{"title":"近20 a人类活动对陕西省地下土壤有机碳的空间影响","authors":"Yujie Zhou , Yiheng Zhang , Wanying Li","doi":"10.1016/j.ecolind.2025.113603","DOIUrl":null,"url":null,"abstract":"<div><div>Soil organic carbon (SOC), as a crucial carbon reservoir and a key component of ecosystems, plays an essential role in mitigating global climate warming driven by carbon emissions from human activities. In this study, we developed the Human Activity Intensity (HAI) index, which integrates factors such as population density and land use/land cover, establishing a spatial linkage between surface and subsurface SOC data at multiple depths. Additionally, we investigated the influence of surface ecological conditions, represented by the Remote Sensing-based Ecological Index (RSEI) on SOC. Our analysis elucidates the differential impacts of human activities and ecological conditions on SOC across distinct soil layers, underscoring the pivotal role of SOC as a fundamental ecological variable. Results from the Geographically Weighted Regression (GWR) model showed that the primary negative impacts (GWR regression coefficient < 0) of HAI on RSEI were concentrated in the central region of Shaanxi Province, with relatively minor positive effects. In contrast, significant positive impacts (GWR regression coefficient > 0) were predominantly observed in the northern part of Yulin City. Furthermore, we found that the spatial effects of HAI on surface SOC were more pronounced than those on multi-subsurface SOC layers. GWR model results indicated a gradual decline in the spatial effects with increasing soil depth, stabilizing at approximately 60 cm. The spatial distribution of surface vegetation conditions and land use/cover was found to significantly influence the spatial patterns of both surface and subsurface SOC across multiple soil layers. Collectively, our findings offer valuable macro-scale insights into the spatial relationships between human activities and SOC, extending the analysis into a multidimensional environmental context.</div></div>","PeriodicalId":11459,"journal":{"name":"Ecological Indicators","volume":"175 ","pages":"Article 113603"},"PeriodicalIF":7.0000,"publicationDate":"2025-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Spatial effects of human activities on multi-subsurface soil organic carbon during the last 20 years in Shaanxi Province, China\",\"authors\":\"Yujie Zhou , Yiheng Zhang , Wanying Li\",\"doi\":\"10.1016/j.ecolind.2025.113603\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Soil organic carbon (SOC), as a crucial carbon reservoir and a key component of ecosystems, plays an essential role in mitigating global climate warming driven by carbon emissions from human activities. In this study, we developed the Human Activity Intensity (HAI) index, which integrates factors such as population density and land use/land cover, establishing a spatial linkage between surface and subsurface SOC data at multiple depths. Additionally, we investigated the influence of surface ecological conditions, represented by the Remote Sensing-based Ecological Index (RSEI) on SOC. Our analysis elucidates the differential impacts of human activities and ecological conditions on SOC across distinct soil layers, underscoring the pivotal role of SOC as a fundamental ecological variable. Results from the Geographically Weighted Regression (GWR) model showed that the primary negative impacts (GWR regression coefficient < 0) of HAI on RSEI were concentrated in the central region of Shaanxi Province, with relatively minor positive effects. In contrast, significant positive impacts (GWR regression coefficient > 0) were predominantly observed in the northern part of Yulin City. Furthermore, we found that the spatial effects of HAI on surface SOC were more pronounced than those on multi-subsurface SOC layers. GWR model results indicated a gradual decline in the spatial effects with increasing soil depth, stabilizing at approximately 60 cm. The spatial distribution of surface vegetation conditions and land use/cover was found to significantly influence the spatial patterns of both surface and subsurface SOC across multiple soil layers. Collectively, our findings offer valuable macro-scale insights into the spatial relationships between human activities and SOC, extending the analysis into a multidimensional environmental context.</div></div>\",\"PeriodicalId\":11459,\"journal\":{\"name\":\"Ecological Indicators\",\"volume\":\"175 \",\"pages\":\"Article 113603\"},\"PeriodicalIF\":7.0000,\"publicationDate\":\"2025-05-15\",\"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/S1470160X25005333\",\"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/S1470160X25005333","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}
Spatial effects of human activities on multi-subsurface soil organic carbon during the last 20 years in Shaanxi Province, China
Soil organic carbon (SOC), as a crucial carbon reservoir and a key component of ecosystems, plays an essential role in mitigating global climate warming driven by carbon emissions from human activities. In this study, we developed the Human Activity Intensity (HAI) index, which integrates factors such as population density and land use/land cover, establishing a spatial linkage between surface and subsurface SOC data at multiple depths. Additionally, we investigated the influence of surface ecological conditions, represented by the Remote Sensing-based Ecological Index (RSEI) on SOC. Our analysis elucidates the differential impacts of human activities and ecological conditions on SOC across distinct soil layers, underscoring the pivotal role of SOC as a fundamental ecological variable. Results from the Geographically Weighted Regression (GWR) model showed that the primary negative impacts (GWR regression coefficient < 0) of HAI on RSEI were concentrated in the central region of Shaanxi Province, with relatively minor positive effects. In contrast, significant positive impacts (GWR regression coefficient > 0) were predominantly observed in the northern part of Yulin City. Furthermore, we found that the spatial effects of HAI on surface SOC were more pronounced than those on multi-subsurface SOC layers. GWR model results indicated a gradual decline in the spatial effects with increasing soil depth, stabilizing at approximately 60 cm. The spatial distribution of surface vegetation conditions and land use/cover was found to significantly influence the spatial patterns of both surface and subsurface SOC across multiple soil layers. Collectively, our findings offer valuable macro-scale insights into the spatial relationships between human activities and SOC, extending the analysis into a multidimensional environmental context.
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.