Spatiotemporal Impact Dataset of Climate Factor Trends on Forest NPP Changes in Southeast Tibet (2000-2021)

This dataset focuses on the forest distribution areas of southeastern Tibet (including Changdu City, Shannan City, etc.) over the period from 2000 to 2021. Its objective is to quantitatively reveal the long-term trends of four key climatic factors—annual mean precipitation (PREC), air temperature (TEMP), solar radiation (SRAD), and vapor pressure deficit (VPD)—as well as their driving effects on the spatiotemporal variations of Net Primary Productivity (NPP) in the forest vegetation of southeastern Tibet. All raw data were acquired via the Google Earth Engine (GEE) platform, comprising the MODIS MOD17A3HGF V6 NPP product, MODIS 16A2 air temperature data, CHIRPS precipitation data, and TerraClimate VPD and SRAD data. These data underwent a series of preprocessing steps—including clipping to the study area, coordinate system unification, annual mean synthesis, and spatial resolution standardization—before being utilized for analysis. The trends in climatic factors and NPP were assessed using the Theil-Sen slope estimator and the Mann-Kendall trend test; employing a significance threshold of |Z| > 1.65, pixel-level trends were categorized into three classes: significant increase, no significant change, and significant decrease. Quantitative attribution of the climatic factors' influence on NPP variations was performed using a Generalized Linear Model (GLM), with the multi-year mean NPP serving as the dependent variable and the multi-year means of forest age (AGE), PREC, SRAD, TEMP, and VPD serving as independent variables. All variables were Z-score standardized prior to model input, and the relative degree of influence exerted by each factor was gauged by the magnitude of its standardized regression coefficient.The dataset is organized into two subfolders based on the direction of NPP change: "Climatic Trends in NPP-Increasing Regions" and "Climatic Trends in NPP-Decreasing Regions." These folders store the trend data for the four climatic factors corresponding to their respective regions and can be directly read and processed using GIS software such as ArcGIS or QGIS. There are four raster files in total, all in GeoTIFF format (.tif): ZDNforest_prec_trendint.tif, ZDNforest_srad_trendint.tif, ZDNforest_temp_trendint.tif, and ZDNforest_vpd_trendint.tif. These files respectively record the spatiotemporal distribution of change trends for precipitation, mean annual solar radiation, mean annual air temperature, and mean annual vapor pressure deficit (VPD). The pixel values ​​within each file represent the comprehensive classification results for the corresponding climatic factor, derived from a combined analysis using the Theil-Sen slope estimator and the Mann-Kendall trend test. The vector files include administrative boundary files for Changdu City (CHANGDU.shp) and Shannan City (SHANNAN.shp), a boundary file for the entire Southeast Tibet study area (ZDNM.shp), a file depicting the distribution of rivers in Southeast Tibet (藏东南河流.shp), as well as point vector files identifying areas of increasing and decreasing Net Primary Production (NPP) for three specific forest types: Deciduous Broadleaf Forest (DBF), Evergreen Broadleaf Forest (EBF), and Evergreen Coniferous Forest (ENF). The administrative boundary and study area boundary files are suitable for spatial clipping, map overlaying, and zonal statistics, while the point files serve to support attribution analyses categorized by forest type.