Abstract
This chapter shows how direct and indirect gradient analysis can be handled in the ade4 package, with a special emphasis on three direct ordination methods: Coinertia Analysis, Redundancy Analysis and Canonical Correspondence Analysis.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
ter Braak C (1986) Canonical correspondence analysis: a new eigenvector technique for multivariate direct gradient analysis. Ecology 67:1167–1179
ter Braak CJF (1987) The analysis of vegetation-environment relationships by canonical correspondence analysis. Vegetatio 69:69–77
ter Braak CJF, Verdonschot PFM (1995) Canonical correspondence analysis and related multivariate methods in aquatic ecology. Aquat Sci 57:255–289
Dolédec S, Chessel D (1994) Co-inertia analysis: an alternative method for studying species-environment relationships. Freshw Biol 31:277–294
Dormann CF, Elith J, Bacher S, Buchmann C, Carl G, Carré G, Marquéz JRG, Gruber B, Lafourcade B, Leitão PJ, Münkemüller T, McClean C, Osborne PE, Reineking B, Schröder B, Skidmore AK, Zurell D, Lautenbach S (2013) Collinearity: a review of methods to deal with it and a simulation study evaluating their performance. Ecography 36:27–46
Dray S, Chessel D, Thioulouse J (2003) Co-inertia analysis and the linking of ecological data tables. Ecology 84:3078–3089
Escoufier Y (1973) Le traitement des variables vectorielles. Biometrics 29:750–760
Gimaret-Carpentier C, Dray S, Pascal JP (2003) Broad-scale biodiversity pattern of the endemic tree flora of the Western Ghats (India) using canonical correlation analysis of herbarium records. Ecography 26:429–444
Green RH (1971) A multivariate statistical approach to the Hutchinsonian niche: bivalve molluscs of Central Canada. Ecology 52:543–556
Green RH (1974) Multivariate niche analysis with temporally varying environmental factors. Ecology 55:73–83
Hotelling H (1936) Relations between two sets of variates. Biometrika 28:321–377
Lebreton JD, Chessel D, Prodon R, Yoccoz NG (1988a) L’analyse des relations espèces-milieu par l’analyse canonique des correspondances. I. Variables de milieu quantitatives. Acta Oecol Oecol Generalis 9(1):53–67
Lebreton JD, Chessel D, Richardot-Coulet M, Yoccoz NG (1988b) L’analyse des relations espèces-milieu par l’analyse canonique des correspondances. II. Variables de milieu qualitatives. Acta Oecol Oecol Generalis 9(2):137–151
Miller JK (1975) The sampling distribution and a test for the significance of the bimultivariate redundancy statistic: a Monte Carlo study. Multivar Behav Res 10(2):233–244
Miller JK, Farr SD (1971) Bimultivariate redundancy: a comprehensive measure of interbattery relationship. Multivar Behav Res 6(3):313–324
Obadia J (1978) L’analyse en composantes explicatives. Revue de Statistique Appliquée 26(4): 5–28
Pélissier R, Couteron P, Dray S, Sabatier D (2003a) Consistency between ordination techniques and diversity measurements: two alternative strategies for species occurrence data. Ecology 84:242–251
Peres-Neto PR, Legendre P, Dray S, Borcard D (2006) Variation partitioning of species data matrices: estimation and comparison of fractions. Ecology 87:2614–2625
Rao CR (1964) The use and interpretation of Principal Component Analysis in applied research. Sankhya: Indian J Stat Ser A 26:329–358
van den Wollenberg AL (1977) Redundancy analysis, an alternative for canonical analysis. Psychometrika 42(2):207–219
Author information
Authors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer Science+Business Media, LLC, part of Springer Nature
About this chapter
Cite this chapter
Thioulouse, J., Dray, S., Dufour, AB., Siberchicot, A., Jombart, T., Pavoine, S. (2018). Description of Species-Environment Relationships. In: Multivariate Analysis of Ecological Data with ade4. Springer, New York, NY. https://doi.org/10.1007/978-1-4939-8850-1_8
Download citation
DOI: https://doi.org/10.1007/978-1-4939-8850-1_8
Published:
Publisher Name: Springer, New York, NY
Print ISBN: 978-1-4939-8848-8
Online ISBN: 978-1-4939-8850-1
eBook Packages: Mathematics and StatisticsMathematics and Statistics (R0)