Journal of Applied Ecology

2007

44

, 340–351

© 2007 The Authors. Journal compilation © 2007 British Ecological Society

Blackwell Publishing Ltd

How landscape structure, land-use intensity and habitat diversity affect components of total arthropod diversity in agricultural landscapes

FREDERIK HENDRICKX,*† JEAN-PIERRE MAELFAIT,*† WALTER VAN WINGERDEN,‡ OLIVER SCHWEIGER,§ MARJAN SPEELMANS,† STÉPHANIE AVIRON,¶ ISABEL AUGENSTEIN,** REGULA BILLETER,†† DEBRA BAILEY,¶ ROMAN BUKACEK,‡‡ FRANÇOISE BUREL,§§ TIM DIEKÖTTER,†† JOLANDA DIRKSEN,‡ FELIX HERZOG,¶ JAAN LIIRA,¶¶ MARTINA ROUBALOVA,*** VIKI VANDOMME* and ROB BUGTER‡

*

Terrestrial Ecology Unit (TEREC), Department of Biology, Ghent University, K. L. Ledeganckstraat 35, 9000 Gent, Belgium;

†

Institute of Nature and Forest Research, Kliniekstraat 25, 1070 Brussels, Belgium;

‡

Alterra Green World Research, Landscape Centre, PO Box 47, 6700 AA Wageningen, the Netherlands;

§

UFZ, Centre for Environmental Research Leipzig-Halle, Department of Community Ecology, Theodor-Lieser-Str. 4, D-06210 Halle, Germany;

¶

Agroscope FAL Reckenholz, Swiss Federal Research Station for Agroecology and Agriculture, Reckenholzstrasse 191, CH-8046 Zurich, Switzerland;

**

UFZ, Centre for Environmental Research Leipzig-Halle, Department of Applied Landscape Ecology, Permoserstr. 15, D-04318 Leipzig, Germany;

††

ETH Swiss Federal Institute of Technology, Geobotanical Institute, Zurichbergstr. 38, CH-80444 Zurich, Switzerland;

‡‡

Nature Conservation Authority, Department of Informatics, Nuselská 39, CZ-14000, Praha 4, Czech Republic;

§§

UMR Ecobio, Université de Rennes 1, Avenue du Général Leclerc, 35042, Rennes, Cedex, France;

¶¶

Institute of Botany and Ecology, University of Tartu, Lai 40, Tartu, EE51005, Estonia; and

***

Institute of Forest Ecosystem Research, 254 01 Jílové u Prahy 1544, Czech Republic

Summary

1.

Agricultural intensification poses a serious threat to biodiversity as a consequence ofincreased land-use intensity, decreased landscape heterogeneity and reduced habitatdiversity. Although there is interest in the preservation of total species richness of anagricultural landscape (

γ

diversity), the effects of intensification have been assessedprimarily by species richness at a local scale (

α

diversity). This ignores species richnessbetween local communities (

β

diversity), which is an important component of totalspecies richness.

2.

In this study, measures of land-use intensity, landscape structure and habitat diversitywere related to

γ

,

α

and

β

diversity of wild bees (Apoidea), carabid beetles (Carabidae),hoverflies (Syrphidae), true bugs (Heteroptera) and spiders (Araneae) within 16 localcommunities in 24 temperate European agricultural landscapes.

3.

The total landscape species richness of all groups was most strongly affected by increasedproximity of semi-natural habitat patches. Bees also decreased in landscapes with a highintensity of farmland management, demonstrating additive effects of both factors.

4.

Separating total species diversity into components, the decrease in total speciesrichness could be attributed primarily to a decrease in species diversity between localcommunities. Species richness of the local communities of all investigated groupsdecreased with increasing land-use intensity and, in the case of spiders, decreasingproximity of the semi-natural habitat patches.

5.

The effect of increased habitat diversity appeared to be of secondary importance tototal species richness but caused a shift in the relative contribution of

α

and

β

diversitytowards the latter.

Correspondence: Frederik Hendrickx, Terrestrial Ecology Unit (TEREC), Department of Biology, Ghent University, K.L.Ledeganckstraat 35, 9000 Gent, Belgium (fax +31 9264 87 94; e-mail frederik.hendrickx@ugent.be).

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6.

Synthesis and applications

. This study demonstrates that the effects of agriculturalchange operate at a landscape level and that examining species diversity at a local levelfails to explain the total species richness of an agricultural landscape. The coincidenceof patterns of

β

diversity with those of

γ

diversity emphasizes that such information is ofcrucial importance for the implementation and evaluation of restoration programmesaiming to restore sustainable countryside diversity. As local extinction processesin highly fragmented landscapes shape biodiversity, priority should be given to theconservation of diverse agricultural landscape remnants in Europe.

