Generalised latent variable models for multivariate abundances in ecology
Technological advances have enabled a new class of multivariate models for ecology, with the potential now to specify a statistical model for abundances jointly across many taxa, to simultaneously explore interactions across taxa and the response of abundance to environmental variables. Generalised latent variable model can be used for several purposes of interest to ecologists, including estimating patterns of residual correlation across taxa, ordination, multivariate inference about environmental effects and environment-by-trait interactions, accounting for missing predictors, and improving predictions in situations where one can leverage knowledge of some species to predict others. We demonstrate this by example, stepping through code from the gllvm package, and discuss future directions.
David Warton is a Professor in the Department of Statistics at the University of New South Wales and leads the Eco-Stats Research Group. His research focuses on developing new methodologies for data analysis in ecological research and increasing awareness in ecology and related disciplines of existing methodologies.