Assessing Multi‐Dimensional Impacts of Achieving Sustainability Goals by Projecting the Sustainable Agriculture Matrix Into the Future
Assessing Multi‐Dimensional Impacts of Achieving Sustainability Goals by Projecting the Sustainable Agriculture Matrix Into the Future
复制标题
DOI：
10.1029/2022ef003323
复制
发表时间：
2023-10
期刊：
影响因子：
--
通讯作者：
P. Kyle;Mary Ollenburger;Xin Zhang;Hassan Niazi;Siddarth Durga;Yang Ou
中科院分区：
文献类型：
--
作者：
P. Kyle;Mary Ollenburger;Xin Zhang;Hassan Niazi;Siddarth Durga;Yang Ou
可持续性的概念本质上跨越多个空间尺度、部门、变量和时间范围。本研究将最近开发的评估当今农业可持续性的方法与基于过程的综合评估模型联系起来，以实现对区域和情景的可持续性的前瞻性分析。可持续农业矩阵使用18个指标变量估计了国家一级当前的农业可持续性，本研究使用全球变化分析模型的增强版估计了其中9个到2100年的可持续性。情景包括一个参考情景，以及单独或组合应用以下措施的情景，这些措施被认为可以提高可持续性：产量集约化，向更多植物性饮食（“弹性饮食”）过渡，以及经济范围内的温室气体排放减缓。这些设想说明了在全球所有区域提高农业可持续性的努力所固有的相当大的复杂性和权衡。例如，产量强化通常会增加氮污染，弹性饮食会减少农业产量，温室气体减排工作可能会增加森林砍伐或因随之而来的生物能源需求而排挤作物和牲畜生产。然而，区域间的反应存在相当大的异质性，这种次级反应的重要性也因区域而异。本研究中开发的分析和后处理方法可以量化和可视化跨区域，时间段和情景的农业可持续性指标变量之间权衡的绝对和相对幅度。
The concept of sustainability inherently spans multiple spatial scales, sectors, variables, and time horizons. This study links a recently developed method of assessing present‐day agricultural sustainability across environmental, economic, and social dimensions with a process‐based integrated assessment model, in order to allow forward‐looking analysis of sustainability by region and scenario. The sustainable agriculture matrix estimates present‐day agricultural sustainability at the national level using 18 indicator variables, of which this study estimates nine to the year 2100, using an enhanced version of the Global Change Analysis Model. Scenarios include a reference scenario, and scenarios that apply the following measures, both individually and in combination, that are thought to improve sustainability: yield intensification, transition toward more plant‐based (“flexitarian”) diets, and economy‐wide greenhouse gas emissions mitigation. The scenarios illustrate considerable complexity and tradeoffs inherent to efforts to improve agricultural sustainability in all regions globally. For example, yield intensification typically increases nitrogen pollution, flexitarian diets can reduce agricultural output, and greenhouse gas mitigation efforts may either increase deforestation or crowd out crop and livestock production due to consequent bioenergy demands. However, there is considerable inter‐regional heterogeneity in the responses, and the importance of such secondary responses also differs by region. The analysis and post‐processing methods developed in this study allow quantification and visualization of the absolute and relative magnitude of the tradeoffs between agricultural sustainability indicator variables across regions, time periods, and scenarios.