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Mixture of Generalized Linear Regression Models for Species-Rich Ecosystems

Mortier F.. 2017. In : ENAR 2017 Spring Meeting abstracts. Washington : Eastern North American Region International Biometric Society, p. 263-263. ENAR 2017 Spring Meeting, 2017-03-12/2017-03-15, Washington (Etats-Unis).

Understanding how climate change could impact population dynamics is of primary importance for species conservation. In species-rich ecosystems with many rare species, the small population sizes hinder a good fit of species-specific models. We propose a mixture of regression models with variable selection allowing the simultaneous clustering of species into groups according to vital rate information (recruitment, growth, and mortality) and the identification of group-specific explicative environmental variables. We illustrate the effectiveness of the method on data from a tropical rain forest in the Central African Republic and demonstrate the accuracy of the model in successfully reproducing stand dynamics and classifying tree species into well-differentiated groups with clear ecological interpretations.

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