Handbook of Quantitative Ecology
Author | : Justin Kitzes |
Publisher | : University of Chicago Press |
Total Pages | : 174 |
Release | : 2022-08-16 |
ISBN-10 | : 9780226818337 |
ISBN-13 | : 0226818330 |
Rating | : 4/5 (330 Downloads) |
Download or read book Handbook of Quantitative Ecology written by Justin Kitzes and published by University of Chicago Press. This book was released on 2022-08-16 with total page 174 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.