Effects of abiotic environmental factors and land use on the diversity of carrion-visiting silphid beetles

24 Pages·2017·1.8 MB·English

RESEARCHARTICLE
Effects of abiotic environmental factors and
land use on the diversity of carrion-visiting
silphid beetles (Coleoptera: Silphidae): A large
scale carrion study
ChristianvonHoermann1,2*,DennisJauch1,CarolinKubotsch1,KirstenReichel-Jung1,
SandraSteiger1,ManfredAyasse1
a1111111111 1 InstituteofEvolutionaryEcologyandConservationGenomics,UniversityofUlm,Ulm,Germany,
2 DepartmentofConservationandResearch,BavarianForestNationalPark,Grafenau,Germany
a1111111111
a1111111111
*[email protected]
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Abstract
Anthropogeniclandusecausesglobaldeclinesinbiodiversity.Despitetheknowledgethat
animalcarrionisthemostnutrient-richformofdeadorganicmatter,studiesonlandscape
OPENACCESS
andlocalscalesdeterminingwhetherandthemeansbywhichlanduseintensityinfluences
Citation:vonHoermannC,JauchD,KubotschC,
Reichel-JungK,SteigerS,AyasseM(2018)Effects thediversityofthecarrion-associatedinsectfaunaaregloballyscarce.Weinvestigatedthe
ofabioticenvironmentalfactorsandlanduseon effectsoflanduseintensityandabioticandbioticenvironmentalfactorsontheabundance,
thediversityofcarrion-visitingsilphidbeetles
speciesrichness,anddiversityoftheimportantecosystem-service-providingsilphidbeetle
(Coleoptera:Silphidae):Alargescalecarrionstudy.
taxon(carrionbeetles)inthreeregionsofGermany.In61foreststandsdistributedover
PLoSONE13(5):e0196839.https://doi.org/
10.1371/journal.pone.0196839 threegeographicallydistinctregionsinCentralEurope,wetrappedsilphidbeetleson
exposedpigletcadaversduringlatesummer.Inallthreeregions,higherambienttempera-
Editor:PauloDeMarcoJu´nior,Universidade
FederaldeGoias,BRAZIL turesandhigherfinesandcontentswereassociatedwiththeabundanceofthesilphid
beetletaxa.Thecarrioncommunitysilphiddiversitywasnegativelyaffectedbyanincrease
Received:July10,2017
inmeanambienttemperatureinallthreeregions.Althoughmanagementintensityinforests
Accepted:April20,2018
didnotaffecttheoverallabundanceofSilphidae,theabundanceofNicrophorushumator
Published:May30,2018
decreasedsignificantlywithhigherforestmanagementintensityacrossallthreeregions.
Copyright:©2018vonHoermannetal.Thisisan Unmanagedandage-classforestsshowedahigherabundanceofN.humatorcompared
openaccessarticledistributedunderthetermsof
withextensivelymanagedforeststands.ThesefindingsindicatethatN.humatorhaspoten-
theCreativeCommonsAttributionLicense,which
tialasanindicatorspeciesforanthropogenicdisturbancesinforests.Overall,thedirect
permitsunrestricteduse,distribution,and
reproductioninanymedium,providedtheoriginal responsesofthesilphidbeetlecommunitytodiversesoilcharacteristicsunderlinesoilasan
authorandsourcearecredited. importantfactordeterminingtheabundanceanddiversityofnecrophagouscarrionbeetles
DataAvailabilityStatement:Allrelevantdataare inCentralEurope.Toprotectthesevaluableecosystem-serviceproviders,forest-manage-
withinthepaperanditsSupportingInformation ment-inducedsoilmodificationsneedtobepaidcloseattention.
files.ThedatasetfileisavailablefromtheDryad
database(DOI:doi:10.5061/dryad.r5c64).
Funding:Thisworkhasbeen(partly)fundedbythe
GermanResearchFoundation(DFG)Priority
Program1374"Infrastructure-Biodiversity-
Exploratories"(AY12/9-1,STE1874/4-1toDr.
ChristianvonHoermann,http://www.biodiversity-
exploratories.de).Thefundershadnoroleinstudy
PLOSONE|https://doi.org/10.1371/journal.pone.0196839 May30,2018 1/24
Effectoflanduseonsilphidbeetlediversity
design,datacollectionandanalysis,decisionto Introduction
publish,orpreparationofthemanuscript.
Increasinglanduseintensityandlandusechangearemajordriversofbiodiversityloss,partic-
Competinginterests:Theauthorshavedeclared
ularlyinforestecosystems[1–3].Approximately82%ofCentralEuropeanforestsarehuman-
thatnocompetinginterestsexist.
dominatedandthereforearehighlydisturbed[4].Inmanyforests,intensifiedage-classfor-
estryhasreducedthequalityofthehabitatandalsoitsstructuralheterogeneity[5].The
homogenizationofsuchanthropogenicallyinfluencedecosystemsonthelandscapescale,
wherebyspeciesassemblagesbecomeincreasinglydominatedbyasmallnumberofwide-
spreadspecies,isoneofthemainthreatstobiodiversity[6,7].Commendably,inrecentyears,
modernforestmanagementstrategieshaveavoidedlarge-scaleclear-fellinginage-classforests
orhaveestablishedincreasedamountsofdeadwoodinforeststoincreasespeciesrichness[8].
