National Institute of Water and Atmospheric Research, Christchurch, New Zealand.
Wildlife Ecology & Management, Manaaki Whenua - Landcare Research, Lincoln, Canterbury, New Zealand.
Conserv Biol. 2023 Aug;37(4):e14084. doi: 10.1111/cobi.14084. Epub 2023 May 25.
Estimates of temporal trends in species' occupancy are essential for conservation policy and planning, but limitations to the data and models often result in very high trend uncertainty. A critical source of uncertainty that degrades scientific credibility is that caused by disagreement among studies or models. Modelers are aware of this uncertainty but usually only partially estimate it and communicate it to decision makers. At the same time, there is growing awareness that full disclosure of uncertainty is critical for effective translation of science into policies and plans. But what are the most effective approaches to estimating uncertainty and communicating uncertainty to decision makers? We explored how alternative approaches to estimating and communicating uncertainty of species trends could affect decisions concerning conservation status of freshwater fishes. We used ensemble models to propagate trend uncertainty within and among models and communicated this uncertainty with categorical distributions of trend direction and magnitude. All approaches were designed to fit an established decision-making system used to assign species conservation status by the New Zealand government. Our results showed how approaches that failed to fully disclose uncertainty, while simplifying the information presented, could hamper species conservation or lead to ineffective decisions. We recommend an approach that was recently used effectively to communicate trend uncertainty to a panel responsible for setting the conservation status of New Zealand's freshwater fishes.
估算物种占有度的时间趋势对于保护政策和规划至关重要,但数据和模型的局限性通常会导致趋势不确定性非常高。一个降低科学可信度的关键不确定性来源是研究或模型之间的分歧。建模者意识到了这种不确定性,但通常只是部分估计并将其传达给决策者。与此同时,人们越来越意识到,充分披露不确定性对于将科学有效地转化为政策和计划至关重要。但是,估计不确定性和将不确定性传达给决策者的最有效方法是什么?我们探讨了估算物种趋势不确定性和将不确定性传达给决策者的替代方法如何影响有关淡水鱼类保护状况的决策。我们使用集合模型在模型内和模型间传播趋势不确定性,并使用趋势方向和幅度的分类分布来传达这种不确定性。所有方法都旨在适应新西兰政府用于分配物种保护状况的既定决策制定系统。我们的结果表明,未能充分披露不确定性的方法,虽然简化了所呈现的信息,但可能会阻碍物种保护或导致无效决策。我们建议采用一种最近被有效用于向负责设定新西兰淡水鱼类保护状况的小组传达趋势不确定性的方法。