Spatiotemporal Dynamics of Vegetation Net Primary Productivity and Its Drivers in China's Three Eco‐Zones and Four Shelterbelts Region
ABSTRACT Understanding the spatiotemporal dynamics of vegetation carbon stocks in ecologically functional areas and identifying their driving factors remain crucial for informing ecosystem protection and restoration efforts. The three eco‐zones and four shelterbelts (TEFS) region encompasses critical ecological barriers and functional zones in China. Utilizing MODIS NDVI data, alongside climatic and topographic variables, we developed regionally optimized models to estimate net primary productivity (NPP) across the TEFS region from 2000 to 2023. Subsequently, the spatiotemporal variability of vegetation NPP and its associated drivers were explored using trend analysis, correlation, and residual analysis. The results revealed a significant NPP increase in approximately 90% of the TEFS region between 2000 and 2023, with an average annual increase rate of 3.46 gC m −2 yr −1 . The most rapid increases occurred in ecological zones along the Yellow River basin. NPP changes were driven by the combined effects of climate change (CC) and human activities (HA) over the 24‐year period. While CC contributed positively to NPP changes in 67.9% of the total area, HA had a positive impact in 75.4% of the region. Notably, HA dominated as the primary driver in western regions, whereas CC exerted a stronger influence in many eastern areas. Enhanced efforts in desertification control and protection of coastal wetland ecosystems are recommended to improve carbon sequestration potential.
Authors
- Yuhe Ji (ORCID: https://orcid.org/0000-0002-9115-9863)
- Linlin Lu (ORCID: https://orcid.org/0000-0003-1647-1950)
- Mengke Zhao (ORCID: https://orcid.org/0000-0003-0596-6608)
- Xuting Liu (ORCID: https://orcid.org/0000-0003-3980-5386)
- Jihua Meng
- Qingting Li (ORCID: https://orcid.org/0000-0002-6322-8307)
- Yonghuan Ma
Institutions
- Chinese Academy of Sciences (CN)
- Chang'an University (CN)
- Beijing Institute of Big Data Research (CN)
- Chinese Academy of Meteorological Sciences (CN)
- Aerospace Information Research Institute (CN)
Publication Details
- Journal
- Land Degradation and Development
- Published
- 2025-05-02
- DOI
- https://doi.org/10.1002/ldr.5629
- Primary Topic
- Land Use and Ecosystem Services
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China