Distance decay reveals contrasting effects of land-use types on arthropod community homogenization

Distance decay reveals contrasting effects of land-use types on arthropod community homogenization | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Distance decay reveals contrasting effects of land-use types on arthropod community homogenization Orsi Decker, Jorg Muller, Johannes Uhler, Sarah Redlich, Anne Chao, and 9 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4522164/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 15 Jan, 2026 Read the published version in Nature Communications → Version 1 posted You are reading this latest preprint version Abstract Global biodiversity decline with increasing land-use intensity is supposedly linked to the homogenization of species communities across landscapes. However, the contribution of landscape homogenization to insect diversity loss is still largely untested. We compared an indicator for community homogenization, the distance decay slope between four local habitats of increasing land-use intensity, from forests to managed grasslands, to arable lands and to settlements, imbedded in near-natural, agricultural and urban regions. This comparison was based on 12k arthropod species from 400 families, covering an area of 70.500 km 2 . Distance decay – taking rarity and species traits into account - identified grasslands as the most homogenous local land-use type. In contrast, settlements and arable lands showed the most heterogeneous arthropod communities between locations. Large and low-mobility species communities were the most heterogeneous in space, but distance decay patterns were dependent on local land-use. Regional landscape type modified local land-use patterns: near-natural landscapes lowered, while agricultural landscapes increased the impact of homogenisation. Based on our findings we recommend enhanced conservation efforts particularly in grasslands to reverse current homogenization, while settlements and arable lands could be more strongly considered in insect beta-biodiversity heterogenization. Biological sciences/Ecology/Biodiversity Earth and environmental sciences/Ecology/Community ecology land-use distance decay arthropod communities biotic homogenization Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Introduction Human activities shape the diversity and composition of species assemblages both locally and on a regional scale. Excessive habitat modification often favours a few well-adapted species, while specialised and endemic species decline 1 , 2 . With increasing land-use intensification, both biotic heterogenization and homogenization can occur 3 , 4 , and communities become less or more similar across space 5 , 6 . This process can be measured via changes in β-diversity, describing community scale patterns driven by environmental factors 7 , 8 . Socolar et al. 9 hypothesized a bell shaped response of beta-diversity, with increasing values at moderate land-use intensity (heterogenization), but a sharp decline with high land-use intensity (homogenization). Such homogenization effect was demonstrated for increasing mowing intensity in managed grasslands 10 . Although increasing land-use intensity is predicted to drastically increase biotic homogenization 6 , 11 , global studies showed no clear net diversity loss in the Anthropocene 12 , but strong taxa-dependent trends 3 , 13 . An improved understanding of the influence of land-use on beta-diversity of arthropods is critical not only to maintain biodiversity, but also from a functional perspective 14 : homogenisation often degrades ecosystem functions via loosing ‘sets’ of species from the community 15 – 17 . Insects and other arthropods play crucial roles ecosystem functioning 18 – 21 , and despite their high diversity 22 , there is still an ongoing debate on insect declines due to human activities 23 – 25 . An open research question is about the impact of land-use on insect whole-of-community responses. Here, we use a distance decay of pairwise similarity (hereafter ‘distance decay’) approach, because it can quantify the homogenization effect on species communities over large scales and between many localities 26 , 27 . Distance decay patterns are based on two assumptions: 1) areas closer to each other exhibit similar environments, therefore species composition should be more similar; and 2) there is a physical limit to species dispersal distances. Steep distance decay slopes represent less similar or heterogeneous, while flat slopes indicate more similar or homogeneous communities between locations. While global studies help to understand the changes of communities’ in various different ecosystem types, the found changes are more likely to be related to complex environmental and climatic differences 11 , 28 , 29 ; while management-relevant and comparative studies between many land-use types are scarce but see 30 , 31 – 33 . We investigated distance decay in four major habitats of Central Europe at the scale of a large federal state - a scale most relevant for political decisions -, using arthropod assemblages of ~ 12k species from 450 families collected with Malaise traps at 179 plots over an area of 70.500 km 2 . The study design allowed to balance macro-environmental differences, while focusing on land-use 34 . We tested distance decay patterns on a local scale, where arthropods are impacted by their immediate surroundings 35 , while also assessed the outcome on a regional scale, which could impact local processes 36 . Arthropod communities are affected by regional landscapes 37 , 38 , but assemblage variations are explained better by local habitat attributes 39 . Thus, we focused on distance decay on local land-use types. As all our habitats are at least moderately managed, we hypothesized according to McGill et al. (2015) and Socolar et al. (2016) a continuous decline of beta diversity - measured by distance decay-, with increasing land-use intensity. Further, regional land-use could have add-on effects 40 . Therefore, we expected further homogenization effects in agricultural and urban regions compared to near-natural ones. Besides homogenizing communities 10 , high land-use intensity creates environmental filters for species, affecting not only assemblages, but species with specific traits 41 , 42 . We hypothesized large and less mobile species’ communities to be more dissimilar between locations (steep distance decay slope), while small and highly mobile arthropods to occur more evenly across space (flat distance decay slope), given that intensely managed habitats select for these traits 43 , 44 . To consider rare and dominant species, and the inherent incompleteness of insects samples, we applied a framework of community dissimilarity along the Hill numbers 45 standardized by sample coverage 46 , 47 . Rare species often drive observed diversity patterns, therefore we accounted for changes in communities focusing on rare, typical and dominant species separately 48 . Results The sampling resulted in 1432 samples (179 study plots with 8 time periods), which gained 11387 individual arthropod taxonomic groups (BINs, thereafter ‘species’) via metabarcoding analysis. Of all arthropod taxonomic groups, 42% could be assigned to species level. Sample coverage was fluctuating between 0.6 and 0.9 for local land-use types, and between 0.5–0.9 for arthropod trait categories (Supp. Figure 1 ). For land-use types, we therefore standardised sample coverage to 0.8, and for arthropod traits, to 0.7 in subsequent analyses. Number of observed species was highest in the forest systems and lowest in settlements (Supp. Figure 2 ), in accordance with a previous study on raw numbers of observed species (Uhler et al. 57 ). Land-use types Distance decay relationships on the local land-use types differed along Hill-numbers. Forest distance decay slopes were only significantly different from those in managed grasslands, where forest distance decay was stronger than those in grasslands, but not different from arable land or settlement. The distance decay of grasslands consistently had the significantly weakest slopes, independent of species rarity, indicating that species assemblages on grasslands were most similar among the four habitats. Forests, arable lands, and settlements had similar distance decay when focusing on rare (q = 0) and typical (q = 1) species communities. In dominant species communities (q = 2), arable lands had the strongest distance decay pattern, similar to settlements, but significantly stronger than forests and grasslands (Fig. 2 , Supp. I. Table 1). When considering regions surrounding the local land-uses, near-natural regions had a heterogenizing impact on arable lands, settlements and grasslands, but not on forests. Agricultural regions had a further homogenizing impact on grasslands and forests; while urban surroundings had diverse effects. Urban regions had a homogenizing effect on arable lands, settlements and grasslands, but only in rare and typical species communities, and a heterogenizing effect on communities focusing on dominant species. On the contrary, urban regions had a heterogenizing impact on forests, regardless of community type (Fig. 3 ). Arthropod traits On average, forests harboured the largest arthropods (6.21 ± 0.05 mm), and the smallest species occurred in settlements (5.85 ± 0.07 mm). Species in arable lands had the highest mobility score (2.72 ± 0.003) while the other three land-use types were similar in their mobilities (Fig. 4 , Supplementary I. Table 2). Body size did not impact community similarity in most land-use types. Large arthropod communities of typical species (q = 1) in settlements were more homogeneous between locations than medium, but not small species. In arable lands, large arthropod communities of typical species (q = 1) were more homogenous between locations than both medium and small species communities. In forests, arthropod communities including small arthropods were more heterogenous than medium and large species, when focusing on typical (q = 1) and dominant (q = 2) species (Fig. 5 , Supplementary I. Table 3). Distance decay only changed with mobility scores in grasslands and forests. Low-mobility species in grasslands had significantly stronger distance decay than intermediate-, and high-mobility communities, when focusing on rare (q = 0) and typical species (q = 1). In forests, intermediate-mobility species’ communities were more heterogeneous than high-mobility ones, but not different from low-mobility species in rare (q = 0) and typical species (q = 1). In dominant species communities (q = 2) intermediate mobility-species were the most heterogenous (Fig. 6 , Supp. I. Table 4). Discussion Global distance decay studies help to understand the changes of communities’ response to complex environmental differences, but studies on a management-relevant spatial resolution are scarce but see 30 , 31 . Combining distance decay studies from continental and intercontinental datasets in meta-analyses is informative see 28 , but could be problematic: it is widely shown that distance decay depend not only on spatial scale 67 – 69 , but on study extent and design 70 . Regional and local diversity assist in conservation planning 9 , but study designs of available data often do not allow for testing diversity on the appropriate scale 71 . Here, we compare different land-use types on the same spatial scale within a large federal state, where the same political decisions apply. This provides a standardised dataset; and a background in which land-use intensity drive arthropod communities, while biogeographic patterns play a lesser role. Besides the design, another strength of the study is the inclusion of most arthropod taxa, which provides a better understanding of whole community responses see also 72 . Single-taxonomic group approaches to distance decay are highly valuable 73 , 74 , but are regularly biased towards specific characteristics of the studied group when comparing different environments. Our study extends the findings of Gossner et al. (2016), which showed increasingly similar arthropod communities with increasing grassland management intensity to other land-use types. However, we did not find evidence for a continuation of homogenization of communities along the gradient of land-use categories with increasing intensity. Instead, species communities were only highly homogenized between locations in grasslands, but with a mediating impact by the surrounding near-natural region. Contrary to grasslands, the most modified land-use type, arable lands and settlements harboured the most heterogenized arthropod communities between locations. While traditionally managed grasslands are the most species-rich habitat types for vascular plants and insects in Europe 75 , 76 , low-input methods are widely replaced by more intensive management practices 77 , 78 . The