To analyze the main variables affecting crown biomass, we measured crown biomass and a number of variables describing tree size, such as stem diameter at breast height (D), tree height (H), crown width (Cw) and crown length (Cl), from 754 sample trees of four pine species in China, specifically, Pinus massoniana, P. yunnanensis, P. tabulaeformis and P. elliottii. In addition, we developed individual tree crown biomass equations and compatible branch and needle biomass equations based on one-, two- and multi-variable models using nonlinear mixed-effects modeling and error-in-variable simultaneous equations. The results showed that: (i) crown biomass was strongly correlated to D and H, and the new combined variables (D⁴/H) and (D²/H) were suitable for modeling two- and multi-variable crown biomass equations, respectively; (ii) the four species were ranked as P. yunnanensis, P. massoniana, P. elliottii and P. tabulaeformis from small to large based on estimates from crown biomass equations, and the crown biomass estimate of P. tabulaeformis was about 60% greater than that of P. yunnanensis; (iii) the ratio of branch to crown biomass increased with increasing D, and the four species were ranked as P. elliottii, P. tabulaeformis, P. massoniana and P. yunnanensis from small to large by the proportion of the branch to crown biomass; (iv) the mean prediction errors (MPE’s) of the crown biomass equations for the four species were less than 10%, which could meet precision needs for biomass estimation.

The Chinese pine (Pinus tabulaeformis Carr.) is an ecologically and economically important evergreen coniferous tree which dominates warm temperate forests throughout northern China. We established two permanent plots within the Chinese pine forest in the Jiulong Mountains, Beijing, China. To understand the structural characteristics and dynamics of these plots, we analyzed the spatial structural characteristics within nearest-neighbor relationships using the bivariate distributions of the stand spatial structural parameters: uniform angle index, W; mingling index, M; dominance index, U; and crowding index, C. Results revealed that most trees in the forest were randomly distributed. The predominant individuals and randomly arranged trees were in very dense areas and surrounded by the same species. In addition, both plots exhibited a uniform size differentiation pattern. The two plots differed mainly in the level of species mixture and dominance. The majority of reference trees in the pure Chinese pine forest (plot 1) exhibited poor species mingling and low dominance, whereas trees in the mixed Chinese pine forest (plot 2) were evenly distributed in each mingling class and most trees were of intermediate dominance. The study results are useful for optimizing forest management activities in the studied stands, promoting tree growth, regeneration and habitat diversity, and improving forest quality at a fine scale.

Structure-based forest management (SBFM) is a method for improving forest structure and quality based on nearest-neighbor analysis. Stand spatial structure directly affects the health and stability of forest ecosystems. Research on the effects of SBFM on the distribution of spatial structure parameters is needed to provide a scientific basis for further development and implementation of SBFM technology in forestry. The present study was conducted on six permanent plots (20 m × 20 m) established within a Platycladus orientalis (L.) Franco plantation in Beijing, China. Changes in stand spatial structure parameters (SSSPs) were evaluated in managed and control plots at three time points: before SBFM and after 2 and 7 years of SBFM. The results showed that SBFM gradually accelerated the development of the P. orientalis plantation toward a random distribution pattern, reaching a significant difference within 2 years. SBFM promoted the growth of medium and dominant trees, with a significant difference between SBFM and control stands after 7 years. It led to a slight increase in mingling compared to the control, although no significant differences were observed between treatments. SBFM generally decreased the proportions of disadvantageous microstructures (disadvantaged trees with non-randomly distributed, disadvantaged trees with a low degree of mingling, and non-randomly distributed trees with a low degree of mingling). It also improved the ratio of torch (R2) units to dumbbell (R1) units, gradually improving the stability of the plantation forest. The results of this study suggest that SBFM optimized the spatial structure of a P. orientalis plantation in Beijing, China, and was conducive to tree growth and forest stand productivity.

Forest inventory data (FID) are important resources for understanding the dynamics of forest carbon cycling at regional and global scales. Developing carbon storage growth models and analyzing the difference and climate effect on carbon sequestration capacity have a great importance in practice, which can provide a decision-making basis for promoting high-quality development of forestry and implementing the carbon emission peak and carbon neutralization strategy. Based on the carbon storage dataset of 2680 sample plots from the ninth national forest inventory (NFI) of China, the carbon storage growth models and climate-sensitive variable-parameter carbon storage growth models for three major coniferous plantations (Larix spp., Pinus massoniana, and Pinus tabuliformis) were developed by using weighted nonlinear regression method. The effects of two climate factors (mean annual temperature ($MAT$) and mean annual precipitation ($MAP$)) on carbon storage growth and carbon sequestration capacity were analyzed and compared. The mean prediction error ($MPE$) of carbon storage growth models for three major coniferous plantations was less than 5%, and total relative error ($TRE$) was approximately less than 2% for self- and cross- validation. The maximum current annual increment of carbon storage for P. massoniana, Larix, and P. tabuliformis was 2.29, 1.89, and 1.19 t/(ha·a), respectively, and their corresponding age of inflection point was 9a, 14a, and 30a, respectively. The maximum average increment of carbon storage for P. massoniana, Larix, and P. tabuliformis was 1.85, 1.50, and 0.94 t/(ha·a), respectively, and their corresponding age of quantitative maturity was 16a, 24a, and 53a, respectively. The maximum average increment of carbon storage for the P. massoniana and Larix plantations was approximately 1.97 and 1.60 times, respectively, that of P. tabuliformis plantation. The average increment of carbon storage for the P. massoniana and Larix plantations reduced approximately by 4.5% and 3.8%, respectively, when the MAT decreases by 1 °C. The average increment of carbon storage for the Larix and P.tabuliformis plantations decreased by approximately 6.5% and 3.6%, respectively, when the $MAP$ decreases by 100 mm. Our findings suggest that: the carbon sequestration capacity is from highest to lowest in the P. massoniana, Larix, and P. tabuliformis forests. $MAT$ and $MAP$ have different effects on the carbon growth process and carbon sequestration capacity of these plantations. The greatest impact on carbon sequestration capacity was detected in the Larix plantation, followed by the P. massoniana and P. tabuliformis plantations. It is essential to coordinate regional development and employ scientific management strategies to fully develop the maximum carbon sequestration capacity in terms of plantations in China. In the present study, we estimate the carbon storage in major coniferous plantations in China and describe a useful methodology for estimating forest carbon storage at regional and global levels.

Knowledge of seasonal variations of carbon (C), nitrogen (N), and phosphorus (P) concentrations plus C:N:P ratios can provide insight into the dynamics of biological processes, nutrient cycling, resource acquisition, and mass partitioning in plants and soils. Platycladus orientalis (Cupressaceae) is an important tree species distributed throughout northern China. We studied the seasonal dynamics of C, N, and P concentrations and their stoichiometry in leaves, branches, roots, and soil in a P. orientalis plantation. Plant and soil C, N, and P concentrations, and their stoichiometry varied significantly among ecosystem components and growth season sampling times, indicating nutrient allocation patterns and mobility in the P. orientalis plantation. Accurately quantifying and comparing C:N:P stoichiometry in the plant and soil of P. orientalis requires a study of plant organs, soil depth, and sampling times. The mean N concentration in leaves was 14.06 g kg-1 and the mean N:P ratio was 11.82, indicating that the growth of P. orientalis was N limited during the growing season. N and P concentrations and stoichiometry in plants were correlated with those in soil, suggesting coupled nutrient control between plant and soil. The C:N:P ratio was regulated in different components of the ecosystem.