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Article

Trampling and Dung and Urine Addition of Livestock Increase the Soil Organic Carbon in Mountain Meadows by Augmenting the Organic Carbon in Different Aggregates

by
Weisi Li
1,
Qunce Sun
1,
Shuzhen Zhang
1,*,
Xiaojing Hu
1,
Manlike Asiya
2,
Jie Xiong
1,
Mengyue Wang
1,
Xuerui Wang
1,
Runzhou Long
1 and
Guili Jin
1
1
College of Grassland Science, Xinjiang Agricultural University, Urumqi 830052, China
2
Pratacultural Research Institute of Xinjiang Academy of Animal Sciences, Urumqi 830052, China
*
Author to whom correspondence should be addressed.
Agronomy 2025, 15(4), 843; https://doi.org/10.3390/agronomy15040843
Submission received: 14 February 2025 / Revised: 25 March 2025 / Accepted: 27 March 2025 / Published: 28 March 2025
(This article belongs to the Special Issue Utilization and Management of Grassland Ecosystems)
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Abstract

:
Grassland soil carbon stocks contain substantial amounts of organic carbon and play a crucial role in the global carbon cycle. Grazing is one of the most primary land use types in grasslands. However, few studies have focused on the impact of three grazing behaviors (mowing (M), trampling (T), and dung and urine addition (D)) on the soil organic carbon (SOC) of mountain meadows. In this experiment, we simulated three grazing behaviors to explore the impacts of grazing behaviors on plant characteristics with plant growth, soil physicochemical properties, soil aggregate, and analyzed the main factors influencing the changes in SOC. After six years of treatment, the experimental results showed that M significantly decreased plant height, density, and aboveground biomass and significantly decreased soil organic carbon (SOC) (no M vs. M, −3.64%). T significantly increased soil bulk density, the proportion of macroaggregates, the organic carbon of microaggregates, and silt and clay aggregates and significantly increasing SOC (no T vs. T, +3.17%). D significantly increased plant density, soil total nitrogen and the organic carbon of macroaggregates, significantly increasing SOC (no D vs. D, +9.74%). Correlation and principal component analyses indicated that SOC was significantly negatively correlated with soil bulk density and plant coverage and significantly positively correlated with soil total nitrogen, soil C/N, microaggregate proportion, and the organic carbon of macroaggregates. Redundancy analysis indicated that the proportion of microaggregates and the organic carbon of macroaggregates were the main factors influencing SOC. The following conclusions were drawn: SOC responds differently to three types of grazing behaviors, D primarily increases the organic carbon in macroaggregates, while T mainly enhances the organic carbon in microaggregates and silt and clay aggregates, thereby affecting the SOC in mountain meadows.

1. Introduction

The increase in the concentration of carbon dioxide (CO2) in the atmosphere, causing global warming, is one of the major environmental issues facing humanity today [1,2]. In the context of global warming, understanding the process of the soil carbon cycle is the key to accurately estimating regional carbon balance, and carbon sequestration can slow down the rise of atmospheric CO2 concentration [3]. Soil carbon pools are the largest carbon pools in terrestrial ecosystems, and their small fluctuations lead to significant changes in atmospheric CO2 concentrations, which play an important role in global carbon balance [4]. Grassland ecosystems are an important component of terrestrial ecosystems, covering more than 40% of the area [5] and less than 10% of the carbon in grasslands is stored in vegetation through photosynthetic uptake, and more than 90% of the carbon is stored in the soil in the form of organic carbon [6]. Therefore, the stable sequestration of soil organic carbon (SOC) in grassland ecosystems is an important measure to reduce the atmospheric carbon pool [3]. According to statistics, the global grassland area exceeds 5 billion hectares [7], playing a crucial role in regulating the carbon cycle of ecosystems and alleviating environmental issues such as global warming [8].
Grazing is one of the main ways to use and manage grassland [9], and its impact on SOC is inconsistent. Some studies have found that grazing reduces SOC [10,11], while other studies indicate that grazing can increase the SOC [12,13]. Grazing mainly affects grassland plant and soil through the three mechanisms of livestock mowing, trampling, and dung and urine addition [14,15], influencing the content of SOC. SOC reflects the size of the soil carbon pool and its dynamic inputs and outputs. The input of SOC includes litter, root exudates, and microbial residues, and the output includes microbial decomposition, soil respiration, soil erosion, and leaching, which is significant for assessing the carbon balance of grassland ecosystems [16]. The impact of grazing on SOC in grasslands is multifactorial, generally affecting carbon fluxes through changes in plant coverage, aboveground biomass, soil bulk density, soil moisture content, soil aggregates’ structure, etc. [17,18]. The combined effects of the three mechanisms of grazing affect the overall soil organic carbon content. Existing studies have shown that livestock mowing reduces plant aboveground biomass and affects photosynthesis, directly decreasing the input sources to the grassland’s soil carbon pool and thus reducing SOC [19]. Livestock trampling increases soil bulk density, damages soil structure, affects the content of stable aggregates in the soil surface, exposing stable organic carbon to easier decomposition [20]. Soil crust damage leads to wind and water erosion [21], both of which decrease SOC. However, trampling can also break up aboveground litter, accelerating its decomposition rate and increasing SOC [22]. Livestock input organic carbon into the soil through dung and urine return, leading to an increase in SOC [23]. Soil aggregates, as the basic units of soil structure [24], provide physical protection for the formation of SOC, maintaining the stability of the soil carbon pool [25]. Macroaggregates are considered temporary carbon stores, while microaggregates serve as permanent carbon stores and the main sites for carbon sequestration [26]. Microaggregates are more stable, with higher internal carbon content [27]. Studies have shown that macroaggregates are formed by the cementing of microaggregates, encapsulating organic matter inside, thus forming a physical protection mechanism that reduces mineralization and decomposition [28].
Many areas in Central Asia have arid or semi-arid climates, where pastoralism serves as a significant economic resource and plays a crucial role in maintaining ecological balance, cultural heritage, and social stability [29]. Currently, there are some studies on the impact of the three behaviors of grazing on SOC. Liu et al. [30] studied the effects of these three behaviors on soil carbon storage in typical grasslands, while Wei et al. [22] demonstrated that trampling is an important mechanism for SOC storage. Xinjiang, as one of China’s five major pastoral areas, features a rich variety of grassland types, with mountain meadows being an especially important part [31]. This study, based on a long-term simulated grazing experiment platform established in 2018, assesses the effects of the three behaviors of grazing on plant characteristics, soil physicochemical properties, and the composition and carbon–nitrogen content of soil aggregates, analyzing the relationships between plant, soil, and aggregate indicators and SOC and clarifying the main processes by which grazing influences SOC in mountain meadows, which is crucial for maintaining the carbon sequestration capacity of grassland ecosystems. Our hypotheses were as follows: (1) livestock mowing reduces plant aboveground biomass, which decreases SOC; (2) trampling damages the soil surface structure, causing wind and water erosion, which decreases SOC; (3) livestock return some nutrients to the soil through dung and urine, increasing SOC.

