Characteristics of Grassland Species Diversity and Soil Physicochemical Properties with Elevation Gradient in Burzin Forest Area

Abstract

In order to explore the changes and interrelationships of grassland plant community species diversity and soil physicochemical properties with elevation gradient, this study takes the grassland in the Burzin forest area of Xinjiang as the research object and analyzes the responses of grassland species diversity, aboveground biomass, and soil physicochemical properties to the changes of elevation gradient within the altitude range of 1000~2200 m in this area. The results of the study show that: (1) The number of species and aboveground biomass reached the highest levels at elevation gradient III and showed a tendency of increasing and then decreasing with elevation. The Margalef and Shannon–Wiener indices were the largest at elevation III, while the Simpson and Alatalo indices were the largest at elevation I. (2) With the change of elevation, the available nitrogen (AN), available phosphorus (AP), soil electric conductivity (SEC), and soil pH showed a trend of increasing and then decreasing, while soil temperature decreased with elevation. Available potassium and soil water content reached their maximum values at elevation I and elevation IV, respectively. (3) The soil conductivity and diversity index were negatively correlated in elevation gradients I to III. In elevation gradient I~III, soil conductivity was positively correlated with the diversity index and aboveground biomass. Available nitrogen had a significant effect on plant diversity and biomass in elevation gradients IV to VI. (4) Aboveground biomass was significantly positively correlated with the Simpson’s index, while the relationship with the Shannon–Wiener index was less significant, and Margalef’s and Alatalo’s indices were not significant. Soil conductivity and pH significantly affected the Margalef and Simpson indices. Available nitrogen was closely related to the aboveground biomass and Margalef and Alatalo indices. Soil moisture content significantly affected Simpson’s index and the aboveground biomass. This study provides a solid theoretical foundation for the conservation and management of grassland plant community ecosystems along the elevation gradient, and has important reference value for study of the impact of environmental change on species diversity and biodiversity conservation.

1. Introduction

Differences in the structure and type of grassland plant communities generally result from plant composition and species diversity, and different geographic locations will also have different impacts on them, while plant community diversity can maintain ecosystem stability and can lay a certain foundation for ecosystem services [1,2]. In addition, there is a close relationship between grassland plant diversity and the physical and chemical properties of soil [3]. Different physical and chemical properties of soil can directly affect the growth and distribution of plants, but also indirectly affect the diversity of plant community species, and different geographic locations will also have an impact on plant diversity and the physical and chemical properties of soil. For example, with the change in elevation gradient, the distribution and diversity of grassland plants are affected by changes in the water and heat conditions. At the same time, this will also have a certain impact on the physical and chemical properties of soil [4,5,6]. Changes in the climate and environmental conditions caused by the altitude gradient result in different geographical environments at different altitudes, which will have a certain impact on plant diversity and soil physicochemical properties [7]. Therefore, in the study of plant species diversity, the change of elevation gradient plays an extremely important role. By studying the changes of the species diversity of different plant communities on different elevation gradients, revealing the response of species diversity of different plant communities to the environment, we can gain a deeper understanding of the spatial distribution patterns of plants, analyze the formation mechanisms of plant species diversity [8,9,10,11], and provide a theoretical basis for the management and protection of ecosystems.

Plant distribution and community structure are affected by a variety of environmental factors, and one of the most critical factors is the physical and chemical properties of soil. In a study of alpine meadow communities on the eastern edge of the Tibetan Plateau, some scholars found that plant distribution and community structure were mainly affected by various functional traits of the soil [12]. Meanwhile, the calculation of species diversity and functional trait indices for loess hilly areas also highlighted the relative influence of biodiversity and soil single factors on community productivity [13]. In addition, studies in different areas such as karst forests in the Li River basin, karst mountain grasslands in Guizhou Province, and Balentai on the south slope of the middle section of the Tianshan Mountains have shown that there is a significant correlation between soil physicochemical properties and plant species diversity [14,15,16,17,18,19,20,21,22]. Meanwhile, by analyzing the relationship between plant communities and soil physicochemical properties at different altitudes in these studies, it was pointed out that plant species diversity and soil physicochemical properties would change with the change of altitude. Studies in tropical and temperate regions further support this view, emphasizing the key role of soil properties on plant community diversity [23]. Studies in the Peruvian Andes [24] have also shown that plant community composition and structure, as well as productivity in grassland ecosystems, vary with elevation, and have shown that soil factors play an important role in the diversity and productivity of alpine grassland communities. Therefore, a large number of studies have shown that soil physicochemical properties play a crucial role in the process of plant distribution and community structure formation. Furthermore, by analyzing the relationship between plant communities and soil physicochemical properties at different elevation gradients, the complex mechanisms in grassland ecosystems can be more fully understood.

