Nijuan Yang , Ting Zhang , Jianzhu Li , Ping Feng , Nina Yang
{"title":"基于最佳空间尺度的中国滦河流域景观生态风险评估及驱动因素分析","authors":"Nijuan Yang , Ting Zhang , Jianzhu Li , Ping Feng , Nina Yang","doi":"10.1016/j.ecolind.2024.112821","DOIUrl":null,"url":null,"abstract":"<div><div>Rapid urbanization and human activities have significantly influenced landscape ecological pattern and increased ecological risk. Landscape ecological risk (LER) assessment serves as an effective tool to capture the effects of natural evolution and human activities on ecosystems comprehensively, but the assessment result is subject to spatial scales. This paper figured out the optimal spatial scales of the Luan River Basin integrating response curves, area accuracy loss model, and semi-variation function under the appropriate resampling method. The improved landscape ecological risk index (ILERI) model was established to assess LER based on optimal spatial scales, employing spatial autocorrelation theory and Geodetector to reveal the spatio-temporal traits and influencing factors of LER. The results showed: (1) Nearest is the appropriate raster resampling method in landscape pattern analysis of Luan River Basin, and the optimal spatial granularity and amplitude are 30 m and 3200 m, respectively; (2) In 2000, 2008, 2016 and 2022, ILERI was 0.242, 0.249, 0.250 and 0.234, respectively, and LER levels were medium–low and medium predominantly, which accounted for 64.87 %, 52.28 %, 68.76 % and 70.55 %; (3) Recent data showed a decline in LER levels, with higher risks concentrated in the northwest and lower risks in the southeast. Precipitation, population density, and primary industry were the primary factors and the interaction of multiple factors played a more significant role. This study will provide reference for planning land use and managing ecological environment in the Luan River Basin.</div></div>","PeriodicalId":11459,"journal":{"name":"Ecological Indicators","volume":"169 ","pages":"Article 112821"},"PeriodicalIF":7.0000,"publicationDate":"2024-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Landscape ecological risk assessment and driving factors analysis based on optimal spatial scales in Luan River Basin, China\",\"authors\":\"Nijuan Yang , Ting Zhang , Jianzhu Li , Ping Feng , Nina Yang\",\"doi\":\"10.1016/j.ecolind.2024.112821\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Rapid urbanization and human activities have significantly influenced landscape ecological pattern and increased ecological risk. Landscape ecological risk (LER) assessment serves as an effective tool to capture the effects of natural evolution and human activities on ecosystems comprehensively, but the assessment result is subject to spatial scales. This paper figured out the optimal spatial scales of the Luan River Basin integrating response curves, area accuracy loss model, and semi-variation function under the appropriate resampling method. The improved landscape ecological risk index (ILERI) model was established to assess LER based on optimal spatial scales, employing spatial autocorrelation theory and Geodetector to reveal the spatio-temporal traits and influencing factors of LER. The results showed: (1) Nearest is the appropriate raster resampling method in landscape pattern analysis of Luan River Basin, and the optimal spatial granularity and amplitude are 30 m and 3200 m, respectively; (2) In 2000, 2008, 2016 and 2022, ILERI was 0.242, 0.249, 0.250 and 0.234, respectively, and LER levels were medium–low and medium predominantly, which accounted for 64.87 %, 52.28 %, 68.76 % and 70.55 %; (3) Recent data showed a decline in LER levels, with higher risks concentrated in the northwest and lower risks in the southeast. Precipitation, population density, and primary industry were the primary factors and the interaction of multiple factors played a more significant role. This study will provide reference for planning land use and managing ecological environment in the Luan River Basin.</div></div>\",\"PeriodicalId\":11459,\"journal\":{\"name\":\"Ecological Indicators\",\"volume\":\"169 \",\"pages\":\"Article 112821\"},\"PeriodicalIF\":7.0000,\"publicationDate\":\"2024-11-14\",\"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/S1470160X24012780\",\"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/S1470160X24012780","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}
Landscape ecological risk assessment and driving factors analysis based on optimal spatial scales in Luan River Basin, China
Rapid urbanization and human activities have significantly influenced landscape ecological pattern and increased ecological risk. Landscape ecological risk (LER) assessment serves as an effective tool to capture the effects of natural evolution and human activities on ecosystems comprehensively, but the assessment result is subject to spatial scales. This paper figured out the optimal spatial scales of the Luan River Basin integrating response curves, area accuracy loss model, and semi-variation function under the appropriate resampling method. The improved landscape ecological risk index (ILERI) model was established to assess LER based on optimal spatial scales, employing spatial autocorrelation theory and Geodetector to reveal the spatio-temporal traits and influencing factors of LER. The results showed: (1) Nearest is the appropriate raster resampling method in landscape pattern analysis of Luan River Basin, and the optimal spatial granularity and amplitude are 30 m and 3200 m, respectively; (2) In 2000, 2008, 2016 and 2022, ILERI was 0.242, 0.249, 0.250 and 0.234, respectively, and LER levels were medium–low and medium predominantly, which accounted for 64.87 %, 52.28 %, 68.76 % and 70.55 %; (3) Recent data showed a decline in LER levels, with higher risks concentrated in the northwest and lower risks in the southeast. Precipitation, population density, and primary industry were the primary factors and the interaction of multiple factors played a more significant role. This study will provide reference for planning land use and managing ecological environment in the Luan River Basin.
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.