Introduction

As the largest ecosystem and ecological barrier on land, the forest is known as the “lung of the earth”. With various substances, huge productivity, complex structures, and rich diversity, forest is the green protective umbrella on which human beings rely for survival1,2. It can not only produce wood and related forest products, bring economic benefits, and then promote social progress, but also play a huge role in conserving water resources, cementing water and preserving soil, purifying air, regulating climate, and maintaining ecosystem stability. It has powerful and diverse functions and has an important impact on the historical process of human civilization and natural development3,4,5. Forest quality refers to the comprehensive advantages and disadvantages degree of forest stand structure, growth status, regeneration ability, and health status. It is the sum of all functions and values of forests in terms of ecological, social, and economic benefits6. The evaluation of forest quality can not only reflect the current situation and dynamic change trend of forest resource quality, but also provide the scientific basis for the formulation of a sustainable management strategy of forest resources, the improvement of forest resource management level, and the enhancement of regional ecological environment7. It is possible to carry out accurate and effective management adjustments by making a scientific and reasonable evaluation of forest quality. Stand status refers to the characteristics and conditions of stands in their natural habitats. In the process of stand development, stand status is not only the specific manifestation of stand quality, but also directly affects stand productivity and evolution development trend. An accurate quantitative description of stand status can help people better understand the development process, development status, and development trend of stands8,9,10. The evaluation of stand quality based on stand status has better timeliness and operability, and the stand status will have a direct impact on the necessity and urgency of stand management. Therefore, it is necessary to have a full understanding of the current structural status of the stand before the reasonable management of a particular stand. And the evaluation results provide an important scientific basis for the adjustment of stand management measures, which is a necessary means to improve the quality of the stand effectively11,12. Because the forest is a complex ecosystem, the multi-indicator comprehensive evaluation of stand quality is the premise and key to the decision-making of forest management. However, the premise of a multi-indicator comprehensive evaluation is to construct a scientific indicator system and select a reasonable evaluation method to evaluate the quality of actual stands, so as to draw a scientific and impartial comprehensive evaluation conclusion13, and then formulate and carry out targeted stand management measures, which is conducive to the accurate improvement of stand quality.

In recent years, many scholars have conducted extensive and in-depth research on forest quality evaluation according to different research purposes and objects7,14,15,16,17,18, but there is no unified evaluation indicator system17, such as forest resources quality evaluation indicator system15,19,20,21, forest health evaluation indicator system22,23,24,25, forest ecological environment quality evaluation indicator system26, forest multi-functional evaluation system27, forest naturalness evaluation system28, and stand management urgency evaluation system29. Furthermore, the evaluation methods are different18, such as expert evaluation method13,30, analytic hierarchy process method31, multiplication division method32, fuzzy comprehensive evaluation method33, and radar chart analysis method34. Forest has spatial scale attributes, including regional level, landscape level, stand level and other scale levels. Therefore, it is necessary to evaluate forest quality according to different scales35,36. The stand is a forest section with very similar internal structure characteristics, but there are obvious differences with its adjacent stands37. At present, there were many studies on forest quality evaluation at the stand level10,14,16,20,29,38,39,40. Among them, Hui et al. proposed the stand status unit circle method10,12, which inspired the evaluation of stand quality and provided new ideas for the comprehensive evaluation of stand quality in this research. Through the comprehensive evaluation of forest quality, it was the premise and key to implement management measures and make forest decisions according to local conditions13. In terms of policies, the use of a single indicator may lead to one-sided results in stand quality assessment, which in turn could misguide forest management decisions. This research attempted to give a quantitative comparison method of stand quality that aimed to provide the overall expression and measurement of stand quality for the purpose of cultivating healthy, stable, high-quality and efficient forests. It could directly address the two core issues of “one-sidedness in single-dimensional assessment” and “neglect of interactive influences among multiple factors”, thereby achieving a comprehensive and dynamic assessment of forest stand quality. Moreover, its quantitative data could support macro decision-making. For example, it could help adjust plans based on contradictions in regional stand quality, balance protection and development, and promote sustainable utilization. Meanwhile, this method could concisely and intuitively reflect the relative advantages and disadvantages of the assessed stands in terms of indicators, identify the “shortcomings” in stand quality, guide managers in formulating targeted measures, and contribute to the precise optimization of stand quality. It was expected to compare the quality of different stands, provide important references and insights for diagnosing problems in stand quality and precisely improving it, and further effectively enhance the overall quality of stands and promote their balanced development.

The application results of evaluation methods in different forest types in China

According to the above stand quality evaluation methods, the stand quality of typical forest types in China were analyzed and evaluated. The results are shown in Table 1; Fig. 1. In terms of vertical structure, the results of the two measurement methods were consistent. Furthermore, in terms of stand growth, this research selected the number of larger trees in the stands according to the proportions of 50%, 70%, and 80%, respectively, calculated the potential densities of the stands, and compared them. However, this research finally selected 70% as the proportion of the number of larger trees in the stands. The specific reasons for the selection are shown in “Discussion”.

