2026-10-12T06:17:41Z https://www.scidb.cn/oai

10.57760/sciencedb.39965 2026-06-15T10:39:41Z

2026-06-15 Hidden spatial compensation sustains apparent stability in global maize cultivation doi:10.57760/sciencedb.39965 en This repository contains the Python analysis code and derived data supporting the manuscript “Hidden spatial compensation sustains apparent stability in global maize cultivation”. The code was developed and tested using Python v3.10.13. The repository is organized into Code_core and Data_core.Code_core/Code_for_main_analysis contains memory-safe Python scripts used for the main analyses, including input inspection, trajectory compaction, construction of the 0.015° cell-event table, covariate attachment, maize mobility and recovery-replacement accounting, water-risk and hydroclimatic overlays, basin/country accounting, uncertainty analyses, and production/trade exposure analyses.Code_core/Code_for_SI contains supplementary scripts for preparing the GGCP10 maize production-importance baseline, summarizing annual maize fractions to 0.015° grids, exporting basin/country mechanism vectors, and running sensitivity analyses for intensity tolerance and denominator choices.Data_core contains the derived tables and aligned layers required by the scripts and used to support the main figures and supplementary analyses. Core files include the compact 0.015° trajectory table (trajectory_summary_by_0p015_cell_compact.csv) and the covariate-enriched cell-event table (cell_event_table_0p015_with_covariates2.csv). Additional files provide validation and confusion-matrix inputs (accuracy_confusion_rates_by_region_season_year.csv, annual_confusion_for_error_null_GLOBAL.csv), basin and country reporting-unit layers (basin_idx.tif, basin_map.csv, country_idx_aligned_to_maize0p015.tif, country_map.csv), GGCP10 production-importance layers (GGCP10_yield_layer/), recovery–replacement and water-risk summaries, aggregation-blindness diagnostics, event-year hydroclimatic overlays, and FAOSTAT production/trade tables. Area variables are reported in km² unless otherwise stated.The annual 10 m maize map products and public external datasets are described in the manuscript Data availability statement. This repository provides the derived data and scripts needed to reproduce the reported analytical results. Global maize cultivation; Hidden spatial compensation; Code and Data Guilong Xiao Jianxi Huang Fei Li Anne Gobin Xuecao Li Kaiqi Du Wei Su Shuangxi Miao Juepeng Zheng Yelu Zeng Xiaojun Li Jean-Pierre Wigneron Philippe Ciais PUBLIC https://creativecommons.org/licenses/by/4.0/ dataset Science Data Bank