Understanding nutrient quantity and quality in forest soils is important for sustainable management of forest resources and maintaining forest ecosystem services. In this study, six soil nutrient indicators, including soil organic matter (SOM), total nitrogen (TN), total phosphorus (TP), available nitrogen (AN), available phosphorus (AP), and available potassium (AK) were measured in five different aged stands of Chinese fir forests in subtropical China. A structural equation model (SEM) was developed based on these soil nutrients indicators in order to better evaluate the soil fertility index (SFI) in these studied forests. The results show that soil nutrient contents changed with the soil depth in different age groups. The SOM decreased in a specific order: over mature > mature > near mature > middle > young stands. The TN content of the soil gradually decreased with increased soil depth throughout all age groups. The SEM indicated that the TN had the highest weight of 0.4154, while the TP had the lowest weight at 0.1991 for estimating the SFI. The weights of other indicators (AN, SOM, AP, and AK) ranged 0.2138–0.3855 in our study. The established SEM satisfied the fitness reference values and was able to accurately describe the forest soil nutrient status through the SFI. The overall SFI values were significantly higher in over mature stands than in young-aged stands and in topsoil than in deeper soil in all examined forests. Soil TN, AP, and AK were the most important nutrient indicators to the evaluation of the SFI in the study sites. The results confirmed that the SEM was suitable to estimate the weights of the SFI and better describe the soil nutrient status in forests. Our research provides an innovative approach to assess a soil nutrient status and soil fertility and provides a scientific basis for accurate implementation of soil nutrient assessment in forest ecosystems.

Competition among trees for limited resources (e.g., sunlight, water, and nutrients) impacts their growth differently. Crown plays a crucial role in resource access for trees. However, uncertainties persist regarding crown size differences, tree growth, and tree competition levels between coniferous and broadleaf trees in mixed-age forests. We conducted a study on 3008 live trees across 28 plots in Hunan Province to measure individual crown size and tree growth increment. Introducing a new metric, the Crown Size Competition Index (CSCI), we assessed competition pressure among coniferous and broadleaf species in mixed-age forests. We examined the correlation between competition indices and tree growth increment while also investigating the influence of neighboring species diversity on tree competition. Our results revealed a significant negative correlation between the tree growth of Cunninghamia lanceolata (Lamb.) Hook.(CL) and Phoebe bournei (Hemsl.) Yang (PB) and the competition index. Increased competitive pressure on the focal tree corresponded to a decline in the growth of focal tree volume, with a more pronounced impact observed in PB compared to CL. The diversity of neighboring species contributed to variations in competition for the focal tree, with broadleaved species (PB) exerting a greater influence on the focal tree than coniferous species (CL). These findings underscore the competitive potential of PB in mature coniferous stands and advocate for the restoration of stratified mixes in CL broadleaf forests. Furthermore, our findings support the management strategies for the valuable tree species PB.

The spatial structure of forest stands significantly influences inter-tree competition and the overall stability of the stand’s ecological dynamics, and a profound understanding of forest stand spatial structure is essential for both effective forest management and ecological research. Previous studies on spatial structure have primarily employed single variables, offering only one-dimensional structural insights and lacking the capacity to interpret multidimensional information. In light of these limitations, our study introduces a novel approach founded on a six-variable distribution, aimed at conducting a comprehensive analysis and interpretation of the spatial attributes of forest stands. Diverging from conventional univariate or bivariate methods, the hexi-variate approach simultaneously considers six variables, facilitating a more intricate exploration of the intricate interrelationships within forest ecosystems from six distinct dimensions. We conducted an in-depth analysis of the spatial structural attributes within the forest stand, encompassing factors such as species diversity, size variation, spatial distribution patterns, openness, vertical stratification, and stand competition. To capture a comprehensive view of the trees’ spatial information, we employed the hexadecimal distribution method, effectively quantifying their characteristics across six dimensions. Our study unveiled a significant correlation between spatial structure and stand growth, establishing a connection by integrating the spatial structure with key structural features relevant to tree size. The outcomes of this study shed light on the effectiveness and superiority of the six-element distribution method when it comes to the analysis of forest structural characteristics. Our approach offers valuable insights into the optimization of forest management strategies, encompassing selective harvesting and biodiversity conservation, thereby establishing a solid footing for sustainable forest management practices.

