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Article

Microplastics Abundance and Spatial Distribution in Bayinbuluk Alpine Swamp Meadow

by
Yuxin Tian
1,†,
Maidinuer Abulaizi
1,†,
Yunpeng Hu
2,
Yang Hu
2,3,
Mo Chen
1,
Yuanbin Jia
2,
Tianle Kou
2,
Jianqin Zhou
2,4 and
Hongtao Jia
2,4,5,*
1
College of Grassland Science, Xinjiang Agricultural University, Urumqi 830052, China
2
College of Resources and Environment, Xinjiang Agricultural University, Urumqi 830052, China
3
College of Resources and Environment, Northwest A & F University, Yangling 712100, China
4
Xinjiang Key Laboratory of Soil and Plant Ecological Processes, Urumqi 830052, China
5
College of Life Sciences, Xinjiang Agricultural University, Urumqi 830052, China
*
Author to whom correspondence should be addressed.
†
These authors contributed equally to this work.
Agriculture 2025, 15(13), 1343; https://doi.org/10.3390/agriculture15131343
Submission received: 29 April 2025 / Revised: 17 June 2025 / Accepted: 21 June 2025 / Published: 22 June 2025
(This article belongs to the Topic Livestock and Microplastics)
Browse Figures
Versions Notes

Abstract

In order to investigate the current pollution status and distribution characteristics of soil microplastics (MPs) in Bayinbuluk alpine swamp meadow, soil samples of different depths were collected from the study area. The physicochemical properties of the soil, as well as the abundance and morphological distribution of microplastics, were analyzed. The results showed that the microplastics’ abundance in the samples ranged from 46 to 266 microplastics/kg, with significantly higher levels (p < 0.05) in the 0–10 cm soil layer than in the other layers (10–100 cm). The shapes of microplastics mainly include fibrous, fragmented, thin film, and foamed, and the number of fibrous shapes is significantly higher than the other three types. Microplastic colors included black, yellow, red, blue, green, and clear, with black accounting for 70.16%, significantly more abundant than other colors (p < 0.05). Among the different particle sizes of microplastics, 0.5–1 mm microplastics comprised the largest proportion and were significantly more abundant than other particle sizes. Polyethylene (PE) was found to be a major component of soil microplastics in the study area through random sampling using Raman spectroscopy. Correlation analysis showed that the change in soil layer had a significant effect (p < 0.05) on the number, color, and particle size of microplastics. Meanwhile, an increase in microplastic abundance had a significant effect (p < 0.05) on the soil physicochemical properties. The results of RDA (Redundancy Analysis) and Monte Carlo testing showed that there was a significant correlation between microplastic quantity and soluble organic carbon and soil water content (p < 0.01).

