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The Potential for Misleading Correlations in Single-factor Analysis of Complex Gradients : Volume 9, Issue 1 (21/12/2009)

By He, W.-m.

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Book Id: WPLBN0004023414
Format Type: PDF Article :
File Size: Pages 5
Reproduction Date: 2015

Title: The Potential for Misleading Correlations in Single-factor Analysis of Complex Gradients : Volume 9, Issue 1 (21/12/2009)  
Author: He, W.-m.
Volume: Vol. 9, Issue 1
Language: English
Subject: Science, Ecology
Collections: Periodicals: Journal and Magazine Collection, Copernicus GmbH
Publication Date:
Publisher: Copernicus Gmbh, Göttingen, Germany
Member Page: Copernicus Publications


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Callaway, R. M., & He, W. (2009). The Potential for Misleading Correlations in Single-factor Analysis of Complex Gradients : Volume 9, Issue 1 (21/12/2009). Retrieved from

Description: State Key Lab of Vegetation and Environmental Change, Inst. of Botany, Chinese Academy of Sciences, 100093 Beijing, China. Gradient analysis is an important tool for describing patterns in ecology. Natural environmental gradients are complex combinations of factors, suggesting that gradientsshould, when possible, be analyzed in multi-factorial ways. We searched papers published in Ecology, Global Change Biology, Journal of Ecology, Oecologia, Oikos, and Journal of Vegetation Science from January 2001 to December 2005, and found 133 papers matching two keywords: “gradient analysis” and “environmental gradient”. Of these, 86 utilized single-factor correlation analyses between ecological entities and natural environmental gradients. Thus the use of single-factor correlations in studies of natural environmental gradients is widespread despite the potential of this approach to overemphasize the importance of the particular factor chosen. We reanalyzed a data set from the literature, provided a example of contrasting analyses, and analyzed our own data with both single- and multiple-factor analyses to demonstrate how single-factor correlation can result in correlations that provide incomplete analysis. Integrated multi-factor approaches to studying natural environmental gradients cannot solve all analytical problems when two or more important variables are correlated, but are likely to better test the relative importance of factors driving ecological patterns.

The potential for misleading correlations in single-factor analysis of complex gradients


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