Mountain regions are centres of biodiversity endemism at a global scale but the role of arid- zone mountain ranges in shaping biodiversity patterns is poorly understood. Focusing on three guilds of taxa from a desert upland refugium in Australia, we sought to determine: 1) the relative extent to which climate, terrain or geological substrate predict endemism, and 2) whether patterns of endemism are complimentary across broad taxonomic guilds. We mapped regional endemism for plants, land snails and vertebrates using combined Species Distribution Models (SDMs) for all endemic taxa (n=82). We then modelled predictors of endemism using Generalised Additive Models (GAMs) and geology, terrain and climate variables. We tested for the presence of inter- and intraguild hotspots of endemism. Many individual plant and land snail taxa were tightly linked with geology, corresponding to small distributions. Conversely, most vertebrate taxa were not constrained to specific geological substrates and occurred over larger areas. However, across all three guilds, climate was the strongest predictor of regional endemism, particularly for plants wherein discrete hotspots of endemism were buffered from extreme summer temperatures. Land snail and vertebrate endemism peaked in areas with the highest precipitation in the driest times of the year. Hotspots of endemism within each guild poorly predicted endemism in other guilds. We found an overarching signal that climatic gradients play a dominant role in the persistence of endemic taxa in an arid-zone mountain range system. An association with higher rainfall and cooler temperatures indicates that continuing trends towards hotter and drier climates may lead to range contractions in this, and potentially other, arid-zone mountain biotas. Contrasting patterns of endemism across guilds highlight the need to couple comprehensive regional planning for the protection of climate refugia, with targeted management of more localised and habitat specialist taxa.

Please refer to paper

The csv file contains all species location data used to generate SDMs or distribution polygons.

The R code was used for GAM analysis for regional endemism.