high nitrogen- phosphorus-potassium (NPK) fertilizer inputs 79 , 80 , frequent mowing and intensive grazing 10 , 81 result in simplified and floristically homogeneous grasslands 82 . This shapes insect communities to be adapted to uniformly managed grasslands, lowering both local diversity and community differences between locations 38 , 83 . In contrast to grasslands, intensively modified arable lands and settlements harboured the most different set of arthropods between locations. Although agricultural practices change the local environment for most species 84 – 86 , these systems can offer a diverse habitat mosaic in time and space. Series of arable lands in a given area can be composed of a variety of different crop plants, which makes land characteristics highly diverse within a small area 87 . The diversity of crops creates a locally unique sets of arthropod communities associated with the different plants grown. Indeed, crop field size in Bavaria, where the study was conducted, can be described as small- to medium-scale ~ 1.6 ha arable field size, 88 compared to the German average ~ 5 ha, 89 . This is reflected in our results, and in accordance with recent studies showing that high crop heterogeneity and small crop field size can have a greater benefit to biodiversity than semi-natural land cover 90 , 91 . However, Uhler et al. (2021) found the lowest insect α-diversity in arable lands, where we found the strongest distance decay. This pattern could be a result of increased habitat heterogeneity between the compared patches of arable lands, combined with decreased average species occupancy: only a few number of high-occupancy species benefit from each arable land patch (species specialised on a given grown plant or pest species), decreasing α-, but increasing β-diversity 3 . Besides agriculture, urban expansion is a major cause of habitat loss for many species 92 , 93 but, increasing attention is given to the amount of dense mosaic of habitat types within urban areas for species 94 , 95 . Similarly to our finding for beta diversity, Uhler et al. 57 reported high alpha diversity of arthropod species richness in settlements, - despite low biomass - especially in settlements within near-natural regions. On the regional scale, near-natural and agricultural regions had a clear mitigating, or worsening homogenisation impact respectively. Near-natural regional landscapes could act as insurance for wildlife 96 according to the ‘landscape-moderated insurance hypothesis’ 97 . Natural patches, such as semi-natural forests provide a more stable environment, compared to managed grassland or arable land with frequent rotations between harvest and growth periods. When located in close proximity to each other, species can move between the less stable local land-use type (arable land or grassland) and the surrounding near-natural areas to escape the disturbance periods, or to recolonise from there 98 . This process increases species pools locally, therefore can increase community heterogeneity between locations 99 . As opposed to near-natural regions, surrounded by agricultural areas weakened distance decay at grassland and forest local land-use types. This detrimental impact of agricultural landscapes surrounding natural and semi-natural local habitats 38 , 100 decreased β-diversity between our less intensely used local land-use types. On the other hand, urban regions had the strongest heterogenizing impact on forest local land-use types. This could imply that urban environments isolated forests 101 , and arthropod species became limited in their dispersal, creating unique communities within each individual forest surrounded by urban landscapes. However, because this strong isolating impact by urban regions was not apparent in any other local land-use types in our study, the more likely explanation is that urban regions include highly diverse structures, which further heterogenized forest communities between locations 102 . Urban features add diverse hospitable habitats for otherwise forest-inhabiting arthropods, such as small hobby farms, private gardens, riparian corridors and even small remnant vegetation 103 , 104 . Such contrasting habitat types could act as complementary or supplementary environments explained by the ‘cross-habitat spillover hypothesis’ 97 , where species flow between land-use types depending on their temporal or spatial requirements and local habitat characteristics. Again, this could enhance local species pools, and therefore increase β-diversity between local forest locations. Land-use not only shapes taxonomic communities, but also acts as an environmental filter for specific traits 41 . Large bodied arthropods require larger patches of suitable habitat 105 , 106 , and low disturbance regimes 107 – 109 . This is reflected in our results, where forests harboured communities with the largest arthropods, while the smallest assemblages were found in the most modified land-use types, in settlements. The most mobile arthropods occurred in arable lands, where species have to adapt to the frequent cropping and replanting cycles with high mobility to escape and recolonise during and post-disturbance 110 – 112 . Distance decay patterns were mostly not impacted by body size, implying that land-use affects arthropod communities stronger than body size impacts community similarity within land-use types. However, large arthropods within typical species communities in the most modified land-use types (settlement and arable land) were more similar between locations than communities including smaller species. Studies on urbanisation gradients showed that flying insect communities are homogenised and shift to larger, more mobile communities 113 , 114 , which we can extend to all arthropods in heavily modified land-use types in the current study. Typical (or common) species communities expressing a large body size became homogenised within settlement and arable land systems, the most modified land-use types in our study. It is not clear why this pattern is only present within typical species communities, but depending on local species pools, some species could become more widespread than others 15 , 115 driven by processes typical to modified land-uses 43 . Forests on the other hand exhibit high structural diversity and therefore various microhabitats, which could have resulted in a highly heterogeneous species community including small arthropods. Body size can be linked to many life strategies and behaviours adapted to local habitats 116 , 117 , therefore arthropods in forests might track microenvironmental differences, rather than distance itself 29 ; or community assembly might be more stochastic for small species, making communities dissimilar between locations 118 . In grasslands, low-mobility species communities (rare and typical) were the most heterogenous, which was expected, given the disadvantage of low mobility in frequently mowed land-use types 43 , 119 . Highly mobile species are capable of escaping the disturbance and rapidly recolonizing after, while low-mobility species must find local refugia, therefore populations might become very patchy, strengthening distance decay. However, dominant species did not exhibit this pattern, implying that dominant species with various mobilities are homogenized between locations. As our major finding is the high homogenization of arthropod communities in grasslands of Central Europe, it highlights the need for improvement in Europe’s conservation actions e.g. 120 : while broad policies are needed for general directions, adaptive local management decisions impact diversity more profoundly 77 , 121 . Our studied grasslands probably reflect the overarching problem of the long-term and mostly uniform management in Europe, which led to homogenous species communities. It is important to note that the current study did not include truly natural habitat types, and all studied plots were managed to some degree, and there was no unmanaged natural baseline included in our study, which also reflects the lack of European natural habitats 122 , 123 . This urges the authorities to focus not only on the improvement of local habitat quality, but also on the improvement of habitat heterogeneity between habitat patches to boost regional diversity. Intense management practices in grasslands should reduce by favouring extensive management practices (reduction of fertilisation, less intensive mowing), improving seed banks, or optimising grazing and cutting regimes 124 – 126 . Conclusions Our study, to our knowledge, is the first to directly compare distance decay using arthropod communities including all taxa as a response to the four major terrestrial land-use types in Europe within the same ecoregion. The strong distance decay in settlements and arable lands showed that these land-use types have a higher-than-expected heterogeneity between locations, contributing to overall gamma-diversity. Thus, we found no strong evidence for broad-scale biotic homogenisation driven by anthropogenetic land-use, except for managed grasslands. The finding highlights the fact, that however natural habitat types have been mostly lost in the Anthropocene, and the process of biodiversity decline is ongoing, anthropogenic habitat types can still create heterogenous communities on a regional scale, mainly driven by habitat mosaics. This effect however disappears on a global scale, where net species diversity is declining. Management intensification on grasslands still continues, which could lower the diversity of communities even more, while degrading multiple ecosystem services in the future. Permanent grasslands cover 13% of the area of the European Union (Eurostat, www.ec.europa.eu/eurostat ) and still resembles a semi-natural habitat for many native species if managed extensively. Therefore, it is important to call for a change of management in order to halt the further grassland community homogenisation. Methods Study design The study was conducted in Central Europe in 2019 as part of the LandKlif project: https://www.landklif.biozentrum.uni-wuerzburg.de . 60 regions (each 5.8 x 5.8 km) were selected in Bavaria with land-use characterizations according to Corine land cover data 34 . Each region was classified into three regional land-use types based on the Corine land cover assessments: near-natural, agricultural and urban (to be called ‘regions’). In each region, on a smaller scale, local land-use types were further determined based on the most dominant local land-use type based on the dominant local land-use and vegetation on a 0.5 ha resolution: forest (n = 55), grassland (n = 45), arable land (n = 44) and settlement (n = 35). In each regional landscape type, three study plots were set up, in a combination of three different local land-use types, out of the four possible land-use types. This resulted in 179 study plots, covering a ~ 1000 m elevational gradient, mean annual temperatures ranging from 5 to 10.3°C, and precipitation from 550 and 1961 mm, distributed in the whole state of Bavaria, Germany for details see 34 . All plots were set up on a 3 m × 30 m herbaceous vegetation in close proximity to the studied land-use type. This was done to standardize traps in the four habitat types; while, it possibly introduced some heterogeneity by establishing a small grassy area within forests, arable lands and settlements. However, we do not expect this to affect our distance decay study, as the local land-use type should always dominate the habitats, and drive arthropod species occurrence. Forest plots were located in a variety of forest types, but near beech stands, at least 50 m from the edge, and in an opened, sunny position (e.g., forest glade). Managed grassland plots were established as part of larger managed permanent grasslands, as far as possible from other land-use types, at least 50 m. Arable land plots were set up adjacent to various field crops. Settlement plots were established in green areas with at least 50 m away from public roads, and did not include forest patches. Sample collection Malaise traps were used to capture invertebrates with the following dimensions: height front: 0.90 m; height rear: 0.60 m; length: 1.60 m, with 80% ethanol as preserving solution. As with any sampling method, using only Malaise traps for arthropod sampling introduces a bias in sampled taxa and not capturing all arthropod taxa equally 49 . Nevertheless, this method reliably represents most groups of terrestrial arthropods, including flying and ground-dwelling groups 50 , providing by far more comprehensive data than window traps or pitfall traps. Traps were active between April or May and August 2019, with a fortnightly collection for 4 months, resulting in 8 sampling periods in total. Timing of sample collections varied due to weather and snow cover differences between locations. Samples were then split in small and large