Connor Lovell , Terence P. Dawson , J. Gareth Polhill
{"title":"Projecting population dynamics and range expansion of reintroduced wild boar in Scotland using agent-based modelling","authors":"Connor Lovell , Terence P. Dawson , J. Gareth Polhill","doi":"10.1016/j.ecoinf.2025.103261","DOIUrl":null,"url":null,"abstract":"<div><div>The number of species reintroductions is increasing globally via both legal and illegal routes. These reintroductions can be controversial with uncertain social-ecological outcomes, particularly for unsanctioned illegal releases, which risks causing conflict between stakeholders. Despite this, current reintroduction science is focused on short-term population establishment, with little long-term modelling of reintroduced populations. In this study, we develop an agent-based model (ABM) to simulate the controversial reintroduction of wild boar in Scotland. The ABM uses probabilistic birth, death, and movement rules from the literature to stochastically simulate boar population dynamics from their initial release to 50 years in the future. Model evaluation demonstrated that the ABM behaves in predictable and explainable ways, whilst reproducing real boar behaviours and aligning with the spatial distribution of boar sightings in Scotland. Projecting the ABM 50 years into the future suggests that current boar populations are likely viable and will continue to grow and expand, with the model confirming the existence and long-term persistence of four boar populations. We conclude by commenting on the potential future uses of the ABM.</div></div>","PeriodicalId":51024,"journal":{"name":"Ecological Informatics","volume":"90 ","pages":"Article 103261"},"PeriodicalIF":7.3000,"publicationDate":"2025-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Ecological Informatics","FirstCategoryId":"93","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1574954125002705","RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ECOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
The number of species reintroductions is increasing globally via both legal and illegal routes. These reintroductions can be controversial with uncertain social-ecological outcomes, particularly for unsanctioned illegal releases, which risks causing conflict between stakeholders. Despite this, current reintroduction science is focused on short-term population establishment, with little long-term modelling of reintroduced populations. In this study, we develop an agent-based model (ABM) to simulate the controversial reintroduction of wild boar in Scotland. The ABM uses probabilistic birth, death, and movement rules from the literature to stochastically simulate boar population dynamics from their initial release to 50 years in the future. Model evaluation demonstrated that the ABM behaves in predictable and explainable ways, whilst reproducing real boar behaviours and aligning with the spatial distribution of boar sightings in Scotland. Projecting the ABM 50 years into the future suggests that current boar populations are likely viable and will continue to grow and expand, with the model confirming the existence and long-term persistence of four boar populations. We conclude by commenting on the potential future uses of the ABM.
期刊介绍:
The journal Ecological Informatics is devoted to the publication of high quality, peer-reviewed articles on all aspects of computational ecology, data science and biogeography. The scope of the journal takes into account the data-intensive nature of ecology, the growing capacity of information technology to access, harness and leverage complex data as well as the critical need for informing sustainable management in view of global environmental and climate change.
The nature of the journal is interdisciplinary at the crossover between ecology and informatics. It focuses on novel concepts and techniques for image- and genome-based monitoring and interpretation, sensor- and multimedia-based data acquisition, internet-based data archiving and sharing, data assimilation, modelling and prediction of ecological data.