Environmental conditions affecting spiders in grasslands at the lower reach of the River Tisza in Hungary

2011·0.24 MB·

by  Róbert Gallé

©EntomologicaFennica.31May2011
Environmental conditions affecting spiders in grasslands
at the lower reach of the River Tisza in Hungary
RóbertGallé,NorbertVesztergom&TamásSomogyi
Gallé,R.,Vesztergom,N.&Somogyi,T.2011:Environmentalconditionsaffect-
ingspidersingrasslandsatthelowerreachoftheRiverTiszainHungary.—
Entomol.Fennica22:29–38.
Theaimsofthepresentstudyweretorevealthedifferencesbetweengrassland
types,andtoidentifythelocalandlandscapeparametersthatinfluencethespider
assemblagesatthereachoftheRiverTisza.Therarefiednumberofspiderspecies
was negatively correlated with the proportion of forests in a radius of 500 m
aroundeachsite.Anegativecorrelationwasfoundbetweenthenumberofgrass-
landspecialistspeciesandtheproportionoftheforests,butthenumberofforest
speciesincreasedsignificantlywiththeneighboringforestarea.Therelativearea
ofneighboringforests,thenumberofplantspeciesandregularfloodingplayed
majorrolesinshapingofthespeciescompositionofspiders.Theresultsofthe
presentstudyemphasizetheimportanceoftheeffectofhabitatlandscapeproper-
tiesonspiderassemblages.Thestructuraldiversityofthelandscapemayinflu-
encespeciesrichnessandcompositionofthehabitats.
R. Gallé, N. Vesztergom &T. Somogyi, Department of Ecology, University of
Szeged, Középfasor 52, H-6726 Szeged, Hungary; Corresponding author’s e-
mail:[email protected]
Received15February2010,accepted3December2010
1.Introduction habitats(Wardetal.2002,Lambeetsetal.2008,
2009).
In the Hungarian Great Plain, grasslands are The distribution of organisms across such a
threatenedbytheexpansionofagriculturalactiv- mosaiclandscapeisinfluencedbynumerousfac-
ity(Horváthetal.2009).Duringtheriverregula- torsandpresumablybythecomplexrelationships
tionsinthe19thcenturythehistoricalfloodplain amongthesefactors(Turner2005).
was divided by dikes into floodplain and non- Amongthehabitatfeatures,thecomposition
flooded,protectedareas.Theremnantsofthepro- and structure of vegetation (Ysnel & Canard
tectedgrasslandsaremainlyusedaspasturesor 2000,Heikkinen&MacMahon2004)influence
meadows. the species composition and diversity of the in-
These small patches are enclosed between vertebrate assemblages. Plant species richness
highly modified landscape elements, i.e. arable and the height of the vegetation is supposed to
fieldsandforestplantationsofmainlynon-native haveamajorinfluenceonthespiderassemblages,
treespecies.Thenaturaldisturbanceoftheregu- as higher plant species richness offers more di-
larfloodingeventsandtherelatedchangesinthe versehabitatstructureandmorepotentialsitesfor
vegetationstructureareexpectedtoaffectstruc- webbuilding(Jeanneretetal.2003a,Horváthet
turalandmicroclimaticparametersinfloodplain al.2009).
30 Galléetal. (cid:127) ENTOMOL.FENNICAVol.22
Onthelandscapescale,heterogeneity ofthe grasslandsaroundthestudysites,asthethe-
surroundinghabitatpatchesmayinfluencethedi- ory of island biogeography states that more
versityandthenumberofspeciesoftheassem- isolated habitats retain less habitat specialist
blagesatagivenpatch(Duelli1997).Although speciesthanlessisolatedones(e.g.Löveiet
numerousauthorshavedemonstratedthesignifi- al.2006).
canceofthespatialstructureofthelandscapeon (4)Accordingtotheabove-mentionedhypothe-
invertebrate assemblages (e.g. Diekötter 2008, sesweexpectedboththeproportionofforests
Ricketts2001),itisdifficulttogeneralizetheef- andgrasslandstoinfluencethespeciescom-
fect of the landscape heterogeneity, as various positionofspiderassemblages.
taxareactdifferentlytothehabitatandlandscape
features,sincespeciesecologyanddispersalabil-
ities are different for every organism (Burel & 2.Materialsandmethods
Baudry1995,Jeanneretetal.2003a).
