Using codispersion analysis to quantify and understand spatial patterns in species-environment relationships

Abstract

Summary 1. Analysis of spatial patterns in species-environment relationships can provide new insights about the niche requirements and potential co-occurrence of species, but species abundance and environmental data are routinely collected at different spatial scales. Here, we investigate the use of codispersion analysis to measure and assess the scale, directionality, and significance of complex relationships between plants and their environment in large forest plots. 2. We applied codispersion analysis to both simulated and field data on spatially-located tree species basal area and environmental variables. The significance of observed bivariate spatial associations between the basal area of key species and underlying environmental variables was tested using three null models. 3. Codispersion analysis reliably detected directionality (anisotropy) in bivariate species-environment relationships and identified relevant scales of effects. Null model-based significance tests applied to codispersion analyses of forest plot data enabled us to infer the extent to which environmental conditions, tree sizes, and/or tree spatial positions underpinned observed basal area-environment relationships, or whether relationships were due to other unmeasured factors. 4. Codispersion analysis, combined with appropriate null models, can be used to infer hypothesized ecological processes from spatial patterns allowing us to start disentangling the possible drivers of plant species-environment relationships.