2. Materials and Methods

2.1. Study Site

The study area was located at the Xinjiang Academy of Animal Science’s Tianshan North Slope Grassland Ecological Environment Field Observation Research Station in Xiejia Gou, Nanshan, Urumqi County, Xinjiang, China (E 87°02′34″, N 43°28′60″), at an altitude of 1932 m. The grassland type in the region is mountain meadow steppe, falling under the category of a temperate continental climate. The average annual temperature in the study region is 1.8 °C, and the temperature can drop to minus 30 °C in January and 40 °C in July, which is an extreme continental climate in Central Asia. The main precipitation is concentrated in July, August, and September, with concurrent heat and rainfall when the summer is hot, resulting in extremely high evaporation [32]. According to the Köppen climate classification, the study region is located in the BWk zone. The soil type is chernozem, with an organic matter content of 74.60 g/kg. In this area, a simulated grazing experiment site was established. The main plants in this area are Alchemilla tianschanica, Geranium rotundifolium, Galium aparine, Potentilla chinensis, Elymus nutans, Achillea millefolium, Thalictrum aquilegifolium, Phleum pratense, and Bromus inermis.

2.2. Experimental Design

This experiment was based on a long-term simulated grazing experiment platform established in 2018. The experiment employed a three-factor factorial design, with the presence or absence of three grazing behaviors: mowing (M), trampling (T), and dung and urine return (D) as treatments [30]. The treatment were set up as follows: control (C), mowing (M), trampling (T), dung and urine addition (D), mowing + trampling (MT), dung and urine addition + trampling (DT), dung and urine addition + mowing (DM), and dung and urine addition + mowing + trampling (DMT). The control set up in the experiment was no grazing treatment, the grassland vegetation was in a natural growth state, and there was no grazing interference. There were eight treatment setups in total, with three replicates per treatment, making up 24 experimental plots. Each plot measured 2 m × 2 m, with a 1.5 m interval between plots. Based on the grazing intensity of the area, moderate grazing was practiced with simulated grazing treatments conducted in June, August, and September each year. In July, livestock were moved to high-altitude summer pastures for about a month, with no treatments applied (Table 1). The stubble height of the plants after cattle feed on grass is 5 cm, so we simulated the cattle feeding process and left the plants with a height of 5 cm to represent cattle grazing. Trampling was simulated by a person wearing “cow hoof” shoes, with the person’s body weight plus additional weights totaling 100 kg, to mimic the pressure of an adult cow’s hoof (65% of the pressure from a 306 kg cow), with a trampling density of 100 steps/m2, to ensure every point within the plot was trampled [33,34]. The breeds of grazing cattle in our study area were mainly native Kazakhs, which are medium to small. The weight of an adult cow is 300~600 kg, and the average weight of grazing cattle in the study area was about 306 kg. The mountain meadows have a high altitude and a large difference in climate, and Kazakh cattle are hardy to cold and rough feeding. The grazing intensity in this study area was 2 cattle units/hm2. Dung and urine addition involved using local cow dung and urine, with an application rate of 0.75 kg/m2 for dung and 2.25 L/m2 for urine, annually providing 52.5 g of carbon, 37.5 g of nitrogen, and 0.525 g of phosphorus per square meter [30,35].

2.3. Plant Sampling and Measurements

In mid-August 2023, during the peak growing period of plants, the characteristics of the plants on the grassland (species composition, height, coverage, density, and aboveground biomass) were surveyed using a 0.5 × 0.5 m2 sample plot. The plant coverage was estimated visually in each quadrat plot, and the height of each species was measured with a tape measure. Aboveground biomass was collected by cutting the plant at ground level, weighing the fresh weight, and then drying at 65 °C for 48 h until a constant weight was achieved, which was recorded as the dry weight of the plants, expressed per square meter of aboveground biomass. Based on plant composition, the plants were categorized into three functional groups: grasses, legumes, and forbs.

2.4. Soil Sampling and Measurements

After plant removal, within each experimental plot, soil bulk density was measured using a 100 cm3 ring cutter method. A five-point sampling method was used, where soil samples were taken from the top 0–10 cm layer using a 3.5 cm diameter soil auger, mixed into a single soil sample. Sampling points were placed 50 cm from the boundary to reduce edge effects. Fresh soil samples were sieved through a 2 mm mesh; about 10 g of soil was used for moisture content determination, and the remaining samples were air-dried in the lab for the soil parameter and aggregate size analysis.
Soil moisture content was determined by a gravimetric analysis [36]. Soil suspension (8 g of dry soil and 40 mL of deionized water shaken for 30 min, 200 rpm, then let stand for 30 min) were used to measure soil pH [37]. Soil organic carbon (SOC) was determined using the potassium dichromate–concentrated sulfuric acid external heating method [38], and total nitrogen (TN) was determined using the Nessler’s colorimetric method [39].

