAChaseJMJimeacutenezIJoslashrgensenPMAraujo-MurakamiAPaniagua-ZambranaNampSeidelR(2013)Beta-diversityintem-perateandtropicalforestsreflectsdissimilarmechanismsofcommu-nityassemblyEcology Letters16151ndash157httpsdoiorg101111ele12021
OksanenJBlanchetFGFriendlyMKindtRLegendrePMcGlinnDhellipWagnerH(2018)vegan Community ecology package Version 25-2Retrievedfromhttpscranr-projectorgpackage=vegan
Paradis EClaude JampStrimmerK (2004)APEAnalysesof phylo-genetics and evolution inR languageBioinformatics20 289ndash290httpsdoiorg101093bioinformaticsbtg412
PeetRK (1992)Community structureand function InDCGlenn-LewinRKPeetampTTVeblen(Eds)Plant succession theory and prediction(pp103ndash140)NewYorkNYChapmanampHall
Peres-NetoPRLegendrePDraySampBorcardD(2006)Variationpartitioningofspeciesdatamatricesestimationandcomparisonof
fractionsEcology872614ndash2625httpsdoiorg1018900012-9658(2006)87[2614VPOSDM]20CO2
Punchi-Manage R Wiegand T Wiegand K Getzin S SavitriGunatillekeCV ampNimalGunatilleke IAUN(2014)EffectofspatialprocessesandtopographyonstructuringspeciesassemblagesinaSriLankandipterocarpforestEcology95376ndash386httpsdoiorg10189012-21021
RCoreTeam (2017)R A language and environment for statistical com-puting Vienna Austria R Foundation for Statistical ComputingRetrievedfromhttpswwwR-projectorg
Ricklefs R E (1990) Seabird life histories and the marine environ-mentsomespeculationsColonial Waterbirds13(1)1ndash6httpsdoiorg1023071521414
SchwinningSampWeinerJ(1998)MechanismsdeterminingthedegreeofsizeasymmetryincompetitionamongplantsOecologia113447ndash455httpsdoiorg101007s004420050397
SoilScienceSocietyofChina(Ed)(1999)Soil agricultural chemical analy-sis procedureBeijingChinaChineseAgriculturalSciencePress
van der Plas F Janzen T Ordonez A FokkemaW Reinders JEtienneRSampOlffH(2015)Anewmodelingapproachestimatesthe relative importance of different community assembly pro-cesses Ecology961502ndash1515httpsdoiorg10189014-04541
VellendM(Ed)(2017)The theory of ecological communitiesPrincetonNJPrincetonUniversityPresshttpsdoiorg1015159781400883790
Weiner J (1990) Asymmetric competition in plant popula-tions Trends in Ecology and Evolution 5 360ndash364 httpsdoiorg1010160169-5347(90)90095-U
WhittakerRH (1960)VegetationoftheSiskiyoumountainsOregonand California Ecological Monographs 30 279ndash338 httpsdoiorg1023071943563
WhittakerRH(1972)EvolutionandmeasurementofspeciesdiversityTaxon21213ndash251httpsdoiorg1023071218190
XuWHaoMWangJZhangCZhaoXampvonGadowK(2016)Soilelementsinfluencingcommunitystructureinanold-growthfor-est innortheasternChinaForests7159httpsdoiorg103390f7080159
YamakuraTKanzakiMItohAOhkuboTOginoKChaiEOKhellipAshtonPS(1995)Topographyofalarge-scaleresearchplotes-tablishedwithinatropicalrainforestatLambirSarawakTropics541ndash56httpsdoiorg103759tropics541
YanYZhangCWangYZhaoXampvonGadowK(2015)Driversofseedlingsurvivalinatemperateforestandtheirrelativeimportanceat threestagesofsuccessionEcology and Evolution54287ndash4299httpsdoiorg101002ece31688
YaoJZhangXZhangCZhaoXampvonGadowK(2016)EffectsofdensitydependenceinatemperateforestinnortheasternChinaScientific Reports632844httpsdoiorg101038srep32844
ZhangCZhaoXampvonGadowK(2014)Analyzingselectiveharvestevents inthree largeforestobservationalstudies inNorthEasternChina Forest Ecology and Management 316 100ndash109 httpsdoiorg101016jforeco201307018
ZhangCZhaoYZhaoXampvonGadowK (2012)Species-habitatassociations inanorthern temperate forest inChinaSilva Fennica46501ndash519
How to cite this articleYaoJZhangCDeCaacuteceresMLegendrePZhaoXVariationincompositionalandstructuralcomponentsofcommunityassemblageanditsdeterminantsJ Veg Sci 201930257ndash268 httpsdoiorg101111jvs12708
emspensp emsp | emsp263Journal of Vegetation Science
YAO et Al
themeantobetadiversity)arevariedamongthreecomponentsofacommunity (Figure4)Specifically342(456)290(387)and331 (441)outof750quadratscontributedmorethanthemeanto beta diversity in term of species composition (ie LCBDCOMPFigure4a)sizestructure(ieLCBDSTRFigure4g)andbothcompo-nentstogether(ieLCBDCOMPndashSTRFigure4f)respectively
34emsp|emspVariation partitioning of matrices DCOMP DSTR and DCOMPndashSTR
Theexplanatorypoweroftheenvironmentalvariablesandthespa-tialvariablesvariedforthethreetypesofmatricesandwithquadratsizes (Table 1) The variation explained by the environmental vari-ables(a+b)andbythespatialvariables(b+c)increasedsystemati-callywith increasingscale (Table1)Averagingacrossquadratsizeshabitatandspacejointlyexplained438254and341ofthevariation in compositional component structural component andthe two components together of community assemblage respec-tivelyHoweverthecontributionofthepurehabitatcomponent (a)was negligible The combination of environmental and spatial vari-ablesexplained the lowestproportionofvariation in the structuralcomponentaloneandexplainedthehighestproportionofvariationinthecompositionalcomponentalone(Table1)Boththeenvironmen-talvariables(a+b)andthepurespatialvariables(c)explainedmore
variationinthecompositionalcomponentthanthatinthestructuralcomponentsofcommunityassemblageAdditionallyourfindingsin-dicatethattheunexplained(d)fractionsdominatedthevariancepar-titioningcomputedforthestructuralcomponentYstralone(Table1)
4emsp |emspDISCUSSION
Forest ecosystems can be characterized and evaluated in terms ofboththeirstructureandcomposition(Peet1992)Inpreviousstud-ies the compositional and structural components of a communityassemblagewereusuallyanalyzedseparately(egFangetal2012)Howeverthenatureofspeciesassemblagesindicatesthateitherspe-cies composition or size structure of constituent individuals alonemayoversimplifycommunityorganization (DeCaacuteceresetal2013)Changes in structure and compositionmay be onlyweakly related(egArsenaultampBradfield1995)thereforeassessmentofbothsi-multaneouslyisimportantwhenevaluatingcommunityassemblyInthepresentstudywegeneralizedtheconventionalapproachtocom-munityassemblagebyincorporatingstructuraldataofacommunityinadditiontocompositionaldatausingtheCAPframeworkToourknowledge this is the firstpaper that investigates inasinglestudythevariationinboththecompositionalandstructuralcomponentsofcommunityassemblagessimultaneouslyaswellasitsdeterminants
F IGURE 3emspThecorrelationsbetweentheLocalContributionstoBetaDiversity(LCBD)intermsofcommunitycomposition(LCBDCOMP)structure(LCBDSTR)andbothcomponentstogether(LCBDCOMPndashSTR)ThecorrelationsofLCBDCOMPvsLCBDSTRLCBDCOMP vsLCBDCOMPndashSTRandLCBDSTR vs LCBDCOMPndashSTRwiththesizeofbinsofthestructuralvariable(binsizes=1ndash15cm)atthescaleof(a)10mtimes10m(b)20mtimes20mand(c)50mtimes50mIngraphs(a)(b)and(c)thehorizontalreddottedlineshorizontalbluelong-dashlinesandhorizontalgreensolidlinesrepresentthemeanvaluesofSpearmanrsquosrankcorrelationcoefficientr across 1ndash15 cm binsizeofLCBDCOMPvsLCBDSTRLCBDCOMPvsLCBDCOMPndashSTRLCBDSTR vs LCBDCOMPndashSTRrespectively(d)BoxplotsfortheSpearmanrsquosrankcorrelationcoefficientrbetweenthepairwiseofthethreekindsofLCBDof1ndash15cmbinsizesatdifferentquadratsizes[Colourfigurecanbeviewedatwileyonlinelibrarycom]
264emsp |emsp emspenspJournal of Vegetation Science
YAO et Al
We found thatbothoverall betadiversity (BD) and the rela-tive contribution of sampling units to beta diversity (LCBD) de-pended on whether the species composition size structure orbothcomponentstogetherhadbeentakenintoaccountBetadi-versity partitioning indicated that the explanatory power of the
environmental and the spatial variables also varied widely withdifferentcomponentsofacommunityOur resultshighlight thatconsideringboth species compositional and size structural com-ponentsmaybeamorecomprehensivewaytodescribethecom-munityorganization
emspensp emsp | emsp265Journal of Vegetation Science
YAO et Al
41emsp|emspStructural and compositional components of forest variation
The framework of CAP allowed us to incorporate the distribu-tionof individualtreesize intotheanalysisofcommunityassem-blage thusmaking it possible toquantify the spatial variationofcommunitystructurebetadiversityEvensosuchstructuralbetadiversitycanbequantified independentlyor incombinationwithspecies composition TheBDCOMPndashSTR is the largest among thesethreecomponentsofbetadiversity indicating thatapplyingspe-ciescompositionaloneorsizestructurealonetoassessthebetadi-versitymayunderestimatethevariationofassemblages(Figure2)ThevaluesofBDCOMPareclosertotheBDCOMPndashSTRvaluesthanthatofBDSTR(theBDSTRvaluesarerelativelysmallFigure2)ThusasfarasourCAPframework isconcerned it seemsmoreappropri-atetoquantifybetadiversityusingthespeciescomposition indi-viduallythanusingthesizestructureindividuallyNeverthelessifstructureprovidesindependentinformationandisdeemedimpor-tantoneshouldincorporateitinBDassessmentAsbetadiversityindiceswerecalculatedfromdissimilaritymatrices thestructuralcomponent of beta diversity depended on the weight given to
structural vs compositional informationwhencalculatingdissimi-larity(Figure2andashc)Thelargerthebinsizes(iethesmallerweightgiventospeciesstructuralinformation)thecloserBDCOMPndashSTR val-uesapproachedthevaluesofBDCOMP(Figure2andashc)Ifthebinsizesare big enough theBDCOMPndashSTR value and theBDCOMP value are expected to converge at a certain size of dbh binNeverthelessconsideringthenecessityofcomprehensiveassessmentofbetadi-versityweadvocateforsmallbinsizesastheyprovidemoreinde-pendentstructuralinformationFinallyitisimportanttonotethatthisforestplotincludes47differenttreespecieswhichresultsinastrongrelativeweightofthecompositionalcomponentofBDCOMPndashSTRwhenusingtheCAPframeworkRepeatingourstudyinforestswith lower species richness or in this forest but using a coarsercompositional resolution (eg at the family level)would result inlargerrelativeweightofthestructuralcomponent
42emsp|emspLocal contributions to beta diversity in terms of community composition and structure
EcologicallyLCBDindicesonlyrepresentthedegreeofuniquenessofthesamplingunitsintermsofcommunitycomposition(Legendre
F IGURE 4emspMapsof30-ha(500mtimes600m)plotshowingthelocalcontributionstobetadiversity(LCBD)intermsofcommunitycompositionandstructurefor750quadrats(20mtimes20m)ThesolidcirclesrepresentthevaluesofLCBDiforeachithquadrat(i =[1750])(a)ThemapofLCBDsonlyintermsofspeciescompositionNotethatthesizestructureofindividuals(iedbh)isnotconsideredwhencalculatingtheLCBDCOMPthusthevaluesofLCBDCOMPwerenotaffectedbythesizeofthebinsofthestructuralvariable(b)ndash(e)ThetwoextremecasesoftheLCBDmap(b)and(c)givingthemostweighttothestructuralcomponentandcorrespondinglytheleastweighttothecompositionalcomponent(ie1-cmbinsize)and(d)and(e)givingthemostweighttothecompositionalcomponentandcorrespondinglytheleastweighttothestructuralcomponent(ie15-cmbinsize)(f)and(g)MapsofLCBDsafteraveragingacrossdbhbinsizesSizeofthecirclesisproportionaltotheLCBDivaluesTheblackandgreysolidcirclesrepresentthesiteswithLCBDvalueshigherandlowerthanthemeanrespectively
TABLE 1emspVariationpartitioningresultsforthreetypesofmatricesatdifferentscalesofquadratsThepartitioningisbasedonadjustedR2 statisticsasrecommendedbyPeres-Netoetal(2006)
Quadrat sizes (a) (b) (c) (d) (a + b) (b + c) (a + b + c)
YCOMP
10mtimes10m 00044 00796 01361 07799 00840 02157 02201
20mtimes20m 00028 01783 02862 05327 01811 04645 04673
50mtimes50m 00050 02995 03229 03726 03045 06224 06274
YSTR
10mtimes10m 00123 00131 00296 09450 00254 00427 00550
20mtimes20m 00013 00907 01652 07428 00920 02560 02572
50mtimes50m 00029 02300 02163 05509 02328 04463 04492
YCOMPndashSTR
10mtimes10m 00055 00564 00932 08449 00619 01496 01551
20mtimes20m 00028 01576 02559 05837 01604 04135 04163
50mtimes50m 00013 02543 01948 05496 02556 04492 04504
Fractions(a)ndash(d)(adjustedR2statistics)(a)variationexplainedbytheenvironmentalvariablesaftercontrollingforthespatialstructure(b)variationexplainedbythespatiallystructuredenvironmentalvariables(c)spatiallystructuredvariationexplainedbypurespaceaftercontrollingforenviron-mentalvariation(d)residualvariationEnvironmentalvariablesusedtocomputefraction(a+b)dbMEMeigenfunctionsweretheexplanatoryvaria-blesusedtocomputefraction(b+c)Only5-cm-diameterclasses(iebinsize=5cm)asthestructuralvariablewereusedtocalculatetheYSTR and YCOMPndashSTR
266emsp |emsp emspenspJournal of Vegetation Science
YAO et Al
amp De Caacuteceres 2013) However natural communities may exhibitsimilarspeciescompositionsbutdifferinotherfeaturessuchasthesizestructureof individuals Inthepresentstudyweassessedthedegreeofuniquenessofthequadratsintermsnotonlyoftheirspe-ciescompositionbutalsooftheirsizestructureandbyusingbothcomponentstogetherThedegreeofuniquenessofquadratsintermsofcommunitycompositionindividuallyhadaveryweakcorrelationwithuniqueness in termsof size structure individually (LCBDCOMP vsLCBDSTRFigure3) indicating that sites that areunique in spe-cies composition are not necessarily unique in size structure andvice versa Additionally we found that the spatial distribution ofsiteswithhighLCBDvaluesisdifferentforthetwocomponentsofacommunitywith siteswithhighstructuraluniquenessoccurringinsmallforestpatches(Figure4)Alltheseresultsreinforcetheideathatconsideringbothspeciescompositionalandsizestructuralcom-ponentsmaybeamorecomprehensivewaytodescribethecommu-nityorganizationHoweverifweacceptthefactthatsitesthatareuniqueintermsofsizestructurearetheresultofgapdynamics(seebelow) the non-zero correlation between LCBDCOMP vs LCBDSTR mayindicatethatforestgapsmaybecolonizedbyspeciesthatmaylaterbesuppressedastheforestgrowssothatrecentforestgapshaveadifferentspeciescompositionthanclosedforeststructures(Comitaetal2009)
43emsp|emspPartitioning the structural and compositional components of beta diversity
