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Ecological community data. Spatial pattern analysis. Species-abundance relations. Species affinity. Community classification. Community ordination. Community interpretation.
We developed the first edition of this book because we perceived a need for a compilation on study design with application to studies of the ecology, conser- tion, and management of wildlife. We felt that the need for coverage of study design in one source was strong, and although a few books and monographs existed on some of the topics that we covered, no single work attempted to synthesize the many facets of wildlife study design. We decided to develop this second edition because our original goal – synthesis of study design – remains strong, and because we each gathered a substantial body of new material with which we could update and expand each chapter. Several of us also used the first edition as the basis for workshops and graduate teaching, which provided us with many valuable suggestions from readers on how to improve the text. In particular, Morrison received a detailed review from the graduate s- dents in his “Wildlife Study Design” course at Texas A&M University. We also paid heed to the reviews of the first edition that appeared in the literature.
Bayesian modeling has become an indispensable tool for ecological research because it is uniquely suited to deal with complexity in a statistically coherent way. This textbook provides a comprehensive and accessible introduction to the latest Bayesian methods—in language ecologists can understand. Unlike other books on the subject, this one emphasizes the principles behind the computations, giving ecologists a big-picture understanding of how to implement this powerful statistical approach. Bayesian Models is an essential primer for non-statisticians. It begins with a definition of probability and develops a step-by-step sequence of connected ideas, including basic distribution theory, network diagrams, hierarchical models, Markov chain Monte Carlo, and inference from single and multiple models. This unique book places less emphasis on computer coding, favoring instead a concise presentation of the mathematical statistics needed to understand how and why Bayesian analysis works. It also explains how to write out properly formulated hierarchical Bayesian models and use them in computing, research papers, and proposals. This primer enables ecologists to understand the statistical principles behind Bayesian modeling and apply them to research, teaching, policy, and management. Presents the mathematical and statistical foundations of Bayesian modeling in language accessible to non-statisticians Covers basic distribution theory, network diagrams, hierarchical models, Markov chain Monte Carlo, and more Deemphasizes computer coding in favor of basic principles Explains how to write out properly factored statistical expressions representing Bayesian models
Regression, analysis of variance, correlation, graphical.
Ecologists interested in assessing landscapes and ecosystems must measure biomass, cover, and the density or frequency of various key species. Recently, sampling designs for measuring species richness and diversity, patterns of plant diversity, species-environment relationships, and species distributions have become fine-grained, as it has become increasingly important to accurately map and assess rare species for conservation. This book lays out the range of current methods for mapping and measuring species diversity, for field ecologists, resource managers, conservation biologist, and students, as a tool kit for future measurements of plant diversity.
Phylogenies in Ecology is the first book to critically review the application of phylogenetic methods in ecology, and it serves as a primer to working ecologists and students of ecology wishing to understand these methods. This book demonstrates how phylogenetic information is transforming ecology by offering fresh ways to estimate the similarities and differences among species, and by providing deeper, evolutionary-based insights on species distributions, coexistence, and niche partitioning. Marc Cadotte and Jonathan Davies examine this emerging area's explosive growth, allowing for this new body of hypotheses testing. Cadotte and Davies systematically look at all the main areas of current ecophylogenetic methodology, testing, and inference. Each chapter of their book covers a unique topic, emphasizes key assumptions, and introduces the appropriate statistical methods and null models required for testing phylogenetically informed hypotheses. The applications presented throughout are supported and connected by examples relying on real-world data that have been analyzed using the open-source programming language, R. Showing how phylogenetic methods are shedding light on fundamental ecological questions related to species coexistence, conservation, and global change, Phylogenies in Ecology will interest anyone who thinks that evolution might be important in their data.