Understanding fine root characteristics in relation to soil properties of bamboo–broadleaf mixed forests may help optimize belowground production management and ecological functions in mixed-forest ecosystems. In this study, we compared four different bamboo–broadleaf mixed forests: Castanopsis chinensis (Sprengel) Hance with moso bamboo (CCB), Alniphyllum fortunei (Hemsl.) Makino with moso bamboo (AFB), Choerospondias axillaris (Roxb.) Burtt and Hill with moso bamboo (CAB), and Castanopsis fargesii Franch with moso bamboo (CFB), and analyzed their effects on the traits of fine roots of moso bamboo, soil nutrient contents, and enzyme activities. In January 2022, fine root and soil samples from four different mixed bamboo–broadleaf forests were collected from a subtropical region of Fujian Province, China. Results showed that CAB significantly increased fine root biomass (FRB) and root length density (RLD); however, specific root length (SRL) was only in the 0–20 cm soil layer. Specific surface area (SSA) was significantly reduced in the CCB in the 0–20 cm and 20–40 cm soil layers. The total phosphorous (TP) and total potassium (TK) contents of AFB and CAB were significantly increased (p < 0.05), and the alkali-hydrolyzable nitrogen (AN) content was significantly increased by CCB in the 0–20 cm soil layer (p < 0.05). Additionally, CFB increased the activities of acid phosphatase (ACP) and catalase (CAT) but decreased the activity of sucrase (SC). Principal component analysis showed that fine root traits (FRB, RLD, SRL, and SSA) were not only positively associated with soil organic carbon (SOC), total nitrogen (TN) and available potassium (AK) but also associated with urease (UE) and CAT. Therefore, belowground interactions between different species have a significant impact on the characteristics of fine roots and soil in bamboo–broadleaf mixed forests.

Moso bamboo (Phyllostachys edulis) is a critical forest resource in subtropical China, and reasonable cutting management of moso bamboo forests is essential for improving the productivity of bamboo forests, increasing the income of farmers, and improving the ecological environment. Therefore, we set up sample plots with different cutting widths at the Yixing Forest Farm in Jiangsu Province in December 2017. Moso bamboo growth surveys and soil sampling were conducted in May 2018 to study the effects of different cutting widths on the growth and nutrient content of moso bamboo forests. Our results indicate that strip cutting had significant effects on degraded bamboo shoots, the number of new bamboos, and their ratios. Soil elements showed surface aggregation, and cutting increased the soil nutrient content. Principal component analysis showed that stand characteristics (diameter at breast height and number of new bamboo shoots) were positively associated with total phosphorus and available phosphorus but negatively correlated with available potassium, total potassium, and soil organic carbon. A cutting width of 8 m resulted in rich nutrient content, which is suitable for bamboo cultivation. These results will provide theoretical guidance for the formulation of scientific and reasonable strip cutting methods for moso bamboo forests.

Height to crown base (HCB) is an important variable used as a predictor of forest growth and yield. This study developed a nonlinear, mixed-effects HCB model through inclusion of plot-level random effects using data from 29 sample plots distributed across a state-owned Yixing forest farm in Jiangsu province, eastern China. Among several predictor variables evaluated in the analyses, bamboo height, canopy density, and total basal area of bamboo with a diameter larger than that of the subject bamboo individual contributed significantly to the HCB variations. The inclusion of random effects improved the prediction accuracy of the model significantly, indicating that the HCB variations within and across the sample plots were substantial. The model was localized using four sampling strategies, and the study identified that using two medium-sized bamboos by diameter at breast height per sample plot resulted in the smallest prediction error. This strategy, which would balance both measurement cost and potential error, may be applied to estimate the random effects and localization of the nonlinear mixed-effects HCB model for moso bamboo in eastern China.

Degraded bamboo shoots (DBS) constitute an important variable in the carbon fixation of bamboo forests. DBS are useful for informed decision making in bamboo forests. Despite their importance, studies on DBS are limited. In this study, we aimed to develop models to describe DBS variations. By using DBS data from 64 plots of Yixing forest farm in Jiangsu Province, China, a mixed-effects model was constructed, including block-level random effects. We evaluated the potential impact of several variables on DBS. The number of bamboo shoots (NBS), mean height to crown base (MHCB), hydrolytic nitrogen (HN), and available potassium (AK) significantly contributed to the model. By introducing the block-level random effect in the logistic model, the fitting statistics were significantly improved. The model showed that there were increased DBS in bamboo stands with decreased MHCB and AK, whereas DBS decreased with decreasing NBS and HN. The application of K fertilizer reduced the number of DBS during the emergence stage. By adjusting these factors, the number of DBS in bamboo forests can be reduced, which provides a theoretical basis for increasing the biomass of bamboo forests. It can also provide an important basis for studying the carbon sink characteristics of bamboo forests and help to formulate more effective bamboo forest management plans.