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将危害映射到全球粮食系统。

Mapping hazards to the global food system.

作者信息

Willer David F, Short Samuel, Khripko Diana, Petrovan Silviu O, Christie Alec P, Bremner Julie, Sutherland William J, Aldridge David C

机构信息

Department of Zoology, University of Cambridge, The David Attenborough Building, Pembroke Street, Cambridge, CB2 3QZ, UK.

Institute for Manufacturing, IfM Engage, University of Cambridge, 17 Charles Babbage Road, Cambridge, CB3 0FS, UK.

出版信息

Environ Monit Assess. 2024 Dec 4;197(1):18. doi: 10.1007/s10661-024-13475-4.

DOI:10.1007/s10661-024-13475-4
PMID:39630310
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11618188/
Abstract

Environmental hazards associated with the global food system threaten societal integrity. Yet, there is a major data gap in the global understanding of how the prevalence of hazards is changing over time, how different classes of hazard are distributed, and whether the combined literature represents hazard prevalence equitably across research, policy and legislation, and news. Here, we explore this data gap, leveraging global research, policy, and news databases. We reveal increasing attention on food system hazards over time, in line with major geopolitical events. Coverage on environmental hazards is not distributed equally geographically, and media attention does not match research and policy evidence focus. Climate change and water scarcity in particular receive substantial attention across all source types, whilst, for example biodiversity loss, genetic erosion, or harmful algal blooms receive much less. Environmental, financial and food systems sustainability damage due to hazard neglect should be avoided and a first step is to understand, map, and quantify biases in focus.

摘要

与全球粮食系统相关的环境危害威胁着社会的完整性。然而,在全球范围内,对于危害的流行程度如何随时间变化、不同类型的危害如何分布,以及综合文献在研究、政策与立法以及新闻方面是否公平地反映危害流行情况,存在重大的数据缺口。在此,我们利用全球研究、政策和新闻数据库来探究这一数据缺口。我们发现,随着时间推移,人们对粮食系统危害的关注不断增加,这与重大地缘政治事件相符。环境危害的报道在地理上分布不均,媒体关注与研究及政策证据重点不匹配。特别是气候变化和水资源短缺在所有来源类型中都受到了大量关注,而例如生物多样性丧失、基因侵蚀或有害藻华等受到的关注则少得多。应避免因忽视危害而对环境、金融和粮食系统可持续性造成损害,第一步是了解、梳理并量化关注重点中的偏差。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4ca9/11618188/85966391f41e/10661_2024_13475_Fig4a_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4ca9/11618188/acbc4bfc8300/10661_2024_13475_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4ca9/11618188/37e6c5ec4e71/10661_2024_13475_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4ca9/11618188/b54d23b49899/10661_2024_13475_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4ca9/11618188/85966391f41e/10661_2024_13475_Fig4a_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4ca9/11618188/acbc4bfc8300/10661_2024_13475_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4ca9/11618188/37e6c5ec4e71/10661_2024_13475_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4ca9/11618188/b54d23b49899/10661_2024_13475_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4ca9/11618188/85966391f41e/10661_2024_13475_Fig4a_HTML.jpg

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