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Article

Interannual Variability in Precipitation Modulates Grazing-Induced Vertical Translocation of Soil Organic Carbon in a Semi-Arid Steppe

by
Siyu Liu
1,
Xiaobing Li
1,2,*,
Mengyuan Li
1,
Xiang Li
1,
Dongliang Dang
1,3,
Kai Wang
1,
Huashun Dou
1 and
Xin Lyu
1
1
State Key Laboratory of Earth Surface Processes and Disaster Risk Reduction, Faculty of Geographical Science, Beijing Normal University, No. 19, XinJieKouWai St., HaiDian District, Beijing 100875, China
2
School of Geography and Tourism, Shaanxi Normal University, Xi’an 710119, China
3
School of Environment, Beijing Normal University, Beijing 100875, China
*
Author to whom correspondence should be addressed.
Agronomy 2025, 15(8), 1839; https://doi.org/10.3390/agronomy15081839
Submission received: 7 July 2025 / Revised: 27 July 2025 / Accepted: 28 July 2025 / Published: 29 July 2025
(This article belongs to the Topic Carbon and Nitrogen Cycling in Agro-Ecosystems and Other Anthropogenically Maintained Ecosystems—2nd Edition)
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Abstract

Grazing affects soil organic carbon (SOC) through plant removal, livestock trampling, and manure deposition. However, the impact of grazing on SOC is also influenced by multiple factors such as climate, soil properties, and management approaches. Despite extensive research, the mechanisms by which grazing intensity influences SOC density in grasslands remain incompletely understood. This study examines the effects of varying grazing intensities on SOC density (0–30 cm) dynamics in temperate grasslands of northern China using field surveys and experimental analyses in a typical steppe ecosystem of Inner Mongolia. Results show that moderate grazing (3.8 sheep units/ha/yr) led to substantial consumption of aboveground plant biomass. Relative to the ungrazed control (0 sheep units/ha/yr), aboveground plant biomass was reduced by 40.5%, 36.2%, and 50.6% in the years 2016, 2019, and 2020, respectively. Compensatory growth failed to fully offset biomass loss, and there were significant reductions in vegetation carbon storage and cover (p < 0.05). Reduced vegetation cover increased bare soil exposure and accelerated topsoil drying and erosion. This degradation promoted the downward migration of SOC from surface layers. Quantitative analysis revealed that moderate grazing significantly reduced surface soil (0–10 cm) organic carbon density by 13.4% compared to the ungrazed control while significantly increasing SOC density in the subsurface layer (10–30 cm). Increased precipitation could mitigate the SOC transfer and enhance overall SOC accumulation. However, it might negatively affect certain labile SOC fractions. Elucidating the mechanisms of SOC variation under different grazing intensities and precipitation regimes in semi-arid grasslands could improve our understanding of carbon dynamics in response to environmental stressors. These insights will aid in predicting how grazing systems influence grassland carbon cycling under global climate change.

