Assessing Community Distribution Characteristics and Succession Stages on Mountainous Areas Hosting Coming Winter Olympics Games

Background


Introduction
Climate and human activities play a key role in the growth of vegetation, especially in mountainous areas (Parmesan and Yohe 2003;Li et al. 2017). One of the largest human events with more environmental repercussions is the Winter Olympic Games. May (1995) showed some pioneer results related to the 1992 Winter Olympics and the di culties to assess its potential direct adverse effects on the environment. This author emphasized on the assessment of secondary and longer-term impacts, which are di cult to be foreseen. Some common issues of these big events are related to oods and erosion, and the damage to young trees, natural ora and fauna due to skiing, which is not restricted to runs (Vanwynsberghe 2015).
Therefore, an appropriate interpretation of the relationship between alpine vegetation types and the environment with human activities cannot be fully understood without considering other factors such as soils (Rodrigo-Comino et al. 2018), hillslope morphologies (Saco et al. 2007) and water availability (Brown et al. 2005).
Holistic studies considering all above-mentioned factors must be one of the main tasks of vegetation ecology scholars. According to, environmental heterogeneity is not only considered as one of the most important factors to control the species richness gradient (Stein et al. 2014; Khanalizadeh et al. 2020) but also closely related to the micro-climatic conditions induced by topography and the distribution of plant species (Scherrer conservation area, which could achieve the regeneration of visual elements of plant zero-carbon landscapes, spatial emotions and ecological environments (Li et al. 2018).
Therefore, the main aim of this paper is to assess the difference between the impact of plantation and natural secondary forest on the ecosystem before the realization of the Winter Olympic Games. This would provide theoretical support for vegetation restoration and reconstruction in this large area considering the distribution range and characteristics of the plantations before any human disturbance. In this research, the plant communities of the Yin Mountains in North China were studied considering; i) the spatial distribution of Yin Mountains and vegetation communities in the region as a function of a set of measurable environmental variables; ii) the two-way indicator species analysis to assess the distribution characteristics and succession stages of communities in the whole ecosystem including the plantations were used; iii) the direct ordination method to observe the relationships between vegetation communities and measurable environmental variables (e.g. topography). Furthermore, as the host of the 2022 Winter Olympic Games, Chongli needs to have a further understanding of the oristic composition and ecological distribution of the plant community to avoid any uncontrolled impact (May 1995

Study area
The study area (864. 79  The Chongli mountain area is widely distributed occupying 80% of the county territory, and the forest coverage rate reaches 52.4%. The climate belongs to the East Asian continental monsoon climate and moderate temperate sub-arid zone. The annual average temperature is 3.7℃. The average temperature is in summer is 19℃ and in winter is -12 ℃ ( Song et al. 2018). The snowfall is early and the snow is thick, and the with a long snow-storing period. The annual precipitation averages 483. 3 mm (Song et al. 2018).
Therefore, due to its climatic and topographical conditions, the ecosystem of the study area includes mottled meadow ecosystems, deciduous broad-leaved and coniferous forests, alpine shrub and meadow ecosystems.
In the mountainous area, forest soil types are mainly cinnamon soil and brown soil, and birch and larch trees, Spiraea and Rosaceae shrubs and herbaceous are the main vegetation species (Song et al. 2018).

Field sampling
A total of 91 Sample points considering different aspects following the strategy described by Lindsey (1956) were collected: on the sunny, shady, semi-sunny and semi-shady hillslopes. They were collected from 1220 to 2040 m a.s.l. (Table 1). Mainly distributed in the middle and high altitude areas, the footslope position is mainly composed by shrubs and herbs, and the backslopes and shoulders by trees and herbs.
The number of sampling points was determined according to the altitude range of the hillslope aspect, and distribution along the altitude contour line with a gradient of 50 m. The rst eld survey season was between August and September 2018, the second one from July to September 2019. It is important to highlight that the surveyed sampling points in 2018 were revisited during the second survey.
