RESEARCH ARTICLE

Functional beetle diversity in managed grasslands: effectsof region, landscape context and land use intensity

Yunhui Liu • Christoph Rothenwohrer • Christoph Scherber • Peter Batary •

Zoltan Elek • Juliane Steckel • Stefan Erasmi • Teja Tscharntke • Catrin Westphal

Received: 30 June 2013 / Accepted: 7 January 2014 / Published online: 28 January 2014

� Springer Science+Business Media Dordrecht 2014

Abstract Current biodiversity conservation policies

have so far had limited success because they are

mainly targeted to the scale of individual fields with

little concern on different responses of organism

groups at larger spatial scales. We investigated the

relative impacts of multi-scale factors, including local

land use intensity, landscape context and region, on

functional groups of beetles (Coleoptera). In 2008,

beetles were suction-sampled from 95 managed

grasslands in three regions, ranging from Southern to

Northern Germany. The results showed that region

was the most important factor affecting the abundance

of herbivores and the abundance and species compo-

sition of predators and decomposers. Herbivores were

not affected by landscape context and land use

intensity. The species composition of the predator

communities changed with land use intensity, but only

in interaction with landscape context. Interestingly,

decomposer abundance was negatively related to land

use intensity in low-diversity landscapes, whereas in

high-diversity landscapes the relation was positive,

possibly due to enhanced spillover effects in complex

landscapes. We conclude that (i) management at

multiple scales, from local sites to landscapes and

regions, is essential for managing biodiversity, (ii)

beetle predators and decomposers are more affected

than herbivores, supporting the hypothesis that higher

trophic levels are more sensitive to environmental

change, and (iii) sustaining biological control and

decomposition services in managed grassland needs a

diverse landscape, while effects of local land use

intensity may depend on landscape context.

Electronic supplementary material The online version ofthis article (doi:10.1007/s10980-014-9987-0) contains supple-mentary material, which is available to authorized users.

Y. Liu (&) � C. Rothenwohrer � C. Scherber �P. Batary � T. Tscharntke � C. Westphal

Agroecology, Department of Crop Sciences,

Georg-August-University, 37077 Gottingen, Germany

e-mail: liuyh@cau.edu.cn

Present Address:

Y. Liu

College of Agricultural Resources and Environmental

Sciences, China Agricultural University, Beijing 100193,

China

Z. Elek

MTA-ELTE-MTM, Ecology Research Group,

Budapest 1117, Hungary

J. Steckel

Department of Animal Ecology and Tropical Biology,

Biocenter, University of Wuerzburg, Am Hubland,

97074 Wuerzburg, Germany

S. Erasmi

Institute of Geography, Georg-August-University,

37077 Gottingen, Germany

123

Landscape Ecol (2014) 29:529–540

DOI 10.1007/s10980-014-9987-0

Keywords Coleoptera � Functional groups �Functional traits � Multiple scales � Landscape

diversity

Introduction

Biodiversity conservation in agriculturally dominated

areas is of growing concern, because it is important to

sustain ecosystem services (Altieri 1999; MEA 2005).

As the intensive application of synthetic fertilizers and

pesticides at local scales is a main cause of biodiver-

sity loss (Matson et al. 1997; Wilson et al. 1999),

improved local-scale management with, for example,

ecological intensification strategies has been sug-

gested as a major solution for biodiversity conserva-

tion in agricultural landscapes (Tscharntke et al.

2012a; Bommarco et al. 2013).

However, conservation policies neglecting large-

scale effects may achieve only limited success (Ben-

gtsson et al. 2005; Batary et al. 2011; Tscharntke et al.

2012b). Factors at larger spatial scales, including

regional effects and landscape context, may be

important for species distributions and community

composition. Regions are broad geographical areas

composed of many landscapes and often vary in many

aspects such as land use, topography and climate

(Ricklefs 1987; Caley and Schluter 1997). Land-

scapes, on other hand, are composed of a mix of

ecosystems and land-use types, which cover the short-

term dispersal ranges of most (non-migratory) organ-

isms. The landscape context can moderate biodiversity

patterns in agroecosystems in various ways, including

population dynamics and functional trait selection of

populations (Tscharntke et al. 2012b). Complex

landscapes with high proportions of non-crop habitat

can enhance local diversity, where source populations

can spill over into crops and therefore provide spatio-

temporal insurance (Tscharntke et al. 2012b). The

surrounding landscape can modify effects of local

management on biodiversity, and conservation man-

agement is often most effective in landscapes with

intermediate complexity, rather than in simplified or

complex landscapes (Tscharntke et al. 2005; Concep-

cion et al. 2012). Therefore, landscape-scale manage-

ment should take priority over local measures

(Concepcion et al. 2012). In addition, variation in

functional traits can also affect the responses of

species to environmental change (Henle et al. 2004).

For example, species at higher trophic levels are often

more likely to become extinct than those at lower

levels, because of their lower population density,

longer duration of juvenile stages or larger home

ranges, making them less likely to persist in changing

environments (Gard 1984; Holt 1996; Lovei et al.

2006). Incorporating functional traits into biodiversity

research can help to better understand the effects of

land-use changes on biodiversity (Weiher and Keddy,

1995) and associated ecosystem services (Dıaz et al.

2007; Lavorel et al. 2011). Therefore, for successful

biodiversity management, it is important to identify

the appropriate scale of the intervention (Kleijn et al.

2006), and more information is needed about how

region, landscape context and local land use intensity

interact in affecting the distribution, abundance and

community composition of organisms with different

traits (Bommarco et al. 2013).

Beetles (order Coleoptera) are the most diverse

group in the animal kingdom, accounting for almost

25 % of all known life-forms (Powell 2009). They are

diverse in feeding habits and play important roles for a

wide range of ecological processes (Slade et al. 2007;

Nichols et al. 2008). Because of the important roles of

beetles in both biodiversity and ecosystem function-

ing, a number of well-known beetle families, such as

Carabidae, Coccinellidae and Staphylinidae, have

been investigated with respect to their responses to

landscape context and local land management (Grand-

champ et al. 2005; Clough et al. 2007; Gardiner et al.

