One taxon does not fit all: herb-layer diversity and stand structural complexity are weak predictors of biodiversity in Fagus sylvatica forests

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ContentslistsavailableatScienceDirect

Ecological

Indicators

j ou rn a l h om ep a g e :w w w . e l s e v i e r . c o m / l o c a t e /e c o l i n d

One

taxon

does

not

ﬁt

all:

Herb-layer

diversity

and

stand

structural

complexity

are

weak

predictors

of

biodiversity

in

Fagus

sylvatica

forests

F.M.

Sabatini

a,∗,1

_,

_S.

_Burrascano

a,1

_,

_M.M.

_Azzella

a,b

_,

_A.

_Barbati

c

_,

_S.

_De

_Paulis

d

_,

D. Di

Santo

d

_,

_L.

_Facioni

a

_,

_D.

_Giuliarelli

c

_,

_F.

_Lombardi

e

_,

_O.

_Maggi

a

_,

_W.

_Mattioli

c

_,

F. Parisi

f,g

_,

_A.

_Persiani

a

_,

_S.

_Ravera

f

_,

_C.

_Blasi

a

a_Department_of_{Environmental}_Biology,_Sapienza_University_of_Rome,_P.le_Aldo_Moro_5,₀₀₁₈₅_Rome,_Italy

b_Department_of_Life_and_{Environmental}_Sciences,_University_of_Cagliari,_Viale_S._Ignazio_da_Laconi_11-13,₀₉₁₂₃_Cagliari,_Italy

c_Department_for_Innovation_in_Biological,_Agro-food_and_Forest_systems_(DIBAF),_University_of_Tuscia,_via_S._Camillo_de_Lellis,₀₁₁₀₀_Viterbo,_Italy d_Servizio_Agro_Silvo_Pastorale,_Gran_Sasso_e_Monti_della_Laga_National_Park,_via_Del_Convento_1,₆₇₀₁₀_Assergi,_Italy

e_Dipartimento_di_Agraria,_Università_degli_Studi_Mediterranea_di_Reggio_Calabria,_Contrada_Melissari,_Loc._Feo_di_Vito,₈₉₁₂₂_Reggio_Calabria,_Italy f_Dipartimento_di_Bioscienze_e_Territorio,_Università_degli_Studi_del_Molise,_C.da_Fonte_Lappone,₈₆₀₉₀_Pesche,_Isernia_Italy

g_Dipartimento_Agricoltura,_Ambiente_e_Alimenti,_Università_degli_Studi_del_Molise,_Via_de_Sanctis,₈₆₁₀₀_Campobasso,_Italy

a

r

t

i

c

l

e

i

n

f

o

Articlehistory: Received9October2015

Receivedinrevisedform1April2016 Accepted4April2016

Keywords: Apennines Cross-taxon Complementarity Europeanbeechforests Habitat-basedsurrogates Species-basedsurrogates

a

b

s

t

r

a

c

t

Sinceadequateinformationonthedistributionofbiodiversityishardlyachievable,biodiversityindicators

arenecessarytosupportthemanagementofecosystems.Thesesurrogatesassumethateithersome

habitatfeatures,orthebiodiversitypatternsobservedinawell-knowntaxon,canbeusedasaproxy

ofthediversityofoneormoretargettaxa.Nevertheless,atleastforcertaintaxa,thevalidityofthis

assumptionhasnotyetbeensufﬁcientlydemonstrated.

Weinvestigatedtheeffectivenessofbothahabitat-andataxa-basedsurrogateinsixEuropeanbeech

forestsintheApennines.Particularly,wetested:(1)whetherthestandstructuralcomplexityandthe

herb-layerspeciesrichnessweregoodpredictorsoftheﬁne-scalepatternsofspeciesrichnessofﬁve

groupsofforest-dwellingorganisms(beetles,saproxylicandepigeousfungi,birdsandepiphyticlichens);

and(2)thecross-taxoncongruenceinspeciescomplementarityandcompositionbetweenherb-layer

plantsandthetargettaxa.

WeusedGeneralizedLinearMixedModels(GLMMs),accumulationcurvesandProcrustesanalysisto

evaluatetheeffectivenessofthesesurrogateswhenspeciesrichness,complementarityandcomposition

wereconsidered,respectively.

Ourresultsprovidedalimitedsupporttothehypothesisthattheherb-layerplantsandthestand

structuralcomplexityweregoodsurrogatesofthetargettaxa.Althoughtherichnessoftheherb-layer

plantsreceivedastrongersupportfromthedatathanstructuralcomplexityasapredictorforthegeneral

patternsofspeciesrichness,theoverallmagnitudeofthiseffectwasweakanddistincttaxaresponded

differently.Forinstance,forincreasinglevelsofherb-layerrichness,therichnessoflichensshoweda

markedincrease,whiletherichnessofsaproxylicfungidecreased.Wealsofoundsigniﬁcantlysimilar

complementaritypatternsbetweentheherb-layerplantsandbeetles,aswellasasigniﬁcantcongruence

inspeciescompositionbetweenherb-layerplantsandsaproxylicfungi.Finally,whendifferentstand

structuralattributeswereconsideredsingularly,onlythetotalamountofdeadwoodreceivedsupport

fromthedataasapredictoroftheoverallspeciesrichness.

Attheﬁnescaleofthisstudy,herb-layerplantsandstandstructuralcomplexitydidnotproveto

beeffectivesurrogatesofmulti-taxonbiodiversityinwell-preservedsouthernEuropeanbeechforests.

Ratherthanonweaksurrogates,theseresultssuggestthatsoundconservationdecisionsshouldbe

supportedby the informationprovided by comprehensive multi-taxonomic assessments offorest

biodiversity.

license(http://creativecommons.org/licenses/by-nc-nd/4.0/).

∗ Correspondingauthor.Currentaddress:DepartmentofGeography,Humboldt-UniversitätzuBerlin,UnterdenLinden6,10099Berlin,Germany.Tel.:+4903020935394; fax:+4903020936848.

E-mailaddress:francescomaria.sabatini@uniroma1.it(F.M.Sabatini).

1 _These_authors_contributed_equally.

http://dx.doi.org/10.1016/j.ecolind.2016.04.012

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1. Introduction

The prioritization of conservation and restoration efforts requiresa thoroughunderstandingof thespatialdistributionof biodiversityalthough,unfortunately,thisisstillremarkablypoor formosttaxa,especiallyatﬁnespatialscales(Grussuetal.,2014; Westgateetal.,2014).Ecosystemsareextremelycomplex,andan adequateknowledgeofthewholebiodiversityspectrumishardly achievable.Thishasledtothedevelopmentand useof proxies orsurrogatestosimplify,represent,andhelpthemanagementof forestecosystems(Lindenmayeretal.,2014).

Asurrogateisdeﬁnedas“[ameasure]thatreadilyreﬂects:the bioticorabioticstateofanenvironment;representstheimpact ofanenvironmentalchangeonahabitat,communityor ecosys-tem;theabundanceofaparticularspecies;orisindicativeofthe diversityofasubsetoftaxa,orofwholesalediversity,withinan area”(Lindenmayeretal.,2014).Surrogatesareusuallydividedinto twobroadtypes(1)habitat-basedand(2)taxa-basedsurrogates (Lewandowskietal.,2010;Lindenmayeretal.,2014).Habitat-based surrogatesassumethatsomehabitatsorenvironmentalfeatures aregoodproxiesoftherichness,compositionordiversityofoneor moretaxa.Taxa-basedsurrogates,instead,assumethatthe biodi-versitypatternsobservedinagiventaxon(thesurrogate),which isusuallywellknownand/oreasytosample,canbegeneralized tooneormore(target)taxa.Thus,taxa-basedsurrogatesassume ahighcross-taxoncongruencethatavoidstheneedtodetectall specieswithinastudyarea(Gioriaetal.,2011;Westgateetal., 2014).Therationalebehindtheuseoftaxa-basedsurrogateshas beenexplainedbyseveralhypotheses:forinstance,theeffectofone taxondiversityonanothertaxon’sdiversitycouldbemediatedby cross-taxonfunctionalinteractions(e.g.,trophic,mutualistic, par-asitic),byasimilarresponsetotheenvironmentalconditionsor throughasharedbiogeographichistory(ToranzaandArim,2010; Gioriaetal.,2011).