2.5. Soil Aggregate Screening and Analysis

Aggregates were determined using the wet sieving method [40] and separated into three size classes: 2–0.25 mm, 0.053–0.25 mm, and <0.053 mm, corresponding to macroaggregates, microaggregates, and silt and clay aggregates, respectively. We dried the soil aggregates at a constant weight at 60 °C, determined the weights of soil aggregates of different particle sizes, and calculated the percentage content of aggregates.
We determined the organic carbon and total nitrogen content of the macroaggregates, microaggregates, and silt and clay aggregates using the method described in Section 2.4.

2.6. Statistical Analysis

Prior to the statistical analysis, all data were tested for normality using Shapiro–Wilkinson’s test. Experimental data statistical analyses used IBM SPSS 26.0. A three-way ANOVA was used to test the main effects and interaction effects of each treatment, Duncan’s method was used for multiple comparisons, and an independent samples T-test was used to compare and analyze the indicators under different main effects. A plant diversity analysis was conducted by calculating four types of plant diversity indices [41,42,43,44]. These included the Margalef richness index (Ma), which measures species richness; the Simpson dominance index (D), which measures the dominance or concentration of species; the Shannon–Wiener diversity index (H), which describes species relative abundance independent of population density; and the Pielou evenness index (Jsw), which explains absolute numbers and measures the closeness in number among species.
Tables were created using Microsoft Word 2019, graphs were created with Graphpad Prism 8.0. Plant coverage, soil bulk density, soil total nitrogen, soil C/N, specific gravity of microaggregates, and organic carbon of macroaggregates were significantly correlated with SOC. In order to further analyze and discuss the effects of these six influencing factors and the other six main related factors (plant height, specific gravity of macroaggregates, specific gravity of silt and clay aggregates, organic carbon of microaggregates, organic carbon of silt and clay aggregates, and total nitrogen of macroaggregates) on SOC, a principal component analysis (PCA) was used. In the PCA diagram, the length and direction of the vector representing each variable represent how closely this variable is related to various treatments and axes. The angle between vectors represents the relationship between variables: <90° indicates a positively correlated relationship, and the smaller the angle, the higher the correlation; >90° indicates a negatively correlated relationship, and the larger the angle, the higher the correlation. If it is around 90°, it means that there is no relationship between the two. The correlation analysis and principal component analysis were conducted using Origin 2022. A redundancy analysis was carried out using Canoco 5.0. In the RDA analysis, vegetation, soil, and aggregate indicators were used as environmental variables, and SOC and TN were used as dependent variables.

3. Results

3.1. The Impact of Grazing on Plant Characteristics

M significantly reduced plant height (no M vs. M, −54.43%) and plant density (no M vs. M, −11.98%) (p < 0.001), and significantly increased plant coverage (no M vs. M, +3.16%) (p < 0.01). T had no significant effect on plant height, coverage, or density. D had no significant effect on plant height and coverage but significantly increased plant density (no D vs. D, +5.02%) (p < 0.05). There were significant interactive effects on plant coverage and density with the combined treatments of M + T, D + T, and D + M. The combination of D + M + T had a significant interactive effect on plant density (Figure 1A–C). All three grazing behaviors significantly reduced aboveground biomass (no M vs. M, −60.29%) (no T vs. T, −26.00%) (no D vs. D, −17.29%) (p < 0.001). There were also significant interactive effects between the combined treatments of the three behaviors (Figure 1D). Overall, the three grazing behaviors affected plant growth.
D significantly reduced the Margalef index of plant (p < 0.01) (no D vs. D, −12.86%). Other treatments had no significant effect on the Margalef index (Figure 2A). The three grazing behaviors had no significant effect on the Simpson index, Shannon–Wiener index, and Pielou index. Compared to C, the combined treatment of D, M, and T reduced the diversity indices of plant (Figure 2B–D). It is evident that the three grazing behaviors generally had no significant effect on plant diversity indices, but there was a trend of decreasing diversity.
As shown in Figure 3, compared to C, M increased the proportion of legumes and forbs and decreased the proportion of grasses. T increased the proportion of grasses and legumes and decreased the proportion of forbs. D increased the proportion of grasses and forbs and decreased the proportion of legumes.

3.2. The Impact of Grazing on Soil Physicochemical Properties

M and D significantly reduced soil moisture by 8.08% (p < 0.05) and 12.00% (p < 0.01), respectively. T had no significant effect on soil moisture. There were significant interactive effects on soil moisture for the combined treatments of M + T and D + M + T (Figure 4A). M significantly increased soil bulk density (no M vs. M, +3.51%), T significantly increased soil bulk density (no T vs. T, +9.28%), and D significantly decreased soil bulk density (no D vs. D, −7.93%). Significant interactions were observed for M + T and D + T (Figure 4B). M and T significantly reduced soil pH (no M vs. M, −1.64%; no T vs. T, −1.59%), while D significantly increased soil pH (no D vs. D, +1.32%). Significant interactions were observed among all three grazing behaviors (Figure 4C). M significantly reduced SOC (no M vs. M, −3.64%). T and D significantly increased SOC (no T vs. T, +3.17%) (no D vs. D, +9.74%). D combined with T and M had a significant interactive effect on SOC (Figure 4D). M and D significantly increased soil total nitrogen (no M vs. M, +4.27%) (no D vs. D, +12.00%). T had no significant effect on soil total nitrogen; all three combined behaviors had significant interactive effects, increasing the total nitrogen of the soil (Figure 4E). The three grazing behaviors all significantly reduced the soil carbon-to-nitrogen ratio (C/N) (no M vs. M, −9.75%; no T vs. T, −4.47%; no D vs. D, −3.51%), and there were significant interactions between the three behaviors (p < 0.001) (Figure 4F). In summary, the three grazing behaviors combined to reduce the soil C/N.

