Data from: Disentangling biotic interactions, environmental filters, and dispersal limitation as drivers of species co-occurrence

A key focus in ecology is to search for community assembly rules. Here we compare two community modelling frameworks that integrate a combination of environmental and spatial data to identify positive and negative species associations from presence-absence matrices, and incorporate an additional comparison using joint species distribution models (JSDM). The frameworks use a dichotomous logic tree that distinguishes dispersal limitation, environmental requirements, and interspecific interactions as causes of segregated or aggregated species pairs. The first framework is based on a classical null model analysis complemented by tests of spatial arrangement and environmental characteristics of the sites occupied by the members of each species pair (Classic framework). The second framework, (SDM framework) implemented here for the first time, builds on the application of environmentally-constrained null models (or JSDMs) to partial out the influence of the environment, and includes an analysis of the geographical configuration of species ranges to account for dispersal effects. We applied these approaches to examine plot-level species co-occurrence in plant communities sampled along a wide elevation gradient in the Swiss Alps. According to the frameworks, the majority of species pairs were randomly associated, and most of the non-random positive and negative species associations could be attributed to environmental filtering and/or dispersal limitation. These patterns were partly detected also with JSDM. Biotic interactions were detected more frequently in the SDM framework, and by JSDM, than in the Classic framework. All approaches detected species aggregation more often than segregation, perhaps reflecting the important role of facilitation in stressful high-elevation environments. Differences between the frameworks may reflect the explicit incorporation of elevational segregation in the SDM framework and the sensitivity of JSDM to the environmental data. Nevertheless, all methods have the potential to reveal general patterns of species co-occurrence for different taxa, spatial scales, and environmental conditions.Environmental data and presence-absence information of 175 species in 912 plots in western Swiss AlpsThe file contains data on 5 environmental predictors (ddeg0=growding degree days with threshold of 0 degree, SLOPE=slope angle in degrees, MIND=moisture index as the difference between precipitation and evapotranspiration summed over the growing season, SOLRAD=summed annual solar radiation, TPI=topographic position index describing exposure of exposure of a location in space compared to the surrounding terrain) and species presence-absence information on 912 plots (4x4m) collected in Swiss western Alps (46°23' N, 7°5' E). Additionally, geographic coordinates of the plots are provided in Swiss coordinate system. Subsets and parts of the data have been used in other publications of the related research group, ECOSPAT, University of Lausanne. For the complete list of publications related to the dataset, see https://www.unil.ch/ecospat/home/menuinst/publications.html. In addition, "Randin, C. F., et al. (2006). Journal of Biogeography 33: 10" provides the description of how ddeg0, SLOPE, MIND and SOLRAD were derived using meteorological data and 25-m resolution digital elevation model (DEM). TPI was calculated from the same 25-m DEM using 3x3 moving window implementing the method of "Zimmermann, N.E. & Roberts, D.W. (2001) Final report of the MLP climate and biophysical mapping project. Swiss Federal Research Institute WSL, Birmensdorf, Switzerland."Data_Ecospat_Env_PresAbsPlants_912plots.tx