1. Introduction

Soil is the largest terrestrial carbon pool with more carbon than aboveground vegetation and the atmosphere combined. Soil organic carbon (SOC) accounts for approximately 62% of total soil carbon and plays a crucial role in mitigating rising atmospheric CO2 concentrations [1,2,3]. SOC is the result of a dynamic equilibrium between inputs of exogenous organic matter (primarily litter, roots, and microbial residues) and outputs of existing SOC due to decomposition, leaching, and erosion [4]. SOC serves as a key indicator of grassland soil quality and vegetation health. Due to high background levels and natural soil variability, short-term and medium-term SOC changes from management practices are often difficult to detect. In contrast, labile SOC fractions that participate directly in biochemical reactions can serve as sensitive early indicators of management impacts on soil quality [5,6,7]. Moreover, monitoring labile SOC fractions can help predict future changes in total SOC [8].
Grasslands constitute a vital component of terrestrial ecosystems, and they cover approximately 40% of Earth’s land surface and 69% of agricultural land. Nearly half of this land is utilized for grazing [9,10,11]. As one of the most widespread grassland management strategies globally, grazing significantly alters carbon cycling by modifying vegetation structure and soil properties [12]. Grazing can stimulate plant growth and enhance the allocation of carbon to belowground biomass, thereby increasing soil carbon sequestration from the atmosphere. The carbon is typically stored in the soil as mineral-associated organic carbon [12,13,14]. Concurrently, manure and urine deposition increase soil organic matter by stimulating microbial activity, enhancing nutrient availability, and promoting plant growth [15,16]. However, grazing can also negatively impact SOC by directly reducing the net primary productivity of plants and indirectly decreasing carbon inputs from aboveground litter [12]. Overgrazing can easily exacerbate soil erosion and reduce carbon storage [17]. It has been estimated that approximately half of the natural grasslands worldwide have experienced some degradation [9,18]. Globally, overgrazing is now recognized as a major driver of grassland degradation and soil carbon loss [14,19]. Therefore, balancing grazing management to optimize its effects on SOC density is critical.
Studies have presented conflicting findings on the impact of grazing on soil carbon. There have been reports that grazing could increase carbon storage [20,21], while other studies found the opposite [22,23]. Some research suggests that grazing has no significant effect on soil carbon [24]. These contradictions highlight the complex nature of grazing impacts on SOC. These impacts are mediated by grassland type, environmental factors (e.g., precipitation, soil type, and soil depth), and management practices (e.g., grazing intensity and grazing duration) [12,16,17]. Precipitation is a particularly important water source for arid and semi-arid ecosystems, directly affecting soil moisture and exerting significant direct and indirect effects on biogeochemical cycles [25,26,27,28].
Despite numerous individual studies and meta-analyses, our understanding of how grazing intensity affects grassland SOC still remains incomplete and requires further investigation [29,30]. We conducted a three-year study in a typical steppe ecosystem within Inner Mongolia using plots with varying grazing intensities. Our objectives were to (1) examine how grazing intensity affects SOC and its labile fractions and (2) understand the role of precipitation change in modifying grazing effects on SOC. Therefore, we monitored vegetation and SOC dynamics across soil depths through field surveys and laboratory analyses while concurrently gathering precipitation data. We hypothesized that (1) moderate grazing would enhance labile SOC fractions, (2) moderate grazing would potentially have detrimental effects on the accumulation of SOC, and (3) increased precipitation would amplify grazing-induced SOC accumulation.

2. Materials and Methods

2.1. Study Site Description

The study site is located in the Chaoke Wula Sumu region, Xilinhot, Xilin Gol League, Inner Mongolia (44°15″ N, 116°32″ E), at an elevation range of 1111–1121 m. The dominant soil type is chestnut soil, and the plant growing season spans from May to September [31]. The vegetation is typical of a steppe ecosystem and is primarily dominated by Stipa grandis, Stipa krylovii, and Leymus chinensis.
The region has a typical continental monsoon climate that is characterized by dry, cold winters and humid, warm summers. Annual precipitation ranges from 350 to 450 mm, with approximately 80% occurring between May and September [11,32]. During the study period, annual precipitation was measured as 308.4 mm (2016), 293.5 mm (2019), and 389.8 mm (2020) (Figure 1). Based on the 60-year mean annual precipitation of 283.6 mm and applying the precipitation year-type classification system developed by Zhang et al. [33], the years 2016 and 2019 were identified as normal precipitation years, whereas 2020 was categorized as a high-precipitation year. The temperature and precipitation data are all observed measurements from China’s national surface meteorological stations (https://data.cma.cn/data/detail/dataCode/A.0019.0001.S001.html (accessed on 29th July 2025).

2.2. Experimental Design

This study was conducted in a controlled grazing experimental platform established by the Grassland Research Institute of the Chinese Academy of Agricultural Sciences. The experimental site was excluded from grazing from 2007 to 2013 and used as a mowing pasture, and vegetation thrived during this period. Through several years of pretreatment, we ensured that all selected plots exhibited comparable vegetation cover, species composition, and soil properties prior to the initiation of grazing experiments [7]. This grazing experiment was initiated in 2014 using 2-year-old Ujumqin wethers (a local sheep breed) with an average body weight of 31.5 kg. The trial design confined sheep to designated grazing plots during the experimental period, which commenced annually on June 10th and continued for 90 days.
The experiment used 15 fenced grazing plots (each 1.33 ha) that were arranged in three randomized blocks. Within each block, five grazing intensity treatments were randomly assigned. The five grazing treatments were as follows: no grazing as control (CK, 0 sheep units/ha/yr), light grazing with 4 sheep (LG, 1.9 sheep units/ha/yr), moderate grazing with 8 sheep (MG, 3.8 sheep units/ha/yr), heavy grazing with 12 sheep (HG, 5.7 sheep units/ha/yr), and extremely heavy grazing with 16 sheep (EHG, 7.6 sheep units/ha/yr). Due to the Grassland Ecological Subsidy Policy of China, current grazing management in Xilinhot rarely reaches heavy grazing levels [34]. Thus, this study focused only on the CK, LG, and MG treatments. Field trials for our study were carried out in 2016, 2019, and 2020. The grazing experiment was conducted annually throughout the study period, with consistent grazing intensity maintained across all experimental plots each year.

