DOI: 10.5061/dryad.g79cnp5ns
title: Multiscale drivers of carabid beetle (Coleoptera: Carabidae) assemblages in small European woodlands

description: Aim The spatiotemporal connectivity of forest patches in lowland
 agricultural landscapes and their age matter to explain current
 biodiversity patterns across regional as well as biogeographical extents,
 to the point that it exceeds the contribution of macroclimate for plant
 diversity in the understory of temperate forests. Whether this holds true
 for other taxonomic groups remains largely unknown. Yet, it has important
 consequences for ecosystem functioning and the delivery of ecosystem
 services. Focusing on carabid beetle assemblages, we assessed the relative
 importance of macroclimatic, landscape, and patch attributes on driving
 local species richness (-diversity) and species dissimilarity between
 patches (-diversity). Location Deciduous forest patches in seven regions
 along a 2,100-km long latitudinal gradient across the European temperate
 forest biome, from southern France to central Sweden. Methods We sampled
 221 forest patches in two 55-km landscape windows with contrasting
 management intensities. Carabid beetles were classified into four
 habitat-preference guilds: forest-specialist, forest-generalist,
 eurytopic, and open-habitat species. We quantified the multi-level
 environmental influence using mixed-effects models and variation
 partitioning analysis. Results We found that both - and -diversity were
 primarily determined by macroclimate, acting as a large-scale ecological
 filter on carabid assemblages among regions. Forest-patch conditions,
 including biotic and abiotic heterogeneity as well as patch age (but not
 patch size), increased -diversity of forest species. Landscape management
 intensity weakly influenced -diversity of forest species, but increased
 the number of non-forest species in forest patches. Beta-diversity of
 non-forest species increased with patch heterogeneity and decreased with
 landscape management intensity. Main conclusions Our results highlight the
 leading role of broad macroclimatic gradients over local and landscape
 factors in determining the composition of local carabid communities,
 thereby shedding light on macroecological patterns of arthropod
 assemblages. This study emphasizes the urgent need for preserving ancient
 forest patches embedded in agricultural landscapes, even the small and
 weakly connected ones.
description: All data collection information may be found in the published
 article related to this dataset and its appendices.
 <strong>Study sites</strong> We collected data across
 a total of 221 deciduous forest patches, distributed among seven European
 regions. Regions were distributed along a south-west-to-north-east
 gradient of ca. 2,100 km across the European temperate forest biome (Fig.
 1). In each region, we selected two 5 km 5 km landscape windows differing
 by their degree of landscape permeability (see Valds et al., 2015 for more
 details). The first window was characterized by forest patches embedded in
 an intensively cultivated open field landscape (hereafter open field). The
 second window contained forest patches more or less connected by woody
 corridors (e.g., hedgerows) within a less intensively managed landscape,
 dominated by grasslands and small crop fields (hereafter bocage). A
 detailed and updated list of landscape and macroclimatic variables
 associated with each landscape window can be found in Vanneste et al.
 (2019). For each landscape window, we computed area, perimeter, and age of
 all forest patches using digitized maps (one contemporary map at a scale
 of 1:25,000 and historical maps from the 17th, 18th, 19th, and 20th
 centuries) in a Geographic Information System (GIS; ArcGIS 9.3, ESRI).
