Département des Sciences Biologiques
C.P. 6128 succ. "Centre-Ville",
Montréal, Québec, Canada H3C 3J7
English version
Numerical Ecology
Fonctions R
BIO 2041: Biostatistique I
BIO 6077: Analyse quantitative des données biologiques
Tirés à parts / Reprints
Logiciels et Jeux de Données / Computer Programs and Datasets
Le personnel du département
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Contents | Description
Contents
- Complex ecological data sets, including: Autocorrelation and spatial structure. Statistical testing by permutation. Computers. Descriptors. Coding. Missing data.
- Matrix algebra: a summary
- Dimensional analysis in ecology
- Multidimensional quantitative data
- Multidimensional semiquantitative data
- Multidimensional qualitative data
- Ecological resemblance, including: Review of similarity, distance, and R-mode coefficients. Computer programs and packages.
- Cluster analysis, including: Agglomerative and divisive methods. K-means partitioning. Cophenetic matrix and ultrametric property. Reversals. TWINSPAN. Species clustering: biological associations. Indicator species. Seriation. Clustering statistics. Cluster validation. Choice of a clustering method.
- Ordination in reduced space, including: Principal component analysis (PCA). Principal coordinate analysis (PCOA). Nonmetric multidimensional scaling (MDS). Correspondence analysis (CA). Factor analysis.
- Interpretation of ecological structures, including: Review of regression methods. Path analysis. Matrix comparison: Mantel tests, ANOSIM, Procrustes analysis, and 4th-corner statistics.
- Canonical analysis, including: Redundancy analysis (RDA). Canonical correspondence analysis (CCA). Partial RDA and CCA. Tests of significance in RDA and CCA. Canonical correlation analysis (CCORA). Discriminant analysis. Canonical analysis of species data.
- Ecological data series: time series analysis, including: Trend extraction and numerical filters. Correlogram. Periodogram. Spectral analysis. Detection of discontinuities in multivariate series. Box-Jenkins models. Computer programs.
- Spatial analysis, including: Scale. Structure functions (spatial correlograms, variograms, multivariate Mantel correlogram). Mapping. Patches and boundaries. Connection networks. Unconstrained and constrained ordination maps. Causal modelling through partial canonical analysis and partial Mantel analysis. Computer programs.
Description
This second English edition of Numerical ecology is a revised and largely expanded translation of the second edition of Écologie numérique (Legendre & Legendre, 1984). Compared to the first English edition (1983), there are three new chapters, dealing with the analysis of semiquantitative data (Chapter 5), canonical analysis (Chapter 11), and spatial analysis (Chapter 13). New sections have been added to almost all other chapters. These include, for example, new sections (numbers given in parentheses) on: autocorrelation (1.1), statistical testing by permutation (1.2), coding (1.5), missing data (1.6), singular value decomposition (2.11), multiway contingency tables (6.3), cophenetic matrix and ultrametric property (8.3), reversals (8.6), partitioning by K-means (8.8), cluster validation (8.12), a review of regression methods (10.3), path analysis (10.4), a review of matrix comparison methods (10.5), the 4th-corner problem (10.6), several new methods for the analysis of data series (12.3-12.5), detection of discontinuities in multivariate series (12.6), and Box-Jenkins models (12.7). 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. Additional information is available from the Elsevier WWWeb site:http://www.elsevier.com/wps/find/bookdescription.cws_home/601498/descriptionElsevier offers a Text Book Inspection Service for this book.