The optimum size selected to survey each particular vegetation type was estimated using the concepts of minimal area and species-area curves (Kent 2011). We selected 20 mx20 m sampling points dominated by trees and 10x10 m by shrubs and herbs. The specie coverage (%) is assessed as the vertical projection of all above-ground parts of a single species onto the ground, expressed as a percentage of the unit area of the species (Greig-Smith 1983). Additional recorded environmental factors include the location (longitude, latitude), altitude, aspect, inclination, and forest canopy. Moreover, ve soil surface samples were randomly taken from each plot and transported to the laboratory. The soil organic matter content was measured by the potassium dichromate method (Walkley and Black 1934). The soil bulk density and porosity were measured by the core method (Margesin and Schinner 2005). Soil pH was measured in a suspension using an electronic pH-meter. The nomenclature and classi cations of all plant species in this article are based on the handbook Flora of China edited by Lin (1991).

Data analysis
Two-way indicator species analysis (TWINSPAN), a binary indicator species analysis similar to the multi-level dichotomy method is used to study ecological factors and species (Kooch et al. 2008). The advantage of this method is that the species classi cation can be completed at the same time as the sample plot classi cation.
The TWINSPAN 2.3. for Windows (Hill and Hill 1979;Peeters and Gylstra 1997) was used to classify the vegetation data. The analysis using this method takes into account the following considerations: the maximum number of division levels was 3, the minimum group size for the division was 5 and the maximum number of indicators per division was 5.

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The indicator species analysis (ISA) (Dufrêne and Legendre 1997), and the Monte Carlo methods were used to test the signi cance of the indicator value (IV) for each specie ). The IV used by ISA allows the combination of the relative abundance (RA) and relative frequency (RF) information of the species in each group. The values of IV ranges from 0 (no indicator) to 100 (perfect indicator) (McCune and Mefford 1999).
After calculating the ISA, the market basket analysis (MBA) was carried out for all species about each community. The working principle of an MBA is to mine a data set, which is composed of a group of projects. In this case, it is the species and their respective communities. These populations correspond to the species found at each sampling point, and all populations can be analyzed to nd a set of species frequently placed together in each community. The Apriori algorithm (Agrawal and Srikant 1994) of market basket analysis uses to be applied to analyze the existence of species combination in each habitat, and the results of the association rules of species A and B in community X were generated. When α = 0. 05, Fisher's exact test and Holm Bonferroni's correction are used to test the signi cance. In addition to indicating which species appear in which community, these rules also have three main parameters. First, the support (S) is the proportion of the whole data set, showing the probability of the species combination occurring in the community. Second, the con dence (C) is the value that allows indicating the probability of nding a habitat if a given species combination is found. Finally, the third one is the lift (L), which is a method to measure the correlation between the species group and the community (Leote et al. 2020). Because of ISA is only used for the species and their characteristics among the screening community, it does not have the relevant information between the characteristic species and the species and the community. As a result, the MBA is used to supplement ISA. Therefore, two species meeting MBA threshold (S = 0. 25, C = 0. 8) and IV maximum were selected in each community to name the whole community.
ISA analysis was performed using PC-ORD 5.0 (McCune and Mefford 1999). For the market basket analysis (MBA), the data were analysed using the R software v.3.6. 2 (R.C.Team 2018), and the package arules (Hahsler and Hornik 2007) also demonstrated how to use data sets to combine clustering and association rule mining.
Vegan package (Oksanen 2013) in R software v.3.6. 2 (R.C.Team 2018) was used to perform detrended correspondence analysis (DCA) and canonical correspondence analysis (CCA) of species and environmental data (Ter Braak 1986). Then, sorting is used to analyze the relationship between species composition and environmental factors. The prior DCA shows that the longest gradient length is 4.41 (Table 4), indicating that there is greater heterogeneity in the species composition data. Therefore, the CCA could be considered as a suitable method to determine the relationship between environmental variables and community distribution by correlating community differences with environmental variables (Lepš and Šmilauer 2003). Rarity is eliminated by using coverage of less than 5% or a frequency of less than 5% species (Zhang et al. 2001). The remaining 48 common species were used in both classi cation and ordination analyses, and to identify potential differences in the contribution of environmental variables among sampling points. The CCA axis was statistically evaluated by the Monte Carlo displacement test (P = 0. 001).
