2026-10-14T20:02:18Z https://www.scidb.cn/oai

10.57760/sciencedb.010do 2026-09-04T17:33:57Z

2026-09-04 Model Outputs and Analysis Code for “Food-System Spillovers Extend the Benefits of Phenology-Based Staple Crop Adaptatio doi:10.57760/sciencedb.010do en This dataset contains the model outputs, supporting data, and analysis code used in the study “Food-system spillovers extend the benefits of phenology-based staple crop adaptation.”The study combines crop-yield projections from the Global Gridded Crop Model Intercomparison (GGCMI) with the Global Change Analysis Model (GCAM v7.0) to examine how phenology-based cultivar adaptation in maize, wheat, rice, and soybean affects crop production, land allocation, food prices, and the affordability of a healthy diet. The analysis covers SSP1–2.6, SSP2–4.5, and SSP3–6.0 through the end of the twenty-first century. Unless otherwise specified, all effects compare simulations including climate change and cultivar adaptation with paired simulations including the same climate change but no cultivar adaptation.The dataset includes climate-change-only model outputs; cultivar-adaptation outputs incorporating a USDA-calibrated 10% increase in seed costs; adaptation outputs without additional seed costs; seed-cost sensitivity experiments spanning increases from 0% to 100%; population, income, income-distribution, and food-consumption inputs used to estimate healthy-diet affordability; USDA crop cost-and-return data; GCAM regional boundary files; and Python scripts and a Jupyter Notebook for reproducing the main and supplementary figures.Large GCAM output collections are provided as ZIP archives. After downloading, users should follow the instructions in README.md to extract the CSV files and place them directly in the corresponding climate_only, adaptation_usda_cost, or adaptation_no_cost directory. The supplied Jupyter Notebook can automatically extract and flatten CSV files stored within nested archive directories.The primary manuscript workflow uses files containing “_USDA” while excluding files containing “test”. The historical no-cost workflow is retained separately and is not combined with the primary results. In the original filenames, “min”, “mean”, and “max” identify low-, intermediate-, and high-benefit cultivar-adaptation responses, respectively; they do not represent the ensemble statistics reported in the study. climate change; cultivar adaptation; crop phenology; staple crops; maize; wheat; rice; soybean; crop production; land-use change; food prices; healthy-diet affordability; food systems; integrated assessment modelling; GGCMI; GCAM Yongye Jiang PUBLIC https://creativecommons.org/licenses/by/4.0/ dataset Science Data Bank