Key-words

: agro-ecosystems, biodiversity, conservation, diversity partitioning,fragmentation, insects, landscape ecology

Journal of Applied Ecology

(2007)

44

, 340–351doi: 10.1111/j.1365-2664.2006.01270.x

Introduction

Agricultural landscapes cover the vast majority ofnon-urbanized areas in Europe. During the long historyof agriculture, numerous species have adapted to thiswidespread form of land use. The persistence of struc-turally diverse agricultural landscapes is hence aprerequisite for the conservation of a significant part ofEurope’s biodiversity (Bignal 1998; Krebs

et al

. 1999).However, land dedicated to food production has changeddramatically during the post-Second World War period.In parallel with an increased input of pesticides andfertilizers, as well as increased livestock densities, analmost irreversible change of the spatial structuringof the agricultural landscape has taken place (Krebs

et al

. 1999). The originally diverse, highly structuredlandscapes have been converted into much more uniformareas consisting almost solely of intensively usedagricultural units (Stoate

et al

. 1991; Robinson &Sutherland 2002), which has coincided with a reductionof species diversity, as has been demonstrated in particularfor birds (Siriwardena

et al

. 1998; Krebs

et al

. 1999; Benton,Vickery & Wilson 2003; Heikkinen

et al

. 2004).Previous studies have demonstrated that increased

management intensity of the agricultural fields is one ofthe main causes of the decline of local species richness(Bengtsson, Ahnström & Weibull 2005; Dauber

et al

.2005). It was predicted that local species diversity wouldbe enhanced under organic farming management butthis has not been widely observed, probably because ofthe confounding effects of the surrounding landscape(Weibull, Bengtsson & Nohlgren 2000; Kleijn

et al

. 2001).This demonstrates that ecological processes actingon spatial scales larger than the local environmentmay additionally impact local species diversity andoften have an interactive affect with land-use intensity(Tscharntke

et al

. 2005). Such landscape effects can bemanifested at two non-exclusive levels, landscape andhabitat heterogeneity (Weibull, Östman & Granqvist2003; Tews

et al

. 2004), as well as the amount of semi-natural habitat (Bergman

et al

. 2004; Clough

et al

.2005; Schmidt

et al

. 2005). In a previous study, local

environmental factors proved to be subordinate toenvironmental factors at the landscape scale in explain-ing the total variation in local species composition(Schweiger

et al

. 2005).These observations emphasize that the preserva-

tion of diverse agricultural landscapes should focus onspecies enhancement of entire agricultural areas ratherthan just on diversity of local communities. The decreasein total species diversity of an agricultural landscapecan be seen with the species diversity of the localcommunity, i.e. alpha diversity (

α

), and the diversitybetween local communities, i.e. beta diversity (

β

).Both components contribute to gamma diversity (

γ

)(Whittaker 1972; Lande 1996; Veech

et al

. 2002), whichin this context is the total diversity of an agriculturallandscape. Until now, changes in the components oflandscape species diversity in relation to agricultural orlandscape features remain largely unexplored, althoughsuch an approach can yield additional insight into how(environmental) factors affect species diversity (Loreau2000; Wagner, Wildi & Ewald 2000; Veech

et al

. 2002).Agricultural landscapes can be viewed as a mosaic of

habitat islands sustaining high levels of biodiversityembedded in a matrix of more intensively used agricul-tural land (Duelli 1997; Wagner, Wildi & Ewald 2000;Fournier & Loreau 2001). The size as well as spatialconfiguration of these semi-natural habitat patchescan be important determinants for sustaining a (meta)population of less ubiquitous species (Hanski

et al

.1995; Hanski 1998). Consequently, when suitablehabitat patches become simultaneously reduced in sizeand more distant from each other, local extinction ratesas a result of stochastic intrinsic and extrinsic effectsare not compensated for by recolonization if the dispersalcapacities of the involved species are low (Thomas 2000;Fahrig 2003; Colas, Thomas & Hanski 2004; Parvinen2004). This can lead to a strong impoverishment ofthe local diversity. Despite the convincing theoreticaland empirical framework concerning the expectedloss of single species in response to habitat loss, studiesrelating the local community diversity to the amountof suitable habitat still remain scant (but see Robinson

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et al

. 1992; Burkey 1995; Bergman

et al

. 2004;Summerville & Crist 2004). Also, information on theextent to which similar or dissimilar species becomeeliminated from the habitat patches or, alternatively,invade from the intensively used agricultural matrix isscarce. However, as only a small set of species is adaptedto the high disturbance levels of agricultural fields(Maelfait & De Keer 1990; Samu & Szinetar 2002),uniform landscapes as well as intensive farmingsystems can lead to a strong homogenization of thelocal communities, resulting in a decrease in diversitybetween local communities.

When investigating biodiversity responses, multiplespecies group studies are most suitable for gaininginsights into the effects of intensification of agriculture.The diverse nature of arthropods allows (i) investiga-tion of the responses of species covering a wide rangeof ecological functions and (ii) identification of theecological characteristics of the organisms mostsensitive to environmental change (Duelli 1997; Duelli,Obrist & Schmatz 1999). Indeed, in their reviewconcerning the effects of post-war changes in arablefarming on biodiversity in Britain, Robinson &Sutherland (2002) concluded that data for many taxaare too scarce at present to permit a detailed assessmentof the factors involved. This is particularly true ifthe aim is to separate the effects of increased land-useintensity, altered landscape structure and decreasedhabitat diversity (but see Schweiger

et al

. 2005). Althoughthese effects are often associated with each other inpractice, separating them is of great importance fordesigning guidelines to restore a sustainable country-side (Sutherland 2002; Tscharntke

et al

. 2005), as is thecase in agri-environment schemes. Recent evaluationsof these schemes reveal that the results are ratherequivocal (Kleijn

et al

. 2001; Kleijn & Sutherland 2003),which might be partly because of the confoundingeffects of large-scale landscape structure (Sutherland2002; Kleijn & Sutherland 2003; Bergman

et al

. 2004;Bengtsson, Ahnström & Weibull 2005; Tscharntke

et al

.2005) but additionally because diversity has beenprimarily explored at the local scale.