Incertainecologicalcontexts,taxon-andhabitat-based surro-gatescouldbeusedjointlyandreturncomplementaryinformation onthetargettaxa(Lindenmayeretal.,2014).Forinstance,in tem-perateforestsbothvascularplantsandtheforeststandstructural characteristicswereoftenconsideredasgoodsurrogatecandidates offorestoverallbiodiversity.Vascularplantsareapotentially effec-tivetaxon-basedsurrogate,sincetheyarerelativelyeasytosample andtheirtaxonomyissufficientlywelldescribed(Santietal.,2010; Blasietal.,2011).Ontheonehand,plantsrepresentthebulkof bothecosystems’biomassandnetprimaryproductivity,andplay afundamentalroleinthetrophicnetworksofforestecosystems. Trophicormutualisticinteractionsmayaccountforpartofthe pat-ternsofcongruencebetweenvascularplantsandotherforesttaxa, suchasinsects(deAraujo,2013)ormycorrhizalfungi.Forinstance, arbuscularmycorrhizacaninfluencetheforestplantspecies diver-sitybyalteringthecompetitivebalanceinplantcommunities(Gerz etal.,2016).Ontheotherhand,vascularplantsandothertaxamay respondsimilarlytoacommondisturbancehistory(Nordénetal., 2014)ortosharedenvironmentalconditionsintheunderstory,e.g. forestfloorhumidityorlightintensity.Insupportofthese hypothe-ses,severalworksreportedthatrichnessofvascularplantspecies ispositivelycorrelatedwiththatofbryophytes(RooneyandAzeria, 2015),lichens(Blasietal.,2010),andanimalssuchasbirds(Blasi etal.,2010)andbutterflies(Santietal.,2010).Nevertheless, con-trastingresultswerereportedandthusarigoroustestingofplants asabiodiversityindicatorisstillneeded(Lewandowskietal.,2010; Santietal.,2010;Gaoetal.,2015).

Foreststructuralcomplexity,whichsynthesizesthevarietyof structuralcomponentsoccurringinastand,isalsoapossible can-didateasahabitat-basedsurrogateintemperateforests.Indeed, structuralcomplexityshowsagoodpotentialtobeusedasa bio-diversityproxy,atleastwhenconsideringthosetaxathatutilize

specificforeststructures(McElhinny etal.,2005;Gossneretal., 2014).Linking the standstructural complexity to specific taxa providesinformationabouttheproximatecausesofbiodiversity change,includingthoserelatedtospecificsilviculturalpractices. Forinstance,thelackofacertainstructuremaybecorrelatedto theabsenceof aparticulargroupoforganisms,asitisthecase withdeadwoodandsaproxylicbeetlesorfungi(Bougetetal.,2014; Gossneretal.,2014).

Whateverkindofsurrogateischosen,itisnecessarytocarefully assessitseffectiveness(Gaoetal.,2015).Agrowingbodyof litera-turehasemergedoverthelastdecadestoevaluatesurrogatesand synthesizetheavailableinformation (Lewandowskietal.,2010; RodriguesandBrooks,2007;Westgateetal.,2014).Formanytaxa, theassumptionsbehindcross-taxoncongruencehavenotyetbeen sufﬁcientlytested,norweretheidentityofthefactorsdrivingthe hugevariationobservedacrosssystemsandscales(Gaoetal.,2015). Thesefactorsmayresultininconsistenciesthatmayundermine thereliabilityofsurrogacyindicatorswhenappliedtonovel con-texts(Kirkmanetal.,2012;Westgateetal.,2014);forinstance,the degreeofcross-taxoncongruencemayvarygreatlyinrelationto thespatialscaleofthestudy(Lewandowskietal.,2010;Rodrigues andBrooks,2007).

Differentsurrogatescanalsobedesignedtotakeintoaccount differentfacetsofbiodiversity.Earlyworksfocusedeitheronsingle species(e.g.umbrellaspecies)orontherichnessofaspecies assem-blageasaproxyoftherichnessofawholetaxonorcommunity (Lewandowskietal.,2010).Inthiscase,cross-taxoncongruence was measured by analyzing the existing pairwise correlations betweenthevaluesofspeciesrichnessoftwoormoretaxasampled acrossmanysites.Nevertheless,focusingonlyonthespecies rich-nessfailsatadequatelyrepresentingthevariousfacetsofbiological diversity.Theuseof multiplemeasuresofcommunitystructure (e.g. richness, complementarity and composition) is hence rec-ommendedtodepictacomprehensiveassessmentofcross-taxon congruence (Gioria etal.,2011).Complementarity,for instance, accountsforthecompositionaldifferencebetweensitesanditis therefore often considered in conservation planning,e.g. when selecting a set of sites or actions that togethercould preserve themaximumnumberofspeciesina givenarea(Ferrier,2002; RodriguesandBrooks,2007;Lewandowskietal.,2010).

In this work, we tested: (1) the effectiveness of herb-layer speciesrichness(asataxa-basedsurrogate)andofstandstructural complexity(asahabitat-basedsurrogate)atpredicting simulta-neouslythegeneralpatternsofspeciesrichnessofﬁvegroupsof forest-dwellingorganisms(hereafter“targettaxa”),i.e.,saproxylic andepigeousfungi,beetles,birdsandlichens.Theeffectofthe for-eststandstructuralcomplexitywastestedbothusingasynthetic indexandconsideringasetofstandstructuralfeatures individu-ally.Finally,weevaluated(2)thecross-taxoncongruenceinspecies complementarityandcompositionbetweenherb-layerplantsand thetargettaxa.

2. Methods 2.1. Studyarea

Thedataherepresentedwerecollectedwithinthecontextof therestorationprojectLIFE+‘FAGUS’(11/NAT/IT/135, www.fagus-life-project.eu),andrepresenttheinformationbaselinethatwillbe usedtomonitortheeffectsoftheproject’sconcreteconservation actions.TheprojectfocusedontwohabitatsofEuropeanpriority interestaccordingtotheEUHabitatsDirective(92/43/EEC)i.e.,the habitat9210*–ApenninebeechforestswithTaxusandIlex,andthe habitat9220*–ApenninebeechforestswithAbiesalbaandbeech forestswithAbiesnebrodensis.DatawerecollectedinsixEuropean

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Table1

Maincharacteristicsofthestudyareas. NationalPark Municipality

(studyarea)

NATURA2000SCI Habitat type Coordinates (degrees) Altitude (ma.s.l.) MeanAnnual Precipitation (mm) MeanAnnual Temperature (◦_C) Areasubjected toconservation actions(ha) Numberof sampling plots GranSassoNP Pietracamela

(PratidiTivo)

SCIIT7110202“GranSasso” 9210* 42.5096N 13.5679E

1500 1062 10.6 7.86 5

Pietracamela (Venacquaro)

1250 1097 10.0 17.45 7

Crognaleto (Incodara)

1400 1097 10.0 11.23 7

CilentoNP Corleto Monforte

SCIIT8050033“MontiAlburni” 9210* 40.4705N 15.4317E

1300 1250 10.0 20.21 3

Ottati SCIIT8050033“MontiAlburni” 9210* 40.5136N 15.3292E

1350 718 13.6 11.82 8

Teggiano (M.Motola)

SCIIT8050028“MonteMotola” 9220* 40.3761N 15.4694E

1200 716 13.5 1.3 3

ThehabitattypereferstotheAnnexIoftheEUHabitatsDirective(92/43/EEC):9210*–ApenninebeechforestswithTaxusandIlex;9220*–Apenninebeechforestswith AbiesalbaandbeechforestswithAbiesnebrodensis.

SCI:siteofcommunityinterest.

beech(Fagussylvatica)forestslocatedintheApennines,withintwo Italiannationalparks(Table1).Threeareasarelocatedincentral Italy,withinthe“GranSassoandMontidellaLaga”NationalPark (hereafter“GranSassoNP”).Theremainingthreestudyareasare locatedwithinthe“Cilento,VallodiDianoandAlburni”National Park(hereafter“CilentoNP”),insouthernItaly(Fig.1).

