Spatiotemporal Characteristics and Scale Effects of Ecosystem Service Bundles in the Xijiang River Basin: Implications for Territorial Spatial Planning and Sustainable Land Management

被引:0
|
作者
Zhang, Longjiang [1 ,2 ]
Chen, Guoping [1 ,2 ]
Zhao, Junsan [1 ,2 ]
Lin, Yilin [1 ,2 ]
Yang, Haibo [1 ,2 ,3 ]
He, Jianhua [4 ]
机构
[1] Kunming Univ Sci & Technol, Fac Land Resources Engn, Kunming 650093, Peoples R China
[2] Kunming Univ Sci, Technol Oxbridge Coll, Innovat Team Nat Resources Spatial Informat Integr, Kunming 650106, Peoples R China
[3] Kunming Univ Sci & Technol, Oxbridge Coll, Inst Technol, Kunming 650106, Peoples R China
[4] Wuhan Univ, Sch Resource & Environm Sci, Wuhan 430079, Peoples R China
基金
中国国家自然科学基金;
关键词
ecosystem services; trade-offs/synergies; ecosystem service bundles; multi-scale analysis; Xijiang River Basin; TRADE-OFFS; SYNERGIES; IMPACTS;
D O I
10.3390/su17051967
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
In-depth analysis of the evolution of ecosystem services (ESs) in the basin at different spatial scales, scientific identification of ecosystem service clusters, and revelation of their spatial and temporal characteristics as well as coupling mechanisms of interactions are the key prerequisites for effective implementation of ES management. This paper assessed the spatial and temporal changes of six key ESs covering food provisioning (FP), water yield (WY), soil retention (SR), water conservation (WC), habitat quality (HQ), and carbon sequestration (CS) in the Xijiang River Basin (XRB), China, between 2000 and 2020. Given that the scale effects of ESs and their spatial heterogeneity in the XRB are still subject to large uncertainties, a combination of Spearman correlation analysis and geographically weighted regression (GWR) modelling systematically revealed the trade-offs and synergistic relationships between ESs and the scale effects from a grid, watershed, and county perspective. Additionally, we applied the self-organizing mapping (SOM) method to identify multiple ecosystem service bundles (ESBs) and propose corresponding sustainable spatial planning and management strategies for each cluster. The results reveal the following key findings: (1) Spatial distribution and heterogeneity: The six ESs demonstrated pronounced spatial variability across the study area during the two-decade period from 2000 to 2020. The downstream areas had higher levels of ESs, while the upstream regions showed comparatively lower levels. This trend was particularly evident in areas with extensive arable land, higher population density, and more developed economic activity, where ESs levels were lower. (2) Trade-offs/synergies: The analysis highlighted the prevalence of synergistic effects among ESs, with food provisioning-related services exhibiting notable trade-offs. Trade-off/Synergistic effects were weaker at the grid scale but more pronounced at the sub-basin and county scales, with significant spatial heterogeneity. (3) Identification of ESBs: We identified five distinct ESBs: the HQ-CS synergy bundle (HCSB), the integrated ecological bundle (IEB), the agricultural bundle (AB), the key synergetic bundle lacking HQ (KSB), and the supply service bundle (SSB). These clusters suggest that the overall ecological environment of the study area has significantly improved, the supply functions have strengthened, and ecosystem vulnerability has been effectively mitigated. Building upon the identified multi-scale spatiotemporal heterogeneity patterns of ESBs in the XRB, this study proposes an integrated framework for territorial spatial planning and adaptive land management, aiming to optimize regional ecosystem service provisioning and enhance socio-ecological sustainability.
引用
收藏
页数:23
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