Spatiotemporal Characteristic Prediction and Driving Factor Analysis of Vegetation Net Primary Productivity in Central China Covering the Period of 2001–2019

Xiuping Hao, Xueliu Wang, Jianqin Ma (), Yang Chen and Shiyi Luo
Additional contact information
Xiuping Hao: School of Water Resources, North China University of Water Resources and Electric Power, Zhengzhou 450045, China
Xueliu Wang: School of Water Resources, North China University of Water Resources and Electric Power, Zhengzhou 450045, China
Jianqin Ma: School of Water Resources, North China University of Water Resources and Electric Power, Zhengzhou 450045, China
Yang Chen: School of Water Conservancy, North China University of Water Resources and Electric Power, Zhengzhou 450045, China
Shiyi Luo: School of Water Resources, North China University of Water Resources and Electric Power, Zhengzhou 450045, China

Land, 2023, vol. 12, issue 12, 1-18

Abstract: Unveiling the variation mechanism of vegetation net primary productivity (NPP) and elucidating the underlying drivers of these changes is highly necessitated for terrestrial carbon cycle research and global carbon emission control. Taking Henan Province, renowned as the anciently central China and current China’s foremost grain producer, as an example, this study employed the Theil–Sen Median Trend Analysis to evaluate the spatiotemporal characteristics and trends of NPP. Correlation Analysis and Residual Analysis were used to explain the drivers of NPP dynamics. To deepen the inquiry, the Geodetector method was employed to scrutinize the multifaceted effects and interplay among diverse variables influencing NPP. The result showed demonstrated that approximately 85.72% of the area showed an increase in NPP, covering a broad geographical distribution. Notably, 89.31% of the province has witnessed a positive human-driven NPP change. It means human activities emerged as a driving force with a positive effect on vegetation NPP, consequently fostering an increasing trend of NPP. Among climatic factors, the correlation between NPP and precipitation was stronger than that between the temperature and NPP, the determined power of factors in Henan Province was population density, (0.341) > GDP (0.326) > precipitation (0.255) > elevation (0.167) > slope (0.136) > temperature (0.109), and a single factor had a lesser interaction effect than two factors. The implications of these findings extend beyond the realms of research, potentially offering valuable insights into the formulation of targeted ecosystem restoration measures tailored to the distinct context of Henan Province, and also expect to provide crucial references for carbon emission control in China and across the world.

Keywords: NPP; residual analysis; Geodetector; human-driven NPP; climate change (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2023
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/2073-445X/12/12/2121/pdf (application/pdf)
https://www.mdpi.com/2073-445X/12/12/2121/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jlands:v:12:y:2023:i:12:p:2121-:d:1290439

Access Statistics for this article

Land is currently edited by Ms. Carol Ma

More articles in Land from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().