About344ofthevariationincommunityassemblagewasdeter-minedbyenvironmentalandspatialvariablesdependingonthescale(quadratsize)andonwhichcomponentsofcommunityassemblage(ie compositional component structural component and takingbothcomponents together)were taken intoaccountThispropor-tion isslightly lowerthanthevaluesfound instudiesbyLegendreetal (2009)andPunchi-Manageetal (2014)Areasonforthisre-sult is thatwe incorporateddifferencesboth insizestructureandspeciescomposition intocommunityassemblagesratherthanonlyusingtheconventionalspeciescompositiondataWhenthespeciescomposition and size structure of the constituent individuals areincorporatedintothecommunityatthesametimemorevariationwilloccurincommunityassemblagesInourstudyhabitat(a+b)ex-plainedmorevariationinthecompositionalcomponent(190)thaninthestructuralcomponent(117)ofthecommunityassemblagesBetadiversitypartitioningindicatedthatthevariationinthestruc-turalcomponentislessdictatedbyenvironmentthanvariationinthecompositional componentWe here hypothesize that canopy gapdynamicswillbethepotentialdriversofstructuralvariationWinterinourstudyareaiscoldandlongwithalongsnowfallperiodThesnowfallperiodlastsforhalfayearandthesnowcoverthicknessinmountainousareasreaches40ndash50cmWehypothesizethatpulsesofmoderate-severity disturbancesmay be caused by snowstormsin our site In the absence of stand-replacing disturbances forestcanopiesareopenedperiodicallybythedeathofsinglebigtreesorsmallgroupsofadulttreescreatingcanopygapsSnowstormsmay
havealteredforeststructurebyselectivelyremovinglargercanopytrees Environmental selection of individuals shapes compositionbydeterminingthefitnessof individualswhereasstructuralvaria-tionmayhavesomerelationshipwithenvironmentalconditions(ielargertreesinsiteswherelargersizesaresupportedforenergyorwateravailability)butingeneralisthereflectionofdifferentstagesaroundgapdynamicsPreviousstudiesareconsistentwithourfind-ingsFraverandWhite(2005)forinstancefoundthattherepeatedmoderate-severity disturbances (iewindstorms) causeddramaticstructural changes they caused no significant change in speciescomposition
Becausetherelativeimportanceofbothnicheandneutralthe-oryinstructuringcommunitiesvarieswithspatialscale(Legendreetal 2009 Punchi-Manage etal 2014) we conducted scale-dependentanalyses InsharpcontrasttothefindingbyLegendreetal(2009)forabroad-leavedforestinChinawefoundthattheproportionofundeterminedvariation incompositionalandstruc-turalcomponentsofcommunityassemblageswasveryhighatfinespatialscales(upto945forthestructuralcomponent780forthecompositionalcomponentand844forbothcomponentsto-gether)butdecreasedsystematicallywith increasingspatial scale(up to a minimum of 373 for compositional component at the50-mscale)TheseresultsareinlinewiththefindingsbyPunchi-Manageetal(2014)inaSriLankandipterocarpforestandbyDeCaacuteceresetal(2012)inacomparisonofseveralforestsOntheonehandthehighproportionofunexplainedvariationmayberelatedtounmeasuredandnotspatially-structuredbiologicalorenviron-mentalvariablesXuetal(2016)showedthatthesoilnutrientsintheupper(0ndash10cmconsideredinourstudy)andlowersoillayers(10ndash20cm)andtheheavymetalelements(CuNiCdAsPbZnMoCrMnandMg)inthesoilshowastrongcorrelationwiththespeciesspatialdistributionsatJiaoheThismaypartlyexplainwhythepureenvironmentalvariable(a)explainedsuchlittlevariationinthecommunityassemblagesAnotherexplanationforthehighpro-portionofunexplainedvariationisthatitmaybeduetostochasticprocesseswhich related to theneutral theoryassuming that thedynamicsofpopulationsareprimarilydrivenbyecologicaldriftanddispersal(Legendreetal2009)Ontheotherhandtheproportionofundeterminedvariationincompositionalandstructuralcompo-nents of community assemblages decreased systematically withincreasingspatialscaleThismayindicatethatcommunityassem-blageishighlystochasticintermsofspeciescompositionandtreesizedistributionatfinescales (ie10-mscale)butthisfinescalestochasticitytendstosmoothoutatthe50-mscalewheremoreconsistent habitat-driven species assemblages emerged Whenvariance partitioning is conducted on the structural componentalonetheunexplained(d)fractionisdominantWhiletheinfluenceofenvironmental factorsonsizestructuremaybe less importantthan for thecompositionalcomponent theeffectof localdistur-bances (eg appearanceof canopygaps resulting frommortalityof largetrees)results inrandomspatialpatternsofquadratswithrather different structure contributing to a large unexplainedfraction
emspensp emsp | emsp267Journal of Vegetation Science
YAO et Al
5emsp |emspCONCLUSIONS
SpeciescompositionandsizestructurearethetwoessentialfeaturesofacommunityOnlyoneofthemindividuallymaybeinsufficienttodescribetheorganizationoftreespeciesassemblagesDefiningandquantifyingbetadiversityusingthespeciescompositionalonemaybesufficienttheninmanyoccasionsNeverthelessspeciescompo-sition is justonedimensionofbiodiversity variation in size struc-tureisalsoimportantIncorporatingstructuraldatainbetadiversityassessmentsallowsecologiststomakeuseofvaluableinformationcollectedduringfieldsurveysIfitisavailablethereisnoreasontoignorethewealthofinformationaboutsizestructurewhencompar-ingspeciesassemblagesOurstudyhighlightstheneedtoincorpo-ratethestructuraldataofacommunityinadditiontocompositionaldatawhenquantifyingandanalyzingbetadiversityFinallyourre-sults suggest thatbothdeterministicandstochasticprocessesarerelevantdeterminantsofcompositionalandstructuralcomponentsof communityassemblages inour temperate forestNeverthelesstheseprocessesarescale-andorresolution-dependent
ACKNOWLEDGEMENTS
WewouldliketothankHeHuaijiangDingShengjianNiRuiqiangandZuoQiangandseveralothersforassistingwiththefielddatacollectionAuthorsaregratefultotheJiaoheManagementBureauof the Forest Experimental Zone for permission to undertake thefieldworkWealsothankthreeanonymousreviewersforprovidingthevaluablecomments
CONFLICTS OF INTEREST
Theauthorsdeclarenocompetingfinancialinterests
DATA ACCESSIBILITY
DataownershipbelongstoBeijingForestryUniversitywhosestaffconductedtheanalysesandwrotethemanuscripthttpwwwbjfueducn
ORCID
Jie Yao httpsorcidorg0000-0002-8606-8158
REFERENCES
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ArsenaultAampBradfieldGE (1995)Structuralndashcompositionalvaria-tioninthreeage-classesoftemperaterainforestsinsoutherncoastalBritishColumbiaCanadian Journal of Botany7354ndash64httpsdoiorg101139b95-007
Borcard D amp Legendre P (1994) Environmental control and spatialstructureinecologicalcommunitiesanexampleusingoribatidmites(Acari Oribatei) Environmental and Ecological Statistics 1 37ndash61httpsdoiorg101007BF00714196
Borcard D Legendre P Avois-Jacquet C amp Tuomisto H (2004)DissectingthespatialstructureofecologicaldataatmultiplescalesEcology851826ndash1832httpsdoiorg10189003-3111
BorcardDLegendrePampDrapeauP(1992)PartiallingoutthespatialcomponentofecologicalvariationEcology731045ndash1055httpsdoiorg1023071940179
Caswell H (1976) Community structure a neutral model anal-ysis Ecological Monographs 46 327ndash354 httpsdoiorg1023071942257
ChaseJM(2010)Stochasticcommunityassemblycauseshigherbiodi-versityinmoreproductiveenvironmentsScience3281388ndash1391httpsdoiorg101126science1187820
ChaveJ(2004)NeutraltheoryandcommunityecologyEcology Letters7241ndash253httpsdoiorg101111j1461-0248200300566x
Chesson P (2000) Mechanisms of maintenance of species diversityAnnual Review of Ecology and Systematics31343ndash366httpsdoiorg101146annurevecolsys311343
ComitaLSUriarteMThompsonJJonckheereICanhamCDampZimmermanJK(2009)Abioticandbioticdriversofseedlingsur-vival inahurricane-impacted tropical forestJournal of Ecology971346ndash1359httpsdoiorg101111j1365-2745200901551x
DeCaacuteceresMFontXampOlivaF(2010)Themanagementofvegeta-tionclassificationswithfuzzyclusteringJournal of Vegetation Science211138ndash1151httpsdoiorg101111j1654-1103201001211x
De Caacuteceres M Legendre P amp He F (2013) Dissimilarity mea-surements and the size structure of ecological communitiesMethods in Ecology and Evolution 4 1167ndash1177 httpsdoiorg1011112041-210X12116
De Caacuteceres M Legendre P Valencia R Cao M Chang L-W Chuyong G hellip He F (2012) The variation of tree betadiversity across a global network of forest plots Global Ecology and Biogeography 21 1191ndash1202 httpsdoiorg101111j1466-8238201200770x
DraySBaumanDBlanchetGBorcardDClappeSGuenardGhellipWagnerHH(2018)adespatial Multivariate multiscale spatial analy-sis R package version 03-2RetrievedfromhttpsCRANR-projectorgpackage=adespatial
Dumbrell A J NelsonM Helgason T Dytham C amp Fitter A H(2010)Relativerolesofnicheandneutralprocesses instructuringa soil microbial community ISME Journal 4 337ndash345 httpsdoiorg101038ismej2009122
FaithDAustinMBelbinLampMargulesC (1985)Numericalclas-sification of profile attributes in environmental studies Journal of Environmental Management2073ndash85
Fang J Shen Z Tang ZWang XWang Z Feng J hellip Zheng C(2012) Forest community survey and the structural character-istics of forests in China Ecography 35 1059ndash1071 httpsdoiorg101111j1600-0587201300161x
FraverSampWhiteAS(2005)Disturbancedynamicsofold-growthPicea rubens forests of northern Maine Journal of Vegetation Science 16 597ndash610 httpsdoiorg101111j1654-11032005tb02401x
Gower J C (1966) Some distance properties of latent root and vec-tormethodsusedinmultivariateanalysisBiometrika53325ndash338httpsdoiorg101093biomet533-4325
Harms K E Condit R Hubbell S P amp Foster R B (2001)Habitat associations of trees and shrubs in a 50-ha neotrop-ical forest plot Journal of Ecology 89 947ndash959 httpsdoiorg101111j1365-2745200100615x
HilleRisLambers J Adler P B Harpole W S Levine J M ampMayfield M M (2012) Rethinking community assembly
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through the lens of coexistence theory Annual Review of Ecology Evolution and Systematics 43 227ndash249 httpsdoiorg101146annurev-ecolsys-110411-160411
HubbellSP(Ed)(2001)The unified theory of biodiversity and biogeogra-phyPrincetonNJPrincetonUniversityPress
Hubbell S P (2006) Neutral theory and the evolution of eco-logical equivalence Ecology 87 1387ndash1398 httpsdoiorg1018900012-9658(2006)87[1387NTATEO]20CO2
HussonFJosseJLeSampMazetJ(2015)FactoMineR Multivariate exploratory data analysis and data mining Version 1314 RetrievedfromhttpsCRANR-projectorgpackage=FactoMineR
Hutchinson G E (1961) The paradox of the plankton American Naturalist95137ndash145httpsdoiorg101086282171
KeddyPA(1992)Assemblyandresponserulestwogoalsforpredic-tive community ecology Journal of Vegetation Science3 157ndash164httpsdoiorg1023073235676
KoleffPGastonKJampLennonJJ(2003)MeasuringbetadiversityforpresencendashabsencedataJournal of Animal Ecology72367ndash382httpsdoiorg101046j1365-2656200300710x
KraftN JBComita L SChase JM SandersN J SwensonNGCrist TOhellipMyers JA (2011)Disentangling thedriversofβdiversityalong latitudinalandelevationalgradientsScience3331755ndash1758httpsdoiorg101126science1208584
LaliberteacuteEPaquetteALegendrePampBouchardA(2009)Assessingthescale-specificimportanceofnichesandotherspatialprocessesonbetadiversityacasestudyfromatemperateforestOecologia159377ndash388httpsdoiorg101007s00442-008-1214-8
Legendre P amp Anderson M J (1999) Distance-based redundancyanalysis testing multispecies responses in multifactorial ecolog-ical experiments Ecological Monographs 69 1ndash24 httpsdoiorg1018900012-9615(1999)069[0001DBRATM]20CO2
Legendre P Borcard D amp Peres-Neto P R (2005) Analyzing betadiversity partitioning the spatial variation of community com-position data Ecological Monographs 75 435ndash450 httpsdoiorg10189005-0549
LegendrePampDeCaacuteceresM(2013)BetadiversityasthevarianceofcommunitydatadissimilaritycoefficientsandpartitioningEcology Letters16951ndash963httpsdoiorg101111ele12141
LegendrePampLegendreL (2012)Numerical ecology Vol 24 (3rded)AmsterdamTheNetherlandsElsevierScienceBV
LegendrePMiXRenHMaKYuMSun I-FampHeF (2009)Partitioning beta diversity in a subtropical broad-leaved forest ofChina Ecology90663ndash674httpsdoiorg10189007-18801
MayfieldMMampLevineJM(2010)Opposingeffectsofcompetitiveex-clusiononthephylogeneticstructureofcommunitiesEcology Letters131085ndash1093httpsdoiorg101111j1461-0248201001509x
MyersJAChaseJMJimeacutenezIJoslashrgensenPMAraujo-MurakamiAPaniagua-ZambranaNampSeidelR(2013)Beta-diversityintem-perateandtropicalforestsreflectsdissimilarmechanismsofcommu-nityassemblyEcology Letters16151ndash157httpsdoiorg101111ele12021
OksanenJBlanchetFGFriendlyMKindtRLegendrePMcGlinnDhellipWagnerH(2018)vegan Community ecology package Version 25-2Retrievedfromhttpscranr-projectorgpackage=vegan
Paradis EClaude JampStrimmerK (2004)APEAnalysesof phylo-genetics and evolution inR languageBioinformatics20 289ndash290httpsdoiorg101093bioinformaticsbtg412
PeetRK (1992)Community structureand function InDCGlenn-LewinRKPeetampTTVeblen(Eds)Plant succession theory and prediction(pp103ndash140)NewYorkNYChapmanampHall
Peres-NetoPRLegendrePDraySampBorcardD(2006)Variationpartitioningofspeciesdatamatricesestimationandcomparisonof
fractionsEcology872614ndash2625httpsdoiorg1018900012-9658(2006)87[2614VPOSDM]20CO2
Punchi-Manage R Wiegand T Wiegand K Getzin S SavitriGunatillekeCV ampNimalGunatilleke IAUN(2014)EffectofspatialprocessesandtopographyonstructuringspeciesassemblagesinaSriLankandipterocarpforestEcology95376ndash386httpsdoiorg10189012-21021
RCoreTeam (2017)R A language and environment for statistical com-puting Vienna Austria R Foundation for Statistical ComputingRetrievedfromhttpswwwR-projectorg
Ricklefs R E (1990) Seabird life histories and the marine environ-mentsomespeculationsColonial Waterbirds13(1)1ndash6httpsdoiorg1023071521414
SchwinningSampWeinerJ(1998)MechanismsdeterminingthedegreeofsizeasymmetryincompetitionamongplantsOecologia113447ndash455httpsdoiorg101007s004420050397