Thepresentstudyaimedattestingtheeffect 2.1.Studysitesandsampling
of habitat parameters (soil humidity, regular
flooding, structure and cover of the vegetation) TwohabitatcomplexesofthelowerTisza-valley
andlandscape(proportionofgrasslands,forests were selected for sampling spider assemblages.
andarablefields)onthespiderassemblages,and The southern habitat complex (Vessz(cid:1)s) is situ-
torevealthedifferencesbetweenassemblagesof ated near Szeged (46°17’30”N; 20°14’20”E),
thefloodplainandonprotectedgrasslands.Spi- where the landscape mainly consists of arable
ders were chosen for the study as they are the fieldswithsmallpatchesofgrasslands,andoak
mostdiverseandabundantpredatoryinvertebrate andpoplarforestplantationsareembeddedinthe
groupofgrasslands(Wise1993). matrixofarablefields.TheDóchabitatcomplex
lies40kmnorthofSzeged(46°26’20”N;20°10’
Thefollowinghypothesesweretested: 40”E),inastructurallymorecomplexlandscape.
Higherproportionofsemi-naturalgrasslandsand
(1)In terms of the habitat features we expected forestsoccurhere.
thenumberofspeciestoincreasewithmore The spider assemblages were studied at six
structuredvegetation,asitiswell-knownthat grasslands(samplingsites)inthesouthernhabitat
vegetationheightanddensityisimportantfor complex and four in the northern habitat com-
spiders (e.g. Greenstone 1984). We did not plex,respectively.Ineachhabitatcomplex,hay-
expectthenumberofspeciestochangewith meadow, saline grassland, floodplain meadow,
regularfloodingeventasfloodplainhabitats degraded grassland, and at the southern habitat
do not necessarily harbor more species but complexapairofdike-sidemeadows(i.e.flood-
rather exhibitdifferentspeciescompositions plainandprotected)werestudied.
anddifferentdiversity patterns(Lambeetset Tosamplethefaunapitfalltrapswereapplied
al.2009). (diameter65mm,filledwithethyleneglycolas
(2)AccordingtoEntlingetal.(2007)andLam- preservative,Koivula2003,Schmidtetal.2006).
beetsetal.(2008,2009)wealsoexpectedthe Ateachsitethreelinesoftraps(samplingplots)
vegetationstructure,soilmoistureandregular were placed, each line consisted of five traps
flooding to alter the species composition of keepingadistanceof4mbetweenthem.Theav-
spiders. eragedistancebetweenthelineswas150m.Prior
(3)Asregardstheeffectofthelandscapecompo- tothedataanalysis,thedataofthefivetrapswere
sition,weexpectedthenumberofspeciesto pooled. We expected an underestimation of the
increasewithincreasingproportionofforests abundance of web-building species, as pitfall
aroundthestudysites,asaconsequenceofthe traps measure the activity-density of species at
occurrenceofforestspecialistandgeneralist the ground level, thus they capture the spiders
speciesinthegrasslands(Usheretal.1993). withanactivehunterlifestyleonthesoilsurface
Wealsoexpectedthenumberofspeciestoin- more efficiently (Topping & Sunderland 1992,
crease with the increasing proportion of Urák&Samu2008).However,pitfalltrapsoffer
ENTOMOL.FENNICAVol.22 (cid:127) Spidersofrivervalleygrasslands 31
a relatively good alternative for comparing the Toassessthesignificanceoftheireffect,the
activity-densityofepigaeicspiderfaunaofdiffer- explanatoryvariablessuggestedbytheURTme-
ent habitats (Scmidt et al. 2005, Öberg et al. thod were subjected to a linear mixed-effect
2007).Thetrapswerekeptopenforfour2-week model with nested random effects using the li-
samplingperiods(27May–13June,30June–15 brarynlmeinR(Pinheiroetal.2007).Theeffect
July, 16–30 Aug., 18 Sept.–01 Oct.) in 2007 to ofthedifferenthabitatcomplexesandsampling
coverthemainactivityperiodofthespiderspe- siteswereusedasrandomeffectsandtheexplan-
cies.Thedataofthefoursamplingperiodswere atory variables suggested by the regression tree
pooled. methodwereusedasfixedeffectsinthemixedef-
To characterize the structure of the vegeta- fectlinearmodel(Crawley2007).Thecollected
tion, the number of plant species and the total specieswerecategorizedaccordingtotheirhabi-
coverofthevegetationatthegroundlevel,at10 tatrequirements(Buchar&Ruzicka2002,Szita
and 40 cm above the ground, were measured etal.2006,Schmidt&Hanggi2007,Batáryetal.