2009). Strong effects of landscape context (Millan de

la Pena et al. 2003; Purtauf et al. 2005b) or both local

and landscape scale factors (Aviron et al. 2005;

Werling and Gratton 2008) have so far been recorded,

and beetle responses have been suggested to vary with

functional traits such as body size, feeding habit or

habitat affinity (Aviron et al. 2005; Batary et al. 2007;

Clough et al. 2007). Predatory species, for instance,

have been reported to be more affected by changing

landscape context and pesticide application than

herbivorous and omnivorous species (Theiling and

Croft 1988; Purtauf et al. 2005a). Unfortunately, very

few studies have so far considered a wider diversity of

Coleoptera groups and related their responses to

environmental change across multiple scales as

affected by functional traits (Batary et al. 2007;

Clough et al. 2007; Barragan et al. 2011).

In this study, we aimed to investigate the roles of

region, landscape context and local land use intensity

530 Landscape Ecol (2014) 29:529–540

123

for abundance and composition of a broad range of

coleopterans, and whether the importance of these

factors differs among functional groups of beetles.

Specifically, we focus on the interactions between

landscape context and local land use intensity, because

it is crucial to design efficient conservation strategies

for agricultural landscapes across scales (Tscharntke

et al. 2005; Concepcion et al. 2012). We hypothesized

that large-scale factors, either region or landscape

context, affect abundance and composition of beetles

more strongly than local-scale factors. The effects of

local land use intensity on abundance and community

composition of beetles depend on landscape context,

and we assume higher abundances in more diverse

landscapes. Species at higher trophic levels, including

predators and decomposers, are assumed to be more

sensitive to land use intensity and changing landscape

context than herbivores.

Materials and methods

Study regions and sampling design

The study was performed within the framework of the

large-scale and long-term functional biodiversity

research platform ‘‘Biodiversity Exploratories’’ (Fischer

et al. 2010). Three study regions were selected for

sampling: The Biosphere Reserve ‘‘Schorfheide-Chorin’’

(Schorfheide) in North-eastern Germany, the Hainich

National Park and its surroundings (Hainich) in Central

Germany, and the Biosphere Reserve ‘‘Schwabische

Alb’’ (Alb) in South-Western Germany (for more details

see http://www.biodiversity-exploratories.de) (Table 1).

The Schorfheide can be characterized by numerous water

bodies and wetlands such as lakes, moors and fens. The

Hainich is characterized by intensively managed grass-

lands and arable fields, but also extensively managed

grasslands surrounding the small forested core area of the

Hainich National Park. The Alb is a typical heteroge-

neous region with a relatively high proportion of grass-

lands, with interspersed agricultural land and forests.

In 2008, a total of 95 grasslands in the three regions

(32 in Alb, 28 in Hainich, 35 in Schorfheide) were

selected for sampling, whose locations were stored in a

keyhole markup language (KML) file and can be

tracked using Google Earth (www.google.com/earth)

(Shapiro and Baldi 2012) (see Appendix S1 in the

Supplementary Material). All grasslands were man-

aged by farmers with mowing up to three times per

year and/or grazing as well as fertilization, repre-

senting a gradient in local land use intensity.

Beetle sampling and classification of functional

groups

We used suction sampling to collect beetles, which

allows sampling from a defined area, covering a broad

Table 1 Land use types, landscape diversity, LUI and land use management for the three study regions

Index Alb Hainich Schorfheide

Mean ± SD Min. Max. Mean ± SD Min. Max. Mean ± SD Min. Max.

% Arable lands 13.0 ± 14.5 0.0 50.6 26.4 ± 20.3 0.0 72.5 16.8 ± 16.6 0.0 53.6

% Forests 36.5 ± 23.2 1.5 88.0 21.7 ± 23.4 0.0 74.9 15.2 ± 20.8 0.0 67.5

% Grasslands 30.8 ± 16.5 0.0 70.8 33.1 ± 19.6 0.0 89.3 52.7 ± 17.7 18.1 86.9

% Semi-natural habitats 13.7 ± 17.0 0.0 67.7 12.1 ± 16.7 0.0 62.6 7.4 ± 6.8 0.0 31.4

% Water bodies 0.0 ± 0.0 0.0 0.1 0.0 ± 0.0 0.0 0.1 2.4 ± 5.0 0.0 27.6

Landscape diversity 1.1 ± 0.3 0.4 1.6 1.2 ± 0.3 0.4 1.7 1.1 ± 0.3 0.5 1.5

Land use intensity 1.6 ± 0.7 0.4 3.5 1.6 ± 0.7 0.5 2.5 1.6 ± 0.7 0.9 3.2

Nitrogen input (kg nitrogen ha-1 year-1) 25.1 ± 26.2 0 100 27.2 ± 33.5 0 80 17.9 ± 37.4 0 125

Mowing frequency 1.1 ± 1.1 0 3 1.0 ± 1.0 0 3 1.0 ± 0.9 0 3

Livestock units (ha-1) 34.2 ± 42.9 0 200 38.8 ± 26.7 0 83 37.8 ± 36.3 0 99.5

Grazing days (day year-1) 18.9 ± 28.9 0 120 44.8 ± 63.3 0 263 24.8 ± 32.7 0 133

Proportional area of land use types (% arable lands, % forests etc.) and landscape diversity were calculated for circular areas with a

500 m radius around each grassland plot

Livestock units were converted from the data on age and density of livestock as presented by Fischer et al. (2010)

Landscape Ecol (2014) 29:529–540 531

123

range of beetle taxa from both plants and the soil

surface in grassland (Borges and Brown 2003; Brook

et al. 2008). A 3.5 m 9 7 m plot was defined at least

15 m away from the border of each grassland. At each

plot, two suction samples were taken at randomly

selected locations in the first run (from 15th May to

2nd July in 2008), and retaken at the same sites in

another run (from 11th August to 1st September in

2008). For each suction sample, a D-Vac sampling

device (Stihl SH 56), was operated for 1 min (Brook

et al. 2008). The D-Vac was equipped with a gauze

cage covering 0.25 m2 area of vegetation to prevent

insects from escaping. All beetles were identified to

species or morphospecies (genus) level, and assigned

to functional groups (predators, herbivores and

decomposers) according to the main feeding habits

during their entire phenology (Koch1989a, b, 1992;

Bohme 2001). The decomposers included mycetoph-

agous, saprophagous and coprophagous beetles.

