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- W4387573085 abstract "Researchers build growth models to predict the growth of forest stands and propose management measures to improve the overall quality of these stands. In this study, data collected from 91 sample plots from the eighth (2010) and ninth (2015) Chinese National Forest Inventories in Jiangxi Province were used to establish a transition-matrix growth model. Then, 12 potential equilibrium curves were set to guide forest management, and a transition-matrix growth model was used to predict stand growth in Jiangxi Province. In each 10-year management period, trees with diameters that exceeded the equilibrium curve were cut down. The results show that species diversity (H1), size diversity (H2), and basal area (B) have statistically significant influences on growth, mortality, and recruitment. Moreover, the high accuracy of the transition-matrix growth model is demonstrated. According to the simulation results, B = 35 m2/ha, the maximum diameter of retained trees Dmax = 45 cm and the adjacent diameter ratio q = 1.7 constitute the optimal equilibrium curve to guide forest management. The diameter distribution guided by the equilibrium curve is reverse J-shaped and is associated with significant increases in the hardwood stock volume and current annual growth. Under the guidance of the equilibrium curve, the forests in Jiangxi Province can be reasonably managed, produce more high-economic-value timber, and achieve a more stable species composition. This study will help maximize the ecological and economic benefits of forests and provide a reference for the realization of the sustainable development of forestry. Furthermore, the results can be used to improve the facility and accuracy of natural forest harvesting." @default.
- W4387573085 created "2023-10-13" @default.
- W4387573085 creator A5050021472 @default.
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- W4387573085 date "2023-10-11" @default.
- W4387573085 modified "2023-10-13" @default.
- W4387573085 title "A Transition-Matrix Growth Model and Equilibrium Curve for Natural Forests in Jiangxi Province" @default.
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- W4387573085 doi "https://doi.org/10.3390/f14102038" @default.
- W4387573085 hasPublicationYear "2023" @default.
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