Suppr超能文献

绘制和监测零森林砍伐承诺

Mapping and Monitoring Zero-Deforestation Commitments.

作者信息

Austin Kemen G, Heilmayr Robert, Benedict Jason J, Burns David N, Eggen Michael, Grantham Hedley, Greenbury Aida, Hill Jane K, Jenkins Clinton N, Luskin Matthew S, Manurung Timer, Rasmussen Laura V, Rosoman Grant, Rudorff Bernardo, Satar Musnanda, Smith Charlotte, Carlson Kimberly M

机构信息

RTI International's Center for Applied Economics, Research Triangle Park, North Carolina, United States.

Bren School of Environmental Science and Management, University of California Santa Barbara, Santa Barbara, California, United States.

出版信息

Bioscience. 2021 Aug 18;71(10):1079-1090. doi: 10.1093/biosci/biab082. eCollection 2021 Oct.

Abstract

A growing number of companies have announced zero-deforestation commitments (ZDCs) to eliminate commodities produced at the expense of forests from their supply chains. Translating these aspirational goals into forest conservation requires forest mapping and monitoring (M&M) systems that are technically adequate and therefore credible, salient so that they address the needs of decision makers, legitimate in that they are fair and unbiased, and scalable over space and time. We identify 12 attributes of M&M that contribute to these goals and assess how two prominent ZDC programs, the Amazon Soy Moratorium and the High Carbon Stock Approach, integrate these attributes into their M&M systems. These programs prioritize different attributes, highlighting fundamental trade-offs in M&M design. Rather than prescribe a one-size-fits-all solution, we provide policymakers and practitioners with guidance on the design of ZDC M&M systems that fit their specific use case and that may contribute to more effective implementation of ZDCs.

摘要

越来越多的公司宣布了零毁林承诺(ZDC),以从其供应链中消除以牺牲森林为代价生产的商品。要将这些理想目标转化为森林保护行动,就需要具备技术上足够且因此可信、显著从而能满足决策者需求、合法即公平且无偏见、以及能在空间和时间上扩展等特点的森林测绘与监测(M&M)系统。我们确定了有助于实现这些目标的M&M的12个属性,并评估了两个著名的ZDC项目——亚马逊大豆禁运和高碳储存方法——如何将这些属性整合到其M&M系统中。这些项目对不同属性进行了优先排序,突出了M&M设计中的基本权衡。我们并非规定一种一刀切的解决方案,而是为政策制定者和从业者提供有关设计适合其特定用例的ZDC M&M系统的指导,这可能有助于更有效地实施ZDC。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/324c/8490929/82c8d7a3db01/biab082fig1.jpg

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验