When planning conservation efforts, protecting climatically stable refugia is a low-risk investment, as species are considered more likely to persist in areas less affected by climate change. Such prioritization, however, is often done at the expense of less stable high-risk areas, effectively leaving inhabiting species unprotected and committed to extinction.
Proposing a novel strategy for the conservation of mammals in the Amazon, researchers used GBIF-mediated occurrences of 256 species to generate ecological niche models that served as primary input to a spatial prioritization analysis taking into consideration climate change metrics including climate anomalies and extremes.
The resulting analysis identified a network of both high-risk areas and low-risk refugia while revealing more current and future distributions of species in the former. The study presents a robust approach to conservation planning, taking into account uncertainties arising from alternative climate models and showing that trade-offs related to species representation can be quantified explicitly.