Before performing the CCA analysis, a logarithmic conversion was performed based on the above-mentioned environmental variables that do not obey normal distribution such as altitude and inclination. According to the current inclination degree, the hillslope position of the experimental plot was divided into three different types by the method of value assignment, 1 for the shoulder, 2 for the backslope, and 3 for footslope position (Shao et al. 2012). For the aspect, we introduced two variables: northness and eastness. Northness will take values close to 1 if the aspect is generally northward and close to -1 if the aspect is southward, or close to 0 if the aspect is either east or west (Vogiatzakis et al. 2003).

Community classi cation
Based on the ora composition of the study area, the TWINSPAN method divided 91 sampling points into eight groups, and the classi cation stopped at the third level (Fig. 3). Each group contained a su cient number and variety of samples to make different vegetation communities considering their characteristics.
According to the analysis results of ISA and MBA, the original eight TWINSPAN groups were reduced to six community types. In ISA, the characteristic species (Pteridium aquilinum (Linn.) Kuhn var. latiusculum (Desv.)Underw.ex Heller and Juncus effusus Linn.) of groups 1 and 2 occupy the most important position in the IV ranking within the group, except for similar geographical coordinates and topographic factors. In the MBA, the support and con dence of Pteridium aquilinum (Linn.) Kuhn var. latiusculum (Desv.)Underw.ex Heller and Juncus effusus Linn. are greater than 0.5 and 0.9 respectively, so groups 1 and 2 were amalgamated. Similarly, groups 7 and 8 were assigned to the same group (i. e. Larix-Carex Community type). Information about indicator species and environmental variables for the six community types are included in Tables 2 and 3, respectively.

Vegetation grouping
Group 1-Group 2 (Pteridium-Juncus community type) includes a community with 27 species, mainly herbs, with a small number of shrubs. The characteristic species belonging to this community are Pteridium aquilinum (Linn.) Kuhn var. latiusculum (Desv.)Underw.ex Heller, Juncus effusus Linn., ium linearifolium Turcz., etc. It is mainly distributed on the sunny hillslopes at high and middle altitudes, with steep slopes between 20° and 40°. The content of organic matter in soil was (9.06 ± 1.47%), which is second to Betula-Rosa community type. 12 sampling points (mainly below 1800 m) were affected by human activities such as Olympic venues, track and road construction, and the human activities decreased with the altitude. Group 4 (Spiraea-Artemisia community type) contains 34 sampling points, which are widely distributed on shady and sunny hillslopes between 1290 and 1901 m a.s.l., and when they are distributed on shady hillslopes, they use to occupy the footslopes. Their characteristic species are Artemisia carvifolia Buch.-Ham. ex Roxb., Spiraea fritschiana Schneid., Polygonum divaricatum Linn. and Scutellaria baicalensis Georgi, which are conditioned by warm and humid environments and well-developed soil. The inclination ranges from 7 to 46°. The soil color is slightly darker than that of the Pteridium-Juncus and Armenia-Poa communities. Soils are loamy, and the content of organic matter is in the middle of all community types (6.77 ± 2.45%). The soil and vegetation of this community could be classi ed as an intermediary type between the shrub grass and the arbor communities (transitional). 23 points (concentrated below 1700 m) were disturbed by human activities such as road construction and human settlements (mainly abandoned farmland).
Group 5 (Betula-Potentilla community type). This community contains only 7 sampling points, but they are all distributed on the semi-sunny or semi-shady hillslopes with altitudes up to1980 m. Its characteristic species are Betula platyphylla Suk., Epilobium angustifolium Linn., Potentilla fruticosa Linn. and, Phaeosperma and Elymus dahuricus Turcz.. It is relevant to highlight that Betula platyphylla Suk. is a pioneer tree species, and gradually was replaced by other tree species after planting. The soil is loamy, and the pH is neutral. The community is located at a high altitude in this area, which is not affected by human activities and other factors.
