Tree allometric models that are used to predict the biomass of individual tree are critical to forest carbon accounting and ecosystem service modeling. To enhance the accuracy of such predictions, the development of site-specific, rather than generalized, allometric models is advised whenever possible. Subtropical forests are important carbon sinks and have a huge potential for mitigating climate change. However, few biomass models compared to the diversity of forest ecosystems are currently available for the subtropical forests of China. This study developed site-specific allometric models to estimate the aboveground and the belowground biomass for south subtropical humid forest in Guangzhou, Southern China. Destructive methods were used to measure the aboveground biomass with a sample of 144 trees from 26 species, and the belowground biomass was measured with a subsample of 116 of them. Linear regression with logarithmic transformation was used to model biomass according to dendrometric parameters. The mixed-species regressions with diameter at breast height (DBH) as a single predictor were able to adequately estimate aboveground, belowground and total biomass. The coefficients of determination (R²) were 0.955, 0.914 and 0.954, respectively, and the mean prediction errors were −1.96, −5.84 and 2.26%, respectively. Adding tree height (H) compounded with DBH as one variable (DBH²H) did not improve model performance. Using H as a second variable in the equation can improve the model fitness in estimation of belowground biomass, but there are collinearity effects, resulting in an increased standard error of regression coefficients. Therefore, it is not recommended to add H in the allometric models. Adding wood density (WD) compounded with DBH as one variable (DBH²WD) slightly improved model fitness for prediction of belowground biomass, but there was no positive effect on the prediction of aboveground and total biomass. Using WD as a second variable in the equation, the best-fitting allometric relationship for biomass estimation of the aboveground, belowground, and total biomass was given, indicating that WD is a crucial factor in biomass models of subtropical forest. Root-shoot ratio of subtropical forest in this study varies with species and tree size, and it is not suitable to apply it to estimate belowground biomass. These findings are of great significance for accurately measuring regional forest carbon sinks, and having reference value for forest management.

A catastrophic ice storm occurred in the spring of 2008, which severely destroyed nearly 13% of China’s forests; among them, the broad-leaved forest suffered the most extensive damage. In this study, allometric models of the evergreen broad-leaved forests damaged at different recovery stages after the disaster were established to estimate the aboveground biomass of damaged trees. Plant plots were established and surveyed in damaged forests to determine species composition and diameter distribution, and finally a sample scheme was formulated that contained 47 trees from 13 species. The destructive measurements of aboveground biomass of trees selected according to the scheme were conducted in 2008, 2010, 2012 and 2016, respectively. Undamaged trees in the same region were also selected to measure the biomass in 2010. Linear regression of logarithmic transformation of the power function form was performed using Diameter at Breast Height (DBH) as predictor to develop biomass allometric models. The results showed that the ice storm caused tree aboveground biomass loss, which caused different parameters of the tree biomass models at different recovery stages. The models have a high accuracy in predicting trunk and total aboveground biomass, with high determination coefficients (R², 0.913~0.984, mean 0.957), and have a relatively low accuracy in predicting the biomass of branches and leaves (R², 0.703~0.892, mean 0.784). The aboveground biomass reduced by 35.0% on average due to the ice storm, and recovered to the same level of undamaged trees in the same diameter 8 years after the disturbance. The branches and leaves recovered very fast, and the biomass of these parts exceeded that of the undamaged trees, reaching the same diameter 2 years after the disaster, indicating an over compensatory growth. The trees with a smaller diameter were mostly composed of middle and late succession species, and recovered faster than other species, indicating that the ice storm may alter the forest structure and accelerate community succession. The biomass allometric models built in this study, combined with forest inventory data, can estimate forest biomass loss and recovery after disturbance, and offer an important sense of the assessment of forest damage and the formulation of forest post-disaster management strategies.

Schima superba is a widely distributed and broadly planted broadleaf tree in southern China. Information regarding the probability of stump resprouting, characteristics of the growth of resprouts and their influencing factors after disturbance is lacking. In this study, plant survey plots were established in fertile and barren soil conditions one month after a severe ice-snow storm disaster and the resprouting investigations were conducted four years after the treatment. The species showed a rather high (87.8% in total) resprouting probability and independent of stump diameter and soil fertility condition but positively affected by stump height. Stumps in fertile soil can generate more resprouts than in barren soil and there is no influence in the subsequent resprouts survival and growth. Stump diameter has no influence on the number of resprouts per stump generated, but facilitated the survival and growth of resprouts. Stump height had a positive influence on resprouts number per stump generated and a negative influence on resprouts growth, but had no significant influence on resprouts survival rate and dominant resprouts growth. We recommend conducting a harvest of S. superba at <30 cm aboveground level (traditional method). Fertilization immediately following logging or disturbance and artificial resprouts thinning is not recommended for this species.

Assessing carbon stocks in tropical forests is crucial for understanding their role in mitigating climate change. (1) Background: However, existing assessments have underestimated certain factors that can substantially influence carbon dynamics. (2) Methods: This study focuses on one such factor - buttress roots from a tropical forest. (3) Results: Our findings reveal that a significant proportion of trees (69.57%) had 3 to 5 buttress roots per tree. The total biomass of the buttress roots and the aboveground portion of the trees with buttress roots were calculated to be 8.5 tonnes/ha and 10.7 tonnes/ha respectively. The buttress root biomass accounted for 16.18% of the total tree biomass. It was observed that the presence of buttress roots during both the rainy and dry seasons increased the soil organic carbon content by an average of 20.8% in the upslope areas with buttress roots. During the rainy season, the presence of buttress roots did not affect the heavy fraction organic carbon in the soil layers in a statistically significant way. Regardless of the season, the soil respiration rate in the areas without buttress roots was higher than that in the areas with buttress roots. The presence of buttress roots had a positive effect on soil nutrient concentration in all seasons, creating a healthier environment for trees. Tree species with buttress roots had on average 20% higher organic carbon content during both the wet and dry seasons. (4) Conclusions: These findings highlight the importance of considering buttress roots in carbon stock assessments and forest management strategies. By integrating buttress roots into carbon accounting models, we can obtain more accurate estimates of carbon stock potential and develop more effective conservation and restoration strategies for tropical forests.

Accurate estimation of forest biomass and its growth potential could be important in assessing the mitigation potential of forest for climate change. However, severe mechanical disturbance such as stem breakage imposed significant changes to tree individuals in biomass structure, which could bring new inaccuracy to biomass estimation. In order to investigate the influence of severe mechanical disturbance on tree biomass accumulation and to construct accurate models for biomass and carbon storage estimation, this paper analyzed the relationship between tree size and biomass for China fir (Cunninghamia lanceolata (Lamb.) Hook) which suffered stem breakage from, and survived, an ice storm. The performance of independent variables diameter (D) and height (H) of China fir, were also compared in biomass estimation. The results showed that D as an independent variable was adequate in biomass estimation for China fir, and tree height was not necessary in this case. Root growth was faster in China fir which had suffered breakage in the main stem by the ice storm, than China fir which were undamaged for at least 7 years after the mechanical disturbance, which, in addition to biomass loss in stem, caused changes in the allocation pattern of the damaged trees. This suggests biomass models constructed before severe mechanical disturbance would be less suitable in application for a subsequent period, and accurate estimations of biomass and forest carbon storage would take more effort.