Remote Sensing, Fire, and Drought: Scaling Biodiversity Insights for Large Mammals in the American West

Emerging remote sensing technologies are revolutionizing our ability to monitor biodiversity and ecosystem function, particularly across fire-prone and drought-stressed landscapes. Leveraging 12 years of GPS telemetry from over 3,000 individuals across three mammalian trophic groups—herbivorous mule deer (Odocoileus hemionus), omnivorous black bears (Ursus americanus), and carnivorous cougars (Puma concolor)—and integrating satellite-derived vegetation indices, burn severity maps, and habitat suitability models, we quantify how fire and drought drive changes in the spatial distribution, quality, and demographic outcomes of large mammal habitats in the American West.

Our first study explores the role of wildland fires, including both high-severity wildfires and prescribed fires, in shaping large mammal habitat quality and selection. We integrated GPS and remote sensing data to quantify how fire characteristics (extent, severity, age, vegetation recovery) influence resource use, showing substantial habitat overlap with burned landscapes. Herbivores and omnivores showed improved or neutral habitat quality in low-severity or small burns, driven by increased forage and cover, but consistently avoided large, severe wildfires, which diminished habitat quality for up to 30 years post-fire. Machine learning algorithms helped distinguish the nuanced effects of fire at broad scales, revealing pathways to optimize fire management for biodiversity outcomes.

Our second analysis addresses the mounting threat of extreme drought. We examined how annual drought conditions, quantified with high-resolution remote sensing of vegetation productivity and biomass, cause widespread contractions in highly suitable habitats for all three species. Severe droughts reduced suitable habitat by 10–18%, with the greatest impacts observed for upper trophic levels. Critically, we linked broad-scale predictions to demographic shifts, finding that mule deer fawn recruitment dropped by over 34% during severe drought years. These findings underscore the necessity of integrating multi-source remote sensing products, ecological theory, and in-situ fitness data to scale biodiversity monitoring from individual movement to population viability, thereby informing adaptive management under the Kunming-Montreal Biodiversity Framework and SDG targets.

Our work demonstrates that next-generation Earth observation combined with advanced ecological modeling is essential to anticipate, monitor, and mitigate the synergistic impacts of fire and drought on wildlife and ecosystem resilience at landscape scales.