Climate and human drivers of grassland carbon sink in the Tianshan Mountains, 2000–2050
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# README for supporting data: "Climate and human drivers of grassland carbon sink in the Tianshan Mountains, 2000–2050" ## 1. Dataset OverviewThis dataset supports the findings in the above paper (submitted to Ecological Indicators). It contains the main model outputs and derived data needed to reproduce all figures and tables. ## 2. File descriptions ### 2.1 Historical NPP rasters (2000–2024)Files: `Tianshan_NPP_2000.tif` to `Tianshan_NPP_2024.tif` (25 files)- Annual mean actual NPP estimated by the improved CASA model.- **Format**: GeoTIFF, LZW compressed- **CRS**: EPSG:4326 (WGS84)- **Spatial resolution**: 0.01° × 0.01° (~1 km)- **Units**: gC·m⁻²·yr⁻¹- **NoData**: -3.4028235e+38- **Used in**: Figures 3a, 4a *Note: The `.ovr` pyramid files are auxiliary and can be ignored.* ### 2.2 Future PNPP trend rasters (2025–2050)- `trend_ssp245.tif` – Linear trend (slope) of PNPP under SSP2‑4.5 (gC·m⁻²·yr⁻¹·yr⁻¹)- `trend_ssp585.tif` – Same for SSP5‑8.5- **Format, CRS, resolution, NoData** same as above- **Used in**: Figure 8b ### 2.3 Summary tables (CSV / XLS)- `grassland_type_trends.xls` – NPP trends for nine grassland subtypes (slope, R², p‑value, Z‑value). Used in Figure 5b and Supplementary Table 1.- `zonal_stats_wide_for_origin.csv` – Future PNPP zonal statistics per grassland type and year. Used in Figure 9.- `table3_scenario_area.csv` – Area percentages of driving scenarios (R1, R2, D1, D2). Used in Figure 6a.- `grassland_correlation_full.csv` – Partial correlation coefficients (Table 4 in the paper). ### 2.4 Study area boundary- `TSCD.SHP` (with .shx, .dbf, .prj) – Polygon of the Tianshan Mountain study area. Used as mask and spatial reference. ## 3. Methodological summary- Historical NPP: Improved CASA model (Potter et al., 1993; Liu et al., 2025) with MODIS and TerraClimate inputs.- PNPP: Miami model (Lieth, 1975).- Future climate: CMIP6 ACCESS‑CM2, SSP2‑4.5 and SSP5‑8.5, downscaled via NASA/GDDP‑CMIP6.- Trend analysis: Theil‑Sen + Mann‑Kendall for historical; linear regression for future. ## 4. LicenseThis dataset is released under **CC0 1.0 Universal (Public Domain Dedication)**. You may use it without restriction. ## 5. ContactCorresponding author: Zhonglin Xu Email: zlxu@xju.edu.cn ORCID: [your ORCID] ## 6. CitationWhen using this data, please cite:- This dataset (Zenodo/Dryad DOI – will be added)- The original article (once published)