SoilScienceSocietyofChina(Ed)(1999)Soil agricultural chemical analy-sis procedureBeijingChinaChineseAgriculturalSciencePress
van der Plas F Janzen T Ordonez A FokkemaW Reinders JEtienneRSampOlffH(2015)Anewmodelingapproachestimatesthe relative importance of different community assembly pro-cesses Ecology961502ndash1515httpsdoiorg10189014-04541
VellendM(Ed)(2017)The theory of ecological communitiesPrincetonNJPrincetonUniversityPresshttpsdoiorg1015159781400883790
Weiner J (1990) Asymmetric competition in plant popula-tions Trends in Ecology and Evolution 5 360ndash364 httpsdoiorg1010160169-5347(90)90095-U
WhittakerRH (1960)VegetationoftheSiskiyoumountainsOregonand California Ecological Monographs 30 279ndash338 httpsdoiorg1023071943563
WhittakerRH(1972)EvolutionandmeasurementofspeciesdiversityTaxon21213ndash251httpsdoiorg1023071218190
XuWHaoMWangJZhangCZhaoXampvonGadowK(2016)Soilelementsinfluencingcommunitystructureinanold-growthfor-est innortheasternChinaForests7159httpsdoiorg103390f7080159
YamakuraTKanzakiMItohAOhkuboTOginoKChaiEOKhellipAshtonPS(1995)Topographyofalarge-scaleresearchplotes-tablishedwithinatropicalrainforestatLambirSarawakTropics541ndash56httpsdoiorg103759tropics541
YanYZhangCWangYZhaoXampvonGadowK(2015)Driversofseedlingsurvivalinatemperateforestandtheirrelativeimportanceat threestagesofsuccessionEcology and Evolution54287ndash4299httpsdoiorg101002ece31688
YaoJZhangXZhangCZhaoXampvonGadowK(2016)EffectsofdensitydependenceinatemperateforestinnortheasternChinaScientific Reports632844httpsdoiorg101038srep32844
ZhangCZhaoXampvonGadowK(2014)Analyzingselectiveharvestevents inthree largeforestobservationalstudies inNorthEasternChina Forest Ecology and Management 316 100ndash109 httpsdoiorg101016jforeco201307018
ZhangCZhaoYZhaoXampvonGadowK (2012)Species-habitatassociations inanorthern temperate forest inChinaSilva Fennica46501ndash519
How to cite this articleYaoJZhangCDeCaacuteceresMLegendrePZhaoXVariationincompositionalandstructuralcomponentsofcommunityassemblageanditsdeterminantsJ Veg Sci 201930257ndash268 httpsdoiorg101111jvs12708
264emsp |emsp emspenspJournal of Vegetation Science
YAO et Al
We found thatbothoverall betadiversity (BD) and the rela-tive contribution of sampling units to beta diversity (LCBD) de-pended on whether the species composition size structure orbothcomponentstogetherhadbeentakenintoaccountBetadi-versity partitioning indicated that the explanatory power of the
environmental and the spatial variables also varied widely withdifferentcomponentsofacommunityOur resultshighlight thatconsideringboth species compositional and size structural com-ponentsmaybeamorecomprehensivewaytodescribethecom-munityorganization
emspensp emsp | emsp265Journal of Vegetation Science
YAO et Al
41emsp|emspStructural and compositional components of forest variation
The framework of CAP allowed us to incorporate the distribu-tionof individualtreesize intotheanalysisofcommunityassem-blage thusmaking it possible toquantify the spatial variationofcommunitystructurebetadiversityEvensosuchstructuralbetadiversitycanbequantified independentlyor incombinationwithspecies composition TheBDCOMPndashSTR is the largest among thesethreecomponentsofbetadiversity indicating thatapplyingspe-ciescompositionaloneorsizestructurealonetoassessthebetadi-versitymayunderestimatethevariationofassemblages(Figure2)ThevaluesofBDCOMPareclosertotheBDCOMPndashSTRvaluesthanthatofBDSTR(theBDSTRvaluesarerelativelysmallFigure2)ThusasfarasourCAPframework isconcerned it seemsmoreappropri-atetoquantifybetadiversityusingthespeciescomposition indi-viduallythanusingthesizestructureindividuallyNeverthelessifstructureprovidesindependentinformationandisdeemedimpor-tantoneshouldincorporateitinBDassessmentAsbetadiversityindiceswerecalculatedfromdissimilaritymatrices thestructuralcomponent of beta diversity depended on the weight given to
structural vs compositional informationwhencalculatingdissimi-larity(Figure2andashc)Thelargerthebinsizes(iethesmallerweightgiventospeciesstructuralinformation)thecloserBDCOMPndashSTR val-uesapproachedthevaluesofBDCOMP(Figure2andashc)Ifthebinsizesare big enough theBDCOMPndashSTR value and theBDCOMP value are expected to converge at a certain size of dbh binNeverthelessconsideringthenecessityofcomprehensiveassessmentofbetadi-versityweadvocateforsmallbinsizesastheyprovidemoreinde-pendentstructuralinformationFinallyitisimportanttonotethatthisforestplotincludes47differenttreespecieswhichresultsinastrongrelativeweightofthecompositionalcomponentofBDCOMPndashSTRwhenusingtheCAPframeworkRepeatingourstudyinforestswith lower species richness or in this forest but using a coarsercompositional resolution (eg at the family level)would result inlargerrelativeweightofthestructuralcomponent
42emsp|emspLocal contributions to beta diversity in terms of community composition and structure
EcologicallyLCBDindicesonlyrepresentthedegreeofuniquenessofthesamplingunitsintermsofcommunitycomposition(Legendre
F IGURE 4emspMapsof30-ha(500mtimes600m)plotshowingthelocalcontributionstobetadiversity(LCBD)intermsofcommunitycompositionandstructurefor750quadrats(20mtimes20m)ThesolidcirclesrepresentthevaluesofLCBDiforeachithquadrat(i =[1750])(a)ThemapofLCBDsonlyintermsofspeciescompositionNotethatthesizestructureofindividuals(iedbh)isnotconsideredwhencalculatingtheLCBDCOMPthusthevaluesofLCBDCOMPwerenotaffectedbythesizeofthebinsofthestructuralvariable(b)ndash(e)ThetwoextremecasesoftheLCBDmap(b)and(c)givingthemostweighttothestructuralcomponentandcorrespondinglytheleastweighttothecompositionalcomponent(ie1-cmbinsize)and(d)and(e)givingthemostweighttothecompositionalcomponentandcorrespondinglytheleastweighttothestructuralcomponent(ie15-cmbinsize)(f)and(g)MapsofLCBDsafteraveragingacrossdbhbinsizesSizeofthecirclesisproportionaltotheLCBDivaluesTheblackandgreysolidcirclesrepresentthesiteswithLCBDvalueshigherandlowerthanthemeanrespectively
TABLE 1emspVariationpartitioningresultsforthreetypesofmatricesatdifferentscalesofquadratsThepartitioningisbasedonadjustedR2 statisticsasrecommendedbyPeres-Netoetal(2006)
Quadrat sizes (a) (b) (c) (d) (a + b) (b + c) (a + b + c)
YCOMP
10mtimes10m 00044 00796 01361 07799 00840 02157 02201
20mtimes20m 00028 01783 02862 05327 01811 04645 04673
50mtimes50m 00050 02995 03229 03726 03045 06224 06274
YSTR
10mtimes10m 00123 00131 00296 09450 00254 00427 00550
20mtimes20m 00013 00907 01652 07428 00920 02560 02572
50mtimes50m 00029 02300 02163 05509 02328 04463 04492
YCOMPndashSTR
10mtimes10m 00055 00564 00932 08449 00619 01496 01551
20mtimes20m 00028 01576 02559 05837 01604 04135 04163
50mtimes50m 00013 02543 01948 05496 02556 04492 04504
Fractions(a)ndash(d)(adjustedR2statistics)(a)variationexplainedbytheenvironmentalvariablesaftercontrollingforthespatialstructure(b)variationexplainedbythespatiallystructuredenvironmentalvariables(c)spatiallystructuredvariationexplainedbypurespaceaftercontrollingforenviron-mentalvariation(d)residualvariationEnvironmentalvariablesusedtocomputefraction(a+b)dbMEMeigenfunctionsweretheexplanatoryvaria-blesusedtocomputefraction(b+c)Only5-cm-diameterclasses(iebinsize=5cm)asthestructuralvariablewereusedtocalculatetheYSTR and YCOMPndashSTR
266emsp |emsp emspenspJournal of Vegetation Science
YAO et Al
amp De Caacuteceres 2013) However natural communities may exhibitsimilarspeciescompositionsbutdifferinotherfeaturessuchasthesizestructureof individuals Inthepresentstudyweassessedthedegreeofuniquenessofthequadratsintermsnotonlyoftheirspe-ciescompositionbutalsooftheirsizestructureandbyusingbothcomponentstogetherThedegreeofuniquenessofquadratsintermsofcommunitycompositionindividuallyhadaveryweakcorrelationwithuniqueness in termsof size structure individually (LCBDCOMP vsLCBDSTRFigure3) indicating that sites that areunique in spe-cies composition are not necessarily unique in size structure andvice versa Additionally we found that the spatial distribution ofsiteswithhighLCBDvaluesisdifferentforthetwocomponentsofacommunitywith siteswithhighstructuraluniquenessoccurringinsmallforestpatches(Figure4)Alltheseresultsreinforcetheideathatconsideringbothspeciescompositionalandsizestructuralcom-ponentsmaybeamorecomprehensivewaytodescribethecommu-nityorganizationHoweverifweacceptthefactthatsitesthatareuniqueintermsofsizestructurearetheresultofgapdynamics(seebelow) the non-zero correlation between LCBDCOMP vs LCBDSTR mayindicatethatforestgapsmaybecolonizedbyspeciesthatmaylaterbesuppressedastheforestgrowssothatrecentforestgapshaveadifferentspeciescompositionthanclosedforeststructures(Comitaetal2009)
43emsp|emspPartitioning the structural and compositional components of beta diversity
About344ofthevariationincommunityassemblagewasdeter-minedbyenvironmentalandspatialvariablesdependingonthescale(quadratsize)andonwhichcomponentsofcommunityassemblage(ie compositional component structural component and takingbothcomponents together)were taken intoaccountThispropor-tion isslightly lowerthanthevaluesfound instudiesbyLegendreetal (2009)andPunchi-Manageetal (2014)Areasonforthisre-sult is thatwe incorporateddifferencesboth insizestructureandspeciescomposition intocommunityassemblagesratherthanonlyusingtheconventionalspeciescompositiondataWhenthespeciescomposition and size structure of the constituent individuals areincorporatedintothecommunityatthesametimemorevariationwilloccurincommunityassemblagesInourstudyhabitat(a+b)ex-plainedmorevariationinthecompositionalcomponent(190)thaninthestructuralcomponent(117)ofthecommunityassemblagesBetadiversitypartitioningindicatedthatthevariationinthestruc-turalcomponentislessdictatedbyenvironmentthanvariationinthecompositional componentWe here hypothesize that canopy gapdynamicswillbethepotentialdriversofstructuralvariationWinterinourstudyareaiscoldandlongwithalongsnowfallperiodThesnowfallperiodlastsforhalfayearandthesnowcoverthicknessinmountainousareasreaches40ndash50cmWehypothesizethatpulsesofmoderate-severity disturbancesmay be caused by snowstormsin our site In the absence of stand-replacing disturbances forestcanopiesareopenedperiodicallybythedeathofsinglebigtreesorsmallgroupsofadulttreescreatingcanopygapsSnowstormsmay
havealteredforeststructurebyselectivelyremovinglargercanopytrees Environmental selection of individuals shapes compositionbydeterminingthefitnessof individualswhereasstructuralvaria-tionmayhavesomerelationshipwithenvironmentalconditions(ielargertreesinsiteswherelargersizesaresupportedforenergyorwateravailability)butingeneralisthereflectionofdifferentstagesaroundgapdynamicsPreviousstudiesareconsistentwithourfind-ingsFraverandWhite(2005)forinstancefoundthattherepeatedmoderate-severity disturbances (iewindstorms) causeddramaticstructural changes they caused no significant change in speciescomposition
Becausetherelativeimportanceofbothnicheandneutralthe-oryinstructuringcommunitiesvarieswithspatialscale(Legendreetal 2009 Punchi-Manage etal 2014) we conducted scale-dependentanalyses InsharpcontrasttothefindingbyLegendreetal(2009)forabroad-leavedforestinChinawefoundthattheproportionofundeterminedvariation incompositionalandstruc-turalcomponentsofcommunityassemblageswasveryhighatfinespatialscales(upto945forthestructuralcomponent780forthecompositionalcomponentand844forbothcomponentsto-gether)butdecreasedsystematicallywith increasingspatial scale(up to a minimum of 373 for compositional component at the50-mscale)TheseresultsareinlinewiththefindingsbyPunchi-Manageetal(2014)inaSriLankandipterocarpforestandbyDeCaacuteceresetal(2012)inacomparisonofseveralforestsOntheonehandthehighproportionofunexplainedvariationmayberelatedtounmeasuredandnotspatially-structuredbiologicalorenviron-mentalvariablesXuetal(2016)showedthatthesoilnutrientsintheupper(0ndash10cmconsideredinourstudy)andlowersoillayers(10ndash20cm)andtheheavymetalelements(CuNiCdAsPbZnMoCrMnandMg)inthesoilshowastrongcorrelationwiththespeciesspatialdistributionsatJiaoheThismaypartlyexplainwhythepureenvironmentalvariable(a)explainedsuchlittlevariationinthecommunityassemblagesAnotherexplanationforthehighpro-portionofunexplainedvariationisthatitmaybeduetostochasticprocesseswhich related to theneutral theoryassuming that thedynamicsofpopulationsareprimarilydrivenbyecologicaldriftanddispersal(Legendreetal2009)Ontheotherhandtheproportionofundeterminedvariationincompositionalandstructuralcompo-nents of community assemblages decreased systematically withincreasingspatialscaleThismayindicatethatcommunityassem-blageishighlystochasticintermsofspeciescompositionandtreesizedistributionatfinescales (ie10-mscale)butthisfinescalestochasticitytendstosmoothoutatthe50-mscalewheremoreconsistent habitat-driven species assemblages emerged Whenvariance partitioning is conducted on the structural componentalonetheunexplained(d)fractionisdominantWhiletheinfluenceofenvironmental factorsonsizestructuremaybe less importantthan for thecompositionalcomponent theeffectof localdistur-bances (eg appearanceof canopygaps resulting frommortalityof largetrees)results inrandomspatialpatternsofquadratswithrather different structure contributing to a large unexplainedfraction
emspensp emsp | emsp267Journal of Vegetation Science
YAO et Al
5emsp |emspCONCLUSIONS
