Joint species distribution modelling: how to make more out of community data?

A central aim community ecology is to understand the processes that determine the assembly and dynamics of species assemblages at different spatiotemporal scales. To facilitate the integration between conceptual and statistical approaches in community ecology, we have developed Hierarchical Modelling of Species Communities (HMSC) as a general, flexible framework for modern analysis of community data. HMSC belongs to the class of joint species distribution models, and it makes it possible to derive simultaneously species- and community level inference from data on species occurrences, environmental covariates, species traits, and phylogenetic relationships. HMSC applies to a wide variety of study designs, including hierarchical data, spatial data, temporal data, and spatio-temporal data. I describe the general HMSC framework and its relationships to other methods for analysing community data, demonstrate the R-package Hmsc by applying it to a case study on Finnish birds, and conclude by discussing the strengths and development needs of this methodological framework.

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