2.3. Plant Sampling and Analysis

The data for this study were collected during the peak growing season (mid-July). Data collected during 2016 were sourced from Zhang et al. [7]. Following the same experimental design, we employed an identical sampling approach to that of Zhang et al. [7] to guarantee the comparability of the obtained data. During the annual peak growing season, three 1 m × 1 m quadrats were established in each experimental plot. We collected all aboveground biomass (AGB) in the quadrats and then oven-dried the samples at 65 °C for 48 h to constant weight. We used an element analyzer (CN 802, VELP, Usmate, Italy) to measure the carbon content of the aboveground plants.

2.4. Soil Sampling and Analysis

The data for this study were collected during the peak growing season (mid-July). Data collected during 2016 were sourced from Zhang et al. [7]. Following the same experimental design, we employed an identical sampling approach to that of Zhang et al. [7] to guarantee the comparability of the obtained data. Soil samples were randomly collected at 0–10 cm, 10–20 cm, and 20–30 cm depths in each quadrat using a soil auger. The three samples from each quadrat were homogenized with a total of 81 composite soil samples per year. Each composite sample was divided into two subsamples. One subsample was air-dried at room temperature and was passed through a 2 mm-diameter sieve to remove roots and stones. This subsample was used to measure soil pH, SOC, and particulate organic carbon (POC). The other subsample was stored at 4 °C for later analysis of microbial biomass carbon (MBC), dissolved organic carbon (DOC), and potentially mineralizable carbon (PMC).
SOC was measured using an element analyzer (CN 802, VELP, Usmate, Italy). We determined the MBC content using the chloroform fumigation method [35]. POC content was measured using the method of Zhang et al. [7]. PMC and DOC contents were determined using the methods of Xu et al. [8]. We calculated soil organic carbon density (SOCD) using the measured SOC content and the formula proposed by Ellert and Bettany [36]:
SOCD = SOCC × BD × H × 10,000 cm2/m2 × 0.001 g/mg
where SOCD is the soil organic carbon density (g/m2); SOCC is the soil organic carbon content (mg/g); BD is the soil bulk density (g/cm3); and H is the soil depth (cm).
We used the cutting-ring method to determine the soil bulk density (BD) and soil water content (SWC). We collected undisturbed soil columns (100 cm3) at 0–10 cm, 10–20 cm, and 20–30 cm depths in each quadrat after removing the surface litter layer. We then weighed the fresh collected soil columns (W1). Finally, we oven-dried the samples at 105 °C to constant weight (W2). The calculation formulae are as follows:
SWC = (W1 − W2)/W2 × 100%
BD = W2/100 cm3

2.5. Data Analysis

All data were analyzed using IBM SPSS Statistics 20 (SPSS Inc., Chicago, IL, USA), and figures were generated using Origin 2022. Selected raw data were log-transformed to improve normality and linearity before analysis, because not all data were normally distributed. Then, we used a one-way analysis of variance (ANOVA) followed by Tukey’s test to analyze vegetation characteristics and soil properties across three soil depths under different grazing intensities. Additionally, Pearson correlation analysis was conducted to assess inter-variable relationships, providing the basis for structural equation modeling. Statistical significance was assessed at p = 0.05.
Structural equation modeling (SEM) was employed to examine the direct and indirect effects of precipitation and grazing intensity on SWC, soil pH, and soil carbon density [16]. A full-path model was initially constructed using maximum likelihood estimation. To optimize the model fit and parsimony, non-significant paths were sequentially removed until the model exhibited a good fit, as evaluated by the chi-square/degrees of freedom ratio (χ2/df), model p-value, goodness-of-fit index (GFI), and root mean square error of approximation (RMSEA). SEM was performed using IBM SPSS Amos 24.0 (IBM Corp., Armonk, NY, USA).

3. Results

3.1. Aboveground Biomass (AGB) and AGB Carbon Density

AGB showed a gradual decrease with increasing grazing intensity. In both 2016 and 2020, MG resulted in significantly lower AGB than LG and CK (p < 0.05). A 40–50% decrease in AGB was observed under MG relative to the CK. No significant difference was observed between LG and CK (p > 0.05). However, the difference between LG and MG in 2019 was not statistically significant (Figure 2a). The AGB carbon density followed an identical pattern to AGB across grazing intensities (Figure 2b).