SpeciescompositionandsizestructurearethetwoessentialfeaturesofacommunityOnlyoneofthemindividuallymaybeinsufficienttodescribetheorganizationoftreespeciesassemblagesDefiningandquantifyingbetadiversityusingthespeciescompositionalonemaybesufficienttheninmanyoccasionsNeverthelessspeciescompo-sition is justonedimensionofbiodiversity variation in size struc-tureisalsoimportantIncorporatingstructuraldatainbetadiversityassessmentsallowsecologiststomakeuseofvaluableinformationcollectedduringfieldsurveysIfitisavailablethereisnoreasontoignorethewealthofinformationaboutsizestructurewhencompar-ingspeciesassemblagesOurstudyhighlightstheneedtoincorpo-ratethestructuraldataofacommunityinadditiontocompositionaldatawhenquantifyingandanalyzingbetadiversityFinallyourre-sults suggest thatbothdeterministicandstochasticprocessesarerelevantdeterminantsofcompositionalandstructuralcomponentsof communityassemblages inour temperate forestNeverthelesstheseprocessesarescale-andorresolution-dependent
ACKNOWLEDGEMENTS
WewouldliketothankHeHuaijiangDingShengjianNiRuiqiangandZuoQiangandseveralothersforassistingwiththefielddatacollectionAuthorsaregratefultotheJiaoheManagementBureauof the Forest Experimental Zone for permission to undertake thefieldworkWealsothankthreeanonymousreviewersforprovidingthevaluablecomments
CONFLICTS OF INTEREST
Theauthorsdeclarenocompetingfinancialinterests
DATA ACCESSIBILITY
DataownershipbelongstoBeijingForestryUniversitywhosestaffconductedtheanalysesandwrotethemanuscripthttpwwwbjfueducn
ORCID
Jie Yao httpsorcidorg0000-0002-8606-8158
REFERENCES
Anderson M J Crist T O Chase J M Vellend M InouyeB D Freestone A L hellip Swenson N G (2011) Navigatingthe multiple meanings of β diversity a roadmap for the prac-ticing ecologist Ecology Letters 14 19ndash28 httpsdoiorg101111j1461-0248201001552x
ArsenaultAampBradfieldGE (1995)Structuralndashcompositionalvaria-tioninthreeage-classesoftemperaterainforestsinsoutherncoastalBritishColumbiaCanadian Journal of Botany7354ndash64httpsdoiorg101139b95-007
Borcard D amp Legendre P (1994) Environmental control and spatialstructureinecologicalcommunitiesanexampleusingoribatidmites(Acari Oribatei) Environmental and Ecological Statistics 1 37ndash61httpsdoiorg101007BF00714196
Borcard D Legendre P Avois-Jacquet C amp Tuomisto H (2004)DissectingthespatialstructureofecologicaldataatmultiplescalesEcology851826ndash1832httpsdoiorg10189003-3111
BorcardDLegendrePampDrapeauP(1992)PartiallingoutthespatialcomponentofecologicalvariationEcology731045ndash1055httpsdoiorg1023071940179
Caswell H (1976) Community structure a neutral model anal-ysis Ecological Monographs 46 327ndash354 httpsdoiorg1023071942257
ChaseJM(2010)Stochasticcommunityassemblycauseshigherbiodi-versityinmoreproductiveenvironmentsScience3281388ndash1391httpsdoiorg101126science1187820
ChaveJ(2004)NeutraltheoryandcommunityecologyEcology Letters7241ndash253httpsdoiorg101111j1461-0248200300566x
Chesson P (2000) Mechanisms of maintenance of species diversityAnnual Review of Ecology and Systematics31343ndash366httpsdoiorg101146annurevecolsys311343
ComitaLSUriarteMThompsonJJonckheereICanhamCDampZimmermanJK(2009)Abioticandbioticdriversofseedlingsur-vival inahurricane-impacted tropical forestJournal of Ecology971346ndash1359httpsdoiorg101111j1365-2745200901551x
DeCaacuteceresMFontXampOlivaF(2010)Themanagementofvegeta-tionclassificationswithfuzzyclusteringJournal of Vegetation Science211138ndash1151httpsdoiorg101111j1654-1103201001211x
De Caacuteceres M Legendre P amp He F (2013) Dissimilarity mea-surements and the size structure of ecological communitiesMethods in Ecology and Evolution 4 1167ndash1177 httpsdoiorg1011112041-210X12116
De Caacuteceres M Legendre P Valencia R Cao M Chang L-W Chuyong G hellip He F (2012) The variation of tree betadiversity across a global network of forest plots Global Ecology and Biogeography 21 1191ndash1202 httpsdoiorg101111j1466-8238201200770x
DraySBaumanDBlanchetGBorcardDClappeSGuenardGhellipWagnerHH(2018)adespatial Multivariate multiscale spatial analy-sis R package version 03-2RetrievedfromhttpsCRANR-projectorgpackage=adespatial
Dumbrell A J NelsonM Helgason T Dytham C amp Fitter A H(2010)Relativerolesofnicheandneutralprocesses instructuringa soil microbial community ISME Journal 4 337ndash345 httpsdoiorg101038ismej2009122
FaithDAustinMBelbinLampMargulesC (1985)Numericalclas-sification of profile attributes in environmental studies Journal of Environmental Management2073ndash85
Fang J Shen Z Tang ZWang XWang Z Feng J hellip Zheng C(2012) Forest community survey and the structural character-istics of forests in China Ecography 35 1059ndash1071 httpsdoiorg101111j1600-0587201300161x
FraverSampWhiteAS(2005)Disturbancedynamicsofold-growthPicea rubens forests of northern Maine Journal of Vegetation Science 16 597ndash610 httpsdoiorg101111j1654-11032005tb02401x
Gower J C (1966) Some distance properties of latent root and vec-tormethodsusedinmultivariateanalysisBiometrika53325ndash338httpsdoiorg101093biomet533-4325
Harms K E Condit R Hubbell S P amp Foster R B (2001)Habitat associations of trees and shrubs in a 50-ha neotrop-ical forest plot Journal of Ecology 89 947ndash959 httpsdoiorg101111j1365-2745200100615x
HilleRisLambers J Adler P B Harpole W S Levine J M ampMayfield M M (2012) Rethinking community assembly
268emsp |emsp emspenspJournal of Vegetation Science
YAO et Al
through the lens of coexistence theory Annual Review of Ecology Evolution and Systematics 43 227ndash249 httpsdoiorg101146annurev-ecolsys-110411-160411
HubbellSP(Ed)(2001)The unified theory of biodiversity and biogeogra-phyPrincetonNJPrincetonUniversityPress
Hubbell S P (2006) Neutral theory and the evolution of eco-logical equivalence Ecology 87 1387ndash1398 httpsdoiorg1018900012-9658(2006)87[1387NTATEO]20CO2
HussonFJosseJLeSampMazetJ(2015)FactoMineR Multivariate exploratory data analysis and data mining Version 1314 RetrievedfromhttpsCRANR-projectorgpackage=FactoMineR
Hutchinson G E (1961) The paradox of the plankton American Naturalist95137ndash145httpsdoiorg101086282171
KeddyPA(1992)Assemblyandresponserulestwogoalsforpredic-tive community ecology Journal of Vegetation Science3 157ndash164httpsdoiorg1023073235676
KoleffPGastonKJampLennonJJ(2003)MeasuringbetadiversityforpresencendashabsencedataJournal of Animal Ecology72367ndash382httpsdoiorg101046j1365-2656200300710x
KraftN JBComita L SChase JM SandersN J SwensonNGCrist TOhellipMyers JA (2011)Disentangling thedriversofβdiversityalong latitudinalandelevationalgradientsScience3331755ndash1758httpsdoiorg101126science1208584
LaliberteacuteEPaquetteALegendrePampBouchardA(2009)Assessingthescale-specificimportanceofnichesandotherspatialprocessesonbetadiversityacasestudyfromatemperateforestOecologia159377ndash388httpsdoiorg101007s00442-008-1214-8
Legendre P amp Anderson M J (1999) Distance-based redundancyanalysis testing multispecies responses in multifactorial ecolog-ical experiments Ecological Monographs 69 1ndash24 httpsdoiorg1018900012-9615(1999)069[0001DBRATM]20CO2
Legendre P Borcard D amp Peres-Neto P R (2005) Analyzing betadiversity partitioning the spatial variation of community com-position data Ecological Monographs 75 435ndash450 httpsdoiorg10189005-0549
LegendrePampDeCaacuteceresM(2013)BetadiversityasthevarianceofcommunitydatadissimilaritycoefficientsandpartitioningEcology Letters16951ndash963httpsdoiorg101111ele12141
LegendrePampLegendreL (2012)Numerical ecology Vol 24 (3rded)AmsterdamTheNetherlandsElsevierScienceBV
LegendrePMiXRenHMaKYuMSun I-FampHeF (2009)Partitioning beta diversity in a subtropical broad-leaved forest ofChina Ecology90663ndash674httpsdoiorg10189007-18801
MayfieldMMampLevineJM(2010)Opposingeffectsofcompetitiveex-clusiononthephylogeneticstructureofcommunitiesEcology Letters131085ndash1093httpsdoiorg101111j1461-0248201001509x
MyersJAChaseJMJimeacutenezIJoslashrgensenPMAraujo-MurakamiAPaniagua-ZambranaNampSeidelR(2013)Beta-diversityintem-perateandtropicalforestsreflectsdissimilarmechanismsofcommu-nityassemblyEcology Letters16151ndash157httpsdoiorg101111ele12021
OksanenJBlanchetFGFriendlyMKindtRLegendrePMcGlinnDhellipWagnerH(2018)vegan Community ecology package Version 25-2Retrievedfromhttpscranr-projectorgpackage=vegan
Paradis EClaude JampStrimmerK (2004)APEAnalysesof phylo-genetics and evolution inR languageBioinformatics20 289ndash290httpsdoiorg101093bioinformaticsbtg412
PeetRK (1992)Community structureand function InDCGlenn-LewinRKPeetampTTVeblen(Eds)Plant succession theory and prediction(pp103ndash140)NewYorkNYChapmanampHall
Peres-NetoPRLegendrePDraySampBorcardD(2006)Variationpartitioningofspeciesdatamatricesestimationandcomparisonof
fractionsEcology872614ndash2625httpsdoiorg1018900012-9658(2006)87[2614VPOSDM]20CO2
Punchi-Manage R Wiegand T Wiegand K Getzin S SavitriGunatillekeCV ampNimalGunatilleke IAUN(2014)EffectofspatialprocessesandtopographyonstructuringspeciesassemblagesinaSriLankandipterocarpforestEcology95376ndash386httpsdoiorg10189012-21021
RCoreTeam (2017)R A language and environment for statistical com-puting Vienna Austria R Foundation for Statistical ComputingRetrievedfromhttpswwwR-projectorg
Ricklefs R E (1990) Seabird life histories and the marine environ-mentsomespeculationsColonial Waterbirds13(1)1ndash6httpsdoiorg1023071521414
SchwinningSampWeinerJ(1998)MechanismsdeterminingthedegreeofsizeasymmetryincompetitionamongplantsOecologia113447ndash455httpsdoiorg101007s004420050397
SoilScienceSocietyofChina(Ed)(1999)Soil agricultural chemical analy-sis procedureBeijingChinaChineseAgriculturalSciencePress
van der Plas F Janzen T Ordonez A FokkemaW Reinders JEtienneRSampOlffH(2015)Anewmodelingapproachestimatesthe relative importance of different community assembly pro-cesses Ecology961502ndash1515httpsdoiorg10189014-04541
VellendM(Ed)(2017)The theory of ecological communitiesPrincetonNJPrincetonUniversityPresshttpsdoiorg1015159781400883790
Weiner J (1990) Asymmetric competition in plant popula-tions Trends in Ecology and Evolution 5 360ndash364 httpsdoiorg1010160169-5347(90)90095-U
WhittakerRH (1960)VegetationoftheSiskiyoumountainsOregonand California Ecological Monographs 30 279ndash338 httpsdoiorg1023071943563
WhittakerRH(1972)EvolutionandmeasurementofspeciesdiversityTaxon21213ndash251httpsdoiorg1023071218190
XuWHaoMWangJZhangCZhaoXampvonGadowK(2016)Soilelementsinfluencingcommunitystructureinanold-growthfor-est innortheasternChinaForests7159httpsdoiorg103390f7080159
YamakuraTKanzakiMItohAOhkuboTOginoKChaiEOKhellipAshtonPS(1995)Topographyofalarge-scaleresearchplotes-tablishedwithinatropicalrainforestatLambirSarawakTropics541ndash56httpsdoiorg103759tropics541
YanYZhangCWangYZhaoXampvonGadowK(2015)Driversofseedlingsurvivalinatemperateforestandtheirrelativeimportanceat threestagesofsuccessionEcology and Evolution54287ndash4299httpsdoiorg101002ece31688
YaoJZhangXZhangCZhaoXampvonGadowK(2016)EffectsofdensitydependenceinatemperateforestinnortheasternChinaScientific Reports632844httpsdoiorg101038srep32844
ZhangCZhaoXampvonGadowK(2014)Analyzingselectiveharvestevents inthree largeforestobservationalstudies inNorthEasternChina Forest Ecology and Management 316 100ndash109 httpsdoiorg101016jforeco201307018
ZhangCZhaoYZhaoXampvonGadowK (2012)Species-habitatassociations inanorthern temperate forest inChinaSilva Fennica46501ndash519
How to cite this articleYaoJZhangCDeCaacuteceresMLegendrePZhaoXVariationincompositionalandstructuralcomponentsofcommunityassemblageanditsdeterminantsJ Veg Sci 201930257ndash268 httpsdoiorg101111jvs12708
emspensp emsp | emsp265Journal of Vegetation Science
YAO et Al
41emsp|emspStructural and compositional components of forest variation
The framework of CAP allowed us to incorporate the distribu-tionof individualtreesize intotheanalysisofcommunityassem-blage thusmaking it possible toquantify the spatial variationofcommunitystructurebetadiversityEvensosuchstructuralbetadiversitycanbequantified independentlyor incombinationwithspecies composition TheBDCOMPndashSTR is the largest among thesethreecomponentsofbetadiversity indicating thatapplyingspe-ciescompositionaloneorsizestructurealonetoassessthebetadi-versitymayunderestimatethevariationofassemblages(Figure2)ThevaluesofBDCOMPareclosertotheBDCOMPndashSTRvaluesthanthatofBDSTR(theBDSTRvaluesarerelativelysmallFigure2)ThusasfarasourCAPframework isconcerned it seemsmoreappropri-atetoquantifybetadiversityusingthespeciescomposition indi-viduallythanusingthesizestructureindividuallyNeverthelessifstructureprovidesindependentinformationandisdeemedimpor-tantoneshouldincorporateitinBDassessmentAsbetadiversityindiceswerecalculatedfromdissimilaritymatrices thestructuralcomponent of beta diversity depended on the weight given to
structural vs compositional informationwhencalculatingdissimi-larity(Figure2andashc)Thelargerthebinsizes(iethesmallerweightgiventospeciesstructuralinformation)thecloserBDCOMPndashSTR val-uesapproachedthevaluesofBDCOMP(Figure2andashc)Ifthebinsizesare big enough theBDCOMPndashSTR value and theBDCOMP value are expected to converge at a certain size of dbh binNeverthelessconsideringthenecessityofcomprehensiveassessmentofbetadi-versityweadvocateforsmallbinsizesastheyprovidemoreinde-pendentstructuralinformationFinallyitisimportanttonotethatthisforestplotincludes47differenttreespecieswhichresultsinastrongrelativeweightofthecompositionalcomponentofBDCOMPndashSTRwhenusingtheCAPframeworkRepeatingourstudyinforestswith lower species richness or in this forest but using a coarsercompositional resolution (eg at the family level)would result inlargerrelativeweightofthestructuralcomponent
42emsp|emspLocal contributions to beta diversity in terms of community composition and structure
EcologicallyLCBDindicesonlyrepresentthedegreeofuniquenessofthesamplingunitsintermsofcommunitycomposition(Legendre
