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1.
Environ Sci Pollut Res Int ; 31(5): 7514-7532, 2024 Jan.
Article in English | MEDLINE | ID: mdl-38159188

ABSTRACT

Vegetation is an essential component of terrestrial ecosystems, influenced by climate change and human activities. Quantifying the relative contributions of climate change and human activities to vegetation dynamics is crucial for addressing global climate change. Sichuan Province is one of the essential ecological functional areas in the upper reaches of the Yangtze River, and its vegetation change is of great significance to the environmental function and ecological security of the Yangtze River Basin and southwest China. In this paper, the modified Carnegie-Ames-Stanford Approach(CASA) model was used to estimate the monthly NPP (Net Primary Productivity) of vegetation in Sichuan Province from 2000 to 2018, and the univariate linear regression analysis was used to analyze the temporal and spatial variation of vegetation NPP in Sichuan Province from 2000 to 2018. In addition, taking vegetation NPP as an index, Pearson correlation analysis, partial correlation analysis, and second-order partial correlation analysis were carried out to quantitatively analyze the contribution of climate change and human activities to vegetation NPP. Finally, the Hurst index and nonparametric Man-Kendall significance test were used to predict the future change trend of vegetation NPP in Sichuan Province. The results show that (1) from 2000 to 2018, the NPP of vegetation in Sichuan Province has a significant increasing trend (Slope = 6.09gC·m-2·a-1), with a multi-year average of 438.72 gC·m-2·a-1, showing a trend of low in the east and high in the middle. The response of vegetation NPP to altitude is different at different elevations; (2) the contribution rates of climate change and human activities to vegetation NPP change are 4.12gC·m-2·a-1 and 1.97gC·m-2·a-1, respectively. In contrast, the impact of human activities on NPP is more significant than climate change. Human activities are the main factors affecting vegetation restoration and degradation in Sichuan Province. However, the positive contribution to NPP change is less than climate change; (3) the future vegetation NPP change trend in Sichuan Province is mainly rising, and the same direction change trend is much larger than the reverse change trend. The areas with an increasing trend in the future account for 89.187% of the total area. This research helps understand the impact of climate change and human activities on vegetation change in Sichuan Province. It offers scientific bases for vegetation restoration and ecosystem management in Sichuan and the surrounding areas.


Subject(s)
Climate Change , Ecosystem , Humans , Models, Theoretical , Human Activities , China
2.
Guang Pu Xue Yu Guang Pu Fen Xi ; 34(7): 1763-8, 2014 Jul.
Article in Chinese | MEDLINE | ID: mdl-25269276

ABSTRACT

In order to explore the intrinsic relationship of mineral spectral characteristics and its composition, and provide the basis for the detection of mineral micro information by using hyperspectral technology, based on the thinsection analysis, the authors identified the minerals characteristics and mineral assemblages in rock samples, delineated typical chlorite minerals and divided the occurrence characteristics of chlorite. The authors measured chemical composition of 146 typical chlorite mineral particles by using electron probe micro analysis technology, and calculated the relevant chemical parameters of n(Al(IV)), n(Al(VI)), n(Fe), n(Mg), and n(Fe)/n(Fe + Mg) ratio. In addition we analysed the rock and mineral spectra, and extracted chlorite characteristic spectral parameters. The relationship between the spectra feature parameters and the main crystal chemical parameters in chlorite was analyzed. The study indicated that the diagnostic spectral wavelength of chlorites moved to long wavelength. The results have important guiding significance for identifying the alteration and rock forming mineral species, composition and structure characteristics by usinghyperspectral remote sensing technology.

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