## 2 Materials and Methods
### Data Sources and Processing  
In this study, the carbon budget response characteristics of vegetation changes in the Dongting Lake basin were studied based on remote sensing and ground multisource data. The primary data and their descriptions were as follows. (1) NDVI data. The data were obtained from NASA's MODIS NDVI (MOD 13A3) product for 2001-2020 ([[https://ladsweb.modaps.eosdis.nasa.gov/search/](https://ladsweb.modaps.eosdis.nasa.gov/search/)]([https://ladsweb.modaps.eosdis.nasa.gov/search/](https://ladsweb.modaps.eosdis.nasa.gov/search/)), accessed on 20 January 2022), and the data resolution is 1 km with synthetic products every month. The product is calculated from atmospheric corrected bidirectional surface reflectance to remove water, clouds, heavy aerosols, and cloud shadows. It is widely used to monitor vegetation change and ecological environment at regional and global scales [20]. (2) NPP data. The data were obtained from NASA's MODIS NPP (MOD17A3 HGF) dataset for 2001-2020 ([[https://ladsweb.modaps.eosdis.nasa.gov/search/order](https://ladsweb.modaps.eosdis.nasa.gov/search/order)]([https://ladsweb.modaps.eosdis.nasa.gov/search/order](https://ladsweb.modaps.eosdis.nasa.gov/search/order)), accessed on 20 January 2022), and the data resolution is 500 m with synthetic products every year. These data are based on MODIS/TERRA satellite remote sensing metrics. The annual NPP information is calculated by using the MME-BGG model and the light energy usage model, which is an upgraded version of the MOD17 data product. This product has a good correlation with Chinese field observation data (\(R^{2}\) = 0.81) [21], showing that it is reliable. (3) Meteorological data. These mainly include monthly precipitation and temperature data, which are used for calculating soil microbial heterotrophic respiration and as input parameters of land use simulation models. The data were obtained from the National Science and Technology Infrastructure Platform-National Earth System Science Data Center  
Figure 1: The Dongting Lake Basin. ([[http://www.geodata.cn](http://www.geodata.cn)]([http://www.geodata.cn](http://www.geodata.cn)), accessed on 16 February 2022), with a 1 km data resolution and monthly synthesis products [22]. (4) Land use data. These were used to analyze the spatial variability in NEP for different land use types and as input parameters of the land use change model (CLUE-S). The data were obtained from Globalland30 ([[http://www.globallandcover.com](http://www.globallandcover.com)]([http://www.globallandcover.com](http://www.globallandcover.com)), accessed on 12 March 2022), and it is a global Land cover dataset with a 30 m spatial resolution developed in China [23]. (5) Natural and social driving factor data. As the input parameters of the land use simulation model (CLUE-S), the driving factors of LUCC mainly include natural geographical factors, which are relatively stable on a short time scale, and socioeconomic factors, such as population economy and road traffic. Population density data were obtained from Worldpop ([[https://www.worldpop.org/](https://www.worldpop.org/)]([https://www.worldpop.org/](https://www.worldpop.org/)), accessed on 30 March 2022) [24] and GDP data from the Resource and Environment Science and Data Center of the Chinese Academy of Sciences ([[http://www.resdc.cn](http://www.resdc.cn)]([http://www.resdc.cn](http://www.resdc.cn)), accessed on 1 April 2022) [25].