3.2. Labile SOC Fractions

Grazing intensity had no significant effect on POC density in surface soil (0–10 cm) (p > 0.05). POC density generally increased with grazing intensity. In the 10–20 cm layer, during 2019 and 2020, MG showed significantly higher POC density than the CK (p < 0.05; Figure 3b). In 2020, POC density in moderately grazed plots (1036.10 g/m2) was nearly 60% higher than in control plots (650.63 g/m2) in the 20–30 cm layer (p < 0.05; Figure 3c).
The effects of grazing intensity on MBC density varied across years. In 2016 and 2019, surface soil MBC density increased with grazing intensity. MG (58.81 g/m2) exhibited significantly higher values than CK (41.27 g/m2) in 2019 (p < 0.05). In 2020, surface MBC density decreased with increasing grazing intensity (Figure 4a). During 2019, MBC density showed a nearly 40% increase under MG relative to CK in the 10–20 cm soil layer (p < 0.05; Figure 4b). However, MBC density in 2020 initially increased and then decreased as grazing intensity increased with a peak under LG (Figure 4c).
The results of the analysis of variance indicate that the impacts of different grazing intensities on soil PMC and DOC were relatively limited. In the 10–30 cm layer, PMC density was significantly higher under MG than under LG only in 2016 (p < 0.05; Figure 5b,c). In the 20–30 cm layer, during 2016, DOC density was significantly lower under MG than under LG (p < 0.05; Figure 6c).

3.3. Total Soil Organic Carbon (SOC)

Overall, grazing exhibited limited effects on total SOC density in this study. Statistical analysis showed that grazing intensity did not significantly influence SOC density in the 0–20 cm soil layer (p > 0.05). In 2016, MG significantly increased SOC density in the 20–30 cm layer compared to LG (Figure 7c). Relative to CK, LG showed higher SOC proportions in the 0–10 cm layer, while MG showed greater proportions in the 10–30 cm layer (Figure 8).
While SOC density typically decreased with soil depth, the 10–20 cm layer under MG in 2019 maintained an SOC density similar to that of surface soil. Notably, MG enhanced the SOC proportion in the 20–30 cm layer to 32.143%, representing a ~15% increase relative to both control (27.953%) and light grazing treatments (27.357%) (Figure 8b). These results may suggest potential downward translocation of SOC.

3.4. The Direct and Indirect Effects of Predictor Variables on SOC Density

The structural equation model revealed that all predictor variables collectively explained 35% of the variation in surface SOC density (R2 = 0.35; Figure 9a). Soil water content, POC, and DOC exhibited significant direct positive effects on SOC density (Figure 9a). Precipitation exerted an indirect positive effect on SOC via SWC, but it exhibited an indirect negative effect via POC. Grazing intensity had an indirect negative effect on surface SOC via its impact on SWC. In contrast, grazing intensity showed an indirect positive effect on SOC in the 10–20 cm layer. While its effect on SWC diminished, grazing intensity positively influenced POC by altering soil pH. This resulted in an increase in SOC (Figure 9b). Similar to the surface soil, SOC in the 10–20 cm layer responded positively to precipitation changes (Table 1).

4. Discussion

4.1. Effects of Grazing Intensity on AGB and Carbon Density

Grazing livestock directly impacts surface vegetation through foraging activities. Existing studies showed divergent findings. While some studies reported decreased AGB in grazed grasslands [37,38], others suggest that grazing may enhance net primary productivity [39]. Research in our study region indicated that grazing significantly increases annual primary productivity, with maximum values under moderate grazing [40]. Our results show significantly reduced residual AGB under MG compared to that under CK (Figure 2a). While compensatory plant growth following herbivory can enhance productivity, intensive grazing often exceeds this compensation capacity [41,42]. We found a strong positive correlation between aboveground carbon density and biomass (Figure S1). This explains why MG showed significantly lower carbon density than CK.
Vegetation is generally considered a key factor in protecting soil from erosion. Vegetation cover can mitigate wind erosion and sediment transport through multiple mechanisms [43,44]. Wind erosion poses serious threats within Inner Mongolia and northwestern China in general. The ecosystems of this region are highly vulnerable. Vegetation cover is particularly critical for local ecosystem stability. Our results reveal significantly reduced vegetation coverage under MG (Figure S2). This increased bare ground might accelerate soil drying and erosion while potentially coarsening soil texture and impairing carbon sequestration [17]. This can ultimately destabilize ecosystems. Collectively, our measurements of AGB, AGB carbon density, and vegetation coverage suggested that LG promotes grassland vegetation development better than MG.

