Dataset for Assessing Multi-Dimensional Impacts of Achieving Sustainability Goals by Projecting the Sustainable Agriculture Matrix into the Future

This data repository feeds into the meta-repository setup for post-processing of GCAM-SAM outputs. GitHub link of meta-repository is: https://github.com/JGCRI/Kyle-etal_2022_EF Folders: model/ is the static version of the model used to simulate 8 scenarios. See the GitHub GCAM-SAM repository to follow active development of this model. inputs/ folder contains input datasets and scripts used to prepare files while postprocessing. This is to be used with GitHub post-processing meta-repository. outdata/ contains GCAM-SAM output and post-processed output files used to plot figures. Key files: SAM-matrix.dat is the consolidated GCAM-SAM output. Use proj_load.R in the metarepo to read the file. region_vals.csv has all 8 indicators in all 8 scenarios for years 2020 till 2100 on a 10 year time step. Short introduction to the study: In this paper sustainable agriculture matrix (SAM) is estimated to 2100 using Global Change Analysis Model (GCAM). We model combinatorial variations of yield intensification, dietary shift, and greenhouse gas mitigation scenarios. Findings include scenarios having significant tradeoffs across multiple environmental, economic, and social dimensions. Assessment of these multi-dimensional tradeoffs in a consistent framework improves the quality of information for decision-making. Should you have any questions, feel free to reach out Page Kyle at [e-mail].本数据集仓库服务于GCAM-SAM输出后处理的元仓库（meta-repository）搭建。该元仓库的GitHub链接为：https://github.com/JGCRI/Kyle-etal_2022_EF 文件夹说明： model/ 为用于模拟8种情景的模型静态版本。如需追踪该模型的迭代开发，请访问GitHub上的GCAM-SAM仓库。 inputs/ 文件夹包含后处理阶段所需的输入数据集与文件制备脚本，需配合元仓库（metarepo）中的后处理流程使用。 outdata/ 包含用于绘图的GCAM-SAM原始输出与经后处理的结果文件。 关键文件说明： SAM-matrix.dat 为整合后的GCAM-SAM输出文件，可通过元仓库中的proj_load.R脚本读取该文件。 region_vals.csv 包含2020年至2100年（以10年为时间步长）的8种情景下全部8项指标数据。 本研究简介： 本研究借助全球变化分析模型（Global Change Analysis Model, GCAM），将可持续农业矩阵（Sustainable Agriculture Matrix, SAM）推演至2100年。我们建模了产量强化、膳食结构转型与温室气体减排三类情景的组合变体。研究结果表明，部分情景在环境、经济与社会多个维度存在显著权衡关系。在统一框架下评估此类多维度权衡，可提升决策参考信息的质量。 如有任何疑问，请联系Page Kyle，邮箱地址：[e-mail]。