Assessing how the different diversity componentsof landscape species richness react to the major factorsrelated to agricultural change should therefore provideindispensable information for identifying the appro-priate scale for the implementation of agri-environmentschemes (Kareiva & Wennergren 1995). In this study,we addressed whether (i) the total species richness isaffected by increased land-use intensity, homogenizedlandscape structure and decreased habitat diversityand (ii) this is caused either by a decrease in localspecies richness (

α

diversity) and/or an additionaldecrease in species diversity between local com-munities (

β

diversity). These diversity componentswere estimated for five different groups of arthropodscovering different ecological niches and assessed for16 local communities in 24 agricultural landscapes oftemperate Europe.

Materials and methods

The landscape test sites (LTS) were spread over seventemperate European countries: Belgium (four), CzechRepublic (two), Estonia (four), France (three), Germany(four), the Netherlands (four) and Switzerland (three).Each LTS measured 16 km

2

and was divided into 1-km

2

grid cells wherein one trap set was located. As we wantedto sample the local community of the more naturalhabitat patch as well as the agricultural field, trap setswere located at the border of a randomly chosensemi-natural habitat patch and an agricultural field. Apatch was considered semi-natural if it was unmanagedor managed to the extent that its natural productionlevels were not purposely increased. This strategyensured that the species composition of the sampleswas not influenced by the distance between the trapset and the agricultural field, which would complicatestandardization of the sampling procedure as habitatpatches strongly differed in size. However, the geographicalstandardization of our sampling scheme did not allowfor sampling the same habitat type in each LTS or withineach 1-km

2

grid cell.A trap set consisted of two pitfall traps (diameter

10 cm; half-filled with formalin solution) and twocombined flight traps that were separated between25 and 50 m from each other. Flight traps consisted oftwo vertical orthogonal crossed plastic window glassesabove a yellow pan trap (Duelli 1997).

Although the spatial scale of the study did not allowfor year-round sampling, the study was conducted over7 weeks in summer–autumn 2001 and 5 weeks in spring2002. Traps were emptied weekly and only the mostabundant samples were taken into consideration (4 and3 weeks in summer–autumn and spring, respectively).Full bloom of

Taraxacum officinalis

Wiggers was usedas an indicator to standardize the period of sampling ineach country and minimize differences in species com-position as a result of different phenological propertiesof the organisms and climatic conditions between thecountries (Duelli 1997; Duelli, Obrist & Schmatz 1999).

Five taxonomic groups, i.e. wild bees (Apoidea), truebugs (Heteroptera), carabid beetles (Carabidae),hoverflies (Syrphidae) and spiders (Araneae), weresorted, and adult specimens were identified to specieslevel. For bees, bugs and hoverflies, only specimens fromthe combined flight traps were considered, and forcarabids and spiders only specimens from pitfall trapswere taken into consideration.

-

A large set of characteristics in each LTS was assessedand condensed into one measure of land-use intensity,four measures of landscape structure and two measuresof habitat diversity (Table 1). An estimate of land-use

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intensity was obtained by interviewing at least 10individual farmers per LTS, although only two to fourinterviews were performed where the area of managedland per farm was extremely large. Questionnairesgathered information on (i) fertilization application ongrassland and arable crops, (ii) pesticide use (herbicides,insecticides, fungicides and retardants) and (iii) livestockdensities. These indicators of agricultural land usecan be considered independent of landscape properties.Information regarding these three main indicatorswas condensed into one single measurement of overallland-use intensity per LTS, referred to as the LUI (land-use intensity index). Summary results of the ques-tionnaires and details about the calculation of the LUIcan be found in Herzog

et al

. (2006).Measures of landscape structure were obtained from

digitized habitat maps derived from aerial photographsand based on the amount and configuration of naturaland semi-natural elements in the agricultural landscape.Field observations were used to update the photographs,discriminate between the major types of land use (annualcrops, grazing) and define the main types of semi-naturalelements (field boundaries, woods, rough grasslands,moorland, etc.).

The total percentage of the landscape covered by semi-natural habitat patches (PPERC), the average patchsize (PSIZE) and the density of semi-natural patches(PDENS) were calculated for each LTS. To account forspatial configuration of the habitat patches, we alsocalculated the mean proximity index (PROXM), whichis distance weighted and area based because it sums theratios of patch area to distance for all habitat patchesthat fall within some specified distance (boundary ofthe LTS) to the focal patch (Gustafson & Parker 1992).Hence a high proximity index refers to a landscape withlarge patches situated close to each other.

Habitat diversity, i.e. the range of habitat typeswithin an LTS, was based on the (i) number of differenthabitats present within the landscape, wherein habitatswere categorized according to the European NatureInformation System (NEUNIS) habitat classification(http://mrw.wallonie.be/dgrne/sibw/EUNIS/home.html,

accessed 30 October 2006) and (ii) mean Euclidian dis-tance in habitat composition between the trap sets withinan LTS (HDIV). The latter was assessed by estimatingthe percentage coverage of the different EUNIS habitattypes in a circle with radius of 50 m around the trap sets.

The hierarchical sampling design enabled us to decom-pose the total biological diversity within an LTS (

γ

diversity) into

α

diversity (i.e. diversity within onetrap set) and

β

diversity (i.e. diversity between trap setswithin an LTS).

