AI Article Synopsis
- Recent technological advances have led to the development of multivariate models that allow ecologists to analyze species abundances together and assess interactions between different taxa and environmental variables.
- These joint models can help estimate correlations between species, perform multivariate environmental impact assessments, and handle missing data, enhancing predictive accuracy across species.
- The text presents examples of these methods in action, discusses new computational tools available to researchers, and outlines potential future developments in this field.
Article 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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| http://dx.doi.org/10.1016/j.tree.2015.09.007 | DOI Listing |
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