 Patches were subsequently distributed among four classes according to
 their area and age: small ( median patch area value for the focal window)
 and recent ( 150 years); large ( median patch area value for the focal
 window) and recent; small and ancient ( 150 years); and large and
 ancient. <strong>Carabid sampling and habitat
 preference </strong>Whenever possible, we selected four forest
 patches (i.e., four repetitions) per level of patch size-age combination
 (n = 4) and per landscape window (n = 14). A perfect balanced design was
 achieved in five out of seven regions, to finally include a total of 221
 forest patches to trap carabid beetles (i.e., 16 forest patches in each
 window, except 14 in the openfield window in eastern Germany and 15 in the
 openfield window in southern Sweden). For this purpose, we used 10-cm
 diameter pitfall traps installed for 14 consecutive days in both spring
 (ca. April) and summer (ca. August) 2013. Traps were filled with 200 mL of
 a 50 % conservative solution of ethylene-glycol and a few drops of
 detergent, and protected from litter and rain fall by aluminum roofs. A
 total of four pairs of traps were disposed in each patch as follows. A
 first pair, consisting of two traps separated by a plastic barrier (100-cm
 long, 18-cm high), was disposed into the inner part of a south-facing edge
 (or, when not possible, first a west-, and then an east-facing edge was
 chosen). This setup was replicated 5-m apart along the same edge. A third
 pair was installed at the barycenter of the forest patch (except in
 eastern Germany, where all traps were located in the edge), and similarly
 replicated (fourth pair). The plastic barrier was always parallel to the
 selected forest edge. To make data comparable among the seven studied
 regions, and because of the latitudinal climatic gradient covered by our
 study, the two sampling sessions carried out in each region started when
 local growing degree hours (GDH ; Graae et al., 2012) reached values of
 ca. 10,000C h and 20,000C h, respectively. Following trap collection,
 carabid beetles were sorted in the lab in a 70% ethanol solution and
 identified to the species level following Jeannel (1941, 1942). Species
 names follow Fauna Europaea (de Jong et al., 2014). Data from all pitfall
 traps of a given patch and from the two trapping sessions were pooled in
 all subsequent statistical analyses. Species were distributed among four
 guilds, according to their habitat preference and using knowledge from the
 scientific literature (Hůrka, 1996; Sadler et al., 2006; Gaublomme et al.,
 2008; Brunicke Trautner, 2009): forest-specialist species, limited to
 stable, mature forest stands; forest-generalist species, occurring in any
 type of forest stand, in ancient as well as recent forest; open-habitat
 species, associated with non-forest habitats such as grasslands and arable
 lands; and eurytopic species, occurring in open habitats and tolerating
 transiently forest habitats. We could not assign only one species (Oodes
 helopioides, n = 1 individual) to any group because of a lack of
 information in the literature.
 <strong>Environmental variables</strong> Three groups
 of explanatory variables (patch, landscape, and macroclimatic variables)
 were derived from field observations, historical archives, or global
 climatic layers, for and around each forest patch using a GIS.
 <strong>Macroclimatic variables</strong> To assess
 the influence of macroclimate on species diversity, we extracted 10
 candidate bioclimatic variables from the WorldClim global database (1-km
 resolution, http://www.worldclim.org), and averaged each variable for each
 forest patch using all 1-km2 pixels intersecting it. Four macroclimatic
 variables were retained for further analyses, based on a principal
 component analysis (PCA; see Valds et al., 2015), namely maximum
 temperature of the warmest month (MaTWm; BIO5); minimum temperature of the
 coldest month (MiTCm; BIO6); precipitation of the wettest month (PWm;
 BIO13); and precipitation of the driest month (PDm; BIO14). The selection
 was made in a way to minimize the correlation between variables and to
 maximize the correlation with the PCA axes. Our variables were correlated
 (Pearsons r) as follow with the PC1 (67.0 % of explained variance) and PC2
 (17.2 %): BIO5 (PC1: r = -0.64; PC2: r = -0.12), BIO6 (PC1: -0.93; PC2:
 0.34), BIO13 (PC1: -0.52; PC2: -0.85), and BIO14 (PC1: -0.94; PC2:
 -0.04). <strong>Landscape variables
 </strong>Landscape variables were computed for five concentric
 doughnut-like buffers of increasing width around each forest patch: 50;
 100; 250; 500; and 1,000 m width. We used Corine Land Cover 2006 (Bttner
 Kosztra, 2007) to map the distribution of woodland, cropland, and
 grassland. We digitized hedgerows from aerial photographs. As proposed by
 Martin Fahrig (2012) and Fahrig (2013), we considered composition-based
 measurements of spatial isolation for each forest patch, by calculating
 the proportion of each cover type and the hedgerow density within each
 buffer. <strong>Patch-scale
 attributes</strong> We included patch area and patch age as
 covariates in our analyses, to account for both the species-area and
 species-time relationship (Rosenzweig, 1995). We took the coefficient of
 variation in elevation values (CVe) within a given forest patch using the
 ASTER Global Digital Elevation Map at 30-m resolution (see Valds et al.,
 2015 for further details), as a proxy for heterogeneity of abiotic
 conditions (incl. microclimate, soil conditions, and light availability)
 (Lenoir et al., 2017; Graae et al., 2018). Finally, we computed a
 dissimilarity index in understory plant species composition within each
 forest patch (i.e., intra-patch b-diversity; see Valds et al., 2015 for
 details on computation), separately for forest plant specialists and
 generalists following distinction criteria as in Valds et al.
 (2015).
description: Exact spatial coordinates of sampling points have been removed
 from the public dataset. They may be available upon direct request to the
 corresponding author.