Katie M. Beckmann, Nicola C. Dessi, Anthony W. Sainsbury, Kate McInnes, Rosa Lopez Colom, William H. Costa, Michelle F. O'Brien, Jessica-Leigh Penman, Daniel Calvo Carrasco, Taiana P. Costa, Nigel S. Jarrett, Tanya Grigg, Baz Hughes, Richard A. Kock, Ruth L. Cromie, Rebecca Lee
{"title":"Wildlife health risk analysis for conservation translocation: A scalable approach illustrated for wader population restoration","authors":"Katie M. Beckmann, Nicola C. Dessi, Anthony W. Sainsbury, Kate McInnes, Rosa Lopez Colom, William H. Costa, Michelle F. O'Brien, Jessica-Leigh Penman, Daniel Calvo Carrasco, Taiana P. Costa, Nigel S. Jarrett, Tanya Grigg, Baz Hughes, Richard A. Kock, Ruth L. Cromie, Rebecca Lee","doi":"10.1111/csp2.70131","DOIUrl":null,"url":null,"abstract":"<p>Conservation translocations are human-mediated movements of wildlife for conservation purposes. They risk compromising the health of wildlife, and potentially domestic animals and humans, in the short and long term, but these risks vary with project context. Wildlife health risk analysis (disease risk analysis) is a process enabling these risks to be characterized and managed; multiple methods have been developed for conservation translocation. It would be beneficial for the depth of health risk analysis to be proportionate to context; however, few methods currently facilitate this flexibility. We aimed to produce a refined methodological framework for health risk analysis that enabled it to be scalable and adaptable to different translocation scenarios. We developed such a framework by adapting and assimilating elements of existing methods. We describe its key features and application to two wader (shorebird) conservation translocations with differing translocation plans and epidemiological circumstances. We then reflect on the framework's utility in light of the observed project outcomes, which exemplified the uncertain and changeable nature of disease risks over time. Our framework has the potential to expedite health risk analysis for repeat translocations of a particular taxon in a region and has application to other taxa and potentially other forms of wildlife translocation.</p>","PeriodicalId":51337,"journal":{"name":"Conservation Science and Practice","volume":"7 9","pages":""},"PeriodicalIF":2.8000,"publicationDate":"2025-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://conbio.onlinelibrary.wiley.com/doi/epdf/10.1111/csp2.70131","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Conservation Science and Practice","FirstCategoryId":"93","ListUrlMain":"https://conbio.onlinelibrary.wiley.com/doi/10.1111/csp2.70131","RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"BIODIVERSITY CONSERVATION","Score":null,"Total":0}
引用次数: 0
Abstract
Conservation translocations are human-mediated movements of wildlife for conservation purposes. They risk compromising the health of wildlife, and potentially domestic animals and humans, in the short and long term, but these risks vary with project context. Wildlife health risk analysis (disease risk analysis) is a process enabling these risks to be characterized and managed; multiple methods have been developed for conservation translocation. It would be beneficial for the depth of health risk analysis to be proportionate to context; however, few methods currently facilitate this flexibility. We aimed to produce a refined methodological framework for health risk analysis that enabled it to be scalable and adaptable to different translocation scenarios. We developed such a framework by adapting and assimilating elements of existing methods. We describe its key features and application to two wader (shorebird) conservation translocations with differing translocation plans and epidemiological circumstances. We then reflect on the framework's utility in light of the observed project outcomes, which exemplified the uncertain and changeable nature of disease risks over time. Our framework has the potential to expedite health risk analysis for repeat translocations of a particular taxon in a region and has application to other taxa and potentially other forms of wildlife translocation.