Data · dataset · 2026
Model Outputs and Analysis Code for “Food-System Spillovers Extend the Benefits of Phenology-Based Staple Crop Adaptatio
Listed in ScienceDB
Description
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.
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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.
Links
Where it is published
- DOI doi.org/10.57760/sciencedb.010do ↗
DOI / persistent id · from scidb cn
Catalogue records · 1
- OAI-PMH record scidb.cn/oai?verb=GetRecord&metadataPrefix=oai_dc&identifier=10.57760%2… ↗
metadata API · from scidb cn
Topics
- From keywords
- Earth & Environmental Science · Engineering · Humanities · Life Sciences · Medicine & Health · Social Science
- Inferred from text
- Agriculture, land and farm management 74%
Provenance · 1 source records, 12 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| ScienceDB | 10.57760/sciencedb.010do | 12 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| access_level | source · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].anzsrc:group:3002 | enrichment · scidb cn | taxonomy-embedding@1.0.0 | title+keywords+description (74%) |
| concepts[field].local:field:earth-environmental | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:engineering | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:humanities | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:life-sciences | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:medicine-health | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:social-science | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| description | source · scidb cn | connector:scidb_cn@1.0.0 | /metadata/dc/description |
| license | source · scidb cn | connector:scidb_cn@1.0.0 | /metadata/dc/rights |
| publication_date | source · scidb cn | connector:scidb_cn@1.0.0 | |
| title | source · scidb cn | connector:scidb_cn@1.0.0 | /metadata/dc/title |