Ecology and Environment

The supply-demand risks of ecosystem services and threshold characteristics of their influencing factors in Fenhe River Basin

  • DUAN Baoling ,
  • FENG Qiang ,
  • WANG Jing ,
  • ZHANG Wei
Expand
  • 1. College of Resources and Environment, Shanxi University of Finance and Economics, Taiyuan 030006, Shanxi, China
    2. State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China

Received date: 2025-04-16

  Revised date: 2025-06-11

  Online published: 2025-09-16

Abstract

Revealing the supply-demand risks of ecosystem services and their driving mechanisms is of reference value for supporting the ecological protection and high-quality development. This study developed formulas for supply-demand matching and risk assessment, employing the InVEST model, Extreme Gradient Boosting trees, and Shapley Additive Explanations (SHAP) to analyze the spatiotemporal differentiation of carbon sequestration, soil conservation, and water yield supply-demand matching from 2000 to 2020, as well as the threshold characteristics of factors influencing supply-demand risks. The results show that: (1) From 2000 to 2020, the supply and demand levels of carbon sequestration and soil conservation continuously increased. The temporal trend of water yield supply was relatively complex but increased significantly in 2020, while the demand for water yield generally showed an increasing trend. Carbon sequestration and water yield demand displayed higher values in the Fenhe river valley and lower values in surrounding mountainous areas, whereas carbon sequestration supply, soil conservation supply and demand exhibited inverse spatial patterns. (2) Carbon sequestration were all in the supply-demand risk zone, while soil conservation exhibited a mixed pattern of high, medium, and low-risk areas. Among them, Linfen region faced the greatest supply-demand risks of carbon sequestration and soil conservation, with the proportion of medium-high risk zones accounting for 21.73% and 18.14% of the basin area respectively. The Fenhe River Basin was mainly in the supply-demand safety zone for water yield, with only Taiyuan and Yuncheng region having relatively high proportion of high-risk zones, accounting for only 6.74%, with high risk areas mainly located in the Taiyuan and Yuncheng regions. (3) Population density and GDP nearly linearly intensified carbon sequestration risks. Annual average temperature exhibited a critical threshold of 10 ℃, beyond which risks were escalated. Soil conservation risks were increased with cropland and grassland coverage, while slope gradient(11°) and precipitation (600 mm) served as inflection points: risks rose rapidly below these thresholds but stabilized above them. Water yield risks were decreased with precipitation and grassland coverage but increased with GDP and population density. With 7 ℃ and 12 ℃ as thresholds, the impact of mean annual temperature on water yield supply-demand risk was characterized by three stages: mild promotion, no impact, and strong promotion. Thus, ecological restoration, economic development, and precipitation changes have collectively driven the spatiotemporal evolution of ecosystem services supply, demand, and associated risks. The supply-demand risk index developed in this study offers practical value for managing ecosystem service supply-demand dynamics.

Cite this article

DUAN Baoling , FENG Qiang , WANG Jing , ZHANG Wei . The supply-demand risks of ecosystem services and threshold characteristics of their influencing factors in Fenhe River Basin[J]. Arid Zone Research, 2025 , 42(9) : 1726 -1741 . DOI: 10.13866/j.azr.2025.09.16