species by sieving them through an 8mm sieve to control for differences in biomass and to increase the identification of rare and small species 51 , 52 . Species were identified using CO1-5P (mitochondrial cytochrome oxidase 1), and DNA metabarcoding, including the bioinformatics pipeline was done following the methods of Hausmann 53 . Taxonomic groups (species) were separated with the Barcode Index Number (BIN) system defining genetic units 54 , and identified using the BOLD platform www.boldsystems.org , 55 . Single reads of individual BINs were removed from the raw dataset assuming sequencing errors. Due to incomplete libraries the allocation to BIN units is a challenge, particularly for groups harbouring "dark taxa" such as dipterans, hymenopterans and hemipterans. For ecological analyses, the goal is to assign the sequences to units representing the solution of species themselves and to derive ecological properties from the sequence information. For this purpose, we followed the procedure described in Müller et al. 56 , assigning the sequences to the next existing BIN from the study region reporting the genetic distance. Thus, BINs with a distance > 3% are seen as identified species, while for those with a distance > 3% function as “genetic morpho-species” in the ecological analyses. In this way, all sequences across all lineages receive a reasonably balanced assignment to taxonomic units and information on ecological properties, as mobility or body size class could be extracted with high confidence because many of them are conserved on genus or family level. For simplicity we use the term species for our BINs in the following. For more details about the metabarcoding process, see Uhler et al 57 . Details of the metabarcoding can be found in Uhler, et al. 57 . Statistical analysis We used detection frequency in all samples instead of reads from the sequenced data, which has issues due to sequencing errors 58 . This method should also control for the fact that arthropod populations can be highly patchy in distribution both temporally and spatially, therefore abundant data could lead to species being over-, or underestimated in a given sample community. Frequency data ranged between 0 and 16, as we had samples from 8 collection events from two subsamples based on body size. By using frequency, we consider species captured at all sampling periods (captured 16 out of 16 times) as species with high relative abundance. Besides the temporal replication, the inclusion of both fractions (‘big’ and ‘small’) introduces more replicates from the same sampling period. When estimating diversity and assemblage similarity metrics, it is important for assemblages (samples) to be statistically comparable across all study sites, which requires a standardised sample coverage-based analysis 59 . Sample coverage and species detectability may differ between land-use types, therefore we used coverage-based indices calculated by the package iNEXT.beta3D 47 . The method estimates sample coverage based on singletons presented in the data for all assemblages, which enables us to compare samples from the four different land-use types without significant detection bias in our samples. All statistical analysis was done using R statistical software, version 4.3.1 60 .We had three components of the statistical analysis: i ) Establishment of community similarity matrices along the Hill-numbers 45 , where species are weighed differently based on their detection frequency, giving them a ‘rarity’ variable (see below). Then, ii) Creation of trait-based community matrices, where species are categorized into trait groups according to their body size (large, medium, and small) and dispersal ability (high, intermediate, and low-mobility) using the existing literature and expert knowledge. Lastly, iii ) Analysis of distance-decay patterns: model distance-decay relationships in the four land-use types according to their rarity and traits. i) Rarity Species matrices based on their rarity were created using their overall frequency in the dataset. This variable is purely based on detection frequency within a community, and did not take their functional contribution or geographical range into account 61 . All categories refer to the sample-scale rarity, i.e., local rare, local typical and local dominant species within the sampled community following 62 . Based on the framework of effective number of species, the Hill numbers (Hill 1973, Chao et al. 2014), we can shift the focus of diversity from rare species to dominant species by adjusting the diversity order q when creating similarity matrices. Hill number of q = 0 (Sørensen index) reduces to species richness which is more sensitive to rare species; Hill number of q = 1 (Horn index) focuses on common/typical species; Hill number of q = 2 (Morista-Horn index) heavily weighs the dominant or very abundant species. However Hill numbers were developed for abundance data, this approach can be used appropriately for DNA-derived frequency and incidence data 63 , 64 . We constructed community matrices along Hill-numbers using standardised coverage-based indices (Sørensen, Horn and Morista-Horn) for each land-use type, body size and mobility. Using the above-described similarity distances, we created community similarity matrixes for rarity (q = 0, q = 1, q = 2) within the four land-use types, resulting in 12 subset matrices. ii) Traits We used body size and mobility of 450 arthropod families from classes Arachnida, Chilopoda, Collembola, Diplopoda, Hexanauplia, Insecta, Malacostraca. Traits were assigned at family level (averaged where possible) using existing data bases, expert opinions and taxonomic keys (sources can be found in Supplementary Information II, available at https://figshare.com/s/fda6129fe1cbe0316341 ). Body size classes were established based on the distribution of the data: we considered arthropods as “small” if body size was equal to or less than 2.7 mm (n = 3517), “intermediate” between 2.8 mm and 7 mm (n = 3493), and “large” equal to or above 7 mm (n = 3578). 91% of BINs were classified for body size. We used mobility as a category, which was determined by experts: “low” (n = 1255), “medium” (n = 2516) and “high” (n = 6840) (for detailed classifications, see https://figshare.com/s/fda6129fe1cbe0316341 Supplementary Information II). Average body sizes and mobility scores were calculated using the package FD 65 as community weighted means for each land-use type. Pairwise differences were tested with an analysis of variance and Tukey’s post-hoc test. iii) Analysis Distance decay is defined by species community similarities (or dissimilarities) between two given study sites (or samples) and physical distance between these two sites, pairing up all studied samples and locations. This way, we created two matrices for every rarity and trait group: a community similarity and a physical distance matrix (km), where the x- and the y-axes are the paired sampling sites, and the cells are the community and physical distances between them. Community similarity matrices were created according to rarity (detailed above), and traits. BINs belonging to trait-classified families were assigned to a trait group, then different matrices were created including only specific trait groups according to body size and mobility (3 matrices each). Then, all trait groups were reassigned to the land-use types they occurred in, resulting in trait group subsets for each land-use type (3 body size matrices and 3 mobility matrices for each land-use, 24 subset matrices in total). All groups had their corresponding rarity submatrices, q = 0, q = 1 and q = 2. Slopes of distance decay relationships were compared between land-use types, mobility, and body size classes. Given that community similarity matrices were derived from sample coverage-based diversity metrics according to Hill-numbers, distance decay relationships were compared with the package Simba 66 , which accepts a variety of similarity matrices instead of creating one based on fixed indices (such as Sorensen or Jaccard). For significance tests, we used the function ‘diffslope’, which compares slopes of different distance decay regression lines directly with a randomization approach comparing our datasets instead of a bootstrapping approach based on a simulated dataset by model parameters. where we used Bonferroni-Hochberg correction for multiple comparisons between the four habitat types. Furthermore, we constructed linear regression models and extracted the distance decay slopes for better visualization. Main outputs from linear regressions can be found in the Supplementary Information I. (Supplementary I. Tables 1 and 4). To test whether regional landscape types change the general patterns found within local land-use types, we compared slopes of overall land-use types and specific land-use types surrounded by each regional landscape (urban, agricultural or natural). This was done by deducting the absolute value of the general slope of local land-use (including all landscapes) from the absolute value of the slope of the same local land-use, but imbedded in a specific landscape type. This way positive values imply an increased heterogeneity (more negative distance decay slope) of a given regional landscape type compared to the general slope, without considering the surrounding regional landscape type. Data availability Arthropod community data, trait data (body size and mobility) and the used R code are available via the Figshare repository, at https://figshare.com/s/fda6129fe1cbe0316341 . Declarations Acknowledgements We would like to thank all landowners who allowed us to conduct our experiments on their land. We acknowledge the support of all students and technical staff in the field and laboratory. We thank Torsten Hothorn and Oliver Mitesser for statistical support, and Caryl Benjamin, Rebekka Riebl, Sandra Rojas-Botero, Lars Uphus for fieldwork and technical support. This study was conducted within the framework of the joint project LandKlif (https://www.landklif.biozentrum.uni-wuerzburg.de/) funded by the Bavarian Ministry of Science and Arts via the Bavarian Climate Research Network (bayklif). Open Access funding enabled and organized by Projekt DEAL. Author contributions Johannes Uhler: Investigation (equal). Sarah Redlich: Conceptualization (equal); investigation (equal); project administration (equal); review (equal). Jie Zhang: Conceptualization (equal). Anne Chao: analysis (equal), review (equal). Ingolf Steffan-Dewenter: Project administration (equal); review (equal). Cynthia Tobisch: review (equal). Jörg Ewald: review (equal). Jana Englmeier: review (equal). Ute Fricke: review (equal). Cristina Ganuza: review (equal). Maria Haensel: review (equal). Jörg Müller: Conceptualization (equal); formal analysis (equal); methodology (equal); project administration (equal); supervision (equal); review and editing (equal). Orsi Decker: Conceptualization (equal), analysis (lead); writing – original draft (lead); writing – review and editing (lead). Data availability statement: The datasets generated during and analyzed during the current study are available in the Figshare repository (see Methods). The authors declare no conflict of interest. References McKinney, M. L. & Lockwood, J. L. Biotic homogenization: a few winners replacing many losers in the next mass extinction. Trends in Ecology & Evolution 14 , 450-453, doi:https://doi.org/10.1016/S0169-5347(99)01679-1 (1999). 