To assess the alterations in soil properties resulting from the interplanting of broad-leaved tree species within coniferous forests, we conducted an investigation into soil quality in a mixed Chinese fir and broad-leaved forest, as well as in a Chinese fir pure forest (used as a control) in subtropical China. A total of 15 soil physicochemical properties were assessed across three soil depths—0–15 cm, 15–30 cm, and 30–45 cm—for the two forest types in the experimental study. Principal component analysis in conjunction with the Norm value was employed to create a minimal data set (MDS) for assessing six indicators, including bulk density (BD), total nitrogen (TN), total phosphate (TP), available potassium (AK), soil pH, and catalase (CAT). The soil quality index (SQI) was calculated for both forest types. The results demonstrated that following the interplanting of broad-leaved tree species in the Chinese fir forest, all soil physicochemical indicators were significantly improved compared to the control, and significant differences were also observed in the 0–15 cm and 15–30 cm soil layers (p < 0.05). The overall average of the SQI of the mixed forest (0.8523, 0.6636) was significantly higher than that of the control (0.4477, 0.3823) (p < 0.05) in the 0–15 cm and 15–30 cm soil layers, respectively. However, there was no significant difference in the SQI in the 30–45 cm soil layer (p > 0.05) between the two forest types. The results indicated that the SQI based on the minimal dataset (MDS) can reflect the SQI of the total dataset (TDS) when assessing soil quality in forests. Our research provides valuable scientific insights into soil science and an understanding of the relationships between soil properties, forest structure, and species composition in sustainable forest management.

Soil quality evaluation provides necessary and fundamental data and information for understanding the current situation of the soils and for promoting the sustainable use of land resources. In this study, soil quality was assessed by developing a structural equation model (SEM) in five aged Chinese fir plantations, located in the same soil type, with similar site conditions, in Subtropical China. A total of 150 soil samples were taken from the five aged stands of Chinese fir forests: 8-year-old young forests (stand I), 14-year-old middle-aged forests (stand II), 20-year-old near-mature forests (stand III), 26-year-old mature forests (stand VI), and 33-year-old over-mature forests (stand V). Fifteen soil indicators, including soil bulk density (BD), capillary porosity (CP), total capillary porosity (TCP), water holding capacity (WHC), soil organic matter (SOM), total nitrogen (TN), available nitrogen (AN), available phosphorus (AP), available potassium (AK), soil pH, soil acid phosphatase (ACP), invertase (INV), urease (URE), and catalase (CAT), were measured. The SEM was used to determine the weight of each soil indicator, and the soil quality index (SQI) was estimated for the Chinese fir plantations. Results showed that soil physical indicators, such as BD, CP, TCP, WHC, and chemical indicators, including SOM, TN, and AN, significantly degraded in stand II groups compared with the stand I groups, but were significantly recovered in the stand III groups. However, the enzyme activity of soil biological indicators had different patterns with changes in soil physical and chemical properties. The calculated SQI in the studied Chinese fir forests ranged from 0.4084 to 0.7298, which was significantly higher in the stand V and lower in the stand II (middle-aged stand) than in the other four aged stands (p < 0.05). The SEM weight analysis showed that the BD, SOM, and ACP were the most important indicators affecting the physical, chemical, and biological properties of the soils in Chinese fir forests in the study area. This study provided an innovative scientific approach for estimating the weight of SQI in forests and a theoretical basis and practical application for sustainable management of Chinese fir forest ecosystems.

Understory vegetation plays a key role in forest ecosystem material cycling and energy flow, and studying its biomass dynamics and underlying driving mechanisms is vital for understanding forest ecosystem functions and achieving precise management. In order to elucidate the complex pathways through which stand structure and environmental factors influence understory vegetation biomass, a study was conducted on 180 plots of Chinese fir forests at different developmental stages in the subtropical region of China. The study included 36 plots each of young forest (6 years), middle-age forest (12 years), near-mature forest (20 years), mature forest (25 years), and over-mature forest (30 years) stands. Based on the quantification of shrub and herb biomass in Chinese fir forests and functional clustering, structural equation modeling (SEM) was employed to systematically analyze the direct and indirect effects of environmental factors and stand structure on understory vegetation biomass. The results indicate the following: First, K-means clustering analysis revealed that shrub can be classified into two categories: Tall, dense shrubs (TD-SB) and Low-Sparse Shrubs (LS-SB), and herb can be classified into three categories: Tall, dense herbs (TD-HB), Low-Sparse herbs (LS-HB), and Medium-density herbs (MD-HB); Second, stand structure and environmental factors have significant effects on understory shrub and herb biomass. The Mingling Index of tree species within stand structure exerts the greatest negative effect on shrub biomass and the greatest positive effect on herb biomass. Among environmental factors, slope position and slope gradient have been found to exert a relatively strong positive influence on understory vegetation biomass. The results revealed that all stand structure indicators had a negative effect on the shrub biomass of TD-SB and LS-SB, while environmental factors had a negative impact on MD-HB. This study establishes a theoretical framework for the sustainable management of subtropical Chinese fir forest ecosystems and demonstrates its practical application.