Group 6 (Betula-Rosa community type) has 16 sampling points. As in the Betula-Potentilla community, the pioneer and main tree species are the Betula platyphylla Suk., but the difference is that most of the sampling points are distributed on shady hillslopes, the inclinations are about 25°, and the altitude range from 1423 to 1950 m a.s.l. In addition to Betula platyphylla Suk., its characteristic species include Rosa xanthina Lindl. and Corylus mandshurica Maxim. The soils are similar to the Betula-Potentilla community, they are loamy. However, the soil organic matter content is the highest among all community types (9.74 ± 2.1%), and the soil texture is loose and neutral. Due to the in uence of enclosure measures, the in uence of human activities is not obvious. Only some afforestation activities were found around the area below 1600 m altitude (5 sampling points), such as road traces left by human transportation and trampling.   Table 4). Therefore, TWINSPAN was used to organize and classify vegetation and sampling points, because the rst step of the TWINSPAN method is to perform DCA (or CA) ordination. CCA is more bene cial to the ecological sense, and CCA can re ect the similarity of species composition and environmental factors at the same time, and even re ect the correlation between environmental factors and sampling points from the side.
Therefore, we used CCA to explain the relationship between environmental factors and various species. Species with high positive scores on the rst axis are Hemistepta lyrata (Bunge) Bunge, Pogonatherum crinitum (Thunb.) Kunth, Conyza canadensis (Linn.) Cronq., Sophora avescens Alt., Corylus mandshurica Maxim., Armeniaca sibirica (Linn.) Lam., and Galium linearifolium Turcz. Some of these species, such as Galium linearifolium Turcz., Hemistepta lyrata (Bunge) Bunge, and Pogonatherum crinitum (Thunb.) Kunth is the main species in the footslopes, widely distributed on the sunny hillslopes, while others such as Conyza canadensis (Linn.) Cronq. and Armeniaca sibirica (Linn.) Lam., are usually associated with back-and footslope positions´ shrubland. Species with low scores on the rst axis include Serratula centauroides Linn., Betula platyphylla Suk., Geum aleppicum Jacq., Polygonum divaricatum Linn., Vicia sepium Linn. unijuga A. Br., Kochia scoparia (Linn.) Schrad. and Larix gmelinii (Ruprecht) Kuzeneva. Among them, Betula platyphylla Suk. and Larix gmelinii (Ruprecht) Kuzeneva are the main tree species on the shady and semi-shady hillslopes in the area, and most of them are pure forests, if on the same hillside, Betula platyphylla Suk. is generally distributed at the higher altitudes than Larix gmelinii (Ruprecht) Kuzeneva. While other species such as Geum aleppicum Jacq., Vicia sepium Linn. unijuga A. Br. and Kochia scoparia (Linn.) Schrad. are undergrowth vegetation. These species ranked low on the rst axis are widely distributed on the shady or semi-shady hillslope, with thick humus layers, shoulder position and loose soil, the soil porosity is above 66.7%, and the soil organic matter content is above 7.6%, which are signi cantly higher than the average values of 60.6% (soil porosity) and 7.2% (soil organic matter content) in all sampling points.
In the middle of the rst axis, most species are related to shrubland or usually distributed in standing forest.

Regional distribution characteristics of species community
In order to differentiate the community types obtained by the TWINSPAN method and compare the classi cation and ordination results among them, the nal six community types were superimposed on the CCA sample ordination, and the nal results are shown in Fig. 5.
