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  • 标题:Co-development of a risk assessment strategy for managed relocation
  • 本地全文:下载
  • 作者:Aviv Karasov-Olson ; Mark W. Schwartz ; Sarah A. Skikne
  • 期刊名称:Ecological Solutions and Evidence
  • 电子版ISSN:2688-8319
  • 出版年度:2021
  • 卷号:2
  • 期号:3
  • 页码:1-10
  • DOI:10.1002/2688-8319.12092
  • 语种:English
  • 出版社:John Wiley & Sons, Inc.
  • 摘要:Resource managers face mounting challenges when it comes to the implementation of climate change adaptation strategies. Novel adaptation strategies, such as managed relocation, frequently entail embracing substantial risk of unintended harm to the focal ecosystems, in an effort to alleviate serious threats to biological diversity (e.g. extinction). Assessing ecological risks associated with different adaptation strategies is consistently called for, but the process for doing so is often undefined. Here, we describe a collaboration amongst university researchers, agency scientists and resource managers to create a set of ecological risk assessment protocols for managed relocation decision support. These protocols are designed to foster a rigorous assessment of ecological risk, while simultaneously being flexible and easy to use. We describe a collaborative process through which we developed a structure for assessing risk that includes a suite of 17 risk categories aggregated into six overarching groups, which is placed within a broader decision context for managed relocation (e.g. evaluating feasibility, social acceptability). Our risk scoring includes both scaled estimates of risk and perceived confidence in those estimates. Because of differences in the importance of risk categories, we do not recommend a quantitative summary across risk areas, but suggest decision makers make decisions based on three criteria: overall confidence that a proposed action can be confidently evaluated; low overall level or risk across categories; and no single risk category that is highly likely to result in severe adverse outcomes.
  • 关键词:assisted colonisation;assisted migration;climate change;decision support;ecological risk
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