BHPMF – a hierarchical Bayesian approach to gap-filling and trait prediction for macroecology and functional biogeographyTools Schrodt, Franziska and Kattge, Jens and Shan, Hanhuai and Fazayeli, Farideh and Joswig, Julia and Banerjee, Arindam and Reichstein, Markus and Bönisch, Gerhard and Diaz, Sandra and Dickie, John and Gillison, Andy and Karpatne, Anuj and Lavorel, Sandra and Leadley, Paul and Wirth, Christian B. and Wright, Ian J. and Wright, S. Joseph and Reich, Peter B. (2015) BHPMF – a hierarchical Bayesian approach to gap-filling and trait prediction for macroecology and functional biogeography. Global Ecology and Biogeography, 24 (12). pp. 1510-1521. ISSN 1466-8238 Full text not available from this repository.AbstractAim: Functional traits of organisms are key to understanding and predicting biodiversity and ecological change, which motivates continuous collection of traits and their integration into global databases. Such trait matrices are inherently sparse, severely limiting their usefulness for further analyses. On the other hand, traits are characterized by the phylogenetic trait signal, trait–trait correlations and environmental constraints, all of which provide information that could be used to statistically fill gaps. We propose the application of probabilistic models which, for the first time, utilize all three characteristics to fill gaps in trait databases and predict trait values at larger spatial scales.
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