Grassland plant communities and soil physicochemical properties change with altitude. In previous studies, many scholars have paid attention to the characteristics of plant community diversity and biomass changes with altitude and the relationship between them [25,26,27], and few have paid attention to the relationship between plant community species diversity and soil physicochemical properties and the characteristics of changes with altitude. In this study, we investigated the species diversity and aboveground biomass of grassland plants, as well as the physicochemical properties of soils at different altitude gradients, and analyzed the relationship between the three and the characteristics of the changes with altitude in the forested area of Burzin in the Altai Mountains. The relationship between the diversity of grassland plant species, aboveground biomass, and soil physicochemical properties was analyzed, and the change with altitude was characterized. This study can not only provide a theoretical basis for the protection and management of ecosystems in the Burzin forest area, but also help elucidate the characteristics of the ecosystem structure of the grasslands in the Burzin forest area, which provides an important reference value for this type of research, furthermore laying a theoretical foundation for our understanding of the impact of environmental change on species diversity.

2. Materials and Methods

2.1. Overview of the Study Area

The Altay Burqin forest area is located in the north of the Xinjiang Uygur Autonomous Region in the arid northwest of China, which lies between 86°25′~88°06′ E and 47°22′~49°11′ N, with an area of about 3770 km², a forested area of 2,805,600 mu, and a forest stock of 15,510,000 m³. The altitude range is about 450~4330 m, generally showing a long geographic pattern extending from north to south and narrower from east to west, with the terrain gradually rising from south to north. The region features a temperate mountainous climate, with obvious climatic differences between the north and south, and an average annual precipitation of about 300~600 mm [25]. Within the altitude range of 1000~2200 m, the main grassland types are mountain desert grassland, mountain grassland, mountain meadow grassland, and mountain meadow. The dominant species include Dactylis glomerata, Poa annua, Eleusine indica, and Potentilla chinensis. The diversity of vegetation types also indicates the complexity and richness of the grassland ecosystem and lays the foundation for the study of the relationship between vegetation species diversity and the physical and chemical properties of soil. In addition, the grasslands of the Burzin forest region not only provide an important habitat for the region’s biodiversity, but can also be of significant ecological and economic value in maintaining the ecological balance of the region’s grasslands and promoting sustainable development (Figure 1).

2.2. Research Methodology

2.2.1. Sample Plot Setup and Vegetation Survey

The main purpose of this study is to explore the changes in the grassland plant community with altitude gradient in the Burzin forest area, combined with the actual situation of grassland in the Burzin forest area, where the altitude range of 1000~2200 m was selected as the research object. In order to observe the changes of the plant and soil physicochemical properties with the altitude gradient in more detail, the design was divided into six altitude gradients, namely I, II, III, IV, V, VI, with altitude steps of 200 m, respectively, which ultimately achieved effective capturing of the diversity of plant species and soil physicochemical properties, as well as the change of the trend of the aboveground biomass with the altitude gradient. A 20 m × 20 m large sample plot was randomly set up within each elevation gradient, and five more 1 m × 1 m small sample squares were set up in each large sample plot. In order to prevent the sample plots from influencing each other, each grass sample plot was spaced 10 m away from each other. In addition, we further recorded the species name, cover, number of species, plant height, etc., in each small sample plot. To determine the aboveground biomass, the ground mowing method was used. All aboveground parts of plants in the sample plots were cut flush with the ground and then weighed in terms of their fresh weight. After the grass samples were mowed, we used a 5-cm-diameter soil auger to collect surface soil samples from 0–30 cm of depth for the determination of soil physicochemical properties, and, at the same time, soil samples were taken with a ring knife to determine the soil moisture content.