Nevertheless,theaboveindicatesthatlandusetypeandintensityaffectsthediversityofinsects,
includingthatofforest-dwellingcarrioninsectcommunities;thisinturnmighthaveanega-
tiveimpactontheimportantecosystemservices,suchascarcassremovalrateandnutrient
cycling,carriedoutbytheseinsects[9,10].
Animalcarrionisthemostnutrient-richformofdeadorganicmatteranddecomposesata
fastrate[11–13].Thesetwokeyqualitiesofhighnutrientconcentrationandacceleratedtem-
poraldynamicsmakecarrionahighlyimportantcomponentofthedetrituspool[14].Carrion
hasasignificantimpactonterrestrialbiodiversityandecosystempropertiesthroughitsinflu-
enceonbelow-groundmicrobialcommunities,soilnutrients,arthropodsandonscavenging
vertebrates[15].Consequently,animalcarrionisapreconditionfortheevolutionandmainte-
nanceofdetritivoreanddecomposerdiversity,andinturn,thediversityofdetritivoresand
decomposersimpactsnutrientcyclingratesandultimatelyinfluencesproducerandconsumer
diversity[12].
Interrestrialecosystems,thedecompositionanddispersionofcarrionnutrientsisheavily
dependentonabioticfactors,suchasthetemperature,humidity,soiltype,andpH-valuesof
soil(e.g.,seereferencesin[16]),andontheavailabilityofinsectdetritivoresanddecomposing
microorganisms[17].Consequently,forthecontinuousfunctioningofecosystemprocesses
andservices,thebiodiversityofthecarcass-associatedinsectandmicrobialfaunamustbepre-
served,andtherefore,theirinfluencingfactorsneedtobeidentified.
Forfunctionalarthropodgroupssuchaspredatorsandwooddecomposers,severalstudies
havefoundclearindicationsthattheyarenegativelyaffectedbyforestmanagement(e.g.,
[18,19]).Beetles(Insecta:Coleoptera)occupydiverseniches,andseveralspeciesarespecificto
theirgivensubstrates(e.g.,[20,21]).Consideringtheseaspects,beetlesinvolvedintheprocess
ofdecompositionwilloftenformasignificantpartofthebiodiversityoftheircarrionmicro-
habitat[21–23].Inparticular,carrionbeetles(Coleoptera:Silphidae)arefrequentlyassociated
withvertebratecadaversandprovideawiderangeofecosystemservices[24,25]bypromoting
thebreakdownandrecyclingoforganicmatterintoterrestrialecosystems[26–29].Mostsil-
phidspeciesarenecrophagousbutcanalsopreyoncarrion-inhabitingnecrophagousflylar-
vae,othersmallnecrophilouscarrionbeetles,andflyeggs[26,27,30,31].ThetaxonSilphidaeis
partofthetaxonStaphylinoideaandisdividedintotwogroups:theNicrophorinae(11species
innorthwesternEurope;allfromthegenusNicrophorus,calledburyingbeetles)andtheSil-
phinae(17speciesinnorthwesternEurope)[24,26,30,32,33,34].Accordingtotheirname,
buryingbeetles(Nicrophorus)burysmallvertebratecadaversinthesoilasfoodfortheirlarvae
[35].Theelaboratebiparentalcarecarriedoutbyoneconspecificpairofbeetles,whichhave
securedafreshlydeadcadaversuitableforreproduction,hasbeenknownforalongtimein
thetaxonNicrophorus[36].Buryingbeetlesalsocolonizelargevertebratecadaversinhigh
numbers[37,38].Dozensofburyingbeetleindividuals,particularlyduringtheperiodwhen
theirovariesarematuring,convergeonlargecadaversthataretoolargeforburialanduse
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Effectoflanduseonsilphidbeetlediversity
themasfeedingsites(>300g,[24,36]).IncontrasttotheNicrophorinae,femaleSilphinaespe-
ciesaresemelparousandlaytheireggsinoronthesoilaroundlargevertebratecadavers,and
noparentalcareoftheirlarvaeisprovided[24,30,39].Silphidspromotetherecyclingofnutri-
entsandtheirnecrophagousfeedingactivitiesmayalsodestroysomefociofinfectionof
humanpathogenicbacteria[40].
