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The CATS model (Community Assembly by Trait Selection) uses average trait values of both species and communities in a system of linear equations to predict the relative abundance of each species in a community C from the regional species pool P. This model has been tested in a variety of habitats. There is an asymptote to the number of useful traits. The asymptote is determined by the strength of covariation among the traits of the species pool. The Traitspace model uses Bayes’ theorem to combine trait–environment relationships and multidimensional trait distributions for each species to predict the relative abundance of each species in a community C from the regional species pool P. Both models can be used to determine the importance of traits in community assembly. Each model has costs and benefits, which future work will clarify.
This book addresses an important problem in ecology: how are communities assembled from species pools? This pressing question underlies a broad array of practical problems in ecology and environmental science, including restoration of damaged landscapes, management of protected areas, and protection of threatened species. This book presents a simple logical structure for ecological assembly and addresses key areas including species pools, traits, environmental filters, and functional groups. It demonstrates the use of two predictive models (CATS and Traitspace) and consists of many wide-ranging examples including plants in deserts, wetlands, and forests, and communities of fish, amphibians, birds, mammals, and fungi. Global in scope, this volume ranges from the arid lands of North Africa, to forests in the Himalayas, to Amazonian floodplains. There is a strong focus on applications, particularly the twin challenges of conserving biodiversity and understanding community responses to climate change.
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