Landscape data and land use index

Landscapes within a 500 m radius of the sampled plots

were mapped and digitized for all 95 grasslands based

on an extensive field mapping campaign as well as

high resolution aerial photographs taken by ‘‘Hansa

Luftbild’’ company with a geometric resolution of

40 cm. A radius of 500 m surrounding the sampled

plot was considered because it has been suggested to

be large enough to describe the landscape relevant for

beetle dispersal (Aviron et al. 2005; Batary et al.

2007). The landscape was classified into eight general

land use categories, including arable lands, forests,

grasslands, semi-natural habitats, roads, woodlands,

urban areas and water bodies. Landscape Shannon

diversity index (SHDI or landscape diversity in

abbreviation), which reflects the diversity and com-

position of landscape context, is one of the most

widely applied landscape metrics in biodiversity

research on a landscape scale (Concepcion et al.

2008; Bassa et al. 2011). SHDI was calculated within a

radius of 500 m around the sampling plots using

FRAGSTATS 3.3 (McGarigal et al. 2002). SHDI was

positively correlated with proportion of non-crop

habitats including semi-natural habitats (Spearman’s

rho = 0.456, P \ 0.001) and woodlands (Spearman’s

rho = 0.397, P \ 0.001) in our study, and exhibited a

good gradient across the three study regions.

In addition, we used a land use intensity index

(LUI) to measure the local land use intensity of the

grassland plots (Bluthgen et al. 2012). The index is

simple and additive and incorporates grazing intensity,

mowing frequency and the level of fertilization,

allowing us to test how biodiversity of beetles changes

along a single continuous land use intensity gradient

(Bluthgen et al. 2012).

Statistical analysis

Beetle data from the four suction samples of the same

plot were pooled for analysis. Both abundance and

species composition were analyzed. Abundance was

selected because it is more important in deciding

ecosystem function and is usually strongly correlated

with species richness (Naeem and Wright 2003).

Effects of region, landscape context and local land

use intensity on the abundance of beetles from all three

feeding types were analyzed with R 2.15.2 (R Core

Team 2012). Variance inflation factors (VIF) were

calculated to assess collinearity between SHDI and

LUI; however, collinearity was not severe (VIF \3)

(Zuur et al. 2009). We used generalized least squares

models (gls, nlme package version 3.1–108 in R) for

analysis (Pinheiro et al. 2013). Region, SHDI and LUI

were entered as fixed-effects terms, including two-

way interactions, and the model was simplified using

the stepAIC function in the MASS library (Venables

and Ripley 2002). To account for spatial autocorrela-

tion, we fitted gls models to response variables with

Gauss–Kruger coordinates treated as spatial covari-

ates, assuming a spherical spatial correlation structure

(Pinheiro and Bates 2000), but only the final model of

herbivore abundance included a spatial covariate as

indicated by the lower AIC of the model containing

spatial autocorrelation.

For the analysis of species composition of different

functional groups in response to region, landscape

context, local land use intensity, and interaction

between landscape context and land use intensity

(SHDI 9 LUI), we calculated four separate partial

redundancy analyses (pRDA) for each functional

group. The species matrix was constrained either by

region, landscape context, local land use intensity or

SHDI 9 LUI, with the remaining variables set as

conditional. Prior to the analyses, the species matrix

was modified using the Hellinger transformation

(Legendre and Gallagher 2001) to allow the use of

532 Landscape Ecol (2014) 29:529–540

123

ordination methods such as PCA, RDA, which are

Euclidean-based, with community composition data

containing many zeros. Pseudo-F values with the

corresponding P-values were calculated using permu-

tation tests based on 999 permutations. Finally, the

spatial autocorrelation of plots was diagnosed using

the mso function, but no spatial patterns were

observed. Calculations were performed using the

vegan package for R (version 2.0; Oksanen et al.

2012).

Five species accounting for 0.5 % of total abun-

dance, for which feeding was not identified due to

morphospecies or missing recording (see Appendix S2

in Supplementary Material), were excluded from the

RDA analyses. When analyzing the decomposers, one

plot at the Hainich region was excluded due to the

highly aggregated abundance of one decomposers

species, Tytthaspis sedecimpunctata (Linnaeus),

accounting for more than 74.3 % of total decomposer

abundance at Hainich.

Results

Species diversity and composition

In total, 2,283 individuals representing 26 families and

201 species (herbivores: 95; predators: 64; decom-

posers: 37; unidentified: 5 species), were collected

(Appendix S2). Herbivores accounted for 49.8 % of

total abundance, followed by decomposers (38.9 %)

and predators (10.8 %). The relative abundances of

the feeding types varied among regions. Herbivores

were dominant in Alb (73.1 %), but had a similar

abundance with decomposers in Hainich (herbivores:

44.3 % and decomposers: 50.7 %). In Schorfheide,

herbivores (49.5 %) had the greatest relative abun-

dance followed by decomposers (32.1 %) and preda-

tors (18.2 %). Abundance and species richness were

strongly correlated in herbivores (Spearman’s

Rho = 0.881, P \ 0.001), predators (Spearman’s

rho = 0.976, P \ 0.001) and decomposers (Spear-

man’s rho = 0.898, P \ 0.001).

Effects of region, landscape context and land use

intensity on beetle abundances

The abundance of herbivores was not affected by

region, landscape context and land use intensity as

shown by our generalized least squares models

(Table 2; Fig. 1). Predators were only affected by

region, with higher abundance in Schorfheide than in

Hainich and in Alb (Table 2; Fig. 1). Decomposers

were also strongly influenced by region, with highest

abundance in Schorfheide and lowest in Alb. In

addition, there was an interaction between land use

intensity and landscape context (Table 2): The abun-

dance of decomposer beetles increased with the

increase of land use intensity in highly diverse

landscapes (Fig. 2a), but showed a negative relation

in low diversity landscapes (Fig. 2b).

Effects of region, landscape diversify and land use

intensity on community composition

The partial RDA analyses showed that region

explained the greatest percentage of overall variance

in the community matrix across all feeding types

(Table 3), indicating differences in species composi-

tion among regions (Appendix 1). Land use intensity

was only related to the species composition of

predators, explaining 2.3 % of the variation (Table 3).

Landscape context, however, was only related to the

species composition of predatory beetles in combina-

tion with land use intensity, indicating a strong

interactive effect between landscape context and local

land use intensity on the species composition of

predatory beetles (Table 3; Fig. 3).