2.2.2. Determination of Soil Physical and Chemical Properties

Soil moisture content was determined by the drying method. Soil pH and conductivity were mainly determined by taking part of the air-dried soil, passing it through a 100 mesh sieve, weighing 10 g, adding 50 mL of deionized water, oscillating at 150 rpm for 1 h on a fully automated shaker, resting for 10 min, and then determining the soil pH and conductivity by using an acidimeter and conductivity meter. The determination of soil physicochemical properties was referred as per the Methods of Soil Agrochemical Analysis [28]. For the determination of soil available components mainly, part of the shade-dried soil was also passed through a #100 mesh sieve and ground such that the particle size was less than 0.25 mm, and then the determination of soil available nitrogen, available phosphorus and available potassium was carried out. Firstly, soil available nitrogen (AN) was determined by a diffusive absorption method [29]. Available phosphorus (AP) content was determined by a 0.5 mol-L⁻¹ NaHCO₃ leaching-molybdenum antimony colorimetric method, and available potassium (AK) content was determined by a NH₄OAC-flame photometer method [30].

2.2.3. Vegetation Data Collection

In this study, the cover of all the plants was recorded as a fraction of vegetation cover, as well as the species name and abundance of each plant, and by determining the height, cover, and frequency of the plants, the flora was named as “flora of China” [31,32]. Species importance values were calculated as follows:

$$P_i=\left({\displaystyle \frac{C_i}{{{\displaystyle \sum }}_i^s{C}_i}}+{\displaystyle \frac{H_i}{{{\displaystyle \sum }}_i^s{H}_i}}+{\displaystyle \frac{F_i}{{{\displaystyle \sum }}_i^s{F}_i}}\right)/3\times 100$$

(1)

where P_i is the importance value of species $i$, C_i is the coverage of species $i$, H_i is the height of species $i$, and F_i is the frequency of species $i$. In this paper, alpha diversity was used to describe species diversity, and the alpha diversity indices were the Margalef species richness index ($R$), the Shannon–Wiener index ($\mathrm{H}$), the Alatalo evenness index, and the Simpson dominance index ($D$) [33]. The formula is as follows:

$$\mathrm{R}=\left(S-1\right)/\ln \mathrm{N}$$

(2)

$$D=1-{\displaystyle \sum }{P}_i^2$$

(3)

$$\mathrm{H}=-{\displaystyle \sum }{\mathrm{P}}_{\mathrm{i}}\ln {\mathrm{P}}_{\mathrm{i}}$$

(4)

$$E_a=\left[1/\left({\displaystyle \sum }{P}_i^2\right)-1\right]/\left[exp\left(-P_i\ln P_i\right)-1\right]$$

(5)

$$P_i={\displaystyle \frac{N_i}{N}}$$

(6)

In the equation, S is the total number of species in the sample plot, N is the total number of individuals in the sample plot, N_i is the number of individuals of the $i$th plant, and P_i is the ratio of the number of individuals of the $i$th plant to the total number of individuals. The Margalef index (R) is an expression of the abundance of a species relative to the number of individuals, and the Simpson index (D) is used to represent the evenness of distribution and diversity of individuals of a species in the community, where the closer the index is to 1, the more even the distribution is and the higher the diversity is. The Shannon–Wiener index (H) indicates the diversity of the community, taking into account both species richness and evenness. The Alatalo index (E_a) presents the degree of evenness of distribution of individuals in the community among species.

2.3. Statistical Analysis

In order to systematically analyze the interrelationships between plant community characteristics and soil physicochemical properties, the following steps were carried out in this study:

(1)

We used the Excel 2010 software package to organize and calculate the raw data.

(2)

One-way analysis of variance (ANOVA) was conducted using the IBMSPSS25.0 statistical software package, which mainly tested whether there were significant differences in the species diversity, soil physicochemical properties, and aboveground biomass at different altitude gradients, thus demonstrating the extent to which different altitude gradients affect plant communities and soil physicochemical properties.

(3)

ArcGIS 10.8 was used to produce an overview map of the study area, describing the geographic location of the study area and the distribution of sample plots.

(4)

Plotting was carried out using the Origin2018 software package to show the trend of plant diversity at different elevation gradients.

(5)

Network analysis was performed by the igraph and Hmisc packages inside the R language to describe the interactions and complex relationships between grassland plant diversity, aboveground biomass, and soil physicochemical factors at each elevation gradient in detail [34,35].