As mentioned in Table 5, there are four main factors related to axis 1. The positive correlation includes soil bulk density (r = 0.63, p < 0.05) and hillslope position (r = 0.46, p < 0.05). Negative correlations include aspect

Zonal characteristics of six vegetation communities
The area in this study belongs to a typical warm temperate deciduous broad-leaved forest. The geographical composition of the ora shows an obvious transition pattern. In addition to the European Siberian species composition, it can also the ora of the Black Sea and Central Asian steppe ora (Committee 1995 , and their ecological adaptability could be considered extremely strong. In particular, Betula platyphylla Suk. has obvious distribution characteristics in this area, as the most common warm temperate pioneer tree species in the middle and high altitude regions of the north. Betula platyphylla Suk. is only distributed at an altitude higher than 1500 m a.s.l. in this area. This could be because of its heliophilous and hydrophilous characteristics. Most of them are on the shoulder of the shady hillslope, and a small amount of them is distributed on the backslope. The soil moisture is signi cantly higher than that of the shrub grassland on the sunny hillslope, but it is signi cantly lower than that of the Larix gmelinii (Ruprecht) Kuzeneva plantation or the shrub grassland under the secondary forest of Betula platyphylla Suk. Due to the aspect factors and almost no human disturbance, the percentage of soil organic matter content is signi cantly higher than other forests or shrub grasslands, and it increases with the elevation. Therefore, the main limiting factor of Betula platyphylla Suk. distribution in this area is the mountain environment, including altitude, illumination, moisture content and soil organic matter content (Peterson 1998;Cumming 2002). One representative example is the research conducted by (Xu et al. 2015) in China, under humid alpine areas.
These authors con rmed changes in leaf morphology, water viscosity and carboxylation e ciency with temperature, which, are subsequently affected by the altitude and aspect.
Among the six communities in TWINSPAN classi cation results, Betula platyphylla Suk. dominated communities accounted for two of them, which were Betula-Potentilla community and Betula-Rosa community respectively. The difference between the two communities was mainly manifested as undergrowth. The undergrowth of Betula-Potentilla community was subalpine shrubs and herbs dominated by Epilobium angustifolium Linn., Potentilla fruticosa Linn., Elymus dahuricus Turcz., and other obvious pioneer species (Lin 1991). These pioneer species need not only a certain amount of light, but also suitable soil moisture, and also have obvious strong diffusion ability in a certain altitude range (Turrill 1953).
Therefore, Betula-Potentilla community is located in a semi-shady slope with an altitude of more than 1800 m (It should be emphasized here that a few sampling points of Betula-Potentilla community are mixed forests of Betula platyphylla Suk. and Larix gmelinii (Ruprecht) Kuzeneva, which follow a rule that the proportion of Betula platyphylla Suk. is higher and higher with the increase of altitude, while that of Larix gmelinii (Ruprecht) Kuzeneva is the opposite). The undergrowth vegetation in Betula-Rosa community is composed of shrubs and herbs such as Rosa xanthina Lindl. and Corylus mandshurica Maxim. and other shade-resistant transitional vegetation in the back-and footslope positions. Furthermore, in addition to the pioneer or transitional species that are unique to Betula-Potentilla community or Betula-Rosa community, there are also a signi cant number of overlapping species in the two communities, such as Phaenosperma globosa Munro ex Benth., Carex doniana Spreng. and some other herbaceous plants, they have a wide niche and can survive in complex and diverse environments (Dragon and Barrington 2009). Geographically, the community is widely distributed on altitude gradients (1400-2000 m), most of them appear on shady hillslopes, and there are also very few sampling points on semi-shady hillslopes, which are only distributed on the shoulder or in the backslopes. In summary, it can be seen that the undergrowth vegetation of Betula-Rosa community has partially or completely completed the conversion from pioneer species to transitional species. However, Betula-Potentilla community located in the high altitude area is still occupied by pioneer species.
Larix gmelinii (Ruprecht) Kuzeneva forest is the largest and most widely distributed plantation tree species in the region. Since 1979, the stand management and vegetation succession for 40 years up to the investigation date, as well as the closure management and protection from human interference have also lasted for more than 20 years (Committee 1995). The Larix gmelinii (Ruprecht) Kuzeneva community has developed into a near-natural state. Due to the high requirements of Larix gmelinii (Ruprecht) Kuzeneva on soil conditions, it not only needs a certain amount of soil water, but also needs good drainage, and is born in the deep and fertile soil layer (Leng et al. 2008). Therefore, after 20 years of natural succession, the Larix gmelinii (Ruprecht) Kuzeneva forest in Larix-Carex community has developed to appear only in the backslope of the shady hillslope, it is close to and under the Betula platyphylla Suk. forest. The reason is that the natural secondary forest (Betula platyphylla Suk.) in this area has been developing for a long time, the biodiversity is increasing, and the organic matter content and other nutrients in the soil are accumulating, which provide su cient nutrients for the natural growth of Larix gmelinii (Ruprecht) Kuzeneva forest. From Table 3, it can be noted that the organic matter content of Betula-Rosa community and Larix-Carex community, especially the community dominated by Betula platyphylla Suk., is signi cantly higher than that of other forests and shrub grassland. As we mentioned above, the growth of Larix gmelinii (Ruprecht) Kuzeneva needs wet soil with good drainage performance. However, in the mountainous area where the rainfall is concentrated in time and space, the position of footslope is easy to have poor drainage, high soil humidity, even waterlogging disaster, which affects the growth and development of deep root vegetation (Kastanek 1988;Berry et al. 2016).
