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

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. • Novel approach using agent-based models for ecological modeling with integrated GPS and GIS data. • Identifies dairy farms as significant, revealing spatial dynamics beyond traditional explanations of husbandry and farm management. • Highlights that badger and farm density outweigh disturbance effects in influencing encounter rates post-clearfell. • Strong model performance against real-world disease testing data, underscoring ABMs’ potential for applied ecological impact.

Authors

Institutions

Publication Details

Journal
Agriculture Ecosystems & Environment
Published
2025-03-06
DOI
https://doi.org/10.1016/j.agee.2025.109561
Citations
9
Primary Topic
Zoonotic diseases and public health
Type
article
Field-Weighted Citation Impact
16.91

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

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

Maria O’Hagan, Damien Barrett, Nicola M. Marples, Guy McGrath et al.
9 citations
Agriculture Ecosystems & Environment
Zoonotic diseases and public health
16.91
article

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

Maria O’Hagan, Damien Barrett, Nicola M. Marples, Guy McGrath, David M. Quinn, Virginia Morera‐Pujol, Simone Ciuti, Kilian J. Murphy, Andrew W. Byrne, Renée M. Khouri, David Kelly, Phillip Breslin
article en
9 citations

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. • Novel approach using agent-based models for ecological modeling with integrated GPS and GIS data. • Identifies dairy farms as significant, revealing spatial dynamics beyond traditional explanations of husbandry and farm management. • Highlights that badger and farm density outweigh disturbance effects in influencing encounter rates post-clearfell. • Strong model performance against real-world disease testing data, underscoring ABMs’ potential for applied ecological impact.

Agriculture Ecosystems & EnvironmentVol. 386
University College Dublin (IE), Trinity College Dublin (IE), Government of Ireland (IE), Department of Agriculture and Rural Development (GB), Department of Agriculture Food and the Marine (IE)
Department of Agriculture, Food and the Marine, Ireland
Zero hunger
Openalex Percentile: Top 1%
Zoonotic diseases and public health
16.91
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.