Despite the standardized sampling protocol, varia-tion in the numbers of trapped arthropods was highand might therefore have influenced species richnessestimates substantially (Gotelli & Colwell 2001; Magurran2004). Indeed, a strong and highly significant correlationbetween the number of captured species and number ofcaptured individuals was observed for each taxonomicgroup (

n

= 23, 0·76 <

r

< 0·98,

P

< 0·0001). As thenumber of captured individuals can be influencedby activity patterns (for example as a result of weatherconditions), we used abundance-based methods thatestimate species richness independent of sample size(Brose & Martinez 2004).

Rarefaction curves allowed for comparison of speciesnumber independently of number of individuals captured(Gotelli & Colwell 2001) and enabled estimation of

γ

diversity and separation into

α

and

β

diversity(Olszewski 2004). Also, the number of species for alocal sample size was estimated by means of a sample-based rarefaction curve and used as an estimate ofaverage

α

diversity within an LTS. Gamma diversitywas calculated by estimating the number of species fora regional, i.e. landscape, sample size by means of rarefac-tion curves in which individuals were randomized amongtrap sets within an LTS. Two measures of

β

diversitywere calculated as (i) the number of species attributedto differences between local communities, which wasobtained by taking the difference between

α

and

γ

diversity, and (ii) the relative contribution of

β

diversity

Table 1. Summary of explanatory variables and their abbreviation

Land-use intensityLUI Index of land-use intensity of the agricultural fields based on amount of fertilizer application, livestock densities

and use of pesticides (for details see Herzog et al. 2006)

Landscape structure of natural and semi-natural elementsPPERC Percentage of the landscape covered with semi-natural habitat patchesPPERC Percentage of the landscape covered with semi-natural habitat patchesPPROX Mean proximity index, wherein proximity combines the size of the focal patch with the distance to other patches

(for details see Gustafson & Parker 1992)PSIZE Average size of the semi-natural habitat patchesPDENS Patch density

Habitat diversity of natural and semi-natural habitat patchesHDIV Measure of habitat diversity based on the mean Euclidian distance between the habitat composition around the

trap sets within a landscapeNEUNIS Number of European Nature Information System (EUNIS) habitat categories present within the landscape

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to

γ

diversity. Rarefaction curves were calculated withthe software program EstimateS Vs. 6 (Colwell 2004).

Diversity metrics were calculated for a sample sizethat was equal to the nearest round number to the leastabundant sample for each taxonomical group. How-ever, sample size of one Czech LTS fell far below thoseof the other LTS and was therefore excluded foranalysis. The average number of individuals per LTS(landscape scale)/trap set (local scale), respectively,per taxonomic group was

n

= 963/61 for Apoidea,

n

=2236/140 for Araneae,

n

= 2814/175 for Carabidae,

n

=785/51 for Heteroptera and

n

= 401/26 for Syrphidae.

Estimates of the diversity components were relatedto the environmental variables presented in Table 1 bymeans of general linear mixed models. Preceding thesestatistical analyses, we explored the correlation structureamong the independent variables in detail by means ofcorrelation graphs, simple linear correlation coefficientsand principal component analysis (PCA).

A first set of models was based on fitting eachindependent variable individually to the diversityestimates. We explicitly did not rely on the obtainedPCA axes as they obscure additive and interactiveeffects among variables that are partially correlated. Aswe also wanted to test whether a heterogeneous responsewas present between the different taxa, taxonomic groupas well as its interaction with the environmental variablewas included as a fixed effect. Different interceptsand slopes were estimated for each taxonomic groupseparately (Neter

et al

. 1996). To investigate whichfixed effect variable was most important in explainingthe observed variation in each diversity component,Akaike’s information criteria (AIC) was calculated foreach model (based on maximum likelihood). Thismeasure of model fit is based on the

−

2 log likelihoodof the model but controls for the number of freeparameters (cf. Verbeke & Molenberghs 2000).

Additional factors were then included in the modelto test for additive effects and/or interactive effectsbetween the land-use intensity, landscape structure andhabitat diversity variables. We used a stepwise selectionprocedure in which we started with the model that gavethe lowest value of AIC in the first step. Thereafter,

all remaining variables, including their interaction withtaxonomic group, were tested using forward stepwiseregression and were retained when significant and theirAIC value computed. The model with the lowest AICvalue best explained the observed variation in diversityamong the investigated variables.

To correct for possible country effects on thediversity measures (i.e. climatic factors, differences inaverage habitat type) that were not of main interest inthis study, country as well as its interaction withtaxonomical group was included as a random effect ineach model (Verbeke & Molenberghs 2000).

As absolute values of environmental variables differedstrongly, they were standardized to have a mean of zeroand a standard deviation of one, which eased comparisonof their effects based on regression coefficients.

Results

Correlations among the variables are presented in Table 2.On average, correlations were low, although somesignificant correlations were present after sequentialBonferroni correction. Land-use intensity was negativelycorrelated with the proximity index, and the percentageof the landscape covered with semi-natural patches(PPERC) was positively correlated with habitat diversityand mean proximity index.

Based on these LTS characteristics, a PCA wasconducted to inspect further the correlation structureamong the independent variables. The first and secondprincipal component axis explained, respectively, 43·5%and 25·4% of the total variability in LTS characteristics,respectively (Fig. 1). Values of the eigenvectors revealedthat LTS with high values along the first principal com-ponent axis were characterized by a large amount ofsemi-natural habitat patches, high habitat diversity andlow land-use intensity (Table 2). Although LTS of eachcountry were situated in each other’s neighbourhoodaccording to their PCA scores, overlap along the firstaxis was large and they did not appear as separateclusters. Along the second axis, which mainly comprisedthe effect patch density, each country’s LTS appearedmore or less grouped.

