Abstract
Community ecology aims to understand what factors 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 propose Hierarchical Modelling of Species Communities (HMSC) as a general, flexible framework for modern analysis of community data. While non-manipulative data allow for only correlative and not causal inference, this framework facilitates the formulation of data-driven hypotheses regarding the processes that structure communities. We model environmental filtering by variation and covariation in the responses of individual species to the characteristics of their environment, with potential contingencies on species traits and phylogenetic relationships. We capture biotic assembly rules by species-to-species association matrices, which may be estimated at multiple spatial or temporal scales. We operationalise the HMSC framework as a hierarchical Bayesian joint species distribution model, and implement it as R- and Matlab-packages which enable computationally efficient analyses of large data sets. Armed with this tool, community ecologists can make sense of many types of data, including spatially explicit data and time-series data. We illustrate the use of this framework through a series of diverse ecological examples.
Highlights
Ecology has been described as the scientific understanding of factors determining the abundance and distribution of species (Smith 1966; Begon et al 1986)
Community ecology began as a descriptive science in which communities were classified based on the identities and sizes of local species pools (e.g. Clements 1936; Elton 1966)
Modern community ecology is progressing from the description of patterns towards a mechanistic perspective, which seeks to understand the processes determining the identities and abundances of the species from local to global spatiotemporal scales (Agrawal et al 2007; Logue et al 2011)
Summary
Ecology has been described as the scientific understanding of factors determining the abundance and distribution of species (Smith 1966; Begon et al 1986). To relate community-level responses to environmental variation to response traits, one may wish to include data on species-specific traits (T matrix, Fig. 3).
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