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Scale dependence of vegetation–environment relationships: a meta‐analysis of multivariate data
Author(s) -
Siefert Andrew,
Ravenscroft Catherine,
Althoff David,
AlvarezYépiz Juan C.,
Carter Benjamin E.,
Glen Kelsey L.,
Heberling J. Mason,
Jo In Su,
Pontes Alyssa,
Sauer Amy,
Willis Adam,
Fridley Jason D.
Publication year - 2012
Publication title -
journal of vegetation science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.1
H-Index - 115
eISSN - 1654-1103
pISSN - 1100-9233
DOI - 10.1111/j.1654-1103.2012.01401.x
Subject(s) - edaphic , spatial ecology , vegetation (pathology) , ecology , scale (ratio) , variable (mathematics) , multivariate statistics , plant community , geography , spatial variability , physical geography , disturbance (geology) , statistics , mathematics , biology , cartography , species richness , soil water , medicine , mathematical analysis , pathology , paleontology
Questions 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? Location Global. Methods 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. 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. Results Edaphic variables had the highest primacy in the overall data set and at fine grain sizes (<200 m 2 ), 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 2 for extent and 295 m 2 for grain. Conclusions 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.