Analysis of Spatiotemporal Variation and Driving Forces of Vegetation Net Primary Productivity in the North China Plain over the Past Two Decades

The net primary productivity (NPP) of vegetation—a critical component of ecosystem carbon cycling and a key indicator of the quality and functionality of ecosystems—is jointly influenced by natural and anthropogenic factors. As NPP is a vital agricultural and ecological region in China, understanding the spatiotemporal dynamics and driving mechanisms of vegetation NPP in the North China Plain (NCP) has significant implications for regional sustainable development. Utilizing MODIS NPP, temperature, precipitation, and human activity data from 2003 to 2023, this study employs univariate linear regression, ArcGIS spatial analysis, and the Hurst index to investigate the spatiotemporal characteristics, driving factors, and future trends in vegetation NPP. The results indicate that vegetation NPP exhibited a fluctuating upward trend over the 21-year period, with an annual increase of 2.60 g C/m2. Spatially, NPP displayed a “high in the south, low in the north” pattern. There is significant spatial heterogeneity between temperature, precipitation, and vegetation NPP in the study area, with natural factors generally exerting a greater influence than human activities; however, the coupling of human activities with other factors significantly amplify their impact. The Hurst index (mean: 0.43) revealed an anti-persistent future trend in vegetation NPP, suggesting substantial uncertainties regarding its long-term dynamics. These findings enhance our understanding of the responses of vegetation to global change and provide a scientific basis for balancing food security and ecological conservation in the NCP.

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Publication Details

Journal
Agronomy
Published
2025-04-17
DOI
https://doi.org/10.3390/agronomy15040975
Citations
3
Primary Topic
Remote Sensing and Land Use
Type
article
Field-Weighted Citation Impact
3.90
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article

Analysis of Spatiotemporal Variation and Driving Forces of Vegetation Net Primary Productivity in the North China Plain over the Past Two Decades

Liyan Shang, Kuan‐Ching Li, Dongming Zhang, Zhiyuan An et al.
3 citations
Agronomy
Remote Sensing and Land Use
3.90
article

Analysis of Spatiotemporal Variation and Driving Forces of Vegetation Net Primary Productivity in the North China Plain over the Past Two Decades

Liyan Shang, Kuan‐Ching Li, Dongming Zhang, Zhiyuan An, Mingxuan Yi, Kelin Sui
article en
3 citations

Abstract

The net primary productivity (NPP) of vegetation—a critical component of ecosystem carbon cycling and a key indicator of the quality and functionality of ecosystems—is jointly influenced by natural and anthropogenic factors. As NPP is a vital agricultural and ecological region in China, understanding the spatiotemporal dynamics and driving mechanisms of vegetation NPP in the North China Plain (NCP) has significant implications for regional sustainable development. Utilizing MODIS NPP, temperature, precipitation, and human activity data from 2003 to 2023, this study employs univariate linear regression, ArcGIS spatial analysis, and the Hurst index to investigate the spatiotemporal characteristics, driving factors, and future trends in vegetation NPP. The results indicate that vegetation NPP exhibited a fluctuating upward trend over the 21-year period, with an annual increase of 2.60 g C/m2. Spatially, NPP displayed a “high in the south, low in the north” pattern. There is significant spatial heterogeneity between temperature, precipitation, and vegetation NPP in the study area, with natural factors generally exerting a greater influence than human activities; however, the coupling of human activities with other factors significantly amplify their impact. The Hurst index (mean: 0.43) revealed an anti-persistent future trend in vegetation NPP, suggesting substantial uncertainties regarding its long-term dynamics. These findings enhance our understanding of the responses of vegetation to global change and provide a scientific basis for balancing food security and ecological conservation in the NCP.

AgronomyVol. 15(4)
China Geological Survey (CN)
Openalex Percentile: Top 7%
Remote Sensing and Land Use
3.90
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