Dynamicchangesinthecompositionoforganisms(especiallyarthropods)thatvisitcarrion
duringitsvariousdecompositionstageshasbeenwidelydocumented[41–45].However,asno
large-scalecarrionstudyisavailablethatexplicitlyexaminestheinteractingeffectoflanduse
intensificationandbioticandabioticenvironmentalfactorsonoverallcarrionecology[17],
keyknowledgegapsstillexistconcerningtheeffectoflanduseoncarcass-inhabitinginsect
diversity,speciesrichnessandabundance,andconsequently,theircriticalecosystemservices.
Toaddressthisareaofknowledge,wehaveconductedalarge-scalestudyinwhichwehave
exposed75pigletcadaversacrossdifferentlymanagedforeststandsinCentralEuropeand
monitoredcadaver-visitingsilphidbeetlesduringthewholecourseofdecomposition.We
havehypothesisedthatforestmanagementintensityandotherbioticandabioticenvironmen-
talfactorswillaffectsilphidbeetleabundance,speciesrichness,anddiversity.Forestmanage-
mentintensityhasbeenquantifiedbyusingtherecentlydevelopedsilviculturalmanagement
intensityindicator(SMI),whichcombinesthreemaincharacteristicsofagivenstand:stand
age,treespecies,andaboveground,living,anddeadwoodenbiomass[46].Ourconclusions
canbegeneralizedbecauseourstudyencompassesthreeregionsdifferingingeology,topogra-
phy,andclimate.
Methodsandmaterials
Ethicsstatement
Allnecessarypermitswereobtainedforthedescribedfieldstudies.Noanimalswerekilledfor
thisstudy.Allcadaversofexclusivelystillbornpigletswereobtainedunderveterinarysupervi-
sion(specialpermitforanimalby-products(EG)No.1069/2009)fromalocalpigfarmer
(WinfriedWalter,Go¨gglingen,Germany).Forfieldsamplingofarthropods,anexemption
existedconcerning§67BNatSchGandspeciesprotectionlegislationaccordingto§45
BNatSchG.
Studysitesandpigletcadaverexposure
WeconductedourstudyinthreedifferentgeographicalregionsinGermanyasspecifiedby
theframeworkoftheBiodiversityExploratories(http://www.biodiversity-exploratories.de):
theSchwa¨bischeAlb(Baden-Wu¨rttemberg,48˚20´60.0´´Nto48˚32´3.7´´N;9˚12´13.0´´
Eto9˚34´48.9´´E)intheSouth-West,theHainich-Du¨nregion(Thuringia,50˚56´14.5´´N
to51˚22´43.4´´N;10˚10´24.0´´Eto10˚46´45.0´´E)inCentralGermany,andtheBio-
spherereserveSchorfheide-Chorin(Brandenburg,52˚47´24.8´´Nto53˚13´26.0´´N;13˚
23´27´´Eto14˚8´52.7´´E)intheNorth-East.Amoredetaileddescriptionofthethree
regionsissuppliedinsupplementalmethods.Inall,75forestexperimentalplots(EPs,25in
eachofthethreeregions)ofonehectareeachwereselectedfollowingastratifiedrandom
designwithstratarepresentingdiverseforestmanagementintensitiesandseveralotherabiotic
factorssuchassoiltypeandsoildepth(FigA1inS2File,[47]).These25plotschosenper
regionrepresenttheexistingrangeofdifferentlanduseintensities[47].
FromAugust4thuntilSeptember4th2014,wesimultaneouslyexposed75stillbornpiglet
cadavers(Susscrofadomestica,1.44kgaverageweight)on25forestEPsperregion(onepiglet
perplot,FigA1inS2File).EPsweresufficientlyspacedataminimumdistanceof200m
betweentheouteredgesoftwoEPs(BiodiversityExploratoriescriteria,after[47])toavoid
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Effectoflanduseonsilphidbeetlediversity
crossinteractionsamongindividualcadavers.Weusedpigletsasacarrionsubstratebecauseof
theirwell-studiedandassuredsuccessionofcarrioninsects,andbecausetheyareawell-estab-
lishedmodelsysteminforensicentomology(e.g.,[45,48,49,50]).Furthermore,theyarepresent
nationwideasthewild-typeSusscrofa(wildboar)intheforesthabitatsofGermany.Aftera
defrostingperiodof24hours,freshlydeadpigletexposurestartedonAugust4th(n=38)and
5th(n=37)andlasteduntilSeptember3th(n=38)and4th(n=37),respectively.Allcadavers
ofexclusivelystillbornpigletswereobtainedunderveterinarysupervision(specialpermitfor
animalby-products(EG)No.1069/2009)fromalocalfarmerinGo¨gglingen(Baden-Wu¨rttem-
berg,Germany)andwerefrozen(-20˚C)upuntil24hrsbeforethestartofexposure.Sincethe
studyaimedtofocusoninsectcommunities,allpigletswereexposedinblackwirecages(63
cmx48cmx54cm,MHHandelGmbH,Munich,Germany)toexcludefeedingandremoval
bylargerscavengerssuchasfoxes,wildboars,orraccoons.Wemounteddataloggers(Ther-
mochroniButton,Whitewater,WI,USA)insideofeachwirecagetorecordthetemperature
ofthecarrionmicrohabitatevery30minutesduringthewholefieldworkperiod.Wirecages
containingcadaversandcontrols(pitfalltrapswithoutcarcassesandwirecages)wereinstalled
atadistanceof100mtoeachotherwithindifferentlymanagedforeststands(FigA1inS2
File).Controlswereneededtocapturetheprevailingandnotnecessarilycarrion-associated
insectfaunaofthehabitat(FigA1inS2File).