2.2. Samplingdesign

The forest structural features and multi-taxon composition weresampledthroughanon-alignedsystematicsamplingmethod. Basedonapreliminaryfieldsurvey,wefirstdefinedanareaof inter-estforeachstudyarea,i.e.thefractionofthestudyareawherethe habitats9210*and9220*actuallyoccurred.Thetotalsurfaceofthe areaofinterestacrossthesixstudyareaswas70ha.A100×100m square gridwasthen overlapped to theareaof interest, and a samplingplotwasrandomlylocatedwithineachcellofthegrid completelycontainedwithintheareaofinterest.For twostudy areaslocatedin CilentoNP(i.e.‘Corleto Monforte’and ‘Ottati’), thesamplingdesignwasslightlydifferent,inordertobe coher-entwiththemethodsappliedina previousproject(Blasietal., 2010;Burrascanoetal.,2011).Inthiscase,thesamplingplotswere locatedatthenodesofa500×500msquaregrid.Atotalof33plots weresampled,19intheGranSassoNPand14intheCilentoNP. Foreachplot,werecordedthetopographicalpositionintermsof altitude,slopeandaspect.

2.3. Foreststructuralcomplexity

Wesampledthestructuralfeaturesoftheforestplotswithin threeconcentriccircularareaswitharadiusof4,13,and20m. Werecordedthespeciesanddiameter-at-breast-height(DBH)of everystandingtree(livinganddead)havingaDBHgreaterthana giventhresholdforeacharea.Thediameterthresholdswas2.5cm forthe4mradiusarea,10cmforthe13mradiusarea,and50cm forthe20mradiusarea.Wealsomeasuredtheheightofoneout oftensampledtrees,chosenrandomly.Moreover,thelengthand diameterofallthelyingdeadwoodcomponents(minimum diame-ter≥10cm)wererecordedintheintermediatecirculararea(13m radius),assessingalsothedecaylevelbasedonthemethod pro-posedbyHunter(1990).

We then derived eight plot-level structural variables: (1) growingstock volume(m3_/ha),₍₂₎ _number_of _large_living _trees (DBH >40cm), (3) DBH diversity (Gini-Simpson diversity index for 5-cm DBH classes), (4) tree height standard deviation, (5) coarsewoody debris index (CWDI i.e. an index constructed to

scoresitesaccording totheCWD volumeoccurringindifferent decayclasses,seeMcElhinnyetal.,2006),(6)treespeciesrichness, (7)basalareaofstandingdeadwood(m2_/ha),₍₈₎_total_deadwood volume(m3_/ha)._These_structural_variables_were_selected_among thoseroutinelycollectedinplot-basedforestinventories,keeping multicollinearitytoaminimum,andwerethenusedforcalculating theStructuralHeterogeneityIndex(SHI).SHIisanindexderived bySabatinietal.(2015)whichisdesignedtoaccountforthemain sourcesofstructuralcomplexityoccurringinthebeechforestsof southernEurope,whencomparedtoreferenceold-growthstands (Burrascanoetal.,2013;Mottaetal.,2015).Inordertocalculate SHI,each variable was scaledtoa 0–10range according toits overallregionalvariability.Theeightscoreswerethencombined intoasimpleadditiveindexandtransformedtopercentage.SHI wascalibratedagainstadatasetof64foreststandshavingdifferent agesand structures,andbeinglocatedacross12 forestareasin southernItaly.Thecalibrationdatasetencompassesanextentof about137km2 _with_a_substantial_geographical_overlap_with_the studyareashereconsidered(Sabatinietal.,2015).

2.4. Biodiversitysampling

In2013wesampledthespeciesdiversityofdifferenttaxainall theplots.Foreachtaxonweusedanad-hocprotocol.The herb-layervegetationwassampledin20mcircularplotsdividedinto fourquadrantsalongthecardinaldirections.Wevisuallyassigned acovervaluetoeachspeciesineachquadrant,usinganordinal coverclassscalewithclasslimits0.5%,1%,2%,5%,10%,15%,20%,and thereafterevery10%upto100%(eachclassincludesitsupperlimit). Thecovervalueswerethenaveragedacrossthefourquadrants. NomenclatureofspeciesfollowsContietal.(2005).

Epiphyticlichensweresampledonthethreebeechtrees near-esttothecenterofeachplothavingaDBHequalorgreaterthan 16cm. Lichensweresampledusingaportable10×50cmframe composedofﬁve10×10cmquadrats;theframewasplaced on thetreetrunkfacingthefourcardinaldirections,withthebottom partbeingataheightof100cmfromtheground.Alllichenspecies insidetheframeswereconsidered;attheplotlevel,therichnessof thelichenassemblageequaledthetotalnumberofspecies occur-ringacrossthethreesampledtrees.Thefrequencyofeachspeciesin eachgivenplotwascomputedastheproportionofthe60quadrats (10×10cm)inwhichthespeciesoccurred.Thisprotocolfollows theEuropeanguidelinesforlichenmonitoring(Astaetal.,2002). Lichensnomenclatureandgeneralinformationonspecies biolog-icaltraitsandecologywereretrievedfromNimisandMartellos (2008).

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Fig.1.Locationofthenationalparksandofthestudyareas.SCI:siteofcommunity interest(sensuHabitatsDirective;92/43/EEC).

Fungi(bothsaproxylicandepigeous)weresampledinautumn 2013inthesame13mcircularplot(530m2₎_used_for_deadwood sampling.Allthe standingand downeddeadwood components characterizedbyamid-diametergreaterthan10cmwere exam-inedforsporocarpslargerthan1mm,anddataondeadwooddecay class andfungal morphogroupswerealsorecorded.Since fungi weresurveyedonlyonce,ourmeasureshouldnotbeconsidered asaninventoryoftheoverallfungirichness,butratherasa snap-shotintime.ThenomenclaturewasbasedontheDictionaryofthe Fungi(Kirketal.,2008)andtheCABIBioscienceDatabaseofFungal Names.

Forest-dwellingbeetlesweresampledusingonewindowflight trapforeachplot.Trapswereplacedat1.5–2mheightabovethe groundtointercepttheflightofinsects;theywerethentrapped insideapreservingvialcontainingasolutionofwaterandsalt.Since thismethoddoesnotexertanattractionselectivewithrespectto saproxylicbeetles,itwasintegratedthroughtheuseofeclectors (emergencetraps).Eclectorswereusedforcollectingsaproxylic insectsactiveindeadwoodfragmentsontheforestfloor. Depend-ingontheavailabilityofcoarsewoodydebris,uptothreeeclector trapsweresetupondeadwoodfragmentsinthefirstthreedecay classes.Trapswereplacedascloseaspossibletotheplotcenter. Nevertheless,deadwoodfragmentswerenotavailableinallthe samplingplots.Forthisreason,inordertokeepthesamplingeffort constantthroughtheplotsinquantitativeanalyses,thesewererun onlyconsideringthebeetlescollectedthroughwindowflighttraps (∼96%ofthecaptures).Thedataobtainedthroughtheuseof eclec-torswereonlyusedtoprovideanintegrativedescriptionofthe beetleassemblages.Themonitoringofsaproxylicinsectstookplace fromJunetoSeptember2013.Eachtrapwassampledthreetimes, onceevery27–30days.ThespeciesnomenclaturefollowsNieto andAlexander(2010).

Finally,breedingbirdsweresampledthroughone10-minute countpoints,duringwhichwerecordedeveryspeciesdetected. ThespeciesnomenclaturefollowsBrichettiandFracasso(2015).

Eachtaxonwassampledbyadifferentfield teamcomposed byonetothreeobserverswhichconductedthesurveyinallthe studyareas.To ensuredata qualityand homogeneitya respon-sibleincharge ofsupervisingthefieldwork activities(S.B.) was appointedbeforestartingsampling.We comparedthesampling effortamongdifferenttaxabyestimatingtheasymptoticrichness ofeachassemblageusingthefirst-orderJackknifeestimator.We thencalculatedtheratiobetweentheestimatedasymptotic num-berofspeciesandthenumberofspeciesactuallyobservedasan estimationofsamplingcompleteness(Azzellaetal.,2013;Gotelli andColwell,2010).

We decomposed thespecies diversity of each taxonintoits alpha,betaandgammacomponents.Alphadiversityistheaverage numberofspeciesofagiventaxonacrosstheplotsofagivenstudy area;gammadiversityisthetotalnumberofspeciesoccurringina studyareaandbetadiversitywascalculatedwiththemultiplicative approachasˇ=/˛.

