by Chris Barratt

This journey began sometime in 2020 after way too many difficult months of being locked down due to COVID-19 in our apartment with my pregnant wife and my (then 2 year old, and thankfully now diagnosed and much happier) autistic son. The pandemic was an extremely tough time for us as a family, and we had zero space or energy for creative thinking, but as the doom slowly started to lift and we began to experience something resembling a normal existence again, discussions with my wife (also an evolutionary biologist and nature lover) began to scratch at some long-standing questions that were in my head. As late summer turned into a cold and dark Leipzig winter, my ideas slowly grew alongside my wife’s belly, ultimately crystallising as the ‘Life on the edge’ proposal which was funded in 2021 by sDiv as a three year individual postdoc grant.

I conceived the Life on the edge project because I’m committed to combining predictive spatial modelling and genomics to contribute to conservation efforts. Although there are lots of really cool climate change vulnerability assessment tools available that can predict which species are likely to be at risk from climate and anthropogenic changes, these lack information about what happens within species (i.e. using populations as early warning signals). The decreasing cost of high throughput sequencing naturally led many people to begin thinking of interesting ways to plug this knowledge gap using population genomic data, but this was always system or species-specific and we lack a generalized framework to do this on any species.

Together with my iDiv and external collaborators, I developed a new informatic toolbox which makes it possible to predict population vulnerability by integrating spatial modelling and population genomics approaches. Harnessing the recommendations from the IPCC’s fourth and fifth assessments, we built a tool that can comparatively and objectively quantify biodiversity related metrics across populations using ecological and evolutionary principles. Life on the edge integrates ecological, environmental and genomic data and analyses (environmental dissimilarity, species distribution models, landscape connectivity, neutral and adaptive genetic diversity, genotype-environment associations and genomic offset) to estimate population vulnerability, which can be compared across populations to see which may need conservation interventions. Within the toolbox, functions and data structures are coded in a transparent and standardised way so that it is applicable to any species or geographic region where appropriate data are available.

To demonstrate its applicability, we applied Life on the edge to three georeferenced genomic datasets for co-occurring East African spiny reed frogs (Afrixalus fornasini, A. delicatus and A. sylvaticus) to predict their population vulnerability, as well as demonstrating that range loss projections based on adaptive variation can be accurately reproduced from a previous study using data for two European bat species (Myotis escalerai and M. crypticus). Life on the edge sets the stage for large scale, multi-species genomic datasets to be leveraged in a novel climate change vulnerability framework to quantify intraspecific differences in genetic diversity, local adaptation, range shifts and population vulnerability based on exposure, sensitivity and landscape barriers. This is one of the major projects that I continue to work on, and several related manuscripts are either published or forthcoming.

Barratt, C. D., Onstein, R. E., Pinsky, M. L., Steinfartz, S., Kühl, H. S., Forester, B. R., & Razgour, O. (2024). Life on the edge: A new toolbox for population-level climate change vulnerability assessments. Methods in Ecology and Evolution, 00, 1–21. https://doi.org/10.1111/2041-210X.14429