Vegetation Dynamics and Potential Factors Driving Mechanisms in the Tarim River Basin
Given the extreme aridity of the Tarim River basin,it is critical to explore the characteristics of vegetation dynamics in the region and to quantitatively evaluate the strength of potential drivers to maintain ecosystem function and achieve sustainable development. The spatial and temporal trends and spatial autocorrelation of vegetation cover in the Tarim River basin from 2000 to 2020 are explored,based on long time series NDVI datasets,climate data,background data and land use data,and the strength of potential driving factors on NDVI changes is quantitatively assessed,using geographical detector. It is found that the average NDVI from 2000 to 2020 was 0.159,and 52.63％ of the area showed a significant growth trend with a growth rate of 0.02/10a,and the global Moran's index of NDVI showed a fluctuating upward trend and exhibited a spatial agglomeration. Land use conversion,soil type,and distance from the man-made surface were the main driving factors of vegetation change in the Tarim River basin,with explanatory power of 22.20％,8.57％,and 8.28％ for NDVI change,respectively. Precipitation is the dominant climatic factor in the northern part of the Tarim River basin,temperature has a stronger explanatory power for NDVI changes in the west and south,and distance to glaciers and snow is a factor affecting NDVI changes that cannot be ignored. The interaction of any two factors can improve the explanatory power of NDVI changes,among which the strongest explanatory power is found in land use conversion ∩ soil type (q=29.44％) at the watershed scale,while there are differences in the combination and intensity of the strongest explanatory interactions at the sub-basin scale. The results help to improve the understanding of NDVI change mechanisms in the Tarim River basin and provide a scientific basis for ecological conservation in arid and semi-arid regions.
Tarim River basinNDVIgeographical detectordriving factorsvegetationclimate change
NETL
NSTL
万方数据