Table 1 Comprehensive evaluation results of stand quality. (a) in each indicator sequence, the value or status on the left side of the Slash is obtained according to the calculation and evaluation method of the corresponding indicator, and then the assignment on the right side of the Slash is obtained according to the assignment standard. (b) the value of the stand growth sequence : when the value obtained by the calculation method is less than the interval boundary value, the value is assignment. (c) the vertical structure and stand growth were compared according to different methods, and the data are presented in the table.
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Unit circle of different stand quality evaluation.

Stand quality of artificial forest

In terms of stand growth, the potential density (B0) values of artificial mixed forests and artificial pure forests were all > 0.75, stands were growing well, and the grade assignments were all 1. In terms of stand regeneration, only the number of seedlings with seedling height H ≥ 50 cm in artificial mixed forest stand-25 was 3680 plants/ha, the regeneration level was excellent, and the grade assignment was 1. The remaining stands had no seedlings with seedling height H ≥ 50 cm, the regeneration level of these stands was very poor, and the grade assignments were all 0. In terms of tree health, the proportion of healthy trees in artificial pure forest stand-13 was 85.0%, the health level of trees was general, and the grade assignment was 0.5. The proportion of healthy trees in other stands was > 90%, the health level of trees was very good, and the grade assignments were all 1. It could be seen that there was little difference in growth, regeneration, and health between artificial mixed forests and artificial pure forests. However, in terms of vertical structure, the artificial mixed forests were all multi-layer forests that could obviously present two layers according to the difference in tree height, and the grade assignments were all 0.5. In the artificial pure forests, some stands were similar to the artificial mixed forests, and the vertical layers were more significant, which could show obvious two layers, that was, the two layers of multi-layer forests, and the grade assignments were all 0.5. in contrast, the other part of the forests were the typical single-layer forests due to the approximate tree height between the trees and no obvious layers, and the grade assignments were all 0. In terms of horizontal structure, the trees in artificial pure forests were evenly distributed, the distribution pattern of trees was unreasonable, and the grade assignments were all 0. In the artificial mixed forests, the trees of stand-14 and stand-15 were similar to those of artificial pure forests, which were evenly distributed, the distribution pattern of trees was unreasonable, and the grade assignments were all 0, while the trees of stand-24 and stand-25 were randomly distributed, the distribution pattern of trees was reasonable, and the grade assignments were all 1, so the horizontal structure was significantly better than that of artificial pure forests. In terms of age structure, the artificial pure forests were the even-aged forests, with the normal diameter distribution and the grade assignments of 0. In the artificial mixed forests, the stand-24 and stand-25 were the even-aged forests, the diameter distribution was similar to that of artificial pure forests, which was the normal distribution, and the grade assignments were all 0. The stand-14 and stand-15 were incomplete uneven-aged forests with the multi-peak diameter distribution and the grade assignments of 0.5, so the age structure was better than that of artificial pure forests. In terms of tree species composition, the sr of artificial pure forests was < 0.50, the relative tree species richness of stands was lower, and the grade assignments were all 0. In the artificial mixed forests, the sr of stand-24 and stand-25 were 0.411 and 0.406, respectively. Although the grade assignments were all 0, the sr of these two stands was higher than that of artificial pure forests. The sr of stand-14 and stand-15 were 0.503 and 0.513, respectively. The relative tree species richness of stands was general, and the grade assignments were all 0.5. Therefore, the tree species composition of artificial mixed forests was generally better than that of artificial pure forests. In terms of stand density, the stand crowding degree K of artificial pure forest stands was distributed in all ranges, but the proportion of artificial pure forests in [0.7, 0.9) was relatively large, the densities were relatively crowded, and the grade assignments were all 0.5. However, in the artificial mixed forests, the crowding degree K of stand-15 and stand-25 was between [0.9, 1.1], the densities were moderate, and the grade assignments were all 1. Although the grade assignments of stand-14 and stand-24 were all 0.5, the crowding degree K of stands was close to [0.9, 1.1], especially the crowding degree of stand-24 was K = 1.108. It could be seen that the stand densities of the artificial mixed forests were generally significantly better than those of the artificial pure forests. In terms of large-diameter tree, the relative large trees of the artificial pure forest stand-26 accounted for 6.08%, the proportion of dominant trees in the stand was moderate, and the grade assignment was 0.5. In addition, the proportion of relative large trees in other artificial pure forests was < 5%, the proportion of dominant trees in the stands was lower, and the grade assignments were all 0. In the artificial mixed forests, the relative large trees of stand-25 accounted for 4.73%, the proportion of dominant trees in the stand was lower, and the grade assignment was 0. In addition, the proportion of relative large trees in other artificial mixed forests was > 5%, the proportion of dominant trees in the stands was moderate, and the grade assignments were all 0.5. Therefore, the large-diameter trees of artificial mixed forests were generally better than those of artificial pure forests. In summary, except that the quality grades of individual artificial mixed forests were consistent with those of artificial pure forests, the quality grades of artificial mixed forests were generally better than those of artificial pure forests.