(6)

The spatial correlation between plant community characteristics and soil physicochemical factors was explored by using Mantel test correlation heatmapping with the ggcor package of the R 4.3.3, thus showing the strength of the correlation between the variables.

(7)

Random forest modeling using the randForest package inside the R language assessed the contribution of each factor to grassland plant diversity [36], helping to identify the factors that contribute most to species diversity.

3. Research Result

3.1. Characteristics of Grassland Plant Communities under Different Altitude Gradients

Through detailed investigation of grassland plant communities at different altitudes in the Burzin forest area, the results show (

Table 1. Overview of plant communities in the study area.

Elevation Gradient	Elevation Range/m	Number of Families, Genera and Species	Aboveground Biomass /g-m−2	Dominant Species	Significant Value (%)
I	1000–1200 m	20 families, 33 genera, 36 species	185.11 ± 22.20 abc	Festuca rubra	85.73
				Potentilla chinensis	51.78
				Poa annua	47.75
				Viola biflora	47.36
II	1200–1400 m	25 families, 45 genera, 49 species	167.90 ± 17.52 bc	Poa annua	64.49
				Eleusine indica	55.80
				Paeonia officinalis	47.85
				Dactylis glomerata	47.19
III	1400–1600 m	25 families, 53 genera, 57 species	258.67 ± 17.05 a	Poa annua	52.54
				Cyperus rotundus	46.54
				Dactylis glomerata	45.57
				Eleusine indica	42.97
IV	1600–1800 m	23 families, 45 genera, 51 species	237.84 ± 30.16 ab	Poa annua	59.41
				Equisetum arvense	44.34
				Lithospermum zollingeri	44.32
				Eleusine indica	42.87
V	1800–2000 m	22 families, 36 genera, 43 species	229.67 ± 29.23 ab	Ranunculus japonicus	61.56
				Poa annua	55.71
				Equisetum arvense	52.86
				Antennaria dioica	46.82
VI	2000–2200 m	23 families, 35 genera, 38 species	142.95 ± 27.11 c	Cyperus rotundus	74.99
				Acorus gramineus	66.70
				Potentilla chinensis	60.52
				Poa annua	58.84

Note: Aboveground biomass data are shown as mean ± standard error; different lowercase letters in the same column represent significant differences between elevation gradients (p < 0.05).

) that there were 134 species of plants in the area, belonging to 41 families and 100 genera, dominated by Poaceae, Equisetaceae, Rosaceae, Cyperaceae, and the differences in the compositions of grassland plants at different altitudes are significant. With the increase of elevation, the number of grassland plant species generally showed a trend of increasing first and then decreasing, with the least number of plants at elevation I, totaling 33 species, mainly dominated by Festuca rubra, Potentilla chinensis, Poa annua, and Viola biflora, and the most number of plant species at elevation III, mainly dominated by Poa annua, Cyperus rotundus, Dactylis glomerata, and Eleusine indica. By calculating the species importance values of grassland plant communities at different altitude gradients, the top four plants with species importance values at each altitude gradient were selected. The aboveground biomass showed a trend of decreasing, then increasing, and then decreasing with the increase of elevation, especially at elevation III and elevation VI with significant differences (p < 0.05).

3.2. Species Diversity Characteristics of Grassland Plant Communities at Different Elevations

Grassland plant communities at different elevations were analyzed for their alpha diversity indices. The results showed (Figure 2) that the trends of the Margalef index, Shannon–Wiener index, Simpson index, and Alatalo index were inconsistent. The Margalef index, Shannon–Wiener index, and Simpson index were all smallest at elevation VI, about 0.89, 0.79, and 0.38, respectively, while the Alatalo index was smallest at elevation III, about 0.54. The Margalef index and Shannon–Wiener index were largest at elevation III, about 1.62 and 1.37, respectively, while the Simpson index and Alatalo index were largest at elevation I, about 0.64 and 0.68, respectively. Margalef’s and Shannon-Wiener’s indices were maximum at elevation III with 1.62 and 1.37, respectively, while Simpson’s and Alatalo’s indices were maximum at elevation I with 0.64 and 0.68, respectively. Regression analysis of α-diversity with each elevation band showed that the Margalef index had a good fit with an R² value greater than 0.5 with each elevation band, while the Shannon–Wiener index had a somewhat weaker fit.