Therefore, the natural development of Larix gmelinii (Ruprecht) Kuzeneva forest in the backslope is promoted by the smooth drainage, appropriate humidity and nutrients, while the footslope position is occupied more by shrub grassland. Furthermore, due to its distribution characteristics on the hillslope, the sunlight is not as ample as that of shoulder positions. The undergrowth vegetation of Larix gmelinii (Ruprecht) Kuzeneva is dominated by herbaceous vegetation such as Carex doniana Spreng., Brachypodium sylvaticum (Huds.) Beauv., Saussurea japonica (Thunb.) DC. and Vicia sepium Linn. unijuga A. Br. Moreover, the shrub and herb coverage was signi cantly lower than Betula platyphylla Suk. community.
As with the sunny hillslopes in most northern mountainous areas of China, except for a small area of arti cially planted Pinus tabuliformis Carr. forest in some areas (due to serious human interference), most areas are natural shrubs or grasslands (Jintun et al. 2013;Wu et al. 2018), but the regional and soil texture make the vegetation composition signi cantly different. In the fooslope position of the shady hillslope in this area, there is also a distribution of shrub grassland (see Table 1 and Table 3). Therefore, shrub grassland was divided into three communities according to TWINSPAN vegetation classi cation. We found Armenia-Poa community in the low altitude area (1220-1380 m), with obvious inclination difference (5-45°), poor soil with more gravel, rare species composition and more bare land, among which Poa annua Linn., Caragana acanthophylla Kom., Armeniaca sibirica (Linn.) Lam. and other barren tolerant species are dominant. Because the distribution of this community is low in elevation and mostly in the footslope position, compared to other communities, the bad ecological environment is severely disturbed by construction activities such as largescale events. (Gabarrón-Galeote et al. 2013). In addition, Pteridium-Juncus community is an alpine meadow community with Gallium, Sanguisorba o cinalis Linn. and Pteridium aquilinum (Linn.) Kuhn var. latiusculum (Desv.)Underw.ex Heller as the main species were found in the middle and high altitude areas (1520-2040 m), and a small number of cold-resistant alpine shrubs such as Potentilla fruticosa Lin. and Lespedeza bicolor Turcz. appeared in some sampling points, and the content of soil organic matter and biodiversity increased with altitude. The community of Spiraea-Artemisia community is the most widely distributed and numerous shrub herbage sample plot in this area, and there is no special distribution rule from the data, but from the analysis results of TWINSPAN, Artemisia carvifolia Buch.-Ham. ex Roxb. and Spiraea fritschiana Schneid. are the characteristic species of this community. From the results of indicator speci cations analysis, in addition to these two species, Polygonum divaricatum Linn. and Scutellaria baicalensis Georgi are also regarded as characteristic species of the community, but these species are all without major characteristics, that is, they can thrive in fertile soil and survive in poor soil (Lin 1991). In particular, Artemisia carvifolia Buch.-Ham. ex Roxb. can be seen from the DCA analysis (Fig. 4, above) that it is closest to the center of the gure, which shows that Artemisia carvifolia Buch.-Ham. ex Roxb. exists in most of the investigated sampling points, including some woodlands, but only in quantity difference. Therefore, logically speaking, Spiraea-Artemisia community is more like the remaining community of these grouping and classi cation methods, which has loose requirements for altitude, light, water and nutrients. Slope position 0.46* 0.06 *P < 0. 05, **P < 0. 01, ***P < 0. 001 Table 6 Correlation among six environmental variables in the study area. Although there is a certain degree of overlap in the ordination space among different groups, CCA con rmed the community types from TWINSPAN classi cation. CCA analysis of this area shows that the most signi cant correlation with the rst axis of CCA is the slope direction (r = -0. 79, P < 0. 01), soil porosity (r= -0.73, P < 0.05) and soil bulk density (r = 0.63, P < 0.05) ( Table 5). The correlation between environmental variables (Table 6) shows that soil porosity is positively correlated with aspect (r = 0.43, P < 0.01), and negatively correlated with soil bulk density (r=-0.62, P < 0.01). Therefore, the rst axis of CCA is closely related to the aspect and soil porosity, and aspect directly affects the evaporation and conservation of moisture on the slope (Miller and Poole 1983), and the soil moisture can be controlled by the vegetation type on the soil surface (Moustafa and Zaghloul 1996). Therefore, the rst axis of CCA represents the moisture gradient.

