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- Title
Assessing Multi‐Dimensional Impacts of Achieving Sustainability Goals by Projecting the Sustainable Agriculture Matrix Into the Future.
- Authors
Kyle, Page; Ollenburger, Mary; Zhang, Xin; Niazi, Hassan; Durga, Siddarth; Ou, Yang
- Abstract
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. Plain Language Summary: This study links two fundamentally different approaches of assessing long‐term agricultural sustainability. The first one, the sustainable agricultural matrix (SAM), uses 18 economic, environmental, and social indicator variables, available at the national scale for recent historical years. This approach characterizes present‐day sustainability, but isn't well‐suited to long‐term assessment in the context of changes in socio‐economic, technological, and/or environmental conditions. The second approach involves a process‐based integrated assessment model, GCAM, which explicitly tracks the physical inputs and outputs of the agricultural sector, and how these interact with the other dynamically evolving systems represented in the model (energy, water, land, atmosphere, climate). Because GCAM only carries information sufficient to calculate 3 of the 18 variables in the SAM, these approaches for assessing sustainability are normally quite distinct. In this study we expand the capabilities of GCAM in order to allow analysis of 9 of the 18 SAM variables, and perform an assessment of the global and regional consequences to 2100 of realizing several ambitions thought to improve sustainability in general: reducing greenhouse gas emissions, transitioning toward predominantly plant‐based diets, and intensifying agriculture so as to reduce the areal extent of cropland globally. Key Points: The sustainable agriculture matrix is estimated to 2100 in the Global Change Analysis ModelYield intensification, dietary shift, and greenhouse gas mitigation scenarios are assessedAssessment of these tradeoffs in a consistent framework improves the quality of information for decision‐making
- Subjects
SUSTAINABLE agriculture; GREENHOUSE gas mitigation; AGRICULTURAL intensification; AGRICULTURE; PLANT-based diet; LIVESTOCK productivity
- Publication
Earth's Future, 2023, Vol 11, Issue 10, p1
- ISSN
2328-4277
- Publication type
Article
- DOI
10.1029/2022EF003323