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Kitzes J Handbook Of Quantitative Ecology 2022
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An essential guide to quantitative research methods in ecology and conservation biology, accessible for even the most math-averse student or professional. Quantitative research techniques have become increasingly important in ecology and conservation biology, but the sheer breadth of methods that must be understood—from population modeling and probabilistic thinking to modern statistics, simulation, and data science—and a lack of computational or mathematics training have hindered quantitative literacy in these fields. In this book, ecologist Justin Kitzes addresses those challenges for students and practicing scientists alike. Requiring only basic algebra and the ability to use a spreadsheet, Handbook of Quantitative Ecology is designed to provide a practical, intuitive, and integrated introduction to widely used quantitative methods. Kitzes builds each chapter around a specific ecological problem and arrives, step by step, at a general principle through the process of solving that problem. Grouped into five broad categories—difference equations, probability, matrix models, likelihood statistics, and other numerical methods—the book introduces basic concepts, starting with exponential and logistic growth, and helps readers to understand the field’s more advanced subjects, such as bootstrapping, stochastic optimization, and cellular automata. Complete with online solutions to all numerical problems, Kitzes’s Handbook of Quantitative Ecology is an ideal coursebook for both undergraduate and graduate students of ecology, as well as a useful and necessary resource for mathematically out-of-practice scientists. Introduction Change over Time Introducing Difference Equations Duckweed on a Pond: Exponential Growth Throwing Shade I: Logistic Growth Throwing Shade II: Lotka-Volterra Competition Rabies Removal: SIR Models Understanding Uncertainty Introducing Probability A Bird in the Cam I: Single-Variable Probability A Bird in the Cam II: Two-Variable Probability Picking Ticks: Bayes’s Rule Rabbit Rates: Probability Distributions Modeling Multiple States Introducing Matrix Models Imagine All the Beetles: Age-Structured Models The Road to Succession: Transition Matrices A Pair of Populations: Absorption Fish Finders: Diffusion Explaining Data Introducing Statistics Seedling Counts I: Maximum Likelihood Seedling Counts II: Model Selection Flattened Frogs I: Generalized Linear Models Flattened Frogs II: Hypothesis Testing Expanding the Toolbox Other Techniques Bird Islands: Graphical Thinking Max Plant Institute: Optimization Bears with Me: Stochastic Simulation Natives in the Neighborhood: Cellular Automata References Index
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