Discussion

Consistent with our hypotheses, the largest spatial

scale (region) had the greatest effect on the compo-

sition of the beetle communities. Landscape context

showed interactive effects with local land use intensity

on higher tropic levels such as the decomposer

abundance and predator composition. Our results

support a multiple-scale perspective, from local sites

to landscapes and regions, for biodiversity conserva-

tion. They further show that highly diverse landscapes

are needed to sustain high diversity of predators and

decomposers and associated services including bio-

logical control and decomposition, while the impor-

tance of local land use intensity changed with

landscape context.

The strong effects of region may be explained by a

wide range of factors, including climate, topography,

Landscape Ecol (2014) 29:529–540 533

123

soil conditions, land use history, landscape pattern and

land use intensity (Aviron et al. 2005; Clough et al.

2005). Due to the large scale and variety of factors, it is

difficult to identify the exact causes for such strong

regional effects. As landscape context and land use

intensity did not significantly differ among regions,

other factors such as regional climate or land use

history may have been the main driver. Given that the

current directives of EU agri-environment schemes

are mainly targeting the national or federal state level,

with regions differing in natural conditions or land use

history, it is important to encourage regionally explicit

conservation schemes (Wilson et al. 1999). Mean-

while, our results also indicate that the relative

abundance and composition of functional groups

may change considerably with region. It would be

interesting to investigate whether these differences

would lead to variations in ecological services

(Symondson et al. 2002; Clough et al. 2005) and what

the main drivers of such regional differences could be.

This should be crucial to develop a rigorous

Table 2 Effects of region, landscape context and local land use intensity on the abundance of feeding types in managed grasslands

Functional group Explanatory variables numDF Denom. DF F-value P value

Herbivores Region (R) 2 86 1.13 0.327

Landscape context (SHDI) 1 86 0.42 0.521

Land use intensity(LUI) 1 86 0.63 0.429

R 9 SHDI 2 86 0.86 0.425

R 9 LUI 2 86 2.63 0.078

Predators Region (R) 2 92 11.98 \0.0001

Decomposers Region (R) 2 86 24.77 \0.0001

Landscape context (SHDI) 1 86 2.18 0.143

LUI 1 86 0.64 0.426

R 9 SHDI 2 86 1.19 0.309

SHDI 9 LUI 1 86 4.11 0.046

Fig. 1 Beetle abundance (log10-transformed) of different

feeding types across study regions

Fig. 2 Contrasting effects

of local land use intensity on

decomposer abundance

(log10-transformed) in

landscapes with high and

low levels of diversity.

Results are predictions from

generalized least squares

models

534 Landscape Ecol (2014) 29:529–540

123

conservation management for ecosystem services

(Chan et al. 2006) and also to provide recommenda-

tions for associated management strategies on a local

scale.

In our study, the decomposers were dominated by

mycetophagous herb layer species, which may change

to feed on pollen, Acari or Thysanoptera (Ricci 1986;

Sutherland and Parrella 2009), and consisted of

families such as Hydrophilidae, Lathridiidae and

Staphylinidae, requiring diverse food sources like

fungi, decaying plant matter, dung, and carrion. In

diverse landscapes, where sufficient habitats for

overwintering, shelter, breeding and food (plant

detritus, fungus, carrion) are available, decomposer

species can avoid the negative effects of increasing

land use intensity by dispersing between intensively

managed and natural/semi-natural habitats (Fournier

and Loreau 2001; Duelli and Obrist 2003). In such a

landscape context, increases in land use intensity may

result in higher productivity providing higher amount

of food resources benefiting many species spilling

over between managed and natural habitat (Hutton and

Giller 2003; Tscharntke et al. 2005; Rand et al. 2006).

On the contrary, in landscapes with low structural

diversity, where suitable habitat outside agricultural

land use systems is missing, the decomposer assem-

blage will be negatively affected by intensive man-

agement (Dennis et al. 1998; Hutton and Giller 2003).

Accordingly, our findings indicate that the abundance

Table 3 Species composition of beetles in three feeding types sampled on managed grasslands: percentage of variance explained by

partial redundancy analyses (pRDA)

Explanatory Herbivores Predators Decomposers

Region (R) 5.8** 5.4** 9.0**

(Pseudo-F2, 90 = 2.84;

P = 0.001)

(Pseudo-F2, 63 = 1.87;

P = 0.001)

(Pseudo-F2, 73 = 3.75;

P = 0.001)

Landscape context

(SHDI)

1.2 1.5 1.4

(Pseudo-F1, 90 = 1.16;

P = 0.265)

(Pseudo-F1, 63 = 1.05;

P = 0.337)

(Pseudo-F1, 73 = 1.20;

P = 0.267)

Land use intensity (LUI) 1.2 2.3* 1.5

(Pseudo-F1, 90 = 1.20;

P = 0.216)

(Pseudo-F1, 63 = 1.61;

P = 0.016)

(Pseudo-F1, 73 = 1.22;

P = 0.268)

SHDI?LUI 2.4 3.8* 2.9

(Pseudo-F2, 90 = 1.18;

P = 0.169)

(Pseudo-F2, 63 = 1.31;

P = 0.035)

(Pseudo-F2, 73 = 1.21:

P = 0.208)

Significance marked with asterisk (Monte-Carlo test, 999 permutations); levels of statistical significance: ** 0.001 \ P \ 0.010;

* 0.010 \ P \ 0.050

Fig. 3 Biplot of partial RDA ordination for predators with

landscape context (SHDI) and LUI as constraints variables and

region as condition variable. For visibility, only beetles having

greater value on both axes are labeled. Amisanal—Amischa

analis; Amisnigr—Amischa nigrofusca; Bembgilv—Bembidion

gilvipes; Bemblamp—Bembidion lampros; Bembobtu—Bembi-

dion obtusum; Calamela—Calathus melanocephalus; Drom-

line—Dromius linearis; Druscana—Drusilla canaliculata;

Dyscglob—Dyschirius globosus; Hippvari—Hippodamia var-

iegata; Micrmaur—Microlestes maurus; Malabipu—Malachius

bipustulatus; Quedboop—Quedius boops; Scymmimu—Scym-

nus mimulus; Stenclav—Stenus clavicornis; Synttrun—Synto-

mus truncatellus; Trecquad—Trechus quadristriatus;

Propquat—Propylaea quatuordecimpunctata; Sunimela—Su-

nius melanocephalus

Landscape Ecol (2014) 29:529–540 535

123

of decomposers increased with increasing land use

intensity in high-diversity landscapes, but decreased in

low-diversity landscapes.