3.3. Changes of Soil Physical and Chemical Properties under Different Altitude Gradients

As shown in

Table 2. Changes in physicochemical properties of grassland soils at different elevation gradients.

Elevation Gradient/m	AN/(mg·kg−1)	AP/(mg·kg−1)	AK/(mg·kg−1)	SEC/(μs/cm)	pH	ST/°C	SM/%
I	103.71 ± 12.31 b	22.48 ± 1.99 a	286.81 ± 14.38 a	23.12 ± 2.88 bc	5.78 ± 0.35 ab	19.99 ± 0.77 a	15.49 ± 1.22 a
II	105.56 ± 6.45 ab	24.03 ± 1.22 a	268.46 ± 2.38 ab	15.79 ± 1.51 d	5.15 ± 0.12 b	18.31 ± 0.55 ab	11.78 ± 0.98 b
III	129.19 ± 7.54 a	25.65 ± 0.58 a	277.89 ± 1.29 ab	34.48 ± 2.55 a	6.40 ± 0.78 a	18.96 ± 1.00 ab	15.29 ± 0.56 a
IV	112.84 ± 6.41 ab	25.73 ± 1.58 a	276.27 ± 4.37 ab	28.01 ± 2.72 ab	6.33 ± 0.21 a	18.85 ± 0.90 ab	15.57 ± 0.94 a
V	112.28 ± 4.69 ab	22.71 ± 0.94 a	264.43 ± 2.29 b	23.87 ± 1.59 bc	6.20 ± 0.28 a	17.14 ± 0.93 b	14.51 ± 0.71 ab
VI	108.10 ± 5.62 ab	22.32 ± 1.04 a	268.07 ± 3.06 ab	18.21 ± 2.20 cd	5.36 ± 0.20 b	13.09 ± 0.84 c	12.11 ± 1.18 b

Note: Data are shown as mean ± standard error. Different lowercase letters in the same column represent significant differences between elevation gradients (p < 0.05). AN, soil available nitrogen; AP, soil available phosphorus; AK, soil available potassium; SEC, soil electrical conductivity; pH, soil pH; ST, soil temperature; SM, soil moisture content. Elevation gradient I, 1000~1200 m; elevation gradient II, 1200~1400 m; elevation gradient III, 1400~1600 m; elevation gradient IV, 1600~1800 m; elevation gradient V, 1800~2000 m; elevation gradient VI, 2000~2200 m.

, available nitrogen, available phosphorus, soil conductivity, and soil pH all increased and then decreased with the elevation gradient, and soil temperature decreased with the elevation. Available potassium and soil water content showed a trend of decreasing, then increasing, and then decreasing with the elevation gradient, while available nitrogen content reached a maximum of 129.19/mg·kg⁻¹ at elevation III and a minimum at elevation I, and then declined with the elevation, and it was significant at elevation I and elevation III (p < 0.05). Available phosphorus content was higher at elevations III and IV, reaching 25.65/mg·kg⁻¹ and 25.73/mg·kg⁻¹, respectively, and none of the variations with elevation were significant (p > 0.05). The available potassium content was highest at elevation I, reaching 286.81/mg·kg⁻¹, and lowest at elevation V, reaching 264.43/mg·kg⁻¹, and it was significant (p < 0.05) at both elevation I and elevation V. Soil pH was greatest at medium elevation IV, reaching 6.33/mg·kg⁻¹, and soil pH showed significance (p < 0.05) at all elevation gradients except at elevation I, where it was not significant. Soil temperature generally showed a decreasing trend from low to high elevations, and was lowest at elevation VI, reaching 13.09/mg·kg⁻¹, and was significant (p < 0.05) at elevations I, V, and VI. Soil water content was lowest at elevation II at 11.78/mg·kg⁻¹ and highest at elevation IV at 15.57/mg·kg⁻¹, which was significant at all elevation gradients except at elevation V where it was not significant (p > 0.05).

