全球智库信息集成服务系统(G2TT): Causal relationship in the interaction between land cover change and underlying surface climate in the grassland ecosystems in China.

G2TT

来源类型	Article
规范类型	其他
DOI	10.1016/j.scitotenv.2018.07.401
	Causal relationship in the interaction between land cover change and underlying surface climate in the grassland ecosystems in China.
	Li Z; Wang Z; Liu X; Fath B; Liu X; Xu Y; Hutjes R; Kroeze C
发表日期	2019
出处	Science of the Total Environment 647: 1080-1087
出版年	2019
语种	英语
摘要	Land-climate interactions are driven by causal relations that are difficult to ascertain given the complexity and high dimensionality of the systems. Many methods of statistical and mechanistic models exist to identify and quantify the causality in such highly-interacting systems. Recent advances in remote sensing development allowed people to investigate the land-climate interaction with spatially and temporally continuous data. In this study, we present a new approach to measure how climatic factors interact with each other under land cover change. The quantification method is based on the correlation analysis of the different order derivatives, with the canonical mathematical definitions developed from the theories of system dynamics and practices of the macroscopic observations. We examined the causal relationship between the interacting variables on both spatial and temporal dimensions based on macroscopic observations of land cover change and surface climatic factors through a comparative study in the different grassland ecosystems of China. The results suggested that the interaction of land-climate could be used to explain the temporal lag effect in the comparison of the three grassland ecosystems. Significant spatial correlations between the vegetation and the climatic factors confirmed feedback mechanisms described in the theories of eco-climatology, while the uncertain temporal synchronicity reflects the causality among the key indicators. This has been rarely addressed before. Our research show that spatial correlations and the temporal synchronicity among key indicators of the land surface and climatic factors can be explained by a novel method of causality quantification using derivative analysis.
主题	Advanced Systems Analysis (ASA)
关键词	Remote sensing Grassland Land-climate Cause-effect Correlation analysis Eco-climatology
URL	http://pure.iiasa.ac.at/id/eprint/15406/
来源智库	International Institute for Applied Systems Analysis (Austria)
引用统计
资源类型	智库出版物
条目标识符	http://119.78.100.153/handle/2XGU8XDN/131650
推荐引用方式 GB/T 7714	Li Z,Wang Z,Liu X,et al. Causal relationship in the interaction between land cover change and underlying surface climate in the grassland ecosystems in China.. 2019.