Xu Bi , Kailong Shi , Yongyong Fu , Wangyue Zhou , Ruoning Zhao , Haijun Bao
{"title":"自然因素和人类社会经济活动对中亚干旱区生态系统健康的影响机制——以西北富云地区为例","authors":"Xu Bi , Kailong Shi , Yongyong Fu , Wangyue Zhou , Ruoning Zhao , Haijun Bao","doi":"10.1016/j.ecolind.2025.113356","DOIUrl":null,"url":null,"abstract":"<div><div>Ecosystem health is a critical focus in ecosystem management. Understanding the spatial distribution patterns and driving factors of ecosystem health is crucial for efficient governance and restoration. However, research in arid pastoral regions remains limited. This research examined the ecosystem health of Fuyun County, a representative pastoral area located in the Altay Prefecture of Xinjiang, China. Utilizing a deep learning-based Vigor-Organization-Resilience-Service (VORS) framework, this paper evaluated the spatio-temporal variation characteristics of the ecosystem health index (EHI) and its correlation with natural and human socio-economic factors across different elevation gradients in 2000, 2010, and 2020. Subsequently, the Partial Least Squares Structural Equation Modeling (PLS-SEM) and mediation analysis were employed to investigate the interactive mechanisms among influencing factors and elucidate the drivers of EHI changes.</div><div>The findings indicated that: (1) EHI exhibited significant spatial heterogeneity, decreasing along the elevation gradient from north to south. (2) Potential evapotranspiration (PET), temperature, and precipitation were the primary drivers of EHI spatial differentiation. Within a decade, climate factors dominated EHI changes, whereas over two decades, socio-economic variables such as population density and per capita GDP became primary drivers. (3) In low- and medium-elevation regions (460–2460 m), EHI was positively correlated with precipitation. In high-elevation areas (above 2460 m), EHI showed a positive correlation with both temperature and potential evapotranspiration. Natural and human socio-economic activities significantly impacted ecosystem health in low- and medium-elevation regions, while human socio-economic activities had no significant influence in high altitude regions. (4) As a mediator, PET amplified the negative effect of temperature on EHI, weakened the positive impact of precipitation and the digital elevation model (DEM) on EHI, and strengthened the positive influence of slope on EHI. Meanwhile, the mediator grazing pressure index weakened the negative impact of per capita GDP and population density on EHI, but enhanced the positive effects of distance from roads and the proportion of grassland on EHI. These results offer valuable policy insights and scientific guidance for ecological conservation, promoting sustainable development in pastoral regions.</div></div>","PeriodicalId":11459,"journal":{"name":"Ecological Indicators","volume":"173 ","pages":"Article 113356"},"PeriodicalIF":7.0000,"publicationDate":"2025-03-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Influence mechanism of natural factors and human socio-economic activities on ecosystem health in arid regions of Central Asia: A case study of Fuyun area, northwest China\",\"authors\":\"Xu Bi , Kailong Shi , Yongyong Fu , Wangyue Zhou , Ruoning Zhao , Haijun Bao\",\"doi\":\"10.1016/j.ecolind.2025.113356\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Ecosystem health is a critical focus in ecosystem management. Understanding the spatial distribution patterns and driving factors of ecosystem health is crucial for efficient governance and restoration. However, research in arid pastoral regions remains limited. This research examined the ecosystem health of Fuyun County, a representative pastoral area located in the Altay Prefecture of Xinjiang, China. Utilizing a deep learning-based Vigor-Organization-Resilience-Service (VORS) framework, this paper evaluated the spatio-temporal variation characteristics of the ecosystem health index (EHI) and its correlation with natural and human socio-economic factors across different elevation gradients in 2000, 2010, and 2020. Subsequently, the Partial Least Squares Structural Equation Modeling (PLS-SEM) and mediation analysis were employed to investigate the interactive mechanisms among influencing factors and elucidate the drivers of EHI changes.