3.3. The Impact of Grazing on Soil Aggregate Composition

M and D significantly reduced the proportion of macroaggregates (no M vs. M, −13.62%) (no D vs. D, −4.22%). T significantly increased the proportion of macroaggregates (no T vs. T, +5.58%) (p < 0.01). The M + T, D + T, and D + M + T treatments showed significant interactive effects on the proportion of macroaggregates (Figure 5A). The three grazing behaviors all increased the proportion of microaggregates within soil aggregates (no M vs. M, +10.89%) (no T vs. T, +8.09%) (no D vs. D, +3.08%). M and T had a significant effect on the proportion of microaggregates in the soil (Figure 5B). M and D significantly increased the proportion of silt and clay aggregates within soil aggregates (no M vs. M, +26.10%) (no D vs. D, +4.22%). T significantly reduced the proportion of silt and clay aggregates in soil (no T vs. T, −14.02%) (p < 0.05) (Figure 5C). The combined treatment of the three behaviors had a significant interactive effect on the proportion of silt and clay aggregates in the soil. Overall, grazing affected the stability of the soil structure. Grazing significantly reduced the proportion of macroaggregates in the soil while markedly increasing the proportion of microaggregates and silt and clay aggregates (Figure 5D). Additionally, changes in the carbon and nitrogen content of soil aggregates may also occur.

3.4. Effects of Grazing on Organic Carbon, Total Nitrogen, and Carbon-to-Nitrogen Ratio of Soil Aggregates

M resulted in a significant decrease in the organic carbon across three different sizes of soil aggregates: a reduction of 5.46% in macroaggregates, 11.52% in microaggregates, and 5.46% in silt and clay aggregates. T significantly increased the organic carbon in microaggregates and silt and clay aggregates (no T vs. T, +14.16%) (no T vs. T, +10.44%). D significantly increased the organic carbon in macroaggregates (no D vs. D, +4.22%). The combined treatment with the three behaviors had a significant interactive effect on the organic carbon of macroaggregates. The combined treatment of D and M had a significant interactive effect on the organic carbon of microaggregates. The pairwise combined treatments with the three behaviors all had a significant interactive effect on the organic carbon of silt and clay aggregates (Figure 6A–C). Under the effect of M, the total nitrogen in soil aggregates of three different sizes significantly decreased, with a reduction of 13.47% in macroaggregates, 11.60% in microaggregates, and 3.43% in silt and clay aggregates. T significantly increased the total nitrogen in both macroaggregates and silt and clay aggregates (no T vs. T, +7.17%; no T vs. T, +8.55%). D significantly increased the total nitrogen in silt and clay aggregates (no D vs. D, +7.84%). The combined treatment of D and M did not have a significant interactive effect on the total nitrogen in macroaggregates and silt and clay aggregates. The combined treatment of M and T did not have a significant interactive effect on the total nitrogen in microaggregates. Other combined grazing factor treatments all had a significant interactive effect on the total nitrogen in soil aggregates (Figure 6D–F). M and D significantly increased the C/N of macroaggregates (no M vs. M, +8.32%) (no D vs. D, +7.68%). There was a significant interaction between M + T and D + M treatments. T significantly increased the C/N of microaggregates (no T vs. T, +13.30%). There was a significant interaction between the D + T and D + M treatments. D significantly reduced the C/N of silt and clay aggregates, and there was a significant interaction among the combined treatments with the three behaviors (Figure 6G–I). The C/N reflected the decomposition rate of organic matter in the soil.

3.5. The Relationships Between SOC and Plant, Soil, and Aggregate Indicators

As shown in Figure 7, the SOC was significantly negatively correlated with soil bulk density and positively correlated with soil total nitrogen, soil C/N, soil microaggregates’ gravity, and soil macroaggregates’ organic carbon. Plant coverage was significantly positively correlated with soil bulk density, negatively correlated with organic carbon and total nitrogen in macroaggregates, and negatively correlated with the C/N of silt and clay aggregates. Soil bulk density was negatively correlated with plant height, soil moisture, pH value, soil C/N, the specific gravity of soil macroaggregates, and organic carbon and positively correlated with the proportion of silt and clay aggregates. Soil total nitrogen was significantly negatively correlated with plant height and density, soil C/N, and the proportion of soil macroaggregates and positively correlated with the proportion of silt and clay aggregates. Soil C/N was significantly positively correlated with plant height, soil moisture, and total nitrogen of macroaggregates and negatively correlated with the specific gravity of silt and clay aggregates. The specific gravity of soil microaggregates was significantly negatively correlated with aboveground biomass and positively correlated with the organic carbon of soil macroaggregates and silt and clay aggregates. There was a significant positive correlation between the organic carbon of soil macroaggregates and the organic carbon of silt and clay aggregates and the total nitrogen of macroaggregates.

3.6. Principal Component Analysis Between SOC and Plant, Soil, and Aggregate Indicators

The correlation analysis showed that plant coverage, soil bulk density, soil total nitrogen, soil C/N, specific gravity of microaggregates, and organic carbon of macroaggregates were significantly correlated with SOC. From Figure 8 and Table 2, PC1, PC2, PC3, and PC4 explained 38.9%, 23.3%, 14.7%, and 9.7% of the change rates of all variables, respectively, and the cumulative contribution rate reached 86.6%. The results showed that M mainly affected plant coverage, soil bulk density, and the proportion of silt and clay aggregates; T mainly affected SOC, microaggregates gravity, macroaggregates’ organic carbon, total nitrogen, and silt and clay aggregates’ organic carbon; D mainly affected soil C/N and macroaggregates’ specific gravity, and SOC had a high correlation with macroaggregates’ organic carbon, silt and clay aggregates’ organic carbon, macroaggregates’ total nitrogen, and microaggregates’ specific gravity.