References

[1] Millennium Ecosystem Assessment. Ecosystems and Human Well-being: Synthesis[M]. Washington, DC: Island Press, 2005.
[2] 李双成. 生态系统服务地理学[M]. 北京: 科学出版社, 2014.
  [Li Shuangcheng. The Geography of Ecosystem Services[M]. Beijing: Science Press, 2014.]
[3] Xiao S, Zhao Y L, Li H, et al. Realization of integrated regional ecological management based on ecosystem service supply and demand flow networks: An example from a dominant mineral resources development area[J]. Remote Sensing, 2024, 16(21): 4021.
[4] de Knegt B, Marjolein E L, Solen L C, et al. Growing mismatches of supply and demand of ecosystem services in the Netherlands[J]. Journal of Environmental Management, 2025, 373: 123442.
[5] Li J Y, Chen X, De Maeyer P, et al. Investigating the supply-demand gap of farmland ecosystem services to advance sustainable development goals (SDGs) in Central Asia[J]. Agricultural Water Management, 2025, 312: 109419.
[6] Burkhard B, Kroll F, Nedkov S, et al. Mapping ecosystem service supply, demand and budgets[J]. Ecological Indicators, 2012, 21: 17-29.
[7] Tao Y, Wang H N, Ou W X, et al. A land-cover-based approach to assessing ecosystem services supply and demand dynamics in the rapidly urbanizing Yangtze River Delta region[J]. Land Use Policy, 2018, 72: 250-258.
[8] Chen D S, Li J, Yang X N, et al. Quantifying water provision service supply, demand and spatial flow for land use optimization: A case study in the YanHe watershed[J]. Ecosystem Services, 2020, 43: 101117.
[9] Li D L, Wu S Y, Liu L B, et al. Evaluating regional water security through a freshwater ecosystem service flow model: A case study in Beijing-Tianjian-Hebei region, China[J]. Ecological Indicators, 2017, 81: 159-170.
[10] Qiu H H, Bai Y C, Han H R, et al. Ecosystem service supply and demand relationship and spatial identification of driving threshold in Loess Plateau of China[J]. Ecological Engineering, 2025, 212: 107534.
[11] 冯强, 赵文武, 段宝玲. 生态系统服务权衡强度与供需匹配度的关联性分析——以山西省为例[J]. 干旱区研究, 2022, 39(4): 1222-1233.
  [Feng Qiang, Zhao Wenwu, Duan Baoling. Relationship between trade-off intensity of ecosystem services and matching degree of supply and demand: A case study in Shanxi Province[J]. Arid Zone Research, 2022, 39(4): 1222-1233.]
[12] Fusaro L, Nardella L, Manes F, et al. Supply and demand mismatch analysis to improve regulating ecosystem services in Mediterranean urban areas: Insights from four Italian Municipalities[J]. Ecological Indicators, 2023, 155: 110928.
[13] Li J, Jiang H, Bai Y, et al. Indicators for spatial-temporal comparisons of ecosystem service status between regions: A case study of the Taihu River Basin, China[J]. Ecological Indicators, 2016, 60: 1008-1016.
[14] Wang Z, Zhang L, Li X, et al. Integrating ecosystem service supply and demand into ecological risk assessment: A comprehensive framework and case study[J]. Landscape Ecology, 2021, 36: 2977-2995.
[15] 朱月华, 侯宗东, 徐彩仙, 等. 基于生态系统服务供需关系的甘肃白龙江流域生态风险识别与管理[J]. 地理科学, 2023, 43(3): 423-433.
  [Zhu Yuehua, Hou Zongdong, Xu Caixian, et al. Ecological risk identification and management based on ecosystem service supply and demand relationship in the Bailongjiang River Watershed of Gansu Province[J]. Scientia Geographica Sinica, 2023, 43(3): 423-433.]
[16] Shen J, Li S, Wang H, et al. Understanding the spatial relationships and drivers of ecosystem service supply-demand mismatches towards spatially-targeted management of social-ecological system[J]. Journal of Cleaner Production, 2023, 406: 136882.
[17] Gong J, Dai X, Wang L, et al. The impact of urbanization on the supply-demand relationship of ecosystem services in the Yangtze River Middle Reaches Urban Agglomeration[J]. Remote Sensing, 2023, 15(19): 4749.
[18] Chen Y R, Qiao X N, Yang Y J, et al. Identifying the spatial relationships and drivers of ecosystem service supply-demand matching: A case of Yiluo River Basin[J]. Ecological Indicators, 2024, 163: 112122.
[19] Zhai T L, Ma Y B, Huang L Y, et al. Research on the spatiotemporal evolution characteristics and driving mechanisms of supply-demand risks of ecosystem services in the Yellow River Basin integrating the hierarchy of needs theory[J]. Ecological Indicators, 2025, 171: 113229.
[20] Zhang Z Y, Tong Z M, Zhang L T, et al. What are the dominant factors and optimal driving threshold for the synergy and tradeoff between ecosystem services, from a nonlinear coupling perspective?[J]. Journal of Cleaner Production, 2023, 422: 138609.
[21] Lundberg S M, Lee S I. A unified approach to interpreting model predictions[C]// Proceedings of the 31st International Conference on Neural Information Processing Systems, Long Beach, California, USA, 2017: 4768-4777.
