Multivariate Climatic Drivers of Local Extirpation: Long-term Temperature, Snowfall, and Precipitation Dynamics in Michigan

This study applies a multivariate climatic framework to evaluate how interacting long-term changes in minimum temperature, snowfall, and precipitation contribute to species decline and local extirpation in Michigan. We integrate 129 years of minimum temperature data, 64 years of precipitation records, and multi-decadal snowfall measurements with species-occurrence histories to quantify climatic pressures driving documented losses. The analysis shows a pronounced post-2000 rise in winter minimum temperatures marked by the near disappearance of extreme cold events (e.g., February minimums rising from –30°F to –9°F). These warmer minimum temperatures disrupt key ecological pathways by reducing the duration and intensity of cold-dependent physiological cues, increasing overwinter metabolic stress, and expanding predator and pathogen survival windows. Concurrent declines in January–February snowpack and the virtual loss of April snowfall further compound risk by diminishing the insulating snow layer essential for thermal buffering, hibernation stability, and protection of subnivean microhabitats. Precipitation patterns reveal increasing seasonal imbalance, with reduced summer rainfall and elevated spring and autumn precipitation, altering hydrological stability, breeding-site persistence, and seasonal habitat quality. To evaluate species responses, we develop synthetic K-Nearest Neighbors (KNN) population models for several climate-sensitive taxa-including Blanchard’s Cricket Frog, American Goshawk, Kirtland’s Snake, and the Long-eared Owl-which represent a novel integration of long-term multi-variable climate anomalies with data-driven population modeling. These models show coherent seasonal and interannual population declines that align with observed climatic anomalies, highlighting the combined effects of winter warming, snowpack loss, and altered moisture regimes on demographic resilience. A broader historical comparison further indicates a shift in the dominant drivers of biodiversity loss: whereas early extirpations were primarily linked to habitat conversion, recent and ongoing declines increasingly stem from the interaction of climatic warming with persistent habitat degradation. The findings demonstrate that no single climatic factor explains extirpation patterns; instead, vulnerability emerges from interacting climatic stressors that reshape overwintering conditions, hydrological cycles, and habitat suitability. By merging long-term climate datasets with synthetic KNN population modeling, this study advances tools for assessing climate-driven extinction risk and provides actionable insight for conservation planning in the Great Lakes region.