Spatiotemporal variations and driving mechanisms of vegetation coverage in the Wumeng Mountainous Area, China

Abstract

Quantifying the influence of factors on changes in fractional vegetation cover (FVC) is critical for assessing regional environmental changes and consequent ecological protection. However, accurately identifying the factors responsible for vegetation changes remains a challenge. This study focuses on the Wumeng Mountain Area, China (WM), where the ecological environment is extremely fragile and the social economy underdeveloped. Using the enhanced vegetation index to calculate FVC, Sen's slope trend analysis, Mann–Kendall test with the trend-free prewhitening procedure, Pettitt change-point test, and Hurst exponent, we analyzed the spatiotemporal variations in vegetation from 2000 to 2019 and projected future variations. The geographical detector model was used to analyze the spatial differentiation driving mechanism of changes in vegetation cover in the WM. We observed that the spatiotemporal variation of vegetation in the WM was significant between 2000 and 2019. The areas of the WM with extremely significant growth and significant growth accounted for 32.57% (p < 0.01) and 15.28% (0.01 < p < 0.05), respectively. The mutation years of the significantly changed vegetation were concentrated between 2007 and 2011. However, 36.09% of vegetation growth exhibited strong unsustainable characteristics and based on the past 20 years, a potential decreasing trend that has great uncertainty in the future. The geographical detector model indicated that temperature and soil type were the primary driving forces for spatial differentiation of vegetation changes in the WM, with q values of 0.131 and 0.101, respectively. Interactions between climate, topography, and human activities promote vegetation growth in a nonlinear fashion