1. Introduction

As a new type of pollutant, microplastics (plastics with a particle size <5 mm [1]) can cause far-reaching effects on plants and animals [2,3] and human health [4] when released into the soil environment due to their wide distribution [5], minute size [6], slow degradation, and ease of migration with water flow. The main sources of microplastics in soil include landfills [7], sewage irrigation [8], river runoff [9], and atmospheric deposition pathways [10,11]. While it is the main resource for human survival, less than 5% of studies on microplastic pollution nationally and globally focus on soil [12], and microplastics in alpine meadows, a special terrestrial ecosystem, have rarely been reported. The flow of groundwater is an important driving force for microplastics to migrate with water in soil. Under the interaction of soil and groundwater, the fluctuation in the groundwater level will cause a change in the spatial distribution of microplastics, which will make the microplastics migrate from the surface layer of soil to the deep layer with the water flow [13]. Seasonal changes can lead to changes in the water table in alpine meadows, so it is extremely important to understand the abundance, spatial distribution characteristics, and sources of microplastics in grassland ecosystems.
The current global studies on microplastics show that they are present in most soils, and their abundance ranges from almost zero to thousands per kilogram of soil [12]. Corradini et al. [14] reported relatively low soil microplastic concentrations in pasture and farmland, with a concentration of about 300 microplastics/kg. In the agricultural coverage area of Xinjiang, China, soil microplastic pollution in a cotton field covered with plastic film for an extended amount of time was serious, with the highest abundance at 3560 microplastics/kg [15]. Affected by industrial activities, the highest microplastic abundance in soils in Australian industrial areas is close to 7000 microplastics/kg [16]. In 2018, Liu et al. [17] published the first investigative report of Chinese soil microplastics, marking the official launch of research in this area in China. Follow-up studies focused on the negative effects of microplastics on the soil physical properties (density, bulk density, water holding capacity) and ecological functions (water balance, plant growth). Machado et al. [18] found that microplastics can reduce the soil particle density and bulk density (BD), affecting the water storage capacity, with polyester fibers (PET) having a significantly stronger effect than PE. Xiao et al. [19] found that microplastics disrupt soil moisture infiltration, causing uneven water distribution that mismatches plant root zones and threatens ecosystem stability. Boots et al. found that the incorporation of PE led to a decrease in soil pH, while PET reduced soil fertility [20]. Additionally, Dong et al. showed that higher microplastic abundance leads to a decrease in soil organic matter and quick nutrients, with a linear relationship [21].
As of 2024, China had the largest number of microplastics in soil ecosystems globally, but the vast majority of studies in this area have focused on the investigation and risk assessment of mulched farmland and farmland in industrial areas, as well as the interactions of microplastics with heavy metal elements, plants, and animals in soil [22,23,24]. Compared with that in film-covered farmland, greenhouses, and conventional farmland, the microplastic abundance in grassland ecosystems is the lowest [25]. However, the pollution source, spatial distribution law, and interaction mechanism with environmental factors of grassland microplastics are still unclear. It has been pointed out that microplastics are easy to migrate with water [13], and their dynamic change in soil is related to nutrient cycling [26]. Taking the swamp meadows of Bayinbuluk alpine grassland as an example, as a seasonal waterlogging area, the occurrence characteristics of microplastics in this area may be significantly affected by hydrological conditions. By systematically analyzing the abundance, spatial distribution characteristics, and sources of microplastics in this region and their relationship with environmental factors (such as soil moisture, nutrients, organic matter, etc.), in this study, we fill the gap in the research on alpine swamp meadow microplastics in arid areas of Central Asia and provide a scientific basis for the sustainable management of alpine ecosystems and microplastic pollution prevention and control.

2. Materials and Methods

2.1. Overview of the Study Area

The alpine grassland in Bayinbuluk (42°18′~43°34′ N, 82°27′~86°17′ E) encompasses a total area of 23,835 km2, with usable grassland covering 20,519 km2 and elevations ranging between 1500 m and 2500 m. It is located in the inner section of Hejing County, Xinjiang Uygur Autonomous Region, China (Figure 1). Situated in Central Asia’s arid region, it exhibits a typical alpine climate characterized by long, cold winters and brief, cool summers, making it highly responsive to global climate change. The area receives an average annual rainfall of 273 mm, maintains an average annual temperature of −4.8 °C, experiences a minimum temperature of −49.6 °C, and undergoes seasonal freeze–thaw cycles exceeding 6 months, and a maximum historical frozen soil depth of 4.39 m has been recorded (the highest value documented by China Meteorological Station) [27].
The research area encompassed the Swan Lake alpine wetland in Bayinbuluk (42°45′~43°00′ N, 82°59′~83°31′ E), representing the core zone of this alpine grassland. The site spanned approximately 60 km east–west and 20 km north–south, covering a region of 770 km2 at elevations of 2300–3042 m. The predominant soil types included muddy swamp soil, peat swamp soil, meadow swamp soil, and meadow soil in alpine valleys. The vegetation communities primarily consisted of Carex rhynchophysa, Carex melanantha, Carex stenocarpa, and Poa pratensis [28].

2.2. Experimental Design and Soil Sample Collection

Based on the long-term monitoring transect of Swan Lake established in an early stage in this study, the swamp meadow area of Swan Lake alpine wetland in Bayinbuluk was selected as the research object. The soil in the area is snow-covered in winter. In spring, snowmelt and rainfall lead to surface water accumulation during the growing season. But there is no water accumulation in the dry season, the soil water content fluctuating significantly. Twenty-one 1 m × 1 m quadrats were randomly selected in the experimental area (the quadrats were spaced more than 20 m apart to avoid interference) (Figure 2), and soil samples of 0–10 cm, 10–20 cm, 20–30 cm, 30–50 cm, 50–70 cm, and 70–100 cm were collected by the five-point method with a stainless steel soil drill (Beijing jiuzhou shengxin technology Co., Ltd., JZ-AQ, Beijing, China). A total of 378 samples were put into a cloth bag and brought back to the laboratory.

