Extinction risk and diversification are linked in a plant biodiversity hotspot.

It is widely recognized that we are entering an extinction event on a scale approaching the mass extinctions seen in the fossil record. Present-day rates of extinction are estimated to be several orders of magnitude greater than background rates and are projected to increase further if current trends continue. In vertebrates, species traits, such as body size, fecundity, and geographic range, are important predictors of vulnerability. Although plants are the basis for life on Earth, our knowledge of plant extinctions and vulnerabilities is lagging. Here, we disentangle the underlying drivers of extinction risk in plants, focusing on the Cape of South Africa, a global biodiversity hotspot. By comparing Red List data for the British and South African floras, we demonstrate that the taxonomic distribution of extinction risk differs significantly between regions, inconsistent with a simple, trait-based model of extinction. Using a comprehensive phylogenetic tree for the Cape, we reveal a phylogenetic signal in the distribution of plant extinction risks but show that the most threatened species cluster within short branches at the tips of the phylogeny--opposite to trends in mammals. From analyzing the distribution of threatened species across 11 exemplar clades, we suggest that mode of speciation best explains the unusual phylogenetic structure of extinction risks in plants of the Cape. Our results demonstrate that explanations for elevated extinction risk in plants of the Cape flora differ dramatically from those recognized for vertebrates. In the Cape, extinction risk is higher for young and fast-evolving plant lineages and cannot be explained by correlations with simple biological traits. Critically, we find that the most vulnerable plant species are nonetheless marching towards extinction at a more rapid pace but, surprisingly, independently from anthropogenic effects. Our results have important implications for conservation priorities and cast doubts on the utility of current Red List criteria for plants in regions such as the Cape, where speciation has been rapid, if our aim is to maximize the preservation of the tree-of-life.

Alien phytogeographic regions of southern Africa: numerical classification, possible drivers, and regional threats.

The distributions of naturalised alien plant species that have invaded natural or semi-natural habitat are often geographically restricted by the environmental conditions in their new range, implying that alien species with similar environmental requirements and tolerances may form assemblages and characterise particular areas. The aim of this study was to use objective numerical techniques to reveal any possible alien phytogeographic regions (i.e. geographic areas with characteristic alien plant assemblages) in southern Africa. Quarter degree resolution presence records of naturalised alien plant species of South Africa, Lesotho, Swaziland, Namibia and Botswana were analysed through a divisive hierarchical classification technique, and the output was plotted on maps for further interpretation. The analyses revealed two main alien phytogeographic regions that could be subdivided into eight lower level phytogeographic regions. Along with knowledge of the environmental requirements of the characteristic species and supported by further statistical analyses, we hypothesised on the main drivers of alien phytogeographic regions, and suggest that environmental features such as climate and associated biomes were most important, followed by human activities that modify climatic and vegetation features, such as irrigation and agriculture. Most of the characteristic species are not currently well-known as invasive plant species, but many may have potential to become troublesome in the future. Considering the possibility of biotic homogenization, these findings have implications for predicting the characteristics of the plant assemblages of the future. However, the relatively low quality of the dataset necessitates further more in-depth studies with improved data before the findings could be directly beneficial for management.