Stand quality of natural forest

In terms of stand density, the stand crowding degree K of most stands in the selected sample plots was between [0.7, 0.9), the densities were relatively crowded, and the grade assignments were all 0.5. In general, there was no significant difference between natural mixed forests and natural pure forests. In terms of forest health, the proportion of healthy trees in natural pure forest stand-10 was 89.1%, the health level of trees was general, and the grade assignment was 0.5. In addition, the proportion of healthy trees in the other stands was > 90%, and those in most of the stands could reach more than 99%, the health level of trees was very high, and the grade assignments were all 1. Based on the above two evaluation contents of stand density and forest health, there was almost no difference between natural mixed forests and natural pure forests. In terms of stand growth, the stand potential density (B0) values of natural mixed forests were all < 0.75, and the stand growth was general, so the grade assignment of each stand was the actual B0 value. The stand potential density (B0) values of the natural pure forests were all > 0.75, the stand growth was good, and the grade assignments were all 1. It could be seen that the stand growth of the natural pure forests was better than that of the natural mixed forests. However, in terms of vertical structure, some stands of the natural pure forests were all multi-layer forests that could obviously present two layers according to the difference in tree height, and the grade assignments were all 0.5. The other part of the natural pure forests were the typical single-layer forests due to the similarity of tree height between the trees and no obvious layers, and the grade assignments were all 0. In the natural mixed forests, only the stand-20 was similar to some natural pure forests, which could present two obvious layers, that was, the two layers of multi-layer forests, and the grade assignment was 0.5. In addition, the tree height differences between the other natural mixed forests were obvious, and the vertical layers were significant. The stands could present three distinct layers, and the grade assignments were all 1. Therefore, compared with the natural pure forests, the vertical stratification phenomenon of the natural mixed forests was more significant, and the vertical layers of the stands were more abundant. In terms of horizontal structure, in the natural mixed forests, the trees in stand-5 were evenly distributed, the distribution pattern of trees was unreasonable, and the grade assignment was 0. The trees in stand-4 and stand-22 were distributed in clusters, the distribution pattern of trees was quite reasonable, and the grade assignments were all 0.5. In addition, the trees in the other natural mixed forests were randomly distributed, the distribution pattern of trees was reasonable, and the grade assignments were all 1. However, the trees in the natural pure forests were evenly distributed, the distribution pattern of trees was unreasonable, and the grade assignments were all 0. Therefore, the horizontal structure of natural mixed forests was generally significantly better than that of natural pure forests. In terms of age structure, the natural pure forest stands were all the even-aged forests, with the normal diameter distribution and the grade assignments of 0. In the natural mixed forests, the stand-22 was an incomplete uneven-aged forest, with the multi-peak diameter distribution and the grade assignment of 0.5. In addition, the other natural mixed forests were uneven-aged forests, with the inverted “J” type diameter distribution and the grade assignments of 1. It could be seen that the age structure of natural mixed forests was generally significantly better than that of natural pure forests. In terms of tree species composition, the sr of natural mixed forest stand-21 was 0.534, the relative tree species richness of stand was general, and the grade assignment was 0.5. In addition, the sr of other natural mixed forests was > 0.67, the relative tree species richness of the stand was higher, and the grade assignments were all 1. In the natural pure forests, the sr of stand-1 and stand-2 was 1, the relative tree species richness of stands was higher, and the grade assignments were all 1, which were consistent with those of most natural mixed forests. However, the sr of natural pure forest stand-9, stand-10, and stand-11 was < 0.50, the relative tree species richness of stands was lower, and the grade assignments were all 0. Therefore, the tree species composition of most natural mixed forests was significantly better than that of natural pure forests. In terms of stand regeneration, the number of seedlings with seedling height H ≥ 50 cm in natural mixed forests was ≥ 500 plants/ha, especially the number of seedlings with seedling height H ≥ 50 cm in half of natural mixed forests was ≥ 2500 plants/ha, the regeneration level of these stands was excellent, and the grade assignments were all 1. In natural pure forests, although the number of seedlings with seedling height H ≥ 50 cm in stand-9, stand-10 and stand-11 was ≥ 500 plants/ha, there were no seedlings with seedling height H ≥ 50 cm in other natural pure forests, the regeneration level of these stands was very poor, and the grade assignments were all 0. It could be seen that the regeneration status of natural mixed forests was relatively better than that of natural pure forests. In terms of large-diameter tree, the proportion of relatively large trees in natural mixed forests was > 10%, the proportion of dominant trees in stands was higher, and the grade assignments were all 1. However, the proportion of relatively large trees in natural pure forests was < 5%, the proportion of dominant trees in stands was lower, and the grade assignments were all 0. It could be seen that the large-diameter trees of natural mixed forests were significantly better than those of natural pure forests. In summary, the quality grades of natural mixed forests were significantly better than those of natural pure forests, and the quality grades of some natural mixed forests were optimal.

