Arid Zone Research ›› 2023, Vol. 40 ›› Issue (2): 292-302.doi: 10.13866/j.azr.2023.02.13

• Ecology and Environment • Previous Articles     Next Articles

Spatial heterogeneity of gravel size in Northern Tibetan Plateau

XU Tao1(),YU Huan1(),KONG Bo2,QIU Xia1,3,HU Mengke1,LING Pengfei1   

  1. 1. School of Earth Sciences, Chengdu University of Technology, Chengdu 610059, Sichuan, China
    2. Chengdu Institute of Mountain Land and Disasters, Ministry of Water Resources, Chinese Academy of Sciences, Chengdu 610041, Sichuan, China
    3. Sichuan Real Estate Registration Center, Chengdu 610014, Sichuan, China
  • Received:2022-07-09 Revised:2022-11-27 Online:2023-02-15 Published:2023-03-08
  • Contact: Huan YU E-mail:1509371533@qq.com;yuhuan0622@126.com

Abstract:

Gravel is the product of various hydrological and erosion processes and is a symbol of grassland and soil degradation and ecosystem deterioration. Consequently, gravel also affects various erosion processes. Studying the spatial differentiation of gravel in the Northern Tibetan Plateau is of considerable importance for the restoration of regional ecological environments. In this paper, the size and spatial location of surface gravel were studied, and the spatial heterogeneity was systematically analyzed by Moran’s I index, spatial variogram, geographic detector, and regression analysis. The following results are presented. (1) The global Moran’s I index is 0.481, which shows a significant positive correlation. Meanwhile, the local Moran’s I index shows a high-high gravel accumulation pattern in the eastern part of the study area, low-low in the middle part, and mostly random distribution in the rest of the study area. (2) Gravel spatial heterogeneity is dominated by structural factors. However, some differences are found between the best fitting model of the variogram and the values of characteristic parameters; that is, certain anisotropy characteristics exist. (3) The geographic detector results showed that NDVI and land-use type were the main factors affecting the spatial heterogeneity of gravel size in the study area, while population density, vegetation type, and annual average precipitation were the secondary factors. (4) The results of regression analysis revealed that the optimal scale regression was the best regression model, and NDVI had the largest influence on gravel size, followed by land-use type, annual mean precipitation, and vegetation type.

Key words: Northern Tibetan Plateau, gravel size, spatial heterogeneity, geographic detector, regression analysis