Jeremy B. Yoder, Assistant Professor, California State University
Moises Exposito-Alonso Staff Associate and Assistant Professor (by courtesy) of Biology, Carnegie Institution for Science and Stanford
Joshua tree, an ecological keystone of the Mojave Desert, is expected to see dramatic losses in habitat under projected climate change. The trees cannot migrate to track suitable climates, but they encounter a range of extreme heat and drought across their existing range, and populations may harbor genetic variation to support adaptation in place and assisted gene flow. Finding genetic variants that predict Joshua tree adaptation to particular climates could help to identify populations with adaptive capacity and prioritize them for protection, and could bolster restoration of Joshua tree populations by matching seed sources to projected future climates. We are conducting whole-genome resequencing of 300 Joshua trees sampled across the species’ range, to produce first large-scale sequencing of a keystone desert species. This will likely enable discovery of new genes related to the evolution of extremophile plants, allow us to map genetic variants for climate adaptation, and predict climate change resilience of extant Joshua tree populations to better target conservation efforts. The scope and scale of this work will, we hope, serve as a model for genetically-informed desert species conservation.
More species than ever before are at risk of extinction due to anthropogenic habitat loss and climate change. But even species that are not threatened have seen reductions in their populations and geographic ranges, likely impacting their genetic diversity. Although preserving genetic diversity is a key conservation target to maintain the adaptability of species, we lack predictive tools and global estimates of genetic diversity loss across ecosystems. By bridging biodiversity and population genetics theories, we introduce the first mathematical framework to understand the loss of naturally occurring DNA mutations within a species—what we call genetic diversity extinction. Analyzing genome-wide variation data of 10,126 geo-tagged individuals from 19 plant and animal species, we show that genome-wide diversity follows a power law with geographic area, which can predict genetic diversity decay in simulated spatial extinctions. Given pre-21st century values of ecosystem transformations, we estimate that over 10% of genetic diversity may be extinct, already surpassing the United Nations targets for genetic preservation. These estimated losses could rapidly increase with advancing climate change and habitat destruction, highlighting the need for new fore