从生产-生活-生态空间角度看土地利用变化对生态环境质量的影响:天山北坡案例研究

IF 5.8 2区 环境科学与生态学 Q1 ECOLOGY
Yu Cao , Mingyu Zhang , Zhengyong Zhang , Lin Liu , Yu Gao , Xueying Zhang , Hongjin Chen , Ziwei Kang , Xinyi Liu , Yu Zhang
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引用次数: 0

摘要

阐明生产-生活-生态空间(PLES)与生态环境之间的关系有助于确定促进可持续发展的新战略。天山北坡是干旱地区山地-绿洲-荒漠相互作用的典型复杂生态系统,人地矛盾突出,生态环境错综复杂。在此,我们从 PLES 的角度分析了研究区土地利用的时空变化。基于中分辨率成像分光辐射计(MODIS)数据,建立了适用于干旱地区的改进遥感生态指数(IRSEI),通过引入盐度和清洁度指数来评价生态环境质量(EEQ)。然后利用逐步回归模型确定并量化了 PLES 传输模式对 EEQ 的影响。结果表明(1)绿洲地区以农业生产用地为主,而沙漠地区和高寒地区分别以其他生态用地和牧场生态用地为主。绿洲区主要是牧场生态用地向农业生产用地的转化,而荒漠区和高寒区则表现为生态空间的相互转化。(2)各分区 EEQ 的大小关系为:高寒区(0.555)>;绿洲区(0.509)>;荒漠区(0.424)。研究区的 EEQ 总体呈上升趋势,但在高寒地区有所下降。(3) PLES 和 IRSEI 的变化主要发生在绿洲地区。在影响 EEQ 的 21 种 PLES 转移模式中,农业生产用地的增加是提高 IRSEI 的主要模式,而不透水地面的增加则显著降低了 IRSEI。影响程度如下:工矿生产(-0.594)>;城市生活(-0.462)>;农村生活用地(-0.316)。此外,EEQ 还受到气候、地形等因素的综合影响。通过提出 IRSEI,从 PLES 的角度突出了土地利用流转方式对生态环境质量的影响,可为干旱地区生态环境评价提供参考,对土地利用规划和生态环境保护具有重要意义。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The impact of land-use change on the ecological environment quality from the perspective of production-living-ecological space: A case study of the northern slope of Tianshan Mountains

Elucidating the relationships between production-living-ecological space (PLES) and ecological environments can help identify new strategies to promote sustainable development. The northern slope of the Tianshan Mountains represents a typical complex ecosystem characterized by mountain-oasis-desert interactions in arid regions with prominent human-land conflicts and intricate ecological environments. Here, we analyzed the spatiotemporal variations in land use in the study area from the perspective of PLES. Based on moderate resolution imaging spectroradiometer (MODIS) data, an improved remote sensing ecological index (IRSEI) suitable for arid areas was established to evaluate the eco-environment quality (EEQ) by introducing salinity and cleanliness indexes. A stepwise regression model was then used to identify and quantify the impact of the PLES transfer modes on EEQ. The results showed that: (1) The oasis area was dominated by agricultural production land, whereas the desert and alpine areas were dominated by other and pasture ecological lands, respectively. The oasis area primarily involved the conversion of pasture ecological land to agricultural production land, whereas the desert and alpine areas showed mutual transformation of ecological space. (2) The size relationship of the EEQ in each sub-region was alpine region (0.555) > oasis region (0.509) > desert region (0.424). The EEQ in the study area showed an overall upward trend but decreased in the alpine region. (3) Changes in the PLES and IRSEI primarily occurred in the oasis region. Among the 21 PLES transfer modes that affect EEQ, an increase in agricultural production land was the primary mode that enhanced IRSEI, whereas an increase in impervious surfaces significantly decreased IRSEI. The degree of influence was as follows: industrial and mining production (−0.594) > urban living (−0.462) > rural living land (−0.316). In addition, EEQ is also affected by the combined effects of climate, topography, and other factors. By proposing IRSEI, we highlight the impact of land-use transfer mode on ecological environment quality from the perspective of PLES, which can provide a reference for ecological environment evaluation in arid areas and is of great significance for land-use planning and ecological environment protection.

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来源期刊
Ecological Informatics
Ecological Informatics 环境科学-生态学
CiteScore
8.30
自引率
11.80%
发文量
346
审稿时长
46 days
期刊介绍: The journal Ecological Informatics is devoted to the publication of high quality, peer-reviewed articles on all aspects of computational ecology, data science and biogeography. The scope of the journal takes into account the data-intensive nature of ecology, the growing capacity of information technology to access, harness and leverage complex data as well as the critical need for informing sustainable management in view of global environmental and climate change. The nature of the journal is interdisciplinary at the crossover between ecology and informatics. It focuses on novel concepts and techniques for image- and genome-based monitoring and interpretation, sensor- and multimedia-based data acquisition, internet-based data archiving and sharing, data assimilation, modelling and prediction of ecological data.
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