F IGURE 4emspMapsof30-ha(500mtimes600m)plotshowingthelocalcontributionstobetadiversity(LCBD)intermsofcommunitycompositionandstructurefor750quadrats(20mtimes20m)ThesolidcirclesrepresentthevaluesofLCBDiforeachithquadrat(i =[1750])(a)ThemapofLCBDsonlyintermsofspeciescompositionNotethatthesizestructureofindividuals(iedbh)isnotconsideredwhencalculatingtheLCBDCOMPthusthevaluesofLCBDCOMPwerenotaffectedbythesizeofthebinsofthestructuralvariable(b)ndash(e)ThetwoextremecasesoftheLCBDmap(b)and(c)givingthemostweighttothestructuralcomponentandcorrespondinglytheleastweighttothecompositionalcomponent(ie1-cmbinsize)and(d)and(e)givingthemostweighttothecompositionalcomponentandcorrespondinglytheleastweighttothestructuralcomponent(ie15-cmbinsize)(f)and(g)MapsofLCBDsafteraveragingacrossdbhbinsizesSizeofthecirclesisproportionaltotheLCBDivaluesTheblackandgreysolidcirclesrepresentthesiteswithLCBDvalueshigherandlowerthanthemeanrespectively
TABLE 1emspVariationpartitioningresultsforthreetypesofmatricesatdifferentscalesofquadratsThepartitioningisbasedonadjustedR2 statisticsasrecommendedbyPeres-Netoetal(2006)
Quadrat sizes (a) (b) (c) (d) (a + b) (b + c) (a + b + c)
YCOMP
10mtimes10m 00044 00796 01361 07799 00840 02157 02201
20mtimes20m 00028 01783 02862 05327 01811 04645 04673
50mtimes50m 00050 02995 03229 03726 03045 06224 06274
YSTR
10mtimes10m 00123 00131 00296 09450 00254 00427 00550
20mtimes20m 00013 00907 01652 07428 00920 02560 02572
50mtimes50m 00029 02300 02163 05509 02328 04463 04492
YCOMPndashSTR
10mtimes10m 00055 00564 00932 08449 00619 01496 01551
20mtimes20m 00028 01576 02559 05837 01604 04135 04163
50mtimes50m 00013 02543 01948 05496 02556 04492 04504
Fractions(a)ndash(d)(adjustedR2statistics)(a)variationexplainedbytheenvironmentalvariablesaftercontrollingforthespatialstructure(b)variationexplainedbythespatiallystructuredenvironmentalvariables(c)spatiallystructuredvariationexplainedbypurespaceaftercontrollingforenviron-mentalvariation(d)residualvariationEnvironmentalvariablesusedtocomputefraction(a+b)dbMEMeigenfunctionsweretheexplanatoryvaria-blesusedtocomputefraction(b+c)Only5-cm-diameterclasses(iebinsize=5cm)asthestructuralvariablewereusedtocalculatetheYSTR and YCOMPndashSTR
266emsp |emsp emspenspJournal of Vegetation Science
YAO et Al
amp De Caacuteceres 2013) However natural communities may exhibitsimilarspeciescompositionsbutdifferinotherfeaturessuchasthesizestructureof individuals Inthepresentstudyweassessedthedegreeofuniquenessofthequadratsintermsnotonlyoftheirspe-ciescompositionbutalsooftheirsizestructureandbyusingbothcomponentstogetherThedegreeofuniquenessofquadratsintermsofcommunitycompositionindividuallyhadaveryweakcorrelationwithuniqueness in termsof size structure individually (LCBDCOMP vsLCBDSTRFigure3) indicating that sites that areunique in spe-cies composition are not necessarily unique in size structure andvice versa Additionally we found that the spatial distribution ofsiteswithhighLCBDvaluesisdifferentforthetwocomponentsofacommunitywith siteswithhighstructuraluniquenessoccurringinsmallforestpatches(Figure4)Alltheseresultsreinforcetheideathatconsideringbothspeciescompositionalandsizestructuralcom-ponentsmaybeamorecomprehensivewaytodescribethecommu-nityorganizationHoweverifweacceptthefactthatsitesthatareuniqueintermsofsizestructurearetheresultofgapdynamics(seebelow) the non-zero correlation between LCBDCOMP vs LCBDSTR mayindicatethatforestgapsmaybecolonizedbyspeciesthatmaylaterbesuppressedastheforestgrowssothatrecentforestgapshaveadifferentspeciescompositionthanclosedforeststructures(Comitaetal2009)
43emsp|emspPartitioning the structural and compositional components of beta diversity
About344ofthevariationincommunityassemblagewasdeter-minedbyenvironmentalandspatialvariablesdependingonthescale(quadratsize)andonwhichcomponentsofcommunityassemblage(ie compositional component structural component and takingbothcomponents together)were taken intoaccountThispropor-tion isslightly lowerthanthevaluesfound instudiesbyLegendreetal (2009)andPunchi-Manageetal (2014)Areasonforthisre-sult is thatwe incorporateddifferencesboth insizestructureandspeciescomposition intocommunityassemblagesratherthanonlyusingtheconventionalspeciescompositiondataWhenthespeciescomposition and size structure of the constituent individuals areincorporatedintothecommunityatthesametimemorevariationwilloccurincommunityassemblagesInourstudyhabitat(a+b)ex-plainedmorevariationinthecompositionalcomponent(190)thaninthestructuralcomponent(117)ofthecommunityassemblagesBetadiversitypartitioningindicatedthatthevariationinthestruc-turalcomponentislessdictatedbyenvironmentthanvariationinthecompositional componentWe here hypothesize that canopy gapdynamicswillbethepotentialdriversofstructuralvariationWinterinourstudyareaiscoldandlongwithalongsnowfallperiodThesnowfallperiodlastsforhalfayearandthesnowcoverthicknessinmountainousareasreaches40ndash50cmWehypothesizethatpulsesofmoderate-severity disturbancesmay be caused by snowstormsin our site In the absence of stand-replacing disturbances forestcanopiesareopenedperiodicallybythedeathofsinglebigtreesorsmallgroupsofadulttreescreatingcanopygapsSnowstormsmay
havealteredforeststructurebyselectivelyremovinglargercanopytrees Environmental selection of individuals shapes compositionbydeterminingthefitnessof individualswhereasstructuralvaria-tionmayhavesomerelationshipwithenvironmentalconditions(ielargertreesinsiteswherelargersizesaresupportedforenergyorwateravailability)butingeneralisthereflectionofdifferentstagesaroundgapdynamicsPreviousstudiesareconsistentwithourfind-ingsFraverandWhite(2005)forinstancefoundthattherepeatedmoderate-severity disturbances (iewindstorms) causeddramaticstructural changes they caused no significant change in speciescomposition
Becausetherelativeimportanceofbothnicheandneutralthe-oryinstructuringcommunitiesvarieswithspatialscale(Legendreetal 2009 Punchi-Manage etal 2014) we conducted scale-dependentanalyses InsharpcontrasttothefindingbyLegendreetal(2009)forabroad-leavedforestinChinawefoundthattheproportionofundeterminedvariation incompositionalandstruc-turalcomponentsofcommunityassemblageswasveryhighatfinespatialscales(upto945forthestructuralcomponent780forthecompositionalcomponentand844forbothcomponentsto-gether)butdecreasedsystematicallywith increasingspatial scale(up to a minimum of 373 for compositional component at the50-mscale)TheseresultsareinlinewiththefindingsbyPunchi-Manageetal(2014)inaSriLankandipterocarpforestandbyDeCaacuteceresetal(2012)inacomparisonofseveralforestsOntheonehandthehighproportionofunexplainedvariationmayberelatedtounmeasuredandnotspatially-structuredbiologicalorenviron-mentalvariablesXuetal(2016)showedthatthesoilnutrientsintheupper(0ndash10cmconsideredinourstudy)andlowersoillayers(10ndash20cm)andtheheavymetalelements(CuNiCdAsPbZnMoCrMnandMg)inthesoilshowastrongcorrelationwiththespeciesspatialdistributionsatJiaoheThismaypartlyexplainwhythepureenvironmentalvariable(a)explainedsuchlittlevariationinthecommunityassemblagesAnotherexplanationforthehighpro-portionofunexplainedvariationisthatitmaybeduetostochasticprocesseswhich related to theneutral theoryassuming that thedynamicsofpopulationsareprimarilydrivenbyecologicaldriftanddispersal(Legendreetal2009)Ontheotherhandtheproportionofundeterminedvariationincompositionalandstructuralcompo-nents of community assemblages decreased systematically withincreasingspatialscaleThismayindicatethatcommunityassem-blageishighlystochasticintermsofspeciescompositionandtreesizedistributionatfinescales (ie10-mscale)butthisfinescalestochasticitytendstosmoothoutatthe50-mscalewheremoreconsistent habitat-driven species assemblages emerged Whenvariance partitioning is conducted on the structural componentalonetheunexplained(d)fractionisdominantWhiletheinfluenceofenvironmental factorsonsizestructuremaybe less importantthan for thecompositionalcomponent theeffectof localdistur-bances (eg appearanceof canopygaps resulting frommortalityof largetrees)results inrandomspatialpatternsofquadratswithrather different structure contributing to a large unexplainedfraction
emspensp emsp | emsp267Journal of Vegetation Science
YAO et Al
5emsp |emspCONCLUSIONS
SpeciescompositionandsizestructurearethetwoessentialfeaturesofacommunityOnlyoneofthemindividuallymaybeinsufficienttodescribetheorganizationoftreespeciesassemblagesDefiningandquantifyingbetadiversityusingthespeciescompositionalonemaybesufficienttheninmanyoccasionsNeverthelessspeciescompo-sition is justonedimensionofbiodiversity variation in size struc-tureisalsoimportantIncorporatingstructuraldatainbetadiversityassessmentsallowsecologiststomakeuseofvaluableinformationcollectedduringfieldsurveysIfitisavailablethereisnoreasontoignorethewealthofinformationaboutsizestructurewhencompar-ingspeciesassemblagesOurstudyhighlightstheneedtoincorpo-ratethestructuraldataofacommunityinadditiontocompositionaldatawhenquantifyingandanalyzingbetadiversityFinallyourre-sults suggest thatbothdeterministicandstochasticprocessesarerelevantdeterminantsofcompositionalandstructuralcomponentsof communityassemblages inour temperate forestNeverthelesstheseprocessesarescale-andorresolution-dependent
ACKNOWLEDGEMENTS
WewouldliketothankHeHuaijiangDingShengjianNiRuiqiangandZuoQiangandseveralothersforassistingwiththefielddatacollectionAuthorsaregratefultotheJiaoheManagementBureauof the Forest Experimental Zone for permission to undertake thefieldworkWealsothankthreeanonymousreviewersforprovidingthevaluablecomments
CONFLICTS OF INTEREST
Theauthorsdeclarenocompetingfinancialinterests
DATA ACCESSIBILITY
DataownershipbelongstoBeijingForestryUniversitywhosestaffconductedtheanalysesandwrotethemanuscripthttpwwwbjfueducn
ORCID
Jie Yao httpsorcidorg0000-0002-8606-8158
REFERENCES
Anderson M J Crist T O Chase J M Vellend M InouyeB D Freestone A L hellip Swenson N G (2011) Navigatingthe multiple meanings of β diversity a roadmap for the prac-ticing ecologist Ecology Letters 14 19ndash28 httpsdoiorg101111j1461-0248201001552x
ArsenaultAampBradfieldGE (1995)Structuralndashcompositionalvaria-tioninthreeage-classesoftemperaterainforestsinsoutherncoastalBritishColumbiaCanadian Journal of Botany7354ndash64httpsdoiorg101139b95-007
Borcard D amp Legendre P (1994) Environmental control and spatialstructureinecologicalcommunitiesanexampleusingoribatidmites(Acari Oribatei) Environmental and Ecological Statistics 1 37ndash61httpsdoiorg101007BF00714196
Borcard D Legendre P Avois-Jacquet C amp Tuomisto H (2004)DissectingthespatialstructureofecologicaldataatmultiplescalesEcology851826ndash1832httpsdoiorg10189003-3111
BorcardDLegendrePampDrapeauP(1992)PartiallingoutthespatialcomponentofecologicalvariationEcology731045ndash1055httpsdoiorg1023071940179
Caswell H (1976) Community structure a neutral model anal-ysis Ecological Monographs 46 327ndash354 httpsdoiorg1023071942257
ChaseJM(2010)Stochasticcommunityassemblycauseshigherbiodi-versityinmoreproductiveenvironmentsScience3281388ndash1391httpsdoiorg101126science1187820
ChaveJ(2004)NeutraltheoryandcommunityecologyEcology Letters7241ndash253httpsdoiorg101111j1461-0248200300566x
Chesson P (2000) Mechanisms of maintenance of species diversityAnnual Review of Ecology and Systematics31343ndash366httpsdoiorg101146annurevecolsys311343
ComitaLSUriarteMThompsonJJonckheereICanhamCDampZimmermanJK(2009)Abioticandbioticdriversofseedlingsur-vival inahurricane-impacted tropical forestJournal of Ecology971346ndash1359httpsdoiorg101111j1365-2745200901551x
DeCaacuteceresMFontXampOlivaF(2010)Themanagementofvegeta-tionclassificationswithfuzzyclusteringJournal of Vegetation Science211138ndash1151httpsdoiorg101111j1654-1103201001211x
De Caacuteceres M Legendre P amp He F (2013) Dissimilarity mea-surements and the size structure of ecological communitiesMethods in Ecology and Evolution 4 1167ndash1177 httpsdoiorg1011112041-210X12116
De Caacuteceres M Legendre P Valencia R Cao M Chang L-W Chuyong G hellip He F (2012) The variation of tree betadiversity across a global network of forest plots Global Ecology and Biogeography 21 1191ndash1202 httpsdoiorg101111j1466-8238201200770x
DraySBaumanDBlanchetGBorcardDClappeSGuenardGhellipWagnerHH(2018)adespatial Multivariate multiscale spatial analy-sis R package version 03-2RetrievedfromhttpsCRANR-projectorgpackage=adespatial
Dumbrell A J NelsonM Helgason T Dytham C amp Fitter A H(2010)Relativerolesofnicheandneutralprocesses instructuringa soil microbial community ISME Journal 4 337ndash345 httpsdoiorg101038ismej2009122
FaithDAustinMBelbinLampMargulesC (1985)Numericalclas-sification of profile attributes in environmental studies Journal of Environmental Management2073ndash85
Fang J Shen Z Tang ZWang XWang Z Feng J hellip Zheng C(2012) Forest community survey and the structural character-istics of forests in China Ecography 35 1059ndash1071 httpsdoiorg101111j1600-0587201300161x
FraverSampWhiteAS(2005)Disturbancedynamicsofold-growthPicea rubens forests of northern Maine Journal of Vegetation Science 16 597ndash610 httpsdoiorg101111j1654-11032005tb02401x
Gower J C (1966) Some distance properties of latent root and vec-tormethodsusedinmultivariateanalysisBiometrika53325ndash338httpsdoiorg101093biomet533-4325
Harms K E Condit R Hubbell S P amp Foster R B (2001)Habitat associations of trees and shrubs in a 50-ha neotrop-ical forest plot Journal of Ecology 89 947ndash959 httpsdoiorg101111j1365-2745200100615x
HilleRisLambers J Adler P B Harpole W S Levine J M ampMayfield M M (2012) Rethinking community assembly
268emsp |emsp emspenspJournal of Vegetation Science
YAO et Al
through the lens of coexistence theory Annual Review of Ecology Evolution and Systematics 43 227ndash249 httpsdoiorg101146annurev-ecolsys-110411-160411
HubbellSP(Ed)(2001)The unified theory of biodiversity and biogeogra-phyPrincetonNJPrincetonUniversityPress
Hubbell S P (2006) Neutral theory and the evolution of eco-logical equivalence Ecology 87 1387ndash1398 httpsdoiorg1018900012-9658(2006)87[1387NTATEO]20CO2