2.3. Measurement Methods

2.3.1. Physicochemical Soil Sample Processing and Analysis

A ring knife was used to collect soil bulk density (BD) samples in the quadrats. Samples of the 0–10 cm soil layer were collected synchronously for the determination of physicochemical indexes. A portion of fresh soil samples were stored at 4 °C for the determination of soil dissolved organic carbon (DOC) and the water content (SWC), while the other portion was naturally air dried to determine the soil acidity and alkalinity (pH), soil organic carbon (SOC), total nitrogen (TN), and total phosphorus (TP). Specifically, the soil pH was determined using a pH meter (Mettler Toledo, Zurich, Switzerland, FE28) after suspending soil in water at a ratio of 1:5. The SOC was determined via the concentrated sulfuric acid–potassium dichromate external heating method. The TP was determined through the molybdenum antimony colorimetric method. The TN was determined using an elemental analyzer (elementar, vario isotope) [29]. The DOC was determined using a total organic carbon analyzer (Shimadzu, Kyoto, Japan, TOC-VCPH). Briefly, 10 g of fresh soil sample was mixed with 50 mL of deionized water in a 100 mL centrifuge tube. Then, the soil–water mixture was shaken for 30 min, centrifuged for 10 min (10,000 r/min), and filtered through a 0.45 μm glass fiber filter membrane. A blank control test (without soil samples) was performed in the same way. The organic carbon in the filtrate was determined using a total organic carbon analyzer [30].

2.3.2. Microplastic Sample Handling and Analysis

Microplastics were extracted from the soil samples via the density separation of saturated sodium chloride solution. The samples were dried in an oven at 100 °C for 24 h and then put into a beaker. Then, 250 mL of saturated sodium chloride solution (density 1.2 g/mL) was added to 100 g of dry soil, and ultrasonicated for 2 min. The mixture was stirred with a glass rod for 30 min, and after standing for 24 h, the supernatant including microplastics was collected in a conical flask. The steps of ultrasound, stirring, and collecting the supernatant were repeated three times to ensure the full extraction of microplastics from the soil. Then, H2O2 solution with a concentration of 30% was added to the supernatant, mixed thoroughly, and digested in a shaker at 50 °C for 72 h to ensure that the organic matter in the supernatant was fully digested [31]. After separation, it was filtered through a glass cellulose filter membrane with a pore size of 0.45 μm using a vacuum filtration device. Then, the filter membrane containing the microplastics was placed under a stereomicroscope (Nikon, Tokyo, Japan, SMZ25) for observation. The color, size, and shape of the microplastics were recorded. The samples were spectroscopically analyzed with the aid of Raman spectroscopy (Thermo Scientific, Waltham, MA, USA, DXR2XI), and the targets were qualitatively analyzed by comparing their spectral maps with standard spectra. Meanwhile, a scanning electron microscope (SEM) (Zeiss, Oberkochen, Germany, Supra55VP) was used to observe the microplastics and their surface micromorphology. To reduce exogenous microplastic contamination, the entire experimental process was conducted in a clean room, cotton test suits were worn during experimental operations, and the glassware in the experiments was required to be cleaned with deionized water and wrapped in aluminum foil for storage when not in use.

2.4. Data Analysis

Excel 2018 and SPSS 26.0 were used to organize the data and perform ANOVA, and IBM SPSS Statistics 27.0 was used to perform ANOVA and post hoc tests to assess significant differences between microplastics of different particle sizes (as well as normality and chi-squared tests). With the help of the OriginPro 2021 (v9.8.0.200) (OriginLab Corporation, Northampton, MA, USA), the vertical variation and abundance of microplastics were mapped. The “vegan” package in R (v.4.1.1; https://www.r-project.org/, accessed on 11 April 2025) was used in the RDA. Principal component analysis (PCA) was utilized in single-factor analysis of variance, redundancy analysis, and Monte Carlo replacement testing to evaluate the influence of soil layer change on changes in microplastics and the correlation between these and the soil physicochemical properties. Monte Carlo permutation testing was used to analyze the significance of the soil physicochemical properties (permu = 999) [28,32].

