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Determining the influence of climate in driving the global distribution of soil microbial communities is fundamental to help predict potential shifts in soil food webs and ecosystem functioning under global change scenarios. Herein, we used a global survey including 80 dryland ecosystems from six continents, and found that the relative abundance of ecological clusters formed by taxa involved in bacteria-fungi and bacteria-cercozoa bipartite networks was highly sensitive to changes in temperature and aridity. Importantly, such a result was maintained when controlling for soil, geographical location and vegetation attributes, being pH and soil organic carbon important determinants of the relative abundance of the ecological clusters. We also identified potential global associations between important soil microbial taxa, which can be useful to support the conservation of terrestrial ecosystems under global change scenarios. Our results suggest that increases in temperature and aridity such as those forecasted for the next decades in drylands could potentially lead to drastic changes in the community composition of functionally important bipartite networks within soil food webs. This could have important but unknown implications for the provision of key ecosystem functions and associated services driven by the organisms forming these networks if other taxa cannot cope with them. This article is part of the theme issue 'Ecological complexity and the biosphere: the next 30 years'

Questions: The current paradigm of plant community assembly relies on a set of processes operating at particular spatial scales. It is assumed that as the spatial scale becomes finer, environmental filtering loses its importance in favor of biotic interactions and neutral processes. Thus, at the very fine spatial scale represented by a rectangular plot of 72.25 m2 in a Mediterranean semiarid dwarf-shrubland, we ask: (a) are the spatial distributions of individuals of the different species explained by neutral models; (b) are these distributions dependent on above-ground plant interactions with the dominant species in the community; and/or (c) are they responding to the spatial variation of different soil variables, in a kind of fine-scale environmental filtering?. Location: Central Spain. Methods: To assess the correlates of fine-scale (i.e., from 0.05–2.00 m) spatial patterns of the species in the community, we fully mapped all perennial individuals inside the rectangular plot. For each species, we fitted one complete spatial randomness (CSR) model that does not assume spatial heterogeneity and three weighted-average inhomogeneous Poisson process (IPP) models using six soil covariates, distribution patterns of the four above-ground dominant plants in the community or both types of covariates. All models were evaluated and compared to select the best-fitting weighted-average model. Results: We recorded 7,988 individuals of 22 species. Patterns of all species were appropriately explained by IPP models. For most species the best-fitting weighted-average model included both soil and dominant plants (i.e., 15) or only soil covariates (i.e., 6). The improvement provided by the best-fitting weighted-averaging model in comparison with the CSR model was consistently high (81%). Conclusions: Our approach suggests that species in this dwarf-shrubland are mainly structured by soil heterogeneity and modulated in some cases by the interactions established with the dominant speci