Study on growth of basal area increment of individual trees in broad-leaved secondary forest based on quantile regression model

The broad-leaved secondary forest is a complex multi-layered mixed-aged forests, and the growth of the basal area determines the stand quality and carbon sink capacity of the forest. The purpose of this study was to investigate the influence of the annual basal area increment (BAI) of individuals in the broad-leaved stratified forests on individual sizes, experimental forests, and forest vertical levels (forest stories).

Three different experimental forests of the broad-leaved secondary forest in southern Jiangxi in China were taken as the research objects. According to the differences in individual-tree height and stand species composition, three experimental forests were divided into three forest stories and six different silvicultural types. The article was adopted the method of quantile regression model that was set 19 quantiles (τ ∈ {0.05, 0.10, 0.15, ..., 0.90, 0.95}), and established the nonlinear regression relationship between the annual basal area increment (BAI) and diameter at breast height (DBH_2021), height-to-diameter ratio (H_D_ratio), forest stories, experimental forests, silvicultural types, etc., and used some indicator, such as AIC, R_τ², MAD and MD, to evaluate each quantile time regression model.

1) There were significant differences in BAI between three experimental forests, but the difference in BAI between the silvicultural plots and the unsilvicultural plots in the same experimental forest was not statistically significant; 2) The quantile regression model when the AIC value was the lowest was log (BAI)_τ - log (DBH_2021) + DBH_2021 + H_D_ratio; when the quantile τ=0.45, the quantile regression model of BAI was most optimal, the fitting coefficient R_τ² of the best quantile regression model of BAI was 0.535 3. When forest stories, experimental forest types, and silvicultural types were considered, the fitting coefficient increased respectively 10%, respectively 0.638 3 (considering forest stories, experimental forest types), 0.638 9 (considering forest stories, silvicultural types); 3) log (DBH_2021), H_D_ratio, forest stories, forest stages, and silvicultural types had positive effects on BAI.

The growth quantile model of annual basal area increment of individual tree based on DBH, height-to-diameter ratio, forest stories, forest stages, and silvicultural types can provide quantitative basis for the quality and efficiency improvement technology of broad-leaved secondary forest, and also provide a technical reference for the sustainable management of forest resources.