Yan Wang , Zhongxue Zhou , Rukeya Reheman , Bingjie Song , Enle Qiao , Haoran Huang
{"title":"空气介导的生态系统服务流模拟与时空动态分析——以关中平原城市群为例","authors":"Yan Wang , Zhongxue Zhou , Rukeya Reheman , Bingjie Song , Enle Qiao , Haoran Huang","doi":"10.1016/j.ecolind.2025.113892","DOIUrl":null,"url":null,"abstract":"<div><div>Analyzing the relationship between supply and demand of ecosystem services (ESs) from a spatiotemporal flow perspective is crucial for in-depth insight into flow process of ESs, and ensuring regional ecological security, optimizing resource allocation, and promoting sustainable development. However, previous studies have primarily focused on the flow of ecosystem service mediated by tangible substances (e.g., water, soil, animals etc.) with specific physical channels, the flow of ecosystem services mediated by intangible carriers (especially by air) remain rare and are lack of methods. Thus, taking the Guanzhong Plain urban agglomeration (GPUA) as a case, we proposed a flow analysis framework for air-mediated ecosystem service flows (AMESFs), quantified the supply–demand relationship of five ESs, simulated the air-mediated ESs flow field, determined the flow direction, volumes and paths, and analyzed their spatiotemporal dynamics. The results showed significant spatial mismatches of ESs in GPUA. High surplus areas were primarily distributed in forest-covered mountainous regions, while high deficit areas were concentrated in the cultivated regions of the Fenwei Plain and parts of the Loess Plateau, particularly in urban and adjacent areas. The flows of above ESs exhibited a similar pattern with minimal interannual variation during 2000–2020. Overall, five primary flow pathways were identified, extending from the northeastern and southeastern parts of GPUA toward the west, northwest, and southwest. Although the total supply of services was greater than the total demand, most of surplus service flowed out of the study area and the demand was not satisfied locally. The AMESFs were predominantly driven by the local prevailing wind rather than the supply–demand relationships. The framework is crucial for revealing the spatial flow characteristics and dynamic processes of ESs mediated by air and applicable to other regions. That also provides an assessment method for regional air pollution prevention and control, and green infrastructure development.</div></div>","PeriodicalId":11459,"journal":{"name":"Ecological Indicators","volume":"178 ","pages":"Article 113892"},"PeriodicalIF":7.0000,"publicationDate":"2025-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Simulation and spatiotemporal dynamic analysis of air-mediated ecosystem service flows: A case study of Guanzhong Plain urban agglomeration\",\"authors\":\"Yan Wang , Zhongxue Zhou , Rukeya Reheman , Bingjie Song , Enle Qiao , Haoran Huang\",\"doi\":\"10.1016/j.ecolind.2025.113892\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Analyzing the relationship between supply and demand of ecosystem services (ESs) from a spatiotemporal flow perspective is crucial for in-depth insight into flow process of ESs, and ensuring regional ecological security, optimizing resource allocation, and promoting sustainable development. However, previous studies have primarily focused on the flow of ecosystem service mediated by tangible substances (e.g., water, soil, animals etc.) with specific physical channels, the flow of ecosystem services mediated by intangible carriers (especially by air) remain rare and are lack of methods. Thus, taking the Guanzhong Plain urban agglomeration (GPUA) as a case, we proposed a flow analysis framework for air-mediated ecosystem service flows (AMESFs), quantified the supply–demand relationship of five ESs, simulated the air-mediated ESs flow field, determined the flow direction, volumes and paths, and analyzed their spatiotemporal dynamics. The results showed significant spatial mismatches of ESs in GPUA. High surplus areas were primarily distributed in forest-covered mountainous regions, while high deficit areas were concentrated in the cultivated regions of the Fenwei Plain and parts of the Loess Plateau, particularly in urban and adjacent areas. The flows of above ESs exhibited a similar pattern with minimal interannual variation during 2000–2020. Overall, five primary flow pathways were identified, extending from the northeastern and southeastern parts of GPUA toward the west, northwest, and southwest. Although the total supply of services was greater than the total demand, most of surplus service flowed out of the study area and the demand was not satisfied locally. The AMESFs were predominantly driven by the local prevailing wind rather than the supply–demand relationships. The framework is crucial for revealing the spatial flow characteristics and dynamic processes of ESs mediated by air and applicable to other regions. 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Simulation and spatiotemporal dynamic analysis of air-mediated ecosystem service flows: A case study of Guanzhong Plain urban agglomeration
Analyzing the relationship between supply and demand of ecosystem services (ESs) from a spatiotemporal flow perspective is crucial for in-depth insight into flow process of ESs, and ensuring regional ecological security, optimizing resource allocation, and promoting sustainable development. However, previous studies have primarily focused on the flow of ecosystem service mediated by tangible substances (e.g., water, soil, animals etc.) with specific physical channels, the flow of ecosystem services mediated by intangible carriers (especially by air) remain rare and are lack of methods. Thus, taking the Guanzhong Plain urban agglomeration (GPUA) as a case, we proposed a flow analysis framework for air-mediated ecosystem service flows (AMESFs), quantified the supply–demand relationship of five ESs, simulated the air-mediated ESs flow field, determined the flow direction, volumes and paths, and analyzed their spatiotemporal dynamics. The results showed significant spatial mismatches of ESs in GPUA. High surplus areas were primarily distributed in forest-covered mountainous regions, while high deficit areas were concentrated in the cultivated regions of the Fenwei Plain and parts of the Loess Plateau, particularly in urban and adjacent areas. The flows of above ESs exhibited a similar pattern with minimal interannual variation during 2000–2020. Overall, five primary flow pathways were identified, extending from the northeastern and southeastern parts of GPUA toward the west, northwest, and southwest. Although the total supply of services was greater than the total demand, most of surplus service flowed out of the study area and the demand was not satisfied locally. The AMESFs were predominantly driven by the local prevailing wind rather than the supply–demand relationships. The framework is crucial for revealing the spatial flow characteristics and dynamic processes of ESs mediated by air and applicable to other regions. That also provides an assessment method for regional air pollution prevention and control, and green infrastructure development.
期刊介绍:
The ultimate aim of Ecological Indicators is to integrate the monitoring and assessment of ecological and environmental indicators with management practices. The journal provides a forum for the discussion of the applied scientific development and review of traditional indicator approaches as well as for theoretical, modelling and quantitative applications such as index development. Research into the following areas will be published.
• All aspects of ecological and environmental indicators and indices.
• New indicators, and new approaches and methods for indicator development, testing and use.
• Development and modelling of indices, e.g. application of indicator suites across multiple scales and resources.
• Analysis and research of resource, system- and scale-specific indicators.
• Methods for integration of social and other valuation metrics for the production of scientifically rigorous and politically-relevant assessments using indicator-based monitoring and assessment programs.
• How research indicators can be transformed into direct application for management purposes.
• Broader assessment objectives and methods, e.g. biodiversity, biological integrity, and sustainability, through the use of indicators.
• Resource-specific indicators such as landscape, agroecosystems, forests, wetlands, etc.