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Trends Ecol Evol. 2015 Dec;30(12):766-779. doi: 10.1016/j.tree.2015.09.007. Epub 2015 Oct 28.

So Many Variables: Joint Modeling in Community Ecology.

Author information

1
School of Mathematics and Statistics, and Evolution & Ecology Research Centre, The University of New South Wales (UNSW), Sydney, Australia. Electronic address: david.warton@unsw.edu.au.
2
Department of Mathematics and Statistics, McMaster University, Hamilton, Canada.
3
Biodiversity and Climate Research Centre, Frankfurt, Germany.
4
Metapopulation Research Center, Department of Biosciences, University of Helsinki, Finland; Centre for Biodiversity Dynamics, Department of Biology, Norwegian University of Science and Technology, Norway.
5
Department of Mathematics and Statistics, University of Jyväskylä, Jyväskylä, Finland.
6
Mathematical Sciences Institute, Australian National University, Canberra, Australia.

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.

PMID:
26519235
DOI:
10.1016/j.tree.2015.09.007
[Indexed for MEDLINE]

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