Limiting factors of six communities
The second axis of CCA is closely related to the altitude and the percentage of organic matter content, and the positive correlation between the altitude and the percentage of organic matter content is signi cant (r = 0. 507, P < 0.01). This is because the altitude affects the regional average temperature and precipitation in the mountain area (Dai and Huang 2006), promotes the accumulation of organic matter. In addition, the high altitude area is rarely visited, which greatly reduced the impact of human interference. Under various factors, the soil organic matter increases with elevation. Although there is a certain correlation between soil porosity and the second axis, it fails to pass the signi cant correlation test with altitude or organic matter content, so the second axis represents the altitude gradient.
To  (1993)and (Vogiatzakis et al. 2003). CCA is an interpretative technology, which aims to separate subsets of environmental factors, to explain relevant gradients in several dimensions. Therefore, because it is a constrained ordination technology when additional environmental variables are used, the interpretable variables will increase.

Vegetation dynamics
It is generally believed that the mixed forest is superior to the single stand in terms of productivity, ecological function and stability (Xu et al. 2020;Zhou et al. 2020). In boreal forests, Shanin et al. (2014) showed that the tree species composition in the succession process of different stands depends on the site fertility and the initial proportion of tree species, and in the Betula-Pinus mixed forests, the proportion of Pinus trees increased in the poorer soils and decreased in the fertile ones. Taking into account the forest history in northern China, some scholars infer that the extension of Betula forests will increase but not the Pinus ones in the future scenarios (Wang et al. 2017). However, in the Chongli area, the composition of the two main tree species varies with the altitude. This could be mainly affected by the initial proportion of tree species and soil fertility at the initial stage of afforestation. As shown in Table 3, the content of organic matter closely related to soil nutrients reaches the highest value (9.7 ± 2.1%) below 1700 m, which greatly increases the survival rate of arti cial afforestation. In addition, the current afforestation from low areas to the plateau and the principle of . This is consistent with the growth status of aboveground vegetation of Betula-Rosa community (the prediction of forest age by DBH and tree height) and soil nutrient status (mainly refers to the content of soil organic matter). There is an obvious transition of species such as Rosa xanthina Lindl. and Corylus mandshurica Maxim. and other shaderesistant transitional vegetation. Therefore, Betula-Rosa community prepared for the next succession stage under the coexistence of external pressure and internal driving force.
The growth potential of speci c community vegetation is mainly limited by climate and other related environmental factors (Kucsicsa and Bălteanu 2020). However, in recent years, with the enhancement of human activities and land-use intensity, natural regeneration and soil properties are prevented (Stöhr 2007).
