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Data from: Measures of biologically relevant environmental heterogeneity improve prediction of regional plant species richness

Citation

Cramer, Michael D.; Verboom, G. Anthony (2017), Data from: Measures of biologically relevant environmental heterogeneity improve prediction of regional plant species richness, Dryad, Dataset, https://doi.org/10.5061/dryad.34c1r

Abstract

Aim:Relatively few models of species richness explicitly consider aspects of environmental heterogeneity, other than topographic heterogeneity. We hypothesized that environmental heterogeneity is an important determinant of species richness, especially in ancient climatically stable environments. Location: South Africa, which accommodates a range of biomes that differ strongly in species richness.Methods: We included measures of climatic, edaphic and biotic variables and their spatial heterogeneities in boosted regression tree models of vascular plant species richness. Species richness was assessed using herbarium records per quarter degree square (QDS). To avoid autocorrelation and problems of variable collection rates we iteratively randomly subsampled 20% of the available QDS. We also verified estimates of species richness using an independent data source. Results: The models predicted 68% of QDS species richness and 95% of biome richness. Spatial variability in diurnal temperature range was the strongest predictor of species richness, and inclusion of edaphic and biotic terms as well as spatial heterogeneities increased the explanatory power of the model considerably. Heterogeneity variables featured strongly (8 of 13) as predictors of species richness, but several resource variables (e.g. precipitation, seasonality and evapotranspiration) were also important. The spatial heterogeneities of some variables (e.g. water availability, fire) were related to their mean values, possibly explaining why some global models that have not explicitly included heterogeneity (other than topographic) perform well. Main conclusions: Environmental heterogeneities are important predictors of species richness, yielding accurate predictions even in the absence of any consideration of diversification rates or environmental stability. Greater heterogeneity of some resource variables when limiting, contributed to modelled species richness, adding to understanding of why species richness of some resource-poor Mediterranean-ecosystems is high. We suggest that species richness in ancient, climatically stable Mediterranean-ecosystems is contingent on resource and environmental heterogeneity that has enabled both the diversification and maintenance of regional species richness.

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Location

Africa
South Africa