## 2 Materials and Methods
### Data Acquisition  
The vegetation GPP, NPP, and ET remote sensing data used were obtained from MODIS data products, specifically MOD17A3H, MOD17A3H, and MOD16A2. MODIS data products are obtained from the Terra polar-orbiting satellite, which was launched by NASA in 1999. These data have been extensively utilized in research on land cover change, biodiversity dynamics, and environmental monitoring [33; 34]. The NPP data have an annual temporal resolution, while GPP and ET data have an 8-day temporal resolution. All datasets have a spatial resolution of 500 m, cover the timeframe from 2001 to 2023, use the WGS-84 geographic coordinate system, and are provided in GeoTIFF format. To avoid traditional challenges associated with downloading data, such as re-projection and mosaicking, this study utilized the Google Earth Engine (GEE) platform for data acquisition. Based on the GEE platform, outliers were removed from the raw data, and annual totals for GPP and ET were calculated. The processed data were exported in GeoTIFF format via Google Drive. Using ArcGIS 10.7, batch masking was performed based on the vector boundaries of the NMR, resulting in the final analyzable datasets. Specific data are detailed in Table 1.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Data** & **Data Source** & **Spatial Resolution** & **Temporal Resolution** \\ \hline \multirow{4}{*}{GPP} & MOD17A3 HGFv061 ([[https://lpdaac.usgs](https://lpdaac.usgs)]([https://lpdaac.usgs](https://lpdaac.usgs)). & \\  & gov/products/mod17a3 hgfv061/, & 500 m & 1a \\  & accessed on 1 September 2024) & & \\  & MOD17A3 HGFv061 ([[https://lpdaac.usgs](https://lpdaac.usgs)]([https://lpdaac.usgs](https://lpdaac.usgs)). & \\ NPP & gov/products/mod17a3 hgfv061/, & 500 m & 1a \\  & accessed on 1 September 2024) & & \\  & MOD16A2 GFv061 ([[https://lpdaac.usgs](https://lpdaac.usgs)]([https://lpdaac.usgs](https://lpdaac.usgs)). & \\ ET & gov/products/mod16a2 gfv061/, & 500 m & 8d \\  & accessed on 1 September 2024) & & \\ \hline \hline \end{tabular}
\end{table}
Table 1: Data sources.  
Figure 1: Elevation maps and plant types of the NMR.  
Land cover datasets were sourced from the MCD12Q1 products based on the GEE platform, which has a spatial resolution of 500 m. As classified under the system established by the International Geosphere-Biosphere Program (IGBP) and the specific objectives of this study, the data were reclassified into seven categories, included forest, grasslands, croplands, shrublands, and barren lands, among others. The analysis primarily concentrated on the spatiotemporal variation in CUE and WUE for forest, grasslands, croplands, and shrublands.  
Precipitation and temperature were derived from the 1 km monthly datasets, both published by the National Tibetan Plateau Data Center. These datasets, produced through the downscaling approach using the CRU 0.5\({}^{\circ}\) global data from WorldClim, have been cross-verified with measurements from approximately 500 meteorological stations across China, ensuring their precision and dependability [35]. The boundary data for the NMR were used in conjunction with ArcGIS 10.7 to clip the datasets and resample them to a spatial resolution of 500 m. This process enabled the generation of annual-scale meteorological raster data for the study area, which were later employed to examine the determinants affecting vegetation CUE and WUE.