3.4. Relationships between Plant Community Diversity, Biomass, and Soil Physical and Chemical Properties

As shown in Figure 3, the patterns of interactions between grassland plant community diversity, aboveground biomass, and soil physicochemical factors were explored at each elevation gradient by network analysis, respectively. The network interrelationships were not exactly the same at different elevation gradients. In elevation gradient I, soil conductivity was negatively correlated with both the Margalef index and the Shannon–Wiener index, while it was positively correlated with elevation. Under elevation gradient II, the Shannon–Wiener index decreased with increasing elevation and showed a negative correlation, except for soil temperature, which showed a positive correlation with aboveground biomass, and soil pH, which showed a positive correlation with both Margalef and Simpson indices. At elevation gradient III, there was a significant positive correlation between soil conductivity, a central node, and the Margalef and Shannon–Wiener indices and aboveground biomass, followed by soil temperature with Simpson’s index and elevation, which also showed to be a positive correlation. At elevation gradient IV, aboveground biomass increased with an increasing soil available nitrogen content, while soil available phosphorus was also positively correlated with the Alatalo and Margalef indices. Soil water content was positively correlated with the Shannon–Wiener index, and soil temperature was positively correlated with the Alatalo and Margalef indices, although soil temperature had a significantly lower association with the network compared to soil water content. The Margalef and Shannon–Wiener indices were positively correlated. Under elevation gradient V, soil conductivity and soil available nitrogen content were the key nodes affecting plant diversity and aboveground biomass, and there was a significant positive correlation between soil conductivity and the Shannon–Wiener index, Alatalo index, and aboveground biomass. Meanwhile, soil available nitrogen content was closely related to Shannon–Wiener index and Simpson index network, which suggests the key role of available nitrogen in plant communities. In elevation gradient VI, the soil available nitrogen content and conductivity were still the key factors, which were significantly and positively correlated with aboveground biomass and the Shannon–Wiener index. In general, the effects of soil physicochemical factors on the characteristics of grassland plant communities varied with increasing altitude, with available nitrogen and soil conductivity having significant effects on species diversity and aboveground biomass at different altitude gradients.

After exploring the complex relationships and variability among grassland species diversity, aboveground biomass, and soil physicochemical factors across elevation gradients, this study also used the Mantel test to analyze the interrelationships among species diversity, aboveground biomass, and soil physicochemical factors within the overall sample plots. The results, as shown in Figure 4, showed a highly significant positive correlation between aboveground biomass and Simpson’s index (p < 0.01), while the relationship with the Shannon–Wiener index was relatively weak (0.01 ≤ p < 0.05). However, aboveground biomass did not show significant correlation with either the Margalef index or Alatalo index. Available nitrogen showed strong correlation with aboveground biomass, while no significant correlation with the Shannon–Wiener index. There was a highly significant positive correlation between soil conductivity and the Margalef index (p < 0.01) as well as between soil pH and the Simpson index (0.01 ≤ p < 0.05). In addition, soil water content showed a highly significant positive correlation not only with Simpson’s index, but also with aboveground biomass. Available phosphorus showed a significant positive correlation with the Shannon–Wiener index, but the relationship with aboveground biomass was relatively weak. Available potassium did not show a significant correlation with either the four values of the species diversity index or aboveground biomass. Finally, elevation showed a highly significant positive correlation (p < 0.01) with the Alatalo index but showed a non-significant relationship with aboveground biomass.

Finally, the importance of different soil physicochemical factors, aboveground biomass, the Margalef species diversity index, and Shannon–Wiener, Simpson, and Alatalo indices were predicted using the random forest model (Figure 5). Available nitrogen had the highest contribution to the Margalef index. Aboveground biomass and soil conductivity also showed relatively high importance, while available phosphorus and soil moisture content were of low importance. Aboveground biomass had the highest importance for the Shannon–Wiener index, which means that aboveground biomass had an important role in the Shannon–Wiener index. Soil temperature and soil conductivity also showed high importance, while available potassium had the lowest importance. Aboveground biomass still contributed significantly to Simpson’s index, but less than Shannon–Wiener’s index. Soil conductivity and available nitrogen were also important soil physicochemical factors with significant effects on the Simpson’s index. Altitude, available nitrogen and soil moisture content contributed more to the Alatalo index and all played a significant effect.