within 1 × 1 meter quadrates near the traps, as 2008). The significant landscape scale parame-
structurallycomplexhabitatsmayprovidemore terswereincludedintwosubsequentlinearmod-
potentialsitesforwebbuilding,andbecausespi- elstoassesstheireffectsonthenumberofforest
dersarestronglyinfluencedbythehabitatstruc- andgrasslandspecialistspecies.
ture(Schwabetal.2002). Rényi’sdiversityorderingwasusedtocom-
To assess the features of the landscape, the parethediversityofthefloodplainandprotected
proportion ofland-use types was measured in a habitats (hypothesis 1). Diversity ordering pro-
radiusof500maroundeachsite,basedonaerial vides the diversity profiles of the assemblages.
photographs (i.e. grasslands, forests and arable Thesecurvesconsistofaseriesofdiversityindi-
fields),asseveralstudiessuggestthatlandscape ces,asthescaleparameterischanged,including
compositionatscalesof500mradiuscanberele- indicessensitivetobothrareandabundantspe-
vantforspiders(Cloughetal.2005,Schmidtet cies(Carranzaetal.2007).Anassemblageiscon-
al. 2005). The remaining landscape elements sideredtobemorediversethananotherifitspro-
(e.g.surfaceoftheriver)werenotenteredintothe file lies above and they do not intersect (Tóth-
analysisinordertodecreasethenumberoffac- mérész1995).Rsoftware(RDevelopmentCore
torswhichweretested. Team 2007) with the BiodiversityR Package
(Kindt2008)wasusedforthecalculations.
The influence of the measured explanatory
2.2.Dataanalysis
variableswastestedonspiderassemblages(hy-
Habitatstructureaffectsthetrappabilityofspider pothesis2and4)byusingthemultivariateregres-
individuals,whichmay resultinbiaseddatafor siontree(MRT)method.Thismethodisanexten-
studies comparing species richness of habitats sionofunivariateregressiontreeshavingmulti-
withdifferentstructures(Melburne1999).Dueto variateresponse(De’ath2002).MRTdoesnotas-
the different habitat properties of the sampling sumeparticularformofrelationshipbetweenspe-
plotsandthelargevariationinthenumberofindi- ciesabundancesandexplanatoryvariables.This
viduals recorded over the trapping period, rar- method can be used to identify interactions be-
efaction was used to standardise the number of tween explanatory variables (De’ath 2002,
species recorded within each of the sampling 2010).
plots(Hecketal.1975,Gotelli&Colwell2001). Thesizeofthetreewasselectedbasedonthe
Asregardshypothesis1and3,theunivariate minimum tree size that falls below 1 SE of the
regression tree method (URT) was used to gain minimum cross-validation estimate. The final
insightintothestructureofthedataandidentify treesizewasselectedbasedonthefrequentlyoc-
the interactions between the variables (Tree curring number of leaves from 100 individual
Package, Ripley 2009). The method performs a trees(Worketal.2004).
binaryrecursivepartitioningofthedataset.Italso The species that characterize each leaf and
offers the opportunity to identify the influential nodeoftheMRTwereidentifiedusingtheindica-
explanatoryvariables(Crawley2007). tor species index (IndVal) based on the relative
32 Galléetal. (cid:127) ENTOMOL.FENNICAVol.22
34,thusthespeciescompositiondifferedconsid-
erablybetweenthestudiedgrasslands.
