Insight into the imbalance of forest cover change at county level in mainland China during 2000-2020: From the perspective of subdividing forest cover change into forest gain and loss

The significant growth of China ' s forest resources presents a remarkable case in global vegetation dynamics. However, there is spatial imbalance in forest cover changes, which is not only reflected in regional imbalances, but also between total and net changes. There is still a lack of knowledge in this imbalance. In our comprehensive study, we subdivided forest cover change into forest gain and loss, and calculated the total and net forest change across 2850 county-level administrative units in mainland China, utilizing the Global Forest Change Dataset. The univariate linear regression and the Sen + Mann-Kendall test is utilized to explore the temporal trends in forest loss. Additionally, spatial autocorrelation models were employed to examine the spatial differentiation of forest cover change. Our findings unveiled a wide spectrum of forest loss rates ranging from 0% to 27%, and gain rates ranging from 0% to 10%, with the highest rates observed in the southern counties. We observed that the forest loss trends in southeastern counties showed significant and slight increases, while the northwestern counties experienced significant and slight decreases, with the Huhuanyong Line serving as the demarcation. In terms of spatial patterning, quite a number of the southern counties displayed a " large net change, large total change " state, which contrasted with diverse patterns observed in certain western regions. Spatial autocorrelation analysis showed that the High -high clusters of both forest gain and loss were primarily observed in southern counties, with the Low-low clusters in the northwest. This detailed analysis provides valuable insights into the dynamics of forest cover changes, offering a robust scientific foundation for developing informed and regionspecific conservation policies.