Aim: Given the importance of environmental heterogeneity as a driver of species richness through its effects on species diversification and coexistence, we asked whether the dramatic difference in species richness per unit area between two similar Mediterranean-type biodiversity hotspots is explained by differences in environmental heterogeneity. Location:The Greater Cape Floristic Region, South Africa (GCFR) and Southwest Australian Floristic Region (SWAFR). Taxon: Vascular plants (tracheophytes).Methods: Comparable, geospatially explicit environmental and species occurrence data were obtained for both regions and used to generate environmental heterogeneity and species richness raster layers. Heterogeneity in multiple environmental variables and species richness per unit area were compared between the two regions at a range of spatial scales. At each scale, richness was also regressed against these individual axes and against a major axis of heterogeneity, derived by principal component analysis (PCA). Results:The GCFR is generally more environmentally heterogeneous and species-rich than the SWAFR. Species richness per unit area is significantly related to the major axis of heterogeneity across both regions, the latter describing c. 38%-50% of overall heterogeneity, the slope of this relationship differing between the two regions only at the finest spatial scale. Multivariate regressions, and regressions against the first axes of the PCAs (PC1), revealed variations in the dependence of species richness on environmental heterogeneity between the two regions.Main conclusions: Notwithstanding some region-specific effects, we present evidence of a common positive relationship between floristic richness and environmental heterogeneity across the GCFR and SWAFR. This is dependent on spatial scale, being strongest at the coarsest level of sampling. The generally greater richness per unit area of the GCFR compared to the SWAFR is thus explained by the former's generally greater environmental heterogeneity and is concordant with its greater levels of floristic turnover.

Aim: High-resolution spatial soil data are crucial to species distribution modelling for fundamental research and conservation planning. Recent globally modelled soil layers (e.g. SoilGrids) have transformed distribution modelling, but may fail to represent regional soil characteristics accurately. We hypothesize that in the Cape biodiversity hotspot of South Africa, the use of global soil layers has led to underestimation of the importance of edaphic factors as determinants of species' and vegetation distributions. We present a series of new, regionally modelled layers to address this deficiency. Location: Greater Cape Floristic Region (GCFR, South Africa). Methods:We georeferenced edaphic characteristics from literature and other sources and used boosted regression trees (BRT) to associate edaphic characteristics with spatially explicit topographic, climatic, soil texture and biotic variables. Multinomial BRTs were used to predict mapped vegetation types from the collated edaphic and other data.Results: BRTs reliably predicted pH (92% of variance), Na (87%), K (85%), electrical conductivity (81%) and P (73%), but were less accurate for total N (55%) and total C (61%), for which data were sparser. Soil clay and pH values differed markedly in range and in spatial variation from those in SoilGrids. Using our new edaphic layers, we were able to accurately predict spatial distributions of vegetation types within the GCFR (multi-class AUC = 0.96). The multinomial BRT predicted vegetation less well when based on SoilGrids data alone (AUC = 0.84). Main conclusions:The more faithful representation of soil properties in our model is attributable both to its use of ca. 10-fold more samples, and to its regional focus. Our model of edaphic characteristics captures important edaphic variability that is vital for understanding plant and consequently faunal distributions, with wide-ranging conservation implications. Ongoing development of global syntheses of soil data requires more samples, especially in areas with high spatial heterogeneity and extreme edaphic conditions.

The predominantly austral genus Schoenus L. is the largest genus in tribe Schoeneae and one of the ten most species-rich Cyperaceae genera, with over 150 accepted species found mostly in Australia, New Zealand, southeast Asia, and southern Africa. Here, we use data based on two nuclear and three plastid DNA regions to present one of the most comprehensive phylogenetic reconstructions of a genus in Cyperaceae to date, covering over 70% of described species of Schoenus. After recent taxonomic realignments in the last 4 years have both added and removed species from the genus, we show that Schoenus is now monophyletic. In addition, our results indicate that Schoenus originated in Western Australia in the Paleocene and eventually dispersed to surrounding continents, but rarely back. The diversification rate of the genus appears to have slightly decreased over time, and there has not been an increase associated with the establishment of the Cape clade endemic to the sclerophyllous fynbos vegetation type, such as has been reported in other plant lineages endemic to the Cape region. These results will serve as a template to understanding the complex patterns of genome size evolution and to untangle drivers of diversification in this genus.

The ongoing drought in the Western Cape of South Africa (2014 to present) has called for an urgent need to improve our understanding of water resources in the area. Rivers within the Western Cape are known to surge rapidly after rainfall events. Such storm-flow in natural river catchments in the Jonkershoek mountains has previously been shown to be driven by displaced groundwater, with less than 5% of rainfall appearing in the storm-flow. However, the origin of storm-flow surges within urban rivers in the region remains unknown. In this study, we used stable isotopes in water to illustrate that at least 90% of water in the Liesbeek River during a storm event was rainwater. There was a strong correlation between storm-flow and rainfall rates (P < 0.001, Pearson’s r = 0.86), as well as between the δ18O and δ2H values of river-water and rainwater (δ18O: Pearson’s r = 0.741 (P = 0.001), δ2H: Pearson’s r = 0.775 (P < 0.001)). Storm-flow within this urban river therefore appears to be driven by overland-flow over the hardened urban catchment, rather than piston-flow as seen in natural catchments. Our results support studies suggesting the Liesbeek River could be a target for stormwater harvesting to augment water resources in the city of Cape Town.

No abstract