Ecological data has several special properties: the presence or absence of species on a semi-quantitative abundance scale; non-linear relationships between species and environmental factors; and high inter-correlations among species and among environmental variables. The analysis of such data is important to the interpretation of relationships within plant and animal communities and with their environments. In this corrected version of Data Analysis in Community and Landscape Ecology, without using complex mathematics, the contributors demonstrate the methods that have proven most useful, with examples, exercises and case-studies. Chapters explain in an elementary way powerful data analysis techniques such as logic regression, canonical correspondence analysis, and kriging.
Growth in the field of landscape ecology has included the development of methods and results that can be applied to an impressive range of environmental issues. This book addresses a broad spectrum...
This important new work--the first of its kind--focuses on the distribution patterns of landscape elements or ecosystems; the flows of animals, plants, energy, mineral nutrients and water; and the...
This book introduces the ade4 package for R which provides multivariate methods for the analysis of ecological data. It is implemented around the mathematical concept of the duality diagram, and...