4.2. Effects of Grazing Intensity on SOC and Labile SOC Fractions

Labile SOC has a rapid turnover rate and plays a crucial role in assessing soil nutrient supply, maintaining nutrient availability, and facilitating carbon transformation [45,46]. Particulate organic carbon, a key component of labile SOC, primarily consists of decomposed plant residues such as stems and roots. It serves as a vital substrate for microbial activity and nutrient cycling in the plant-soil system [30,47,48]. Our findings indicate that moderate grazing increased POC density in the 10–20 cm soil layer (Figure 3b). This was primarily due to two factors: (1) grazing stimulated belowground biomass growth, and (2) grazing led to a moderate increase in soil pH. Grazing enhances belowground biomass production by prompting plants to absorb more water and nutrients through their roots, which increases POC input [49] and POC levels. Low soil pH strongly inhibits the decomposition of cellulose, lignin, and litter [30,50]. Rising pH weakens the inhibitory effect and speeds up litter decomposition, increasing POC input and enhancing POC density. Grazing-induced moisture reduction negatively impacted POC (Figure 9a). Higher soil moisture boosts plant productivity and increases organic matter input from plants and microbes. This elevates the pool of organic material available for POC formation [51,52]. Because these opposing effects offset each other, our results show no significant effect of grazing intensity on topsoil POC density.
Microorganisms utilize soil organic matter for metabolic processes and convert it into plant-available forms or CO2 [18]. Microbial byproducts also constitute a significant fraction of soil organic matter [2]. Grazing directly or indirectly alters microbial abundance and community structure. Since MBC and PMC are closely linked to soil microbes, grazing-induced microbial shifts also affect MBC and PMC levels. Our study demonstrated that moderate grazing elevated MBC and PMC densities. This is likely due to increased microbial biomass [18] and enhanced community diversity under such conditions. The results provide further evidence supporting our Hypothesis 1. Additionally, livestock manure deposition stimulates root growth and carbon-rich exudate release. Moderate grazing further enhances root proliferation and exudation. This accelerates microbial activity and turnover and ultimately increases plant-available nutrients [20,53].
Although moderate grazing promotes labile organic carbon storage, it may exert certain adverse effects on surface SOC accumulation. Plant-synthesized organic matter is subsequently transferred to the soil through litter and root exudates, a process that fundamentally drives SOC sequestration [54]. As primary SOC sources, both plant litter and roots play pivotal roles in carbon sequestration. While moderate grazing intensity showed minimal influence on root systems (p > 0.05) (Figure S3), it caused a significant reduction in litter biomass (p < 0.05) (Figure S4), thereby compromising belowground carbon inputs. Under moderate grazing in 2019, we observed a marked increase in organic carbon density in the 10–30 cm layer (Figure 8). Structural equation modeling further confirmed that grazing negatively affected the organic carbon content of topsoil, which was consistent with the predictions of Hypothesis 2, but grazing improved the organic carbon content in the 10–20 cm layer (Table 1). Together, these findings suggest that moderate grazing might drive the redistribution of organic carbon from surface to subsurface soils. This phenomenon may arise because moderate grazing reduced vegetation cover, which exposed soil to enhanced wind erosion [55] while disrupting soil aggregates and diminishing erosion resistance [56,57]. Consequently, intense erosional processes may transport SOC downward [58]. Increased precipitation may partially mitigate this downward translocation of topsoil organic carbon.

4.3. Effects of Precipitation on SOC and Labile SOC Fractions

Precipitation is the primary water source in arid and semi-arid ecosystems. As the singular hydrologic input in the research area, meteoric water (precipitation) assumes paramount ecological importance. By altering soil moisture, precipitation indirectly influences plant physiological processes, morphological traits, and long-term adaptation strategies. Precipitation helps shape plant community structure and the ecosystem carbon–water balance [25,28]. Structural equation modeling revealed that precipitation exerted a significant positive effect on total SOC primarily by increasing soil moisture (Figure 9). In arid and semi-arid regions, precipitation affects SOC through two opposing mechanisms: (1) Soil moisture alleviates water stress, which enhances plant and microbial growth, biomass production, and SOC accumulation [59]. (2) Elevated moisture also stimulates soil respiration, substrate availability, and microbial/enzymatic activity, which accelerates organic matter decomposition [60,61,62]. In our study, the net effect of increased precipitation on SOC was positive. This suggests that precipitation promotes SOC accumulation. However, the modest effect size (0.085; Table 1) implies that short-term precipitation changes may not markedly alter SOC stocks.
Dissolved organic carbon is a critical energy source for microbes and soil carbon cycling that originates from atmospheric deposition, litter residues, root exudates, and decomposed soil organic matter [63]. Previous studies have suggested that fresh carbon inputs from vegetation via precipitation-driven increases in plant biomass and litter production could elevate soil DOC levels [64]. However, increased precipitation also boosts microbial biomass and activity. This accelerates the release of DOC via mineralization of existing SOM [63,65]. Because DOC losses from microbial mineralization outweigh gains from plant inputs, SEM results indicated a net negative effect of precipitation on DOC accumulation. Increased precipitation enhances microbial growth by raising SWC. Precipitation also mobilizes organic compounds and microbial residues accumulated during dry periods through diffusion, thereby improving nutrient availability and microbial biomass [66]. Although DOC (composed of readily assimilable sugars and amino acids) typically supports microbial growth [67,68], its decline under elevated precipitation in our study likely constrained microbial activity. Our SEM analysis suggests that increased precipitation may exert modest adverse effects on MBC (Figure 9), potentially mediated by precipitation-induced reductions in DOC content, which could lead to decreased MBC density. While this finding contrasts with some previous studies [69,70], the relatively short duration of our experiment and consistently high precipitation levels during the study period may have amplified the observed precipitation effects. Further long-term investigations are needed to validate these preliminary results.