3. Results

3.1. Characteristics of the Spatial Distribution of Microplastics in the Alpine Swamp Meadows of Bayinbuluk

The amplitude of microplastic abundance in the 0–100 cm soil of the alpine swamp meadows of Bayinbuluk ranged from 46 to 266 microplastics/kg (Figure 3a). The microplastic content of the topsoil layer was significantly higher (p < 0.05) than that in the other layers, with an abundance of 266 microplastics/kg. The abundance of microplastics in the 10–20 cm soil was 200 microplastics/kg, which was second only to that in the topsoil, and that in the 0–30 cm soil layer accounted for 74.19% of the total. The microplastic abundance in the 30–100 cm layer ranged 46–93 microplastics/kg (p < 0.05), with 70.16% black, some yellow, and minimal blue, green, red, or transparent plastic (Figure 3b). Fibrous microplastics were significantly more abundant than other forms of microplastics (p < 0.05) (Figure 3c). Particle sizes in the ranges <0.5 mm, 0.5–1 mm, 1–2 mm, and >2 mm were detected, with microplastics in the range 0.5 mm–1 mm predominating (Figure 3d).

3.2. Analysis of the Composition and Source of Different Forms of Microplastics

From the body microscope observation, the microplastic shapes detected included fibrous, fragmented, thin film, and foamed ones (Figure 4). The results of microplastic electron microscope scans showed significant differences in the surface morphology of different forms (Figure 5). Fibrous microplastics were generally slender and had filamentous residues on the surfaces (Figure 5a) and clear branches at the ends (Figure 5b); fragments had evident broken edges but smooth fractures and uneven surfaces (Figure 5c,d); films were thinner, with pronounced fractures and tears (Figure 5e,f); and foamed surfaces had more protruding cracks and folds that were less smooth (Figure 5g,h). The surfaces of the four types were all attached to broken fragments or other substances.
Raman spectroscopy analysis was conducted on 21 randomly selected microplastics to determine their chemical composition. The analysis revealed that 18 samples exhibited distinct strong peaks within the range of approximately 3000–2800 cm (Figure 6a), with peak patterns in the low wave number region corresponding to the molecular vibration characteristics of PE. These samples were confirmed as PE through comparison with standard spectra [33]. The remaining two samples, however, displayed no typical characteristic peaks associated with common microplastics (such as PE, PP, PET) across the full-wave scanning range (Figure 6b). Although these samples showed some spectral fluctuations, they could not be accurately matched with characteristic peaks in the existing standard spectrum library and were therefore classified as unknown substances. Eighteen of the identifiable ones were PE, two could not be identified as to their origin, and one PE was selected to be demonstrated with an unknown (Figure 6).
Expressing the variation in soil layers in terms of different depths, and representing the numbers of six different colors of microplastics distributed among the layers, PC1 explained 38.85% of the variation. Furthermore, PC1 explained 59.48% and 50.03% of the variance for microplastic shape and particle size distributions among soil layers, respectively. One-way ANOVA (Table 1) indicated that changes in soil depth significantly affected the microplastic abundance (p < 0.01), color and size (p < 0.05), but not shape (p > 0.05).
Microplastic data of soil from 0 to 10 cm were selected for RDA with the soil physicochemical data (Figure 7). The results showed the following: the variation in microplastic particle size was positively correlated with the SOC; the shape of microplastics was positively correlated with the TN content; and the number of microplastics was positively correlated with the DOC and negatively correlated with the other indicators of nutrients, water content, and bulkiness. The results of the Monte Carlo permutation test (Table 2) indicate that the changes in the amount of microplastics had the greatest effect on the DOC and SWC.