The present upper forest limit is less than the potential limit (Holtmeier and Broll 2007). In the Chongli mountain area, the growth potential of Armenia-Poa community, which is dominated by low shrubs and herbs, is far from ful lling its growth potential below 1500 m altitude. It is not only affected by land use and site conditions, but also by serious human disturbance. Therefore, barren tolerant herbaceous plants are dominant in the Armenia-Poa community, and a small amount of Armeniaca sibirica (Linn.) Lam. grows in some areas. Here, we mainly discuss the alpine meadow community with Pteridium-Juncus community type. We nd that the transition species such as Pteridium aquilinum To sum up, the succession law of Betula-Rosa community and Pteridium-Juncus community in high altitude area is earlier than that in low altitude area. We do not rule out that the in uence of human factors is greater than that of climatic factors and biological factors in low altitude areas. The initial stage of arti cial afforestation has made a great contribution to the vegetation restoration and biodiversity restoration in this area. However, the in uence of arti cial afforestation may hinder the succession speed and direction of original secondary communities in a certain altitude range, which is especially obvious in the mixed forest belt with medium altitude gradient. It would be necessary to repeat this assessment after the WOG to see if big events can modify this trend or not.

Uncertainty of the relationship between environment and vegetation
In this paper, in addition to the in uence of topography and geomorphology on the distribution of ecosystem vegetation community, environmental variables (including rainfall, surface temperature, soil moisture) under the in uence of climate should not be underestimated (Archibold 1995;Giaccone et al. 2019). The aspect is related to microclimate (aspect is indirectly related to solar radiation, solar radiation affects temperature and humidity), but there is no reliable precipitation and surface temperature data in the Chongli mountain area, so it is excluded that other climate data can be included in the ordination. However, further research on the in uence of climate factors in the region will be carried out in the future.
In addition, although the inclination is measured and analyzed as a topographic factor, it has a low correlation with ordination axes. On the other hand, due to the time difference of weather, the soil moisture content of each plot cannot be quanti ed at the same time. Therefore, the two environmental factors are not considered in the model generation. Grazing also has a certain impact on the plant diversity and richness in mountain areas, but this area bene ts from the policy of returning farmland to forest and grazing to grass

Conclusions And Final Remarks
This research considers the oristic composition of vegetation in Chongli Country, the core area of the 2022 Winter Olympics, which is affected by the change of topography and land uses for thousands of years. In the current stage, shrubs and herbaceous vegetation species in mid-to-high altitude areas generally show the process of transformation from a pioneer community to transitional community in the competition. On the other hand, Larix gmelinii (Ruprecht) Kuzeneva plantations and Betula platyphylla Suk. natural forests compete and integrate on the same slope, trending to form mixed forests. The natural forests above 1700 m altitude migrate downhill, while the plantations at 1400-1700 m altitude migrate uphill. However, in the low altitude area (below 1400 m) were considered as a vulnerable environmental environment, the plant diversity and vegetation coverage in this area exhibited signi cantly lower than those in other areas (Fig. 6), and the poor soil water conservation capacity is not enough to form a resistant vegetation community in the state of natural restoration. During the Winter Olympic Games, human disturbances (including venues, tracks and roads construction) will be further intensi ed. The resistance of vegetation restoration will not be limited to the low altitude areas below 1400 meters, and the vegetation communities in the middle and high altitude areas (above 1400 m) will be affected as well. How to strengthen the stress resistance of vegetation community, and how to build and restore the vegetation community quickly after the major event is the problems that we need to solve urgently.
In most of the vegetation studies in the Yin Mountains, especially in Chongli area, the relationship between topography variables and vegetation is mostly described qualitatively, lacking the basis of quantitative research. In this study, multivariate analysis techniques were used to determine the distribution patterns of the communities, and the results are associated with the measured environmental variables. Some important environmental factors that can be measured and plotted are determined by providing vegetation mapping units. Therefore, these data will be used as the rst step to predict the distribution of vegetation communities in the Yin Mountains, and this methodology can also be used to map other mountain vegetation communities in Yin Mountains.
The managers of this area (especially Chongli City, the core area of the Winter Olympic Games) need to have a detailed understanding of the oristic composition and ecological distribution of the vegetation communities, which not only provides the basis for vegetation monitoring and mapping, but also helps to assess the impact of human disturbance (construction of venues, tracks and roads, etc.) on the vegetation communities, and provides instructive opinions for promoting the ecological restoration and construction after the Winter Olympic Games at 2022.
Annex I Names and abbreviations of the species