Historical and future climate change fosters expansion of Australian harvester termites, Drepanotermes
Heimburger, Bastian et al. (2022), Historical and future climate change fosters expansion of Australian harvester termites, Drepanotermes, Dryad, Dataset, https://doi.org/10.5061/dryad.n2z34tn02
Past evolutionary adaptations to Australia’s aridification can help us to understand potential responses of species in the face of global climate change. Here, we focus on the Australian-endemic termite genus Drepanotermes, which is widespread in semi-arid and arid regions of Australia. We used species delineation, phylogenetic inference, and ancestral state reconstruction to investigate the evolution of mound-building and in relation to reconstructed past climatic conditions. Our results suggest that mound-building evolved several times independently, apparently facilitating expansion into tropical and mesic regions of Australia. Strong phylogenetic signal of bioclimatic variables, especially of limiting environmental factors (e.g. precipitation of warmest quarter), indicates that climate exerts a strong selective pressure. Finally, we used environmental niche modeling to predict present and future habitat suitability for eight Drepanotermes species. Abiotic factors such as annual temperature contributed disproportionately to calibrations, while the inclusion of biotic factors like vegetation cover improved ecological niche models in some species. A comparison between present and future habitat suitability under two different emission scenarios revealed continued suitability of current ranges as well as substantial habitat gains for most studied species, irrespective of nesting habit, yet extensive range expansions in the near future are likely precluded by low dispersal abilities.
For details about the sample collection, the molecular data set, and used methods see Materials and Methods and Supporting Information.
For phylogenetic reconstructions including divergence dating, IQ-TREE and BEAST have been used. Ecological niche modelling has been conducted in MaxEnt and graphics have been drawn with R. For more details see README.txt and Supporting Information.