4. Discussion

4.1. Abundance, Characteristics, and Source Analysis of Microplastic Distribution in Alpine Swamp Meadow Soil

Numerous studies have shown that microplastics are also present in significant quantities in non-tilled soils. For example, Zhang et al. found microplastic levels of 8180 to 18,100 microplastics/kg in forested areas [34], while Duan et al. also reported 136 microplastics/kg in the Yellow River Delta Protected Area [35]. The presence of microplastics is closely linked to human activities, but they can even be found in protected areas and forests. In contrast, in this study, we showed that the microplastic abundance of Bayinbuluk alpine swamp meadow soils ranged from 40 to 320 microplastics/kg, which was much lower than that of farmland and forest soils and similar to that of protected areas such as the Yellow River Delta [34,35].
The abundance of microplastics in the surface soil (0–10 cm) was significantly higher (p < 0.05) than that in the deeper soil in this study, which may have been due to the migration of microplastics. Such migration behavior is determined by the particle shape (e.g., it is easy for fibers to trap particles and for microspheres to migrate) and the polymer type (e.g., it is easy for low-density PE to be suspended and for high-density PET to settle), which affect the diffusion ability in the environment through physical retardation, hydrodynamic, and surface chemical characteristics [36]. Previous studies have shown that the main factors of microplastic migration are dry–wet alternation and freeze–thaw cycles, both of which manifest in alpine meadows [37]. The study area experiences seasonal waterlogging and a freeze–thaw cycle [27]. Microplastics move with the moisture in the soil layers during dry–wet alternation, creating a disordered and uneven distribution of their abundance. Freeze–thaw cycles generate large pore spaces in topsoil, providing entry pathways that lead to significant microplastic accumulation in surface layers.
Based on comprehensive analysis of the color, particle size, and shape of microplastics, the results showed that the black, fibrous and 0.5–1 mm long microplastic was the dominant microplastic resulting from the residues of daily necessities such as black woven bags, plastic bags, and protective nets. Therefore, this study investigated the material source of soil microplastics using Raman spectroscopy. The main source of microplastics in this study was PE. Compared with other microplastics, PE is prone to breaking down into smaller fragments which are difficult to be recycled [38]. And PE is resistant to biological and chemical degradation, because of its stability [39]. The main component of fibrous microplastics is a copolymer of PP (polypropylene) and PE [40], which may be the reason why some of the microplastics in this study could not be accurately identified using Raman spectroscopy. Although the study area was located in a protected area, there are still some herders practicing grazing, and the source of microplastics may be from plastic household items discarded by the herders and from atmospheric deposition [41].

4.2. Relationship Between Soil Microplastics and Soil Physicochemical Properties in Alpine Swamp Meadows

According to the analysis of one-way ANOVA, the changes in soil layers have a great influence on microplastics and the soil physicochemical properties. There were significant differences in the soil DOC, SWC, BD, and microplastics number (p < 0.01), color, and particle size (p < 0.05) in different soil layers. This result is consistent with previous studies which showed that the addition of microplastics changed the SWC, BD, and available nutrients in the soil [18,19,20,21]. Similarly, Liu et al. found that microplastics entering the soil significantly increase the content of DOC and TP [42], so the index of DOC was added in this study. Through RDA, it was found that the DOC content and microplastic abundance had a good indicator aggregation relationship, indicating that there was a highly significant positive correlation between the two, aligning with Liu et al.’s results [17]. However, the change in the TP was the opposite, which may have been due to the special climate of alpine meadows and the freeze–thaw cycle and other factors. The specific reasons need to be validated via further incubation experiments. The number of soil microplastics was negatively correlated with soil nutrients, water content, pH, and BD, a finding similar to that of previous studies [18,19,20,21]. This negative association may be attributed to the fact that an increase in the number of microplastics leads to changes in the soil pore structure and water distribution, which alters the soil biotic community and its diversity [43] and the symbiotic relationship between below-ground soil organisms and plants. In addition, the industrial additives carried by microplastics themselves also have a certain toxic effect on the plant root system and plants [44]. Microplastics have an impact on the soil physicochemical properties under the influence of multiple factors, such as above- and below-ground plant traits, soil biology, and physical structure. In summary, more in-depth explorations on the effects of microplastics on soil physicochemical properties are needed.

5. Conclusions

Soil microplastic pollution has become a global environmental problem, threatening the health of soil ecosystems and the sustainable development of agriculture. This study revealed that the soil microplastics of the Bayinbuluk alpine swamp meadow soil are mainly composed of PE. Microplastics are mainly concentrated in the 0–30 cm (accounting for 74.19%, with a maximum of 266 microplastics/kg). Black color and 0.5–1 mm particle size are dominant microplastics. The changes in soil depth has a significant influence on the distribution of microplastics. There is a correlation between microplastics and soil physicochemical properties. Particularly, the change in microplastic quantity has the greatest influence on the DOC and SWC. These results show that there is a certain degree of microplastic pollution in the study area, and the potential ecological risks need to be paid attention to. Our findings provide key data and theoretical support for the prevention and control of microplastics pollution in alpine meadow soil.

