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Abstract Understanding how global change reshapes species distributions remains a central challenge in ecology, yet most global assessments treat environmental drivers as static, uniform, or aggregate influences. This obscures where, why, and how specific drivers generate ecological risk or opportunity. Here, we apply explainable machine learning to assess how climate averages, variability, extremes, and land cover are projected to reshape future distributions of 1,992 terrestrial mammals.
As a journalist, you can create a free Muck Rack account to customize your profile, list your contact preferences, and upload a portfolio of your best work.
