No abstract

The changing climate is worsening the threats to forests, such as insect outbreaks, fires, and drought, especially old-growth forest, which is more susceptible to disturbance. Therefore, it is important to detect the disturbance areas, identify the disturbance agents, and evaluate the disturbance intensity in old-growth forest. We tried to derive the forest disturbance information based on multiple remote sensing datasets (Global Forest Change, MODIS, and ERA5-Land) from 2000 to 2021 in Changbai Mountain, Northeast China, and explored their relationship with climate factors. The results showed that (1) wind damage and insect outbreaks are two main forest disturbance agents, (2) the increasing temperature during overwintering periods and the decreasing precipitation during activity periods increase the risk of insect outbreaks, and (3) disturbances lead to significant changes in forest structure and functional indices, which can be well captured by the remote sensing data. In the study, we creatively combined low-frequency remote sensing images and high-frequency meteorological data to determine the specific time of wind damage. The final results suggested that the vulnerability of old-growth forest to climate change may be mainly reflected through indirect implications, such as the increased risk of strong winds and insect disturbances.