4. Discussion

4.1. Changes in Species Composition and Species Diversity of Grassland Plant Communities at Different Elevations

The vertical distribution pattern of plant diversity in different grassland ecosystems has different plant distribution patterns and geographical differences. In this study, plant species richness and aboveground biomass were found to show a pattern of first increasing and then decreasing with elevation, which is consistent with the results of Hooper et al. [3] on a global scale. The pattern of an increase and then decrease in the number of plant species in compositions with different elevation gradients is consistent with the findings of Lai et al. [7] in Mt. Shaluli, which may be due to the fact that the mid-elevation region has suitable conditions for plants such as the temperature, humidity, and soil nutrients, which are suitable for the survival of the grassland plant communities. However, this finding differs from that of Sundqvist et al. [37] on a global scale, which may be due to the fact that species diversity under different elevation gradients exhibits different distribution patterns in different regions. In addition, Margalef’s and Shannon–Wiener’s indices of grassland species also varied with the altitude gradient, which is consistent with Li et al.’s [6] conclusion in their study on the Tibetan Plateau where the plant diversity index reaches a maximum at a mid-altitude and then declines, which may be a result of the extreme geographic conditions of high altitude that can limit the survival of most species. This is also in agreement with the findings of Dani et al. [38] in high-altitude reserve in the Indian Himalayas, where, again, plant species richness and diversity varied with an increasing altitude. The maximum aboveground biomass at elevation III in this study was associated with moderate hydrothermal conditions and rich soil nutrients, which differed from the findings of Körner et al. [39], which may be due to the shortened growing season of the plants due to lower temperatures at higher elevations and the environmental constraints on the growth of the plants, etc.

4.2. Analysis of Soil Physicochemical Properties under Different Altitude Gradients

In terrestrial ecosystems, soil is a bridge between organisms and the environment, and soil has a large amount of nutrients, such as nitrogen, phosphorus and potassium, which provide a nutrient base for the growth and survival of plants, and thus also affect the distribution pattern of plant communities. In this study, available nitrogen content was found to be highest at elevation III and decreased with increasing elevation, which is consistent with the findings of John et al. [30] in the tropics. The available phosphorus content, although higher at elevations III and IV, did not vary significantly, which implies that the distribution of available phosphorus content is more homogeneous, or its influencing factors are more complex than available nitrogen. Available potassium content was maximum at the lowest altitude and lowest at mid-altitude, which is in agreement with the results of a study in this part of Alpine meadow of the Qinghai–Tibet Plateau [5], but differs from the results of a study in, for example, the Swedish Scandinavian Mountains [40], possibly due to the high precipitation or the rapid decomposition of organic matter in this area, which indirectly leads to the loss of other nutrients, such as potassium. Secondly, soil pH reached its maximum at intermediate elevations, which is in agreement with the findings of Grace et al. [8], where neutral to alkaline soil conditions may be more suitable for the growth of plant species at this site. However, it differs from the findings of Wiesmeier et al. [41], which may be due to the fact that low temperatures and low biological activity directly lead to the accumulation of organic acids, indirectly lowering the soil pH. Soil temperature showed a significant decreasing trend with increasing altitude, which is consistent with the phenomenon of low soil temperature in high altitude areas, and this phenomenon also affects the growth of plant communities. The soil water content was highest at elevation IV, which was consistent with the findings of Li et al. [6], both proving that the soil moisture content was positively correlated with elevation and began to gradually decrease after reaching the maximum.

4.3. Relationships among Plant Community Diversity, Aboveground Biomass and Soil Physicochemical Properties across the Elevation Gradient

The variability in the interrelationships between vegetation community characteristics and soil physicochemical properties at different elevation gradients is consistent with the results of a study in the Brazilian Atlantic Rainforest [4]. At elevation gradient I, soil conductivity showed a negative correlation with the species diversity index, which is consistent with the results of the study of soil physicochemical properties on plant species diversity at different elevation gradients on the Tibetan Plateau [5]. With an increasing altitude, the soil conductivity, species diversity index, and aboveground biomass showed a positive correlation at elevation III, suggesting that there are differences in plant acclimatization to soil salinity at different elevation gradients, which further affects plant survival and diversity, which is in line with the conclusion of the study by Li et al. [6] on the relationship between soil factors and species diversity on the Qinghai–Tibetan Plateau. Soil pH was positively correlated with the Margalef and Simpson indices in elevation gradient II and was one of the important nodes affecting species diversity, in addition, there was a positive correlation between soil temperature and aboveground biomass, proving that soil temperature plays a key role in harmonizing aboveground biomass. Available nitrogen, as an important nutrient element, played a key role in species diversity and aboveground biomass in elevation gradients V and VI, which is a finding consistent with that of Han et al. [5]. In elevation gradient IV, the significant positive correlation between soil water content and species diversity was significantly more sensitive than that between soil temperature and species diversity, which was consistent with the findings of Wang et al. [42] in the Tianshan Mountains of Xinjiang, indicating that soil water content and soil temperature may also indirectly affect plant diversity by influencing seed germination.