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of Würzburg","correspondingAuthor":false,"prefix":"","firstName":"Jorg","middleName":"","lastName":"Muller","suffix":""},{"id":313006066,"identity":"293ab206-4a9e-47f2-990b-c116e0bdb571","order_by":2,"name":"Johannes Uhler","email":"","orcid":"","institution":"University of Wuerzburg","correspondingAuthor":false,"prefix":"","firstName":"Johannes","middleName":"","lastName":"Uhler","suffix":""},{"id":313006067,"identity":"48ca071e-8e39-4cd5-a0eb-c45a88481fe8","order_by":3,"name":"Sarah Redlich","email":"","orcid":"https://orcid.org/0000-0001-5609-0576","institution":"University of Wuerzburg","correspondingAuthor":false,"prefix":"","firstName":"Sarah","middleName":"","lastName":"Redlich","suffix":""},{"id":313006068,"identity":"fd19156a-c4a1-491c-be98-cf47744ab450","order_by":4,"name":"Anne Chao","email":"","orcid":"","institution":"National Tsing Hua University","correspondingAuthor":false,"prefix":"","firstName":"Anne","middleName":"","lastName":"Chao","suffix":""},{"id":313006069,"identity":"62bd0b93-22c1-4ba1-a27b-4d263a03a73d","order_by":5,"name":"Ingolf Steffan-Dewenter","email":"","orcid":"","institution":"University of Würzburg","correspondingAuthor":false,"prefix":"","firstName":"Ingolf","middleName":"","lastName":"Steffan-Dewenter","suffix":""},{"id":313006070,"identity":"7a4b9f83-bd3e-4060-9469-f2284d8df542","order_by":6,"name":"Cynthia Tobisch","email":"","orcid":"","institution":"Weihenstephan-Triesdorf University of Applied Sciences and Technical University of Munich","correspondingAuthor":false,"prefix":"","firstName":"Cynthia","middleName":"","lastName":"Tobisch","suffix":""},{"id":313006071,"identity":"606c486f-2948-4168-914e-083c12bb37cf","order_by":7,"name":"Jörg Ewald","email":"","orcid":"https://orcid.org/0000-0002-2758-9324","institution":"University of Applied Sciences","correspondingAuthor":false,"prefix":"","firstName":"Jörg","middleName":"","lastName":"Ewald","suffix":""},{"id":313006072,"identity":"9222291a-44b0-458d-9885-b6076ab0130a","order_by":8,"name":"Jana Englmeier","email":"","orcid":"","institution":"Julius-Maximilians-Universität Würzburg","correspondingAuthor":false,"prefix":"","firstName":"Jana","middleName":"","lastName":"Englmeier","suffix":""},{"id":313006073,"identity":"70c7e117-c00f-4d51-b67e-d7ced72ffe8f","order_by":9,"name":"Ute Fricke","email":"","orcid":"https://orcid.org/0000-0002-5284-4518","institution":"University of Wuerzburg","correspondingAuthor":false,"prefix":"","firstName":"Ute","middleName":"","lastName":"Fricke","suffix":""},{"id":313006074,"identity":"5d3ae93d-42f1-4c37-8225-d54eae751550","order_by":10,"name":"Cristina Ganuza","email":"","orcid":"https://orcid.org/0000-0002-4197-1829","institution":"University of Würzburg","correspondingAuthor":false,"prefix":"","firstName":"Cristina","middleName":"","lastName":"Ganuza","suffix":""},{"id":313006075,"identity":"dd432eef-060c-45ec-91bd-20b8c3457853","order_by":11,"name":"Maria Haensel","email":"","orcid":"https://orcid.org/0000-0003-4530-8968","institution":"University of Bayreuth","correspondingAuthor":false,"prefix":"","firstName":"Maria","middleName":"","lastName":"Haensel","suffix":""},{"id":313006076,"identity":"16b7159e-11e5-4789-9334-49317eef396c","order_by":12,"name":"Jérôme Morinière","email":"","orcid":"","institution":"Advanced Identification Methods GmbH","correspondingAuthor":false,"prefix":"","firstName":"Jérôme","middleName":"","lastName":"Morinière","suffix":""},{"id":313006077,"identity":"25032c2f-570b-418c-a37e-f1f13c378f3f","order_by":13,"name":"Jie Zhang","email":"","orcid":"https://orcid.org/0000-0003-2599-5983","institution":"University of Würzburg","correspondingAuthor":false,"prefix":"","firstName":"Jie","middleName":"","lastName":"Zhang","suffix":""}],"badges":[],"createdAt":"2024-06-03 13:41:06","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4522164/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4522164/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41467-025-67612-9","type":"published","date":"2026-01-15T05:00:00+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":60807536,"identity":"409f0c06-da4e-4028-8a34-167327b6fc22","added_by":"auto","created_at":"2024-07-22 10:16:46","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":207536,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFigure 0\u003c/strong\u003e. Graphical abstract showing the focus of the study: distance decay in arthropod communities. Based on the homogenisation hypothesis by intense land-use, communities should be more similar with intense local land-use (shown in dashed lines); however, we found that the most intensively used lands (settlement = grey and arable land = golden) heterogenized arthropod communities- when compared to forests (green) and managed grasslands (purple).\u003c/p\u003e","description":"","filename":"image1.png","url":"https://assets-eu.researchsquare.com/files/rs-4522164/v1/fe30c5ad827b7dfeb3dec6c3.png"},{"id":60807153,"identity":"508ca72f-808f-42fe-92de-c16393cbefe7","added_by":"auto","created_at":"2024-07-22 10:08:45","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":620285,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFigure 1\u003c/strong\u003e. (a) Study area in Southern Germany, Bavaria, where (b) 60 regions were chosen with three landscape types: urban (grey), agricultural (yellow) and near-natural (light green). Within each region, further study plots (c) were established based on the local land-use types. In total, 179 study plots were established in four local land-use types: forest (forest green), managed grassland (purple), arable land (golden), and settlement (dark grey) surrounded by contrasting regional landscapes.\u003c/p\u003e","description":"","filename":"image2.png","url":"https://assets-eu.researchsquare.com/files/rs-4522164/v1/99d44012d27afe82168a4989.png"},{"id":60807535,"identity":"2d302f42-496b-4f46-b335-25f23c9265cc","added_by":"auto","created_at":"2024-07-22 10:16:45","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":426087,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFigure 2. \u003c/strong\u003e(a) The figure shows distance decay in the four local land-use types: forest (forest green), grassland (purple), arable land (golden), and settlement (grey) according to Hill-numbers. Sample coverage=0.8. (b) The mean differences in slope steepness ± SE are shown with a dot over the Hill gradient: rare species - q = 0 (Sørensen index), typical species - q = 1 (Horn index) and dominant species - q = 2 (Morista-Horn index) from left to right on the panel. Steeper slopes with more negative values (to the right) indicate more heterogenous communities with less similarity between locations.\u003c/p\u003e","description":"","filename":"image3.png","url":"https://assets-eu.researchsquare.com/files/rs-4522164/v1/a6063533ca7d9c5a4e891bee.png"},{"id":60807159,"identity":"fc824d3a-4e5b-4146-b5cd-64711ed3fd00","added_by":"auto","created_at":"2024-07-22 10:08:46","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":86044,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFigure 3.\u003c/strong\u003e Changes of distance decay slopes are shown calculated by using the difference between the distance decay slope of local land-use types without considering surrounding regions and the slope of local land-use types imbedded in a given region: near-natural (moss green), agricultural (brown) or urban (sky blue). Panels show communities over the Hill-numbers: rare species - q = 0 (Sørensen index), typical species - q = 1 (Horn index) and dominant species - q = 2 (Morista-Horn index). Bands in the positive area mean less community homogenization in a given region compared to all samples, and bands in the negative area mean further homogenization in a given region.\u003c/p\u003e","description":"","filename":"image4.png","url":"https://assets-eu.researchsquare.com/files/rs-4522164/v1/552b7a25cce80f5b78ca1fd4.png"},{"id":60808003,"identity":"57370f11-deff-4326-92e6-f1b77750c4b7","added_by":"auto","created_at":"2024-07-22 10:24:46","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":85153,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFigure 4\u003c/strong\u003e. Graphs showing community weighed a) body size means ± SE and b) mobility score means ± SE for each land-use type based on 179 study plots and ~12k arthropod species. Body size classes are 0-2.7 mm (small) \u0026lt; 2.8-7 mm (intermediate) \u0026lt; bigger than 7 mm (large). Mobility score indicates 1 = low, 2 = medium, and 3 = high.\u003c/p\u003e","description":"","filename":"image5.png","url":"https://assets-eu.researchsquare.com/files/rs-4522164/v1/583f96ccdfbfdb8683d3e858.png"},{"id":60807157,"identity":"2020f494-7d55-46df-9bb7-b08b7fb2ba2f","added_by":"auto","created_at":"2024-07-22 10:08:45","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":162584,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFigure 5.\u003c/strong\u003e The mean ± SE slopes of distance decay in insect communities focusing on species of different body sizes (lime = small, red = medium, brick = large) in the four local land-use types. Significant differences are shown with different letters according to the SIMBA analysis. Panels from left to right show communities over the Hill-numbers: rare species - q = 0 (Sørensen index), typical species - q = 1 (Horn index) and dominant species - q = 2 (Morista-Horn index). Steeper slopes with more negative values indicate less community similarity between locations.\u003c/p\u003e","description":"","filename":"image6.png","url":"https://assets-eu.researchsquare.com/files/rs-4522164/v1/91fc2aad91b2fe21bd03edf7.png"},{"id":60807161,"identity":"e91a807d-4f1c-44b5-89c4-05b4f48c9da4","added_by":"auto","created_at":"2024-07-22 10:08:47","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":155600,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFigure 6.\u003c/strong\u003e The mean ± SE slopes of distance decay in insect communities focusing on species of different mobility scores (navy blue = low mobility, violet = intermediate mobility, turquoise= high mobility) in the four local land-use types. Significant differences are shown with different letters according to the SIMBA analysis. Panels from left to right show communities over the Hill-numbers: rare species - q = 0 (Sørensen index), typical species - q = 1 (Horn index) and dominant species - q = 2 (Morista-Horn index). Steeper slopes with more negative values indicate less community similarity between locations.\u003c/p\u003e","description":"","filename":"image7.png","url":"https://assets-eu.researchsquare.com/files/rs-4522164/v1/f318fb0c75925560e18d5367.png"},{"id":100765520,"identity":"e4bdea2a-6e52-43a6-b02c-b62ff0ce2308","added_by":"auto","created_at":"2026-01-21 08:45:45","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2530320,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4522164/v1/a5997e0b-cbc2-46f2-8f11-42dfc777e630.pdf"},{"id":60807160,"identity":"fe09ecf0-0048-4171-8134-abf35e65e90e","added_by":"auto","created_at":"2024-07-22 10:08:46","extension":"pdf","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":594312,"visible":true,"origin":"","legend":"","description":"","filename":"Supp.InfoI.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4522164/v1/8fb5780dce787d7e6da3b795.pdf"}],"financialInterests":"There is \u003cb\u003eNO\u003c/b\u003e Competing Interest.","formattedTitle":"Distance decay reveals contrasting effects of land-use types on arthropod community homogenization","fulltext":[{"header":"Introduction","content":"\u003cp\u003eHuman activities shape the diversity and composition of species assemblages both locally and on a regional scale. Excessive habitat modification often favours a few well-adapted species, while specialised and endemic species decline \u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e,\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e. With increasing land-use intensification, both biotic heterogenization and homogenization can occur \u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e,\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e, and communities become less or more similar across space \u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e,\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e. This process can be measured via changes in β-diversity, describing community scale patterns driven by environmental factors \u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e,\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e. Socolar et al. \u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e hypothesized a bell shaped response of beta-diversity, with increasing values at moderate land-use intensity (heterogenization), but a sharp decline with high land-use intensity (homogenization). Such homogenization effect was demonstrated for increasing mowing intensity in managed grasslands \u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e. Although increasing land-use intensity is predicted to drastically increase biotic homogenization \u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e,\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e, global studies showed no clear net diversity loss in the Anthropocene \u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e, but strong taxa-dependent trends \u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e,\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eAn improved understanding of the influence of land-use on beta-diversity of arthropods is critical not only to maintain biodiversity, but also from a functional perspective \u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e: homogenisation often degrades ecosystem functions via loosing \u0026lsquo;sets\u0026rsquo; of species from the community \u003csup\u003e\u003cspan additionalcitationids=\"CR16\" citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e. Insects and other arthropods play crucial roles ecosystem functioning \u003csup\u003e\u003cspan additionalcitationids=\"CR19 CR20\" citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e, and despite their high diversity \u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e, there is still an ongoing debate on insect declines due to human activities \u003csup\u003e\u003cspan additionalcitationids=\"CR24\" citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e. An open research question is about the impact of land-use on insect whole-of-community responses.