Author Contributions

Data curation, Y.H. (Yunpeng Hu) and T.K.; funding acquisition, J.Z. and H.J.; investigation, M.C., Y.J. and T.K.; project administration, J.Z. and H.J.; software, Y.H. (Yang Hu); supervision, J.Z. and H.J.; validation, Y.J.; writing—original draft, Y.T. and M.A.; writing—review and editing, M.A. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by Xinjiang Uygur Autonomous Region “Three Rural” Backbone Training Project (2023SNGGGCC002); Xinjiang Uygur Autonomous Region Graduate Innovation Project (XJ2023G150); and National Natural Science Foundation of China (No.31560171).

Institutional Review Board Statement

Not applicable.

Data Availability Statement

The original contributions presented in this study are included in the article; further inquiries can be directed to the corresponding authors.

Conflicts of Interest

The authors declare no conflicts of interest.

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Figure 1. Geographical location of the study area. Note: linear scale: 1:48,000,000. Drawing approval number: GS(2019)1673. Producer of China Ministry of Natural Resources.
Figure 1. Geographical location of the study area. Note: linear scale: 1:48,000,000. Drawing approval number: GS(2019)1673. Producer of China Ministry of Natural Resources.
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Figure 2. Schematic diagram of sampling position. Note: M stands for meadow area, SM stands for swamp meadow area, and S stands for swamp area.
Figure 2. Schematic diagram of sampling position. Note: M stands for meadow area, SM stands for swamp meadow area, and S stands for swamp area.
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Figure 3. Spatial distribution of microplastics and their color and morphology, as well as abundance and percentage of particle size. Note: different lowercase letters indicate significant differences between groups (p < 0.05). (a), abundance of microplastics in different soil depths; (b), abundance of microplastics in different colors; (c), abundance of microplastics in different forms; (d), abundance of microplastics in different sizes.
Figure 3. Spatial distribution of microplastics and their color and morphology, as well as abundance and percentage of particle size. Note: different lowercase letters indicate significant differences between groups (p < 0.05). (a), abundance of microplastics in different soil depths; (b), abundance of microplastics in different colors; (c), abundance of microplastics in different forms; (d), abundance of microplastics in different sizes.
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Figure 4. Main shapes of soil microplastics ((a,b) fiber; (c,d) thin film; (e,f) debris; (g,h) foam).
Figure 4. Main shapes of soil microplastics ((a,b) fiber; (c,d) thin film; (e,f) debris; (g,h) foam).
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Figure 5. SEM views of different shapes of microplastics ((a) fiber; (b) fiber details; (c) debris; (d) debris details; (e) film; (f) film details; (g) foam; (h) foam details).
Figure 5. SEM views of different shapes of microplastics ((a) fiber; (b) fiber details; (c) debris; (d) debris details; (e) film; (f) film details; (g) foam; (h) foam details).
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Figure 6. Microplastics’ Raman spectra ((a) is polyethylene (PE) and (b) is unknown source).
Figure 6. Microplastics’ Raman spectra ((a) is polyethylene (PE) and (b) is unknown source).
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Figure 7. RDA of soil microplastics and soil physicochemical indicators. Note: BD, soil bulk density; pH, soil acidity and alkalinity; DOC, dissolved organic carbon; SWC, soil water content; SOC, soil organic carbon; TN, total nitrogen; TP, total phosphorus.
Figure 7. RDA of soil microplastics and soil physicochemical indicators. Note: BD, soil bulk density; pH, soil acidity and alkalinity; DOC, dissolved organic carbon; SWC, soil water content; SOC, soil organic carbon; TN, total nitrogen; TP, total phosphorus.
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Table 1. Influence of soil depth change on various indexes in microplastics.
Table 1. Influence of soil depth change on various indexes in microplastics.
IndexesFpPr(>r)
number8.3610.001**
color3.4420.037*
shape2.0750.139
size4.9690.011*
Soil chemical analyses
indexes0−10 cm10−20 cm20−30 cm30−50 cm50−70 cm70−100 cm
DOC (mg/kg)4107.64 ± 149.66 a3385.07 ± 132.58 b2662.96 ± 267.86 c1195.28 ± 120.79 d785.22 ± 51.48 d719.62 ± 66.98 d
SWC (%)25.40 ± 1.05 b31.58 ± 3.20 b46.18 ± 4.53 a49.71 ± 4.05 a50.73 ± 8.25 a59.46 ± 3.33 a
TP (g/kg)0.35 ± 0.02 a0.38 ± 0.03 a0.42 ± 0.06 a0.43 ± 0.01 a0.44 ± 0.08 a0.47 ± 0.07 a
pH8.37 ± 0.08 a8.54 ± 0.22 a8.33 ± 0.08 a8.35 ± 0.16 a8.60 ± 0.14 a8.69 ± 0.10 a
BD (g/cm3)1.02 ± 2.89 d1.40 ± 8.67 ab1.14 ± 2.93 cd1.29 ± 9.89 bc1.36 ± 5.42 abc1.52 ± 7.36 a
SOC (g/kg)21.24 ± 7.52 ab10.53 ± 1.77 c18.28 ± 3.81 ab25.72 ± 6.27 a24.33 ± 9.97 a19.56 ± 2.61 b
TN (g/kg)13.53 ± 1.52 a11.09 ± 1.22 ab10.74 ± 0.52 b6.23 ± 0.25 c4.42 ± 0.32 c4.43 ± 0.30 c
Note: * indicates a significant correlation (p < 0.05), and ** indicates a very significant correlation (p < 0.01). Different lowercase letters represent significant differences. BD, soil bulk density; pH, soil acidity and alkalinity; DOC, dissolved organic carbon; SWC, soil water content; SOC, soil organic carbon; TN, total nitrogen; TP, total phosphorus.
Table 2. Monte Carlo displacement test of microplastics and soil physicochemical indexes.
Table 2. Monte Carlo displacement test of microplastics and soil physicochemical indexes.
RDA1RDA2R2Pr(>r)Significance
DOC0.99804−0.06260.87570.001***
SWC0.943650.330940.67780.002**
TP0.896820.442410.25980.098
pH0.78206−0.62320.20660.191
BD0.987220.159370.20550.187
SOC0.797980.602680.07890.543
TN0.999680.025130.0020.983
Note: ** indicates a very significant correlation (p < 0.01), and *** indicates a very significant correlation (p < 0.001). BD, soil bulk density; pH, soil acidity and alkalinity; DOC, dissolved organic carbon; SWC, soil water content; SOC, soil organic carbon; TN, total nitrogen; TP, total phosphorus.
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MDPI and ACS Style

