Warton DI, Blanchet FG, O'Hara RB, Ovaskainen O, Taskinen S, Walker SC, Hui FKC. So Many Variables: Joint Modeling in Community Ecology.
Trends Ecol Evol 2015;
30:766-779. [PMID:
26519235 DOI:
10.1016/j.tree.2015.09.007]
[Citation(s) in RCA: 329] [Impact Index Per Article: 36.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2015] [Revised: 09/09/2015] [Accepted: 09/10/2015] [Indexed: 01/21/2023]
Abstract
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. Joint models 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 and discuss recent computation tools and future directions.
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