In conclusion, according to the multi-indicator comprehensive evaluation method of stand quality, the quality grades of natural mixed forests were all ≥ grade II. Among them, the quality grades of some natural mixed forests were grade I, and the common feature of these stands was that a number of grade assignments of evaluation indicators were 1, the indicator grades were all at the optimal level, and then the level of FQ was very high, so the stand quality was very good. For example, in addition to the two evaluation contents of stand density and stand growth in natural mixed forest stand-3, the indicator grade assignments of other evaluation contents were all 1, the indicator grades were all at the optimal level, and the final stand quality grade was grade I. Compared with the natural mixed forests, the evaluation contents with indicator grade assignment of 1 were significantly reduced in the artificial mixed forests, and the evaluation contents with indicator grade assignment of 0.5 were significantly increased, the indicator grade level was generally medium, and then FQ was mostly at a medium level. Therefore, the stand quality grades of artificial mixed forests were mostly grade III, and the stand quality of these stands was generally medium. Compared with the mixed forests, the indicator grade assignments were generally ≤ 0.5 in the natural pure forests, among which the indicators with grade assignment of 0 were significantly more, the overall indicator grades were at the lower-middle level, and then FQ was at the lower-middle level. Therefore, the stand quality grades of natural pure forests were grade III or grade IV, and the stand quality of these stands was relatively poor. The indicator grade assignments were mostly 0 in the artificial pure forests, only individual indicator grade assignments were ≥ 0.5, the overall level of indicator grades was very poor, and then FQ was at a lower level, and the stand quality grades were all grade IV. Therefore, the stand quality of artificial pure forests was the worst among the four forest types.