3.7. Redundancy Analysis Between SOC and Plant, Soil, and Aggregate Indicators

As shown in Figure 9, the redundancy analysis indicated that Axis 1 and Axis 2 explained 77.77% and 0.82%, respectively, of the variance in all variables. There were differences in the impact of the three grazing behaviors on each variable, with the proportion of microaggregates and the organic carbon of macroaggregates being the main influencing factors for SOC and the proportion of silt and clay aggregates being the main factor affecting the total nitrogen of the soil.

4. Discussion

Our study indicated that the three behaviors of grazing significantly affected SOC. Mowing reduced SOC, while dung and urine addition increased SOC, consistent with the initial hypothesis. Livestock mowing, which reduced plant aboveground biomass, led to a decrease in SOC, while the return of nutrients to the grassland through excretion of manure increased SOC. Trampling increased SOC, contrary to initial assumptions, suggesting that the impact of trampling on the structure of the soil surface in mountain meadows may differ from previous studies.

4.1. Effects of Grazing on Soil Organic Carbon

Grazing is one of the most important land use in grasslands, involve three mechanisms—defoliation (removal of plant shoot tissue), trampling, and dung and urine return, which alone or in combination affect the SOC [30,45]. SOC storage is determined by carbon inputs, which depend on aboveground biomass, litter, and animal excreta [46]. We found that mowing significantly reduced SOC, consistent with the first proposed hypothesis. Previous studies have indicated that during grazing, a large number of aboveground plants are consumed by livestock, which reduces the amount of litter and consequently decreases the input sources of SOC [47]. Livestock mowing also involves selective feeding and mechanisms such as saliva stimulating the regrowth of pasture grasses [48,49]. This study only studied three types of behaviors and their combined effects, but future research could explore selective mowing by livestock. Trampling significantly increased SOC, contrary to the second hypothesis proposed. Existing studies suggest that livestock trampling might destroy soil aggregates, leading to the decomposition of organic matter by microbes, thereby reducing SOC [50]. Moreover, livestock trampling results in a decrease in grassland plant cover and an increase in exposed soil area, leading to a rise in surface soil temperature [51]. Rising temperatures can affect the distribution of plant roots and mycorrhizal fungal communities in the soil, promoting the decomposition of SOC [52]. This may also accelerate the rate at which soil microbes transform SOC, thereby speeding up its decomposition [53]. Damage to the surface structure of the soil and a reduction in stable aggregates lead to wind erosion, which result in a decrease in the SOC of grasslands [54]. Some studies have shown that livestock trampling can accelerate the decomposition rate of plant litter, enhancing the accumulation of soil organic carbon [20]. Additionally, Liu et al. [30] demonstrated that trampling could increase SOC storage by promoting the allocation of plants to their belowground parts, which is consistent with the increase in SOC found in this study. When the soil bulk density exceeds 1.5 g/cm3, plant root growth is significantly hindered, and soil function deteriorates severely when it exceeds 1.8 g/cm3. Our research increased the bulk density of the soil to a certain extent, but it did not exceed 1 g/cm3 and did not cause soil degradation. In our results, dung and urine addition significantly increased SOC, in line with the third hypothesis proposed. The dung and urine excreted by livestock replenish the soil, enhancing the accumulation of SOC [55]. Livestock dung and urine also produce a large microbial biomass that increases the rate of nitrification, thereby enhancing the transfer of carbon to the soil carbon pool and increasing soil carbon storage [56]. Overall, the impact of the three grazing behaviors on SOC is multifactorial, influenced by a combination of plant community characteristics, soil physical and chemical properties, and soil aggregate structure.

