Rast et al. (2024). Death detector: Using vultures as sentinels to detect carcasses by combining bio-logging and machine learning. Journal of Applied Ecology

This groundbreaking study combines the natural behavior of African white-backed vultures with advanced e-obs bio-logging technology and artificial intelligence. Using GPS and accelerometer data, researchers trained machine learning models to identify feeding locations with remarkable precision (92%).

The findings highlight the potential of using vultures as natural sentinels to monitor wildlife mortality, detect disease outbreaks, and combat environmental threats like poisoning. This innovative framework can be adapted to other species and behaviors, offering broad applications for ecological research and conservation.

Curk et al. (2024). Advantages and disadvantages of using social information for carcass detection–A case study using white-backed vultures. Ecological Modelling

White-backed vultures rely on different foraging strategies to locate carcasses in unpredictable environments. A recent study compares individual and social approaches, including “local enhancement” and “chains of vultures.” While social strategies improve food detection, they also increase competition among individuals. The findings shed light on the balance between efficiency and resource use, providing valuable insights into vulture ecology. These results contribute to understanding their critical role in ecosystems and can inform conservation strategies for this endangered species.