1996
DOI: 10.2307/3236330
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Are ordination and constrained ordination alternative or complementary strategies in general ecological studies?

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Cited by 235 publications
(104 citation statements)
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“…We applied Detrended Correspondence Analysis (DCA) to analyze variation in species compositions, species turnover (from the main matrix) and struc-tural and environmental variables (from the second matrix). The efficacy of this technique has been well established (Okland 1996). Using PC-ORD 6.0 MjM Software (Gleneden Beach, OR, USA), we carried out detrending by segments (default of 26 segments) and did not downweight rare species, because important indicator tree species may be rare in the data set.…”
Section: Fine-scale Ecological Niche Analysismentioning
confidence: 99%
“…We applied Detrended Correspondence Analysis (DCA) to analyze variation in species compositions, species turnover (from the main matrix) and struc-tural and environmental variables (from the second matrix). The efficacy of this technique has been well established (Okland 1996). Using PC-ORD 6.0 MjM Software (Gleneden Beach, OR, USA), we carried out detrending by segments (default of 26 segments) and did not downweight rare species, because important indicator tree species may be rare in the data set.…”
Section: Fine-scale Ecological Niche Analysismentioning
confidence: 99%
“…The two methods were applied to data matrices for all values. Parallel ordination offers an opportunity for controlling if the two different methods reveal the same structure, which is regarded as an indication that the true underlying structure has been found [18]. Congruence between parallel DCA and GNMDS ordinations (i.e., ordinations based on a specific range of the abundance scale) was assessed by means of Procrustes analysis [38,40], and by calculating pairwise Kendall's rank correlation coefficients between corresponding DCA and GNMDS axes.…”
Section: Discussionmentioning
confidence: 99%
“…Like other models for relating response variables to independent variables, constrained ordination thus only summarises variation in species composition that is explained by the supplied variables. This has several important implications [18]: (1) compositional variation due to unmeasured, but important, variables is lost in a black box of "unexplained variation"; (2) compositional variation not linearly related to the supplied variables is lost as residual variation; and (3) being (linear) combinations of environmental gradients, axes of direct gradient analysis are complex-gradients, not gradients in species composition. Økland [18] therefore argues that indirect gradient analysis should be used to generate hypotheses about species-environment relationships, while direct gradient analysis should be used for testing hypotheses or for partitioning the variation in species abundances in a set of sites or on sets of explanatory variables [18].…”
Section: Indirect Versus Direct Gradient Analysis and Weightmentioning
confidence: 99%
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