4.2. Influencing Factors of Soil Organic Carbon Change

In grassland ecosystems, nearly 60% of the carbon absorbed by plant photosynthesis enters the soil through the root system, which is a key driving factor for SOC accumulation [57]. We found that mowing significantly reduced aboveground biomass, which may be due to the decrease in carbon input from aboveground plants to the soil. Some studies have shown that livestock mowing directly reduced the aboveground biomass and litter quantity of grasslands [58], resulting in less carbon input into the soil [59]. Mowing significantly reduced SOC, which is very likely related to the quantity of aboveground litter and its decomposition rate. In our study, the plant function group was significantly changed by mowing, the proportion of grasses decreased, the proportion of forbs increased, and the direct effect of mowing on the aboveground parts of plants reduced the growth advantage of tall grasses so that dwarf grasses received sufficient light and promoted the growth of weeds [60]. Changes in functional groups may lead to changes in belowground biomass [61]. A reduction in belowground biomass allows soil microbes to more effectively utilize root exudates for synthetic metabolism to form a stable carbon pool [62], increasing soil organic carbon [63]. The belowground biomass increases, microorganisms strengthen the decomposition of soil organic matter to meet nutrient demands, resulting in decreased soil organic carbon [64]. Therefore, the reduction in SOC due to mowing may be attributed to a decrease in belowground biomass.
Compared with mowing, trampling has the characteristics of a long action time, wide range, and long duration. Trampling directly contacts grassland soil, breaking up litter, facilitating the mixing of litter with soil, accelerating microbial utilization of carbon from litter, and stabilizing carbon in the soil [65]. Trampling can alter the structure of soil aggregates, causing the breakdown of macroaggregates, which may expose the encapsulated particulate organic carbon and mineral-bound organic carbon, increasing the likelihood of decomposition [18]. In our study, trampling significantly increased the proportion of large soil aggregates. While isolated trampling reduced macroaggregates, the combined effects increased it overall, possibly due to the moderate grazing implemented in this study. Light or moderate grazing can increase the mass fraction of large aggregates [66]. Moderate grazing increases root biomass, thereby enhancing microbial activity and turnover [67]. Microbial cells contain charged colloidal substances that can attach to soil particles through electrostatic forces. Bacterial fimbriae and fungal hyphae can entangle soil particles, facilitating the formation of macroaggregates [67]. An increase in macroaggregates may protect more particulate organic carbon and mineral-associated organic carbon. In this study, trampling significantly increased the organic carbon content in both soil microaggregates and silt–clay aggregates, thereby increasing the total soil organic carbon.
Livestock excreta is a source of active carbon for the soil [68], increasing the mineral nutrients and SOC in grassland [69]. The dung and urine return leads to an increase in microbial biomass and enhanced microbial activity [70]. This can enhance the decomposition and turnover rate of SOC, reducing SOC. Our study showed that dung and urine addition significantly increased SOC. The correlation analysis showed that SOC was significantly positively correlated with total soil nitrogen and the C/N ratio, while the return of manure significantly increased total soil nitrogen and reduced the soil’s C/N ratio. Nutrient input may increase the nitrogen content in litter, thereby reducing its C/N ratio, which enhances the decomposition of the litter [71], leading to an increase in SOC. An increase in nitrogen can affect plant growth and soil nutrients, and most research confirms that various growth indicators of plants increase with the supply of nitrogen [72]. In this study, the return of manure increased the proportion of grasses, reduced the proportion of miscellaneous grasses, significantly decreased the Margalef index of vegetation, and reduced vegetation diversity. The application of dung and urine introduces a large amount of nitrogen, and the addition of nitrogen reduces plant community diversity [73,74], consistent with the results of this study. Compared to the control, the three grazing behaviors studied had no significant effect on plant diversity. The experiment employed moderate grazing, and the impact on plant diversity may take 5–10 years or even longer to stabilize. Moreover, moderate grazing is beneficial for plant growth, as the positive and negative effects of grazing, trampling, and manure return counterbalance each other, resulting in relatively stable plant growth. Therefore, long-term monitoring and research are necessary to more accurately understand the effects of grazing on ecosystems. Previous studies have found that the effects of grazing on grassland’s soil organic carbon sequestration in three ways, mowing, trampling, and dung and urine addition, are different; some promote each other, and some have opposite effects, indicating that the impact of grazing on grassland soil carbon sequestration is the result of a balance of multiple factors. By dividing the mode of action of grazing (mowing, trampling, and dung and urine addition), we aimed to clearly elucidate the process mechanisms behind the changes in soil carbon in the mountain meadows of Xinjiang caused by grazing.

5. Conclusions

Mowing significantly reduced plant height, density, and aboveground biomass and significantly decreased SOC. Trampling significantly increased soil bulk density, the proportion of macroaggregates, and the organic carbon of microaggregates and silt and clay aggregates, significantly increasing SOC. Dung and urine addition significantly increased plant density, total soil nitrogen, and the organic carbon of macroaggregates, significantly increasing SOC. The proportion of microaggregates and the organic carbon of macroaggregates were the main factors influencing SOC. SOC responded differently to three types of grazing behaviors. Dung and urine addition primarily increased the organic carbon in macroaggregates, while trampling mainly enhanced the organic carbon in microaggregates and silt and clay aggregates, thereby affecting the organic carbon content in mountain meadow soils.

6. Patents

In this study, a utility model patent was generated during the experiment: Shuzhen Zhang, et al. A portable field simulation trampling device. CN218847869U. 11 April 2023.

Author Contributions

Conceptualization, W.L. and S.Z.; methodology, W.L., M.A., X.H. and J.X.; data analysis and visualization, W.L., M.W., X.W. and R.L.; writing—original draft preparation, W.L. and S.Z.; experimental procedure guidance, Q.S. and G.J.; all authors contributed to the writing—review and editing. All authors have read and agreed to the published version of the manuscript

Funding

The present work was supported by the China Agriculture Research System of MOF and MARA (CARS34); Key Research and Development Program of the Xinjiang Uygur Autonomous Region (2023B02031); 2023 Central Finance Forest and Grass Science and Technology Promotion Demonstration Project (Xin2023TG18).

Informed Consent Statement

All authors have read and agreed to the published version of the manuscript.

Data Availability Statement

The data that support the findings of this study are available from the corresponding author, S.Z., upon reasonable request.

Acknowledgments

We sincerely thank Yongqi Wang, Wanning Xu, Ying Wang, and all the students from the research group for their assistance during the field experiments.

Conflicts of Interest

The authors declare that they have no known competing financial interests or personal relationships that could have influenced the work reported in this paper.

