Aim of the study: Neighborhood-based stand spatial structure parameters can quantify and characterize forest spatial structure effectively. How these neighborhood-based structure parameters are influenced by the selection of different numbers of nearest-neighbor trees is unclear, and there is some disagreement in the literature regarding the appropriate number of nearest-neighbor trees to sample around reference trees. Understanding how to efficiently characterize forest structure is critical for forest management.Area of study: Multi-species uneven-aged forests of Northern ChinaMaterial and methods: We simulated stands with different spatial structural characteristics and systematically compared their structure parameters when two to eight neighboring trees were selected.Main results: Results showed that values of uniform angle index calculated in the same stand were different with different sizes of structure unit. When tree species and sizes were completely randomly interspersed, different numbers of neighbors had little influence on mingling and dominance indices. Changes of mingling or dominance indices caused by different numbers of neighbors occurred when the tree species or size classes were not randomly interspersed and their changing characteristics can be detected according to the spatial arrangement patterns of tree species and sizes.Research highlights: The number of neighboring trees selected for analyzing stand spatial structure parameters should be fixed. We proposed that the four-tree structure unit is the best compromise between sampling accuracy and costs for practical forest management.

One of the aims of sustainable forest management is to preserve the diversity and resilience of ecosystems. Unfortunately, changes in the soil microbial communities after forest management remain unclear. We analyzed and compared the soil microbial community of a natural Quercus aliena var. acuteserrata forest after four years of four different management methods using high-throughput sequencing technology. The forest management methods were close-to-nature management (CNFM), structure-based forest management (SBFM), secondary forest comprehensive silviculture (SFCS) and unmanaged control (CK). The results showed that: (1) the soil microbial community diversity indices were not significantly different among the different management methods. (2) The relative abundance of Proteobacteria in the SBFM treatment was lower than in the CK treatment, while the relative abundance of Acidobacteria in the SBFM was significantly higher than that in the CK treatment. The relative abundance of Ascomycota was highest in the CNFM treatment, and that of Basidiomycota was lowest in the CNFM treatment. However, the relative abundance of dominant bacterial and fungal phyla was not significantly different in CK and SFCS. (3) Redundancy analysis (RDA) showed that the soil organic matter (SOM), total nitrogen (TN), and available nitrogen (AN) significantly correlated with the bacterial communities, and the available potassium (AK) was the only soil nutrient, which significantly correlated with the composition of the fungal communities. The short-term SBFM treatment altered microbial bacterial community compositions, which may be attributed to the phyla present (e.g., Proteobacteria and Acidobacteria), and the short-term CNFM treatment altered microbial fungal community compositions, which may be attributed to the phyla present (e.g., Ascomycota and Basidiomycota). Furthermore, soil nutrients could affect the dominant soil microbial communities, and its influence was greater on the bacterial community than on the fungal community.

Patterns of tree distribution are an important attribute of forest structure and directly affect the health and stability of forest ecosystems. This paper studied the effects of forest management on the forest distribution pattern of Larix kaempferi plantations with an aim to improve the quality of the spatial structure of plantations by providing scientific grounds for near-nature distribution pattern adjustment. We set up 15 long-term positioning and monitoring plots of 20 m × 20 m of L. kaempferi plantations in Xiaolongshan, Gansu Province, China, based on the Clark and Evans index, and applied the structure analysis method of the neighboring tree relationship to determine the standard angle of the uniform angle index of regularly distributed plantation forests. The changes in forest distribution patterns were compared before and after randomized management (R1 (dumbbell-shaped random unit), R2 (torch-shaped random unit) and R1:R2 = 1:2 models) and underlayer tending and unmanaged control (CK). The results showed that (1) Under different management modes, the distribution patterns obtained by the Clark and Evans index and the mean values of the uniform angle index were entirely the same; all stand patterns were evenly distributed. (2) Regardless of randomized management or underlayer tending, the number of trees in the even distribution was the largest, accounting for more than 40%. (3) The mean values of the uniform angle index of most stands increased obviously after randomized management, among which the R1 and R2 stands showed an upward trend, while the R1:R2 = 1:2 stands showed a slight decrease. However, the mean values of the uniform angle index of the stands with underlayer management showed a decreasing trend. (4) The proportion of random trees in most stands increased significantly after randomized management, increasing by 1%~19% compared with that before adjustment, while the proportion of random trees in the underlayer tending treatment decreased by 2%~10%. Our results suggest that (1) The method based on the modified uniform angle index standard angle could effectively improve the accuracy of the distribution pattern of individual trees in plantation forests and further improve the accuracy of the overall stand pattern quantitatively. (2) Randomized management significantly increased the proportion of random trees in the stands, which accelerated the evolution of the forest distribution pattern of the L. kaempferi plantation to a random distribution.