Discussion

The multi-indicator comprehensive evaluation method of stand quality based on unit circle method proposed in this research was different from the evaluation methods focusing on the accumulation of advantages and disadvantages, such as comprehensive index method41,42 analytic hierarchy process16,23,43, target diagram44, and Spie diagram45. It not only reflected the cumulative effect of various evaluation indicators12, but also reflected the wholeness and equilibrium of the stand quality evaluation indicator system. Furthermore, there were many evaluation indicators in an excellent and comprehensive stand quality evaluation system. Based on the previous research on stand quality evaluation, actual investigation and the logical law of objective existence in nature, this research selected nine contents that are comprehensive, scientific and operable to characterize the main natural attributes of stands. By further assigning specific evaluation indicators to each content, a bran-new, more comprehensive and more reasonable stand quality evaluation system was formed. Among them, the evaluation content of large-diameter tree was added in this research, and the evaluation standard were given for this content, which was not proposed in previous studies. The research considered that large-diameter tree was very important in the evaluation of stand quality, because the large-diameter tree played a skeleton role in the stands. The indicators mentioned in this research adopt the latest research results, and they were given the scientific and concise measurement method, which not only ensured the scientificity and accuracy of the data measured by each indicator, but also enhanced the operability of the indicator measurement and the timeliness of data collection. In terms of vertical structure, The accuracy of the measurement methods was verified by pairwise comparison. It was found that the results obtained by the two measurement methods were consistent, indicating that the measurement methods were accurate and effective for the evaluation of vertical structure. In terms of tree species composition, Poole46 (1974) argued that the number or richness of species in a community was the only genuinely objective indicator to judge the species diversity of the community, that was, species richness was equivalent to species diversity to some extent. However, according to the research method of Gadow and Hui47, we could see that the number of tree species was gradually increasing with the increase of the area of the survey plot. Yang and Hui48 proposed to use the maximum number of tree species to measure the tree species richness of forest communities. This research solved the problem that the number of tree species in different plot areas was regarded as the richness of tree species in the current researches, Moreover, the results of this research also conformed to the general cognition and objective law that the species richness increased gradually with the climatic zone from the north (cold temperate region) to the south (tropical region). It could be seen that the number of tree species in different geographical locations increased or decreased step by step with the changes of climatic zones, and the tree species richness and the maximum number of tree species in each geographical location would also change accordingly48,49. For example, the number of tree species in the subtropical region was very rich, but the actual stand quality of stand-26 and stand-27 was poor. If the tree species richness was simply measured, the quality grades of the stands would be significantly increased, which were inconsistent with the actual stand quality and unfair to the evaluation results. In addition, the trees of stand-1 and stand-2 in the middle temperate region were excellent. If the researchers simply measured the tree species richness without taking into account the extreme site conditions of the local sandy land, it would also significantly reduce the quality grades of the stands, which were inconsistent with the actual stand quality and unfair to the evaluation results. Therefore, this research refered to the above theories and methods, and measured the contribution of tree species composition to stand quality by using the ratio of the average number of tree species in the stand structure unit50 to the average maximum number of tree species in the stand structure unit of the same climatic zone. In terms of stand growth, through the comparative analysis of typical stand data, it was found, when 50%, 70% or 80% were selected as the proportion of larger trees in the stands, and the corresponding potential density values of the stands were ≥ 0.60, 0.75 or 0.83, respectively, indicating that the stand grew well, that the number of well-growing stands in the selected research plots was consistent. However, in the multi-indicator comprehensive evaluation of the stand quality, the indicator value would directly affect the value of the stand quality grades and then affect the classification of the stand quality grades. By comparing the deviation rate between the maximum potential basal area and the standard basal area, as well as the potential density and the density when the proportion of larger trees in the stands was 50% to 80%, Liu et al. found that when the proportion of the selected larger trees was 70%, the overall deviation rate was the smallest, and the maximum potential basal area obtained was close to the standard basal area51. Therefore, in this research, the average basal areas of 70% of the larger trees in the actual stands were selected, and the potential densities of the corresponding stands were calculated. In terms of large-diameter tree, according to the “Technical specification for forest resources planning and design survey” (GB / T 26424 − 2010), trees with D ≥ 26 cm were usually divided into large-diameter trees. It was indisputable if it was only used for the division of tree diameter sizes in stands or the screening of large-diameter trees. However, in the multi-indicator comprehensive evaluation of stand quality, it was unreasonable to compare the tree sizes of stands of different types and different ages in different geographical locations only through this division standard. Therefore, this research used the proportion of relatively large trees in stands to characterize large-diameter trees. By comparing and analyzing the data of the typical stands, the 1.5 times of average breast diameter in the stand was finally adopted as the indicator value to determine the relatively large trees, and the trees that were greater than or equal to the indicator value were the relatively large trees. In addition, due to the complexity and diversity of evaluation indicators, there were both qualitative and quantitative indicators, and the values and units between the indicators vary greatly. Therefore, in this research, the measurement values obtained by each indicator were assigned, standardized and positively processed by using the assignment method, and transformed into the unified positive indicator evaluation values, so that the stand quality evaluation indicators were normalized, which laid the foundation for reasonable and effective comprehensive evaluation of stand quality.

Forest management is the foundation of sustainable forestry development and the most important content of forestry work. It is a general term for a series of activities such as scientific cultivation and management of existing stands aimed at improving forest yield, quality, and stability29,52. Comprehensive evaluation of stand quality is the premise and key to forest management decision-making. Only by constructing a scientific indicator system and selecting reasonable evaluation methods to assess the quality of actual stands can targeted stand management measures be formulated to achieve precise improvement of stand quality. This study referred to the unit circle π-value principle10 and combined the newly constructed stand quality comprehensive evaluation index (FQ) with the unit circle, enabling a holistic evaluation of stand quality. That is, it could more intuitively and vividly reflect the superiority or inferiority trend of actual stand quality and the level of each evaluation indicator. Furthermore, through the adoption of corresponding management measures to targetedly guide the design adjustment of management operations, it not only promoted the improvement of stand quality and ensured that forests develop in a healthier, more stable, and better direction but also effectively avoided losses caused by improper operation design, truly achieving precise optimization of stand quality.

Conclusions

This research proposed a bran-new evaluation method for stand quality. Firstly, this research selected nine evaluation contents from two aspects of stand structure and stand vitality, including vertical structure, horizontal structure, age structure, tree species composition, stand density, stand growth, stand regeneration, large-diameter tree and tree health, and gave specific evaluation indicators to each content, thus forming a bran-new stand quality evaluation system. On this basis, a bran-new stand quality comprehensive evaluation index (FQ) was constructed based on the unit circle method. The multi-indicator comprehensive evaluation method of stand quality proposed in this research could reasonably divide the stand quality grades. By adopting a multi-indicator comprehensive evaluation method of stand quality, the results of stand quality evaluation of typical forest types in China were consistent with the local perception. The results calculated by the index constructed in this research showed that the quality of natural mixed forest was the best, the quality of the artificial mixed forest was the second, the quality of the natural pure forest was the third, and the quality of the artificial pure forest was the worst. The results were in line with the objective reality and universal law of the actual stands, and could scientifically and intuitively express the general cognition of the actual stands. Therefore, the index constructed in this research was a good comprehensive measure index of stand quality, which could scientifically and fairly evaluate the quality of different forest types in different regions, and had a good guiding significance for the evaluation of stand quality.

