The origins and maintenance of global species endemism. Issue 2 (27th November 2018)

• Record Type: Journal Article
• Authors: Zuloaga, Juan; Currie, David J.; Kerr, Jeremy T.
• Editors: Pither, Jason
• Is Part Of: Global ecology & biogeography. Volume 28:Issue 2(2019)
• Page Start: 170
• Page End: 183
• Publication Date: 2018-11-27
• Subjects: amphibians -- climate seasonality -- climate stability -- climate velocity -- endemic species -- endemism -- macroecology -- mammals -- spatial heterogeneity -- species richness; Ecology -- Periodicals; Biogeography -- Periodicals; Biodiversity -- Periodicals; Macroevolution -- Periodicals; 577
• DOI: 10.1111/geb.12834
• Languages: English
• ISSNs: 1466-822X

Abstract

Abstract: Aim: We test macroecological hypotheses ( H1: long‐term climate stability; H2: climate seasonality; H3: climate distinctiveness or rarity; and, H4: spatial heterogeneity in contemporary climate, topography or habitat ) proposed to explain broad‐scale patterns of total species endemism. Location: Continental areas worldwide and zoogeographical realms. Methods: Using species distribution maps for mammals and amphibians, we calculated five metrics of species endemism, based on inverse and median range size, and range size cut‐offs. We performed multi‐model averaging. We tested the accuracy of fitted models using cross‐validation, comparing observed versus predicted values of endemism among zoogeographical realms. Results: Model averaging showed that species endemism for amphibians and mammals was statistically related to all set of predictors ( H1, H2, H4 and richness), except for climate distinctiveness ( H3 ). Effect sizes for spatial heterogeneity were larger and more consistent among zoogeographical realms than the effect sizes of climate stability. The effect of species richness on species endemism varies widely and depends on the metric of endemism and taxonomic group used in the analysis. Cross‐validation across all zoogeographical realms showed that predictions of endemism systematically fail for both taxa. In most cases, low to moderate endemism is predicted reasonably well. However, areas with high numbers of endemic species are systematically under‐predicted. Main conclusions: Our results are not consistent with any of the processes hypothesized to create and maintain global patterns of endemism. Although we found statistically significant relationships, they failed the stronger test of a causal relationship: accurate prediction in independent data. The inconsistent effect of richness in our models suggests that patterns of endemism are not driven by the same variables as total richness. Patterns of endemism have no consistent relationships with climatic stability among zoogeographical realms, so suggestions that endemism reflect climatic stability are likely due to collinearity with other factors, especially spatial heterogeneity.