Predatory beetles, on the other hand, showed a great

variability of responses to landscape context and land

use intensity as indicated by our ordination analyses.

Amischa analis (Gravenhorst) and Bembidion obtu-

sum (Serville), for example, had greater species scores

both on the first and on the second axis, indicating a

positive association with land use intensity and

landscape diversity. These species can benefit from a

combination of a diverse landscape context and a high

management intensity, because they preferentially

occur in both natural and managed habitat (Koch

1989a; Kennedy 1994). Species such as Calathus

melanocephalus (Linnaeus), Syntomus truncatellus

(Linnaeus), Drusilla canaliculata (Fabricius) were

positively related with landscape diversity but did not

react to land use intensity because they prefer more

natural habitats such as dry forest margins, heathland,

bogs, or river banks (Koch 1989a). Species such as

Bembidion gilvipes (Sturm), Malachius bipustulatus

(Linnaeus), Dromius linearis (Olivier) or Trechus

quadristriatus (Schrank) were negatively associated

with both landscape diversity and land use intensity

because they are strongly associated with well-defined

natural habitat types. Finally, species, which prefer

warm open habitat (Koch 1989a) but have small body

sizes, such as Scymnus mimulus Capra and Fursch and

Microlestes maurus (Sturm), are less capable to escape

from intensive farmland management by immigrating

into the surrounding non-crop habitats (Greenleaf

et al. 2007; Purnama Hidayat et al. 2010). Therefore,

they showed a negative association with land use

intensity and were not affected by landscape context.

Furthermore, another important finding of this

study was the wide range of responses of functional

groups to landscape context and local land use

intensity, indicating trait-dependent responses to

landscape context and land use intensity. In contrast

to predators and decomposers, herbivores were not

impacted by landscape context, local land use inten-

sity or interactive effects of landscape context and land

use intensity, confirming the hypothesis that species at

a higher trophic level are more strongly affected by

changes in landscape composition (Purtauf et al.

2005a) and land use intensity than lower trophic levels

such as herbivores (Morris and Rispin 1988;

Tscharntke and Kruess 1999).

However, landscape context and land use intensity

showed generally low effects on the beetle functional

groups in this study, in contrast to earlier studies

indicating strong impacts of either landscape context

(Jonsen and Fahrig 1997; Woltz et al. 2012) or land

use intensity (Kruess and Tscharntke 2002). No effects

of landscape context on herbivore beetle diversity

could be explained by the dominance of open land

species (64.1 % of total herbivore abundance), which

are grassland specialists (Appendix S2) and less

associated with surrounding habitats. For example,

the most abundant species, such as Ischnopterapion

virens (Herbst) and Olibrus bicolor (Fabricius), were

oligophagous species, restricted to defined host plants

or habitats (Koch 1989b; Hoebeke et al. 2000;

Sanderson et al. 2003). Similarly, herbivores were

not affected by local land use intensity in our study.

These results partly support earlier studies indicating

high variability of herbivore responses to local habitat

quality. For example, grazing may affect only spe-

cialist but not generalist leaf beetles (Chrysomelidae)

and not at all weevils (Curculionidae) in extensively

grazed pastures (Batary et al. 2007). Contrasting

reactions of different taxa could buffer the overall

effect of land use intensity at a community level.

Another explanation for the lack of effects of land use

intensity would be that herbivore beetles in our study

regions had already adapted to the intensive manage-

ment (Grandchamp et al. 2005; Batary et al. 2007), at

least at the level of land use intensity investigated here.

Similarly, the great variation in the responses of

predatory beetles would make any general prediction

on the effects of landscape context and land use

intensity on predators difficult.

The suction sampling technique gives a reliable

estimation per area and was applied in a standardized

way to make samples highly comparable and the ratio

of observed to estimated species richness (Borges and

Brown 2003; Colwell 2013) showed high reliability

(that 81.9–82.9 % of all species found). However, also

this sampling method might affect results as suction

sampling results still represent different parts of the

beetle community when compared with other

approaches such as pitfall sampling (Borges and

Brown 2003), with the later commonly analyzed in

earlier studies (Purtauf et al. 2005a, b; Batary et al.

2007; Clough et al. 2007). Suction sampling is

inefficient in catching species living near the soil

surface (Sanders and Entling 2011) or large and heavy

536 Landscape Ecol (2014) 29:529–540

123

species (Mommertz et al. 1996), including predators

and decomposers such as Carabidae and larger Staph-

ylinidae (Mommertz et al. 1996; Sanders and Entling

2011). In our study, no large beetles ([15 mm) were

found, while 159 species accounting for more than

94.4 % of the total individuals were very small beetles

(\5 mm) (Appendix S2) (Cole et al. 2002). The

responses to landscape and local land use intensity

could depend on body size (Concepcion and Dıaz

2011), with larger beetles having longer larval stages

potentially being more susceptible to anthropogenic

disturbances than small species (Blake et al. 1994;

Lovei et al. 2006). Thus, given that large species were

absent from our datasets, our study therefore only

allows conclusions on the effects of landscape context

and local land use intensity for beetle functional

groups with a small body size. However, our study as a

whole highlights the importance of incorporating

functional traits (even multiple traits) into the inves-

tigation on the mechanisms for the land use driven

changes in biodiversity (Henle et al. 2004; Driscoll

and Weir 2005; Dıaz et al. 2007). For a more

comprehensive understanding on how complete

inventories of coleopterans change with the environ-

ment at different spatial scales, future studies may

combine pitfall traps together with suction samples to

derive more complete datasets of beetle composition

and species richness (Mommertz et al. 1996; Sanders

and Entling 2011).

Conclusions

In conclusion, this study has shown that region is the

most important factor driving the abundance of

herbivores and both the abundance and composition

of predators and decomposers. Landscape context and

land use intensity affected herbivores least, which is in

support of a trophic-level hypothesis of sensitivity to

environmental change. Interestingly, both predators

and decomposers were affected by interactive effects

of landscape context and land use intensity. Decom-

posers even benefited from increasing land use

intensity, but only in high-diversity, not in low-

diversity landscapes, possibly due to enhanced spill-

over effects in complex landscapes to highly produc-

tive agroecosystems. Hence, biodiversity management

needs to consider multiple spatial scales, from local

sites to landscapes and regions with a particular focus

on predators and decomposers, being more affected

than herbivores. Sustaining biological control and

decomposition services in managed grassland needs

primarily a diverse landscape, while effects of local

land use intensity regime in grasslands can change

with landscape context.