Table 2. Correlations (rP) among explanatory variables measured on the 23 landscape test sites (LTS).*Significant correlation atP < 0·05. The last two columns show correlations of the variables with principal component axes 1 and 2

LUI PPERC PPROX PSIZE PDENS HDIV NEUNIS PC1 PC2

LUI 1 −0·41 0·31PPERC −0·47* 1 0·50 0·28PPROX −0·64* 0·62* 1 0·49 −0·23PSIZE −0·47* 0·32 0·47* 1 0·34 −0·30PDENS 0·24 0·32 −0·32 −0·26 1 0·01 0·67HDIV −0·28 0·80* 0·58 0·21 0·32 1 0·45 0·30NEUNIS 0·03 0·36 0·08 0·12 0·27 0·21 1 0·17 0·39

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Relating each environmental variable separately to theestimates of

γ diversity revealed that land-use intensityon the one hand, and percentage of the landscapecovered with semi-natural patches, proximity of thesepatches and both measures of habitat diversity onthe other hand, significantly affected total landscapespecies richness in a negative and positive direction,respectively (Table 3). Except for percentage of thelandscape covered with patches, responses were nothomogeneous across the taxonomic groups: wild beesand, to a lesser extent, spiders, appeared to be moststrongly affected. Among these variables, proximityindex best explained the observed variation in totalspecies richness of the agricultural landscape.

A model with land-use intensity, its interaction withtaxonomic group and proximity of the habitat patchesbest explained variation in γ diversity. The interactionbetween taxonomic group and land-use intensity wasmainly caused by the strong decrease in γ diversity of beeswith increasing farming intensity of the agriculturalfields (Table 4 and Fig. 2). This model provided statisticalevidence that, at least for bees, land-use intensity andlandscape features imposed additive effects on γ diversity.

Single variable regression analyses revealed that α diver-sity increased significantly with decreasing levels ofland-use intensity and increasing levels of averageproximity of semi-natural habitats across taxonomicgroups. However, the effect size differed among them,and spiders appeared to exhibit the strongest increasein α diversity when the semi-natural habitat patches ofthe landscape were characterized by a higher proximity(Table 3). The proximity index best explained the observedvariation in α diversity among the seven variablesinvestigated. Effects of habitat diversity did not affectdiversity similarly across taxonomic groups; whilelocal bee species richness increased with higher levels

of habitat diversity, an opposite pattern was observedfor bugs.

Land-use intensity and proximity index were selectedas the set of variables that best explained the totalvariation in local species richness, although the positiveeffect of increased proximity of the patches upondecreasing levels of land-use intensity was only presentfor spiders (Table 4 and Fig. 3).

Across taxonomic groups, land-use intensity and percent-age of the landscape covered with natural patches,patch proximity and both measures of habitat diversitywere significantly related to β diversity negativelyand positively (Table 3). Patch proximity explained thevariation in β diversity best.

Incorporating the different variables into one modelrevealed that land-use intensity and patch proximitycomprised the set of variables that explained mostvariation in β diversity. While the effect of patch proximityon β diversity did not differ between taxonomic groups,land-use intensity had a strong homogenizing effect onlocal bee species composition (Table 4 and Fig. 4).

Fig. 1. Principal component ordination of the investigatedagricultural landscape test sites based on agricultural land-useintensity, four landscape metrics of natural habitat patches(proportion, average proximity, density and average size) andtwo habitat diversity metrics.

Fig. 2. Gamma diversity of five different arthropod groups in23 agricultural landscape test sites in relation to agriculturalland-use intensity and average proximity index of the semi-natural habitat patches (black circles, Apoidea; white circles,Araneae; black triangles, Carabidae; white triangles, Heteroptera;black squares, Syrphidae). Graphs represent results conditionalupon the effect of other variables.

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Table 3. Effect of land-use intensity, landscape structure and habitat diversity on the different diversity components based on single variable regression analyses allowing the relationships to differ among thetaxonomic groups. Asterisks indicate significance of taxonomic group specific regression slopes after Bonferroni correction (*0·05 > P > 0·01; **0·01 > P > 0·001; ***P < 0·001)

Diversity component Variable

Main effect

AIC Overall slope

Interaction Taxon-specific slope

F P F P AIC Apoidea Araneae Carabidae Heteropteridae Syrphidae

Gamma LUI 17·95 0·0006 – – 2·57 0·049 757·6 −7·03 ± 1·59*** −4·47 ± 1·59* −1·07 ± 1·59 −1·76 ± 1·59 −1·79 ± 1·59PPERC 10·49 0·002 763·1 2·05 ± 0·63 1·74 0·15 763·7 – – – – –PDENS 0·26 0·6 772·9 −0·44 ± 0·86 1·06 0·4 776·0 – – – – –PSIZE 0·83 0·4 772·4 0·79 ± 0·87 0·53 0·7 778·5 – – – – –PPROX 25·49 < 0·0001 – – 2·6 0·041 750·1 5·98 ± 1·33*** 4·62 ± 1·33** 2·75 ± 1·33 0·85 ± 1·33 1·66 ± 1·33NEUNIS 7 0·01 – – 2·49 0·048 765·3 4·01 ± 1·38* 1·26 ± 1·38 3·10 ± 1·38 −1·55 ± 1·38 2·13 ± 1·38HDIV 10·48 0·002 – – 3·43 0·01 758·4 4·55 ± 1·21** 2·92 ± 1·21* 2·02 ± 1·21 −1·42 ± 1·21 1·18 ± 1·21