Installationofpitfalltrapsandbeetlesampling
Ontheperipheryofeachcadaver,weinstalledtwopitfalltrapsfortrappingofcadaver-associ-
atedinsects.Onepitfalltrapwasinstalledadjacenttotheheadofthepiglet,withtheotherone
beingadjacenttoitsanus.Thisallowedustosituatebothtrapsinsideeachwirecagebytaking
intoconsiderationtwoimportantsettlementareas(headandanus)forcadaver-inhabiting
insects[51].Pitfalltrapswerecomposedoftwoground-levelsmoothiecupsstackedinside
eachother(half-literPLAcups;diameter:95mm,height:151.2mm;HuhtamakiFoodservice
GmbH,Alf/Mosel,Germany).Theinnercupwasfilledwithanodorlesssoapysolution(one
dropofdetergent,KlarEcoSensitive,AlmaWin,Winterbach,Germany)toreducesurfaceten-
sion.Forprotectionagainstrainfall,eachsingletrapwasequippedwitharaincover(con-
structedatUlmUniversity,Ulm,Germany).Forcontrols,weappliedthesameprocedureas
describedabove,withtheonlydifferencesbeingnocadaverandnowirecageinthesecases.
Forreasonsofcomparability,thedistanceofthetwocontroltrapsatonesinglecapturesite
correspondedtothedistancebetweenthepigletheadandanus.Atotalof7trap-emptying
eventsperexposedcadaverandcontrolduringthewholedecompositionperiodwerecon-
ducted:at2,4,6,9,16,23,and30daysafterday0ofexposure.Thesesamplingintervalscov-
eredallthedistinctstagesofdecompositionbasedonlarge-scalesuccessiondatainthe
literature[45,49].At48hrsbeforethetrap-emptyingevents,weopenedthelidcoveredthepit-
falltraps(PLAdome-coversforsmoothiecups;diameter:95mm;HuhtamakiFoodservice
GmbH,Alf/Mosel,Germany)toguaranteeaconstantsampleperiodforeachtrappingevent.
Therefore,eachinsectsamplingeventlasted48hrs.Forlatermorphologicalassessmentand
classificationofdecaystagesinthelaboratory[20],alloftheconductedtrap-emptyingevents
wereaccompaniedbyphoto-documentationofthedecompositionstagesofallexposedpiglet
cadavers.
Allcollectedinsectindividualsweretransferredinto70%ethanol(VWRInternational
GmbH,Darmstadt,Germany)forlatersortingtolargertaxonomicgroupsandsubsequent
speciesidentificationinthelaboratory.Allsilphidindividualswereidentifiedtospecieslevel
[52]andstoredatUlmUniversity(InstituteofEvolutionaryEcologyandConservationGeno-
mics,DepartmentofBiology).Foranysingletrap-emptyingevent,wepooledalldataforthe2
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Effectoflanduseonsilphidbeetlediversity
cupsoneithersideofeachpigletoneachplot.Thesamewastrueforthecontrols.Becauseof
lossesofpigletcadavers(onecadaverintheSchwa¨bischeAlbandthreecadaversinHainich-
Du¨n)andtheprohibitionoftherightofentryonparticularsamplingdaystoatotalof10
plots,thesamplingcampaignresultedin294sampleunitsfortheSchwa¨bischeAlb,224sample
unitsforHainich-Du¨n,and336sampleunitsforSchorfheide-Chorin.Allthese854sample
unitsfromoverall61plotsformedthebasisforlaterstatisticalanalysis.
Environmentalvariables
Weconsideredatotalof21bioticandabioticenvironmentalvariablesinouranalyses.Allvari-
ablesandtheirrespectivevalueswereknownfromseveralinventorycampaignscarriedout
withintheBiodiversityExploratories(basicdataincludingsoiltype,soilcomposition,bulk
density(fortheupper10cmofthemineralsoil,units:g/cm3),climate,verticalstructure,and
management).Exemplarily,soiltypeandsoilcompositionwereconsideredasimportantabi-
oticenvironmentalparametersinouranalyses,becausesoilcharacteristicsareknownasan
importantfactordeterminingthelocalabundanceofcarrionbeetles[25,36,53].
Statisticalanalyses
AllanalyseswereconductedinRversion3.3.1([54],2016).Kruskal-Wallisranksumtests
withposthocpairwisecomparisonsbyusingTukeytestswereappliedtotesttheeffectsof
thedecompositionstageandtraptype(cadaverversuscontrol)onoverallsilphidbeetle
abundance.
