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

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IntroductionThe natural world is experiencing immense change, driven by increasing human populations, climate change, and the degradation in quality of key resources such as natural habitats and water (Maja and Ayano, 2021). These rapid and widespread environmental changes have created conditions that far exceed the adaptive capacities of many species, leading to significant declines in wildlife populations and the degradation of biodiversity globally (Isbell et al. 2023). This loss of biodiversity not only threatens the survival of individual species but also undermines the integrity of ecosystems that provide essential services to both people and nature (Isbell et al. 2023). Systems that monitor and manage wildlife in areas of land-use change are crucial for disentangling the complex effects that change has on wildlife populations and their habitats (McRae et al. 2008; Murphy et al. 2023a). Without these systems in place, we will fail to understand how rapid change impacts key ecological and economic pillars, such as agricultural productivity, zoonotic disease emergence, and the resilience of natural resources (McMahon et al. 2018). In many countries, preventative systems are in place to identify likely impacts of land-use change and mitigate against them, in the form of policy instruments such as Environmental Impact Assessment (Glasson, and Therivel, 2013). Unfortunately, these processes typically fail to identify multivariate consequences of land-use change that occur over time and space (Murphy et al. 2022).Wildlife responses to human-mediated land-use changes, such as construction, forestry, and agriculture, can occur over varying temporal and spatial scales (Allen et al. 2019; Murphy et al. 2022). These changes may drive species into smaller refugia near human populations, increasing densities and exacerbating conflicts, often mistakenly attributed to wildlife abundance rather than the initial land-use change (Pozo et al. 2017; Fowler et al. 2019; Murphy et al. 2023a). When planned, land-use changes like road construction or forest removal offer opportunities to predict wildlife responses and validate hypotheses with empirical data, informing proactive mitigation strategies (Gaughran et al. 2021; Murphy et al. 2022). One important ecological process impacted by landscape disturbance is disease dynamics (Brearley et al. 2013). Landscape changes, such as habitat fragmentation and alteration, can influence wildlife spatial ecology, leading to increased interactions between wildlife, domestic animals, and humans, thereby facilitating the spread of diseases (Daszak et al. 2001). One notable example is bovine tuberculosis (bTB), a zoonotic disease with a global distribution and complex epidemiology due to the presence of multiple wildlife hosts, for instance, deer (Cervus & Odocoileus spp.) in North America (O’Brien et al. 2011), brush-tailed possums (Trichosurus vulpecula) in New Zealand (Tweddle and Livingstone 1994), buffalo (Syncerus caffer ) in South Africa (Davey 2023), and European badgers (Meles meles ) in Ireland and the UK, where they are the primary wildlife hosts implicated in the maintenance and transmission of bTB to local cattle herds (Allen et al. 2018; Chang et al. 2024). Recent studies have shown disturbances adjacent to agricultural landscapes have been linked to increased risk of bTB breakdowns in cattle herds (Barroso et al. 2022).However, our understanding of the mechanisms behind fluctuations in bTB risk remains incomplete due to conflicting evidence from different studies. It is hypothesized that disturbances alter disease risk by modifying wildlife behaviour and social structures, potentially forcing species like badgers to change their movement patterns and increasing inter/intra species interactions (Murphy et al. 2022). For instance, Barroso et al. (2022) observed an increased risk of bTB in cattle herds near roadworks, suggesting that such disturbances may contribute to disease spread. Conversely, Gaughran et al. (2021) found no significant changes in wildlife territoriality due to road construction and suggest that fully mitigated major road upgrades are unlikely to cause a perturbation effect substantial enough to increase TB in local cattle. This discrepancy underscores the complexity of disease dynamics in disturbed landscapes and emphasises the need for more integrated research that combines ecological, epidemiological, and human factors. The example of how bTB continues to proliferate despite surveillance and control of the disease highlights the necessity for deeper investigation into how macroecological human-mediated landscape disturbances may impact disease and the need to develop effective strategies for mitigating disease risk and spread.Previous research in Ireland has explored the link between landscape disturbances, such as forest clearfells, and bTB risk in cattle herds. Byrne et al. (2022) found that the percentage of herds testing positive for bTB increased after clearfelling, potentially due to disturbance of badger populations, a key wildlife host (Mullen et al. 2019). While unable to infer the mechanism, their study highlighted the need to integrate epidemiology with wildlife ecology. Murphy et al. (2022) extended this work by incorporating ecological covariates, showing that the relationship between clearfells and bTB risk was dynamic, depending on the extent and timing of clearfell activities relative to cattle farms and surrounding habitats. Murphy et al. (2022) hypothesised that badgers may initially leave disturbed areas but return as vegetation regenerates, altering disease transmission in time and space.Finally, Khouri et al. (2023) examined the role of wildlife densities, including badgers and deer, in influencing bTB risk after clearfell. Their study found that active badger sett density consistently predicted increased bTB risk, particularly when clearfells occurred within 2 km of farms, 24-36 months prior. Khouri et al. (2023) call for simulation approaches using agent-based models (ABMs) to simulate individual wildlife behaviours in response to habitat disturbances like clearfells. ABMs can reflect adaptive behaviours and environmental dynamics, offering insights into wildlife dispersal and interactions (Murphy et al. 2020). Additionally, GPS tracking data for wildlife hosts could provide valuable insights on how habitat disturbances affect wildlife movement and contacts with cattle, thereby informing more effective bTB management strategies (Conteddu et al. 2024).In this study, we developed a highly realistic agent-based model (ABM) to simulate wildlife responses to clearfell forestry at 100 sites across Ireland, focusing on the potential link between ecological disturbance and bTB risk. Clearfell forestry, where all marketable trees are harvested at the end of a rotation (typically 30–50 years for conifers), potentially displaces wildlife, thus altering their movement patterns and contact rates with cattle. We hypothesised that such disturbances modulate wildlife movement, increasing the risk of new encounters between wildlife hosts and cattle. Our ABM was parametrised using historical data from 202 individually tracked badgers across two study regions in Ireland, which had experienced both Test and Vaccinate or Remove (TVR) operations and a large road improvement scheme. We also integrated high-resolution GIS data, including spatial information on farms, clearfell sites, habitats, forestry, and badger setts.Methods To simulate the behavioural response of European badgers to clearfell forestry in Ireland and assess the relative impact on bovine tuberculosis, we gathered a mixture of tracking data and field survey data (e.g. badger sett locations and activity) for badgers, and remote sensing spatial data for habitats, farms and forestry operations. We used these data to build a realistic agent-based model. The data, subsequent analysis and an overview of the agent-based model is descr

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