Future-proofing agrobiodiversity: climate and niche-aware conservation planning using reinforcement learning.
This study proposes a novel, climate-aware conservation planning framework using reinforcement learning to optimize the protection of European crop wild relatives, demonstrating that accounting for niche coverage and range shifts significantly improves conservation outcomes compared to traditional methods.