Extreme weather risk shrinks range size estimates and alters biodiversity predictions

Abstract Extreme weather events, including heat waves, cold snaps, and droughts, are increasing in frequency and intensity with expected but little understood consequences for biodiversity. Extreme weather events can push organisms beyond their physiological thermal or hydric tolerances and thus limit where they can persist, affecting their geographic distributions. Species might be especially sensitive to extreme weather at the edges of their geographic ranges, where they are often already living near their physiological limits. However, the influence of climatic variability and extreme weather is often ignored in favor of climatic means when estimating distributional and richness patterns. Here we link hundreds of millions of citizen science bird observations from 2004-2024 to high-resolution extreme weather risk maps to explore how climatic variability and extreme weather risk alters summer and winter distributions and biodiversity patterns for 535 North American species. We find that species distribution models accounting for historical extreme weather risk performed better at predicting richness and the presence of individual species across 220 well-surveyed sites. Models incorporating extreme weather predicted narrower geographic distributions than models relying on only climatic means, with species’ ranges shrinking an average of 6% in summer and 10% in winter and range truncation observed at the range edges. These effects were observed in both seasons but were particularly strong in winter, a time with greater short-term weather variability than summer. Richness estimates were substantially lower when extreme weather was accounted for, especially in the US southwest and central plains (up to 30-40 fewer species), regions highly prone to extreme heat, cold and drought. Our results suggest that more mechanistically informed biodiversity predictions that account for extreme weather are critical for reliably predicting shifting distributional and biodiversity patterns.