The Nature Conservancy- Washington, Seattle, WA, 98121, USA.
Northwest Fisheries Science Center, National Marine Fisheries Service, National Oceanic and Atmospheric Administration, 2725 Montlake Blvd E, Seattle, WA, 98112, USA.
Sci Rep. 2021 Jan 12;11(1):818. doi: 10.1038/s41598-020-79258-2.
Urbanization-driven landscape changes are harmful to many species. Negative effects can be mitigated through habitat preservation and restoration, but it is often difficult to prioritize these conservation actions. This is due, in part, to the scarcity of species response data, which limit the predictive accuracy of modeling to estimate critical thresholds for biological decline and recovery. To address these challenges, we quantify effort required for restoration, in combination with a clear conservation objective and associated metric (e.g., habitat for focal organisms). We develop and apply this framework to coho salmon (Oncorhynchus kisutch), a highly migratory and culturally iconic species in western North America that is particularly sensitive to urbanization. We examine how uncertainty in biological parameters may alter locations prioritized for conservation action and compare this to the effect of shifting to a different conservation metric (e.g., a different focal salmon species). Our approach prioritized suburban areas (those with intermediate urbanization effects) for preservation and restoration action to benefit coho. We found that prioritization was most sensitive to the selected metric, rather than the level of uncertainty or critical threshold values. Our analyses highlight the importance of identifying metrics that are well-aligned with intended outcomes.
城市化驱动的景观变化对许多物种都有害。通过栖息地保护和恢复,可以减轻负面影响,但通常很难优先考虑这些保护措施。部分原因是物种响应数据的稀缺性限制了模型的预测准确性,从而难以估计生物衰退和恢复的关键阈值。为了解决这些挑战,我们量化了恢复所需的努力,并结合明确的保护目标和相关指标(例如,焦点生物的栖息地)。我们开发并应用了这个框架来研究虹鳟(Oncorhynchus kisutch),这是北美西部高度洄游和具有文化标志性的物种,对城市化特别敏感。我们研究了生物参数的不确定性如何改变优先考虑保护行动的地点,并将其与转向不同保护指标(例如,不同的焦点鲑鱼物种)的效果进行了比较。我们的方法优先考虑了郊区(城市化影响中等的地区)进行保护和恢复,以造福于虹鳟。我们发现,优先考虑的因素最敏感于所选指标,而不是不确定性水平或关键阈值。我们的分析强调了确定与预期结果一致的指标的重要性。