4.4. Correlation Analysis of Grassland Species Diversity, Biomass and Soil Physical and Chemical Properties under the Overall Altitude Gradient

In the present study, aboveground biomass was found to be significantly and positively correlated with available nitrogen, which is in agreement with the findings of Khanalizadeh et al. [43], where aboveground biomass increased with increasing soil nitrogen content in the state of Durango, Mexico. Both the Margalef index and Shannon–Wiener index were significantly correlated with most of the soil physicochemical properties, which is consistent with the findings of Grace et al. [8] in five continents. Soil pH was found to be positively correlated with the Shannon–Wiener index and Alatalo index, which is in agreement with the findings of Han et al. [5] in the Alpine meadow of the Qinghai–Tibet Plateau. In addition, soil moisture content showed a strong negative correlation with the Shannon–Wiener index, which means that higher soil moisture may be less favorable to plant growth and survival, which is consistent with the findings of Li et al. [6] in the Tibetan Plateau. Soil conductivity showed significant negative correlation with Simpson’s index. Available nitrogen was the most critical soil physicochemical factor affecting Margalef’s index, which is also in agreement with the findings of Grace et al. [8]. For the Shannon–Wiener index, the key influencing factor was aboveground biomass, indicating that aboveground biomass was the key factor influencing the biodiversity index, which was consistent with the findings in the Arjinshan Nature Reserve on the Tibetan Plateau [11], and the two soil factors, soil electrical conductivity and soil temperature, also presented high importance. Soil conductivity and available nitrogen, as well as aboveground biomass, also play an important role for Simpson’s index, which means that these physicochemical properties are extremely important for maintaining species dominance, which is in line with the results of Pan et al. [24] in the Peruvian Andes for soil factors in terms of the diversity and productivity of alpine grassland communities. Finally, the main driver of the Alatalo index was elevation, followed by the available nitrogen in soil and soil water content, with the importance of these factors affecting plant community homogeneity.

5. Conclusions

This in-depth study on the changes and interrelationships of plant community diversity, aboveground biomass, and soil physicochemical factors at different elevation gradients in the Burzin forest area of Xinjiang has found that the number of species and aboveground biomass reach the maximum value at elevation gradient III and then show a tendency of increasing and then decreasing. The Margalef and Shannon–Wiener indices were at a maximum at elevation III, whereas the Simpson and Alatalo indices were at a maximum at elevation I. The soil temperature decreased with an increasing elevation. Also, available nitrogen, available phosphorus, soil conductivity, and pH showed a tendency to increase and then decrease, while soil temperature decreased with elevation. Soil conductivity was negatively correlated with diversity indices in elevation gradients I to III, but was positively correlated with diversity indices and aboveground biomass in elevation gradients IV to VI. Available nitrogen played a key role in plant diversity and biomass in elevation gradients IV to VI. In addition, aboveground biomass was significantly and positively correlated with Simpson’s index, though relatively weakly with Shannon–Wiener’s index, and not significantly correlated with Margalef’s and Alatalo’s indices. Soil conductivity and pH significantly affected the Margalef and Simpson indices, and available nitrogen was closely related to aboveground biomass. Soil moisture content significantly affected Simpson’s index and aboveground biomass, while available nitrogen was critical for the Margalef and Alatalo indices, and soil conductivity had a key role for all indices. The conclusions of this study provide theoretical support for the growth and survival environments for plant communities at different altitudes in grassland ecosystems in the region and their ecological conservation and management, as well as an important reference value for the management of other grasslands with similar elevation gradients and vegetation types around the world.