Department of Ecology and Vertebrate Zoology, Faculty of Biology and Environmental Protection, University of Lodz, 90-237 Lodz, Poland.
Tropical Aquaculture Laboratory, Program in Fisheries and Aquatic Sciences, School of Forest, Fisheries, and Geomatics Sciences, University of Florida, Ruskin, FL 33570, USA.
Sci Total Environ. 2022 Aug 1;832:154966. doi: 10.1016/j.scitotenv.2022.154966. Epub 2022 Apr 1.
There is increasing use worldwide of electronic decision-support tools to identify potentially invasive non-native species so as to inform policy and management decisions aimed at preventing or mitigating the environmental and socio-economic impacts of biological invasions. This study reviews the analytical approaches used to calibrate scores generated by the Weed Risk Assessment and subsequent adaptations thereof and provides a protocol for: (i) the identification of the assessor(s) who will carry out the screenings; (ii) the definition of the risk assessment area; (iii) the criteria for selection of the species for screening; and (iv) the a priori categorisation of the species into invasive or non-invasive necessary to compute the thresholds by which to distinguish between high-risk and medium-risk non-native species. This analytical approach represents an evidence-based and statistically robust means with which to inform decision-makers and stakeholders about policy and management of potentially invasive species and is expected to serve as a general reference of forthcoming screening applications of Weed Risk Assessment-type toolkits.
全球范围内越来越多地使用电子决策支持工具来识别潜在的入侵非本地物种,以便为旨在防止或减轻生物入侵对环境和社会经济影响的政策和管理决策提供信息。本研究回顾了用于校准杂草风险评估产生的分数的分析方法及其后续改编,并提供了一个协议:(i)确定将进行筛选的评估者;(ii)定义风险评估区域;(iii)选择要筛选的物种的标准;以及 (iv)对物种进行入侵或非入侵的预先分类,这是计算区分高风险和中风险非本地物种所需阈值的必要条件。这种分析方法为决策者和利益相关者提供了一种基于证据和统计稳健的方法,以便对潜在入侵物种的政策和管理做出决策,预计将成为杂草风险评估类工具包未来筛选应用的一般参考。