Abstract
Abstract. 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.
Highlights
Gradient analysis is an important tool for describing patterns in ecology
Gradient analysis is an essential tool in ecology for demonstrating patterns at the scales of individuals, populations, communities, ecosystems, landscapes, and the globe (Whittaker 1967, Austin 1985, Körner et al 1988, 1991, De’ath 1999, Ter Braak and Prentice 2004, Hawkins and Agrawal 2005, Crain and Bertness 2006, Johnson et al 2006)
Natural environmental gradients studied by ecologists are complex combinations of multiple factors
Summary
We examined papers that had been published in Ecology, Global Change Biology, Journal of Ecology, Oecologia, Oikos, and Journal of Vegetation Science from January 2001 through December 2005. We determined the number of papers which utilized single-factor correlations, but were designed to better utilize multiple-factor analyses. The first search located 718 papers, but these included very high numbers of studies that utilized artificial gradients, defined as any single-factor gradients under artificially controlled conditions. Of the 133 papers we located, 86 utilized simple, single-factor correlation analyses between ecological entities (e.g. leaf traits, population traits, and productivity) and environmental factors (e.g. latitude, altitude, temperature, and precipitation). These papers examined the effects of each environmental factor on particular ecological entities separately, even though these factors are known to strongly co-vary. All studies had the potential to apply multi-factorial statistical techniques to the complex patterns of co-variation among suites of variables, with the potential to assign a more appropriate importance to each particular variable
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