2.5. Usingtaxa-andhabitat-basedsurrogatestopredict multi-taxonspeciesrichness

To identify the response of species richness simultaneously across all the target taxa (saproxylic and epigeous fungi, bee-tles,birdsandepiphyticlichens)toincreasinglevelsofherb-layer species richness and standstructural complexity, we ran a set ofGLMMs.ThemodelsassumedaPoissondistributionoferrors andusedalogarithmiclinkfunction.Theresponsevariableswere thespecies richness valuesobserved for eachof theﬁvetarget taxaacrossthe33samplingplots(=165observations).Hereafter, werefertothisastomulti-taxonspeciesrichness.Wemodeled themulti-taxonspeciesrichnessasafunctionoffourexplanatory

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variables,i.e.(1)thespeciesrichnessoftheherb-layer,(2)the struc-turalheterogeneity(SHI)ofagivenplot,(3)habitat(categorical variable:either9210*or9220*)and(4) taxon(categorical vari-able).Sincewehypothesizedthateachtargettaxonmayrespond differentlytoincreasinglevelsofherb-layerrichness,increasing structuraldiversity,andacrossdifferenthabitats,wealso consid-eredthreesecond-orderinteractions,i.e.theinteractionsbetween taxonandtheotherthreevariables.Herb-layerspeciesrichnessand SHIwerescaledtozeromeanandunitvariance,inorderto com-parethemagnitudeoftheireffectonmulti-taxonspeciesrichness. ThefullmodelwasﬁttedwiththeglmerfunctioninR,version3.2.0 (RDevelopmentCoreTeam,2015)withinthepackagelme4(Bates etal.,2015)accordingtotheRformula:

glmer(Richness∼taxa∗(ﬂorarichness+SHI+Habitat) +(1|studyarea),family=poisson)

We first fitted thefull model and then we usedthe dredge functioninR(packageMuMInversion1.12.1),tofitallthe pos-sible(n=35)sub-modelsnestedwithinthefullmodelaccordingto anInformation-Theoretic(IT)approach(BurnhamandAnderson, 2002).ThenestedmodelswererankedbasedontheirAICccriterion (i.e.thesmallsamplesizecorrectionofAkaike’sInformation Crite-ria–AIC),andthebestfittingmodelswereselected(i.e.themodels withina distanceof2AICc unitsfromthefirstrankingmodel). Aftertestingtheselectedmodelsforoverdispersion,thesewere usedtocalculatetheweightedaverage(andrelative95%confidence interval)ofparameterestimatesthroughmulti-modelinference andmodelaveraging(BurnhamandAnderson,2002).Parameters wereestimatedusingthenaturalaveragemethod(Burnhamand Anderson,2002;Grueberetal.,2011).

Inthisway,werankedseveralmodelsandprovideda quantita-tivemeasureoftherelativesupportprovidedbythedatatoeach competinghypothesis.Whentwoormoremodelsachieved simi-larlyhighlevelsofsupport,weusedmodelaveragingtoprovidea robustestimationofregressionparameters.Incomparisontomore traditionalapproaches (e.g.stepwisemethods),theITapproach hastheadvantagetoaccountformodeluncertainty(Burnhamand Anderson,2002;Grueberetal.,2011).Inthisway,wetested:(1) whichofthetwosurrogates(i.e.,herb-layerspeciesrichnessorSHI) receivedmoresupportfromthedataaspredictorsofmulti-taxon speciesrichnessand(2)whethertheyactedinacomplementaryor redundantway.

Finally,wetestedwhethereitherthespeciesrichness ofthe targettaxaortheresidualsofourGLMMmodelsshoweda con-sistentlylowerspatialautocorrelationinthosestudyareaswhere thesamplingplotswerelocatedfurtherapart(i.e.,‘Corleto’ and ‘Ottati’).WecalculatedtheMoran’sIstatisticforeachtaxon sep-aratelyandfoundnosystematiclowerautocorrelation(resultsnot shown).

2.6. Modelingtheresponseofmulti-taxonspeciesrichnessto foreststructuralattributes

BesidestestingtheeffectofSHIonmulti-taxonspeciesrichness, wealsousedGLMMstoexploretheeffectofindividualstructural variables,inordertoobtaininsightsonwhichstructural parame-tershaveahigherpredictivepoweronthepatternsofmulti-taxon speciesrichness.WeﬁttednineGLMMs,models1–8includedeach oneofthestructuralattributesusedforcalculatingtheSHI,model 9wasanullmodel.Allthemodelsalsoincludedtheco-variables ‘taxon’and‘habitat’.Models1–8alsoincludedtheinteractionterms betweentaxonand(1)thetargetstructuralvariableand(2) habi-tat.Finally,werankedtheseninemodelsasdescribedaboveto understandwhichindividualstructuralvariablebestpredictedthe

multi-taxonspeciesrichness,verifyingifanyoftheseperformed betterthanthenull-model.

2.7. Congruenceincomplementaritypatternsbetweenthe herb-layerandothertaxa

Speciescomplementaritybetweenasurrogateandatargettaxa measureswhetherthetwotaxacumulatespeciesatthesamerate asthenumberofplotsincreases.Ferrier(2002)derivedanindexof speciescomplementarity(SpeciesAccumulationIndex–SAI)based onaccumulationcurves.SAIﬁrstcalculatesanoptimalcurve (O-curve),i.e.anaccumulationcurvewhichplotstheproportionof speciesofatargettaxonrepresentedwhentheplotsareselected in theorderthat maximizes therateof accumulationof target species.Thenitcalculatesasurrogatecurve(S-curve),i.e.an accu-mulationcurvereportingtheaveragepercentageoftargetspecies representedwhenselectingplotswiththeorderthatmaximizes thespeciesrichnessofthesurrogatetaxon(inthiscasethe herb-layerplants).Finally,thesecurvesarecomparedtoameanrandom curve(R-curve),whichisthemeanof999individualaccumulation curvesthatplotthecumulativenumberofspeciesofatargettaxon whenplotsareselectedinarandomorderwithoutreferencetothe surrogatedata.SAIiscalculatedas:

SAI= S−R O−R

whereS=theareaunderthesurrogatecurve,R=theareaunderthe meanrandomcurve,andO=theareaundertheoptimumcurve. Theindexrangesbetween−1and1.Itisequalto1foraperfect surrogate,itis0orlessforasurrogatethatperformsnobetterthan arandomselectionofplots.Weusedbootstrappingtocalculate theconﬁdencelimitsasdescribedinFerrier(2002).TheRscriptfor calculatingandplottingSAIanditsconﬁdenceintervalsisprovided intheSupplementarymaterial–Appendix1.

2.8. Speciescompositionoftargettaxavs.herblayerplantsand foreststructuralattributes

Basedonspeciescompositiondata,wecreatedanordination diagramforeachtaxonusingnonmetricmultidimensionalscaling (NMDS).WeranNMDSusingHellingerdissimilaritiesforthosetaxa forwhichwehadabundancedata(i.e.herb-layervegetation, epi-phyticlichensandbeetles),andJaccarddissimilarityfortaxafor whichonlypresence-absencedatawereused(i.e.birds,saproxylic andepigeousfungi).Ineachcase,werun500NMDSordinations withrandomstartingconfigurationtofindthemoststablesolution (i.e.,loweststressvalue).Tohelptheinterpretationofthe ordina-tionplotswesuperimposedthosestructuraland environmental variablessignificantlyrelatedtotheordinationaxesaccordingto theenvfitroutineoftheveganpackage(Oksanenetal.,2013). Sig-nificancewastestedusingpermutationtests(n=999).Giventhe nestedstructureofourdataset(i.e.eachstudyareaencompassed morethanonesamplingplot),thepermutationofplotswas con-strainedatthestudyarealevelusingtheargumentstratainthe functionsenvfit.Sinceplotswithinagivenstudyareaareexpected tobemoresimilartoeachotherthantwo plotsrandomly cho-senoverthewholedataset,thispermutationstrategyreturneda conservativeestimationofthesignificanceoftheresults. Explana-toryvariablesincludedSHI,theeightstructuralvariablesdescribed above,standbasalareaanddensity,andaltitude.

Finally,wemadeaNMDSordination(sameprocedureasabove) basedontheeightstructuralvariables usedforcalculating SHI. Theeightstructuralvariableswerescaledtozeromeanandunit varianceandthenusedtobuildaEuclideandissimilaritymatrix.

ThepairedcongruencebetweentheNMDSordinationsbased onthespeciescompositionofdifferenttaxaand(1)thespecies

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Table2

Alpha-,beta-andgamma-diversityobservedforeachtaxoninthe33samplingplots,asymptoticnumberofspecies(estimatedgamma)anditsratiowiththenumberof speciesactuallyobserved.Thestandarddeviationofalphadiversityisreportedinparenthesis.

