Altitude plays a crucial role in shaping the diversity and distribution of species in forest landscapes in mountainous regions. However, existing studies often lack comprehensive analysis of the intricate relationships among environmental factors, disturbances, and species diversity. This study aims to address this gap by thoroughly analyzing major species’ diversity, distribution, and regeneration status, along with their influencing factors, across different altitudinal gradients (1850 to 2350 m). Field surveys were conducted to examine the major species in different vegetation layers of the secondary Picea forest in Guandi Mountain. The key findings from the study include the following: (1) the study area recorded a total of nine species of adult trees, belonging to eight genera in five families, fourteen species of shrubs from eight genera in five families, and fifty-two herb species representing forty-eight genera in twenty-six families. Dominant species varied across layers, with Picea asperata Mast. and Larix principis-rupprechtii Mayr. dominating the arborous layer, Lonicera ferdinandii Franch. and Cotoneaster acutifolius Turcz. in the shrub layer, and Poa pratensis L. and Duchesnea indica (Andrews.) Focke in the herb layer. (2) Altitude significantly influenced species diversity, with the most pronounced effects observed in the shrub and herb layers. (3) Tree species regeneration varied with altitude, with Picea asperata exhibiting the highest regeneration performance, particularly in the high-altitude zone (2250–2350 m). Regeneration parameters were significantly correlated with species diversity indices in both tree and shrub layers. (4) Redundancy analysis revealed that, apart from altitude, cutting (p = 0.015) influenced the species diversity of the tree layer, while annual precipitation (p = 0.006) and temperature (p = 0.01) determined the diversity of the shrub layer. Grazing (p = 0.042) was identified as a determining factor for species diversity in the herb layer. Overall, these findings provide valuable insights into the sustainable management of forest ecosystems in the study area and offer practical guidance for forest management in similar mountainous landscapes worldwide.

The effects of disturbance on spatial patterns and species interactions provide critical information on community structure and species coexistence. Two standard plots of 1-ha were set, one of them was a sample plot with retrograde succession after disturbance, and the other one was undisturbed. Spatial indices and Spatial patterns statistics were used to analyze the spatial pattern and inter-specific correlation of main tree species in two plots. Our results showed that the diameter distributions of different species have reverse J-shape, unimodal and bimodal distribution in the disturbed plot, while bell-shaped curves were observed in the undisturbed plot. The distributions of tree species were mainly showed clustered patterns in almost all scales through univariate pair correlation function. Some similar results of the classification of Wiegand scheme of species association consistent with the consequences of the bivariate pair correlation. The mark variograms showed positive autocorrelation at a coarse scale. The current study may aid in efforts of forest management planning and ecosystem services. Meanwhile, different research methods of spatial distribution also help to improve the accuracy of spatial distribution and the interspecific association of tree species.

Accurate prediction of individual tree mortality is essential for informed decision making in forestry. In this study, we proposed machine learning models to forecast individual tree mortality within the temperate Larix gmelinii var. principis-rupprechtii forests in Northern China. Eight distinct machine learning techniques including random forest, logistic regression, artificial neural network, generalized additive model, support vector machine, gradient boosting machine, k-nearest neighbors, and naive Bayes models were employed, to construct an ensemble learning model based on comprehensive dataset from this specific ecosystem. The random forest model emerged as the most accurate, demonstrating 92.9% accuracy and 92.8% sensitivity, making it the best model among those tested. We identified key variables impacting tree mortality, and the results showed that a basal area larger than the target trees (BAL), a diameter at 130 cm (DBH), a basal area (BA), an elevation, a slope, NH4-N, soil moisture, crown density, and the soil’s available phosphorus are important variables in the Larix Principis-rupprechtii individual mortality model. The variable importance calculation results showed that BAL is the most important variable with an importance value of 1.0 in a random forest individual tree mortality model. By analyzing the complex relationships of individual tree factors, stand factors, environmental, and soil factors, our model aids in decision making for temperate Larix gmelinii var. principis-rupprechtii forest conservation.

Understory vegetation is an important component of forest ecosystems, and the supply of nutrients in the soil is related to the growth and development of soil microorganisms and understory plants. The effects of different tree species composition ratios in the forest on the process of soil microbial community assembly are not clear in the existing studies, and the factors influencing the differences in the abundance of understory plants under different forest canopy compositions and their mechanisms of action have not yet been clearly explained. In this study, two types of pure forests (PFP and PFQ) and two types of mixed forests (MF and MPQ) were selected from the Zhongcun Forestry, and the soil characteristics, soil microbial community assembly process, and understory plant community abundance, composition, and β-diversity were analyzed for the different forest types. The results showed that changes in the proportion of broadleaf and coniferous species in the forest could lead to changes in the community assembly process of soil fungi, and that the fungal assembly process in the mixed forest was mainly related to dispersal limitation. Compared with pure forests that were exclusively coniferous or exclusively broadleaf, mixed coniferous and broadleaf forests had a higher abundance of understory plants and a more stable forest community composition. In mixed forests, forests with a large proportion of broadleaf arbors had more available resources in the soil, soil pH was closer to neutral, and soil C was less likely to be lost compared to forests with a large proportion of conifers.