Forthequantificationoftherelativeimportanceofenvironmentalvariablesontotalsilphid
beetleabundance,speciesrichness,anddiversity,weusedtherandomforestapproach(ran-
domForestfunctionimplementedintheMASSpackage)toidentifythoseenvironmentalvari-
ableswithanincreaseofmorethan50%ofthemeansquareerror—inthecaseofomission—
togetherwiththemarkedhighestIncNodePurity-valuesoutofall20variablesconsideredin
thisstudy(FiguresA1—A7inS1File,after[55,56]and[5]).Therandomforestapproachisa
recursivepartitioningandclassificationtreemethod[57]basedonregressiontreesbyusing
randominputs[58,59].
Further,weusedgeneralizedlinearmixedmodels(GLMMs)totestforanyeffectsofthe
environmentalvariablesonthetotalabundance,speciesrichness,anddiversity(Shannon’s
diversityandSimpson’sdominance)ofthesilphidbeetletaxonacrossdifferentlymanaged
foreststands.Suchdifferenceswereinvestigatedacrossallsilphidbeetletaxaand,inthecase
oftotalabundance,alsoseparatelyforthesinglesilphidspeciesNicrophorusvespilloides,
N.investigator, andN.humator.Negativebinomialerrordistributionswereappliedinall
thosemodelsinwhichoverdispersionwaspresentwhenpreviouslyfittedwithaPoisson
errordistribution(after[60]).Ourdataareexpectedtobetemporallydependentwithineach
plot,astheyarecollectedacrossexperimentalplotsduringsevensubsequentvisits.Therefore,
wefittedourregressionmodelswitharandomeffectattheplotlevel.Plot-specificrandom
effectsshouldcapturemostofthelatentheterogeneity(andover-dispersion)ofthedata.We
furtherinvestigatedforestmanagementintensitybyusingaprecalculatedindex(SMI)that
canbedescribedbytwocomponents,riskofstandlossandstanddensity,whichtheoretically
areindependentofoneanother[46].Theriskcomponentdefinesthecombinedeffectof
standageandtreespeciesselectiononSMI[46].Theothercomponent,standdensity,quan-
tifiestheeffectofremovalsandregenerationmethodusingactualbiomassrelatedtoarefer-
ence[46].SchallandAmmer(2013)commentedthatSMIattheoperationallevelismostly
relatedtofellings(tending,thinningandharvestoperations),butinthecaseoftreesremain-
inginthestandduetonaturallosses(e.g.windthrow),thediscrepancybetweenfellingsand
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Effectoflanduseonsilphidbeetlediversity
removalsbecomesevenmoreevident.Theystatedthatremovals(usedforSMIdescriptionin
theriskcomponent)aremoreindicativeofsilviculturalmanagementintensitythantreesthat
arelostduetosilviculturalornaturalreasons[46].SchallandAmmer(2013)consequently
proposedtomeasureremovalsbythedeviancebetweenmaximumbiomass(species,ageand
sitespecific)andactualbiomassoflivinganddeadtrees.Weincludedallthreesinglecompo-
nents‘maintreespecies’,‘standdensity’and‘standage’asfixedfactorsinourGLMMstotest
foreffectsontherespectiveresponsevariables(abundance,speciesrichness,Shannon’s
diversityandSimpson’sdominance).ThecombinedSMI-index,togetherwiththefixedeffect
attheregionlevel(variableexploratory)wasconsideredinseparatenegativebinomial-,
gamma-orGaussian-GLMs(thetwolastfamilieswereusedtotesttheeffectsofforestman-
agementintensityandregiononsilphiddiversity—afterexaminingdiversity-indicesdistri-
butionaswellastheassumptionofnormality,FiguresA2andA3inS2File)inorderto
eliminateeffectsoflineardependencyattributabletothecombinationofthreevariablesin
oneforestmanagementintensityindexaswellastoeliminateperfectmulticollinearityofthe
exploratoryvariable.
Apriori,wefittedthoseenvironmentalvariableswithanincreaseofmorethan50%of
themeansquareerror—inthecaseofomission—togetherwiththemarkedhighestIncNo-
dePurity-values(derivedfromarandomforest)innegativebinomial-,gamma-orGaussian-
GLMMsinasequenceaccordingtotheirimportance(Tables1–3,after[5]).Thiswasfol-
lowedbymodeldredging.Thedredgefunction(implementedintheMuMInpackage)was
appliedformodelsimplification[61]basedonthehighestAkaikeweight.Modeldredging
retainsmodelcombinationswiththemostlikelycombinationsofpredictorvariables
[62,63].
