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应用生态学报 ›› 2025, Vol. 36 ›› Issue (1): 271-283.doi: 10.13287/j.1001-9332.202412.022

• 研究报告 • 上一篇    下一篇

多尺度下人为干扰对长江中游城市群生态系统服务供需的影响

钟发明1, 陈竹安1,2*   

  1. 1东华理工大学测绘与空间信息工程学院, 南昌 330013;
    2自然资源部环鄱阳湖区域矿山环境监测与治理重点实验室, 南昌 330013
  • 收稿日期:2024-05-15 修回日期:2024-09-30 出版日期:2025-01-18 发布日期:2025-07-18
  • 通讯作者: *E-mail: cza53@qq.com
  • 作者简介:钟发明, 男, 2000年生, 硕士研究生。主要从事生态系统服务研究。E-mail: mingna20@163.com
  • 基金资助:
    国家自然科学基金项目(52168010)、教育部人文社会科学研究项目(22YJCZH150)和江西省教育厅课题(GJJ2206614)

Impacts of human disturbances on the supply and demand of ecosystem services in the middle reaches of Yangtze River urban agglomeration across multiple scales

ZHONG Faming1, CHEN Zhu’an1,2*   

  1. 1School of Surveying and Geoinformation Engineering, East China University of Technology, Nanchang 330013, China;
    2Key Laboratory of Mine Environmental Monitoring and Improving around Poyang Lake, Ministry of Natural Resources, Nanchang 330013, China
  • Received:2024-05-15 Revised:2024-09-30 Online:2025-01-18 Published:2025-07-18

摘要: 认识人类活动对生态系统服务供需的影响,可为减少生态价值区环境破坏奠定坚实基础,同时对区域可持续发展具有重要意义。本研究以长江中游城市群为研究区,对人口密度、国内生产总值(GDP)、土地利用类型、交通网络、电能消耗和建筑高度6个人类压力关键指标进行测算;同时,基于土地利用、气象和社会经济等多源数据,利用InVEST等多种生态模型,对碳存储、产水、土壤保持和粮食供给这4种生态系统服务供需进行量化和空间分布的刻画,并利用结构方程模型对人为干扰与不同生态系统服务供需之间进行建模,以探索不同空间尺度下不同人为干扰对生态系统服务供需的影响。结果表明: 不同人为干扰的空间分布特征各异,其中,人口密度、GDP和交通道路在人口聚集区域干扰程度高,土地利用、电能消耗和建筑高度则在城市群核心城市较高。生态系统服务在城市区域呈现供不应求的短缺状态,非城市区域则处于供过于求的过剩状态,这种失衡现象随空间尺度增大而加剧。不同尺度下人为干扰对生态系统服务的供需影响程度各异,栅格尺度体现局部土地利用、植被覆盖的直接驱动影响,县域及以上尺度则受社会经济、区域政策及气候变化等综合影响。人口密度、经济发展和土地利用是影响生态系统服务供需的主要因素。多种人为干扰之间的互馈机制和累积效应直接加剧了生态系统服务的退化。研究结果可为协调生态保护与人类活动的政策制定提供科学指引。

关键词: 人为干扰, 多尺度, 生态系统服务供需, 结构方程模型, InVEST模型

Abstract: Understanding the impacts of human activities on the supply and demand of ecosystem services can lay a solid foundation for reducing environmental damage in ecologically valuable areas and is thus of great significance for regional sustainable development. We focused on the middle reaches of Yangtze River urban agglomeration and evaluated six key human pressure indicators: population density, gross domestic product (GDP), land use type, traffic network, energy consumption, and building height. Using multi-source data, including land use, meteorology, and socioeconomic information, and applying various ecological models such as InVEST, we quantified and spatially characterized the supply and demand of four ecosystem services: carbon storage, water yield, soil conservation, and grain production. We used structural equation model to analyze the relationship between human distur-bance and the supply and demand of different ecosystem services, aiming to explore the impacts of different human disturbances on the supply and demand of ecosystem services across various spatial scales. The results showed that the spatial distribution characteristics of different human disturbances varied significantly. Population density, GDP, and transportation network exhibited high levels of disturbance in densely populated areas, while land use, energy consumption, and building height had greater impacts in the core cities of the urban agglomeration. Ecosystem services in urban areas were at a state of undersupply, whereas non-urban areas experienced oversupply, with this imbalance being intensified with increasing spatial scales. The magnitudes of the impacts of human disturbances on ecosystem service supply and demand also varied across scales. At the grid scale, local land use and vegetation cover were the primary and direct drivers, while at the county and larger scales, socioeconomic factors, regional policies, and climate change exerted a combined influence. Population density, economic development, and land use were the main factors affecting the supply-demand relationship of ecosystem services. The feedback mechanisms and cumulative effects of multiple human disturbances directly exacerbated ecosystem service degradation. These findings would provide scientific guidance for policy formulation aimed at balancing ecological protection with human activities.

Key words: human disturbance, multi-scale, supply and demand of ecosystem services, structural equation mode-ling (SEM), InVEST model