Acknowledgments We thank the managers of the three

exploratories, Swen Renner, Sonja Gockel, Kerstin Wiesner,

and Martin Gorke for their work in maintaining the plot and

project infrastructure; Simone Pfeiffer and Christiane Fischer

giving support through the central office, Michael Owonibi for

managing the central data base, and Markus Fischer, Eduard

Linsenmair, Dominik Hessenmoller, Jens Nieschulze, Daniel

Prati, Ingo Schoning, Francois Buscot, Ernst-Detlef Schulze,

Wolfgang W. Weisser and the late Elisabeth Kalko for their role

in setting up the Biodiversity Exploratories project. We are very

grateful to Boris Buche for his great help with the identification

of beetles and classification of feeding types. We thank Michaela

Bellach for her valuable contribution to the land use data. The

work has been partly funded by the DFG Priority Program 1374

‘‘Infrastructure-Biodiversity-Exploratories’’ (DFG- Ts45/28-

1.). Field work permits were issued by the responsible state

environmental offices of Baden-Wurttemberg, Thuringen, and

Brandenburg (according to § 72 BbgNatSchG). Y. L. was

supported by China Scholarship Council, P. B. was supported the

German Research Foundation (DFG BA 4438/1-1) and C. W.

was supported by the German Federal Ministry of Education and

Research (DLR 01LL0917D). We also would like to thank two

anonymous reviewers for their valuable suggestions and

comments, which were of great help in improving the paper.

References

Altieri MA (1999) The ecological role of biodiversity in agro-

ecosystems. Agric Ecosyst Environ 74:19–31

Aviron S, Burel F, Baudry J, Schermann N (2005) Carabid

assemblages in agricultural landscapes: impacts of habitat

features, landscape context at different spatial scales and

farming intensity. Agric Ecosyst Environ 108:205–217

Barragan F, Moreno CE, Escobar F, Halffter G, Navarrete D

(2011) Negative impacts of human land use on Dung

Beetle functional diversity. PLoS One 6:e17976

Bassa M, Boutin C, Chamorro L, Sans FX (2011) Effects of

farming management and landscape heterogeneity on plant

species composition of Mediterranean field boundaries.

Agric Ecosyst Environ 141:455–460

Batary P, Baldi A, Sze G, Podlussany A, Rozner I, Erd}os S

(2007) Responses of grassland specialist and generalist

beetles to management and landscape complexity. Divers

Distrib 13:196–202

Batary P, Baldi A, Kleijn D, Tscharntke T (2011) Landscape-

moderated biodiversity effects of agri-environmental man-

agement: a meta-analysis. Proc R Soc B 278:1894–1902

Landscape Ecol (2014) 29:529–540 537

123

Bengtsson J, Ahnstrom J, Weibull AC (2005) The effects of

organic agriculture on biodiversity and abundance: a meta-

analysis. J Appl Ecol 42:261–269

Blake S, Foster GN, Eyre MD, Luff ML (1994) Effects of habitat

type and grassland management practices on the body size

distribution of carabid beetles. Pedobiologia 38:502–512

Bluthgen N, Dormann CF, Prati D, Klaus VH, Kleinebecker T,

Holzel N, Alt F, Boch S, Gockel S, Hemp A, Muller J,

Nieschulze J, Renner SC, Schoning I, Schumacher U,

Socher SA, Wells K, Birkhofer K, Buscot F, Oelmann Y,

Rothenwohrer C, Scherber C, Tscharntke T, Weiner CN,

Fischer M, Kalko EKV, Linsenmair KE, Schulze ED,

Weisser WW (2012) A quantitative index of land-use

intensity in grasslands: integrating mowing, grazing and

fertilization. Basic Appl Ecol 13:207–220

Bohme J (2001) Phytophage Kafer und ihre Wirtspflanzen in

Mitteleuropa: ein Kompendium. Bioform, Heroldsberg

Bommarco R, Kleijn D, Potts SG (2013) Ecological intensifi-

cation: harnessing ecosystem services for food security.

Trends Ecol Evol 28:230–238

Borges PAV, Brown VK (2003) Estimating species richness of

arthropods in Azorean pastures: the adequacy of suction

sampling and pitfall trapping. Graellsia 59:7–24

Brook A, Woodcock B, Sinka M, Vanbergen A (2008) Exper-

imental verification of suction sampler capture efficiency

in grasslands of differing vegetation height and structure.

J Appl Ecol 45:1357–1363

Caley MJ, Schluter D (1997) The relationship between local and

regional diversity. Ecology 78:70–80

Chan KMA, Shaw MR, Cameron DR, Underwood EC, Daily

GC (2006) Conservation planning for ecosystem services.

PLoS Biol 4:e379

Clough Y, Kruess A, Kleijn D, Tscharntke T (2005) Spider

diversity in cereal fields: comparing factors at local, land-

scape and regional scales. J Biogeogr 32:2007–2014

Clough Y, Kruess A, Tscharntke T (2007) Organic versus con-

ventional arable farming systems: functional grouping helps

understand staphylinid response. Agric Ecosyst Environ 118:

285–290

Cole LJ, McCracken DI, Nennis P, Downie IS, Griffin AL,

Foster GN, Murphy KJ, Waterhouse T (2002) Relation-

ships between agricultural management and ecological

groups of ground beetles (Coleoptera: Carabidae) on

Scottish farmland. Agric Ecosyst Environ 93:323–336

Colwell RK (2013) EstimateS: statistical estimation of species

richness and shared species from samples. Version 9.

http://purl.oclc.org/estimates Accessed 16 Sep 2013

Concepcion ED, Dıaz M (2011) Field, landscape and regional

effects of farmland management on specialist open-land

birds: does body size matter? Agric Ecosyst Environ 142:

303–310

Concepcion ED, Dıaz M, Baquero RA (2008) Effects of land-

scape complexity on the ecological effectiveness of agri-

environment schemes. Landscape Ecol 23:135–148

Concepcion ED, Dıaz M, Kleijn D, Baldi A, Batary P, Clough Y,

Gabriel D, Herzog F, Holzschuh A, Knop E, Marshall EJP,

Tscharntke T, Verhulst J (2012) Interactive effects of

landscape context constrain the effectiveness of local agri-

environmental management. J Appl Ecol 49:695–705

Dennis P, Young MR, Gordon IJ (1998) Distribution and

abundance of small insects and arachnids in relation to

structural heterogeneity of grazed, indigenous grasslands.