Alpha Beta ObservedGamma EstimatedGamma(Jackknife1) Observed/expected(%)

Plants(herb-layer) 35.5(16.6) 6 179 231.4 77.4 Beetles 15(6.3) 8.7 130 193.0 67.3 Fungi(saproxylic) 8.8(4.0) 10 88 131.6 66.9 Fungi(epigeous) 5.6(2.8) 11.5 65 96.0 67.7 Birds 6.8(1.6) 6.9 47 62.5 75.2 Lichens 16.3(5.9) 3.6 58 64.8 89.5

composition of herb-layer plants and (2) standstructural vari-ableswasassessedusingProcrustesrotationonNMDSordination (LegendreandLegendre,1998).Thesignificanceofthefitofthe ordinationconfigurationswasestimatedusingpermutation-based (n=999)protestanalysis(functionprotestintheRpackagevegan). Protestverifieswhethertwodatasetsexhibitgreatercongruence thanwouldbeexpectedatrandom,bytestingwhetherthe Pro-crustesstatisticm2_(which_represents_a_{goodness-of-fit}_statistic_of orthogonalProcrustesanalysis)issmallerthanexpectedbychance. Again,weusedtheargumentstratatoaccountforthenested struc-tureofthedataset.

3. Results

3.1. Speciesdiversityoftheconsideredtaxa

Theherb-layerwasthemostspeciesrichtaxonamongthose considered in this study, both at the alpha and gamma level (Table2).Theplantspeciesmostcommonlyencounteredinthe herb-layerwere Rubus hirtusand Viola reichenbachiana.Lactuca muralisandAremoniaagrimonioideswereverycommonin habi-tat9210*whileDaphnelaureolaandGeraniumrobertianumwere themostfrequentspeciesintheherb-layerofhabitat9220*.

Lichenshadarelativelyhighalphadiversitywhencompared totheothertaxa,but alow betaand gammadiversity, indicat-ingthatthis taxonhada lowbetween-plotvariation.Themost frequently recorded lichen species were Lecidella elaeochroma, thecommonest epiphyticlichenofItaly,andtwospeciesofthe Lecanoragenus,i.e.L.allophanaandL.intumescens,thelatter usu-allyfoundonsmoothbark,withoptimuminhumidbeechforests (Nimisand Martellos,2008).Interestingly,we foundAnaptychia crinalis(studyareaIncodara),a particularlyrare andvulnerable species(Nascimbeneetal.,2013)whichisconﬁnedtohumidbeech forests(NimisandMartellos,2008).Wealsofoundfertilethalliof Lobariapulmonaria(CorletoMonforteandOttati),alichentypically associatedtostandswithalongecologicalcontinuitythatis consid-eredagoodindicatoroftheoccurrenceofotherrareandsensitive lichenspecies(Brunialtietal.,2010;Nascimbeneetal.,2010).

Fungihadingeneral,thehighestbetadiversityamongthesix consideredtaxa.Thespeciesmostfrequentlyfoundinthestudy areaswereMycenapura,HebelomasinapizansandMarasmius wyn-neaeamong the epigeousspecies, and Bisporella citrina,Xylaria hypoxylonandPolyporusmelanopusamongthesaproxylicspecies. WealsofoundthespeciesOssicaulislignatilis(Incodara),whichis amongthe21indicatorspeciessuggestedforassessingthe conser-vationvalueofbeechforestsinEurope(Christensenetal.,2004), andthespeciesFomesfomentarius(CorletoandOttati),whichis fre-quentlyencounteredinunmanagedbeechforestsandconstitutes ahabitatresourcefor severalLepidopteraandColeopteraspecies (Mülleretal.,2007).

Thebeetle species mostfrequentlyencountered were Meso-dasytes plumbeus, Athous haemorrhoidalis, Nothodes parvulus, StenurellamelanuraandAgriotesinfuscatus.Noteworthy,wefound two specimen of Mordellochroa milleri (study areas Ottati and Venacquaro)which is classiﬁed as criticallyendangered in the

Italianredlistofsaproxylicbeetles(Audisioetal.,2014).Outof the130beetlespeciesencountered,wefoundahighproportionof singletons(57),i.e.speciesforwhichwefoundonlyoneindividual. Approximately80%ofthespeciesweresaproxylic,i.e.,speciesthat dependondeadwood,duringatleastapartoftheirlifecycle.

The most common bird species found were Periparus ater, Fringillacoelebs,andErithacusrubecula.Insomestudyareas,we alsodetectedsomepriorityspeciesaccordingtoAnnex1ofthe BirdsDirective(2009/147/EC),i.e.thecollaredﬂycatcher(Ficedula albicollisfoundinOttati,Corleto,IncodaraandVenacquaro),the Europeanhoneybuzzard(PernisapivorusinIncodara),the white-backed woodpecker (Dendrocoposleucotos in Incodara) and the blackwoodpecker(DryocopusmartiusinOttati).

Thecompletenessofthesampling(Table2)wasoverall satis-fyingandcomparableamongﬁveoutofsixtaxa(66–77%),with theexceptionoflichensforwhichthesamplingcompletenesswas muchhigher(89.5%).

3.2. Foreststructuralheterogeneity

TheSHIindexrangedwidelyacrosstheforestplotsandstudy areas:itwascomprisedbetween26.8%foraplotinthestudyarea Ottatiand83.4%foraplotinIncodara(TableS1).Thestudyareas locatedinCilentoNPhadlowerSHIaveragesthanthoselocatedin GranSassoNP.Intheformer,meanSHIrangedbetween39.2%and 51.4%,whileinthelattertheyrangedbetween55.5%and66%. 3.3. Performanceoftaxa-andhabitat-basedsurrogatesat predictingthespeciesrichnessoftargettaxa

Thebest-fittingGLMMmodel,i.e.themodelreturningthe low-estAICc, includedasexplanatoryvariables thespecies richness oftheherb-layer,taxonandtheirinteraction(Table3).Theonly othermodelreceivingsomesupportfromthedata(i.e.havinga AICc<2)hadthesamestructure ofthebest-fittingmodelbut alsoincludedSHIasexplanatoryvariable.Interestingly,the mod-elsincludingSHIbutnottheherb-layerspeciesrichnessreceived almost nosupportfromthe empirical data,and werethus not includedinthelistofthebest-fittingmodels.

Themagnitudeoftheoveralleffectofherb-layerspecies rich-nessontheothertaxawasrelativelysmall(Fig.S1,TableS2).The interactionbetween‘taxon’and herb-layerspeciesrichness was alwaysincludedasanexplanatoryvariableamongthetwo best-ﬁttingmodels,indicatingthatdifferenttaxarespondeddifferently toincreasinglevelsofherb-layerdiversity(Fig.2).Ontheonehand, wedidnotseeastrongrelationshipbetweenthespeciesrichnessof theherb-layerwhencomparedtotherichnessofbeetles,epigeous fungiandbirds.Ontheotherhand,weobservedaclearrelationship betweenthespeciesrichnessoftheherb-layerandtherichnessof saproxylicfungiandlichens.Plotswithhigherherb-layerspecies richnesswerepoorerinsaproxylicfungi(TableS2),butcontained morespeciesoflichens(Fig.2,Fig.S1).Afterback-transformation, ourmodelsreturnedthatforanincreaseof10speciesinthe herb-layer(from30to40species),theexpectedchangeinrichnesswas ca.−1.2unitsforsaproxylicfungiand+1.1unitsforlichens.

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Table3

Listofthebest-fittingGLMMsmodels(i.e.themodelsencompassing95%oftheAkaikeweights),modelingtheresponseofmulti-taxonspeciesrichnessto(1)herb-layer speciesrichness,and(2)foreststandstructuralcomplexityacrossfivetargettaxa.Multi-taxonspeciesrichnessisheredefinedasthespeciesrichnessvaluesobservedfor eachofthefivetargettaxa(saproxylicandepigeousfungi,beetles,birdsandlichens)acrossthe33samplingplot(=165observations).Eachmodelaccountsfordifferentstudy areas(n=6)asarandomeffect(intercept),assumesaPoissonerrorstructureandusesalogarithmlinkfunction.Foreachmodel(rowheadings)wereported:(1)eitherthe estimatedregressioncoefficient(forquantitativevariables)oracheckmark‘√’(fornominalvariablesandinteractions)indicatingwhenaparticularterm(columnheading) wasincludedinthemodel,(2)thedegreesoffreedom(df),(3)thelog-likelihood,(4)AICc,(5)AICcand(6)theAkaikeweight.ThemodelswererankedbyAICc.AICc representsthedistanceinAICcunitsfromthebestfittingmodel.