HussonFJosseJLeSampMazetJ(2015)FactoMineR Multivariate exploratory data analysis and data mining Version 1314 RetrievedfromhttpsCRANR-projectorgpackage=FactoMineR
Hutchinson G E (1961) The paradox of the plankton American Naturalist95137ndash145httpsdoiorg101086282171
KeddyPA(1992)Assemblyandresponserulestwogoalsforpredic-tive community ecology Journal of Vegetation Science3 157ndash164httpsdoiorg1023073235676
KoleffPGastonKJampLennonJJ(2003)MeasuringbetadiversityforpresencendashabsencedataJournal of Animal Ecology72367ndash382httpsdoiorg101046j1365-2656200300710x
KraftN JBComita L SChase JM SandersN J SwensonNGCrist TOhellipMyers JA (2011)Disentangling thedriversofβdiversityalong latitudinalandelevationalgradientsScience3331755ndash1758httpsdoiorg101126science1208584
LaliberteacuteEPaquetteALegendrePampBouchardA(2009)Assessingthescale-specificimportanceofnichesandotherspatialprocessesonbetadiversityacasestudyfromatemperateforestOecologia159377ndash388httpsdoiorg101007s00442-008-1214-8
Legendre P amp Anderson M J (1999) Distance-based redundancyanalysis testing multispecies responses in multifactorial ecolog-ical experiments Ecological Monographs 69 1ndash24 httpsdoiorg1018900012-9615(1999)069[0001DBRATM]20CO2
Legendre P Borcard D amp Peres-Neto P R (2005) Analyzing betadiversity partitioning the spatial variation of community com-position data Ecological Monographs 75 435ndash450 httpsdoiorg10189005-0549
LegendrePampDeCaacuteceresM(2013)BetadiversityasthevarianceofcommunitydatadissimilaritycoefficientsandpartitioningEcology Letters16951ndash963httpsdoiorg101111ele12141
LegendrePampLegendreL (2012)Numerical ecology Vol 24 (3rded)AmsterdamTheNetherlandsElsevierScienceBV
LegendrePMiXRenHMaKYuMSun I-FampHeF (2009)Partitioning beta diversity in a subtropical broad-leaved forest ofChina Ecology90663ndash674httpsdoiorg10189007-18801
MayfieldMMampLevineJM(2010)Opposingeffectsofcompetitiveex-clusiononthephylogeneticstructureofcommunitiesEcology Letters131085ndash1093httpsdoiorg101111j1461-0248201001509x
MyersJAChaseJMJimeacutenezIJoslashrgensenPMAraujo-MurakamiAPaniagua-ZambranaNampSeidelR(2013)Beta-diversityintem-perateandtropicalforestsreflectsdissimilarmechanismsofcommu-nityassemblyEcology Letters16151ndash157httpsdoiorg101111ele12021
OksanenJBlanchetFGFriendlyMKindtRLegendrePMcGlinnDhellipWagnerH(2018)vegan Community ecology package Version 25-2Retrievedfromhttpscranr-projectorgpackage=vegan
Paradis EClaude JampStrimmerK (2004)APEAnalysesof phylo-genetics and evolution inR languageBioinformatics20 289ndash290httpsdoiorg101093bioinformaticsbtg412
PeetRK (1992)Community structureand function InDCGlenn-LewinRKPeetampTTVeblen(Eds)Plant succession theory and prediction(pp103ndash140)NewYorkNYChapmanampHall
Peres-NetoPRLegendrePDraySampBorcardD(2006)Variationpartitioningofspeciesdatamatricesestimationandcomparisonof
fractionsEcology872614ndash2625httpsdoiorg1018900012-9658(2006)87[2614VPOSDM]20CO2
Punchi-Manage R Wiegand T Wiegand K Getzin S SavitriGunatillekeCV ampNimalGunatilleke IAUN(2014)EffectofspatialprocessesandtopographyonstructuringspeciesassemblagesinaSriLankandipterocarpforestEcology95376ndash386httpsdoiorg10189012-21021
RCoreTeam (2017)R A language and environment for statistical com-puting Vienna Austria R Foundation for Statistical ComputingRetrievedfromhttpswwwR-projectorg
Ricklefs R E (1990) Seabird life histories and the marine environ-mentsomespeculationsColonial Waterbirds13(1)1ndash6httpsdoiorg1023071521414
SchwinningSampWeinerJ(1998)MechanismsdeterminingthedegreeofsizeasymmetryincompetitionamongplantsOecologia113447ndash455httpsdoiorg101007s004420050397
SoilScienceSocietyofChina(Ed)(1999)Soil agricultural chemical analy-sis procedureBeijingChinaChineseAgriculturalSciencePress
van der Plas F Janzen T Ordonez A FokkemaW Reinders JEtienneRSampOlffH(2015)Anewmodelingapproachestimatesthe relative importance of different community assembly pro-cesses Ecology961502ndash1515httpsdoiorg10189014-04541
VellendM(Ed)(2017)The theory of ecological communitiesPrincetonNJPrincetonUniversityPresshttpsdoiorg1015159781400883790
Weiner J (1990) Asymmetric competition in plant popula-tions Trends in Ecology and Evolution 5 360ndash364 httpsdoiorg1010160169-5347(90)90095-U
WhittakerRH (1960)VegetationoftheSiskiyoumountainsOregonand California Ecological Monographs 30 279ndash338 httpsdoiorg1023071943563
WhittakerRH(1972)EvolutionandmeasurementofspeciesdiversityTaxon21213ndash251httpsdoiorg1023071218190
XuWHaoMWangJZhangCZhaoXampvonGadowK(2016)Soilelementsinfluencingcommunitystructureinanold-growthfor-est innortheasternChinaForests7159httpsdoiorg103390f7080159
YamakuraTKanzakiMItohAOhkuboTOginoKChaiEOKhellipAshtonPS(1995)Topographyofalarge-scaleresearchplotes-tablishedwithinatropicalrainforestatLambirSarawakTropics541ndash56httpsdoiorg103759tropics541
YanYZhangCWangYZhaoXampvonGadowK(2015)Driversofseedlingsurvivalinatemperateforestandtheirrelativeimportanceat threestagesofsuccessionEcology and Evolution54287ndash4299httpsdoiorg101002ece31688
YaoJZhangXZhangCZhaoXampvonGadowK(2016)EffectsofdensitydependenceinatemperateforestinnortheasternChinaScientific Reports632844httpsdoiorg101038srep32844
ZhangCZhaoXampvonGadowK(2014)Analyzingselectiveharvestevents inthree largeforestobservationalstudies inNorthEasternChina Forest Ecology and Management 316 100ndash109 httpsdoiorg101016jforeco201307018
ZhangCZhaoYZhaoXampvonGadowK (2012)Species-habitatassociations inanorthern temperate forest inChinaSilva Fennica46501ndash519
How to cite this articleYaoJZhangCDeCaacuteceresMLegendrePZhaoXVariationincompositionalandstructuralcomponentsofcommunityassemblageanditsdeterminantsJ Veg Sci 201930257ndash268 httpsdoiorg101111jvs12708
266emsp |emsp emspenspJournal of Vegetation Science
YAO et Al
amp De Caacuteceres 2013) However natural communities may exhibitsimilarspeciescompositionsbutdifferinotherfeaturessuchasthesizestructureof individuals Inthepresentstudyweassessedthedegreeofuniquenessofthequadratsintermsnotonlyoftheirspe-ciescompositionbutalsooftheirsizestructureandbyusingbothcomponentstogetherThedegreeofuniquenessofquadratsintermsofcommunitycompositionindividuallyhadaveryweakcorrelationwithuniqueness in termsof size structure individually (LCBDCOMP vsLCBDSTRFigure3) indicating that sites that areunique in spe-cies composition are not necessarily unique in size structure andvice versa Additionally we found that the spatial distribution ofsiteswithhighLCBDvaluesisdifferentforthetwocomponentsofacommunitywith siteswithhighstructuraluniquenessoccurringinsmallforestpatches(Figure4)Alltheseresultsreinforcetheideathatconsideringbothspeciescompositionalandsizestructuralcom-ponentsmaybeamorecomprehensivewaytodescribethecommu-nityorganizationHoweverifweacceptthefactthatsitesthatareuniqueintermsofsizestructurearetheresultofgapdynamics(seebelow) the non-zero correlation between LCBDCOMP vs LCBDSTR mayindicatethatforestgapsmaybecolonizedbyspeciesthatmaylaterbesuppressedastheforestgrowssothatrecentforestgapshaveadifferentspeciescompositionthanclosedforeststructures(Comitaetal2009)
43emsp|emspPartitioning the structural and compositional components of beta diversity
About344ofthevariationincommunityassemblagewasdeter-minedbyenvironmentalandspatialvariablesdependingonthescale(quadratsize)andonwhichcomponentsofcommunityassemblage(ie compositional component structural component and takingbothcomponents together)were taken intoaccountThispropor-tion isslightly lowerthanthevaluesfound instudiesbyLegendreetal (2009)andPunchi-Manageetal (2014)Areasonforthisre-sult is thatwe incorporateddifferencesboth insizestructureandspeciescomposition intocommunityassemblagesratherthanonlyusingtheconventionalspeciescompositiondataWhenthespeciescomposition and size structure of the constituent individuals areincorporatedintothecommunityatthesametimemorevariationwilloccurincommunityassemblagesInourstudyhabitat(a+b)ex-plainedmorevariationinthecompositionalcomponent(190)thaninthestructuralcomponent(117)ofthecommunityassemblagesBetadiversitypartitioningindicatedthatthevariationinthestruc-turalcomponentislessdictatedbyenvironmentthanvariationinthecompositional componentWe here hypothesize that canopy gapdynamicswillbethepotentialdriversofstructuralvariationWinterinourstudyareaiscoldandlongwithalongsnowfallperiodThesnowfallperiodlastsforhalfayearandthesnowcoverthicknessinmountainousareasreaches40ndash50cmWehypothesizethatpulsesofmoderate-severity disturbancesmay be caused by snowstormsin our site In the absence of stand-replacing disturbances forestcanopiesareopenedperiodicallybythedeathofsinglebigtreesorsmallgroupsofadulttreescreatingcanopygapsSnowstormsmay
havealteredforeststructurebyselectivelyremovinglargercanopytrees Environmental selection of individuals shapes compositionbydeterminingthefitnessof individualswhereasstructuralvaria-tionmayhavesomerelationshipwithenvironmentalconditions(ielargertreesinsiteswherelargersizesaresupportedforenergyorwateravailability)butingeneralisthereflectionofdifferentstagesaroundgapdynamicsPreviousstudiesareconsistentwithourfind-ingsFraverandWhite(2005)forinstancefoundthattherepeatedmoderate-severity disturbances (iewindstorms) causeddramaticstructural changes they caused no significant change in speciescomposition
Becausetherelativeimportanceofbothnicheandneutralthe-oryinstructuringcommunitiesvarieswithspatialscale(Legendreetal 2009 Punchi-Manage etal 2014) we conducted scale-dependentanalyses InsharpcontrasttothefindingbyLegendreetal(2009)forabroad-leavedforestinChinawefoundthattheproportionofundeterminedvariation incompositionalandstruc-turalcomponentsofcommunityassemblageswasveryhighatfinespatialscales(upto945forthestructuralcomponent780forthecompositionalcomponentand844forbothcomponentsto-gether)butdecreasedsystematicallywith increasingspatial scale(up to a minimum of 373 for compositional component at the50-mscale)TheseresultsareinlinewiththefindingsbyPunchi-Manageetal(2014)inaSriLankandipterocarpforestandbyDeCaacuteceresetal(2012)inacomparisonofseveralforestsOntheonehandthehighproportionofunexplainedvariationmayberelatedtounmeasuredandnotspatially-structuredbiologicalorenviron-mentalvariablesXuetal(2016)showedthatthesoilnutrientsintheupper(0ndash10cmconsideredinourstudy)andlowersoillayers(10ndash20cm)andtheheavymetalelements(CuNiCdAsPbZnMoCrMnandMg)inthesoilshowastrongcorrelationwiththespeciesspatialdistributionsatJiaoheThismaypartlyexplainwhythepureenvironmentalvariable(a)explainedsuchlittlevariationinthecommunityassemblagesAnotherexplanationforthehighpro-portionofunexplainedvariationisthatitmaybeduetostochasticprocesseswhich related to theneutral theoryassuming that thedynamicsofpopulationsareprimarilydrivenbyecologicaldriftanddispersal(Legendreetal2009)Ontheotherhandtheproportionofundeterminedvariationincompositionalandstructuralcompo-nents of community assemblages decreased systematically withincreasingspatialscaleThismayindicatethatcommunityassem-blageishighlystochasticintermsofspeciescompositionandtreesizedistributionatfinescales (ie10-mscale)butthisfinescalestochasticitytendstosmoothoutatthe50-mscalewheremoreconsistent habitat-driven species assemblages emerged Whenvariance partitioning is conducted on the structural componentalonetheunexplained(d)fractionisdominantWhiletheinfluenceofenvironmental factorsonsizestructuremaybe less importantthan for thecompositionalcomponent theeffectof localdistur-bances (eg appearanceof canopygaps resulting frommortalityof largetrees)results inrandomspatialpatternsofquadratswithrather different structure contributing to a large unexplainedfraction
emspensp emsp | emsp267Journal of Vegetation Science
YAO et Al
5emsp |emspCONCLUSIONS
SpeciescompositionandsizestructurearethetwoessentialfeaturesofacommunityOnlyoneofthemindividuallymaybeinsufficienttodescribetheorganizationoftreespeciesassemblagesDefiningandquantifyingbetadiversityusingthespeciescompositionalonemaybesufficienttheninmanyoccasionsNeverthelessspeciescompo-sition is justonedimensionofbiodiversity variation in size struc-tureisalsoimportantIncorporatingstructuraldatainbetadiversityassessmentsallowsecologiststomakeuseofvaluableinformationcollectedduringfieldsurveysIfitisavailablethereisnoreasontoignorethewealthofinformationaboutsizestructurewhencompar-ingspeciesassemblagesOurstudyhighlightstheneedtoincorpo-ratethestructuraldataofacommunityinadditiontocompositionaldatawhenquantifyingandanalyzingbetadiversityFinallyourre-sults suggest thatbothdeterministicandstochasticprocessesarerelevantdeterminantsofcompositionalandstructuralcomponentsof communityassemblages inour temperate forestNeverthelesstheseprocessesarescale-andorresolution-dependent
ACKNOWLEDGEMENTS
WewouldliketothankHeHuaijiangDingShengjianNiRuiqiangandZuoQiangandseveralothersforassistingwiththefielddatacollectionAuthorsaregratefultotheJiaoheManagementBureauof the Forest Experimental Zone for permission to undertake thefieldworkWealsothankthreeanonymousreviewersforprovidingthevaluablecomments
CONFLICTS OF INTEREST
Theauthorsdeclarenocompetingfinancialinterests
DATA ACCESSIBILITY
DataownershipbelongstoBeijingForestryUniversitywhosestaffconductedtheanalysesandwrotethemanuscripthttpwwwbjfueducn
ORCID
Jie Yao httpsorcidorg0000-0002-8606-8158
REFERENCES
Anderson M J Crist T O Chase J M Vellend M InouyeB D Freestone A L hellip Swenson N G (2011) Navigatingthe multiple meanings of β diversity a roadmap for the prac-ticing ecologist Ecology Letters 14 19ndash28 httpsdoiorg101111j1461-0248201001552x
ArsenaultAampBradfieldGE (1995)Structuralndashcompositionalvaria-tioninthreeage-classesoftemperaterainforestsinsoutherncoastalBritishColumbiaCanadian Journal of Botany7354ndash64httpsdoiorg101139b95-007