Tian, Y.; Abulaizi, M.; Hu, Y.; Hu, Y.; Chen, M.; Jia, Y.; Kou, T.; Zhou, J.; Jia, H. Microplastics Abundance and Spatial Distribution in Bayinbuluk Alpine Swamp Meadow. Agriculture 2025, 15, 1343. https://doi.org/10.3390/agriculture15131343

AMA Style

Tian Y, Abulaizi M, Hu Y, Hu Y, Chen M, Jia Y, Kou T, Zhou J, Jia H. Microplastics Abundance and Spatial Distribution in Bayinbuluk Alpine Swamp Meadow. Agriculture. 2025; 15(13):1343. https://doi.org/10.3390/agriculture15131343

Chicago/Turabian Style

Tian, Yuxin, Maidinuer Abulaizi, Yunpeng Hu, Yang Hu, Mo Chen, Yuanbin Jia, Tianle Kou, Jianqin Zhou, and Hongtao Jia. 2025. "Microplastics Abundance and Spatial Distribution in Bayinbuluk Alpine Swamp Meadow" Agriculture 15, no. 13: 1343. https://doi.org/10.3390/agriculture15131343

APA Style

Tian, Y., Abulaizi, M., Hu, Y., Hu, Y., Chen, M., Jia, Y., Kou, T., Zhou, J., & Jia, H. (2025). Microplastics Abundance and Spatial Distribution in Bayinbuluk Alpine Swamp Meadow. Agriculture, 15(13), 1343. https://doi.org/10.3390/agriculture15131343

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