Scale dependence of vegetation–environment relationships: a meta‐analysis of multivariate data

  • Andrew Siefert
    Department of Biology Syracuse University 107 College Place Syracuse NY 13244 USA
  • Catherine Ravenscroft
    Department of Biology Syracuse University 107 College Place Syracuse NY 13244 USA
  • David Althoff
    Department of Biology Syracuse University 107 College Place Syracuse NY 13244 USA
  • Juan C. Alvarez‐Yépiz
    College of Environmental Science and Forestry State University of New York One Forestry Drive Syracuse NY 13210 USA
  • Benjamin E. Carter
    Department of Biology Syracuse University 107 College Place Syracuse NY 13244 USA
  • Kelsey L. Glennon
    Department of Biology Syracuse University 107 College Place Syracuse NY 13244 USA
  • J. Mason Heberling
    Department of Biology Syracuse University 107 College Place Syracuse NY 13244 USA
  • In Su Jo
    Department of Biology Syracuse University 107 College Place Syracuse NY 13244 USA
  • Alyssa Pontes
    Department of Biology Syracuse University 107 College Place Syracuse NY 13244 USA
  • Amy Sauer
    Department of Biology Syracuse University 107 College Place Syracuse NY 13244 USA
  • Adam Willis
    Department of Biology Syracuse University 107 College Place Syracuse NY 13244 USA
  • Jason D. Fridley
    Department of Biology Syracuse University 107 College Place Syracuse NY 13244 USA

書誌事項

公開日
2012-02-29
権利情報
  • http://onlinelibrary.wiley.com/termsAndConditions#vor
DOI
  • 10.1111/j.1654-1103.2012.01401.x
公開者
Wiley

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説明

<jats:title>Abstract</jats:title><jats:sec><jats:title>Questions</jats:title><jats:p>How does spatial scale (extent and grain) influence the relative importance of different environmental factors as determinants of plant community composition? Are there general scale thresholds that mark the transition from primarily edaphic to primarily climatic control of plant communities?</jats:p></jats:sec><jats:sec><jats:title>Location</jats:title><jats:p>Global.</jats:p></jats:sec><jats:sec><jats:title>Methods</jats:title><jats:p>We surveyed the empirical literature and identified 89 analyses from 63 published studies that analysed vegetation–environment relationships involving at least two categories of predictor variables (edaphic, climatic, topographic, biotic, spatial or disturbance‐related). For each analysis, we identified the primary predictor variable (i.e. the variable that explained the most variation in community composition) and the relative effect size of the best predictor variable from each category. We defined ‘primacy’ as the proportion of times a variable category was primary when it was measured, and analysed primacy and the relative effect size of each category as a function of spatial extent and grain. We also analysed the subset of studies that measured both edaphic and climatic variables to identify spatial extent and grain thresholds for the primacy of these factors.</jats:p><jats:p>We surveyed the empirical literature and identified 89 analyses from 63 published studies that analysed vegetation–environment relationships involving at least two categories of predictor variables (edaphic, climatic, topographic, biotic, spatial or disturbance‐related). For each analysis, we identified the primary predictor variable (i.e. the variable that explained the most variation in community composition) and the relative effect size of the best predictor variable from each category. We defined ‘primacy’ as the proportion of times a variable category was primary when it was measured, and analysed primacy and the relative effect size of each category as a function of spatial extent and grain. We also analysed the subset of studies that measured both edaphic and climatic variables to identify spatial extent and grain thresholds for the primacy of these factors.</jats:p></jats:sec><jats:sec><jats:title>Results</jats:title><jats:p>Edaphic variables had the highest primacy in the overall data set and at fine grain sizes (<200 m<jats:sup>2</jats:sup>), but there were no strong trends in primacy across studies of varying spatial extent. We detected trends of increasing relative effect size of climatic variables with increasing spatial extent, and decreasing relative effect size of edaphic variables with increasing spatial grain, although these patterns were not statistically significant. Among studies that measured both edaphic and climatic variables, the importance of climate factors relative to edaphic factors increased with increasing spatial extent and grain, with scale thresholds of 1995 km<jats:sup>2</jats:sup> for extent and 295 m<jats:sup>2</jats:sup> for grain.</jats:p></jats:sec><jats:sec><jats:title>Conclusions</jats:title><jats:p>Our study illustrates that vegetation–environment relationships depend on the spatial scale (extent and grain) of observation and provide empirical support for the view that there is a transition from a primarily edaphic influence to a primarily climatic influence on plant community composition with increasing spatial scale.</jats:p></jats:sec>

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