Materials and methods

Research area and sample plot profile

In this research, a total of 27 sample plots were collected in 7 regions of China, representing different forest types located in different climatic zones or in the same climatic zone but different geographical regions, as shown in Table 2; Fig. 2. Among them, 2 sample plots of Pinus sylvestris var. mongolica natural pure forest in Honghuaerji, Inner Mongolia (No.1, 2); 6 sample plots of Broad-leaved Pinus koraiensis natural mixed forest in Jiaohe, Jilin (No.3–8); 3 sample plots of Quercus mongolica natural pure forest in Qingyuan, Liaoning (No.9–11); 4 sample plots of artificial forest in Xishan, Beijing, including 1 sample plot of Pinus bungeana artificial pure forest (No.12), 1 sample plot of Platycladus orientalis artificial pure forest (No.13), and 2 sample plots of coniferous broad leaved artificial mixed forest (No.14, 15); 8 sample plots in Xiaolongshan, Gansu, including 4 sample plots of Larix kaempferi artificial pure forest (No.16–19), 4 sample plots of Quercus aliena var. acuteserrata natural mixed forest (No.20–23); 2 sample plots of Cunninghamia lanceolata artificial mixed forest in Fenyi, Jiangxi (No.24, 25); 2 sample plots of Cunninghamia lanceolata artificial pure forest in Fengyangshan, Zhejiang (No.26, 27).

Table 2 The survey of sample plot.
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Fig. 2
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Geographical distribution of sample plots. The map was created using ArcGIS Pro 3.1. The official website of the software is https://www.esri.com/en-us/arcgis/products/arcgis-pro/overview.

Multi-indicator comprehensive evaluation method of stand quality

Selection and assignment of stand quality evaluation indicator

It is well known that stands usually vary in both density and growth. There are differences in height and thickness among the trees in the stands, as well as the differences between tree species, health status, growth stage, and growth ability. In addition, the distribution of trees in horizontal and vertical spaces shows certain distribution rules, which are not disorderly. These are people’s intuitive understanding of forests, as well as people’s perception of natural attributes such as forest structure and vitality10. In this research, nine evaluation contents were selected from the perspectives of stand structure and stand vitality to characterize the actual stand quality. The evaluation contents of stand structure included vertical structure, horizontal structure, age structure, tree species composition, and stand density. The evaluation contents of stand vitality included stand growth, stand regeneration, large-diameter tree, and tree health (Fig. 3). According to the different evaluation contents and the selection principles of stand quality evaluation indicators, and the corresponding scientific and reasonable evaluation indicators were selected. Due to the complexity and diversity of evaluation indicators, there were both qualitative and quantitative indicators, and there were significant differences in values and units between different indicators. Therefore, according to the biological significance of each evaluation indicator, the measurement values obtained by the selected evaluation indicators were assigned, standardized and forward processed, so that they are transformed into dimensionless values of [0, 1]. The specific assignment was shown in Table 3. The edge effect refers to a phenomenon in numerical calculations, experiments, or data analysis where deviations occur in the results of boundary regions due to incomplete boundary conditions, discontinuous data, or physical constraints. For the calculation of indicator values, to avoid such interference and considering the actual situation of the sample plots in this study (with a maximum side length of 100 m and a minimum of 20 m), buffer zones with a width equivalent to 5% of the side length were set on both sides of each edge of the sample plots. This width is an empirical value for balancing calculation accuracy and resource consumption, and it was determined by comprehensively referring to the commonly used edge buffer zone ratio in forest ecology, the scale and structural characteristics of the sample plots in this study, and operational convenience53,54.

Fig. 3
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Stand quality evaluation content.

Table 3 Evaluation indicator and assignment.
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Vertical structure: It could be expressed by the number of stand layers55. According to the stand vertical stratification standard of the International Union of Forests (IUFRO), the average tree height of the highest 50–100 trees per hectare was selected as the dominant height of the stand. Here, trees with tree height ≥ 2/3 dominant height were defined as the trees in the upper layer, trees with tree height between (1/3, 2/3) dominant height were defined as the trees in the middle layer, and trees with tree height ≤ 1/3 dominant height were defined as the trees in the lower layer56,57. The research used the following two methods to calculate the number of stand layers: (1) Stratification statistics by tree height. There should be a certain number of trees in each layer, and the proportion should be ≥ 10% to be counted as one layer. If the proportion of trees in each layer was ≥ 10%, it was considered that the number of stand layers in the stand was 3, indicating the multi-layer uneven-aged forest, and the assignment was 1. If the proportion of trees in only two layers was ≥ 10%, the number of stand layers was 2, and the assignment was 0.5. Furthermore, if the proportion of trees in one layer was ≥ 90%, which was expressed as the single-layer forest, and the assignment was 0. (2) Statistics by structural unit. In the structural unit composed of the reference tree and its nearest four adjacent trees, the number of the five trees that could be divided into layers according to tree height was counted, and the proportion of the number of stand layers in each structural unit was calculated as 1, 2 and 3 layers was counted, so as to estimate the number of stand layers in the whole stand. The number of stand layers was ≥ 2.1, indicating multi-layer, assigned 1; the number of stand layers was < 1.4, indicating single-layer, assigned 0; the number of stand layers was between [1.4, 2.1), indicating double-layer, assigned 0.5.