Intercept Plantrichness SHI Taxon Plantrichness:taxon df logLik AICc Delta Weight

mod.26 2.742 0.0275 √ √ 11 −437.6 899.0 0 0.669

mod.30 2.742 0.0247 0.036 √ √ 12 −437.1 900.4 1.41 0.331

Table4

Rankingofthe8GLMMsmodelseachincludinganindividualstructuralvariablesusedaspredictorofmulti-taxonspeciesrichness,andanullmodel,i.e.amodelincluding onlythecovariablesbutnotthestandstructuralvariablesasexplanatory.Eachmodelaccountsfordifferentstudyareasasarandomeffect,assumesaPoissonerrorstructure andusesalogarithmlinkfunction.Foreachmodel(rowheadings)wereported:(1)theestimatedregressionslopeestimatedforthetargetstructuralvariable(ˇ),(2)the degreesoffreedom(df),(3)thelog-likelihood,(4)AICc,(5)AICcand(6)theAkaikeweight.ThemodelswererankedbyAICc.

Model ˇ df logLik AICc AICc Weight

Totaldeadwoodvolume 0.100 13 −439.4 907.2 0.0 0.648

Nullmodel – 7 −447.5 909.8 2.6 0.178 Treesp.Richness 0.081 13 −441.4 911.3 4.1 0.084 GrowingStock −0.017 13 −442.6 913.6 6.4 0.026 GINI −0.062 13 −442.6 913.7 6.5 0.025 LLT(dbh>40cm) −0.013 13 −443.1 914.6 7.3 0.017 Height(sd) −0.025 13 −443.1 914.6 7.4 0.016 CWDI 0.090 13 −444.5 917.4 10.2 0.004

Standingdeadwood(BA) −0.027 13 −445.3 919 11.8 0.002

Overall,SHIhadaveryweakeffectonmulti-taxonspecies rich-ness.Foranincreasein10unitsofSHI(from30to40%),therichness ofthetargettaxawasexpectedtoincreaseofca.0.3units;thisresult wasconstantacrosstaxa,sincetheinteractionbetween‘taxon’and SHIwasneverincludedamongthebest-ﬁttingmodels.Similarly, thehypothesisthattherichnessofthetargettaxaresponded differ-entlytoincreasinglevelsofherb-layerspeciesrichnessacrossthe twohabitatshereconsideredreceivednosupportfromthedata. 3.4. Responseofmulti-taxonspeciesrichnesstoforestindividual structuralattributes

Out of the eight structural variables we tested, only the total deadwoodvolume performedbetterthan a null model at

05 10 15 20 25 30

Herb−layer plant Richness

Species Richness 10 20 30 40 50 60 70 Beetles Lichens Saproxylic fungi Epigeous fungi Birds

Fig.2. Themodel-averagedresponseofthespeciesrichnessoftheﬁvetargettaxato increasinglevelsofherb-layerplantrichnessaspredictedbythebest-ﬁttingGLMMs models.Thestudyareawastreatedasarandomeffect(randomintercept). Mod-elswerecomparedandaveragedinanInformation-Theoreticcontext.Themodels assumedaPoissondistributionoferrorsandusedalogarithmiclinkfunction.

predictingmulti-taxonspeciesrichness(Table4).Thenullmodel wasthesecondbest-ﬁttingmodel(_AICc=2.6).Theother struc-turalvariablesinstead,didnotreceivesupportfromthedataas predictorsofmulti-taxonspeciesrichness.

Althoughbeingpositively relatedto themulti-taxonspecies richness,thetotaldeadwoodhadarelevantpredictiveeffectonly forthespeciesrichnessofcertaintaxa(Fig.3).Forinstanceinthe habitat9210*, themodel predictedthat, for an increase inthe amountsofdeadwoodfrom30to40m3_/ha,_the_richness_of bee-tlesand saproxylicfungiisexpectedtoincrease by1.4and 2.2 speciesrespectivelywhiletherichnessoflichensisexpectedto decreaseby0.7species(TableS3).Forhabitat9220*,theresults werequalitativelysimilar,althoughalltheregressioncoefﬁcients wereslightlylower.Theresponseofthespeciesrichnessofother taxatodeadwoodavailabilitywasveryweak.

3.5. Congruenceincomplementaritypatternsbetweenherb-layer andothertaxa

The analysisof SAI patternsshowed only a limited congru-enceinspeciesaccumulationbetweentheherb-layervegetation and the target taxa (Fig. 4). In particular, plants were a good surrogateonlyforbeetles(SAI=0.19,p<0.05),whilewhen consid-eringother targettaxa SAIwas notsigniﬁcantly differentfrom zero.

3.6. Thesurrogacyofherb-layervegetationandstandstructure forthespeciescompositionoftargettaxa

Thetwo-dimensionalNMDSreturnedasufficienttogood rep-resentationofspeciesdiversityoftheconsideredtaxa:thestress values werecomprised between0.134for plants and 0.206for beetles(Fig.S2).We observedthat differentstructural features correlated withtheordination axes of differenttaxa. In partic-ular,the species richness of thetree layer correlated withthe axis 2 for both thebeetles and epigeous fungi.Growing stock wassignificantlycorrelatedwiththespeciescompositionofplants andepigeousfungi.Thespecies compositionofsaproxylicfungi wassignificantlycorrelatedbothwiththeGINI-Simpsonindex(an

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05 10 15 20 25 30

Habitat 9210

Total Deadwood (m3/ha)

Species Richness 0 10 20 30 40 50 0 5 10 15 20 25 30

Habitat 9220

Total Deadwood (m3/ha)

0 10 20 30 40 50 Beetles Lichens Saproxylic Fungi Epigeous Fungi Birds

Fig.3.Responseofthespeciesrichnessoftheﬁvetargettaxatoincreasinglevelsoftotaldeadwoodacrossthetwohabitatshereconsidered(either9210*or9220*).The relationshipwasmodeledthroughGLMMswhichassumedaPoissondistributionoferrorsandusedalogarithmiclinkfunction.Studyareawastreatedasarandomeffect (randomintercept).

indicatoroftheuneven-agedstructureofastand)andwiththe vol-umeofstandingdeadwood.Finally,altitudecorrelatedsigniﬁcantly withtheNMDSaxesofthreetaxa,i.e.plants,beetlesandlichens (Fig.S2).

TheProcrustesrotation(Table5)showedthatthecorrelations observedbetweentheherb-layerandthetargettaxawere rela-tivelyhigh(0.319–0.777)andgreaterthanthoseobservedbetween

theforeststructureandthetargettaxa(0.180–0.401).Nevertheless, mostofthesecorrelationswerenotstatisticallysignificant, possi-blybecauseofthenestednatureofthedataset.Onlythesaproxylic fungihada statisticallysignificantcommunitycongruence with herb-layerplants.Noneoftheconsideredtaxashowedasignificant concordancewiththeNMDSordination basedonthestructural variables. 0 5 10 15 20 25 30 0.0 0 .2 0.4 0 .6 0.8 1 .0

Beetles

% target species

SAI = 0.188* (0.114; 0.596) 0 5 10 15 20 25 30 0.0 0 .2 0.4 0 .6 0.8 1 .0

Saproxylic Fungi

SAI = −0.165 (−0.177; 0.386) 0 5 10 15 20 25 30 0.0 0 .2 0.4 0.6 0.8 1.0

Epigeous Funghi

SAI = −0.206 (−0.196; 0.36) 0 5 10 15 20 25 30 0.0 0 .2 0.4 0 .6 0.8 1 .0

Birds

% target species

SAI = 0.127 (−0.032; 0.574) 0 5 10 15 20 25 30 0.0 0.2 0.4 0 .6 0.8 1 .0

Lichens

# of sites

SAI = −0.025 (−0.008; 0.575)

Legend

Optimal Curve

Random Curve

Surrogate Curve

Fig.4. Between-taxacomplementarityasassessedusingSpeciesAccumulationIndex(SAI).Speciescomplementaritywasassessedbycomparing:asurrogatecurve,indicating theaveragepercentageoftargetspeciesrepresentedwhenselectingplotswiththeorderthatmaximizesthespeciesrichnessofthesurrogatetaxon(inthiscaseherb-layer); arandomcurve,indicatingtheaveragepercentageoftargetspeciesrepresentedwhenplotsareselectedrandomlyover999replications;anoptimumcurvewhichmaximizes thenumberoftargetspeciesrepresented.SAI(bold)andtherelativeconﬁdenceintervals(inparenthesis)arereportedforeachcurve(theasteriskrepresentsasigniﬁcant valueatp<0.05).