3.1.Hypothesis1:Theinfluenceofhabitat
featuresontherarefiednumberofthe
species
According to the univariate regression tree me-
thodthetotalvegetationcoveristheonlyhabitat
parameterthathadapossibleinfluenceontherar-
efiednumberofspeciesincaseofhigherpropor-
tionofforests(Fig.1).However,thevegetation
cover had no significant effect on the rarefied
Fig.1.Univariateregressiontreefortherarefiedspe-
numberofthespeciesaccordingtotheresultsof
ciesrichness.Node1isbasedonForest(%),thepro-
thelinearmixed-effectmodel(t =–0.361;p=
portionofforestsaroundthesamplingplots;node2 17
0.722).
onVeg.cov.(%),thetotalvegetationcover;node3on
Arablefield(%),theproportionofthearablefield.The The diversity profiles of the spider assem-
differentlengthsofthelinesfollowingeachsplitare blages inhabiting the floodplain and protected
proportionaltothevarianceexplainedbythesplit.The habitatsaregiveninFig2.Thecurveforthepro-
numbersbeloweachleafshowthenumberofsamp- tected grasslands runs above that for the
lesfallingintothatleaf. floodplaingrasslandsandthetwocurvesdonot
intersect.Thus,theassemblagesoftheprotected
abundanceandrelativefrequencyofoccurrence grasslandsweremorediverseforthewholerange
(Dufrene&Legendre1997,De’ath2002). ofthescaleparameter.
3.2.Hypothesis2.Theinfluenceofhabitat
3.Results
featuresonthespeciescomposition
Atotal number of 3547 spider specimens were The cross validation of 100 MRT trees yielded
collected,representing95speciesin17families treesoftwo,fourandfiveleaves,11,46and40
(Appendix, downloadable from http://ojs.tsv.fi/ times, respectively, with three trees resulting in
index.php/entomolfennica/). The species rich- 6–8leaves.Thefour-leaftreeispresentedinFig
nessofgrasslandpatchesrangedbetween23and 3.TheMRT,indicatingtheinfluenceofthenum-
Fig.2.Theresultsof
Rényi’sdiverisityorder-
ing.Thediversitypro-
filesdonotintersect,
thustheassemblages
oftheprotectedgrass-
landsaremorediverse.
ENTOMOL.FENNICAVol.22 (cid:127) Spidersofrivervalleygrasslands 33
Fig.3.Multivariateregressiontreeforspiders.Bray-Curtisdissimilaritywasusedforsplitting.Thefinaltreesize
wasselectedbasedonthemostfrequentlyoccurringnumberofleavesfrom100individualtrees.Thenumbers
beloweachleafshowthenumberofsamplesfallingintothatleaf.Theabbreviatednamesofspecieswithsignifi-
cantindicatorvaluearegivenateachleaf,theindicatorvaluesaregiveninparenthesis(***p<0.001,**p<0.01,*
p<0.05).Abbreviations:Tare:Thanatusarenarius,Hrad:Hognaradiata,Mross:Micariarossica,Gluc:Gna-
phosalucifuga,Zseg:Zelotessegrex,Zlon:Z.longipes,Dcon:Diplostylaconcolor,Pala:Pardosaalacris,Zlat:
Z.latreillei,Osim:Ozyptilasimplex,Oapi:Oedothoraxapicatus,Aele:Antisteaelegans,Aleo:Arctosaleopar-
dus,Eden:Erigonedentipalpis,Plat:Piratalatitans,A.hum:Araeoncushumilis,Dlut:Drassylluslutetianus,
Pame:P.amentata,Pcri:P.cribrata,Pdeg:Pachygnathadegeeri,Ppro:Pardosaproxima,Tstr:T.striatus,
Zmun:Z.mundus.