Horizontal structure: It could be expressed by tree point pattern58. The average angular scale of the stand could reflect the horizontal distribution pattern of the stand. In this research, when the distribution pattern of trees was random, the assignment was 1; when the distribution pattern of trees was clustered, the assignment was 0.5; when the distribution pattern of trees was regular, the assignment was 059.

Age structure: It is the age composition of the main trees in the stand, which can reflect the basic situation of whether the stand can achieve sustainable development, and can reveal the current situation and development trend of each age group of the stand tree population60,61 and provide scientific theoretical guidance for the management and development and utilization of the stands62,63,64. Because the age of trees was not easy to determine, the age structure was indirectly expressed by the diameter distribution. In this research, the ideal stand diameter distribution was inverse J-shape distribution, and the assignment was 1; when the distribution was multimodal distribution, the assignment was 0.5; when the distribution was the approximately normal distribution, the assignment was 055,65,66.

Tree species composition: It was expressed by relative tree species richness. The composition of stand tree species was affected by geographical and climatic factors. Therefore, this research used the ratio (sr, relative tree species richness) of the average number of tree species in the stand structure unit (s) to the average maximum number of tree species in the stand structure unit of the same climatic zone (the same longitude, latitude, and altitude) (smax) to measure the contribution of tree species composition to stand quality. In theory, the maximum number of tree species in the structural unit is equal to 5, that is, the reference tree is not the same as the four nearest adjacent trees, and the adjacent trees are also not the same. Affected by geographical climate and site conditions, the average maximum number of tree species in the stand structural units of different forest types in different geographical climate zones (different latitude-longitude and altitude) was different, such as smax = 5 in tropical region, smax = 4.5 in subtropical region, smax = 4.2 in warm temperate region, smax = 3.8 in middle temperate region, smax = 2.0 in cold temperate region, and smax = 1.0 in extreme site region. In this research, when sr was > 0.67, it indicated that the relative tree species richness was higher, with an assignment of 1; when sr was in [0.50, 0.67], it indicated that the relative tree species richness was general, with an assignment of 0.5; when sr was < 0.50, it indicated that the relative tree species richness was lower, with an assignment of 0.

Stand density: Stand crowding degree (K) was used to reflect stand density. Stand crowding degree was the ratio of the average distance (L) to the average crown width (CW) of the trees in the middle and upper layers of the stand. In this research, the stand crowding degree was in [0.9, 1.1], indicating that the stand density was moderate, and the assignment was 1; the stand crowding degree was in [0.7, 0.9), indicating that the stand density was crowded, and the assignment was 0.5; the stand crowding degree was in (1.1, 1.3], indicating that the stand density was sparse, and the assignment was 0.5; the stand crowding degree was > 1.3 or < 0.7, indicating that the stand density was too sparse or too crowded, and the assignment was 067.

Stand growth: It was expressed by the potential density of the stand, and the larger the better10. The potential density of the stand was calculated by \(\:{B}_{0}=\stackrel{-}{G}/{G}_{max}\). \(\:\stackrel{-}{G}\) was the basal area of the actual stand, and the value of Gmax was equal to the product of the average basal area of 70% of the larger trees in the actual stand and the number of existing trees in the actual stand. In this research, the potential density (B0) value of the stand was ≥ 0.75, indicating that the stand growth was good, and the value was assigned 1; the potential density value of the stand was < 0.75, indicating that the growth was general, and the potential density value of the stand was directly used as the assignment. In addition, according to the relevant literature, this research also selected the number of larger trees in the stand according to the proportion of 80%68 and 50%10, and calculated the potential density of the stand. Among them, when the number of larger trees in the stand was selected according to the proportion of 80%, the potential density value of the stand was ≥ 0.83, indicating that the stand was growing well, and the value was assigned 1; the potential density value of the stand was < 0.83, indicating that the growth was general, and the potential density value of the stand was directly used as the assignment. When the number of larger trees in the stand was selected according to the proportion of 50%, the potential density value of the stand was ≥ 0.60, indicating that the stand was growing well, and the value was assigned 1; the potential density value of the stand was < 0.60, indicating that the growth was general, and the potential density value of the stand was directly used as the assignment.

