Study on the Growth Status of the Mixed Forest of Machilus versicolora and Cunninghamia Lanceolata
This study aims to investigate the growth status of the mixed forest of Machilus versicolora and Cunninghamia lanceolata.By collecting and analyzing sample plot data,the impact of mixed ratio on tree height,diameter at breast height,volume,and biomass of roots,leaves,branches,stems,and whole plants was evaluated.The research results indicate that the mixed forest of Machilus versicolora and Cunninghamia lanceolata can significantly improve the growth performance of trees.The tree height,diameter at breast height,and volume in the mixed forest are significantly higher than those in the single forest.This is mainly due to the interaction effect between tree species in the mixed forest,which promotes the growth and development of trees.The increase in the mixed proportion leads to a further increase in tree height,diameter at breast height,and volume;In addition,mixed forests also have an impact on the biomass allocation of trees.In mixed forests,the biomass of the roots,leaves,and branches varies.Due to competition among tree species and uneven resource allocation,the biomass of the roots and leaves increases compared to a single forest,while the biomass of the branches slightly decreases.However,the impact on the biomass of the main stem is relatively small,and there is little correlation with the change in mixed proportion.Overall,the mixed forest of Machilus versicolora and Cunninghamia lanceolata has good growth potential and economic benefits.Mixed forests can improve the growth speed and intensity of trees,thereby promoting the growth of tree height,diameter at breast height,and volume.Although the biomass of the entire plant has slightly decreased compared to a single forest,this reduction has no significant negative impact on economic benefiits.Therefore,the mixed forest of Machilus versicolora and Cunninghamia lanceolata is a potential economic forest planting model that is worthy of further promotion and application.
万方数据
维普
