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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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Urban amphibian assemblages as metacommunities.

TL;DR: Without management intervention, urbanization may lead to a reduction in the number of amphibian species persisting in urban ponds, particularly where increasing isolation of ponds by roads and associated infrastructure reduces the probability of re-colonization following local extinction.
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Using presence-only and presence–absence data to estimate the current and potential distributions of established invasive species

TL;DR: A unifying framework is developed that enables managers to robustly estimate the current and potential distributions of established invasive species using either presence-only and/or presence–absence data, and establish surveillance monitoring to detect incursions within the potential distribution.
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The distribution of breeding birds around upland wind farms

TL;DR: In this paper, the authors examined whether there is reduced occurrence of breeding birds close to wind farm infrastructure (turbines, access tracks and overhead transmission lines) and found that birds are more likely to occur close to the turbines.
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The Use and Misuse of Logic Trees in Probabilistic Seismic Hazard Analysis

TL;DR: Logic trees have become a standard feature of probabilistic seismic hazard analyses (PSHA) for determining design ground motions and it may be more rational to determine the mean ground motion at the selected design return period rather than to find the groundMotion at the mean value of this return period.
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Movement behavior explains genetic differentiation in American black bears.

TL;DR: This work used path-level, conditional logistic regression to predict landscape resistance for American black bear in a landscape in which previous work predicted population connectivity using individual-based landscape genetics, and found consistent landscape factors influence genetic differentiation and movement path selection.