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Table5

Congruencebetweenthemultivariateordinationsbasedoneither(1)theherb-layerspeciescompositionor(2)thestandstructuralattributesandtheordinationsbased onthecommunitycompositionofdifferenttaxa,asreturnedbyProcrustesanalysis.m2

12isthesumofthesquareddistancesbetweencorrespondingpointsofthetwo

ordinations.

Herb-layerplants ForestStructure

m2 12 Correlation p-value m 2 12 Correlation p-value Beetles 0.396 0.777 0.188 0.840 0.401 0.280 Lichens 0.751 0.499 0.616 0.890 0.332 0.597 Fungi(saproxylic) 0.898 0.319 0.034* _0.982 _0.135 _0.950 Fungi(epigeous) 0.79 0.458 0.247 0.968 0.180 0.601 Birds 0.744 0.506 0.123 0.936 0.252 0.964 * _Signiﬁcant_results_at_p_<_0.05. 4. Discussion

4.1. Limitedcross-taxoncongruencebetweenherb-layerplants andothertaxa

Ourdataprovidedalimitedsupporttothehypothesisthatthe herb-layerplantsortheforeststructuralcomplexitycanbeused assurrogatesoftheoverallmulti-taxonspeciesrichnessofasite, atleastintheinvestigatedstudyareas.Acrossthethreefacetsof biodiversityhereconsidered(i.e.speciesrichness, complementar-ityandcomposition),weobservedonlyafewsigniﬁcantcongruent patternsbetweenthesetwosurrogatesandthetargettaxa.These resultsareinlinewitharecentreviewoverthestrengthof biodi-versityindicators,whichfoundonlyaweakevidencethatvascular plantsmaybeeffectivesurrogatesinEuropeanforests(Gaoetal., 2015).

Nevertheless,whenconsideringspeciesrichness,theherb-layer plantsperformedbetterthanstandstructuralcomplexityat pre-dictingmulti-taxonspeciesrichness,andwasconsistentlyselected asthebestpredictoreveniftheoverallmagnitudeofthis relation-shipwasweak.Theweakpositiverelationshipbetweenherb-layer plantsandthemulti-taxonspeciesrichnesswaspartiallydrivenby theeffectoftwospeciﬁctaxa,namelylichensandbeetles(Fig.2).In thecaseoflichens,anotherstudyperformedinthebeechforestsof theApennines(Blasietal.,2010)foundasimilarcongruencethat mayonthesimilarlightrequirementssharedbythesetwotaxa. Althoughwedidnotdirectlymeasurethecanopyopennessinthe sampledplots,weinferthatthoseplotswherethecanopyis rela-tivelyopen,i.e.wheremoresunlightreachestheforest-ﬂoor,are morelikelytohostahigherdensityanddiversityofbothunderstory vegetation(Sabatinietal.,2014b)andepiphyticlichens(Aragon etal.,2010).

Also the congruent patterns of species complementarity betweenplantsandbeetlesmaybepartiallyexplainedbythe occur-renceofgapsintheforestcanopy.Gapsareusuallycharacterized byanincreasedabundanceofﬂower-andfruit-bearingplants(e.g. Rubusspp.),whichmayrepresentakeyresourceformany saprox-ylicbeetles(Bougetet al.,2014).Indeed,the beetlespecies we capturedmorefrequentlyhaveasaproxylicbehaviorduringtheir larvalstage,whiletheadultsareoftenfoundonﬂoweringplants inboththetree-andherb-layer.AtypicalexampleisStenurella melanura(Cerambycidae),which feedsondecayingwoodduring itslarvalstage,whileasanadultitreliesonthepollenof herb-layerspecies,suchasDigitalispurpurea,Rubusfruticosusandseveral AsteraceaeandApiaceaespecies(Sama,2002).

The relationship between plants and saproxylic fungi was insteadcomplex.Thesetaxa showedsimilarpatternsof species composition(asshownthroughtheProcrustesanalysis). Never-theless,whenthespeciesrichnesswasconsidered,weobserved thathigherlevelsofherb-layerspeciesrichnesswereassociated tospecies-poorsaproxylicfungicommunities and viceversa. A possibleexplanationforthisdecoupledtrendofcross-taxon con-gruencebetweenspeciescompositionandrichness mayrelyon

theroleofEuropeanbeechintheseecosystems.Firstly,beechis ashade-tolerantspecieswhichformsverydensecanopies.Under adensebeechcover,thelightlevelsattheforest-ﬂoorare usu-allyverylow.Consequently,theherb-layerisusuallypoorofplant speciessinceonlythosespeciesspecializedtoverylowlight lev-elsareabletothrive(Burrascanoetal.,2011;Mölderetal.,2008; Sabatinietal.,2014a).Secondly,adenseforestcanopymayincrease thehumidityattheforestﬂoorandthismayhaveafavorableeffect onthediversityofsaproxylicfungi.Finally,inbeechforests,the highestnumberofsaproxylicfungispecies isusuallyassociated tobeechdeadwoodinintermediatedecayclasses(Mülleretal., 2007;Brunetetal.,2010;Persianietal.,2015;Granitoetal.,2015). Beechlackstypicalheartwoodandissimilartosomespeciesof soft-woods,especiallythosewithahighmoisturecontentinthetrunk (Penninckxetal.,2001).Beechwoodisalsocharacterizedbythe homogeneousdistributionofsyringylligninthroughoutthexylem andishighlysusceptibletoagreatrangeofwooddecayingfungi whichcancolonizeandreadilydegradeit(Schwarze,2007).For thesereasons,wehypothesizethat,toacertainextent,thenegative relationshipbetweenherb-layerandsaproxylicfungispecies rich-nessmaybemediatedbythecontrastingcorrelationthatthesetwo taxamayhaveinrelationtothedominanceofEuropeanbeech. Sim-ilarly,thecongruenceinspeciescompositionmaybeinterpreted byhypothesizingsimilarpatternsofoccurrenceofthose shade-tolerantherb-layerplantsthataremoretypicallyfoundinbeech forestsandofthespeciesassemblagesofsaproxylicfungithatare strictlyrelatedtobeech.

4.2. Foreststructuralheterogeneityisnotaneffectivepredictorof thebiologicaldiversityofthetargettaxa

Thestructuralheterogeneityofaforeststandhasoftenbeen assumedasagoodpredictorofitscontributiontooverall biodiver-sity(McElhinnyetal.,2005;Gossneretal.,2014).Thisassumption hasbeeninsufﬁcientlytested inliterature anddifferentstudies reportedcontrastingresults(Gossneretal.,2014;Gaoetal.,2015). Inthepresentstudy,wetestedwhetheranindexofstructural com-plexity(SHI)explicitlydesignedtoaccountforthemainsources ofstructuralcomplexityoccurringinthebeechforestsof south-ernEuropecouldbeusedforpredictingthemulti-taxonspecies richnessofastand.SHIperformedworsethantheherb-layerand weonlyfoundamoderateevidencethatSHImaybeusedto com-plementtheinformationprovidedbytheherb-layer.Infact,even ifwefoundthatforincreasinglevelsofSHIthespeciesrichness ofthetargettaxaisexpectedtoincrease,themagnitudeofthis effect was extremely weak. Noticeably, we did not ﬁnd a dif-ferentialresponseofdifferenttargettaxatoincreasinglevelsof SHI.

Whenconsideredindividually,mostofthestructuralvariables werenotgoodsurrogatesoftheoverallbiodiversityeither.Theonly exceptionwasdeadwoodvolume.Forincreasinglevelsof dead-woodamounts,therichnessofbeetlesandsaproxylicfungiwas predictedtoincrease.Furthermore,thecompositionofsaproxylic

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fungiassemblageswassigniﬁcantlyrelatedtotheamountof stand-ingdeadwoodinaplot(Fig.S2),suggestingthat,besidesthetotal amountofdeadwood,thequalityofthedeadwood(e.g.standing vs. lying, aswell asthedecay stage, seeSection 4.1)mayalso haveanimportantroleindeterminingthecompositionof saprox-ylicfungiassemblages(Persianietal.,2010).Indeed,tomaintain richsaproxylicbeetleassemblagesinbeechforests,bothlyingand standingdeadwoodofvaryingdimensionsarenecessary(Brunet etal.,2010).Ingeneral,deadwoodvolumeanditsdiversiﬁcation amongvarious componentsarekeyvariables forpredictingthe richnessofbeetlesandsaproxylicfungi(Christensenetal.,2004; Brunetetal.,2010),alsoinEuropeanforestecosystems(Gaoetal., 2015).

