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Modeling the spatially heterogeneous relationships between tradeoffs and synergies among ecosystem services and potential drivers considering geographic scale in Bairin Left Banner, China

成对比较 比例(比率) 环境资源管理 植被(病理学) 生态系统服务 北京 环境科学 空间生态学 生态学 生态系统 地理 计算机科学 中国 地图学 生物 病理 人工智能 考古 医学
作者
Chenli Xue,Xinghua Chen,Lirong Xue,Huiqiong Zhang,Jianping Chen,Dedong Li
出处
期刊:Science of The Total Environment [Elsevier BV]
卷期号:855: 158834-158834 被引量:145
标识
DOI:10.1016/j.scitotenv.2022.158834
摘要

Understanding the complex relationships of tradeoffs and synergies among ecosystem services (ESs) is essential to achieve a comprehensive, coordinated, and sustainable development for human well-being. However, the quantitative measurement for the properties and intensities within these relationships as well as the deeper exploration of its formation mechanism from a spatial-explicit perspective is still a challenge. In this study, a comprehensive and general methodology was developed to quantitatively illustrate the intensities of tradeoffs/synergies among pairwise ESs and explore the spatially heterogeneous relationships between these relations and several socio-ecological drivers, integrating InVEST, geographical detector and multi-scale geographically weighted regression (MGWR) methods. The results indicated that (1) the properties and intensities of tradeoffs/synergies among various ESs varied greatly over space and presented significant clustered distribution patterns; (2) different relations between ESs were dominated by diverse drivers and the combined effects from multiple factors were stronger than any single one within this process. The tradeoffs/synergies between soil conservation and other ESs were mainly affected by geomorphological drivers including elevation and slope, while relations involved habitat quality could be attributed to vegetation and climate drivers such as precipitation and vegetation fractional cover. The relationships among ESs were more susceptible to topographic and anthropogenic drivers when concerning the carbon storage service; (3) compared to global ordinary least squares and local geographically weighted regression (GWR), the MGWR obtained better performance in explaining relationships between tradeoffs/synergies among ESs and potential drivers by operating different spatial scales. Accordingly, several spatially targeted ecological measures were proposed and recommended to reduce ESs tradeoffs and ultimately achieve better synergies. This research could enrich the methods in revealing the complex evolvement mechanism behind the tradeoffs/synergies among ESs and the proposed framework also provided a new perspective in the field of ESs tradeoffs/synergies studies and might be valuable guidance for other regions worldwide.
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