Analyzing Ecological Data [Hardcover]

This book provides a practical introduction to analyzing ecological data using real data sets. The first part gives a largely non-mathematical introduction to data exploration, univariate methods (including GAM and mixed modeling techniques), multivariate analysis, time series analysis, and spatial statistics. The second part provides 17 case studies. The case studies include topics ranging from terrestrial ecology to marine biology and can be used as a template for a readers own data analysis. Data from all case studies are available from www.highstat.com. Guidance on software is provided in the book.

This book provides a practical introduction to analyzing ecological data using real data sets. It features 17 case studies covering topics ranging from terrestrial ecology to marine biology and can be used as a template for a readers own data analysis.

'Which test should I apply?' During the many years of working with ecologists, biologists and other environmental scientists, this is probably the question that the authors of this book hear the most often. The answer is always the same and along the lines of 'What are your underlying questions?', 'What do you want to show?'. The answers to these questions provide the starting point for a detailed discussion on the ecological background and purpose of the study. This then gives the basis for deciding on the most appropriate analytical approach. Therefore, a better start? ing point for an ecologist is to avoid the phrase 'test' and think in terms of 'analy? sis'. A test refers to something simple and unified that gives a clear answer in the form of a p-value: something rarely appropriate for ecological data. In practice, one has to apply a data exploration, check assumptions, validate the models, per? haps apply a series of methods, and most importantly, interpret the results in terms of the underlying ecology and the ecological questions being investigated. Ecology is a quantitativeló*