\u003c/p\u003e \u003cp\u003eHere, we use a distance decay of pairwise similarity (hereafter \u0026lsquo;distance decay\u0026rsquo;) approach, because it can quantify the homogenization effect on species communities over large scales and between many localities \u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e,\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e. Distance decay patterns are based on two assumptions: 1) areas closer to each other exhibit similar environments, therefore species composition should be more similar; and 2) there is a physical limit to species dispersal distances. Steep distance decay slopes represent less similar or heterogeneous, while flat slopes indicate more similar or homogeneous communities between locations. While global studies help to understand the changes of communities\u0026rsquo; in various different ecosystem types, the found changes are more likely to be related to complex environmental and climatic differences \u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e,\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e,\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e; while management-relevant and comparative studies between many land-use types are scarce but see \u003csup\u003e\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e,\u003cspan additionalcitationids=\"CR32\" citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eWe investigated distance decay in four major habitats of Central Europe at the scale of a large federal state - a scale most relevant for political decisions -, using arthropod assemblages of ~\u0026thinsp;12k species from 450 families collected with Malaise traps at 179 plots over an area of 70.500 km\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e. The study design allowed to balance macro-environmental differences, while focusing on land-use \u003csup\u003e\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e. We tested distance decay patterns on a local scale, where arthropods are impacted by their immediate surroundings \u003csup\u003e\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e, while also assessed the outcome on a regional scale, which could impact local processes \u003csup\u003e\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e. Arthropod communities are affected by regional landscapes \u003csup\u003e\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e,\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u003c/sup\u003e, but assemblage variations are explained better by local habitat attributes \u003csup\u003e\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u003c/sup\u003e. Thus, we focused on distance decay on local land-use types.\u003c/p\u003e \u003cp\u003eAs all our habitats are at least moderately managed, we hypothesized according to McGill et al. (2015) and Socolar et al. (2016) a continuous decline of beta diversity - measured by distance decay-, with increasing land-use intensity. Further, regional land-use could have add-on effects \u003csup\u003e\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e\u003c/sup\u003e. Therefore, we expected further homogenization effects in agricultural and urban regions compared to near-natural ones.\u003c/p\u003e \u003cp\u003eBesides homogenizing communities \u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e, high land-use intensity creates environmental filters for species, affecting not only assemblages, but species with specific traits \u003csup\u003e\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e,\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e\u003c/sup\u003e. We hypothesized large and less mobile species\u0026rsquo; communities to be more dissimilar between locations (steep distance decay slope), while small and highly mobile arthropods to occur more evenly across space (flat distance decay slope), given that intensely managed habitats select for these traits \u003csup\u003e\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e,\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e\u003c/sup\u003e. To consider rare and dominant species, and the inherent incompleteness of insects samples, we applied a framework of community dissimilarity along the Hill numbers \u003csup\u003e\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e\u003c/sup\u003e standardized by sample coverage \u003csup\u003e\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e,\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e\u003c/sup\u003e. Rare species often drive observed diversity patterns, therefore we accounted for changes in communities focusing on rare, typical and dominant species separately \u003csup\u003e\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eThe sampling resulted in 1432 samples (179 study plots with 8 time periods), which gained 11387 individual arthropod taxonomic groups (BINs, thereafter \u0026lsquo;species\u0026rsquo;) via metabarcoding analysis. Of all arthropod taxonomic groups, 42% could be assigned to species level. Sample coverage was fluctuating between 0.6 and 0.9 for local land-use types, and between 0.5\u0026ndash;0.9 for arthropod trait categories (Supp. Figure\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e1\u003c/span\u003e). For land-use types, we therefore standardised sample coverage to 0.8, and for arthropod traits, to 0.7 in subsequent analyses. Number of observed species was highest in the forest systems and lowest in settlements (Supp. Figure\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e2\u003c/span\u003e), in accordance with a previous study on raw numbers of observed species (Uhler et al. \u003csup\u003e\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e\u003c/sup\u003e).\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eLand-use types\u003c/h2\u003e \u003cp\u003eDistance decay relationships on the local land-use types differed along Hill-numbers. Forest distance decay slopes were only significantly different from those in managed grasslands, where forest distance decay was stronger than those in grasslands, but not different from arable land or settlement. The distance decay of grasslands consistently had the significantly weakest slopes, independent of species rarity, indicating that species assemblages on grasslands were most similar among the four habitats. Forests, arable lands, and settlements had similar distance decay when focusing on rare (q\u0026thinsp;=\u0026thinsp;0) and typical (q\u0026thinsp;=\u0026thinsp;1) species communities. In dominant species communities (q\u0026thinsp;=\u0026thinsp;2), arable lands had the strongest distance decay pattern, similar to settlements, but significantly stronger than forests and grasslands (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e2\u003c/span\u003e, Supp. I. Table\u0026nbsp;1).\u003c/p\u003e \u003cp\u003eWhen considering regions surrounding the local land-uses, near-natural regions had a heterogenizing impact on arable lands, settlements and grasslands, but not on forests. Agricultural regions had a further homogenizing impact on grasslands and forests; while urban surroundings had diverse effects. Urban regions had a homogenizing effect on arable lands, settlements and grasslands, but only in rare and typical species communities, and a heterogenizing effect on communities focusing on dominant species. On the contrary, urban regions had a heterogenizing impact on forests, regardless of community type (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eArthropod traits\u003c/h2\u003e \u003cp\u003eOn average, forests harboured the largest arthropods (6.21\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05 mm), and the smallest species occurred in settlements (5.85\u0026thinsp;\u0026plusmn;\u0026thinsp;0.07 mm). Species in arable lands had the highest mobility score (2.72\u0026thinsp;\u0026plusmn;\u0026thinsp;0.003) while the other three land-use types were similar in their mobilities (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e4\u003c/span\u003e, Supplementary I. Table\u0026nbsp;2).\u003c/p\u003e \u003cp\u003eBody size did not impact community similarity in most land-use types. Large arthropod communities of typical species (q\u0026thinsp;=\u0026thinsp;1) in settlements were more homogeneous between locations than medium, but not small species. In arable lands, large arthropod communities of typical species (q\u0026thinsp;=\u0026thinsp;1) were more homogenous between locations than both medium and small species communities. In forests, arthropod communities including small arthropods were more heterogenous than medium and large species, when focusing on typical (q\u0026thinsp;=\u0026thinsp;1) and dominant (q\u0026thinsp;=\u0026thinsp;2) species (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e5\u003c/span\u003e, Supplementary I. Table\u0026nbsp;3).\u003c/p\u003e \u003cp\u003eDistance decay only changed with mobility scores in grasslands and forests. Low-mobility species in grasslands had significantly stronger distance decay than intermediate-, and high-mobility communities, when focusing on rare (q\u0026thinsp;=\u0026thinsp;0) and typical species (q\u0026thinsp;=\u0026thinsp;1). In forests, intermediate-mobility species\u0026rsquo; communities were more heterogeneous than high-mobility ones, but not different from low-mobility species in rare (q\u0026thinsp;=\u0026thinsp;0) and typical species (q\u0026thinsp;=\u0026thinsp;1). In dominant species communities (q\u0026thinsp;=\u0026thinsp;2) intermediate mobility-species were the most heterogenous (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e6\u003c/span\u003e, Supp. I. Table\u0026nbsp;4).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eGlobal distance decay studies help to understand the changes of communities\u0026rsquo; response to complex environmental differences, but studies on a management-relevant spatial resolution are scarce but see \u003csup\u003e\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e,\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e. Combining distance decay studies from continental and intercontinental datasets in meta-analyses is informative see \u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e, but could be problematic: it is widely shown that distance decay depend not only on spatial scale \u003csup\u003e\u003cspan additionalcitationids=\"CR68\" citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e\u003c/sup\u003e, but on study extent and design \u003csup\u003e\u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e70\u003c/span\u003e\u003c/sup\u003e. Regional and local diversity assist in conservation planning \u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e, but study designs of available data often do not allow for testing diversity on the appropriate scale \u003csup\u003e\u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e71\u003c/span\u003e\u003c/sup\u003e. Here, we compare different land-use types on the same spatial scale within a large federal state, where the same political decisions apply. This provides a standardised dataset; and a background in which land-use intensity drive arthropod communities, while biogeographic patterns play a lesser role. Besides the design, another strength of the study is the inclusion of most arthropod taxa, which provides a better understanding of whole community responses see also \u003csup\u003e\u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e72\u003c/span\u003e\u003c/sup\u003e. Single-taxonomic group approaches to distance decay are highly valuable \u003csup\u003e\u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e73\u003c/span\u003e,\u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e74\u003c/span\u003e\u003c/sup\u003e, but are regularly biased towards specific characteristics of the studied group when comparing different environments.\u003c/p\u003e \u003cp\u003eOur study extends the findings of Gossner et al. (2016), which showed increasingly similar arthropod communities with increasing grassland management intensity to other land-use types. However, we did not find evidence for a continuation of homogenization of communities along the gradient of land-use categories with increasing intensity. Instead, species communities were only highly homogenized between locations in grasslands, but with a mediating impact by the surrounding near-natural region. Contrary to grasslands, the most modified land-use type, arable lands and settlements harboured the most heterogenized arthropod communities between locations.