Book ChapterDOI
An evaluation of the relative robustness of techniques for ecological ordination
TLDR
In this article, simulated vegetation data were used to assess the relative robustness of ordination techniques to variations in the model of community variation in relation to environment, and the results clearly demonstrated the ineffectiveness of linear techniques (PCA, PCoA), due to curvilinear distortion.Abstract:
Simulated vegetation data were used to assess the relative robustness of ordination techniques to variations in the model of community variation in relation to environment. The methods compared were local non-metric multidimensional scaling (LNMDS), detrended correspondence analysis (DCA), Gaussian ordination (GO), principal components analysis (PCA) and principal co-ordinates analysis (PCoA). Both LNMDS and PCoA were applied to a matrix of Bray-Curtis coefficients. The results clearly demonstrated the ineffectiveness of the linear techniques (PCA, PCoA), due to curvilinear distortion. Gaussian ordination proved very sensitive to noise and was not robust to marked departures from a symmetric, unimodal response model. The currently popular method of DCA displayed a lack of robustness to variations in the response model and the sampling pattern. Furthermore, DCA ordinations of two-dimensional models often exhibited marked distortions, even when response surfaces were unimodal and symmetric. LNMDS is recommended as a robust technique for indirect gradient analysis, which deserves more widespread use by community ecologists.read more
Citations
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Journal ArticleDOI
phyloseq: an R package for reproducible interactive analysis and graphics of microbiome census data.
Paul J. McMurdie,Susan Holmes +1 more
TL;DR: The phyloseq project for R is a new open-source software package dedicated to the object-oriented representation and analysis of microbiome census data in R, which supports importing data from a variety of common formats, as well as many analysis techniques.
Book ChapterDOI
A Theory of Gradient Analysis
TL;DR: In this article, the authors present a theory of gradient analysis, in which the heuristic techniques are integrated with regression, calibration, ordination and constrained ordination as distinct, well-defined statistical problems.
Journal ArticleDOI
Canonical analysis of principal coordinates: a useful method of constrained ordination for ecology
TL;DR: In this paper, the authors proposed the use of principal coordinate analysis (PCO) followed by either a canonical discriminant analysis (CDA) or a canonical correlation analysis (CCorA) to provide a flexible and meaningful constrained ordination of ecological species abundance data.
Book ChapterDOI
Compositional dissimilarity as a robust measure of ecological distance
TL;DR: In this article, the authors evaluated the robustness of quantitative measures of compositional dissimilarity between sites using extensive computer simulations of species' abundance patterns over one and two dimensional configurations of sample sites in ecological space.
Journal ArticleDOI
Putting things in even better order: the advantages of canonical correspondence analysis'
TL;DR: Canonical Correspondence Analysis (CCA) is quickly becoming the most widely used gradient analysis technique in ecology as discussed by the authors, and it has been shown to perform well with skewed species distributions, with quantitative noise in species abundance data, with samples taken from unusual sampling designs, with highly intercorrelated environmental variables and with situations where not all of the factors determining species composition are known.
References
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Journal ArticleDOI
Multidimensional scaling by optimizing goodness of fit to a nonmetric hypothesis
TL;DR: The fundamental hypothesis is that dissimilarities and distances are monotonically related, and a quantitative, intuitively satisfying measure of goodness of fit is defined to this hypothesis.
Journal ArticleDOI
Nonmetric multidimensional scaling: A numerical method
TL;DR: The numerical methods required in the approach to multi-dimensional scaling are described and the rationale of this approach has appeared previously.
Journal ArticleDOI
Some distance properties of latent root and vector methods used in multivariate analysis
TL;DR: In this paper, the authors derived necessary and sufficient conditions for a solution to exist in real Euclidean space for a multivariate multivariate sample of size n as points P1, P2,..., PI in a Euclidian space and discussed the interpretation of the distance A(Pi, Pj) between the ith and jth members of the sample.
Book ChapterDOI
Detrended correspondence analysis: an improved ordination technique
M. O. Hill,Hugh G. Gauch +1 more
TL;DR: DCA consistently gives the most interpretable ordination results, but as always the interpretation of results remains a matter of ecological insight and is improved by field experience and by integration of supplementary environmental data for the vegetation sample sites.