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生态学杂志 ›› 2025, Vol. 44 ›› Issue (12): 4211-4224.doi: 10.13292/j.1000-4890.202512.039

• 技术与方法 • 上一篇    

生态系统服务供需风险簇时空演变特征及影响因素：以信江流域为例

孟令琦1,2,3，汤佳4,5，胡希军1,2,3*，张亚丽1,2,3，韦宝婧1,2,3，邹薇1,2,3，王烨梓1,2,3   

  1. （1中南林业科技大学风景园林学院， 长沙 410004； 2中南林业科技大学城乡景观生态研究所， 长沙 410004； 3湖南省自然保护地风景资源大数据工程技术研究中心， 长沙 410004； 4江西农业大学园林与艺术学院， 南昌 330045； 5南昌市城乡园林景观研究重点实验室， 南昌 330045）

  • 出版日期:2025-12-10 发布日期:2025-12-11

Spatiotemporal variations and driving factors of ecosystem service supply and demand risk bundles: A case of Xinjiang Basin.

MENG Lingqi1,2,3, TANG Jia4,5, HU Xijun1,2,3*, ZHANG Yali1,2,3, WEI Baojing1,2,3, ZOU Wei1,2,3, WANG Yezi1,2,3   

  1. (1College of Landscape Architecture, Central South University of Forestry and Technology, Changsha 410004, China; 2Institute of Urban and Rural Landscape Ecology, Central South University of Forestry and Technology, Changsha 410004, China; 3Hunan Big Data Engineering Technology Research Center of Natural Protected Areas Landscape Resources, Changsha 410004, China; 4College of Landscape Architecture and Art, Jiangxi Agricultural University, Nanchang 330045, China; 5Nanchang Key Laboratory of Urban and Rural Landscape Architecture Research, Nanchang 330045, China).

  • Online:2025-12-10 Published:2025-12-11

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摘要： 识别流域综合生态系统服务供需风险簇类型演变、时空格局和影响因素，对理解流域的生态问题、制定生态修复和管理决策至关重要。本文利用InVEST-SOM-RDA-RF的多模型框架，对信江流域2000—2020年的固碳（CS）、土壤保持（SR）、产水（WY）、休闲游憩（LR）和生境质量（HQ）的供需状况进行量化分析，结合冗余分析探讨了不同年份生态系统服务供需风险的影响因素，识别生态系统服务供需簇类型，并进一步挖掘供需风险簇的影响因子及其非线性响应关系。结果表明：2000—2020年，信江流域CS、WY、LR和HQ供需比整体呈“南北高，中间低”的分布特征，供需关系呈恶化趋势，SR供需比呈“南北低，中间高”特征，供需关系呈先恶化后改善趋势；人口、坡度和夜间灯光是影响这5类生态系统服务供需关系的主要影响因素；流域主要包括CS-WY-LR-HQ供需风险簇（B1）、HQ供需风险簇（B2）、SR供需风险簇（B3）、供需安全簇（B4）4种供需服务簇类型，2000—2020年，B1面积由47 km2扩张至63 km2，流域内以城市为核心区域的复合供需风险加剧；B3面积先增后减，B2、B4面积减少，土壤保持供需风险仍是区域的主要生态风险；人口、夜间灯光和坡度分别与B1、B2、B3供需风险簇的产生和时空布局呈高敏感和相关性。研究结果可为流域的综合生态系统服务供需风险管控提供研究思路和决策依据。


关键词: 生态系统服务, 供需匹配, 供需风险簇, 影响因素, 信江流域

Abstract: Identifying the type evolution, spatiotemporal pattern and influencing factors of supply and demand risk bundles of basin integrated ecosystem services is important for understanding ecological problems and making ecological restoration and management decisions. Following a multi-model framework including InVEST-SOM-RDA-RF, we analyzed the supply and demand status of carbon sequestration (CS), soil retention (SR), water yield (WY), leisure and recreation (LR), and habitat quality (HQ) in Xinjiang Basin from 2000 to 2020. Combined with redundancy analysis, the influencing factors of supply and demand risk of ecosystem services in different years were examined, the supply and demand bundles of ecosystem services were identified, and the influence factors of supply and demand risk bundles and its nonlinear response relationship were further excavated. The results showed that the supply and demand ratios of CS, WY, LR and HQ in Xinjiang Basin were “high in the north and south, low in the middle” from 2000 to 2020. The relationship between supply and demand was worsening. The ratios of supply to demand in SR was “low in the north and south, high in the middle”, while the relationship between supply and demand was deteriorating first and then trending. Population, slope, and night lighting were the main factors influencing the supply and demand of these five types of ecosystem services. The basin mainly included four supply and demand service bundles: CS-WY-LR-HQ supply and demand risk bundle (B1), HQ supply and demand risk bundle (B2), SR supply and demand risk bundle (B3), and supply and demand security bundle (B4). From 2000 to 2020, the B1 area expanded from 47 km2 to 63 km2, with the compound supply and demand risk with the cities as the core areas being intensified. The area of B3 increased first and then decreased, while the area of B2 and B4 decreased. The risk of supply and demand of soil conservation was still the main ecological risk of the region. Population, night lighting, and slope were highly sensitive and correlated with the generation and spatiotemporal distribution of supply and demand risk bundles of B1, B2, and B3, respectively. Our results can provide decision-making basis for risk management and control of supply and demand of integrated ecosystem services in the basin.


Key words: ecosystem services, matching supply and demand, supply and demand risk bundle, driving factor, Xinjiang Basin

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