Alpha LUI 11·14 0·003 575·1 −1·15 ± 0·34 1·28 0·3 580·0 – – – – –PPERC 2·89 0·1 – 2·67 0·04 581·7 1·25 ± 0·60 0·98 ± 0·60 0·92 ± 0·60 −1·15 ± 0·60 0·36 ± 0·60PDENS 1·21 0·3 586·6 −0·35 ± 0·36 1·02 0·4 589·9 – – – – –PSIZE 0·08 0·8 587·6 0·11 ± 0·38 1·18 0·3 591·3 – – – – –PPROX 10·67 0·001 – 3·39 0·01 571·3 1·37 ± 0·62 2·12 ± 0·62** 1·42 ± 0·62 −0·80 ± 0·62 0·39 ± 0·62NEUNIS 1·73 0·2 – 3·28 0·01 582·1 1·48 ± 0·63 −0·06 ± 0·63 1·48 ± 0·63 −1·05 ± 0·63 0·25 ± 0·63HDIV 1·77 0·2 – 4·64 0·002 575·7 1·49 ± 0·55* 0·98 ± 0·55 0·59 ± 0·55 −1·61 ± 0·55* 0·26 ± 0·55

Beta LUI 14·1 0·002 – – 4·4 0·005 683·8 −5·53 ± 1·07*** −2·14 ± 1·07 0·28 ± 1·07 −1·95 ± 1·07 −1·35 ± 1·07PPERC 11·7 0·001 691·7 1·63 ± 0·47 1·34 0·3 693·8 – – – – –PDENS 0·1 0·8 702·8 −0·20 ± 0·65 0·85 0·5 706·6 – – – – –PSIZE 1·08 0·3 701·8 0·70 ± 0·66 0·27 0·9 708·7 – – – – –PPROX 22·02 < 0·0001 – – 2·8 0·03 680·3 4·94 ± 0·97*** 2·31 ± 0·97* 1·13 ± 0·97 1·94 ± 0·97 1·15 ± 0·97NEUNIS 5·53 0·02 698·0 1·25 ± 0·53 1·22 0·3 700·7 – – – – –HDIV 12·22 0·0008 691·3 1·57 ± 0·45 1·38 0·2 693·6 – – – – –

Beta relative LUI 2·39 0·14 – – 6·74 0·0006 –349·3 −0·053 ± 0·012*** 0·003 ± 0·012 0·019 ± 0·012 −0·009 ± 0·012 −0·016 ± 0·012PPERC 8·93 0·004 – – 2·88 0·03 −340·5 0·035 ± 0·011** 0·002 ± 0·011 0·005 ± 0·011 0·032 ± 0·011* 0·017 ± 0·011PDENS 0 0·9 −327·8 −0·0003 ± 0·007 0·86 0·5 −324·0 – – – – –PSIZE 2·41 0·12 −330·3 0·011 ± 0·007 1·54 0·2 −329·2 – – – – –PPROX 7·39 0·009 – – 4·55 0·002 −345·2 0·048 ± 0·011*** −0·004 ± 0·011 −0·004 ± 0·011 0·027 ± 0·011* 0·016 ± 0·011NEUNIS 5·11 0·03 −332·7 0·014 ± 0·006 1·21 0·3 −330·1 – – – – –HDIV 10·09 0·002 −337·5 0·017 ± 0·005 1·88 0·12 −337·6 – – – – –

347Agricultural factors and arthropod biodiversity

© 2007 The Authors. Journal compilation © 2007 British Ecological Society, Journal of Applied Ecology, 44, 340–351

β γ

On average, between 49% and 60% of the total speciesdiversity of the landscapes could be attributed to βdiversity. These proportions differed significantlybetween the taxonomic groups and were highest forbugs, followed by spiders, carabid beetles, hoverfliesand bees (Table 3).

The percentage of the landscape covered withsemi-natural habitat patches, patch proximity and bothmeasures of habitat diversity affected β diversity morestrongly than α diversity in a positive direction acrosstaxonomic groups. The effect of land-use intensity wasonly significant for bees (Table 4 and Fig. 5).

The change in relative contribution of β diversitycould be explained best by habitat diversity, with allinvestigated invertebrate groups equally affected andan additive effect of land-use intensity for bees.

Discussion

This large-scale study demonstrates that the totalspecies richness of arthropods in temperate Europeanagricultural landscapes decreases with increasing

Fig. 3. Alpha diversity of five different arthropod groups in23 agricultural landscape test sites in relation to agriculturalland-use intensity and average proximity index of the semi-natural habitat patches (black circles, Apoidea; whitecircles, Araneae; black triangles, Carabidae; white triangles,Heteroptera; black squares, Syrphidae). Graphs representresults conditional upon the effect of other variables.

