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基于指标的气候智能型保护规划框架。

A metric-based framework for climate-smart conservation planning.

机构信息

School of Earth and Environmental Sciences, The University of Queensland, Brisbane, Queensland, Australia.

School of Mathematics and Physics, The University of Queensland, Brisbane, Queensland, Australia.

出版信息

Ecol Appl. 2023 Jun;33(4):e2852. doi: 10.1002/eap.2852. Epub 2023 Apr 18.

Abstract

Climate change is already having profound effects on biodiversity, but climate change adaptation has yet to be fully incorporated into area-based management tools used to conserve biodiversity, such as protected areas. One main obstacle is the lack of consensus regarding how impacts of climate change can be included in spatial conservation plans. We propose a climate-smart framework that prioritizes the protection of climate refugia-areas of low climate exposure and high biodiversity retention-using climate metrics. We explore four aspects of climate-smart conservation planning: (1) climate model ensembles; (2) multiple emission scenarios; (3) climate metrics; and (4) approaches to identifying climate refugia. We illustrate this framework in the Western Pacific Ocean, but it is equally applicable to terrestrial systems. We found that all aspects of climate-smart conservation planning considered affected the configuration of spatial plans. The choice of climate metrics and approaches to identifying refugia have large effects in the resulting climate-smart spatial plans, whereas the choice of climate models and emission scenarios have smaller effects. As the configuration of spatial plans depended on climate metrics used, a spatial plan based on a single measure of climate change (e.g., warming) will not necessarily be robust against other measures of climate change (e.g., ocean acidification). We therefore recommend using climate metrics most relevant for the biodiversity and region considered based on a single or multiple climate drivers. To include the uncertainty associated with different climate futures, we recommend using multiple climate models (i.e., an ensemble) and emission scenarios. Finally, we show that the approaches we used to identify climate refugia feature trade-offs between: (1) the degree to which they are climate-smart, and (2) their efficiency in meeting conservation targets. Hence, the choice of approach will depend on the relative value that stakeholders place on climate adaptation. By using this framework, protected areas can be designed with improved longevity and thus safeguard biodiversity against current and future climate change. We hope that the proposed climate-smart framework helps transition conservation planning toward climate-smart approaches.

摘要

气候变化已经对生物多样性产生了深远的影响,但气候变化适应尚未完全纳入用于保护生物多样性的基于区域的管理工具,如保护区。一个主要的障碍是缺乏关于如何在空间保护规划中纳入气候变化影响的共识。我们提出了一个使用气候指标优先保护气候避难所的框架,即气候暴露低、生物多样性保留高的区域。我们探讨了气候智能保护规划的四个方面:(1)气候模型集合;(2)多个排放情景;(3)气候指标;(4)识别气候避难所的方法。我们在西太平洋地区展示了该框架,但它同样适用于陆地系统。我们发现,气候智能保护规划的所有方面都考虑到了对空间规划配置的影响。气候指标的选择和识别避难所的方法对气候智能空间规划的结果有很大影响,而气候模型和排放情景的选择影响较小。由于空间规划的配置取决于使用的气候指标,因此基于气候变化单一指标(例如变暖)的空间规划不一定能抵御其他气候变化指标(例如海洋酸化)的影响。因此,我们建议根据单一或多个气候驱动因素,使用与生物多样性和区域最相关的气候指标。为了包括与不同气候未来相关的不确定性,我们建议使用多个气候模型(即集合)和排放情景。最后,我们表明,我们用于识别气候避难所的方法在以下两个方面存在权衡:(1)它们的气候智能程度,以及(2)它们在满足保护目标方面的效率。因此,方法的选择将取决于利益相关者对气候适应的相对重视程度。通过使用这个框架,可以设计出具有更长寿命的保护区,从而保护生物多样性免受当前和未来的气候变化影响。我们希望所提出的气候智能框架有助于将保护规划向气候智能方法过渡。

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