Revealing Multiscale Characteristics of Ecosystem Service Flows: Application to the Yangtze River Economic Belt
Year: 2025
Type: article
Abstract: Assessing ecosystem service (ES) supply–demand relationships and identifying their driving forces are essential for ecological security and sustainable ecosystem development. Using ES supply–demand mismatches as a basis, this study characterized the spatiotemporal evolution of ES supply and demand from 2000 to 2023. Additionally, a SHAP-informed Stacking Bayesian optimization model was employed to identify key drivers of supply–demand imbalances. Building on this, threshold-aware spatial optimization of ecosystem service flows was performed using an improved minimum-cost algorithm within an NSGA-II multi-objective framework. The results showed that: (1) The YREB’s supply–demand balance (SDB) exhibited significant spatial heterogeneity. Water SDB declined with fluctuations, decreasing from 5.343 × 1011 m3 to 4.433 × 1011 m3, whereas carbon SDB shifted from a surplus (+1.514 × 109 t) to a deficit (−1.673 × 109 t) during the study period. Crop SDB rose from 1.361 × 108 to 1.450 × 108 t across the study period. (2) Nighttime light intensity (NLI) was the dominant factor for water SDB and carbon SDB, while cropland area was the key driver for crop SDB. (3) Over 2000–2023, water SDB flow increased from 8.5 × 109 m3 to 1.43 × 1010 m3. Carbon SDB flows more than tripled from 9.576 × 107 tons to 2.89 × 108 tons. Crop SDB flow increased nearly twelvefold over 2000–2023, from 3.3 × 105 t to 3.93 × 106 t. The findings provide scientific support for coordinating ecological conservation and high-quality development across the Yangtze River Economic Belt.
Source: Land
DOI: 10.3390/land14102076
Authors: Yiyang Li, Hongrui Wang, Li Zhang, Yafeng Yang, Ziyang Zhao, Xin Jiang
Language: English
Subfield: Global and Planetary Change
Field: Environmental Science
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $3,137
Awards: G3114519815, G5061996175, G5574435574
OpenAlex ID: W4415282369
