Suppr超能文献

利用现有系统证据数据库减轻全球粮食系统危害中的挑战与机遇。

Challenges and opportunities in leveraging an existing systematic evidence database for mitigating hazards to the global food system.

作者信息

Willer David Frederick, Short Samuel W, Khripko Diana, Bremner Julie, Aldridge David C, Sutherland William J, Petrovan Silviu O

机构信息

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

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

出版信息

R Soc Open Sci. 2025 Mar 5;12(3):241645. doi: 10.1098/rsos.241645. eCollection 2025 Mar.

Abstract

The global food system, essential for delivering nutritional security to a growing population, is highly vulnerable to diverse hazards. This study investigates the feasibility of leveraging an existing systematic database, specifically the Conservation Evidence database, for mitigating environmental hazards impacting the food system. By focusing on human-wildlife conflict as a case study, we explored the database's potential to inform hazard mitigation strategies. Our analysis revealed significant geographical and taxonomic gaps, varied intervention strategies and differences in study designs across regions. We identified key challenges, such as the need for comprehensive tagging and filtering features, integration of non-academic data and broader stakeholder engagement. The findings underscore the complexity of adapting conservation databases for food system applications but highlight the potential benefits of a free-to-access, systematic, evidence-based approach focusing on food production hazard mitigation. Future work should focus on developing a dedicated food system hazard database, leveraging automation and machine learning to enhance data extraction and application efficacy, ultimately improving global food security and sustainability.

摘要

全球粮食系统对于为不断增长的人口提供营养安全至关重要,但极易受到各种危害的影响。本研究调查了利用现有系统数据库,特别是保护证据数据库,来减轻影响粮食系统的环境危害的可行性。通过将人类与野生动物冲突作为案例研究,我们探索了该数据库为危害缓解策略提供信息的潜力。我们的分析揭示了显著的地理和分类学差距、不同的干预策略以及各地区研究设计的差异。我们确定了关键挑战,例如需要全面的标记和筛选功能、整合非学术数据以及更广泛的利益相关者参与。研究结果强调了使保护数据库适用于粮食系统应用的复杂性,但突出了采用免费访问、系统、基于证据的方法来减轻粮食生产危害的潜在好处。未来的工作应侧重于开发专门的粮食系统危害数据库,利用自动化和机器学习来提高数据提取和应用效率,最终改善全球粮食安全和可持续性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/609d/12105789/b91a799c1b1b/rsos.241645.f001.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验