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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 * Summary

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Bayesian estimation of the global biogeographical history of the Solanaceae

TL;DR: Maximum likelihood methods and newly developed biogeographical stochastic mapping methods are applied to infer the ancestral range of the tomato family Solanaceae and to estimate the frequency of dispersal and vicariance events resulting in its present‐day distribution.
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Modeling electrochemical impedance spectroscopy

TL;DR: In this article, the EIS data can be correlated with many key physical properties, including rates of diffusion and reaction, and microstructural features, which can be used to overcome ambiguities in interpretation.
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As Time Goes by: A Simple Fool's Guide to Molecular Clock Approaches in Invertebrates*

TL;DR: A judicious use of molecular clock analyses in evolutionary studies of invertebrates is encouraged by demonstrating their great potential on the one hand and (often-manageable) problems and pitfalls on the other hand.
Book

Ecosystem-Based Fisheries Management: Confronting Tradeoffs

TL;DR: In this article, a range of interdisciplinary topics surrounding ecosystem-based fisheries management (EBFM) are discussed, with an aim to provide tools for successful implementation and to further the debate on EBFM, ultimately hoping to foster enhanced living marine resource management.