Finally,wecalculatedShannon’sdiversityas‘–SP (cid:3)ln(P)’whereP istheproportionof
i i i
individualsbelongingtospeciesi,andSimpson’sdominanceas‘1/SP2’(formulaefrom[64];
i
[65]).Morrisetal.(2014)suggestthattheinclusionofmultiplediversitymeasures,spread
alongHill’scontinuum[66],providesresearcherswithamorecompleteunderstandingofthe
waythatshiftsinabundantandrarespeciesdriveinteractions.Followingtheirrecommenda-
tion,weincludednotonlyspeciesrichness(sensitivetorarespecies,[67]),butalso,asafore-
mentioned,Shannon’sdiversity(equallysensitivetoabundantandrarespecies;[67])and
Simpson’sdominance(sensitivetoabundantspecies,morecommonthanSimpson’sdiversity;
[68]).Therandomforestapproachandmodeldredgingforthequantificationoftherelative
importanceofenvironmentalvariablesonsilphidbeetlediversitywerecalculatedasdescribed
indetailabove(forplotsofvariabledistributionandfordetectingdeparturesfromnormality,
seeFiguresA2andA3inS2File).
Results
Duringthewholefieldworkperiod,wetrapped8446silphidbeetleindividualsof10specieson
theperipheryof61exposedpigletcadavers:Nicrophorusvespilloides(n=6599),N.investigator
(n=1280),N.humator(n=314),Oiceoptomathoracica(n=158),N.vespillo(n=54),N.inter-
ruptus(n=36),Necrodeslittoralis(n=2),Thanatophilussinuatus(n=1),N.vestigator(n=1),
andPhosphugaatrata(n=1)(Fig1).Intherespectivecontrols,wetrappedonlyoneindividual
ofthespeciesN.vespilloides.Thenumberofindividualstrappedperplotrangedfrom13(one
singleplotinHainich-Du¨n)to409individuals(onesingleplotinSchorfheide-Chorin).
Cadaver-baitedtrapscapturedsignificantlymoresilphidbeetlescomparedwithunbaitedcon-
troltrapsacrossallthreeregions(Kruskal-Wallistest,Chi2=103.01,df=1,P<0.001).Species
numberperplotrangedfromonecapturedsilphidspeciesinHainich-Du¨ntosevencaptured
speciesinSchorfheide-Chorin.
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Effectoflanduseonsilphidbeetlediversity
Table1. Statisticalcharacteristicsofmodelscomparingthetotalabundanceofsilphidsindiverseforesttypes.
Silphidae
Randomeffectvariance(group=plot):0.118,StdDev:0.343
Negativebinomialdispersionparameter:19.963(Stderr:11.898)
F Estimatedslope StdErrorofestimatedslope P
Abundance
Finesand 3.384 -0.002 <0.001 0.072
Meanambienttemperature 10.659 0.300 0.092 0.002
Randomeffectvariance(group=plot):0.092,StdDev:0.303
Negativebinomialdispersionparameter:4.036(Stderr:1.851)
F Estimatedslope StdErrorofestimatedslope P
Abundance
SMI(SilviculturalManagementIntensityIndex) 0.111 0.190 0.569 0.740
N.vespilloides
Randomeffectvariance(group=plot):0.199,StdDev:0.446
Negativebinomialdispersionparameter:9.890(Stderr:10.243)
F Estimatedslope StdErrorofestimatedslope P
Abundance
Finesand 4.050 -0.002 0.001 0.050
Meanambienttemperature 17.199 0.410 0.099 <0.001
Randomeffectvariance(group=plot):0.454,StdDev:0.674
Negativebinomialdispersionparameter:1.001(Stderr:0.002)
F Estimatedslope StdErrorofestimatedslope P
Abundance
SMI(SilviculturalManagementIntensityIndex) 0.148 0.249 0.646 0.702
N.investigator
Randomeffectvariance(group=plot):<0.001,StdDev:0.002
Negativebinomialdispersionparameter:7.266(Stderr:1.541)
F Estimatedslope StdErrorofestimatedslope P
Abundance
Bulkdensity 4.214 0.756 0.368 0.046
Meanambienttemperature 42.181 -0.569 0.088 <0.001
Soiltype 13.006 <0.001
Cambisol:-0.165 0.376
Leptosol:-0.250 0.428
Luvisol:-1.980 0.475
Stagnosol:-2.131 0.644
Randomeffectvariance(group=plot):0.046,StdDev:0.214
Negativebinomialdispersionparameter:7.079(Stderr:2.319)
F Estimatedslope StdErrorofestimatedslope P
Abundance
Exploratory 39.518 <0.001
HEW:-1.990 0.296
SEW:-1.083 0.207
SMI(SilviculturalManagementIntensityIndex) 0.627 0.420 0.531 0.432
N.humator
Randomeffectvariance(group=plot):<0.001,StdDev:0.001
