Patterns of Grewia (Malvaceae) diversity across geographic scales in Africa and Madagascar.

BACKGROUND AND AIMS

Quantifying spatial species richness is useful to describe biodiversity patterns across broad geographic areas, especially in large, poorly known plant groups. We explore patterns and predictors of species richness across Africa in one such group; the paleotropical genus Grewia L. (Malvaceae).

METHODS

Grewia species richness was quantified by extracting herbarium records from GBIF and Tropicos and creating geographic grids at varying spatial scales. We assessed predictors of species richness using spatial regression models with 30 environmental variables. We explored species co-occurrence in Madagascar at finer resolutions using Schoener's index, and compared species' range sizes and IUCN status among ecoregions. Lastly, we derived a trait matrix for a subset of species found in Madagascar to characterize morphological diversity across space.

KEY RESULTS

Grewia species occur in 50 countries in Africa, with the highest number of species in Madagascar (93, with 80 species endemic). Species richness is highest in Madagascar, with up to 23 Grewia species in a grid cell, followed by coastal Tanzania/Kenya (up to 13 species), and northern South Africa and central Angola (11 species each). Across Africa, higher species richness was predicted by variables related to aridity. In Madagascar, a greater range in environmental variables best predicted species richness, consistent with geographic grid cells of highest species richness occurring near biome/ecoregion transitions. In Madagascar we also observe increasing dissimilarity in species composition with increasing geographic distance.

CONCLUSIONS

The spatial patterns and underlying environmental predictors that we uncover in Grewia represent an important step in our understanding of plant distribution and diversity patterns across Africa. Madagascar boasts nearly twice the Grewia species richness, compared to the second most species-rich country in Africa, which might be explained by complex topography and environmental conditions across small spatial scales.

Informations de copyright

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