berofplantspecies(node2,Fig.3),accountedfor Forthefourthleafweidentified14indicator
12.9%ofthetotalvarianceandtheregularflood- species.OutofthesespidersthegeneralistOedo-
ingevents(node3,Fig.3)accountedfor8.9%of thoraxapicatus(Blackwall,1850),Erigoneden-
thetotalvariance. tipalpis(Wider,1834)andPachygnathadegeeri
The IndVal analysis identified one indicator Sundevall, 1830 occur under the regularly dis-
speciesofthefirstleaf(ThanatusarenariusTho- turbed conditions of agricultural fields and 11
rell,1872).Thisspecieslivesinopen,dryhabi- species are associated with wet meadows and
tats. pondmargins(Buchar&Ruzicka2002,Schmidt
ForthesecondleaftheIndValanalysisidenti- &Hanggi2007).
fied6species.Thesespidersoccurinthenatural
alkali grasslands of the Great Hungarian Plain
(Szitaetal.2006,Batáryetal.2008). 3.3.Hypothesis3.Theeffectoflandscape
For third leaf the IndVal analysis identified scaleparametersontherarefiednumber
two forest specialist species (Pardosa alacris ofthespecies
(C.L.Koch,1833)andDiplostylaconcolor(Wi-
der, 1834)), and the generalist Zelotes latreillei According to the URT the two most influential
(Simon,1878)andOzyptilasimplex(O.P.-Cam- parametersweretheproportionofforestsandara-
bridge,1862)(Buchar&Ruzicka2002). blefields(Fig.1).Aspredicted,theproportionof
34 Galléetal. (cid:127) ENTOMOL.FENNICAVol.22
forests had a significant effect according to the waterregimeplayanimportantroleintheshap-
subsequent GLMM (t = –2.228, p = 0.039). ingofthediversityofspiderassemblagesatrive-
17
However, no significant relationship was found rinelandscapes.Numerousstudieshavedemon-
between the proportion of arable fields and the strated that spiders are particularly sensitive to
rarefiednumberofthespecies(t =–1.801,p= flooding. The spider diversity is not only influ-
17
0.089). The subsequent linear models revealed enced by the occurrence of flooding events but
the significant negative effect of forests on the alsobythedurationandfrequencyoftheseevents
number of grassland specialist species (t = – (Uetz1976,Paetzoldetal.2008).
19
2.166,p=0.043)andthemarginallysignificant
positiveeffectontheforestspecialistspecies(t
19
=2.024,p=0.057). 4.2.Thenumberofplantspecies
andtheregularfloodingeventsinfluenced
thespeciescompositionofspiders
3.4.Hypothesis4.Theinfluenceoflandscape
scaleparametersonthecomposition The vegetation and flooding events are con-
ofspecies straintsforspideroccurrence,indicatingtheim-
portanceofthequalityoflocalhabitats.Inlow-
TheMRTanalysisidentifiedonlyoneinfluential land floodplains, flooding dynamics determine
landscapescaleparameter.Theproportionoffo- thecompositionofthespeciesandthestructureof
restsinaradiusof500maroundeachsite(Fig.3, thevegetationwhichinturninfluencethecompo-
node1)accountedfor26.2%ofthetotalvariance. sitionofspiderfauna(Ballingeretal.2005).Asin
mosthabitattypes,vegetationplaysamajorrole
in determining the physical parameters of the
4.Discussion habitat,andtherefore,hasasignificantinfluence
onthedistributionsofinvertebratespecies(Bonte
4.1.Noinfluentialhabitatparameteronthe 2002, Tews et al. 2004). Gravesen (2000) and
rarefiednumberofthespecies,butthereis Lambeetsetal.(2006)alsosupportthehypothe-
ahigherdiversityattheprotectedgrasslands sis that a combination of flooding intensity and
vegetation structure is important factor for the
Although numerous studies have demonstrated species composition of spiders in wet grassland
the effect of plant species richness and habitat areas.
