Spatial pattern evolution and driving forces of ecosystem service value in the Yellow River Basin

The Yellow River Basin is one of the basins characterized by China’s most complex geomorphological features. Investigating how the spatial pattern evolution of land types affects ecosystem service value (ESV) provides critical guidance for enhancing land resource management and ecological conservation in the Yellow River Basin. This study employs grid-based analysis, the modified equivalent factor method, the geographical detector model, and the grey correlation model to examine spatiotemporal variations in land-use patterns and ESV across the basin. Findings reveal: (1) From 1980 to 2020, construction land and ecological land demonstrated positive single dynamic degrees, with the construction land exhibiting the most pronounced expansion, increasing by 8.43. Cultivated land, wetlands, and wasted land showed negative dynamic degrees, and the wasted land showed the most significant decrease by 1.56. The comprehensive dynamic degree indicated overall expansion, peaking at 0.23 during 2010–2020. (2) The ESV of provisioning, regulating, supporting, and cultural services in the Yellow River Basin displayed U-shaped trends, ultimately increasing by 29.856, 2.103, 0.624, and 0.355 billion yuan, respectively, by 2020. (3) Spatial analysis identifies stepwise ESV distribution patterns in the Yellow River Basin, with significant value accumulation and clustering observed in upper reaches and the delta region. The Taihang and Qinling Mountains emerged as critical demarcation lines for ESV spatial gradients. (4) In the analysis of impact factors, spatial drivers, including rainfall, habitat quality, population density, GDP, and DEM, have substantial effects on ESV. In contrast, temporal features, including soil type, slope, population density, GDP, and nighttime light intensity, correlate highly with ESV. Notably, GDP and nighttime light intensity exhibited growing influence on ESV as socioeconomic activities intensified. Ecological governance achieved remarkable progress, particularly in upper and delta regions, though accompanied by increased ESV spatial fragmentation across basin sections. This study would provide scientific support for integrated land management, spatial economic planning, and ecological policy formulation in the Yellow River Basin by conducting the basin-scale analysis.

Authors

Institutions

Publication Details

Journal
Frontiers in Environmental Science
Published
2025-05-14
DOI
https://doi.org/10.3389/fenvs.2025.1562274
Citations
2
Primary Topic
Land Use and Ecosystem Services
Type
article
Field-Weighted Citation Impact
2.21
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Spatial pattern evolution and driving forces of ecosystem service value in the Yellow River Basin

Bin Xu, Yu Wan, Yuan Li, Xiao Hui Wang
2 citations
Frontiers in Environmental Science
Land Use and Ecosystem Services
2.21
article

Spatial pattern evolution and driving forces of ecosystem service value in the Yellow River Basin

Bin Xu, Yu Wan, Yuan Li, Xiao Hui Wang
article en
2 citations

Abstract

The Yellow River Basin is one of the basins characterized by China’s most complex geomorphological features. Investigating how the spatial pattern evolution of land types affects ecosystem service value (ESV) provides critical guidance for enhancing land resource management and ecological conservation in the Yellow River Basin. This study employs grid-based analysis, the modified equivalent factor method, the geographical detector model, and the grey correlation model to examine spatiotemporal variations in land-use patterns and ESV across the basin. Findings reveal: (1) From 1980 to 2020, construction land and ecological land demonstrated positive single dynamic degrees, with the construction land exhibiting the most pronounced expansion, increasing by 8.43. Cultivated land, wetlands, and wasted land showed negative dynamic degrees, and the wasted land showed the most significant decrease by 1.56. The comprehensive dynamic degree indicated overall expansion, peaking at 0.23 during 2010–2020. (2) The ESV of provisioning, regulating, supporting, and cultural services in the Yellow River Basin displayed U-shaped trends, ultimately increasing by 29.856, 2.103, 0.624, and 0.355 billion yuan, respectively, by 2020. (3) Spatial analysis identifies stepwise ESV distribution patterns in the Yellow River Basin, with significant value accumulation and clustering observed in upper reaches and the delta region. The Taihang and Qinling Mountains emerged as critical demarcation lines for ESV spatial gradients. (4) In the analysis of impact factors, spatial drivers, including rainfall, habitat quality, population density, GDP, and DEM, have substantial effects on ESV. In contrast, temporal features, including soil type, slope, population density, GDP, and nighttime light intensity, correlate highly with ESV. Notably, GDP and nighttime light intensity exhibited growing influence on ESV as socioeconomic activities intensified. Ecological governance achieved remarkable progress, particularly in upper and delta regions, though accompanied by increased ESV spatial fragmentation across basin sections. This study would provide scientific support for integrated land management, spatial economic planning, and ecological policy formulation in the Yellow River Basin by conducting the basin-scale analysis.

Frontiers in Environmental ScienceVol. 13
Chinese Academy of Forestry (CN), Research Institute of Forestry Policy and Information (CN), Chinese Academy of International Trade and Economic Cooperation (CN)
Openalex Percentile: Top 14%
Land Use and Ecosystem Services
2.21
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.