\u003c/p\u003e \u003cp\u003eWhile traditionally managed grasslands are the most species-rich habitat types for vascular plants and insects in Europe \u003csup\u003e\u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e75\u003c/span\u003e,\u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e76\u003c/span\u003e\u003c/sup\u003e, low-input methods are widely replaced by more intensive management practices \u003csup\u003e\u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e77\u003c/span\u003e,\u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e78\u003c/span\u003e\u003c/sup\u003e. The high nitrogen- phosphorus-potassium (NPK) fertilizer inputs \u003csup\u003e\u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e79\u003c/span\u003e,\u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e80\u003c/span\u003e\u003c/sup\u003e, frequent mowing and intensive grazing \u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e,\u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e81\u003c/span\u003e\u003c/sup\u003e result in simplified and floristically homogeneous grasslands \u003csup\u003e\u003cspan citationid=\"CR82\" class=\"CitationRef\"\u003e82\u003c/span\u003e\u003c/sup\u003e. This shapes insect communities to be adapted to uniformly managed grasslands, lowering both local diversity and community differences between locations \u003csup\u003e\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e,\u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e83\u003c/span\u003e\u003c/sup\u003e. In contrast to grasslands, intensively modified arable lands and settlements harboured the most different set of arthropods between locations. Although agricultural practices change the local environment for most species \u003csup\u003e\u003cspan additionalcitationids=\"CR85\" citationid=\"CR84\" class=\"CitationRef\"\u003e84\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR86\" class=\"CitationRef\"\u003e86\u003c/span\u003e\u003c/sup\u003e, these systems can offer a diverse habitat mosaic in time and space. Series of arable lands in a given area can be composed of a variety of different crop plants, which makes land characteristics highly diverse within a small area \u003csup\u003e\u003cspan citationid=\"CR87\" class=\"CitationRef\"\u003e87\u003c/span\u003e\u003c/sup\u003e. The diversity of crops creates a locally unique sets of arthropod communities associated with the different plants grown. Indeed, crop field size in Bavaria, where the study was conducted, can be described as small- to medium-scale\u0026thinsp;~\u0026thinsp;1.6 ha arable field size, \u003csup\u003e\u003cspan citationid=\"CR88\" class=\"CitationRef\"\u003e88\u003c/span\u003e\u003c/sup\u003e compared to the German average\u0026thinsp;~\u0026thinsp;5 ha, \u003csup\u003e\u003cspan citationid=\"CR89\" class=\"CitationRef\"\u003e89\u003c/span\u003e\u003c/sup\u003e. This is reflected in our results, and in accordance with recent studies showing that high crop heterogeneity and small crop field size can have a greater benefit to biodiversity than semi-natural land cover \u003csup\u003e\u003cspan citationid=\"CR90\" class=\"CitationRef\"\u003e90\u003c/span\u003e,\u003cspan citationid=\"CR91\" class=\"CitationRef\"\u003e91\u003c/span\u003e\u003c/sup\u003e. However, Uhler et al. (2021) found the lowest insect α-diversity in arable lands, where we found the strongest distance decay. This pattern could be a result of increased habitat heterogeneity between the compared patches of arable lands, combined with decreased average species occupancy: only a few number of high-occupancy species benefit from each arable land patch (species specialised on a given grown plant or pest species), decreasing α-, but increasing β-diversity \u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eBesides agriculture, urban expansion is a major cause of habitat loss for many species \u003csup\u003e\u003cspan citationid=\"CR92\" class=\"CitationRef\"\u003e92\u003c/span\u003e,\u003cspan citationid=\"CR93\" class=\"CitationRef\"\u003e93\u003c/span\u003e\u003c/sup\u003e but, increasing attention is given to the amount of dense mosaic of habitat types within urban areas for species \u003csup\u003e\u003cspan citationid=\"CR94\" class=\"CitationRef\"\u003e94\u003c/span\u003e,\u003cspan citationid=\"CR95\" class=\"CitationRef\"\u003e95\u003c/span\u003e\u003c/sup\u003e. Similarly to our finding for beta diversity, Uhler et al. \u003csup\u003e\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e\u003c/sup\u003e reported high alpha diversity of arthropod species richness in settlements, - despite low biomass - especially in settlements within near-natural regions.\u003c/p\u003e \u003cp\u003eOn the regional scale, near-natural and agricultural regions had a clear mitigating, or worsening homogenisation impact respectively. Near-natural regional landscapes could act as insurance for wildlife \u003csup\u003e\u003cspan citationid=\"CR96\" class=\"CitationRef\"\u003e96\u003c/span\u003e\u003c/sup\u003e according to the \u0026lsquo;landscape-moderated insurance hypothesis\u0026rsquo; \u003csup\u003e\u003cspan citationid=\"CR97\" class=\"CitationRef\"\u003e97\u003c/span\u003e\u003c/sup\u003e. Natural patches, such as semi-natural forests provide a more stable environment, compared to managed grassland or arable land with frequent rotations between harvest and growth periods. When located in close proximity to each other, species can move between the less stable local land-use type (arable land or grassland) and the surrounding near-natural areas to escape the disturbance periods, or to recolonise from there \u003csup\u003e\u003cspan citationid=\"CR98\" class=\"CitationRef\"\u003e98\u003c/span\u003e\u003c/sup\u003e. This process increases species pools locally, therefore can increase community heterogeneity between locations \u003csup\u003e\u003cspan citationid=\"CR99\" class=\"CitationRef\"\u003e99\u003c/span\u003e\u003c/sup\u003e. As opposed to near-natural regions, surrounded by agricultural areas weakened distance decay at grassland and forest local land-use types. This detrimental impact of agricultural landscapes surrounding natural and semi-natural local habitats \u003csup\u003e\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e,\u003cspan citationid=\"CR100\" class=\"CitationRef\"\u003e100\u003c/span\u003e\u003c/sup\u003e decreased β-diversity between our less intensely used local land-use types. On the other hand, urban regions had the strongest heterogenizing impact on forest local land-use types. This could imply that urban environments isolated forests \u003csup\u003e\u003cspan citationid=\"CR101\" class=\"CitationRef\"\u003e101\u003c/span\u003e\u003c/sup\u003e, and arthropod species became limited in their dispersal, creating unique communities within each individual forest surrounded by urban landscapes. However, because this strong isolating impact by urban regions was not apparent in any other local land-use types in our study, the more likely explanation is that urban regions include highly diverse structures, which further heterogenized forest communities between locations \u003csup\u003e\u003cspan citationid=\"CR102\" class=\"CitationRef\"\u003e102\u003c/span\u003e\u003c/sup\u003e. Urban features add diverse hospitable habitats for otherwise forest-inhabiting arthropods, such as small hobby farms, private gardens, riparian corridors and even small remnant vegetation \u003csup\u003e\u003cspan citationid=\"CR103\" class=\"CitationRef\"\u003e103\u003c/span\u003e,\u003cspan citationid=\"CR104\" class=\"CitationRef\"\u003e104\u003c/span\u003e\u003c/sup\u003e. Such contrasting habitat types could act as complementary or supplementary environments explained by the \u0026lsquo;cross-habitat spillover hypothesis\u0026rsquo; \u003csup\u003e\u003cspan citationid=\"CR97\" class=\"CitationRef\"\u003e97\u003c/span\u003e\u003c/sup\u003e, where species flow between land-use types depending on their temporal or spatial requirements and local habitat characteristics. Again, this could enhance local species pools, and therefore increase β-diversity between local forest locations.\u003c/p\u003e \u003cp\u003eLand-use not only shapes taxonomic communities, but also acts as an environmental filter for specific traits \u003csup\u003e\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e\u003c/sup\u003e. Large bodied arthropods require larger patches of suitable habitat \u003csup\u003e\u003cspan citationid=\"CR105\" class=\"CitationRef\"\u003e105\u003c/span\u003e,\u003cspan citationid=\"CR106\" class=\"CitationRef\"\u003e106\u003c/span\u003e\u003c/sup\u003e, and low disturbance regimes \u003csup\u003e\u003cspan additionalcitationids=\"CR108\" citationid=\"CR107\" class=\"CitationRef\"\u003e107\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR109\" class=\"CitationRef\"\u003e109\u003c/span\u003e\u003c/sup\u003e. This is reflected in our results, where forests harboured communities with the largest arthropods, while the smallest assemblages were found in the most modified land-use types, in settlements. The most mobile arthropods occurred in arable lands, where species have to adapt to the frequent cropping and replanting cycles with high mobility to escape and recolonise during and post-disturbance \u003csup\u003e\u003cspan additionalcitationids=\"CR111\" citationid=\"CR110\" class=\"CitationRef\"\u003e110\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR112\" class=\"CitationRef\"\u003e112\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eDistance decay patterns were mostly not impacted by body size, implying that land-use affects arthropod communities stronger than body size impacts community similarity within land-use types. However, large arthropods within typical species communities in the most modified land-use types (settlement and arable land) were more similar between locations than communities including smaller species. Studies on urbanisation gradients showed that flying insect communities are homogenised and shift to larger, more mobile communities \u003csup\u003e\u003cspan citationid=\"CR113\" class=\"CitationRef\"\u003e113\u003c/span\u003e,\u003cspan citationid=\"CR114\" class=\"CitationRef\"\u003e114\u003c/span\u003e\u003c/sup\u003e, which we can extend to all arthropods in heavily modified land-use types in the current study. Typical (or common) species communities expressing a large body size became homogenised within settlement and arable land systems, the most modified land-use types in our study. It is not clear why this pattern is only present within typical species communities, but depending on local species pools, some species could become more widespread than others \u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e,\u003cspan citationid=\"CR115\" class=\"CitationRef\"\u003e115\u003c/span\u003e\u003c/sup\u003e driven by processes typical to modified land-uses \u003csup\u003e\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eForests on the other hand exhibit high structural diversity and therefore various microhabitats, which could have resulted in a highly heterogeneous species community including small arthropods. Body size can be linked to many life strategies and behaviours adapted to local habitats \u003csup\u003e\u003cspan citationid=\"CR116\" class=\"CitationRef\"\u003e116\u003c/span\u003e,\u003cspan citationid=\"CR117\" class=\"CitationRef\"\u003e117\u003c/span\u003e\u003c/sup\u003e, therefore arthropods in forests might track microenvironmental differences, rather than distance itself \u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e; or community assembly might be more stochastic for small species, making communities dissimilar between locations \u003csup\u003e\u003cspan citationid=\"CR118\" class=\"CitationRef\"\u003e118\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eIn grasslands, low-mobility species communities (rare and typical) were the most heterogenous, which was expected, given the disadvantage of low mobility in frequently mowed land-use types \u003csup\u003e\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e,\u003cspan citationid=\"CR119\" class=\"CitationRef\"\u003e119\u003c/span\u003e\u003c/sup\u003e. Highly mobile species are capable of escaping the disturbance and rapidly recolonizing after, while low-mobility species must find local refugia, therefore populations might become very patchy, strengthening distance decay. However, dominant species did not exhibit this pattern, implying that dominant species with various mobilities are homogenized between locations.