Stand regeneration: Seedlings are the main carrier of plant population regeneration and restoration69. The species and quantity of seedlings have a direct impact on the tree species composition, structure, and regeneration direction of the stand, and play a very important role in the dynamic development and stability of the stand. It is of great significance to study the seedling regeneration in depth to understand the dynamic development of the stand and vegetation restoration70,71,72,73. In this research, the standards in the “Technical specification for forest resources planning and design survey” (GB / T 26424 − 2010) were used to evaluate. The number of seedlings with seedling height H ≥ 50 cm was ≥ 2500 plants/ha, indicating that the seedling regeneration level was excellent, and the assignment was 1; the number of seedlings with seedling height H ≥ 50 cm was between [500, 2500), indicating that the seedling regeneration level was medium, and the assignment was 0.5; the number of seedlings with seedling height H ≥ 50 cm was < 500 plants/ha, indicating that the seedling regeneration level was poor, and the assignment was 0.

Large-diameter tree: It was expressed by the proportion of relatively large trees in the stand. In this research, the average diameter at breast height of 1.5 times in the stand was used as the indicator value to determine the relatively large tree, and the tree that was greater than or equal to the indicator value was the relatively large tree. When the proportion of relatively large trees was ≥ 10%, the assignment was 1; when the proportion of relatively large trees was between (5%, 10%), the assignment was 0.5; when the proportion of relatively large trees was ≤ 5%, the assignment was 0.

Tree health: In this research, the proportion of healthy trees was used to express tree health. The health status of the trees in the stand was mainly identified by the characteristics of the tree’s posture, such as insect pests, disease rot, and broken shoots. When the proportion of healthy trees in the stand was ≥ 90%, it meant that the stand was healthy, and the assignment was 1; when the proportion of healthy trees was between (70%, 90%), it meant that the stand was sub-healthy, and the assignment was 0.5; when the proportion of healthy trees was ≤ 70%, it meant that the stand was unhealthy, and the assignment was 068.

Multi-indicator comprehensive evaluation index of stand quality

Based on the unit circle method of stand status proposed by Hui et al.10, the multi-indicator comprehensive evaluation of stand quality was carried out. First, a circle with a radius of 1 was drawn, and scale lines were marked on its radius. Subsequently, the circle was evenly divided into m sectors by using the equal division method. Each sector represented m evaluation contents, such as vertical structure, horizontal structure, age structure, tree species composition, stand density, stand growth, stand regeneration, large-diameter tree, and tree health(Fig. 4). Finally, based on the evaluation value of the corresponding positive indicator of each evaluation content in the actual stand, this evaluation value was used as the radius to outline the area of each evaluation content in the corresponding sector. In this way, m evaluation contents formed m sectors of different sizes, which together constituted a closed graph reflecting the stand quality. Specifically, the cumulative value of these m sectors represented the quality status of the actual stand. Obviously, when the evaluation values of all evaluation contents were 1, the closed-loop area formed was the largest and was always equal to the area of the unit circle (π), which could be regarded as the expected value of the optimal stand quality. Therefore, by comparing this cumulative value with the circular area π corresponding to the optimal stand quality, the quality grade value of the stand to be evaluated was obtained. This value fell within the interval (0, 1], and a larger value indicated better stand quality. The formula is as follows:

Fig. 4
Fig. 4
Full size image

Unit circle of stand quality evaluation.The positive indicator evaluation value is between [0.00, 0.50], and the filling color of corresponding sector area is yellow. The positive indicator evaluation value is between (0.50, 1.00], and the filling color of corresponding sector area is green. The number below each unit circle is the serial number of the sample plot, and each figure is the unit circle of each stand quality evaluation according to the serial number.

$$\:FQ=\frac{\sum\:_{\text{k}=1}^{m}\frac{{\uppi\:}{R}_{\text{k}}^{2}}{m}}{{\uppi\:}{R}^{2}}=\frac{1}{m}{\sum\:}_{\text{k}=1}^{m}{R}_{\text{k}}^{2}$$

In the formula: FQ-Stand quality comprehensive evaluation index; m-The number of evaluation indicators; Rk-The k-th positive indicator evaluation value.

Stand quality grading standards

According to the above stand quality grade evaluation method, except for sparse forest and shrub forest, the stand was divided into five stand quality grades: grade I, indicating very good, FQ ≥ 0.80; grade II, indicating better, FQ = [0.60, 0.80); grade III, indicating general, FQ = [0.40, 0.60); grade IV, indicating poor, FQ= [0.20, 0.40); grade V, indicating very poor, FQ < 0.20.