U.S. Geological Survey, Leetown Science Center, 11649 Leetown Road, Kearneysville, WV, 25430, U.S.A.
Department of Environmental Science, American University, 4400 Massachusetts Avenue NW, Washington, DC, 20016, USA.
Conserv Biol. 2021 Oct;35(5):1627-1638. doi: 10.1111/cobi.13694. Epub 2021 Mar 16.
Many questions relevant to conservation decision-making are characterized by extreme uncertainty due to lack of empirical data and complexity of the underlying ecologic processes, leading to a rapid increase in the use of structured protocols to elicit expert knowledge. Published ecologic applications often employ a modified Delphi method, where experts provide judgments anonymously and mathematical aggregation techniques are used to combine judgments. The Sheffield elicitation framework (SHELF) differs in its behavioral approach to synthesizing individual judgments into a fully specified probability distribution for an unknown quantity. We used the SHELF protocol remotely to assess extinction risk of three subterranean aquatic species that are being considered for listing under the U.S. Endangered Species Act. We provided experts an empirical threat assessment for each known locality over a video conference and recorded judgments on the probability of population persistence over four generations with online submission forms and R-shiny apps available through the SHELF package. Despite large uncertainty for all populations, there were key differences between species' risk of extirpation based on spatial variation in dominant threats, local land use and management practices, and species' microhabitat. The resulting probability distributions provided decision makers with a full picture of uncertainty that was consistent with the probabilistic nature of risk assessments. Discussion among experts during SHELF's behavioral aggregation stage clearly documented dominant threats (e.g., development, timber harvest, animal agriculture, and cave visitation) and their interactions with local cave geology and species' habitat. Our virtual implementation of the SHELF protocol demonstrated the flexibility of the approach for conservation applications operating on budgets and time lines that can limit in-person meetings of geographically dispersed experts.
由于缺乏经验数据和基础生态过程的复杂性，许多与保护决策相关的问题都具有极大的不确定性，这导致越来越多地使用结构化协议来获取专家知识。已发表的生态学应用通常采用改良的德尔菲法，专家匿名提供判断，并且使用数学聚合技术来组合判断。谢菲尔德启发式框架（SHELF）在将个体判断综合为未知数量的完全指定概率分布的行为方法上有所不同。我们使用远程 SHELF 协议来评估三种地下水生物种的灭绝风险，这些物种正在考虑根据美国濒危物种法案进行上市。我们通过视频会议为每位专家提供了每个已知地点的实际威胁评估，并通过 SHELF 软件包中的在线提交表格和 R-shiny 应用程序记录了对四个世代种群持续存在概率的判断。尽管所有种群的不确定性都很大，但基于主要威胁的空间变化、当地土地利用和管理实践以及物种的微生境，物种灭绝的风险存在关键差异。所得的概率分布为决策者提供了一幅完整的不确定性图景，这与风险评估的概率性质是一致的。在 SHELF 的行为聚合阶段，专家之间的讨论清楚地记录了主要威胁（例如，开发、木材采伐、动物农业和洞穴参观）及其与当地洞穴地质和物种栖息地的相互作用。我们对 SHELF 协议的虚拟实现证明了该方法在预算和时间限制下对保护应用的灵活性，这些限制可能会限制地理上分散的专家的面对面会议。
