Dynamics of vegetation cover and its driving factors in the Qinling-Daba Mountains on regional scale for 1986-2019

The Qinling-Daba Mountains is the transitional zone of the north and south of China. The vegetation in this area, characterized by complexity, heterogeneity and transition, is particularly sensitive to global climate change and human activities. Based on the normalized vegetation index (NDVI) data of the growing season from 1986 to 2019, which was synthesized by Landsat series satellite data on Google Earth Engine, this paper uses the methods of spatial analysis and Geo-detectors to clarify dynamics of vegetation cover and its main driving factors in the Qinling-Daba Mountains. The results show that: (1) vegetation coverage in study area shows a U-shaped NDVI distribution pattern in latitude, anti-U-shaped patterns in longitude and with altitude ascending. (2) the dynamics of vegetation coverage can be divided into two periods according to the result of MK mutation test (the breakthrough increasing period around 2005) and the trend of NDVI change: the slow increasing period with an increasing rate of 0.25%/a from 1986 to 2004 (R2 0.74), and the rapid increasing period with an increasing rate of 0.30%/a from 2005 to 2019 (R2 0.92). (3) Soil type, landform, vegetation type, land use type and annual average temperature are the main driving factors of vegetation dynamics in the Qinling-Daba Mountains, while annual precipitation, population density and GDP are the secondary driving factors of vegetation dynamics. The land use type and land management policies in the Qinling-Daba Mountains have a strong impact on vegetation cover change, and the climate warming in recent decades plays more important role than precipitation on the vegetation dynamics. These results are of great significance to comprehensively understand the impact of global climate warming and human activities on the natural environment of the Qinling-Daba Mountains. ### Competing Interest Statement The authors have declared no competing interest.