Surprisingly,wedidnotﬁndanyrelationshipsbetween multi-taxon species richness and other structural variables that are usually acknowledged as potential biodiversity indicators. For instance,ourdatadidnot supportthehypothesisthatthe rich-nessofthetreelayercouldbeusedtopredicttherichnessofother taxa,althoughthetreelayerwasoftenreportedasa good indi-catorofforestbiodiversity(Barbieretal.,2009),anddespitethe richnessofthetree-andherb-layerswerefoundtobesigniﬁcantly correlatedtoeachotherinseveralEuropeanbeechforests(Abbate etal.,2015;Burrascanoetal.,2011;Sabatinietal.,2014a). Simi-larly,thedensityoflargelivingtreesdidnotperformbetterthana nullmodelatpredictingneitherthemulti-taxonspeciesrichness ingeneralnortherichnessofforest-dwellingbirdsandepiphytic lichens,althoughthesetaxaareoftenassociatedtokeystructural featuresthatareusuallyassociatedtolargelivingtrees,e.g.tree cavitiesforbirds(Brunetetal.,2010;Brunialtietal.,2010).Possibly, thisisbecausetheforeststandsthatwesampledarestillexploited fortimberproduction,althoughextensively;therefore,eveniftrees withaDBHgreaterthan40cmoccur,thisdoesnotimplicitly indi-catetheoccurrenceneitherofkeystructuralfeatures,norofthe speciesthatarelikelytotakeadvantageofthem.Indeed,the con-ventionalmanagementofbeechstandsusuallyactivelyremoves hollow-andfungus-bearingtrees,sincethesehavealoweconomic value.For this reason, in managedstandsor recently managed forests,thedensityoflargelivingtreesisanimperfectindicator oftheoccurrenceoftheseimportantstructures,asitwasfoundin apreviousstudy,wherethespeciesrichnessofsaproxylicbeetles wasstrictlyrelatedtotheactualdensityofrelevantmicrohabitats, butnottothedensityoflargetrees(Bougetetal.,2014).Asregards tolichens,mostofthespeciesthatarerelatedtounmanaged for-eststandshaveadispersalpotentiallimitedtoshortdistances.For thesespecies,thelong-termcontinuityandspatialdistributionof largelivingtreeremnants,whichserveasasourceofpropagules afterharvesting,maybemuchmoreimportantatexplainingtheir presencethanthecurrentdensityoflargelivingtrees(Hazelland Gustafsson,1999).

Basedonourresults,eachtaxonrespondedtoaparticularsetof structuralvariables.Therefore,thechoiceofastructuralfeatureto beusedasahabitat-basedsurrogateshouldbedrivenbythe knowl-edgeofthehabitatrequirementsofthetargettaxa.Nevertheless, otherconfounding factorsmay arise and weakenthe effective-nessofasurrogate.Paststanddisturbancehistory,environmental covariates,aswellasthresholdsornonlinearityintheresponse oftargettaxamayallcontributeatweakeningthesurrogate-target relationships,especiallywhensamplingsizeisrelativelysmall,and whenﬁne-scalepatternsareconsidered(Lombardietal.,2015). 4.3. Factorspotentiallyaffectingsurrogacy:powerandscale

The low magnitude of the cross-taxon congruence between plantsand otherindividualtaxa, aswellasthelittlepredictive powerofthehabitat-basedsurrogatesweused,representsanew pieceofevidencethatsurrogatesareausefultoolonlywhenthey

are properly designed and carefullytested. Some recent meta-analysesreportedthatcross-taxoncongruencevariesenormously, evenforthesamepairsoftaxa,amongstudiesencompassing differ-entspatialscalesorbiogeographiccontexts(RodriguesandBrooks, 2007;Lewandowskiet al.,2010;Westgate etal.,2014). Under-standingtherobustnessofagivensurrogateisprobablythemost compellingchallengefortheproximatefuture.Somegeneraltrends areemergingintheliterature:forinstanceahighercross-taxon congruenceisexpectedwhenabroaderspatialextentis consid-ered(Lewandowskietal.,2010;Westgateetal.,2014).Whenthe spatialscaleisbroad,ahigherenvironmentalvariabilityisusually sampled,andthusthediversitypatternsofdifferenttaxaaremore likelytoco-vary,alsoinrelationtothecommonbiogeographical andevolutionaryhistorysharedbythesetaxa(Gioriaetal.,2011; RooneyandAzeria,2015).Inaddition,thesamplingeffortaswell asthesizeoftheregionalspeciespoolsmayhavearelevanteffect onthestrengthoftherelationshipbetweentwotaxa,sincelarger speciespoolsmayprovidegreaterbiologicalresolutiontodetect changesinenvironmentalcondition(RooneyandAzeria,2015).

Inthisstudy,weconsideredanesteddatasetwithlimited num-berofsamplingplots(33),whichwererelativelysimilarintermsof overstorycomposition,altitudinalrangeandbioclimate.Although thespatialdomainwasrelativelybroad(thefarthestplots were about300kmapart),thedatasetwasdesignednottoencompass anymajorenvironmentalgradients.Indeed,welimitedouranalysis torelativelywell-preserved,lowintensitymanagedbeechforests, andweonlyexploredthecross-taxoncongruencethereinataﬁne spatialscale(smallgrain).Inthiscontext,wecannotexcludethat samplingstandsalonga broaderenvironmentalgradient,would resultinstrongerpatternofcross-taxoncongruence.Indeed,when consideringstandscharacterizedbydifferentconservationstatus, managementregimesordisturbancehistory,ahighercross-taxon congruenceislikelytooccurthanwhenconsideringrelatively sim-ilarstandsasinourcase.

Similarly,ahighernumberofsamplingplotsmayalsoimprove theresults.Nevertheless,asmalldatasetistheruleratherthanthe exception whenresearchaimsat informingforestmanagement forbiodiversityconservation,ormonitoringrestorationprojects, sincehigh-qualitybiologicaldatacollectionisveryexpensiveand time-consuming.Tobeuseful,asurrogateshouldhavea power sufﬁcientfordetectingthevariationofatargettaxaevenwhenthe samplingsizeissmall(Lindenmayeretal.,2014).Ifastrong cross-taxoncongruencecannotbeassumed,likeinourcase,itappears justiﬁedtoundertaketheeffortofperforminganextensive assess-mentofmulti-taxonomicaldiversitytolimitthelikelihoodoftaking poorconservationdecisionsbasedontheuseofweakorineffective surrogates(Gaoetal.,2015).

Acknowledgments

This project was funded under the LIFE+ project (11/NAT/IT/00135) FAGUS: ‘Forests of the Apennines: Good practicestoconjugateUseandSustainability’ http://www.fagus-life-project.eu/.Coordinating beneficiary: CilentoVallodi Diano and Alburni NationalPark. Associatedbeneficiaries: GranSasso andMontidellaLagaNationalPark;DepartmentofEnvironmental Biology,Sapienza,UniversityofRome;DepartmentforInnovation inBiological,Agro-foodandForestsystems,UniversityofTuscia. Wewouldliketothankalltheinstitutionsandassociationsthat supportedthisproject(inalphabeticalorder):ASBUCIntermesoli, ASBUC Pietracamela, Comunità Montana ‘Vallo di Diano’, FED-ERPARCHI, the Italian Ministry for the Environment Land and Sea, the municipalities of Corleto Monforte, Crognaleto, Ottati, PietracamelaandTeggiano,andtheStateForestryCorps.Wewould alsoliketothankallthepeopleinvolvedinthefieldsampling,the

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projectmanagerofFAGUSMaurizioGioiosa,MarcoMarchettifor hisscientiﬁcadviceandLenaD’Amicoforthelogisticsupport. AppendixA. Supplementarydata

Supplementarydataassociatedwiththisarticlecanbefound,in theonlineversion,athttp://dx.doi.org/10.1016/j.ecolind.2016.04. 012.ThesedataincludeGooglemapsofthemostimportantareas describedinthisarticle.

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