Gaps in U.S. livestock data are a barrier to effective environmental and disease management.

IF 5.8 2区 环境科学与生态学 Q1 ENVIRONMENTAL SCIENCES
Environmental Research Letters Pub Date : 2025-03-01 Epub Date: 2025-02-11 DOI:10.1088/1748-9326/adb050
Rebecca Logsdon Muenich, Sanskriti Aryal, Amanda J Ashworth, Michelle L Bell, Melanie R Boudreau, Stephanie A Cunningham, K Colton Flynn, Kerry A Hamilton, Ting Liu, Michael L Mashtare, Natalie G Nelson, Barira Rashid, Arghajeet Saha, Danica Schaffer-Smith, Callie Showalter, Aureliane Tchamdja, Jada Thompson
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引用次数: 0

Abstract

Livestock are a critical part of our food systems, yet their abundance globally has been cited as a driver of many environmental and human health concerns. Issues such as soil, water, and air pollution, greenhouse gas emissions, aquifer depletion, antimicrobial resistance genes, and zoonotic disease outbreaks have all been linked to livestock operations. While many studies have examined these issues at depth at local scales, it has been difficult to complete studies at regional or national scales due to the dearth of livestock data, hindering pollution mitigation or response time for tracing and monitoring disease outbreaks. In the U.S. the National Agricultural Statistics Service completes a Census once every 5 years that includes livestock, but data are only available at the county level leaving little inference that can be made at such a coarse spatiotemporal scale. While other data exist through some regulated permitting programs, there are significant data gaps in where livestock are raised, how many livestock are on site at a given time, and how these livestock and, importantly, their waste emissions, are managed. In this perspective, we highlight the need for better livestock data, then discuss the accessibility and key limitations of currently available data. We then feature some recent work to improve livestock data availability through remote-sensing and machine learning, ending with our takeaways to address these data needs for the future of environmental and public health management.

美国牲畜数据的缺失是有效的环境和疾病管理的障碍。
牲畜是我们粮食系统的重要组成部分,但它们在全球范围内的丰富已被认为是许多环境和人类健康问题的驱动因素。土壤、水和空气污染、温室气体排放、含水层枯竭、抗菌素耐药性基因和人畜共患疾病暴发等问题都与畜牧业经营有关。虽然许多研究在地方层面深入研究了这些问题,但由于缺乏牲畜数据,妨碍了减轻污染或追踪和监测疾病爆发的反应时间,因此很难完成区域或国家层面的研究。在美国,国家农业统计局每5年完成一次人口普查,其中包括牲畜,但数据只能在县一级获得,因此在如此粗糙的时空尺度上几乎无法做出推断。虽然通过一些受监管的许可项目存在其他数据,但在牲畜的饲养地点、特定时间内现场有多少牲畜、以及如何管理这些牲畜,重要的是如何管理它们的废物排放等方面存在重大数据缺口。从这个角度来看,我们强调需要更好的牲畜数据,然后讨论当前可用数据的可访问性和主要局限性。然后,我们介绍了最近通过遥感和机器学习改善牲畜数据可用性的一些工作,最后提出了解决未来环境和公共卫生管理中这些数据需求的要点。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Environmental Research Letters
Environmental Research Letters 环境科学-环境科学
CiteScore
11.90
自引率
4.50%
发文量
763
审稿时长
4.3 months
期刊介绍: Environmental Research Letters (ERL) is a high-impact, open-access journal intended to be the meeting place of the research and policy communities concerned with environmental change and management. The journal''s coverage reflects the increasingly interdisciplinary nature of environmental science, recognizing the wide-ranging contributions to the development of methods, tools and evaluation strategies relevant to the field. Submissions from across all components of the Earth system, i.e. land, atmosphere, cryosphere, biosphere and hydrosphere, and exchanges between these components are welcome.
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