Tab

le 4

.E

ffec

t of

land

-use

inte

nsit

y, la

ndsc

ape

stru

ctur

e an

d ha

bita

t div

ersi

ty o

n th

e di

ffer

ent d

iver

sity

mea

sure

s, b

ased

on

mul

tipl

e re

gres

sion

ana

lyse

s al

low

ing

the

rela

tion

ship

s to

dif

fer

amon

g th

e ta

xono

mic

grou

ps. A

ster

isks

indi

cate

sig

nific

ance

of

taxo

nom

ic g

roup

spe

cific

reg

ress

ion

slop

es a

fter

Bon

ferr

oni c

orre

ctio

n (*

0·05

> P

> 0

·01;

**0

·01

> P

> 0

·001

; ***

P <

0·0

01)

Div

ersi

ty

com

pone

ntF

acto

rd.

d.f.

FP

AIC

Slop

es

Ove

rall

Apo

idea

Ara

neae

Car

abid

aeH

eter

opte

raSy

rphi

dae

Gam

ma

TA

X18

·265

·43

< 0

·000

174

8·3

––

––

––

LU

I27

·52·

90 0

·10

––

––

––

TA

X ×

LU

I53

·22·

65 0

·04

−5·1

8 ±

1·62

*−2

·93

± 1·

620.

26 ±

1·6

2 0

·07

± 1·

62−0

·07

± 1·

62P

PR

OX

50·6

11·5

5 0

·001

32·

50 ±

0·7

4**

––

––

–A

lpha

TA

X27

·948

·96

< 0

·000

156

9·1

––

––

––

LU

I10

74·

29 0

·04

−0·7

8 ±

0·38

*–

––

––

PP

RO

X10

42·

54 0

·11

––

––

––

TA

X ×

PP

RO

X10

13·

50 0

·01

–0·

99 ±

0·6

0 1

·74

± 0·

60*

1·03

± 0

·60

−1·1

1 ±

0·60

0·0

1 ±

0·60

Bet

aT

AX

16·6

62·4

1<

0·0

001

674·

7–

––

––

–L

UI

26·4

0·98

0·3

––

––

––

TA

X ×

LU

I38

·34·

48 0

·005

– −

4·05

± 1

·13*

*−0

·76

± 1·

131·

71 ±

1·1

3−0

·39

± 1·

13 0

·09

± 1·

13P

PR

OX

49·2

11·9

4 0

·001

1·98

± 0

·57*

**–

––

––

Bet

a re

lati

veT

AX

16·4

14·6

5<

0·0

001

−355

·9–

0·49

± 0

·01

0·5

7 ±

0·01

0·55

± 0

·01

0·6

0 ±

0·01

0·5

4 ±

0·01

LU

I30

·30·

19 0

·7–

––

––

–T

AX

× L

UI

31·3

6·88

0·0

004

–−0

·045

± 0

·012

** 0

·011

± 0

·012

0·02

7 ±

0·01

2−0

·001

± 0

·012

−0·0

08 ±

0·0

12H

DIV

80·2

9·10

0·0

030·

016

± 0·

005

––

––

–

348F. Hendrickx et al.

© 2007 The Authors. Journal compilation © 2007 British Ecological Society, Journal of Applied Ecology, 44, 340–351

management intensity of the agricultural fields and analtered landscape structure. Although both factorsare related, in practice their effects appear to be, at leastpartially, additive. This is emphasized by the fact thatthe measure of land-use intensity used in the presentstudy is based on characteristics independent of land-scape structure (Herzog et al. 2006). The landscapefactor that best explains the observed γ diversity isproximity index, which integrates the size and inter-distance of the semi-natural habitat patches, but it doesnot allow separation of the effects of amount of availablehabitat and habitat isolation. Notwithstanding thisfact, as other landscape metrics (patch density, averagepatch size and total proportion of the landscapecovered with patches) did not explain a comparableamount of the unexplained variance, it is likely thatboth the amount and spatial configuration of suitablehabitat are important determinants of biodiversity inthe natural habitat patches.

When focusing on biodiversity at a local scale (i.e.α diversity), previously reported negative effects ofincreased land-use intensity on the local diversity(Duelli, Obrist & Schmatz 1999; Fauvel 1999; Marc,Canard & Ysnel 1999) are confirmed by our data. Nega-

tive effects of decreasing proximity upon farming inten-sity were significant for spiders and reveal that the localspider assemblages of a landscape with small andisolated patches contain fewer species. Local spiderassemblages of agricultural fields rarely contain uniquespecies compared with the border of agricultural fieldsand semi-natural habitat patches. In contrast, morenatural habitats embedded in an agricultural matrixcontain the majority of the spider species inhabitingthe agricultural fields plus a supplement of speciesbound to the more natural habitat patches (Maelfait& De Keer 1990; Schmidt & Tscharntke 2005). Thissuggests that local extinction/colonization processesof the latter species group plays an important role indetermining local spider species richness. Stochasticeffects can be expected to be much higher in smallpatches and may drive local populations to extinctionrather quickly (Hanski 1998). If dispersal capacitiesof these species are insufficient to cover the distancebetween these patches, small-scale extinctions are notcompensated for by recolonization from nearby patches.For spiders, dispersal occurs mainly by ballooning, inwhich juveniles produce long silk threads that carrythem up in the air currents (Bell et al. 2005). Dispersalpropensity differs strongly among spider species and

Fig. 4. Beta diversity of five different arthropod groups in23 agricultural landscape test sites in relation to agriculturalland-use intensity and average proximity index of thesemi-natural habitat patches (black circles, Apoidea; whitecircles, Araneae; black triangles, Carabidae; white triangles,Heteroptera; black squares, Syrphidae). Graphs representresults conditional upon the effect of other variables.