structureonthenumberofspeciesandthediver- Saboetal.(2005)reviewedtheliteratureon
sityofspiders(e.g.Jeanneretetal.2003b,Tewset thespeciesrichnessandassemblagecomposition
al. 2004), we found no significant relationship of flooded and non-flooded habitats. In accor-
betweenthevegetationalparametersandtherar- dance with the results of the present study they
efied number of the species. Gallé & Torma found that the species composition differs be-
(2009)andGalléetal.(2010)demonstratedthat tweentheregularlyfloodedandnon-floodedhab-
differenthabitattypesmayexhibitspiderassem- itats.Thiscanincreasetheregionalspeciesrich-
blageswithsimilarnumberofspeciesbutdiffer- ness.Severalstudieshaveconfirmedtheimpor-
ent species compositions. Thus, for a detailed tanceoffluvialdynamicsaffectingspiderassem-
study into the relationship between the spiders blagesbyalteringthehabitatconditions(Bonnet
andthehabitatparameterstheexaminationofthe al.2002,Paetzoldetal.2008).
speciesabundancedataisrequiredinordertoas- AtregularlyfloodedhabitatsLambeetsetal.
sesstheimpactoftheseparametersonthespider (2009)foundthatthedispersalabilityofspecies
assemblages without the loss of information playsaprominentroleinstructuringcarabidand
whensummarizingthedataontheassemblagesin spiderassemblages,thuslife-historytraitsaffect
asinglevaluesuchasspeciesrichness(Jeanneret species composition of spiders. Rothenbücher
etal.2003b,c). andSchaefer(2006)studiedtheimpactofflood-
In accordance with Bell et al. (1999) and ing on invertebrate assemblages. They distin-
Bonnetal.(2002),ourresultsalsoindicatethat guishedtwotypesofadaptationininvertebrates:
ENTOMOL.FENNICAVol.22 (cid:127) Spidersofrivervalleygrasslands 35
submersion tolerance and regular migration be- thustheisolationofthehabitats.Higherpropor-
fore and after the flooding. Most spiders over- tionofforestsmayserveasdispersalbarriersfor
winter at juvenile or adult stages (Pekár 1999). grasslandspecialistspecies.
These stages of terrestrial arthropods are less
flood-resistantthanaretheireggs,thusthey are
not able to tolerate long winter submersions. 4.4.Thefaunaofthesurroundingforests
RothenbücherandSchaefer(2006)demonstrated influencethespeciescompositionofspiders
that the floodplain spider fauna consists of spe-
ciesimmigratingwithrecedingwaterlevels.The AccordingtotheMRTlandscapecompositionis
abundance of cursorial spiders depends on the importantindeterminingthespeciescomposition
proximity and connectivity of natural habitats, ingrasslands.Similarlytoourresults,numerous
possiblyforseasonalmigrationtowardshiberna- studieshaveshownthatlandscapevariablesare
tion sites (Bonte et al. 2003, Lambeets et al. importantdeterminantsofspeciescompositionof
2008),whilegoodballoonersareabletocolonize spiders(e.g.Öbergetal.2007,Batáryetal.2008,
formgreaterdistances(Bonteetal.2002). Schmidtetal.2008).TheIndValanalysesidenti-
Although the IndVal analysis identified 14 fied two forest specialist species (P. alacris and
species associated with floodplain grasslands, D. concolor) at non-flooded grasslands with a
manyspeciesofthefloodplainhabitatsareoppor- high proportion of surrounding forests, and ac-
tunistic species from the surrounding non- cordingtothelinearmodelsthenumberofforest
floodedhabitatsthatcancolonizeaftertheflood- specialist species increased and the number of
ingevents(Adis&Junk2002). grassland specialist species decreased with the
proportion of surrounding forests. Although
Schmidtetal.(2005)foundnosignificantcorre-
4.3.Theproportionofforests lationbetweenthepercentageofforestsandspi-
hadasignificantnegativeeffect derassemblages,Kajak(2007)demonstratedthat
ontherarefiednumberofthespecies forests influence the species composition of ce-
real fields by enhancing the number and abun-
In accordance with the results of the present danceofforestspecialistspecies.Shealsofound
study,Cloughetal.(2005)reportedthattherar- significanteffectofforestageandnaturalness.
