Combining remote sensing and tracking data to quantify species' cumulative exposure to anthropogenic change

Abstract

Identifying when and where organisms are exposed to anthropogenic change is cru-cial for diagnosing the drivers of biodiversity declines and implementing effective conservation measures. Accurately measuring individual-scale exposure to anthro-pogenic impacts across the annual cycle as they move across continents requires an approach that is both spatially and temporally explicit—now achievable through recent parallel advances in remote-sensing and individual tracking technologies. We combined 10 years of tracking data for a long-distance migrant, (common cuckoo, Cuculus canorus), with multi-dimensional remote-sensed spatial datasets encompass-ing thirteen relevant anthropogenic impacts (including infrastructure, hunting, habitat change, and climate change), to quantify mean hourly and total accumulated expo-sure of tracked individuals to anthropogenic change across each stage of the annual cycle. Although mean hourly exposure to anthropogenic change was greatest in the breeding stage, accumulated exposure to changes associated with direct mortality risks (e.g., built infrastructure) and with climate were greatest during the wintering stage, which comprised 63% of the annual cycle on average for tracked individuals. Exposure to anthropogenic change varied considerably within and between migra-tory flyways, but there were no clear between-flyway differences in overall exposure during migration stages. However, more easterly autumn migratory routes were sig-nificantly associated with lower subsequent exposure to anthropogenic impacts in the winter stage. Cumulative change exposure was not significantly associated with recent local-scale population trends in the breeding range, possibly because cuck-oos from shared breeding areas may follow divergent migration routes and therefore encounter very different risk landscapes. Our study highlights the potential for the integration of tracking data and high- resolution remote sensing to generate valuable and detailed new insights into the impacts of environmental change on wild species.