Negativebinomialdispersionparameter:3.638(Stderr:1.582)
F Estimatedslope StdErrorofestimatedslope P
(Continued)
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Effectoflanduseonsilphidbeetlediversity
Table1. (Continued)
Silphidae
Abundance
Managementsystem 4.583 0.007
extensivelymanaged:1.649 1.079
selectionsystem:0.447 0.771
unmanaged:1.271 0.382
Meanambienttemperature 14.731 0.457 0.119 <0.001
Soiltype 2.032 0.107
Cambisol:0.012 0.487
Leptosol:-1.041 0.740
Luvisol:0.176 0.569
Stagnosol:-1.307 0.740
Randomeffectvariance(group=plot):<0.001,StdDev:0.005
Negativebinomialdispersionparameter:0.698(Stderr:0.168)
F Estimatedslope StdErrorofestimatedslope P
Abundance
SMI(SilviculturalManagementIntensityIndex) 7.953 -3.396 1.204 0.007
Resultsofnegativebinomial-GLMMs(plotasrandomeffect)comparingthetotalabundanceofallsilphidbeetletaxaandofthesinglesilphidspeciesNicrophorus
vespilloides,N.investigator,andN.humatorindiverseforesttypesinthreeregions(AEW=AlbExperimentalplotWald(inEnglish:forest),HEW=Hainich
ExperimentalplotWald(inEnglish:forest),SEW=SchorfheideExperimentalplotWald(inEnglish:forest)).Boldtextindicatessignificanteffects(α=0.05).Important
environmentalvariables(FiguresA1—A4inS1File)werefittedfirst,accordingtotheirimportance.Formodeldredging,modelsimplificationbasedonAkaike
informationcriterionAIC(dredgefunctionimplementedintheMuMInpackage)wasperformed.
https://doi.org/10.1371/journal.pone.0196839.t001
Effectsofenvironmentalcharacteristicsonoverallsilphidbeetle
abundance
Twoabioticenvironmentalvariablesinfluencedtheabundanceofmembersofallcaptured
silphidbeetletaxa(Table1).Fromoveralltwopredictorvariablesinthesimplifiedmodel,
witharandomeffectvarianceof0.18(negativebinomial-GLMM,deviance=10.39,
P=0.006),‘meanambienttemperature’significantlyaffectedtheabundanceofSilphidae.
Thesamewastendentiallytrueforthevariable‘finesand’(Table1).Acrossallthreeregions,
totalsilphidbeetleabundanceincreasedwithhighermeanambienttemperatures(Fig2a).
Overallbeetleabundancetendedtoincreasewithanincreasingfine-sandcontent(Fig2b).
Forestmanagementintensityhadnosignificanteffectonoverallsilphidbeetleabundance
(Table1).
EffectsofenvironmentalcharacteristicsontheabundanceofN.vespilloides
TwoabioticenvironmentalvariablesinfluencedtheabundanceofN.vespilloidesindividuals
(Table1).Fromoveralltwopredictorvariablesinthesimplifiedmodel,witharandomeffect
varianceof0.20(negativebinomial-GLMM,deviance=15.25,P<0.001),‘meanambienttem-
perature’significantlyinfluencedtheabundanceofN.vespilloidesindividuals(Table1).Across
allthreeregions,thetotalabundanceofN.vespilloidesincreasedwithhigherambienttempera-
tures(Fig3a).Thesamewastendentiallytrueforhigherfine-sandcontents(Fig3b,Table1).
Silviculturalmanagementintensity(expressedasanindex)didnotaffectN.vespilloidesabun-
dance(Table1).
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Effectoflanduseonsilphidbeetlediversity
Table2. Resultsofnegativebinomial-GLMMscomparingspeciesrichnessofthetaxonSilphidaeinthedifferentforesttypesinthreeregions.
Silphidae
Randomeffectvariance(group=plot):<0.001,StdDev:0.002
Negativebinomialdispersionparameter:1.001(Stderr:<0.001)
Deviance Estimatedslope StdErrorofestimatedslope P
Speciesrichness
Modelnotsignificant 1.773 0.183
Clay >-0.001 <0.001
Randomeffectvariance(group=plot):<0.001,StdDev:0.002
Negativebinomialdispersionparameter:1.001(Stderr:<0.001)
F Estimatedslope StdErrorofestimatedslope P
Speciesrichness
SMI(SilviculturalManagementIntensityIndex) 0.008 0.043 0.473 0.928
Plotwasusedasarandomeffect.Importantenvironmentalvariables(FigA5inS1File)werefittedfirst,accordingtotheirimportance.Formodeldredging,model
simplificationbasedonAkaikeinformationcriterionAIC(dredgefunctionimplementedintheMuMInpackage)wasperformed.
