Abstract: Changes in land-use and climate are considered two of the most important drivers of global biodiversity loss, yet few studies examine the influence of both gradients simultaneously. This research examines how gradients of both land-use and climate in agroecosystems influence the community structure and the presence of certain functional traits in arthropod communities. We used a previously published data set comprised of 2,301 unique spatiotemporal sampling occurrences in agroecosystems spanning the European subcontinent, between the years 2001–2014. We examined the interaction of climate gradients (temperature and precipitation) and land-use gradients (landscape composition and configuration) on community structure (species richness, abundance, evenness, and diversity) and the relative abundance of functional traits (related to diet specialism, foraging strategies, overwintering habitats, and dispersal abilities) in arthropod communities. Preliminary results show that arthropod species richness, evenness, and diversity was higher in sites with higher temperatures and precipitation, while total arthropod abundance was higher in sites with low temperatures and high precipitation. All four of these metrics were highest in sites with more semi-natural habitat and water. Arthropods that were diet generalists, that did not specialize on agricultural species, or were ground dispersers were most abundant in sites associated with high temperatures and precipitation, while arthropods that were overwintering habitat generalists were more abundant in sites experiencing high temperatures and low precipitation. Arthropods that were diet generalists, that did not specialize on agricultural species, were ground dispersers, and were overwintering habitat generalists were most prevalent in sites with high proportions of semi-natural land and water. This research highlights the importance of examining both the effects of climate and land-use when comparing community patterns across broad spatial scales and can help develop predictions of how both drivers will impact future biodiversity patterns.