4.4. Main Limitations and Future Perspectives

A better understanding of SOC responses to grazing intensity and precipitation variability is crucial for predicting grassland carbon sequestration under global climate change. But this study still poses some limitations. Firstly, logistical limitations prevented us from acquiring continuous annual data for 2016–2020. Therefore, the research was conducted using the available data from three discrete years (2016, 2019, and 2020). The relatively short study period (3 years) might not fully account for interannual variability in ecosystem responses, which could influence our findings. Future research should incorporate extended temporal observations to more comprehensively analyze these ecosystem dynamics. Then, our study primarily examined grazing effects through soil microenvironment and carbon input processes but did not address carbon output processes like soil respiration. Future research should incorporate carbon output processes to provide a more comprehensive understanding. While our study primarily focused on surface SOC dynamics, it is noteworthy that subsoil layers (>20 cm) contain over 50% of the total SOC stock [61]. Future investigations should include deep soil sampling to fully assess grazing and precipitation impacts on SOC sequestration potential.

5. Conclusions

This study reveals how grazing intensity affected SOC and labile organic carbon density in semi-arid grasslands via 3 years of field sampling. Our results demonstrate that moderate grazing enhances labile organic carbon accumulation, which supports our first hypothesis. However, consistent with our initial hypothesis (Hypothesis 2), moderate grazing did not enhance SOC accumulation. Moderate grazing under relatively low precipitation may accelerate topsoil degradation. This leads to downward redistribution of surface SOC. Notably, this effect may be reversible under wetter conditions, with higher precipitation potentially offsetting the initial impact. While increased precipitation generally promoted SOC accumulation by improving SWC, the accompanying enhancement of leaching may result in losses of unstable labile carbon fractions. These findings provide critical insights into how semi-arid steppe ecosystems respond to varying grazing intensities and precipitation patterns. These insights will aid in predicting carbon cycle dynamics under climate change and informing sustainable grassland management practices.

Supplementary Materials

The following supporting information can be downloaded at https://www.mdpi.com/article/10.3390/agronomy15081839/s1, Table S1: Changes of soil bulk density (BD), soil pH and soil water content (SWC) under different grazing densities; Figure S1: Relationships between variables including GI, P, AGB, AGBC, SWC, pH, SOCD, POCD, MBCD, PMCD and DOCD; Figure S2: Effects of different grazing intensities on vegetation coverage in 2016, 2019 and 2020; Figure S3: Effects of different grazing intensities on root biomass in 2016, 2019 and 2020 for the (a) 0–10 cm layer; (b) 10–20 cm layer; (c) 20–30 cm layer; (d) 0-30cm layer; Figure S4: Effects of different grazing intensities on litter biomass in 2016, 2019 and 2020.

Author Contributions

M.L.: Investigation, Writing—review and editing. X.L. (Xiang Li): Investigation, Software. D.D.: Investigation. K.W.: Investigation. H.D.: Investigation. X.L. (Xin Lyu): Investigation. X.L. (Xiaobing Li): Writing—review and editing, Supervision, Funding acquisition. S.L.: Writing—original draft, Writing—review and editing, Visualization, Software, Methodology, Investigation, Data curation, Conceptualization. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the National Natural Science Foundation of China (grant nos. 42271291).

Data Availability Statement

Data will be made available on request.

Conflicts of Interest

The authors declare no conflict of interest.

