Multifaceted biodiversity modelling at macroecological scales using Gaussian processes

Modelling the response of β‐diversity (i.e., the turnover in species composition among sites) to environmental variation has wide‐ranging applications, including informing conservation planning, understanding community assembly and forecasting the impacts of climate change. However, modelling β‐diversity is challenging, especially for multiple diversity facets (i.e., taxonomic, functional and phylogenetic diversity), and current methods have important limitations. Here, we present a new approach for predicting the response of multifaceted β‐diversity to the environment, called Multifaceted Biodiversity Modelling (MBM). We illustrate the approach using both a plant diversity dataset from the French Alps and a set of simulated data. We also provide an implementation via an R package.

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