efiednumberofspeciesisinfluencedbytheland- Landscape scale forestry operations may af-
scapeparameters.Öbergetal.(2007)andDrape- fectthediversityandspeciescompositionofthe
laetal.(2008)foundthatahigherproportionof surrounding grassland habitats by altering the
forestsinthesurroundinglandscapewereassoci- proportionorthehabitatqualityofforests.This
atedwithahighernumberofobservedspiderspe- emphasizestheimportanceofthelandscape-level
cies,asforestsmayserveassourcehabitatforspi- approachtonatureconservation.
ders.Ourresultsalsosupportthishypothesisas
we found increasing number of forest specialist
species with the proportion of surrounding fo- 5.Conclusions
rests.Speciesarrivingingrasslandsfromforests
arelikelytoaddnewspeciestothespiderassem- Inthepresentstudywehaveassessedthecompo-
blage, as forests and open habitats are home to sitionaldifferencesofspiderassemblagesofvari-
contrasting spider assemblages (Entling et al. ousgrasslandtypesandtheeffectsofhabitatand
2007,Drapelaetal.2008). landscapepropertiesontherarefiedspeciesrich-
Theeffectofforestsonthegrasslandspecial- nessandcompositionofspiders.Lowlandflood-
istspeciesispossiblyduetothefactthatsmaller, plainhabitatsareofhighconservationalvalue,as
moreisolatedfragmentsretainfewerhabitatspe- theirassociatedarthropodfaunaconsistsofspe-
cies than larger less isolated ones (e.g. Lövei cialistandrarespecies(Rothenbücher&Schae-
2006). Several papers emphasize the effects of fer2004).Evensmallfragmentsplayanimpor-
surrounding habitats on the dispersal of species tantroleinmaintainingtheregionaldiversityof
(Bonteetal.2004,Thorbek&Topping2005)and spiders,astheyarenotentirelyisolated,because
36 Galléetal. (cid:127) ENTOMOL.FENNICAVol.22
spiders are especially successful in dispersal fects of aerial dispersal, habitat specialisation, and
(Horváthetal.2009). landscapestructureonspiderdistributionacrossfrag-
mentedgreydunes.—Ecography27:343–349.
Atotalnumberof95specieswerecollected,
Buchar,J.&Ruzicka,V.2002:CatalogueofSpidersofthe
and the species richness of grassland patches
Czech Republic. — Peres Publishers: Praha, Czech
rangedbetween23and34,thusthespeciescom- Republic.pp:1–349.
positiondifferedconsiderablybetweenthestud- Burel,F.&Baudry,J.1995:Speciesbiodiversityinchang-
iedgrasslands.Ourresultssuggestthatbesidethe ingagriculturelandscapes:AcasestudyinthePays
d’Auge,France.—AgricultureEcosystemsandEnvi-
conservationoffloodplaingrasslands,themain-
ronment55:193–200.
tenanceofdiversityofgrasslandhabitatsisalso
Carranza,M.L.,Acosta,A.&Ricotta,C.2007:Analyzing
essentialforpreservingtheregionalspeciespool landscapediversityintime:TheuseofRènyi’sgenera-
ofinvertebrates. lized entropy function. — Ecological Indicators 7:
505–510.
Clough,Y.,Kruess,A.&Tscharntke,T.2005:Spiderdi-
Acknowledgements. We would like to thank László
versityincerealfields:comparinglocal,landscapeand
KörmöcziandMártaZalatnaifortheirhelpwiththebotan-
regionalscales.—JournalofBiogeography32:2007–
icalsurveys,GáborLaskayforthelinguisticcorrectionof
2014.
the manuscript. We would also acknowledge Katja
Crawley,M.J.2007:TheRBook.—JohnWiley:New
Matveinen-HujuandananonymousRefereeforthecon-
Yorkpp:627–685.
siderableeffortsinsuggestingimprovementsinthemanu-
De’ath,G.2002:Multivariateregressiontrees:anewtech-
script. The present study was supported by NKFP
nique for modeling species-environment relations-
6/013/2005grantandtheRegionalUniversityKnowledge
hips.—Ecology83:1105–1117.
Centre for Environmental and Nanotechnology, Univer-
De’ath, G. 2010: mvpart: Multivariate partitioning. R
sityofSzeged.
package version 1.3-1. — [www document] URL
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