Show simple item record Cramer, Michael D. Verboom, G. Anthony
dc.coverage.spatial South Africa
dc.coverage.spatial Africa 2016-12-07T12:22:35Z 2016-12-07T12:22:35Z 2016-12-02
dc.identifier doi:10.5061/dryad.34c1r
dc.identifier.citation Cramer MD, Verboom GA (2017) Measures of biologically relevant environmental heterogeneity improve prediction of regional plant species richness. Journal of Biogeography 44(3): 579-591.
dc.identifier.issn 0305-0270
dc.description 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.
dc.relation.haspart doi:10.5061/dryad.34c1r/1
dc.relation.isreferencedby doi:10.1111/jbi.12911
dc.subject biodiversity
dc.subject niche
dc.subject resource
dc.subject ecosystems
dc.subject biome
dc.subject productivity
dc.subject speciation
dc.subject extinction
dc.title Data from: Measures of biologically relevant environmental heterogeneity improve prediction of regional plant species richness
dc.type Article
dwc.ScientificName Tracheophytes
dc.contributor.correspondingAuthor Cramer, Michael D.
prism.publicationName Journal of Biogeography
dryad.dansTransferDate 2018-05-12T08:27:48.209+0000
dryad.dansArchiveDate 2018-05-12T10:02:23.910+0000
dryad.dashTransferDate 2019-07-13T05:26:46.818+0000

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Title Modelled vascular plant species richness of South Africa and neighbouring territories
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Description A raster in GeoTiff format at 0.0417° resolution (coordinate reference systems EPSG: 4326) of vascular plant species richness in South Africa, Swaziland and Lesotho, predicted from the full boosted regression tree model. The modelled output includes prediction to areas for which species richness was not included in the data used for model construction (Swaziland and Lesotho). Species richness is expressed as counts per quarter degree square.
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