The importance of the height-diameter (H-D) relationship in forest productivity is well known. The general nonlinear regression model, based on the mean regression technical, is not able to give a complete description of the H-D relationship. This study aims to evaluate the H-D relationship among relative competition levels and develop a quantile regression (QR) model to fully describe the H-D relationship. The dominance index was applied to determine the relative competition levels of trees for the Chinese fir. Based on the basic Weibull growth model, the mean regression for five relative competition levels and 11 QR models was constructed with 10-fold cross-validation. We have demonstrated that the H-D relationship for the Chinese fir strongly correlated with relative competition states, but the five curves from mean regression models did not show a notable difference between the trends of H-D relationship under different competition levels. Similar regression results were found in QR models of the specific quantiles; the average tree height of five competition levels varied between 5.78% and 17.65% (i.e., about 0.06 and 0.18 quantiles). In addition, some special curves of the H-D relationship such as the QR models of the 0.01 and 0.99 quantile showed the H-D relationship under certain conditions. These findings indicate that the QR models not only evaluated the rates of change of the H-D relationships in various competition levels, but also described their characteristics with more information, like the upper and lower boundary of the conditional distribution of responses. Although the flexible QR curves followed the distribution of the data and showed more information about the H-D relationships, the H-D curves may not intersect with each other, even when the trees reached their maximum height. Hence, the QR model requires further practice in assessing the growth trajectory of the tree’s diameter or tree height to gain better results.

Diversified soil microbiomes are the key drivers of carbon fixation and plant residue decomposition in forest ecosystems. Revealing the elevation patterns of soil microbial carbon cycling in forests is essential for utilization of forest ecological resources. However, the soil microbial diversity and carbon cycle processes in Platycladus orientalis plantations across different elevations are still unclear. Here, we established a gradient with three elevations (118 m, 300 m, and 505 m) on the Beijing Ming Dynasty Tombs Forest Farm, which is located in Changping District, Beijing. The metagenomics method was applied to study the soil microbiome, with a special focus on the carbon cycle process at each elevation. We found the diversity and composition of the soil microbiomes significantly varied across the elevation gradients. The structure of bacteria and archaea was mainly driven by soil total potassium, pH and NH₄⁺, but the eukaryota had no significant relationship with the environmental factors. The relative abundance of genes involved in microbial carbon fixation and decomposition of organic carbon were also significantly impacted by elevation, with the former showing increasing, u-shaped, or hump trends with increasing elevation, but the latter only showing hump trends. The rTCA cycle and 3-hydroxypropionate pathway were the dominant carbon fixation pathways in the Platycladus orientalis plantations. The elevation gradient shaped the microbial decomposition of plant-derived organic carbon by changing soil properties and, furthermore, led to soil organic carbon stock losses. These findings increase our understanding of soil microbial diversity and the carbon cycle across different elevations and provide a theoretical basis for the utilization of forest ecological resources to promote carbon sequestration.