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Handbook of Quantitative Ecology

BuchGebunden
176 Seiten
Englisch
The University of Chicago Presserschienen am20.07.2022
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.mehr
Verfügbare Formate
BuchGebunden
EUR96,50
TaschenbuchKartoniert, Paperback
EUR26,00

Produkt

KlappentextAn 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.
Details
ISBN/GTIN978-0-226-81832-0
ProduktartBuch
EinbandartGebunden
Erscheinungsjahr2022
Erscheinungsdatum20.07.2022
Seiten176 Seiten
SpracheEnglisch
MasseBreite 158 mm, Höhe 233 mm, Dicke 18 mm
Gewicht464 g
Artikel-Nr.58546951

Inhalt/Kritik

Inhaltsverzeichnis
Introduction Part I Change over Time Chapter 1 Introducing Difference Equations Chapter 2 Duckweed on a Pond: Exponential Growth Chapter 3 Throwing Shade I: Logistic Growth Chapter 4 Throwing Shade II: Lotka-Volterra Competition Chapter 5 Rabies Removal: SIR Models Part II Understanding Uncertainty Chapter 6 Introducing Probability Chapter 7 A Bird in the Cam I: Single-Variable Probability Chapter 8 A Bird in the Cam II: Two-Variable Probability Chapter 9 Picking Ticks: Bayes´s Rule Chapter 10 Rabbit Rates: Probability Distributions Part III Modeling Multiple States Chapter 11 Introducing Matrix Models Chapter 12 Imagine All the Beetles: Age-Structured Models Chapter 13 The Road to Succession: Transition Matrices Chapter 14 A Pair of Populations: Absorption Chapter 15 Fish Finders: Diffusion Part IV Explaining Data Chapter 16 Introducing Statistics Chapter 17 Seedling Counts I: Maximum Likelihood Chapter 18 Seedling Counts II: Model Selection Chapter 19 Flattened Frogs I: Generalized Linear Models Chapter 20 Flattened Frogs II: Hypothesis Testing Part V Expanding the Toolbox Chapter 21 Other Techniques Chapter 22 Bird Islands: Graphical Thinking Chapter 23 Max Plant Institute: Optimization Chapter 24 Bears with Me: Stochastic Simulation Chapter 25 Natives in the Neighborhood: Cellular Automata References Indexmehr