Habitat fragmentation and human disturbance continue to undermine connectivity across ecosystems, making it harder for wildlife to move, migrate, and survive in increasingly human-dominated landscapes.
Yet conservation planning often relies on static measures of disturbance, such as roads or built infrastructure, that fail to capture when and how people actually use these spaces. Accurately tracking human presence over time and across scales could help pinpoint when disturbance peaks, where wildlife encounters are most likely, and how human activity disrupts movement corridors.
Abernathy, H.N., Ditmer, M.A., Hibbard, S.B., Lombardi, J.V., Stephenson, T.R., Squires, J.R., Newton, J.N., Dewey, S.R., Zeller, K.A., Schwartz, M.K. and Wittemyer, G. 2025. A case for human mobility data applications in wildlife management. Journal of Applied Ecology 62(7): 1636-1646.
A new paper makes the case that human mobility data – anonymized GPS information gathered from smartphones – offers a powerful, underused way to fill this gap. Already applied in urban planning and public health, this technology provides fine-scale, real-time insight into where and when people move across landscapes. By integrating these data into conservation and wildlife management, researchers can better understand human impacts on habitat use, migration, and connectivity.
Two case studies demonstrate how human mobility data can improve management decisions. In Wyoming’s Teton Mountain Range, researchers analyzed smartphone data to assess compliance with winter closures that protect bighorn sheep.
The data revealed excellent adherence in mandatory closures and slightly higher use in voluntary zones, especially near boundaries. Importantly, human activity more than tripled immediately after restrictions ended, suggesting that closure timing should align more closely with the animals’ ecological needs. The study also showed how human mobility data can map subtle spatial patterns of recreation, guiding where signage or enforcement could most effectively reduce disturbance.
A second case study focused on cougars in California’s eastern Sierra Nevada, where GPS-collared animals were paired with smartphone location data to identify potential human-cougar interactions. Over 13,000 potential encounters were recorded, most involving vehicles, with only a few linked to outdoor recreation.
Nearly all interactions were concentrated among just two individual cougars, revealing behavioral differences in how large carnivores respond to human presence. By highlighting when and where encounters are most likely, human mobility data provides managers with new tools to anticipate conflict hotspots and identify where road crossings or other mitigations could strengthen connectivity and safety for both wildlife and people.
In the future, human mobility data could revolutionize connectivity conservation by capturing the dynamics of how human traffic, recreation, and seasonal activity shift across time and space. When integrated with animal movement data, it can distinguish between the physical presence of infrastructure and the actual human use that disrupts wildlife movement. This distinction allows for more accurate modeling of barriers, thresholds, and opportunities to restore or maintain corridors.
Overall, human mobility data offers a transformative approach for conservation planning. It bridges a long-standing data gap by quantifying real-time human activity at the scales where wildlife experience it. While challenges remain, such as high data processing demands, inherent biases, and and privacy constraints, human mobility data has the potential to guide restoration, mitigate conflict, and design landscapes that remain connected for wildlife in an increasingly mobile world.
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