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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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Using environmental DNA methods to improve detectability in a hellbender (Cryptobranchus alleganiensis) monitoring program

TL;DR: The results demonstrate the efficacy of eDNA for detecting hellbender populations and the potential utility of qPCR to assess population status in hellbenders requires further study and testing, although it may be promising for determining population reproductive status.
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It is elemental: soil nutrient stoichiometry drives bacterial diversity

TL;DR: It is found that bacterial diversity and composition were primarily driven by variation in soil resource stoichiometry, itself linked to different land uses, and secondarily driven by other important biodiversity drivers such as climate, soil spatial heterogeneity, soil pH, root influence and microbial biomass.
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Harm to others outweighs harm to self in moral decision making

TL;DR: M measuring how much money people will sacrifice to reduce the number of painful electric shocks delivered to either themselves or an anonymous stranger shows that most people valued others’ pain more than their own pain, and this ‟hyperaltruistic” valuation was linked to slower responding when making decisions that affected others, consistent with an engagement of deliberative processes in moral decision making.
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State-and-Transition Models for Heterogeneous Landscapes: A Strategy for Development and Application

TL;DR: Concepts and a practical approach to potential-based land classification and STM development are outlined and a simple example of how data assembled via this sequence are used to refine ecological site classes and STMs is offered.
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Above ground biomass estimation in an African tropical forest with lidar and hyperspectral data

TL;DR: In this paper, a Partial Least Square Regression (PLSR) was adopted to cope with multiple inputs and multicollinearity issues; the Variable of Importance in the Projection was calculated to evaluate importance of individual predictors for biomass.