Handbook Of Quantitative Ecology

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.

Ecological research is becoming increasingly quantitative, yet students often opt out of courses in mathematics and statistics, unwittingly limiting their ability to carry out research in the future. This textbook provides a practical introduction to quantitative ecology for students and practitioners who have realised that they need this opportunity. The text is addressed to readers who haven't used mathematics since school, who were perhaps more confused than enlightened by their undergraduate lectures in statistics and who have never used a computer for much more than word processing and data entry. From this starting point, it slowly but surely instils an understanding of mathematics, statistics and programming, sufficient for initiating research in ecology. The book’s practical value is enhanced by extensive use of biological examples and the computer language R for graphics, programming and data analysis. Key Features: Provides a complete introduction to mathematics statistics and computing for ecologists. Presents a wealth of ecological examples demonstrating the applied relevance of abstract mathematical concepts, showing how a little technique can go a long way in answering interesting ecological questions. Covers elementary topics, including the rules of algebra, logarithms, geometry, calculus, descriptive statistics, probability, hypothesis testing and linear regression. Explores more advanced topics including fractals, non-linear dynamical systems, likelihood and Bayesian estimation, generalised linear, mixed and additive models, and multivariate statistics. R boxes provide step-by-step recipes for implementing the graphical and numerical techniques outlined in each section. How to be a Quantitative Ecologist provides a comprehensive introduction to mathematics, statistics and computing and is the ideal textbook for late undergraduate and postgraduate courses in environmental biology. "With a book like this, there is no excuse for people to be afraid of maths, and to be ignorant of what it can do." —Professor Tim Benton, Faculty of Biological Sciences, University of Leeds, UK

A follow-up to the highly successful first edition, this book reviews the manifold ways that scale influences the interpretation of ecological variation. As scale, magnitude, quantity, and measurement occupy an expanding role in ecology, this 2e will be an indispensable addition to individual and institutional libraries. In providing a context for resolution of ecological problems, ecologists will appreciate the significance of scale and magnitude addressed in this book. Written for advanced undergraduates, graduate students, and faculty researchers, this book synthesizes a burgeoning literature on the influences of scale. * Expanded by numerous explanatory figures and wide coverage of material * Topic is of crucial importance to ecologists * The most thorough, complete coverage available on quantitative ecology in the market

This handbook focuses on the enormous literature applying statistical methodology and modelling to environmental and ecological processes. The 21st century statistics community has become increasingly interdisciplinary, bringing a large collection of modern tools to all areas of application in environmental processes. In addition, the environmental community has substantially increased its scope of data collection including observational data, satellite-derived data, and computer model output. The resultant impact in this latter community has been substantial; no longer are simple regression and analysis of variance methods adequate. The contribution of this handbook is to assemble a state-of-the-art view of this interface. Features: An internationally regarded editorial team. A distinguished collection of contributors. A thoroughly contemporary treatment of a substantial interdisciplinary interface. Written to engage both statisticians as well as quantitative environmental researchers. 34 chapters covering methodology, ecological processes, environmental exposure, and statistical methods in climate science.

Understand How to Analyze and Interpret Information in Ecological Point PatternsAlthough numerous statistical methods for analyzing spatial point patterns have been available for several decades, they haven't been extensively applied in an ecological context. Addressing this gap, Handbook of Spatial Point-Pattern Analysis in Ecology shows how the t

Primarily written for non-mathematically inclined biologist.

Industrial Ecology (IE) is an emerging multidisciplinary field. University departments and higher education programs are being formed on the subject following the lead of Yale University, The Norwegian University of Science and Technology (NTNU), Leiden University, University of Michigan at Ann Arbor, Carnegie Mellon University, University of California at Berkeley, Institute for Superior Technology in Lisbon, Eidgenössische Technische Hochschule (ETH) Zürich, and The University of Tokyo. IE deals with stocks and flows in interconnected networks of industry and the environment, which relies on a basic framework for analysis. Among others, Input-Output Analysis (IOA) is recognized as a key conceptual and analytical framework for IE. A major challenge is that the field of IOA manifests a long history since the 1930s with two Nobel Prize Laureates in the field and requires considerable analytical rigor. This led many instructors and researchers to call for a high-quality publication on the subject which embraces both state-of-the-art theory and principles as well as practical applications.