Nelson Institute for Environmental Studies, University of Wisconsin, Madison, Wisconsin, United States of America.
PLoS One. 2022 Mar 16;17(3):e0259604. doi: 10.1371/journal.pone.0259604. eCollection 2022.
When humanity confronts the risk of extinction of species, many people invoke precautions, especially in the face of uncertainty. Although precautionary approaches are value judgments, the optimal design and effect of precautions or lack thereof are scientific questions. We investigated Wisconsin gray wolves Canis lupus facing a second wolf-hunt in November 2021 and use three legal thresholds as the societal value judgments about precautions: (1) the 1999 population goal, 350 wolves, (2) the threshold for statutory listing under the state threatened and endangered species act, 250 wolves; and (3) state extirpation <2 wolves. This allows us to explore the quantitative relationship between precaution and uncertainty. Working from estimates of the size wolf population in April 2021 and reproduction to November, we constructed a simple linear model with uninformative priors for the period April 2021-April 2022 including an uncertain wolf-hunt in November 2021. Our first result is that the state government under-counted wolf deaths in the year preceding both wolf-hunts. We recommend better scientific analysis be used when setting wolf-hunt quotas. We find official recommendations for a quota for the November 2021 wolf-hunt risk undesirable outcomes. Even a quota of zero has a 13% chance of crossing threshold 1. Therefore, a zero death toll would be precautionary. Proponents for high quotas bear the burden of proof that their estimates are accurate, precise, and reproducible. We discuss why our approach is transferable to non-wolves. We show how scientists have the tools and concepts for quantifying and explaining the probabilities of crossing thresholds set by laws or other social norms. We recommend that scientists grapple with data gaps by explaining what the uncertainty means for policy and the public including the consequences of being wrong.
当人类面临物种灭绝的风险时,许多人会援引预防措施,尤其是在面对不确定性时。尽管预防措施是价值判断,但预防措施的最佳设计和效果或缺乏预防措施都是科学问题。我们调查了 2021 年 11 月面临第二次狼群猎杀的威斯康星州灰狼 Canis lupus,并将三个法律门槛用作关于预防措施的社会价值判断:(1)1999 年的种群目标,350 只狼,(2)根据州濒危物种法案规定的法定上市阈值,250 只狼;以及(3)州灭绝<2 只狼。这使我们能够探索预防措施与不确定性之间的定量关系。根据 2021 年 4 月和繁殖到 11 月的狼群数量估计,我们构建了一个简单的线性模型,该模型在 2021 年 4 月至 2022 年 4 月期间具有不透明的先验信息,包括 2021 年 11 月不确定的狼群猎杀。我们的第一个结果是,州政府在两次狼群猎杀之前的一年中都低估了狼的死亡人数。我们建议在设定狼群猎杀配额时使用更好的科学分析。我们发现,对 2021 年 11 月狼群猎杀的配额建议存在风险,可能会导致不理想的结果。即使配额为零,也有 13%的机会超过第 1 个阈值。因此,零死亡人数将是预防性的。高配额的支持者有责任证明他们的估计是准确、精确和可重复的。我们讨论了为什么我们的方法可以推广到非狼身上。我们展示了科学家如何使用量化和解释法律或其他社会规范设定的阈值的概率的工具和概念。我们建议科学家通过解释数据空白对政策和公众意味着什么,包括犯错的后果,来解决数据空白问题。