Borcard D amp Legendre P (1994) Environmental control and spatialstructureinecologicalcommunitiesanexampleusingoribatidmites(Acari Oribatei) Environmental and Ecological Statistics 1 37ndash61httpsdoiorg101007BF00714196
Borcard D Legendre P Avois-Jacquet C amp Tuomisto H (2004)DissectingthespatialstructureofecologicaldataatmultiplescalesEcology851826ndash1832httpsdoiorg10189003-3111
BorcardDLegendrePampDrapeauP(1992)PartiallingoutthespatialcomponentofecologicalvariationEcology731045ndash1055httpsdoiorg1023071940179
Caswell H (1976) Community structure a neutral model anal-ysis Ecological Monographs 46 327ndash354 httpsdoiorg1023071942257
ChaseJM(2010)Stochasticcommunityassemblycauseshigherbiodi-versityinmoreproductiveenvironmentsScience3281388ndash1391httpsdoiorg101126science1187820
ChaveJ(2004)NeutraltheoryandcommunityecologyEcology Letters7241ndash253httpsdoiorg101111j1461-0248200300566x
Chesson P (2000) Mechanisms of maintenance of species diversityAnnual Review of Ecology and Systematics31343ndash366httpsdoiorg101146annurevecolsys311343
ComitaLSUriarteMThompsonJJonckheereICanhamCDampZimmermanJK(2009)Abioticandbioticdriversofseedlingsur-vival inahurricane-impacted tropical forestJournal of Ecology971346ndash1359httpsdoiorg101111j1365-2745200901551x
DeCaacuteceresMFontXampOlivaF(2010)Themanagementofvegeta-tionclassificationswithfuzzyclusteringJournal of Vegetation Science211138ndash1151httpsdoiorg101111j1654-1103201001211x
De Caacuteceres M Legendre P amp He F (2013) Dissimilarity mea-surements and the size structure of ecological communitiesMethods in Ecology and Evolution 4 1167ndash1177 httpsdoiorg1011112041-210X12116
De Caacuteceres M Legendre P Valencia R Cao M Chang L-W Chuyong G hellip He F (2012) The variation of tree betadiversity across a global network of forest plots Global Ecology and Biogeography 21 1191ndash1202 httpsdoiorg101111j1466-8238201200770x
DraySBaumanDBlanchetGBorcardDClappeSGuenardGhellipWagnerHH(2018)adespatial Multivariate multiscale spatial analy-sis R package version 03-2RetrievedfromhttpsCRANR-projectorgpackage=adespatial
Dumbrell A J NelsonM Helgason T Dytham C amp Fitter A H(2010)Relativerolesofnicheandneutralprocesses instructuringa soil microbial community ISME Journal 4 337ndash345 httpsdoiorg101038ismej2009122
FaithDAustinMBelbinLampMargulesC (1985)Numericalclas-sification of profile attributes in environmental studies Journal of Environmental Management2073ndash85
Fang J Shen Z Tang ZWang XWang Z Feng J hellip Zheng C(2012) Forest community survey and the structural character-istics of forests in China Ecography 35 1059ndash1071 httpsdoiorg101111j1600-0587201300161x
FraverSampWhiteAS(2005)Disturbancedynamicsofold-growthPicea rubens forests of northern Maine Journal of Vegetation Science 16 597ndash610 httpsdoiorg101111j1654-11032005tb02401x
Gower J C (1966) Some distance properties of latent root and vec-tormethodsusedinmultivariateanalysisBiometrika53325ndash338httpsdoiorg101093biomet533-4325
Harms K E Condit R Hubbell S P amp Foster R B (2001)Habitat associations of trees and shrubs in a 50-ha neotrop-ical forest plot Journal of Ecology 89 947ndash959 httpsdoiorg101111j1365-2745200100615x
HilleRisLambers J Adler P B Harpole W S Levine J M ampMayfield M M (2012) Rethinking community assembly
268emsp |emsp emspenspJournal of Vegetation Science
YAO et Al
through the lens of coexistence theory Annual Review of Ecology Evolution and Systematics 43 227ndash249 httpsdoiorg101146annurev-ecolsys-110411-160411
HubbellSP(Ed)(2001)The unified theory of biodiversity and biogeogra-phyPrincetonNJPrincetonUniversityPress
Hubbell S P (2006) Neutral theory and the evolution of eco-logical equivalence Ecology 87 1387ndash1398 httpsdoiorg1018900012-9658(2006)87[1387NTATEO]20CO2
HussonFJosseJLeSampMazetJ(2015)FactoMineR Multivariate exploratory data analysis and data mining Version 1314 RetrievedfromhttpsCRANR-projectorgpackage=FactoMineR
Hutchinson G E (1961) The paradox of the plankton American Naturalist95137ndash145httpsdoiorg101086282171
KeddyPA(1992)Assemblyandresponserulestwogoalsforpredic-tive community ecology Journal of Vegetation Science3 157ndash164httpsdoiorg1023073235676
KoleffPGastonKJampLennonJJ(2003)MeasuringbetadiversityforpresencendashabsencedataJournal of Animal Ecology72367ndash382httpsdoiorg101046j1365-2656200300710x
KraftN JBComita L SChase JM SandersN J SwensonNGCrist TOhellipMyers JA (2011)Disentangling thedriversofβdiversityalong latitudinalandelevationalgradientsScience3331755ndash1758httpsdoiorg101126science1208584
LaliberteacuteEPaquetteALegendrePampBouchardA(2009)Assessingthescale-specificimportanceofnichesandotherspatialprocessesonbetadiversityacasestudyfromatemperateforestOecologia159377ndash388httpsdoiorg101007s00442-008-1214-8
Legendre P amp Anderson M J (1999) Distance-based redundancyanalysis testing multispecies responses in multifactorial ecolog-ical experiments Ecological Monographs 69 1ndash24 httpsdoiorg1018900012-9615(1999)069[0001DBRATM]20CO2
Legendre P Borcard D amp Peres-Neto P R (2005) Analyzing betadiversity partitioning the spatial variation of community com-position data Ecological Monographs 75 435ndash450 httpsdoiorg10189005-0549
LegendrePampDeCaacuteceresM(2013)BetadiversityasthevarianceofcommunitydatadissimilaritycoefficientsandpartitioningEcology Letters16951ndash963httpsdoiorg101111ele12141
LegendrePampLegendreL (2012)Numerical ecology Vol 24 (3rded)AmsterdamTheNetherlandsElsevierScienceBV
LegendrePMiXRenHMaKYuMSun I-FampHeF (2009)Partitioning beta diversity in a subtropical broad-leaved forest ofChina Ecology90663ndash674httpsdoiorg10189007-18801
MayfieldMMampLevineJM(2010)Opposingeffectsofcompetitiveex-clusiononthephylogeneticstructureofcommunitiesEcology Letters131085ndash1093httpsdoiorg101111j1461-0248201001509x
MyersJAChaseJMJimeacutenezIJoslashrgensenPMAraujo-MurakamiAPaniagua-ZambranaNampSeidelR(2013)Beta-diversityintem-perateandtropicalforestsreflectsdissimilarmechanismsofcommu-nityassemblyEcology Letters16151ndash157httpsdoiorg101111ele12021
OksanenJBlanchetFGFriendlyMKindtRLegendrePMcGlinnDhellipWagnerH(2018)vegan Community ecology package Version 25-2Retrievedfromhttpscranr-projectorgpackage=vegan
Paradis EClaude JampStrimmerK (2004)APEAnalysesof phylo-genetics and evolution inR languageBioinformatics20 289ndash290httpsdoiorg101093bioinformaticsbtg412
PeetRK (1992)Community structureand function InDCGlenn-LewinRKPeetampTTVeblen(Eds)Plant succession theory and prediction(pp103ndash140)NewYorkNYChapmanampHall
Peres-NetoPRLegendrePDraySampBorcardD(2006)Variationpartitioningofspeciesdatamatricesestimationandcomparisonof
fractionsEcology872614ndash2625httpsdoiorg1018900012-9658(2006)87[2614VPOSDM]20CO2
Punchi-Manage R Wiegand T Wiegand K Getzin S SavitriGunatillekeCV ampNimalGunatilleke IAUN(2014)EffectofspatialprocessesandtopographyonstructuringspeciesassemblagesinaSriLankandipterocarpforestEcology95376ndash386httpsdoiorg10189012-21021
RCoreTeam (2017)R A language and environment for statistical com-puting Vienna Austria R Foundation for Statistical ComputingRetrievedfromhttpswwwR-projectorg
Ricklefs R E (1990) Seabird life histories and the marine environ-mentsomespeculationsColonial Waterbirds13(1)1ndash6httpsdoiorg1023071521414
SchwinningSampWeinerJ(1998)MechanismsdeterminingthedegreeofsizeasymmetryincompetitionamongplantsOecologia113447ndash455httpsdoiorg101007s004420050397
SoilScienceSocietyofChina(Ed)(1999)Soil agricultural chemical analy-sis procedureBeijingChinaChineseAgriculturalSciencePress
van der Plas F Janzen T Ordonez A FokkemaW Reinders JEtienneRSampOlffH(2015)Anewmodelingapproachestimatesthe relative importance of different community assembly pro-cesses Ecology961502ndash1515httpsdoiorg10189014-04541
VellendM(Ed)(2017)The theory of ecological communitiesPrincetonNJPrincetonUniversityPresshttpsdoiorg1015159781400883790
Weiner J (1990) Asymmetric competition in plant popula-tions Trends in Ecology and Evolution 5 360ndash364 httpsdoiorg1010160169-5347(90)90095-U
WhittakerRH (1960)VegetationoftheSiskiyoumountainsOregonand California Ecological Monographs 30 279ndash338 httpsdoiorg1023071943563
WhittakerRH(1972)EvolutionandmeasurementofspeciesdiversityTaxon21213ndash251httpsdoiorg1023071218190
XuWHaoMWangJZhangCZhaoXampvonGadowK(2016)Soilelementsinfluencingcommunitystructureinanold-growthfor-est innortheasternChinaForests7159httpsdoiorg103390f7080159
YamakuraTKanzakiMItohAOhkuboTOginoKChaiEOKhellipAshtonPS(1995)Topographyofalarge-scaleresearchplotes-tablishedwithinatropicalrainforestatLambirSarawakTropics541ndash56httpsdoiorg103759tropics541
YanYZhangCWangYZhaoXampvonGadowK(2015)Driversofseedlingsurvivalinatemperateforestandtheirrelativeimportanceat threestagesofsuccessionEcology and Evolution54287ndash4299httpsdoiorg101002ece31688
YaoJZhangXZhangCZhaoXampvonGadowK(2016)EffectsofdensitydependenceinatemperateforestinnortheasternChinaScientific Reports632844httpsdoiorg101038srep32844
ZhangCZhaoXampvonGadowK(2014)Analyzingselectiveharvestevents inthree largeforestobservationalstudies inNorthEasternChina Forest Ecology and Management 316 100ndash109 httpsdoiorg101016jforeco201307018
ZhangCZhaoYZhaoXampvonGadowK (2012)Species-habitatassociations inanorthern temperate forest inChinaSilva Fennica46501ndash519
How to cite this articleYaoJZhangCDeCaacuteceresMLegendrePZhaoXVariationincompositionalandstructuralcomponentsofcommunityassemblageanditsdeterminantsJ Veg Sci 201930257ndash268 httpsdoiorg101111jvs12708
emspensp emsp | emsp267Journal of Vegetation Science
YAO et Al
5emsp |emspCONCLUSIONS
SpeciescompositionandsizestructurearethetwoessentialfeaturesofacommunityOnlyoneofthemindividuallymaybeinsufficienttodescribetheorganizationoftreespeciesassemblagesDefiningandquantifyingbetadiversityusingthespeciescompositionalonemaybesufficienttheninmanyoccasionsNeverthelessspeciescompo-sition is justonedimensionofbiodiversity variation in size struc-tureisalsoimportantIncorporatingstructuraldatainbetadiversityassessmentsallowsecologiststomakeuseofvaluableinformationcollectedduringfieldsurveysIfitisavailablethereisnoreasontoignorethewealthofinformationaboutsizestructurewhencompar-ingspeciesassemblagesOurstudyhighlightstheneedtoincorpo-ratethestructuraldataofacommunityinadditiontocompositionaldatawhenquantifyingandanalyzingbetadiversityFinallyourre-sults suggest thatbothdeterministicandstochasticprocessesarerelevantdeterminantsofcompositionalandstructuralcomponentsof communityassemblages inour temperate forestNeverthelesstheseprocessesarescale-andorresolution-dependent
ACKNOWLEDGEMENTS
WewouldliketothankHeHuaijiangDingShengjianNiRuiqiangandZuoQiangandseveralothersforassistingwiththefielddatacollectionAuthorsaregratefultotheJiaoheManagementBureauof the Forest Experimental Zone for permission to undertake thefieldworkWealsothankthreeanonymousreviewersforprovidingthevaluablecomments
CONFLICTS OF INTEREST
Theauthorsdeclarenocompetingfinancialinterests
DATA ACCESSIBILITY
DataownershipbelongstoBeijingForestryUniversitywhosestaffconductedtheanalysesandwrotethemanuscripthttpwwwbjfueducn
ORCID
Jie Yao httpsorcidorg0000-0002-8606-8158
REFERENCES
Anderson M J Crist T O Chase J M Vellend M InouyeB D Freestone A L hellip Swenson N G (2011) Navigatingthe multiple meanings of β diversity a roadmap for the prac-ticing ecologist Ecology Letters 14 19ndash28 httpsdoiorg101111j1461-0248201001552x
ArsenaultAampBradfieldGE (1995)Structuralndashcompositionalvaria-tioninthreeage-classesoftemperaterainforestsinsoutherncoastalBritishColumbiaCanadian Journal of Botany7354ndash64httpsdoiorg101139b95-007
Borcard D amp Legendre P (1994) Environmental control and spatialstructureinecologicalcommunitiesanexampleusingoribatidmites(Acari Oribatei) Environmental and Ecological Statistics 1 37ndash61httpsdoiorg101007BF00714196
Borcard D Legendre P Avois-Jacquet C amp Tuomisto H (2004)DissectingthespatialstructureofecologicaldataatmultiplescalesEcology851826ndash1832httpsdoiorg10189003-3111
BorcardDLegendrePampDrapeauP(1992)PartiallingoutthespatialcomponentofecologicalvariationEcology731045ndash1055httpsdoiorg1023071940179
Caswell H (1976) Community structure a neutral model anal-ysis Ecological Monographs 46 327ndash354 httpsdoiorg1023071942257
ChaseJM(2010)Stochasticcommunityassemblycauseshigherbiodi-versityinmoreproductiveenvironmentsScience3281388ndash1391httpsdoiorg101126science1187820
ChaveJ(2004)NeutraltheoryandcommunityecologyEcology Letters7241ndash253httpsdoiorg101111j1461-0248200300566x
Chesson P (2000) Mechanisms of maintenance of species diversityAnnual Review of Ecology and Systematics31343ndash366httpsdoiorg101146annurevecolsys311343
ComitaLSUriarteMThompsonJJonckheereICanhamCDampZimmermanJK(2009)Abioticandbioticdriversofseedlingsur-vival inahurricane-impacted tropical forestJournal of Ecology971346ndash1359httpsdoiorg101111j1365-2745200901551x
DeCaacuteceresMFontXampOlivaF(2010)Themanagementofvegeta-tionclassificationswithfuzzyclusteringJournal of Vegetation Science211138ndash1151httpsdoiorg101111j1654-1103201001211x
De Caacuteceres M Legendre P amp He F (2013) Dissimilarity mea-surements and the size structure of ecological communitiesMethods in Ecology and Evolution 4 1167ndash1177 httpsdoiorg1011112041-210X12116
De Caacuteceres M Legendre P Valencia R Cao M Chang L-W Chuyong G hellip He F (2012) The variation of tree betadiversity across a global network of forest plots Global Ecology and Biogeography 21 1191ndash1202 httpsdoiorg101111j1466-8238201200770x
DraySBaumanDBlanchetGBorcardDClappeSGuenardGhellipWagnerHH(2018)adespatial Multivariate multiscale spatial analy-sis R package version 03-2RetrievedfromhttpsCRANR-projectorgpackage=adespatial
