Wildlife response to land-use change forces encounters between zoonotic disease hosts and farms in agricultural landscapes

Abstract

• 1.
  Land-use change can significantly alter wildlife movement patterns and behaviour which may increase the risk of zoonotic disease transmission, particularly diseases with wildlife maintenance hosts that intersect regularly with farmland such as bovine tuberculosis (bTB).
• 2.
  This study utilized an agent-based model (ABM) with high-resolution input data to simulate badger responses to clearfell forestry across 100 sites in Ireland. The model environment was constructed from multiple GIS datasets, including sett locations, habitat, farm boundaries, and forestry operations. Animal movement and behaviour in the model were parameterised using detailed analysis of GPS tracking data from over 200 collared badgers in the wild.
• 3.
  Our results show that badger density and herd type were the strongest predictors of alien encounters—instances where badgers move beyond their established territories and enter farms outside their usual home range. These encounters, if used as a proxy for bTB transmission risk, represent opportunities for badgers to interact with livestock, particularly cattle, increasing the likelihood of disease spread. Dairy herds, despite being fewer in number compared to beef and suckler enterprises, had a higher risk of alien encounters. Larger clearfell events significantly increased alien encounters, supporting the hypothesis that landscape disturbances elevate disease risk.
• 4.
  Contrary to expectations, badger dispersal distance did not significantly affect encounter rates. Instead, landscape heterogeneity, including clearfell size and farm density, played a more substantial role in modulating encounters.
• 5.
  Validation of the ABM using empirical bTB breakdown data confirmed a positive correlation between simulated badger encounter rates per study site and real world bTB outbreaks within those sites.
• 6.
  This research provides a novel spatial framework for predicting bTB risk in disturbed landscapes, offering a valuable tool for Ireland's efforts to mitigate wildlife-livestock disease transmission. By integrating high-resolution GIS data and GPS-tracked wildlife movements, this approach enhances the accuracy of agent-based models (ABMs) for applied ecology and wildlife conflict research.