Abstract

As a typical clonal plant, Moso bamboo expands excessively worldwide, causing changes in various aspects of the native forest ecosystem. Among these aspects, aboveground biomass (AGB) is a key indicator characterizing forest productivity and carbon sequestration. However, it is difficult to track AGB changes of a fixed plot in a relatively short period. In this paper, we utilized terrestrial laser scanner (TLS) to investigate AGB changes resulting from the intrusion of Moso bamboo using the space-for-time substitution method. Three sample plots including a China fir stand, a mixed stand and a pure Moso bamboo stand were chosen at an ecotone to represent the different stages of bamboo expansion in Hutou Village, Chongqing, China. Their point clouds were first scanned using TLS, and then segmented into individual plants through refinedly processing the stem intersections. Subsequently, tree and bamboo classification was achieved via combining the structural features, stem texture features, and point distribution features of individual plants. Finally, the compatible biomass models were employed to estimate plant AGBs and analyze the changes. As a result, the overall classification accuracy of trees and bamboos was improved to 92.67 %. The AGB per unit area initially increased and subsequently decreased at three stages of Moso bamboo expansion (5.83 kg/m2, 6.04 kg/m2 and 5.36 kg/m2), and the AGB differences among individual plants showed the similar tendency. Notably, the average AGB of individual China firs in mixed stand (78.97 kg) was higher than that in the pure stand (70.41 kg), so did the average AGB of individual Moso bamboos (21.22 kg vs 18.70 kg). These results indicated that maintaining a certain degree of tree-bamboo mixture was beneficial for improving the gross forest AGB.

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