Fig. 5. Relative contribution of α diversity to γ diversity forfive different arthropod groups in 23 agricultural landscapetest sites in relation to habitat diversity of the semi-naturalhabitat patches (black circles, Apoidea; white circles, Araneae;black triangles, Carabidae; white triangles, Heteroptera; blacksquares, Syrphidae). Graphs represent results conditional uponthe effect of other variables.

349Agricultural factors and arthropod biodiversity

© 2007 The Authors. Journal compilation © 2007 British Ecological Society, Journal of Applied Ecology, 44, 340–351

has been shown to correlate positively with the degreeof habitat generalism (Bonte et al. 2003; Bell et al. 2005),suggesting that more specialized species become depletedfrom these isolated patches that consequently containonly a few, generalist species with high dispersal abilities.Thus, local spider species diversity is enhanced in patchessurrounded by a larger percentage of non-crop areas, asreported elsewhere (Clough et al. 2005; Schmidt et al.2005). In contrast, for other arthropod groups, suchas carabid beetles, Cole et al. (2005) showed that localspecies diversity in agricultural fields did not differsignificantly compared with natural areas because ofa high turnover of typical agrobiont species.

Most importantly, our results suggest that the lossin species richness of the total landscape is not solelythe result of a decrease in species richness of the localcommunities but additionally caused by a loss of speciesturnover between local communities. Our results implythat local communities of landscapes consisting ofsmall and unconnected patches are characterized bya species composition that hardly diverges betweenpatches. This homogenizing effect can be under-stood most clearly when combined with the results onα diversity, where we found a clear impoverishment ofthe local arthropod diversity with increasing land-useintensity and, to a lesser extent, a decreasing proximityindex. This suggests that local communities becomeunsaturated, most probably because of the depletionof specialist, and typically more competitive, species(Tilman et al. 1994) primarily characterized by low dis-persal capacities (de Vries, den Boer & van Dijk 1996).These vacant positions within the local community canconsequently be replaced by species of the surroundingagricultural matrix. Although these species are typicallycharacterized by low competitive abilities, their highmobility makes them more likely to occupy patches notyet recolonized by superior competitors because ofthe others’ low dispersal properties (Nee & May 1992;Tilman et al. 1994; Kareiva & Wennergren 1995). Thisis also suggested by community analysis of the studysites, where it was found that landscapes with small,isolated patches embedded within a highly agriculturalintensive matrix contained small and relatively unspe-cialized species (Aviron et al. 2005; Schweiger et al. 2005).

Effects of increasing land-use intensity upon theeffect of proximity on β diversity could only be demon-strated for bees, which decreased from 25 species inless intensively managed landscapes to approximately10 species in the most intensively managed landscapes.The prominent homogenizing effect of bee speciescomposition with increasing land-use intensity is likelyto be linked to their dependency on flowering plantdiversity (Tscharntke, Gathmann & Steffan-Dewenter1998). Our measure of land-use intensity is based onnitrogen input, amount of herbicides and pesticides usedand livestock densities. Highly intensively managedlandscapes, which consist of a mixture of species-poorgrassland, dominated by species such as Lolium perenneand Holcus lanatus, and arable land, are therefore

characterized by flowering perennial plants. Thesemanagement practices also lead to spread of fertilizersand herbicides into the borders of the semi-naturalpatches, which will subsequently decrease quality interms of plant species diversity. These environmentalcircumstances are likely to favour only a small subset ofthe original bee fauna, such as some generalist bumblebeespecies that are capable of exploiting mass floweringcrops (Westphal, Steffan-Dewenter & Tscharntke 2003).

In relation to habitat diversity, no net effect ofincrease in species richness was observed in either γ orβ diversity. However, habitat diversity caused a shift inthe relative contribution of α and β diversity to γ diver-sity, wherein increasing habitat diversity resulted inan increase of the relative contribution of β diversity.However, it must be emphasized that this will simul-taneously lead to a decrease in the contribution of αdiversity, probably caused by the decreasing proximityof patches of a particular habitat type.

The coincidence of patterns of β diversity with thoseof γ diversity stresses the importance of dissimilaritybetween local community species composition as oneof the most important determinants of total landscapespecies diversity in agricultural landscapes. It istherefore important to emphasize that evaluation andimplementation of agri-environment schemes mustincorporate the expected gain in species richness as aresult of species differences between local communities.When restricting the results at the local scale, forinstance, the importance of proximity could only bedemonstrated for spiders, while all species groupsappeared to be affected by this landscape featurewhen focusing on β and γ diversity. Evaluation of agri-environment schemes based on the different compo-nents of landscape species diversity hence might help tointerpret the previously recorded ambiguous results.

Acknowledgements

We are particularly grateful to the following who helpedidentify the species: Tim Adriaens, Frank Burger, RafaëlDe Cock and Jaan Luig (wild bees), Berend Aukema,Roland Bartels, Jean-Yves Baugnée and RalphHeckman (bugs), Konjev Desender, Ringo Dietzeand Keaty Maes (carabid beetles), Martin Musche andDieter Doczkal (hover flies) and Herman De Koninck,Valerie Vanloo and Johan Van Keer (spiders).

Luc Lens, Jan Bengtsson and two anonymous refereesare acknowledged for their constructive commentson a previous version of this manuscript. Funding wasreceived from the Energy, Environment and SustainableDevelopment Programme (FP5) of the European Com-mission (contract number EVK2-CT-2000-00082).

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Received 9 March 2006; final copy received 17 November 2006Editor: Paul Giller