Driving Factor Analysis of Ecosystem Service Balance for Watershed Management in the Lancang River Valley, Southwest China

Shiliang Liu, Yongxiu Sun, Xue Wu, Weiqiang Li, Yixuan Liu and Lam-Son Phan Tran
Additional contact information
Shiliang Liu: State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing 100875, China
Yongxiu Sun: State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing 100875, China
Xue Wu: State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing 100875, China
Weiqiang Li: State Key Laboratory of Cotton Biology, Henan Joint International Laboratory for Crop Multi-Omics Research, School of Life Sciences, Henan University, 85 Minglun Street, Kaifeng 475001, China
Yixuan Liu: State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing 100875, China
Lam-Son Phan Tran: Institute of Research and Development, Duy Tan University, 3 Quang Trung, Da Nang 550000, Vietnam

Land, 2021, vol. 10, issue 5, 1-17

Abstract: Revealing the spatio-temporal change of the supply, demand and balance of ecosystem services (ESs) associated with human activities and land-use changes is of great significance for watershed ecosystem management. Taking the Lancang river valley as a case, we explicitly studied the ES spatial characteristics, using the land use/land cover (LULC) matrix model, Optimized Hot Spot Analysis and landscape pattern analysis. Furthermore, we screened out the dominant explanatory variables that had significant influence on the ES supply, demand and balance by means of the Geographical Weighted Regression (GWR) method at pixel scale. The results showed that the ES demand intensity varied little throughout the watershed, while the downstream ES supply capacity and balance values were greater than upstream ones. Meanwhile, the hotspots of ES supply and demand were mainly distributed in the south part with coldspots in the north part. Human activity factors integrating landscape pattern variables were verified to have a negative impact on the ES balance in general. Among them, the Largest Patch Index (LPI) had a negative influence on the majority of pixels, while the Gross Domestic Product (GDP), cultivated land ratio and Area Weighted Average Patch Fractal Dimension (AWAPFD) had positive effects on a few pixels. This study will provide scientific support for regional ecosystem service trade-off and regulation at multiple scales.

Keywords: ecosystem service; Geographical Weighted Regression; human activity; supply and demand; landscape pattern; Lancang river valley (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
https://www.mdpi.com/2073-445X/10/5/522/pdf (application/pdf)
https://www.mdpi.com/2073-445X/10/5/522/ (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:10:y:2021:i:5:p:522-:d:554149

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 ().