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Figure 1. Average monthly temperature and monthly precipitation.
Figure 1. Average monthly temperature and monthly precipitation.
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Figure 2. Effects of different grazing intensities on (a) aboveground biomass (AGB) and (b) aboveground biomass carbon density. Values are means ± SE (n = 9). Values of a parameter labeled with different letters differ significantly between control (CK), light grazing (LG), and moderate grazing (MG).
Figure 2. Effects of different grazing intensities on (a) aboveground biomass (AGB) and (b) aboveground biomass carbon density. Values are means ± SE (n = 9). Values of a parameter labeled with different letters differ significantly between control (CK), light grazing (LG), and moderate grazing (MG).
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Figure 3. Effects of different grazing intensities on soil particulate organic carbon (POC) density in 2016, 2019, and 2020 for the (a) 0–10 cm, (b) 10–20 cm, and (c) 20–30 cm layer. Values are means ± SE (n = 9). Values of a parameter labeled with different letters differ significantly between control (CK), light grazing (LG), and moderate grazing (MG).
Figure 3. Effects of different grazing intensities on soil particulate organic carbon (POC) density in 2016, 2019, and 2020 for the (a) 0–10 cm, (b) 10–20 cm, and (c) 20–30 cm layer. Values are means ± SE (n = 9). Values of a parameter labeled with different letters differ significantly between control (CK), light grazing (LG), and moderate grazing (MG).
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Figure 4. Effects of different grazing intensities on soil microbial biomass carbon (MBC) density in 2016, 2019, and 2020 for the (a) 0–10 cm, (b) 10–20 cm, and (c) 20–30 cm layer. Values are means ± SE (n = 9). Values of a parameter labeled with different letters differ significantly between control (CK), light grazing (LG), and moderate grazing (MG).
Figure 4. Effects of different grazing intensities on soil microbial biomass carbon (MBC) density in 2016, 2019, and 2020 for the (a) 0–10 cm, (b) 10–20 cm, and (c) 20–30 cm layer. Values are means ± SE (n = 9). Values of a parameter labeled with different letters differ significantly between control (CK), light grazing (LG), and moderate grazing (MG).
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Figure 5. Effects of different grazing intensities on soil potentially mineralizable carbon (PMC) density in 2016, 2019, and 2020 for (a) 0–10 cm, (b) 10–20 cm, and (c) 20–30 cm layers. Values are means ± SE (n = 9). Values of a parameter labeled with different letters differ significantly between control (CK), light grazing (LG), and moderate grazing (MG).
Figure 5. Effects of different grazing intensities on soil potentially mineralizable carbon (PMC) density in 2016, 2019, and 2020 for (a) 0–10 cm, (b) 10–20 cm, and (c) 20–30 cm layers. Values are means ± SE (n = 9). Values of a parameter labeled with different letters differ significantly between control (CK), light grazing (LG), and moderate grazing (MG).
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Figure 6. Effects of different grazing intensities on soil dissolved organic carbon (DOC) density in 2016, 2019, and 2020 for the (a) 0–10 cm, (b) 10–20 cm, and (c) 20–30 cm layer. Values are means ± SE (n = 9). Values of a parameter labeled with different letters differ significantly between control (CK), light grazing (LG), and moderate grazing (MG).
Figure 6. Effects of different grazing intensities on soil dissolved organic carbon (DOC) density in 2016, 2019, and 2020 for the (a) 0–10 cm, (b) 10–20 cm, and (c) 20–30 cm layer. Values are means ± SE (n = 9). Values of a parameter labeled with different letters differ significantly between control (CK), light grazing (LG), and moderate grazing (MG).
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Figure 7. Effects of different grazing intensities on total soil organic carbon density in 2016, 2019, and 2020 for the (a) 0–10 cm, (b) 10–20 cm, and (c) 20–30 cm layer. Values are means ± SE (n = 9). Values of a parameter labeled with different letters differ significantly between control (CK), light grazing (LG), and moderate grazing (MG).
Figure 7. Effects of different grazing intensities on total soil organic carbon density in 2016, 2019, and 2020 for the (a) 0–10 cm, (b) 10–20 cm, and (c) 20–30 cm layer. Values are means ± SE (n = 9). Values of a parameter labeled with different letters differ significantly between control (CK), light grazing (LG), and moderate grazing (MG).
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Figure 8. Proportion of soil organic carbon density at different depths under varying grazing intensities in (a) 2016, (b) 2019, and (c) 2020. CK: control check; LG: light grazing; MG: moderate grazing.