Ecol Entomol 23:253–264

Dıaz S, Lavorel S, de Bello F, Quetier F, Grigulis K, Robson TM

(2007) Incorporating plant functional diversity effects in

ecosystem service assessments. Proc Natl Acad Sci USA

104:20684–20689

Driscoll DA, Weir T (2005) Beetle responses to habitat frag-

mentation depend on ecological traits, habitat condition

and remnant size. Conserv Biol 19:182–194

Duelli P, Obrist MK (2003) Regional biodiversity in an agri-

cultural landscape: the contribution of seminatural habitat

islands. Basic Appl Ecol 4:129–138

Fischer M, Bossdorf O, Gockel S, Hansel F, Hemp A, Hes-

senmoller D, Korte G, Nieschulze J, Pfeiffer S, Prati D,

Renner S, Schoning I, Schumacher U, Wells K, Buscot F,

Kalko EKV, Linsenmair KE, Schulze ED, Weisser WW

(2010) Implementing large-scale and long-term functional

biodiversity research: the biodiversity exploratories. Basic

Appl Ecol 11:473–485

Fournier E, Loreau M (2001) Respective roles of recent hedges

and forest patch remnants in the maintenance of ground-

beetle, Coleoptera: Carabidae. diversity in an agricultural

landscape. Landscape Ecol 16:17–32

Gard TC (1984) Persistence in food webs. In: Levin SA,

Hallam TG (eds) Mathematical Ecology. Springer,

Berlin, pp 208–219

Gardiner MM, Landis DA, Gratton C, Schmidt N, O’Neal M,

Mueller E, Chacon J, Heimpel GE, DiFonzo CD (2009)

Landscape composition influences patterns of native and

exotic lady beetle abundance. Divers Distrib 15:554–564

Grandchamp AC, Bergamini A, Stofer S, Niemela J, Duelli P,

Scheidegger C (2005) The influence of grassland man-

agement on ground beetles, Carabidae, Coleoptera in Swiss

montane meadows. Agric Ecosyst Environ 110:307–317

Greenleaf S, Williams N, Winfree R, Kremen C (2007) Bee

foraging ranges and their relationship to body size. Oeco-

logia 153:589–596

Henle K, Davies KF, Kleyer M, Margules C, Settele J (2004)

Predictors of species sensitivity to fragmentation. Biodi-

vers Conserv 13:207–251

Hoebeke ER, Byers RA, Alonso-Zarazaga MA, Stimmel JF

(2000) Ischnopterapion (Chlorapion) virens (Herbst)

(Coleoptera: Curculionoidea: Brentidae: Apioninae), a

Palearctic clover pest new to North America: recognition

features, distribution, and bionomics. P Entomol Soc Wash

102:151–161

Holt RD (1996) Food webs in space: an island biogeographic

perspective. In: Polis GA, Winemiller KO (eds) Food

webs: integration of patterns and dynamics. Chapman &

Hall, New York, pp 313–323

Hutton SA, Giller PS (2003) The effects of the intensification of

agriculture on northern temperate dung beetle communi-

ties. J Appl Ecol 40:994–1007

Jonsen ID, Fahrig L (1997) Response of generalist and specialist

insect herbivores to landscape spatial structure. Landscape

Ecol 12:85–197

Kennedy TF (1994) The ecology of Bembidion obtusum (Ser.)

(Coleoptera: Carabidae) in winter wheat fields in Ireland.

Biol Environ 94B:33–40

Kleijn D, Baquero RA, Clough Y, Diaz M, De Esteban J, Fer-

nandez F, Gabriel D, Herzog F, Holzschuh A, Johl R, Knop

538 Landscape Ecol (2014) 29:529–540

123

E, Kruess A, Marshall EJ, Steffan-Dewenter I, Tscharntke

T, Verhulst J, West TM, Yela JL (2006) Mixed biodiversity

benefits of agri-environment schemes in five European

countries. Eco Lett 9:243–254

Koch K (1989a) Die Kafer Mitteleuropas. Okologie Bds. 1.

Goecke & Evers, Krefeld

Koch K (1989b) Die Kafer Mitteleuropas. Okologie Bds. 2.

Goecke & Evers, Krefeld

Koch K (1992) Die Kafer Mitteleuropas. Okologie Bds. 3.

Goecke & Evers, Krefeld

Kruess A, Tscharntke T (2002) Contrasting responses of plant

and insect diversity to variation in grazing intensity. Biol

Conserv 106:293–302

Lavorel S, Grigulis K, Lamarque P, Colace MP, Garden D, Girel

J, Pellet G, Douzet R (2011) Using plant functional traits to

understand the landscape distribution of multiple ecosys-

tem services. J Ecol 99:135–147

Legendre P, Gallagher ED (2001) Ecologically meaningful

transformations for ordination of species data. Oecologia

129:271–280

Lovei GL, Magura T (2006) Body size changes in ground beetle

assemblages-a reanalysis of Braun (2004)’s data. Ecol

Entomol 31:411–414

Matson PA, Parton WJ, Power A, Swift M (1997) Agricul-

tural intensification and ecosystem properties. Science

277:504–509

McGarigal K, Cushman SA, Neel MC, Ene E (2002) FRAG-

STATS v3: spatial pattern analysis program for categorical

maps. Computer software program produced by the authors

at the University of Massachusetts, Amherst. http://www.

umass.edu/landeco/research/fragstats/fragstats.html. Acces-

sed Jun 2012

MEA (2005) Millenium ecosystem assessment. Island Press,

Washington

Millan de la Pena N, Butet A, Delettre Y, Morant P, Burel F

(2003) Landscape context and carabid beetles, Coleoptera:

Carabidae. communities of hedgerows in western France.

Agric Ecosyst Environ 94:59–72

Mommertz S, Schauer C, Koster N, Lang A, Filser J (1996) A

comparison of D-Vac suction, fenced and unfenced pitfall

trap sampling of epigeal arthropods in agro-ecosystems.