[22] 苏迎庆, 刘庚, 赵景波, 等. 基于FLUS模型的汾河流域生态空间多情景模拟预测[J]. 干旱区研究, 2021, 38(4): 1152-1161.
  [Su Yingqing, Liu Geng, Zhao Jingbo, et al. Multi-scenario simulation prediction of ecological space in the Fenhe River Basin using the FLUS model[J]. Arid Zone Research, 2021, 38(4): 1152-1161.]
[23] 吴朝巧, 林菲, 牛俊杰, 等. 山西中部城市群生态系统服务对土地利用格局变化的响应[J]. 干旱区研究, 2024, 41(7): 1153-1166.
  [Wu Zhaoqiao, Lin Fei, Niu Junjie, et al. Response of ecosystem service to land use pattern change in the Shanxi central urban agglomeration[J]. Arid Zone Research, 2024, 41(7): 1153-1166.]
[24] Su Y, Ma X, Feng Q, et al. Patterns and controls of ecosystem service values under different land-use change scenarios in a mining-dominated basin of northern China[J]. Ecological Indicators, 2023, 151: 110321.
[25] 杨洁, 谢保鹏, 张德罡. 基于InVEST模型的黄河流域产水量时空变化及其对降水和土地利用变化的响应[J]. 应用生态学报, 2020, 31(8): 2731-2739.
  [Yang Jie, Xie Baopeng, Zhang Degang. Spatio-temporal variation of water yield and its response to precipitation and land use change in the Yellow River Basin based on InVEST model[J]. Chinese Journal of Applied Ecology, 2020, 31(8): 2731-2739.]
[26] Feng Q, Zhao W W, Ding J Y, et al. Estimation of the cover and management factor based on stratified coverage and remote sensing indices: A case study in the Loess Plateau of China[J]. Journal of Soils and Sediments, 2018, 18(3): 775-790.
[27] Feng Q, Zhao W W, Hu X P, et al. Trading-off ecosystem services for better ecological restoration: A case study in the Loess Plateau of China[J]. Journal of Cleaner Production, 2020, 257: 120469.
[28] 国家发展和改革委员会, 国家统计局. 生态产品总值核算规范[M]. 北京: 人民出版社. 2022.
  [National Development and Reform Commission, National Bureau of Statistics. Specification for the Calculation of the Gross Ecosystem Product[M]. Beijing: People's Publishing House, 2022.]
[29] 汪晓珍, 吴建召, 吴普侠, 等. 2000—2015年黄土高原生态系统水源涵养、土壤保持和NPP服务的时空分布与权衡/协同关系[J]. 水土保持学报, 2021, 35(4): 114-121.
  [Wang Xiaozhen, Wu Jianzhao, Wu Puxia, et al. Spatial and temporal distribution and trade-offs/synergies of water conservation, soil conservation and NPP services in the Loess Plateau ecosystem from 2000 to 2015[J]. Journal of Soil and Water Conservation, 2021, 35(4): 114-121.]
[30] 张琨, 吕一河, 傅伯杰, 等. 黄土高原植被覆盖变化对生态系统服务影响及其阈值[J]. 地理学报, 2020, 75(5): 949-960.
  [Zhang Kun, Lv Yihe, Fu Bojie, et al. The effects of vegetation coverage changes on ecosystem service and their threshold in the Loess Plateau[J]. Acta Geographica Sinica, 2020, 75(5): 949-960.]
[31] Zhang B, Tian L, Yang Y, et al. Revegetation does not decrease water yield in the Loess Plateau of China[J]. Geophysical Research Letters, 2022, 49: e2022GL098025.
[32] 赵奕博, 于洋, 孙保平, 等. 山西省产水服务供需时空变化[J]. 水土保持学报, 2023, 37(6): 126-133.
  [Zhao Yibo, Yu Yang, Sun Baoping, et al. Research on the spatiotemporal changes of supply and demand for water yield in Shanxi Province[J]. Journal of Soil and Water Conservation, 2023, 37(6): 126-133.]
[33] 吴树荣, 潘换换, 姬倩倩, 等. 基于生态系统服务的山西黄河流域保护优先区识别[J]. 生态学报, 2022, 42(20): 8126-8137.
  [Wu Shurong, Pan Huanhuan, Ji Qianqian, et al. Identification of priority conservation areas in the Yellow River Basin of Shanxi Province based on ecosystem services[J]. Acta Ecologica Sinica, 2022, 42(20): 8126-8137.]
[34] 徐铭璟, 冯强, 吕萌. 生态系统服务权衡及其影响因素——以黄河流域山西段为例[J]. 干旱区研究, 2024, 41(3): 467-479.
  [Xu Mingjing, Feng Qiang, Lyu Meng. Tradeoffs of ecosystem services and their influencing factors: A case study of the Shanxi Section of the Yellow River Basin[J]. Arid Zone Research, 2024, 41(3): 467-479.]
[35] Xu M, Feng Q, Zhang S, et al. Ecosystem services supply-demand matching and its driving factors: A case study of the Shanxi section of the Yellow River Basin, China[J]. Sustainability, 2023, 15(14): 11016.
[36] Zhang X, Wang Y, Yuan X F, et al. Identifying ecosystem service supply-demand imbalance for sustainable land management in China's Loess Plateau[J]. Land Use Policy, 2022, 123: 106423.
[37] Feng Q, Duan B, Zhang X. Relationship between ecosystem services trade-offs and supply-demand balance along a precipitation gradient: A case study in the central Loess Plateau of China[J]. Land, 2024, 13(7): 1057.
[38] 荀斌, 郑莹, 范蓉, 等. 陕西省生态系统服务权衡/协同关系阈值识别[J]. 生态学报, 2024, 44(17): 7431-7444.
  [Xun Bin, Zheng Ying, Fan Rong, et al. Assessment of trade-off/synergy relationships between ecosystem services and identification of ecological restoration thresholds[J]. Acta Ecologica Sinica, 2024, 44(17): 7431-7444.]
[39] Li Z, Hu B, Ren Y. The supply-demand budgets of ecosystem service response to urbanization: insights from urban-rural gradient and major function-oriented areas[J]. Remote Sensing, 2022, 14(22): 5670.
Outlines

/