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| NUMERICAL ECOLOGY, 20
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To order this title, and for more information, click here
Second Edition
By
P. Legendre, Département de Sciences Biologiques, Université de Montréal, H3C 3J7, Québec, Canada
L. Legendre, Département de Biologie, Université Laval, Québec, G1K 7P4, Canada
Included in series
Developments in Environmental Modelling, 20
Description
The book describes and discusses the numerical methods which are successfully being used for analysing ecological data, using a clear
and comprehensive approach. These methods are derived from the fields of mathematical physics, parametric and nonparametric statistics,
information theory, numerical taxonomy, archaeology, psychometry, sociometry, econometry and others. Compared to the first edition of
Numerical Ecology, this second edition includes three new chapters, dealing with the analysis of semiquantitative data, canonical analysis
and spatial analysis. New sections have been added to almost all other chapters. There are sections listing available computer programs
and packages at the end of several chapters. As in the previous English and French editions, there are numerous examples from the ecological
literature, and the choice of methods is facilitated by several synoptic tables.
Audience
For practicing ecologists, graduate students and professional researchers.
Contents
Chapter headings and selected parts:
Preface.
Complex Ecological Data Sets.
Numerical analysis of ecological
data. Statistical testing by permutation. Ecological descriptors.
Matrix Algebra: A Summary.
The ecological data matrix.
Vectors and scaling. Eigenvalues and eigenvectors.
Dimensional Analysis in Ecology.
Fundamental principles and the Pi
theorem. Scale factors and models.
Multidimensional Quantitative Data.
Multidimensional variables and dispersion matrix.
Multinormal distribution. Tests of normality and multinormality.
Multidimensional Semiquantitative data.
Nonparametric
statistics. Quantitative, semiquantitative, and qualitative multivariates.
Multidimensional Qualitative Data.
Multiway
contingency tables. Species diversity.
Ecological Resemblance.
The basis for clustering and ordination. Association
coefficients. R mode: coefficients of dependence.
Cluster Analysis.
The basic model: single linkage clustering. Cophenetic
matrix and ultrametric property. Hierarchical divisive clustering.
Ordination in Reduced Space.
Projecting data sets
in a few dimensions. Principal component analysis (PCA). Nonmetric multidimensional scaling (MDS).
Interpretation of Ecological
Structures.
Ecological structures. The mathematics of ecological interpretation. The 4th-corner problem.
Canonical Analysis.
Redundancy analysis (RDA). Canonical correspondence analysis (CCA). Canonical analysis of species data.
Ecological Data Series.
Characteristics of data series and research objectives. Trend extraction and numerical filters. Periodic variabilty: spectral analysis.
Detection of discontinuities on multivariate series. Box-Jenkins models.
Spatial Analysis.
Unconstrained and constrained
ordination maps. Causal modelling: partial canonical analysis. Causal modelling: partial Mantel analysis.
Bibliography. Tables.
Subject index.
| Bibliographic details |
Paperback, 870 pages, A limited number of inspection copies of this book are available for qualified course instructors. Requests for an Examination Copy (please
provide full course details) should be sent via e-mail to: d.martin@elsevier.com
, publication date: NOV-1998
ISBN-13: 978-0-444-89250-8
ISBN-10: 0-444-89250-8
Imprint: ELSEVIER
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| Price and Ordering |
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Last update: 10 Sep 2009
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