The mid-altitude zone of the Qinling Mountains in China was once dominated by birch and pine-oak belts but are now mainly covered by secondary growth following large-scale deforestation. Assessing the recovery and sustainability of these forests is essential for their management and restoration. We investigated and compared the tree species composition and community assemblages of secondary forests of the birch and pine-oak belts in the Huoditang forest region of the Qinling Mountains after identical natural recoveries. Both types of belts had rich species compositions and similar floristic components but clearly different community structures. Tree diversity was significantly higher for the birch than the pine-oak belt. Niche and neutral processes simultaneously influenced the species distribution and community dynamics of the belts, and these forests were able to maintain stable development during natural recoveries. The conservation and management of these forests should receive more attention to protect biodiversity and the forest resources in the Qinling Mountains.

Understanding the factors that allow the successful regeneration of species is a key step toward the conservation and management of forests. In this study, canonical correspondence analysis was used to examine the relationships between the distribution of the regenerating species in pine-oak mixed forests and 18 environmental factors of topography, soil properties, and forest characteristics in seedlings and saplings in the Qinling Mountains in China. A generalized additive model was used to fit the response of the density of the regenerating species to the various environmental factors. Variation partitioning in both seedling and sapling stories indicated that the order of importance was soil properties > forest characteristics > topography. The distribution of seedlings and saplings was mainly influenced by slope gradient, shrub cover, and available phosphorus. Herb cover and total nitrogen level were major environmental factors affecting the density of the regenerating seedlings, but total potassium level and elevation were significant variables for saplings. Not all seedlings were able to establish successfully, perhaps due to stress from the external environment and the heterogeneity of the light availability in the understory as the forest developed. Appropriate thinning of stands with higher densities and closed canopies is expected to produce gaps and promote the natural regeneration of pine-oak mixed forests in the Qinling Mountains.

Understanding interspecific associations in old-growth forests will help to reveal mechanisms of interspecific replacement in the process of forest development and provide a theoretical basis for vegetation restoration and reestablishment. In this study, we analyzed interspecific associations of eleven dominant tree populations of varying development stages in an old-growth oak forest stand in the Qinling Mountains, China. We examined overall interspecific associations (multiple species) and pairwise interspecific associations (two species). Interspecific competition was intense during forest development and was the main factor driving succession. Community structure appears to become more stable over time which supports the harsh-benign hypothesis that interspecific competition is more common in stable sites. Old growth oak (Quercus spp.) forests are distributed widely around the world in part due to oak being a typical K-selected species. K-selected species produce fewer, high-quality offspring with higher survival rates, strong competitive ability, and longevity. The resulting distribution shifted from clumped to random, likely as a result of intense interspecific competition creating ecological niche differentiation.

Close-to-nature management (CTNM) has been proposed as a promising forestry management approach to improve the structure and quality of forests, which integrates wood production and ecological service functions. Research on the effect of CTNM on the univariate and bivariate distribution of the spatial structure of forest stands provides a scientific basis for the evaluation of CTNM implemented in forestry. Here, we analyzed and compared the spatial-structure characteristics of Masson pine (Pinus massoniana) plantations (young, middle-age, and near-mature stages) under CTNM 8 years after selective cutting and unmanaged control. We used univariate and bivariate distribution of three spatial-structure parameters: mingling (M), dominance (U), and uniform-angle index (W). Results showed that the effect of CTNM on spatial structure was more remarkable in middle-aged and near-mature Masson pine forests compared with the young forest. CTNM significantly improved mingling degree and promoted the horizontal distribution, thereby changing from a cluster to a random distribution. Moreover, CTNM improved the proportion of trees with a high mixing degree and random distribution and the proportion of trees having a micro-structure of random distribution with a high degree of mixture and dominance with a high degree of mixture in middle-aged and near-mature Masson pine forest. Overall, the implementation of CTNM 8 years ago showed a positive effect on the improvement of the spatial structure of Masson pine forest, but the present spatial structure is suboptimal. Further implementation of CTNM to adjust the mingling and uniform-angle index is necessary, and CTNM according to this method of frequency distribution of stand structure parameters can improve the success of forest management.

The relationship between height and diameter (H-D) is an important component in forest growth and yield models, and a better understanding of the relationship will improve forest monitoring, management, and biomass estimation. Sixteen nonlinear growth functions were fitted to H-D data for 1261 trees from a Cryptomeria fortunei plantation in the Pingba region of Guizhou Province, China. Of the 1261 trees, 80 % were randomly selected for model calibration, while the remaining trees were reserved for model validation. All models were evaluated and compared by means of multiple-model performance criteria. Although all 16 models showed a good fit to the dataset and each of them accounted for more than 75 % of the total variation in height, a large difference in asymptotic estimates was observed. The Chapman–Richards, Weibull, and Näslund models were recommended for C. fortunei plantations, due to their satisfactory height prediction and biological interpretability.