Spatially Structured Communities

Abstract

Biodiversity is the variety of life. It is fundamental to all aspects of ecology and conservation biology. Biodiversity can be measured at different levels of organization and at different scales. Here, we provide an overview of how space influences biological communities, why space is important for biodiversity conservation, and we illustrate some common approaches for modeling communities over space and time. Spatial concepts have been emphasized for interpreting biological communities in a variety of ways, such as the species--area relationship, the role of dispersal in metacommunities, and how environmental filters operate at different spatial scales. We illustrate some of these concepts and modeling approaches with the bird communities in the western USA. Our example contrasts three different frameworks for modeling communities in relation to how data are assembled and modeled, such as whether individual species are modeled and then predictions are combined, or if data are combined for communities and then modeled. Approaches ranging from constrained ordination and redundancy analysis to generalized dissimilarity modeling are contrasted. We show how these general frameworks can explicitly capture space by extending approaches on single species, such as spatial weighting matrices and variogram analysis, to multivariate communities. The spatial analysis and mapping of biological communities remains a frontier in ecology and conservation due to the complexity of species interactions and the diverse ways in which communities can be limited. We end by discussing some recent advancements in modeling spatially structured communities.