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Figure 1. Effects of three grazing behaviors on plant height (A), coverage (B), density (C), and aboveground biomass (D). Note: C represents control, M represents mowing, T represents trampling, D represents dung and urine addition, MT represents mowing + trampling, DT represents dung and urine addition + trampling, DM represents dung and urine addition + mowing, and DMT represents dung and urine addition + mowing + trampling. The ns, #, *, **, and *** symbols represent p > 0.1, p < 0.1, p < 0.05, p < 0.01, and p < 0.001, respectively.
Figure 1. Effects of three grazing behaviors on plant height (A), coverage (B), density (C), and aboveground biomass (D). Note: C represents control, M represents mowing, T represents trampling, D represents dung and urine addition, MT represents mowing + trampling, DT represents dung and urine addition + trampling, DM represents dung and urine addition + mowing, and DMT represents dung and urine addition + mowing + trampling. The ns, #, *, **, and *** symbols represent p > 0.1, p < 0.1, p < 0.05, p < 0.01, and p < 0.001, respectively.
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Figure 2. Effects of three grazing behaviors on Margalef index (A), Simpson index (B), Shannon–Wiener index (C), and Pielou index (D). Note: C represents control, M represents mowing, T represents trampling, D represents dung and urine addition, MT represents mowing + trampling, DT represents dung and urine addition + trampling, DM represents dung and urine addition + mowing, DMT represents dung and urine addition + mowing + trampling. The ns, #, and ** symbols represent p > 0.1, p < 0.1, and p < 0.01, respectively.
Figure 2. Effects of three grazing behaviors on Margalef index (A), Simpson index (B), Shannon–Wiener index (C), and Pielou index (D). Note: C represents control, M represents mowing, T represents trampling, D represents dung and urine addition, MT represents mowing + trampling, DT represents dung and urine addition + trampling, DM represents dung and urine addition + mowing, DMT represents dung and urine addition + mowing + trampling. The ns, #, and ** symbols represent p > 0.1, p < 0.1, and p < 0.01, respectively.
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Figure 3. Proportion of different plant functional groups.
Figure 3. Proportion of different plant functional groups.
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Figure 4. Effects of three grazing behaviors on physicochemical properties. (A) soil moisture, (B) soil bulk density, (C) soil pH, (D) soil organic carbon (SOC), (E) soil total nitrogen (TN), (F) carbon-to-nitrogen radio (C/N). Note: C represents control, M represents mowing, T represents trampling; D represents dung and urine addition, MT represents mowing + trampling, DT represents dung and urine addition + trampling, DM represents dung and urine addition + mowing, DMT represents dung and urine addition + mowing + trampling. The ns, *, **, and *** symbols represent p > 0.1, p < 0.05, p < 0.01, and p < 0.001, respectively.
Figure 4. Effects of three grazing behaviors on physicochemical properties. (A) soil moisture, (B) soil bulk density, (C) soil pH, (D) soil organic carbon (SOC), (E) soil total nitrogen (TN), (F) carbon-to-nitrogen radio (C/N). Note: C represents control, M represents mowing, T represents trampling; D represents dung and urine addition, MT represents mowing + trampling, DT represents dung and urine addition + trampling, DM represents dung and urine addition + mowing, DMT represents dung and urine addition + mowing + trampling. The ns, *, **, and *** symbols represent p > 0.1, p < 0.05, p < 0.01, and p < 0.001, respectively.
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Figure 5. Effects of three grazing behaviors on soil aggregate composition. Note: In the figure, (A) represents the mass fraction of macroaggregates, (B) represents the mass fraction of microaggregates, (C) represents the mass fraction of silt and clay aggregates, (D) represents the mass fraction of aggregates with three particle sizes. C represents control, M represents mowing, T represents trampling; D represents dung and urine addition, MT represents mowing + trampling, DT represents dung and urine addition + trampling, DM represents dung and urine addition + mowing, DMT represents dung and urine addition + mowing + trampling. The ns, *, **, and *** symbols represent p > 0.1, p < 0.05, p < 0.01, and p < 0.001, respectively.
Figure 5. Effects of three grazing behaviors on soil aggregate composition. Note: In the figure, (A) represents the mass fraction of macroaggregates, (B) represents the mass fraction of microaggregates, (C) represents the mass fraction of silt and clay aggregates, (D) represents the mass fraction of aggregates with three particle sizes. C represents control, M represents mowing, T represents trampling; D represents dung and urine addition, MT represents mowing + trampling, DT represents dung and urine addition + trampling, DM represents dung and urine addition + mowing, DMT represents dung and urine addition + mowing + trampling. The ns, *, **, and *** symbols represent p > 0.1, p < 0.05, p < 0.01, and p < 0.001, respectively.
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Figure 6. Effects of three grazing behaviors on organic carbon, total nitrogen, and carbon-to-nitrogen ratio of soil aggregates. (A) Macroaggregates’ SOC, (B) microaggregates’ SOC, (C) silt and clay aggregates’ SOC, (D) macroaggregates’ TN, (E) microaggregates’ TN, (F) silt and clay aggregates’ TN, (G) macroaggregates’ C/N, (H) microaggregates’ C/N, (I) silt and clay aggregates’ C/N. The ns, *, **, and *** symbols represent p>0.1, p < 0.05, p < 0.01, and p < 0.001, respectively.
Figure 6. Effects of three grazing behaviors on organic carbon, total nitrogen, and carbon-to-nitrogen ratio of soil aggregates. (A) Macroaggregates’ SOC, (B) microaggregates’ SOC, (C) silt and clay aggregates’ SOC, (D) macroaggregates’ TN, (E) microaggregates’ TN, (F) silt and clay aggregates’ TN, (G) macroaggregates’ C/N, (H) microaggregates’ C/N, (I) silt and clay aggregates’ C/N. The ns, *, **, and *** symbols represent p>0.1, p < 0.05, p < 0.01, and p < 0.001, respectively.
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Figure 7. Correlation analysis among the plant, soil, and aggregate indicators. Note: The smaller the shape size, the stronger the correlation. Height: plant height; Coverage: plant coverage; Density: plant density; Biomass: aboveground biomass; Mar: Margalef index; Sim: Simpson index; Sha: Shannon–Wiener index; Pie: Pielou index; SM: soil moisture; BD: bulk density; SOC: soil organic carbon; TN: total nitrogen; C/N: carbon nitrogen radio; MaA: macroaggregates; MiA: microaggregates; SA: silt and clay aggregates; MaA_SOC: macroaggregates’ soil organic carbon; MiA_SOC: macroaggregates’ soil organic carbon; SA_SOC: silt and clay aggregates’ soil organic carbon; MaA_TN: macroaggregates’ total nitrogen; MiA_TN: microaggregates’ total nitrogen; SA_TN: silt and clay aggregates’ total nitrogen; MaA_C/N: macroaggregates’ carbon–nitrogen ratio; MiA_C/N: microaggregates’ carbon–nitrogen ratio; SA_C/N: silt and clay aggregates’ carbon–nitrogen ratio.
Figure 7. Correlation analysis among the plant, soil, and aggregate indicators. Note: The smaller the shape size, the stronger the correlation. Height: plant height; Coverage: plant coverage; Density: plant density; Biomass: aboveground biomass; Mar: Margalef index; Sim: Simpson index; Sha: Shannon–Wiener index; Pie: Pielou index; SM: soil moisture; BD: bulk density; SOC: soil organic carbon; TN: total nitrogen; C/N: carbon nitrogen radio; MaA: macroaggregates; MiA: microaggregates; SA: silt and clay aggregates; MaA_SOC: macroaggregates’ soil organic carbon; MiA_SOC: macroaggregates’ soil organic carbon; SA_SOC: silt and clay aggregates’ soil organic carbon; MaA_TN: macroaggregates’ total nitrogen; MiA_TN: microaggregates’ total nitrogen; SA_TN: silt and clay aggregates’ total nitrogen; MaA_C/N: macroaggregates’ carbon–nitrogen ratio; MiA_C/N: microaggregates’ carbon–nitrogen ratio; SA_C/N: silt and clay aggregates’ carbon–nitrogen ratio.
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Figure 8. Principal component analysis.
Figure 8. Principal component analysis.
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Figure 9. Redundancy analysis. Note: The red arrows indicate the impact factor, and the blue solid arrows indicate soil organic carbon and total nitrogen; different icons represent different treatments, C represents control, M represents mowing, T represents trampling; D represents dung and urine addition, MT represents mowing + trampling, DT represents dung and urine addition + trampling, DM represents dung and urine addition + mowing, DMT represents dung and urine addition + mowing + trampling. The angle between the lines and the ordination axes indicates the degree of correlation between the factor and the axis, the angle between lines represents the correlation between different factors, and the length of the line ends represents the significance of the factor.
Figure 9. Redundancy analysis. Note: The red arrows indicate the impact factor, and the blue solid arrows indicate soil organic carbon and total nitrogen; different icons represent different treatments, C represents control, M represents mowing, T represents trampling; D represents dung and urine addition, MT represents mowing + trampling, DT represents dung and urine addition + trampling, DM represents dung and urine addition + mowing, DMT represents dung and urine addition + mowing + trampling. The angle between the lines and the ordination axes indicates the degree of correlation between the factor and the axis, the angle between lines represents the correlation between different factors, and the length of the line ends represents the significance of the factor.
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Table 1. Simulated grazing experimental treatment times.
Table 1. Simulated grazing experimental treatment times.
Simulate Grazing Time/Year201820192020202120222023
First15 June 18 June 15 June 15 June 16 June 18 June
Second1 August 3 August 1 August 1 August 2 August 3 August
Third1 September 2 September1 September2 September1 September2 September
Table 2. Eigenvectors of each index in each principal component.
Table 2. Eigenvectors of each index in each principal component.
ProgramEigenvalue
PCA1PCA2PCA3PCA4
SOC0.2730.271−0.3430.033
Height0.286−0.2470.206−0.371
Coverage−0.290−0.2310.0280.408
BD−0.2910.0130.3520.392
TN−0.0620.5220.012−0.092
C/N0.316−0.222−0.3230.091
MaA0.292−0.384−0.0330.168
MiA0.1770.307−0.2470.553
SA−0.3200.3170.080−0.271
MaA_SOC0.3360.288−0.076−0.102
MiA_SOC0.265−0.0150.4950.016
SA_SOC0.2850.2080.3660.326
MaA_TN0.2950.1480.396−0.007
Eigenvalue5.0593.0321.9051.260
Contributions38.91723.32114.6559.690
Cumulative contribution38.91762.23876.89386.582
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Li, W.; Sun, Q.; Zhang, S.; Hu, X.; Asiya, M.; Xiong, J.; Wang, M.; Wang, X.; Long, R.; Jin, G. Trampling and Dung and Urine Addition of Livestock Increase the Soil Organic Carbon in Mountain Meadows by Augmenting the Organic Carbon in Different Aggregates. Agronomy 2025, 15, 843. https://doi.org/10.3390/agronomy15040843

