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Model Selection and Multimodel Inference: A Practical Information-Theoretic Approach
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TLDR
The second edition of this book is unique in that it focuses on methods for making formal statistical inference from all the models in an a priori set (Multi-Model Inference).Abstract:
Introduction * Information and Likelihood Theory: A Basis for Model Selection and Inference * Basic Use of the Information-Theoretic Approach * Formal Inference From More Than One Model: Multi-Model Inference (MMI) * Monte Carlo Insights and Extended Examples * Statistical Theory and Numerical Results * Summaryread more
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Journal ArticleDOI
Bayesian Phylogenetic Analysis of Combined Data
TL;DR: A Bayesian MCMC approach to the analysis of combined data sets was developed and its utility in inferring relationships among gall wasps based on data from morphology and four genes was explored, supporting the utility of morphological data in multigene analyses.
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Improved allometric models to estimate the aboveground biomass of tropical trees
Jérôme Chave,Maxime Réjou-Méchain,Alberto Búrquez,E. N. Chidumayo,Matthew S. Colgan,Welington Braz Carvalho Delitti,Alvaro Duque,Tron Eid,Philip M. Fearnside,Rosa C. Goodman,Matieu Henry,Angelina Martínez-Yrízar,Wilson A. Mugasha,Helene C. Muller-Landau,Maurizio Mencuccini,Bruce Walker Nelson,Alfred Ngomanda,Euler Melo Nogueira,Edgar Ortiz-Malavassi,Raphaël Pélissier,Pierre Ploton,Casey M. Ryan,Juan Saldarriaga,Ghislain Vieilledent +23 more
TL;DR: This work analyzed a global database of directly harvested trees at 58 sites, spanning a wide range of climatic conditions and vegetation types, and found a pantropical model incorporating wood density, trunk diameter, and the variable E outperformed previously published models without height.
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Understanding predictive information criteria for Bayesian models
TL;DR: The Akaike, deviance, and Watanabe-Akaike information criteria are reviewed from a Bayesian perspective and it is better understood, through small examples, how these methods can apply in practice.
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Five (or so) challenges for species distribution modelling
Miguel B. Araújo,Antoine Guisan +1 more
TL;DR: Five areas of enquiry are identified and discussed that are of high importance for species distribution modelling: clarification of the niche concept; improved designs for sampling data for building models; improved parameterization; improved model selection and predictor contribution; and improved model evaluation.
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Primary forests are irreplaceable for sustaining tropical biodiversity
Luke Gibson,Tien Ming Lee,Tien Ming Lee,Lian Pin Koh,Lian Pin Koh,Barry W. Brook,Toby A. Gardner,Jos Barlow,Carlos A. Peres,Corey J. A. Bradshaw,Corey J. A. Bradshaw,William F. Laurance,Thomas E. Lovejoy,Navjot S. Sodhi +13 more
TL;DR: It is found that biodiversity values were substantially lower in degraded forests, but that this varied considerably by geographic region, taxonomic group, ecological metric and disturbance type.