Predicting human-wildlife interaction in urban environments through agent-based models

eSynurbic species adapt to global urbanization by increasingly inhabiting urban environments, where social and ecological factors, such as anthropogenic food resources and habitat alterations, promote close humanwildlife interactions. Ineffective management of these interactions can result in conflicts, altered animal population dynamics, and increased public and private expenditures. This study presents the Barcelona wild boar (BCNWB)-prototype model, a spatially explicit, incremental agent-based simulation that captures interactions between citizens and wild boar (Sus scrofa) agents in fine-scale GIS-based scenarios in Barcelona. Developed using GAMA software, the model's results were analyzed with QGIS and R software. The model aims to simulate the dynamics of the social-ecological system underlying the urban ecosystem use by synurbic wild boars and their interactions with humans in the (peri)urban area of Barcelona, Spain.The BCNWB-prototype model demonstrated high accuracy in predicting the magnitude and location of wild boar movements (multiple-resolution-goodness-of-fit = 0.73) compared to reported wild boar presences in Barcelona. The model also forecasted 115 attack events and 1,442 direct feeding events during a one-year simulation period, as compared to the actual 150 attacks and 1,858 feeding events reported annually. The model's strong performance highlights its potential as a predictive tool for identifying priority areas for human wild boar interactions and conflicts. Additionally, the model could be employed to assess the cost-effectiveness of management strategies and evaluate the spread, transmission risks, and public health implications of pathogens carried by wild boars.