\u003c/p\u003e \u003cp\u003eAs our major finding is the high homogenization of arthropod communities in grasslands of Central Europe, it highlights the need for improvement in Europe\u0026rsquo;s conservation actions e.g. \u003csup\u003e\u003cspan citationid=\"CR120\" class=\"CitationRef\"\u003e120\u003c/span\u003e\u003c/sup\u003e: while broad policies are needed for general directions, adaptive local management decisions impact diversity more profoundly \u003csup\u003e\u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e77\u003c/span\u003e,\u003cspan citationid=\"CR121\" class=\"CitationRef\"\u003e121\u003c/span\u003e\u003c/sup\u003e. Our studied grasslands probably reflect the overarching problem of the long-term and mostly uniform management in Europe, which led to homogenous species communities. It is important to note that the current study did not include truly natural habitat types, and all studied plots were managed to some degree, and there was no unmanaged natural baseline included in our study, which also reflects the lack of European natural habitats \u003csup\u003e\u003cspan citationid=\"CR122\" class=\"CitationRef\"\u003e122\u003c/span\u003e,\u003cspan citationid=\"CR123\" class=\"CitationRef\"\u003e123\u003c/span\u003e\u003c/sup\u003e. This urges the authorities to focus not only on the improvement of local habitat quality, but also on the improvement of habitat heterogeneity between habitat patches to boost regional diversity. Intense management practices in grasslands should reduce by favouring extensive management practices (reduction of fertilisation, less intensive mowing), improving seed banks, or optimising grazing and cutting regimes \u003csup\u003e\u003cspan additionalcitationids=\"CR125\" citationid=\"CR124\" class=\"CitationRef\"\u003e124\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR126\" class=\"CitationRef\"\u003e126\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eOur study, to our knowledge, is the first to directly compare distance decay using arthropod communities including all taxa as a response to the four major terrestrial land-use types in Europe within the same ecoregion. The strong distance decay in settlements and arable lands showed that these land-use types have a higher-than-expected heterogeneity between locations, contributing to overall gamma-diversity. Thus, we found no strong evidence for broad-scale biotic homogenisation driven by anthropogenetic land-use, except for managed grasslands. The finding highlights the fact, that however natural habitat types have been mostly lost in the Anthropocene, and the process of biodiversity decline is ongoing, anthropogenic habitat types can still create heterogenous communities on a regional scale, mainly driven by habitat mosaics. This effect however disappears on a global scale, where net species diversity is declining. Management intensification on grasslands still continues, which could lower the diversity of communities even more, while degrading multiple ecosystem services in the future. Permanent grasslands cover 13% of the area of the European Union (Eurostat, \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e\u003ca href=\"http://www.ec.europa.eu/eurostat\" target=\"_blank\"\u003ewww.ec.europa.eu/eurostat\u003c/a\u003e\u003c/span\u003e\u003cspan address=\"http://www.ec.europa.eu/eurostat\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003cspan type=\"ItalicUnderline\" class=\"ItalicUnderline\" name=\"Emphasis\"\u003e)\u003c/span\u003e and still resembles a semi-natural habitat for many native species if managed extensively. Therefore, it is important to call for a change of management in order to halt the further grassland community homogenisation.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\n\u003ch2\u003eStudy design\u003c/h2\u003e\n\u003cp\u003eThe study was conducted in Central Europe in 2019 as part of the LandKlif project: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.landklif.biozentrum.uni-wuerzburg.de\u003c/span\u003e\u003c/span\u003e. 60 regions (each 5.8 x 5.8 km) were selected in Bavaria with land-use characterizations according to Corine land cover data \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e. Each region was classified into three regional land-use types based on the Corine land cover assessments: near-natural, agricultural and urban (to be called \u0026lsquo;regions\u0026rsquo;). In each region, on a smaller scale, local land-use types were further determined based on the most dominant local land-use type based on the dominant local land-use and vegetation on a 0.5 ha resolution: forest (n\u0026thinsp;=\u0026thinsp;55), grassland (n\u0026thinsp;=\u0026thinsp;45), arable land (n\u0026thinsp;=\u0026thinsp;44) and settlement (n\u0026thinsp;=\u0026thinsp;35). In each regional landscape type, three study plots were set up, in a combination of three different local land-use types, out of the four possible land-use types. This resulted in 179 study plots, covering a\u0026thinsp;~\u0026thinsp;1000 m elevational gradient, mean annual temperatures ranging from 5 to 10.3\u0026deg;C, and precipitation from 550 and 1961 mm, distributed in the whole state of Bavaria, Germany for details see \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eAll plots were set up on a 3 m \u0026times; 30 m herbaceous vegetation in close proximity to the studied land-use type. This was done to standardize traps in the four habitat types; while, it possibly introduced some heterogeneity by establishing a small grassy area within forests, arable lands and settlements. However, we do not expect this to affect our distance decay study, as the local land-use type should always dominate the habitats, and drive arthropod species occurrence. Forest plots were located in a variety of forest types, but near beech stands, at least 50 m from the edge, and in an opened, sunny position (e.g., forest glade). Managed grassland plots were established as part of larger managed permanent grasslands, as far as possible from other land-use types, at least 50 m. Arable land plots were set up adjacent to various field crops. Settlement plots were established in green areas with at least 50 m away from public roads, and did not include forest patches.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\n\u003ch2\u003eSample collection\u003c/h2\u003e\n\u003cp\u003eMalaise traps were used to capture invertebrates with the following dimensions: height front: 0.90 m; height rear: 0.60 m; length: 1.60 m, with 80% ethanol as preserving solution. As with any sampling method, using only Malaise traps for arthropod sampling introduces a bias in sampled taxa and not capturing all arthropod taxa equally \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e49\u003c/span\u003e\u003c/sup\u003e. Nevertheless, this method reliably represents most groups of terrestrial arthropods, including flying and ground-dwelling groups \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e50\u003c/span\u003e\u003c/sup\u003e, providing by far more comprehensive data than window traps or pitfall traps. Traps were active between April or May and August 2019, with a fortnightly collection for 4 months, resulting in 8 sampling periods in total. Timing of sample collections varied due to weather and snow cover differences between locations. Samples were then split in small and large species by sieving them through an 8mm sieve to control for differences in biomass and to increase the identification of rare and small species \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e51\u003c/span\u003e,\u003cspan class=\"CitationRef\"\u003e52\u003c/span\u003e\u003c/sup\u003e. Species were identified using CO1-5P (mitochondrial cytochrome oxidase 1), and DNA metabarcoding, including the bioinformatics pipeline was done following the methods of Hausmann \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e53\u003c/span\u003e\u003c/sup\u003e. Taxonomic groups (species) were separated with the Barcode Index Number (BIN) system defining genetic units \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e54\u003c/span\u003e\u003c/sup\u003e, and identified using the BOLD platform \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ewww.boldsystems.org\u003c/span\u003e\u003c/span\u003e, \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e55\u003c/span\u003e\u003c/sup\u003e. Single reads of individual BINs were removed from the raw dataset assuming sequencing errors. Due to incomplete libraries the allocation to BIN units is a challenge, particularly for groups harbouring \"dark taxa\" such as dipterans, hymenopterans and hemipterans. For ecological analyses, the goal is to assign the sequences to units representing the solution of species themselves and to derive ecological properties from the sequence information. For this purpose, we followed the procedure described in M\u0026uuml;ller et al. \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e56\u003c/span\u003e\u003c/sup\u003e, assigning the sequences to the next existing BIN from the study region reporting the genetic distance. Thus, BINs with a distance\u0026thinsp;\u0026gt;\u0026thinsp;3% are seen as identified species, while for those with a distance\u0026thinsp;\u0026gt;\u0026thinsp;3% function as \u0026ldquo;genetic morpho-species\u0026rdquo; in the ecological analyses. In this way, all sequences across all lineages receive a reasonably balanced assignment to taxonomic units and information on ecological properties, as mobility or body size class could be extracted with high confidence because many of them are conserved on genus or family level. For simplicity we use the term species for our BINs in the following. For more details about the metabarcoding process, see Uhler et al \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e57\u003c/span\u003e\u003c/sup\u003e. Details of the metabarcoding can be found in Uhler, et al. \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e57\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\n\u003ch2\u003eStatistical analysis\u003c/h2\u003e\n\u003cp\u003eWe used detection frequency in all samples instead of reads from the sequenced data, which has issues due to sequencing errors \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e58\u003c/span\u003e\u003c/sup\u003e. This method should also control for the fact that arthropod populations can be highly patchy in distribution both temporally and spatially, therefore abundant data could lead to species being over-, or underestimated in a given sample community. Frequency data ranged between 0 and 16, as we had samples from 8 collection events from two subsamples based on body size. By using frequency, we consider species captured at all sampling periods (captured 16 out of 16 times) as species with high relative abundance. Besides the temporal replication, the inclusion of both fractions (\u0026lsquo;big\u0026rsquo; and \u0026lsquo;small\u0026rsquo;) introduces more replicates from the same sampling period.\u003c/p\u003e\n\u003cp\u003eWhen estimating diversity and assemblage similarity metrics, it is important for assemblages (samples) to be statistically comparable across all study sites, which requires a standardised sample coverage-based analysis \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e59\u003c/span\u003e\u003c/sup\u003e. Sample coverage and species detectability may differ between land-use types, therefore we used coverage-based indices calculated by the package \u003cem\u003eiNEXT.beta3D\u003c/em\u003e \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e47\u003c/span\u003e\u003c/sup\u003e. The method estimates sample coverage based on singletons presented in the data for all assemblages, which enables us to compare samples from the four different land-use types without significant detection bias in our samples.\u003c/p\u003e\n\u003cp\u003eAll statistical analysis was done using R statistical software, version 4.3.1 \u003csup\u003e60\u003c/sup\u003e.We had three components of the statistical analysis: \u003cem\u003ei\u003c/em\u003e) Establishment of community similarity matrices along the Hill-numbers \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e45\u003c/span\u003e\u003c/sup\u003e, where species are weighed differently based on their detection frequency, giving them a \u0026lsquo;rarity\u0026rsquo; variable (see below). Then, \u003cem\u003eii)\u003c/em\u003e Creation of trait-based community matrices, where species are categorized into trait groups according to their body size (large, medium, and small) and dispersal ability (high, intermediate, and low-mobility) using the existing literature and expert knowledge. Lastly, \u003cem\u003eiii\u003c/em\u003e) Analysis of distance-decay patterns: model distance-decay relationships in the four land-use types according to their rarity and traits.