Understanding the diversity and complexity of stand structure is important for managing the biodiversity of forest ecosystem, and stand structural diversity is essential for evaluating forest management activities. Based on the relationship of adjacent trees, a quantitative method of stand structure diversity is proposed to express the heterogeneity of stand structure in tree species, distribution pattern, species separation and size differentiation. In this study, we defined the diversity of structural unit types and derived a new index of forest structural diversity ($S_D^{\prime }$) employing the additivity principle of the Shannon–Weiner index. The efficiency of the index was verified by applying the new measure to sixteen field survey samples at different locations. The mountain rainforest in Hainan had the highest forest structural diversity, followed by broad-leaved Korean pine forests in Jiaohe (2), Jiaohe (1) and an oak-broadleaved mixed natural forest at Xiaolongshan (2). The $S_D^{\prime }$ values of plantations and pure natural forest were lower. The simulated data of different thinning methods and the intensity of broad-leaved Korean pine forests show that the new measure can reflect forest management changes on stand structure diversity. The value of $S_D^{\prime }$ compared with no treatments and the differences were greater as thinning intensity increased. The $S_D^{\prime }$ index provides minimum and maximum values for different structural unit types in forests to achieve a unified comparative basis for calculating forest structure diversity. It has the characteristics of the general diversity index and can well express the diversity of tree species, distribution pattern and size differentiation simultaneously. The $S_D^{\prime }$ index can not only calculate the structural diversity of mixed species forests but can also be used to calculate the structural diversity of pure forests. It can also be used to evaluate the change in stand structure diversity after management interventions.

The significance of biodiversity research is to understand the structure and function of the community, and then to protect and monitor the community. The metric of biodiversity is the base of biodiversity conservation. Species richness and evenness are the most common descriptors of biodiversity. Whether it is diversity information measure, probability measure or geometric measure, they all express the combination of species richness and evenness in different ways. This study presents a new biologically meaningful measure of species diversity, which evaluates species richness and evenness independently, designated as D_RE. The novelty of our method is to use “absolute discrepancy” to express the dissimilarity between the observed community and the uniform distribution community with the same species composition and same abundance of each species, and then measure the species evenness. The logarithmic transformation of the species number is used to measure species richness with values ranging between 0 and 1. We test the performance of this measure using simulated data and observations of natural and planted forests in different climatic zones. The results showed that the new diversity index (D_RE) has superior statistical qualities compared with the traditional indices. Especially, in extremely uneven communities, the new measure describes the causes of diversity changes than the traditional D_RE. In addition, D_RE is more sensitive to the abundance changes of rare species in the simulated community, and the interpretation of the results is more intuitive and meaningful. It is an improved method to evaluate the species diversity of any ecosystem.

Comprehensive evaluation of forest state is the precondition and critical step for forest management. To solve the problem that the radar plot and unit circle only focus on the value of each the evaluation index, this paper proposes a novel method for comprehensively and simultaneously evaluating the functionality and inhomogeneity of forest state based on the modified unit circle method. We evaluated the forest state of the Quercus aliena BL. var. acuteserrata Maxim. ex Wenz. broad-leaved mixed forest in the Xiaolong Mountains Forest Area of Gansu Province and the Pinus koraiensis Sieb. et Zucc. broad-leaved mixed forest in Jilin Province in China. According to the principle of comprehensive, scientific and operability, 10 evaluation indices on forest structure and vitality were selected to construct the evaluation indicator system. Each index was normalized based on the assignment method and ensured to be strictly positive based on reciprocal transformation method. The areas and arc length of the closed graph, formed by connecting every two adjacent indicators, in the radar plot and unit circle were extracted. Based on the isoperimetric theorem (isoperimetric inequality), a comprehensive evaluation model was constructed. Compared with radar chart and unit circle method, each index in the newly proposed unit circle method is represented by an independent sector region, reflecting the contribution of the index to the overall evaluation result. Each index has the same relative importance weight, contributing to the estimation the relative sizes of each aspect of forest state. The unique area and arc length of the closed graph help summarize the overall performance with a global score. The expression effect of improved unit circle has been enhanced, and as an English proverb put it, “A picture is worth a thousand words.” The new proposed method simultaneously evaluates the functionality and inhomogeneity of the forest state and it is a powerful tool for the diagnosis of forest state problems and the decision-making of forest management.