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.