\u003c/p\u003e\n\u003cp\u003ei) Rarity\u003c/p\u003e\n\u003cp\u003eSpecies matrices based on their rarity were created using their overall frequency in the dataset. This variable is purely based on detection frequency within a community, and did not take their functional contribution or geographical range into account \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e61\u003c/span\u003e\u003c/sup\u003e. All categories refer to the sample-scale rarity, i.e., local rare, local typical and local dominant species within the sampled community following \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e62\u003c/span\u003e\u003c/sup\u003e. Based on the framework of effective number of species, the Hill numbers (Hill 1973, Chao et al. 2014), we can shift the focus of diversity from rare species to dominant species by adjusting the diversity order q when creating similarity matrices. Hill number of q\u0026thinsp;=\u0026thinsp;0 (S\u0026oslash;rensen index) reduces to species richness which is more sensitive to rare species; Hill number of q\u0026thinsp;=\u0026thinsp;1 (Horn index) focuses on common/typical species; Hill number of q\u0026thinsp;=\u0026thinsp;2 (Morista-Horn index) heavily weighs the dominant or very abundant species. However Hill numbers were developed for abundance data, this approach can be used appropriately for DNA-derived frequency and incidence data \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e63\u003c/span\u003e,\u003cspan class=\"CitationRef\"\u003e64\u003c/span\u003e\u003c/sup\u003e. We constructed community matrices along Hill-numbers using standardised coverage-based indices (S\u0026oslash;rensen, Horn and Morista-Horn) for each land-use type, body size and mobility. Using the above-described similarity distances, we created community similarity matrixes for rarity (q\u0026thinsp;=\u0026thinsp;0, q\u0026thinsp;=\u0026thinsp;1, q\u0026thinsp;=\u0026thinsp;2) within the four land-use types, resulting in 12 subset matrices.\u003c/p\u003e\n\u003cp\u003eii) Traits\u003c/p\u003e\n\u003cp\u003eWe used body size and mobility of 450 arthropod families from classes Arachnida, Chilopoda, Collembola, Diplopoda, Hexanauplia, Insecta, Malacostraca. Traits were assigned at family level (averaged where possible) using existing data bases, expert opinions and taxonomic keys (sources can be found in Supplementary Information II, available at \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://figshare.com/s/fda6129fe1cbe0316341\u003c/span\u003e\u003c/span\u003e\u003cem\u003e).\u003c/em\u003e Body size classes were established based on the distribution of the data: we considered arthropods as \u0026ldquo;small\u0026rdquo; if body size was equal to or less than 2.7 mm (n\u0026thinsp;=\u0026thinsp;3517), \u0026ldquo;intermediate\u0026rdquo; between 2.8 mm and 7 mm (n\u0026thinsp;=\u0026thinsp;3493), and \u0026ldquo;large\u0026rdquo; equal to or above 7 mm (n\u0026thinsp;=\u0026thinsp;3578). 91% of BINs were classified for body size. We used mobility as a category, which was determined by experts: \u0026ldquo;low\u0026rdquo; (n\u0026thinsp;=\u0026thinsp;1255), \u0026ldquo;medium\u0026rdquo; (n\u0026thinsp;=\u0026thinsp;2516) and \u0026ldquo;high\u0026rdquo; (n\u0026thinsp;=\u0026thinsp;6840) (for detailed classifications, see \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://figshare.com/s/fda6129fe1cbe0316341\u003c/span\u003e\u003c/span\u003e Supplementary Information II). Average body sizes and mobility scores were calculated using the package FD \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e65\u003c/span\u003e\u003c/sup\u003e as community weighted means for each land-use type. Pairwise differences were tested with an analysis of variance and Tukey\u0026rsquo;s post-hoc test.\u003c/p\u003e\n\u003cp\u003eiii) Analysis\u003c/p\u003e\n\u003cp\u003eDistance decay is defined by species community similarities (or dissimilarities) between two given study sites (or samples) and physical distance between these two sites, pairing up all studied samples and locations. This way, we created two matrices for every rarity and trait group: a community similarity and a physical distance matrix (km), where the x- and the y-axes are the paired sampling sites, and the cells are the community and physical distances between them.\u003c/p\u003e\n\u003cp\u003eCommunity similarity matrices were created according to rarity (detailed above), and traits. BINs belonging to trait-classified families were assigned to a trait group, then different matrices were created including only specific trait groups according to body size and mobility (3 matrices each). Then, all trait groups were reassigned to the land-use types they occurred in, resulting in trait group subsets for each land-use type (3 body size matrices and 3 mobility matrices for each land-use, 24 subset matrices in total). All groups had their corresponding rarity submatrices, q\u0026thinsp;=\u0026thinsp;0, q\u0026thinsp;=\u0026thinsp;1 and q\u0026thinsp;=\u0026thinsp;2.\u003c/p\u003e\n\u003cp\u003eSlopes of distance decay relationships were compared between land-use types, mobility, and body size classes. Given that community similarity matrices were derived from sample coverage-based diversity metrics according to Hill-numbers, distance decay relationships were compared with the package \u003cem\u003eSimba\u003c/em\u003e \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e66\u003c/span\u003e\u003c/sup\u003e, which accepts a variety of similarity matrices instead of creating one based on fixed indices (such as Sorensen or Jaccard). For significance tests, we used the function \u0026lsquo;diffslope\u0026rsquo;, which compares slopes of different distance decay regression lines directly with a randomization approach comparing our datasets instead of a bootstrapping approach based on a simulated dataset by model parameters. where we used Bonferroni-Hochberg correction for multiple comparisons between the four habitat types. Furthermore, we constructed linear regression models and extracted the distance decay slopes for better visualization. Main outputs from linear regressions can be found in the Supplementary Information I. (Supplementary I. Tables\u0026nbsp;1 and 4).\u003c/p\u003e\n\u003cp\u003eTo test whether regional landscape types change the general patterns found within local land-use types, we compared slopes of overall land-use types and specific land-use types surrounded by each regional landscape (urban, agricultural or natural). This was done by deducting the absolute value of the general slope of local land-use (including all landscapes) from the absolute value of the slope of the same local land-use, but imbedded in a specific landscape type. This way positive values imply an increased heterogeneity (more negative distance decay slope) of a given regional landscape type compared to the general slope, without considering the surrounding regional landscape type.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eData availability\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eArthropod community data, trait data (body size and mobility) and the used R code are available via the Figshare repository, at \u003cem\u003ehttps://figshare.com/s/fda6129fe1cbe0316341\u003c/em\u003e.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u0026nbsp;\u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe would like to thank all landowners who allowed us to conduct our experiments on their land. We acknowledge the support of all students and technical staff in the field and laboratory. We thank Torsten Hothorn and Oliver Mitesser for statistical support, and Caryl Benjamin, Rebekka Riebl, Sandra Rojas-Botero, Lars Uphus for fieldwork and technical support. This study was conducted within the framework of the joint project LandKlif (https://www.landklif.biozentrum.uni-wuerzburg.de/) funded by the Bavarian Ministry of Science and Arts via the Bavarian Climate Research Network (bayklif). Open Access funding enabled and organized by Projekt DEAL.\u0026nbsp;\u003cbr\u003e\u0026nbsp;\u003c/p\u003e\u003ch2\u003eAuthor contributions\u003c/h2\u003e \u003cp\u003eJohannes Uhler: Investigation (equal). Sarah Redlich: Conceptualization (equal); investigation (equal); project administration (equal); review (equal). Jie Zhang: Conceptualization (equal). Anne Chao: analysis (equal), review (equal). Ingolf Steffan-Dewenter: Project administration (equal); review (equal). Cynthia Tobisch: review (equal). J\u0026ouml;rg Ewald: review (equal). Jana Englmeier: review (equal). Ute Fricke: review (equal). Cristina Ganuza: review (equal). Maria Haensel: review (equal). J\u0026ouml;rg M\u0026uuml;ller: Conceptualization (equal); formal analysis (equal); methodology (equal); project administration (equal); supervision (equal); review and editing (equal). Orsi Decker: Conceptualization (equal), analysis (lead); writing \u0026ndash; original draft (lead); writing \u0026ndash; review and editing (lead).\u003c/p\u003e\u003ch2\u003eData availability statement:\u003c/h2\u003e \u003cp\u003eThe datasets generated during and analyzed during the current study are available in the \u003cem\u003eFigshare\u003c/em\u003e repository (see Methods).\u003c/p\u003e\n\u003cp\u003eThe authors declare no conflict of interest.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eMcKinney, M. L. \u0026amp; Lockwood, J. L. 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Grasslands of eastern Europe. \u003cem\u003eEncyclopedia of the world\u0026rsquo;s biomes\u003c/em\u003e\u003cstrong\u003e3\u003c/strong\u003e, 703-713 (2020).\u003c/li\u003e\n\u003cli\u003e Storkey, J.\u003cem\u003e et al.\u003c/em\u003e Grassland biodiversity bounces back from long-term nitrogen addition. \u003cem\u003eNature\u003c/em\u003e\u003cstrong\u003e528\u003c/strong\u003e, 401-404, doi:10.1038/nature16444 (2015).\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"nature-portfolio","isNatureJournal":true,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"","title":"Nature Portfolio","twitterHandle":"","acdcEnabled":false,"dfaEnabled":false,"editorialSystem":"ejp","reportingPortfolio":"","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"land-use, distance decay, arthropod communities, biotic homogenization","lastPublishedDoi":"10.21203/rs.3.rs-4522164/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4522164/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eGlobal biodiversity decline with increasing land-use intensity is supposedly linked to the homogenization of species communities across landscapes. However, the contribution of landscape homogenization to insect diversity loss is still largely untested. We compared an indicator for community homogenization, the distance decay slope between four local habitats of increasing land-use intensity, from forests to managed grasslands, to arable lands and to settlements, imbedded in near-natural, agricultural and urban regions. This comparison was based on 12k arthropod species from 400 families, covering an area of 70.500 km\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e. Distance decay \u0026ndash; taking rarity and species traits into account - identified grasslands as the most homogenous local land-use type. In contrast, settlements and arable lands showed the most heterogeneous arthropod communities between locations. Large and low-mobility species communities were the most heterogeneous in space, but distance decay patterns were dependent on local land-use. Regional landscape type modified local land-use patterns: near-natural landscapes lowered, while agricultural landscapes increased the impact of homogenisation. Based on our findings we recommend enhanced conservation efforts particularly in grasslands to reverse current homogenization, while settlements and arable lands could be more strongly considered in insect beta-biodiversity heterogenization.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e","manuscriptTitle":"Distance decay reveals contrasting effects of land-use types on arthropod community homogenization","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-07-22 10:08:41","doi":"10.21203/rs.3.rs-4522164/v1","editorialEvents":[],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"nature-communications","isNatureJournal":true,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"NCOMMS","sideBox":"Learn more about [Nature Communications](http://www.nature.com/ncomms/)","snPcode":"","submissionUrl":"https://mts-ncomms.nature.com/","title":"Nature Communications","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Nature Communications","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"e4e98d5a-de2e-48dc-8b5a-ea51f48526dd","owner":[],"postedDate":"July 22nd, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":33089038,"name":"Biological sciences/Ecology/Biodiversity"},{"id":33089039,"name":"Earth and environmental sciences/Ecology/Community ecology"}],"tags":[],"updatedAt":"2026-01-21T08:27:36+00:00","versionOfRecord":{"articleIdentity":"rs-4522164","link":"https://doi.org/10.1038/s41467-025-67612-9","journal":{"identity":"nature-communications","isVorOnly":false,"title":"Nature Communications"},"publishedOn":"2026-01-15 05:00:00","publishedOnDateReadable":"January 15th, 2026"},"versionCreatedAt":"2024-07-22 10:08:41","video":"","vorDoi":"10.1038/s41467-025-67612-9","vorDoiUrl":"https://doi.org/10.1038/s41467-025-67612-9","workflowStages":[]},"version":"v1","identity":"rs-4522164","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4522164","identity":"rs-4522164","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}