Figure 8. Proportion of soil organic carbon density at different depths under varying grazing intensities in (a) 2016, (b) 2019, and (c) 2020. CK: control check; LG: light grazing; MG: moderate grazing.
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Figure 9. Structural equation modeling revealed the potential direct and indirect factors influencing soil organic carbon density including grazing intensity, precipitation, soil water content, soil pH, and labile organic carbon fractions. Panels (a,b) represent the 0–10 cm and 10–20 cm soil layers, respectively. Solid lines indicate statistically significant relationships (p < 0.05), while translucent dashed lines denote non-significant relationships (p > 0.05). Blue and red arrows represent positive and negative effects, respectively, with standardized path coefficients shown for each relationship. R2 values indicate the proportion of total variance in dependent variables explained by all predictors. P: precipitation; GI: grazing intensity; SWC: soil water content; pH: soil pH; POC: soil particulate organic carbon density; DOC: soil dissolved organic carbon density; MBC: soil microbial biomass carbon density; PMC: soil potentially mineralizable carbon density; SOC: soil organic carbon density.
Figure 9. Structural equation modeling revealed the potential direct and indirect factors influencing soil organic carbon density including grazing intensity, precipitation, soil water content, soil pH, and labile organic carbon fractions. Panels (a,b) represent the 0–10 cm and 10–20 cm soil layers, respectively. Solid lines indicate statistically significant relationships (p < 0.05), while translucent dashed lines denote non-significant relationships (p > 0.05). Blue and red arrows represent positive and negative effects, respectively, with standardized path coefficients shown for each relationship. R2 values indicate the proportion of total variance in dependent variables explained by all predictors. P: precipitation; GI: grazing intensity; SWC: soil water content; pH: soil pH; POC: soil particulate organic carbon density; DOC: soil dissolved organic carbon density; MBC: soil microbial biomass carbon density; PMC: soil potentially mineralizable carbon density; SOC: soil organic carbon density.
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Table 1. Direct, indirect, and total standardized effects of grazing intensities (GI), precipitation (P), soil water content (SWC), pH, soil particulate organic carbon (POC), soil microbial biomass carbon (MBC), soil potentially mineralizable carbon (PMC), and soil dissolved organic carbon (DOC) on soil organic carbon (SOC) density based on structural equation model.
Table 1. Direct, indirect, and total standardized effects of grazing intensities (GI), precipitation (P), soil water content (SWC), pH, soil particulate organic carbon (POC), soil microbial biomass carbon (MBC), soil potentially mineralizable carbon (PMC), and soil dissolved organic carbon (DOC) on soil organic carbon (SOC) density based on structural equation model.
Soil DepthPredictorDirect EffectIndirect EffectTotal Effect
0–10 cmGI0.005−0.090−0.085
P-0.0850.085
SWC0.4090.1170.526
pH-0.0620.062
POC0.457−0.1860.271
MBC0.083-0.083
PMC0.167-0.167
DOC0.4480.0270.475
10–20 cmGI−0.0670.1520.084
P0.387−0.1970.189
SWC-0.1170.117
pH-0.090.090
POC0.526−0.2390.287
MBC0.180-0.180
PMC−0.177-−0.177
DOC0.116-0.116
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Liu, S.; Li, X.; Li, M.; Li, X.; Dang, D.; Wang, K.; Dou, H.; Lyu, X. Interannual Variability in Precipitation Modulates Grazing-Induced Vertical Translocation of Soil Organic Carbon in a Semi-Arid Steppe. Agronomy 2025, 15, 1839. https://doi.org/10.3390/agronomy15081839

AMA Style

Liu S, Li X, Li M, Li X, Dang D, Wang K, Dou H, Lyu X. Interannual Variability in Precipitation Modulates Grazing-Induced Vertical Translocation of Soil Organic Carbon in a Semi-Arid Steppe. Agronomy. 2025; 15(8):1839. https://doi.org/10.3390/agronomy15081839

Chicago/Turabian Style

Liu, Siyu, Xiaobing Li, Mengyuan Li, Xiang Li, Dongliang Dang, Kai Wang, Huashun Dou, and Xin Lyu. 2025. "Interannual Variability in Precipitation Modulates Grazing-Induced Vertical Translocation of Soil Organic Carbon in a Semi-Arid Steppe" Agronomy 15, no. 8: 1839. https://doi.org/10.3390/agronomy15081839

APA Style

Liu, S., Li, X., Li, M., Li, X., Dang, D., Wang, K., Dou, H., & Lyu, X. (2025). Interannual Variability in Precipitation Modulates Grazing-Induced Vertical Translocation of Soil Organic Carbon in a Semi-Arid Steppe. Agronomy, 15(8), 1839. https://doi.org/10.3390/agronomy15081839

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