Ecological Statistics: Contemporary theory and application - Tapa dura

In this well-written and well-edited book, the authors successfully convey an understanding of statistics, rather than just a menu of statistical procedures. Ideas are explained preferentially by examples and illustration, and mathematical formalism is held at a minimum ... This book is a source of coherent statistical understanding. (Conservation Biology)

We would be glad to adopt this as a textbook and recommend it as a resource for graduate students who need to strengthen their understanding of modern statistical approaches that can inform ecological problems. (Brian D. Inouye and Scott C. Burgess, The Quarterly Review of Biology)

This is a rich selection of the new canon of ecological statistics. Most examples are illustrated with the relevant R code, all of which is available online. As a result, this is not just an introduction to the theory underlying new approaches ― it is a hands-on introduction to their use! Importantly, the chapters ― though cross-referenced ― are self-contained. As such, many practising ecologists will be able to dip in to a chapter that covers a particular problem that they are facing. That is a real strength of this book and suggests that most ecological research groups will benefit from access to at least one copy. (British Ecological Society Bulletin)

Ecological Statistics: Contemporary Theory and Application is an amazing piece of work that deftly performs the unenviable task of presenting the need to know methods of a complex field. ... This book would be a valuable addition to any course asking students to expand their statistical comfort zone, but also easily lends itself to self-study for those wishing to join the conversation of ecological statistics. (Chase L. Nuñez, Plant Science Bulletin)

Ecological Statistics opens with a commendable introduction that makes some great points and provides an insightful big-picture perspective. (Megan D. Higgs, BioScience)

The application and interpretation of statistics are central to ecological study and practice. Ecologists are now asking more sophisticated questions than in the past. These new questions, together with the continued growth of computing power and the availability of new software, have created a new generation of statistical techniques. These have resulted in major recent developments in both our understanding and practice of ecological statistics.

This novel book synthesizes a number of these changes, addressing key approaches and issues that tend to be overlooked in other books such as missing/censored data, correlation structure of data, heterogeneous data, and complex causal relationships. These issues characterize a large proportion of ecological data, but most ecologists' training in traditional statistics simply does not provide them with adequate preparation to handle the associated challenges. Uniquely, Ecological Statistics highlights the underlying links among many statistical approaches that attempt to tackle these issues. In particular, it gives readers an introduction to approaches to inference, likelihoods, generalized linear (mixed) models, spatially or phylogenetically-structured data, and data synthesis, with a strong emphasis on conceptual understanding and subsequent application to data analysis.

Written by a team of practicing ecologists, mathematical explanations have been kept to the minimum necessary. This user-friendly textbook will be suitable for graduate students, researchers, and practitioners in the fields of ecology, evolution, environmental studies, and computational biology who are interested in updating their statistical tool kits. A companion web site provides example data sets and commented code in the R language.