AMA Style

Li W, Sun Q, Zhang S, Hu X, Asiya M, Xiong J, Wang M, Wang X, Long R, Jin G. Trampling and Dung and Urine Addition of Livestock Increase the Soil Organic Carbon in Mountain Meadows by Augmenting the Organic Carbon in Different Aggregates. Agronomy. 2025; 15(4):843. https://doi.org/10.3390/agronomy15040843

Chicago/Turabian Style

Li, Weisi, Qunce Sun, Shuzhen Zhang, Xiaojing Hu, Manlike Asiya, Jie Xiong, Mengyue Wang, Xuerui Wang, Runzhou Long, and Guili Jin. 2025. "Trampling and Dung and Urine Addition of Livestock Increase the Soil Organic Carbon in Mountain Meadows by Augmenting the Organic Carbon in Different Aggregates" Agronomy 15, no. 4: 843. https://doi.org/10.3390/agronomy15040843

APA Style

Li, W., Sun, Q., Zhang, S., Hu, X., Asiya, M., Xiong, J., Wang, M., Wang, X., Long, R., & Jin, G. (2025). Trampling and Dung and Urine Addition of Livestock Increase the Soil Organic Carbon in Mountain Meadows by Augmenting the Organic Carbon in Different Aggregates. Agronomy, 15(4), 843. https://doi.org/10.3390/agronomy15040843

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