Ann Zool Fennici 33:117–124

Morris MG, Rispin WE (1988) A beetle fauna of oolitic lime-

stone grassland, and the responses of species to conserva-

tion management by different cutting regimes. Biol

Conserv 43:87–105

Naeem S, Wright JP (2003) Disentangling biodiversity effects

on ecosystem functioning: deriving solutions to a seem-

ingly insurmountable problem. Eco Lett 6:567–579

Nichols E, Spector S, Louzada J, Larsen T, Amezquita S, Favila

ME (2008) Ecological functions and ecosystem services

provided by Scarabaeinae Dung Beetles. Biol Conserv

141:1461–1474

Oksanen J, Guillaume Blanchet F, Kindt R, Legendre P, Min-

chin PR, O’Hara RB, Simpson GL, Solymos P, Stevens

MHH, Wagner H (2012) Vegan: community ecology

package. R package version 2.0–5. http://vegan.r-forge.r-

project.org. Accessed Sept 2012

Pinheiro JC, Bates DM (2000) Mixed-effects models in S and

S-PLUS. Springer Verlag, New York

Pinheiro J, Bates D, DebRoy S, Sarkar D, R Core Team (2013)

nlme: Linear and nonlinear mixed effects models. R

package version 3.1–108. http://cran.r-project.org/web/

packages/nlme/index.html. Accessed Jan 2013

Powell JA (2009) Coleoptera. In: Resh VH, Carde RT (eds)

Encyclopedia of insects. Academic Press, Waltham, p 1132

Purnama Hidayat S, Manuwoto S, Noerdjito WA, Tscharntke T,

Schulze CH (2010) Diversity and body size of dung beetles

attracted to different dung types along a tropical land use

gradient in Sulawesi, Indonesia. J Trop Ecol 26:53–65

Purtauf T, Dauber J, Wolters V (2005a) The response of cara-

bids to landscape simplification is different for different

trophic groups. Oecologia 142:458–464

Purtauf T, Roschewitz I, Dauber J, Thies C, Tscharntke T,

Wolters V (2005b) Landscape context of organic and

conventional farms: influences on carabid beetle diversity.

Agric Ecosyst Environ 108:165–174

R Core Team (2012) R: a language and environment for sta-

tistical Computing. R Foundation for Statistical Comput-

ing, Vienna

Rand TA, Tylianakis JM, Tscharntke T (2006) Spillover edge

effects: the dispersal of agriculturally subsidized insect

natural enemies into adjacent natural habitats. Eco Lett

9:603–614

Ricci C (1986) Food strategy of Tytthaspis sedecimpunctata in

different habitats. In: Hodek I (ed) Ecology of aphidoph-

aga. Academia Press, Prague, pp 119–123

Ricklefs RE (1987) Community diversity: relative roles of local

and regional processes. Science 235:167–171

Sanders D, Entling MH (2011) Large variation of suction

sampling efficiency depending on arthropod groups, spe-

cies traits, and habitat properties. Entomol Exp Appl 138:

234–243

Sanderson M, Byers R, Skinner R, Elwinger G (2003) Growth

and complexity of white clover stolons in response to biotic

and abiotic stress. Crop Sci 43:2197–2205

Shapiro JT, Baldi A (2012) Lost locations and the (ir)repeatability

of ecological studies. Front Ecol Environ 10:235–236

Slade EM, Mann DJ, Villanueva JF, Lewis OT (2007) Experi-

mental evidence for the effects of dung beetle functional

group richness and composition on ecosystem function in a

tropical forest. J Anim Ecol 76:1094–1104

Sutherland AM, Parrella MP (2009) Mycophagy in Coccinelli-

dae: review and synthesis. Biol Control 51:284–293

Symondson W, Sunderland K, Greenstone M (2002) Can gen-

eralist predators be effective biocontrol agents? Annu Rev

Entomol 47:561–594

Theiling KM, Croft B (1988) Pesticide side-effects on arthropod

natural enemies: a database summary. Agric Ecosyst

Environ 21:191–218

Tscharntke T, Kruess A (1999) Habitat fragmentation and bio-

logical control. In: Hawkins B, Cornell H (eds) Theoretical

approaches to biological control. Cambridge University

Press, Cambridge, pp 190–205

Tscharntke T, Klein AM, Kruess A, Steffan-Dewenter I, Thies C

(2005) Landscape perspectives on agricultural intensifica-

tion and biodiversity-ecosystem service management. Eco

Lett 8:857–874

Tscharntke T, Clough Y, Wanger TC, Jackson L, Motzke I,

Perfecto I, Vandermeer J, Whitbread A (2012a) Global

Landscape Ecol (2014) 29:529–540 539

123

food security, biodiversity conservation and the future of

agricultural intensification. Biol Conserv 151:53–59

Tscharntke T, Tylianakis JM, Rand TA, Didham RK, Fahrig L,

Batary P, Bengtsson J, Clough Y, Crist TO, Dormann CF,

Ewers RM, Frund J, Holt RD, Holzschuh A, Klein AM,

Kleijn D, Kremen C, Landis DA, Laurance W, Linden-

mayer D, Scherber C, Sodhi N, Steffan-Dewenter I, Thies

C, van der Putten WH, Westphal C (2012b) Landscape

moderation of biodiversity patterns and processes—eight

hypotheses. Biol Rev 87:661–685

Venables WN, Ripley BD (2002) Modern applied statistics with

S, 4th edn. Springer, New York

Weiher E, Keddy PA (1995) Assembly rules, null models, and

trait dispersion: new questions from old patterns. Oikos

74:159–164

Werling BP, Gratton C (2008) Influence of field margins and

landscape context on ground beetle diversity in Wisconsin,

USA. Potato fields. Agric Ecosyst Environ 128:104–108

Wilson JD, Morris AJ, Arroyo BE, Clark SC, Bradbury RB

(1999) A review of the abundance and diversity of inver-

tebrate and plant foods of granivorous birds in northern

Europe in relation to agricultural change. Agric Ecosyst

Environ 75:13–30

Woltz MJ, Isaacs R, Landis DA (2012) Landscape structure and

habitat management differentially influence insect natural

enemies in an agricultural landscape. Agric Ecosyst Environ

152:40–49

Zuur AF, Ieno EN, Walker NJ, Saveliev AA, Smith GM (2009)

Mixed effects models and extensions in ecology with R.

Springer, New York, pp 386–387

540 Landscape Ecol (2014) 29:529–540

123