Dumbrell A J NelsonM Helgason T Dytham C amp Fitter A H(2010)Relativerolesofnicheandneutralprocesses instructuringa soil microbial community ISME Journal 4 337ndash345 httpsdoiorg101038ismej2009122
FaithDAustinMBelbinLampMargulesC (1985)Numericalclas-sification of profile attributes in environmental studies Journal of Environmental Management2073ndash85
Fang J Shen Z Tang ZWang XWang Z Feng J hellip Zheng C(2012) Forest community survey and the structural character-istics of forests in China Ecography 35 1059ndash1071 httpsdoiorg101111j1600-0587201300161x
FraverSampWhiteAS(2005)Disturbancedynamicsofold-growthPicea rubens forests of northern Maine Journal of Vegetation Science 16 597ndash610 httpsdoiorg101111j1654-11032005tb02401x
Gower J C (1966) Some distance properties of latent root and vec-tormethodsusedinmultivariateanalysisBiometrika53325ndash338httpsdoiorg101093biomet533-4325
Harms K E Condit R Hubbell S P amp Foster R B (2001)Habitat associations of trees and shrubs in a 50-ha neotrop-ical forest plot Journal of Ecology 89 947ndash959 httpsdoiorg101111j1365-2745200100615x
HilleRisLambers J Adler P B Harpole W S Levine J M ampMayfield M M (2012) Rethinking community assembly
268emsp |emsp emspenspJournal of Vegetation Science
YAO et Al
through the lens of coexistence theory Annual Review of Ecology Evolution and Systematics 43 227ndash249 httpsdoiorg101146annurev-ecolsys-110411-160411
HubbellSP(Ed)(2001)The unified theory of biodiversity and biogeogra-phyPrincetonNJPrincetonUniversityPress
Hubbell S P (2006) Neutral theory and the evolution of eco-logical equivalence Ecology 87 1387ndash1398 httpsdoiorg1018900012-9658(2006)87[1387NTATEO]20CO2
HussonFJosseJLeSampMazetJ(2015)FactoMineR Multivariate exploratory data analysis and data mining Version 1314 RetrievedfromhttpsCRANR-projectorgpackage=FactoMineR
Hutchinson G E (1961) The paradox of the plankton American Naturalist95137ndash145httpsdoiorg101086282171
KeddyPA(1992)Assemblyandresponserulestwogoalsforpredic-tive community ecology Journal of Vegetation Science3 157ndash164httpsdoiorg1023073235676
KoleffPGastonKJampLennonJJ(2003)MeasuringbetadiversityforpresencendashabsencedataJournal of Animal Ecology72367ndash382httpsdoiorg101046j1365-2656200300710x
KraftN JBComita L SChase JM SandersN J SwensonNGCrist TOhellipMyers JA (2011)Disentangling thedriversofβdiversityalong latitudinalandelevationalgradientsScience3331755ndash1758httpsdoiorg101126science1208584
LaliberteacuteEPaquetteALegendrePampBouchardA(2009)Assessingthescale-specificimportanceofnichesandotherspatialprocessesonbetadiversityacasestudyfromatemperateforestOecologia159377ndash388httpsdoiorg101007s00442-008-1214-8
Legendre P amp Anderson M J (1999) Distance-based redundancyanalysis testing multispecies responses in multifactorial ecolog-ical experiments Ecological Monographs 69 1ndash24 httpsdoiorg1018900012-9615(1999)069[0001DBRATM]20CO2
Legendre P Borcard D amp Peres-Neto P R (2005) Analyzing betadiversity partitioning the spatial variation of community com-position data Ecological Monographs 75 435ndash450 httpsdoiorg10189005-0549
LegendrePampDeCaacuteceresM(2013)BetadiversityasthevarianceofcommunitydatadissimilaritycoefficientsandpartitioningEcology Letters16951ndash963httpsdoiorg101111ele12141
LegendrePampLegendreL (2012)Numerical ecology Vol 24 (3rded)AmsterdamTheNetherlandsElsevierScienceBV
LegendrePMiXRenHMaKYuMSun I-FampHeF (2009)Partitioning beta diversity in a subtropical broad-leaved forest ofChina Ecology90663ndash674httpsdoiorg10189007-18801
MayfieldMMampLevineJM(2010)Opposingeffectsofcompetitiveex-clusiononthephylogeneticstructureofcommunitiesEcology Letters131085ndash1093httpsdoiorg101111j1461-0248201001509x
MyersJAChaseJMJimeacutenezIJoslashrgensenPMAraujo-MurakamiAPaniagua-ZambranaNampSeidelR(2013)Beta-diversityintem-perateandtropicalforestsreflectsdissimilarmechanismsofcommu-nityassemblyEcology Letters16151ndash157httpsdoiorg101111ele12021
OksanenJBlanchetFGFriendlyMKindtRLegendrePMcGlinnDhellipWagnerH(2018)vegan Community ecology package Version 25-2Retrievedfromhttpscranr-projectorgpackage=vegan
Paradis EClaude JampStrimmerK (2004)APEAnalysesof phylo-genetics and evolution inR languageBioinformatics20 289ndash290httpsdoiorg101093bioinformaticsbtg412
PeetRK (1992)Community structureand function InDCGlenn-LewinRKPeetampTTVeblen(Eds)Plant succession theory and prediction(pp103ndash140)NewYorkNYChapmanampHall
Peres-NetoPRLegendrePDraySampBorcardD(2006)Variationpartitioningofspeciesdatamatricesestimationandcomparisonof
fractionsEcology872614ndash2625httpsdoiorg1018900012-9658(2006)87[2614VPOSDM]20CO2
Punchi-Manage R Wiegand T Wiegand K Getzin S SavitriGunatillekeCV ampNimalGunatilleke IAUN(2014)EffectofspatialprocessesandtopographyonstructuringspeciesassemblagesinaSriLankandipterocarpforestEcology95376ndash386httpsdoiorg10189012-21021
RCoreTeam (2017)R A language and environment for statistical com-puting Vienna Austria R Foundation for Statistical ComputingRetrievedfromhttpswwwR-projectorg
Ricklefs R E (1990) Seabird life histories and the marine environ-mentsomespeculationsColonial Waterbirds13(1)1ndash6httpsdoiorg1023071521414
SchwinningSampWeinerJ(1998)MechanismsdeterminingthedegreeofsizeasymmetryincompetitionamongplantsOecologia113447ndash455httpsdoiorg101007s004420050397
SoilScienceSocietyofChina(Ed)(1999)Soil agricultural chemical analy-sis procedureBeijingChinaChineseAgriculturalSciencePress
van der Plas F Janzen T Ordonez A FokkemaW Reinders JEtienneRSampOlffH(2015)Anewmodelingapproachestimatesthe relative importance of different community assembly pro-cesses Ecology961502ndash1515httpsdoiorg10189014-04541
VellendM(Ed)(2017)The theory of ecological communitiesPrincetonNJPrincetonUniversityPresshttpsdoiorg1015159781400883790
Weiner J (1990) Asymmetric competition in plant popula-tions Trends in Ecology and Evolution 5 360ndash364 httpsdoiorg1010160169-5347(90)90095-U
WhittakerRH (1960)VegetationoftheSiskiyoumountainsOregonand California Ecological Monographs 30 279ndash338 httpsdoiorg1023071943563
WhittakerRH(1972)EvolutionandmeasurementofspeciesdiversityTaxon21213ndash251httpsdoiorg1023071218190
XuWHaoMWangJZhangCZhaoXampvonGadowK(2016)Soilelementsinfluencingcommunitystructureinanold-growthfor-est innortheasternChinaForests7159httpsdoiorg103390f7080159
YamakuraTKanzakiMItohAOhkuboTOginoKChaiEOKhellipAshtonPS(1995)Topographyofalarge-scaleresearchplotes-tablishedwithinatropicalrainforestatLambirSarawakTropics541ndash56httpsdoiorg103759tropics541
YanYZhangCWangYZhaoXampvonGadowK(2015)Driversofseedlingsurvivalinatemperateforestandtheirrelativeimportanceat threestagesofsuccessionEcology and Evolution54287ndash4299httpsdoiorg101002ece31688
YaoJZhangXZhangCZhaoXampvonGadowK(2016)EffectsofdensitydependenceinatemperateforestinnortheasternChinaScientific Reports632844httpsdoiorg101038srep32844
ZhangCZhaoXampvonGadowK(2014)Analyzingselectiveharvestevents inthree largeforestobservationalstudies inNorthEasternChina Forest Ecology and Management 316 100ndash109 httpsdoiorg101016jforeco201307018
ZhangCZhaoYZhaoXampvonGadowK (2012)Species-habitatassociations inanorthern temperate forest inChinaSilva Fennica46501ndash519
How to cite this articleYaoJZhangCDeCaacuteceresMLegendrePZhaoXVariationincompositionalandstructuralcomponentsofcommunityassemblageanditsdeterminantsJ Veg Sci 201930257ndash268 httpsdoiorg101111jvs12708
268emsp |emsp emspenspJournal of Vegetation Science
YAO et Al
through the lens of coexistence theory Annual Review of Ecology Evolution and Systematics 43 227ndash249 httpsdoiorg101146annurev-ecolsys-110411-160411
HubbellSP(Ed)(2001)The unified theory of biodiversity and biogeogra-phyPrincetonNJPrincetonUniversityPress
Hubbell S P (2006) Neutral theory and the evolution of eco-logical equivalence Ecology 87 1387ndash1398 httpsdoiorg1018900012-9658(2006)87[1387NTATEO]20CO2
HussonFJosseJLeSampMazetJ(2015)FactoMineR Multivariate exploratory data analysis and data mining Version 1314 RetrievedfromhttpsCRANR-projectorgpackage=FactoMineR
Hutchinson G E (1961) The paradox of the plankton American Naturalist95137ndash145httpsdoiorg101086282171
KeddyPA(1992)Assemblyandresponserulestwogoalsforpredic-tive community ecology Journal of Vegetation Science3 157ndash164httpsdoiorg1023073235676
KoleffPGastonKJampLennonJJ(2003)MeasuringbetadiversityforpresencendashabsencedataJournal of Animal Ecology72367ndash382httpsdoiorg101046j1365-2656200300710x
KraftN JBComita L SChase JM SandersN J SwensonNGCrist TOhellipMyers JA (2011)Disentangling thedriversofβdiversityalong latitudinalandelevationalgradientsScience3331755ndash1758httpsdoiorg101126science1208584
LaliberteacuteEPaquetteALegendrePampBouchardA(2009)Assessingthescale-specificimportanceofnichesandotherspatialprocessesonbetadiversityacasestudyfromatemperateforestOecologia159377ndash388httpsdoiorg101007s00442-008-1214-8
Legendre P amp Anderson M J (1999) Distance-based redundancyanalysis testing multispecies responses in multifactorial ecolog-ical experiments Ecological Monographs 69 1ndash24 httpsdoiorg1018900012-9615(1999)069[0001DBRATM]20CO2
Legendre P Borcard D amp Peres-Neto P R (2005) Analyzing betadiversity partitioning the spatial variation of community com-position data Ecological Monographs 75 435ndash450 httpsdoiorg10189005-0549
LegendrePampDeCaacuteceresM(2013)BetadiversityasthevarianceofcommunitydatadissimilaritycoefficientsandpartitioningEcology Letters16951ndash963httpsdoiorg101111ele12141
LegendrePampLegendreL (2012)Numerical ecology Vol 24 (3rded)AmsterdamTheNetherlandsElsevierScienceBV
LegendrePMiXRenHMaKYuMSun I-FampHeF (2009)Partitioning beta diversity in a subtropical broad-leaved forest ofChina Ecology90663ndash674httpsdoiorg10189007-18801
MayfieldMMampLevineJM(2010)Opposingeffectsofcompetitiveex-clusiononthephylogeneticstructureofcommunitiesEcology Letters131085ndash1093httpsdoiorg101111j1461-0248201001509x
MyersJAChaseJMJimeacutenezIJoslashrgensenPMAraujo-MurakamiAPaniagua-ZambranaNampSeidelR(2013)Beta-diversityintem-perateandtropicalforestsreflectsdissimilarmechanismsofcommu-nityassemblyEcology Letters16151ndash157httpsdoiorg101111ele12021
OksanenJBlanchetFGFriendlyMKindtRLegendrePMcGlinnDhellipWagnerH(2018)vegan Community ecology package Version 25-2Retrievedfromhttpscranr-projectorgpackage=vegan
Paradis EClaude JampStrimmerK (2004)APEAnalysesof phylo-genetics and evolution inR languageBioinformatics20 289ndash290httpsdoiorg101093bioinformaticsbtg412
PeetRK (1992)Community structureand function InDCGlenn-LewinRKPeetampTTVeblen(Eds)Plant succession theory and prediction(pp103ndash140)NewYorkNYChapmanampHall
Peres-NetoPRLegendrePDraySampBorcardD(2006)Variationpartitioningofspeciesdatamatricesestimationandcomparisonof
fractionsEcology872614ndash2625httpsdoiorg1018900012-9658(2006)87[2614VPOSDM]20CO2
Punchi-Manage R Wiegand T Wiegand K Getzin S SavitriGunatillekeCV ampNimalGunatilleke IAUN(2014)EffectofspatialprocessesandtopographyonstructuringspeciesassemblagesinaSriLankandipterocarpforestEcology95376ndash386httpsdoiorg10189012-21021
RCoreTeam (2017)R A language and environment for statistical com-puting Vienna Austria R Foundation for Statistical ComputingRetrievedfromhttpswwwR-projectorg
Ricklefs R E (1990) Seabird life histories and the marine environ-mentsomespeculationsColonial Waterbirds13(1)1ndash6httpsdoiorg1023071521414
SchwinningSampWeinerJ(1998)MechanismsdeterminingthedegreeofsizeasymmetryincompetitionamongplantsOecologia113447ndash455httpsdoiorg101007s004420050397
SoilScienceSocietyofChina(Ed)(1999)Soil agricultural chemical analy-sis procedureBeijingChinaChineseAgriculturalSciencePress
van der Plas F Janzen T Ordonez A FokkemaW Reinders JEtienneRSampOlffH(2015)Anewmodelingapproachestimatesthe relative importance of different community assembly pro-cesses Ecology961502ndash1515httpsdoiorg10189014-04541
VellendM(Ed)(2017)The theory of ecological communitiesPrincetonNJPrincetonUniversityPresshttpsdoiorg1015159781400883790
Weiner J (1990) Asymmetric competition in plant popula-tions Trends in Ecology and Evolution 5 360ndash364 httpsdoiorg1010160169-5347(90)90095-U
WhittakerRH (1960)VegetationoftheSiskiyoumountainsOregonand California Ecological Monographs 30 279ndash338 httpsdoiorg1023071943563
WhittakerRH(1972)EvolutionandmeasurementofspeciesdiversityTaxon21213ndash251httpsdoiorg1023071218190
XuWHaoMWangJZhangCZhaoXampvonGadowK(2016)Soilelementsinfluencingcommunitystructureinanold-growthfor-est innortheasternChinaForests7159httpsdoiorg103390f7080159
YamakuraTKanzakiMItohAOhkuboTOginoKChaiEOKhellipAshtonPS(1995)Topographyofalarge-scaleresearchplotes-tablishedwithinatropicalrainforestatLambirSarawakTropics541ndash56httpsdoiorg103759tropics541
YanYZhangCWangYZhaoXampvonGadowK(2015)Driversofseedlingsurvivalinatemperateforestandtheirrelativeimportanceat threestagesofsuccessionEcology and Evolution54287ndash4299httpsdoiorg101002ece31688
YaoJZhangXZhangCZhaoXampvonGadowK(2016)EffectsofdensitydependenceinatemperateforestinnortheasternChinaScientific Reports632844httpsdoiorg101038srep32844
ZhangCZhaoXampvonGadowK(2014)Analyzingselectiveharvestevents inthree largeforestobservationalstudies inNorthEasternChina Forest Ecology and Management 316 100ndash109 httpsdoiorg101016jforeco201307018
ZhangCZhaoYZhaoXampvonGadowK (2012)Species-habitatassociations inanorthern temperate forest inChinaSilva Fennica46501ndash519
How to cite this articleYaoJZhangCDeCaacuteceresMLegendrePZhaoXVariationincompositionalandstructuralcomponentsofcommunityassemblageanditsdeterminantsJ Veg Sci 201930257ndash268 httpsdoiorg101111jvs12708