Numerical ecology
Author(s)
Bibliographic Information
Numerical ecology
（Developments in environmental modelling, 20）
Elsevier, 1998
2nd English ed
- : hbk
- : pbk.: alk.
- Other Title
-
Écologie numérique
Available at / 19 libraries
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Obihiro University of Agriculture and Veterinary Medicine Library図
: pbk.: alk.468/L52020430337,
pbk. : alk. paper043033 -
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Note
Rev. ed. of: Ecologie numérique / Louis Legendre. 1983
Includes bibliographical references(p. [787]-832) and index
Description and Table of Contents
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.
Table of 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.
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