</div><div>The findings indicated that: (1) EHI exhibited significant spatial heterogeneity, decreasing along the elevation gradient from north to south. (2) Potential evapotranspiration (PET), temperature, and precipitation were the primary drivers of EHI spatial differentiation. Within a decade, climate factors dominated EHI changes, whereas over two decades, socio-economic variables such as population density and per capita GDP became primary drivers. (3) In low- and medium-elevation regions (460–2460 m), EHI was positively correlated with precipitation. In high-elevation areas (above 2460 m), EHI showed a positive correlation with both temperature and potential evapotranspiration. Natural and human socio-economic activities significantly impacted ecosystem health in low- and medium-elevation regions, while human socio-economic activities had no significant influence in high altitude regions. (4) As a mediator, PET amplified the negative effect of temperature on EHI, weakened the positive impact of precipitation and the digital elevation model (DEM) on EHI, and strengthened the positive influence of slope on EHI. Meanwhile, the mediator grazing pressure index weakened the negative impact of per capita GDP and population density on EHI, but enhanced the positive effects of distance from roads and the proportion of grassland on EHI. These results offer valuable policy insights and scientific guidance for ecological conservation, promoting sustainable development in pastoral regions.</div></div>\",\"PeriodicalId\":11459,\"journal\":{\"name\":\"Ecological Indicators\",\"volume\":\"173 \",\"pages\":\"Article 113356\"},\"PeriodicalIF\":7.0000,\"publicationDate\":\"2025-03-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Ecological Indicators\",\"FirstCategoryId\":\"93\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S1470160X25002870\",\"RegionNum\":2,\"RegionCategory\":\"环境科学与生态学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENVIRONMENTAL SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Ecological Indicators","FirstCategoryId":"93","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1470160X25002870","RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENVIRONMENTAL SCIENCES","Score":null,"Total":0}
Influence mechanism of natural factors and human socio-economic activities on ecosystem health in arid regions of Central Asia: A case study of Fuyun area, northwest China
Ecosystem health is a critical focus in ecosystem management. Understanding the spatial distribution patterns and driving factors of ecosystem health is crucial for efficient governance and restoration. However, research in arid pastoral regions remains limited. This research examined the ecosystem health of Fuyun County, a representative pastoral area located in the Altay Prefecture of Xinjiang, China. Utilizing a deep learning-based Vigor-Organization-Resilience-Service (VORS) framework, this paper evaluated the spatio-temporal variation characteristics of the ecosystem health index (EHI) and its correlation with natural and human socio-economic factors across different elevation gradients in 2000, 2010, and 2020. Subsequently, the Partial Least Squares Structural Equation Modeling (PLS-SEM) and mediation analysis were employed to investigate the interactive mechanisms among influencing factors and elucidate the drivers of EHI changes.
The findings indicated that: (1) EHI exhibited significant spatial heterogeneity, decreasing along the elevation gradient from north to south. (2) Potential evapotranspiration (PET), temperature, and precipitation were the primary drivers of EHI spatial differentiation. Within a decade, climate factors dominated EHI changes, whereas over two decades, socio-economic variables such as population density and per capita GDP became primary drivers. (3) In low- and medium-elevation regions (460–2460 m), EHI was positively correlated with precipitation. In high-elevation areas (above 2460 m), EHI showed a positive correlation with both temperature and potential evapotranspiration. Natural and human socio-economic activities significantly impacted ecosystem health in low- and medium-elevation regions, while human socio-economic activities had no significant influence in high altitude regions. (4) As a mediator, PET amplified the negative effect of temperature on EHI, weakened the positive impact of precipitation and the digital elevation model (DEM) on EHI, and strengthened the positive influence of slope on EHI. Meanwhile, the mediator grazing pressure index weakened the negative impact of per capita GDP and population density on EHI, but enhanced the positive effects of distance from roads and the proportion of grassland on EHI. These results offer valuable policy insights and scientific guidance for ecological conservation, promoting sustainable development in pastoral regions.
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.