https://doi.org/10.1371/journal.pone.0196839.t002
EffectsofenvironmentalcharacteristicsontheabundanceofN.investigator
TotalabundanceofN.investigatorwashigherintheSchwa¨bischeAlbwhencomparedwith
Hainich-Du¨nandSchorfheide-Chorin,respectively(negativebinomial-GLMM,deviance=
49.19,P<0.001,Fig2c,Table1(variableExploratory)).From,intotal,threepredictorvari-
ablesinthesimplifiedmodel,witharandomeffectvarianceoflessthan0.001(negativebino-
mial-GLMM,deviance=56.44,P<0.001),thetwoenvironmentalvariables‘meanambient
temperature’and‘soiltype’significantlyinfluencedtheabundanceofN.investigatorindividu-
als(Table1).Bulkdensitytendentiallyinfluencedbeetleabundance(Table1).Acrossallthree
regions,thetotalabundanceofN.investigatordecreasedwithhighermeanambienttempera-
tures(FigA4ainS2File).Concerningsoiltype,theabundanceofN.investigator wassignifi-
cantlyhigheronLeptosolsoilscomparedwithLuvisolandStagnosolsoiltypes,respectively
(FigA4binS2File).Furthermore,totalabundanceofN.investigator tendedtodecreasewith
higherbulkdensities(Fig2d).Silviculturalmanagementintensity(expressedasanindex)had
noeffectonN.investigatorabundance(Table1).
EffectsofenvironmentalcharacteristicsontheabundanceofN.humator
From,intotal,threepredictorvariablesinthesimplifiedmodel,witharandomeffectvariance
oflessthan0.001(negativebinomial-GLMM,deviance=55.73,P<0.001),‘managementsys-
tem’and‘meanambienttemperature’significantlyinfluencedtheabundanceofN.humator
individuals(Table1).Acrossallthreeregions,thetotalabundanceofN.humatorwashigher
inunmanagedforestscomparedwiththosethatwereextensivelymanaged.Thelatterforest
typealsoshowedatendentiallylowerabundanceofN.humatorwhencomparedwithage-class
forests(Fig3c).Inaddition,tendentiallymoreN.humatorindividualswerecapturedin
unmanagedforestscomparedwithage-classforests(Fig3c).Acrossallthreeregions,thetotal
abundanceofN.humatorincreasedwithhighermeanambienttemperatures(FigA5inS2
File).Silviculturalmanagementintensity(expressedasanindex)hadaneffectonN.humator
abundance(negativebinomial-GLMM,deviance=5.04,P=0.025).Acrossallthreeregions,
highersilviculturalmanagementintensityresultedinadecreaseofabundanceofN.humator
(Fig3d,Table1).
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Effectoflanduseonsilphidbeetlediversity
Table3. ResultsofmodelscomparingShannon’sdiversityandSimpson’sdominanceofsilphidsindiverseforesttypes.
Silphidae
Gaussian-GLMM
Randomeffectvariance(group=plot):<0.001,StdDev:0.001
Residualvariance:0.211(Stderr:0.021)
F Estimatedslope StdErrorofestimatedslope P
Shannon’s diversity
Meanambienttemperature 7.840 -0.126 0.045 0.008
Soiltype 20.541 <0.001
Cambisol:-0.519 0.155
Leptosol:-0.526 0.187
Luvisol:-0.907 0.204
Stagnosol:-0.807 0.248
Gaussian-GLMM
Randomeffectvariance(group=plot):<0.001,StdDev:0.001
Residualvariance:0.229(Stderr:0.022)
F Estimatedslope StdErrorofestimatedslope P
Shannon’s diversity
Exploratory 7.606 0.001
HEW:-0.439 0.139
SEW:-0.218 0.108
SMI(SilviculturalManagementIntensityIndex) 1.284 -0.368 0.325 0.263
gamma-GLMM
Randomeffectvariance(group=plot):0.027,StdDev:0.163
Gammashapeparameter:403.43(Stderr:0.043)
F Estimatedslope StdErrorofestimatedslope P
Simpson’s dominance
Finesilt 4.037 -0.002 0.001 0.051
Meanambienttemperature 23.634 -0.184 0.038 <0.001
Soiltype 15.703 <0.001
Cambisol:-0.360 0.106
Leptosol:-0.365 0.126
Luvisol:-0.658 0.122
Stagnosol:-0.519 0.139
gamma-GLMM
Randomeffectvariance(group=plot):0.036,StdDev:0.191
Gammashapeparameter:403.43(Stderr:0.035)
F Estimatedslope StdErrorofestimatedslope P
Simpson’s dominance
Exploratory 22.869 <0.001
HEW:-0.360 0.069
SEW:-0.278 0.065
SMI(SilviculturalManagementIntensityIndex) 2.300 -0.291 0.192 0.136
Statisticalcharacteristicsareshownforallthreeregions.ForGaussian-andgamma-GLMMs,thelink=“log”.Boldtextindicatessignificanteffects(α=0.05).Important
environmentalvariables(FiguresA6andA7inS1File)werefittedfirst,accordingtotheirimportance.Formodeldredging,modelsimplificationbasedonAkaike
informationcriterionAIC(dredgefunctionimplementedintheMuMInpackage)wasperformed.
https://doi.org/10.1371/journal.pone.0196839.t003
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