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Article

Soil Organic Carbon Content and Density in Response to Pika Outbreaks Along the Altitudinal Gradient in Alpine Meadows of the Qinghai–Tibet Plateau, West China

by
Wenzhi Yao
1,2,
Jing Zhang
2,* and
Xilai Li
1,2,*
1
State Key Laboratory of Plateau Ecology and Agriculture, Qinghai University, Xining 810016, China
2
College of Agriculture and Animal Husbandry, Qinghai University, Xining 810000, China
*
Authors to whom correspondence should be addressed.
Land 2025, 14(5), 981; https://doi.org/10.3390/land14050981
Submission received: 19 March 2025 / Revised: 20 April 2025 / Accepted: 30 April 2025 / Published: 1 May 2025
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Abstract

This study investigated the effects of plateau pika (Ochotona curzoniae) disturbances and altitude on soil organic carbon (SOC) storage characteristics, including SOC content and SOC density (SOCD). In this study, plateau pika outbreak areas and non-outbreak areas at different altitudes were compared in terms of vegetation biomass, soil physicochemical properties, SOC content and SOCD to establish the relationship between vegetation and soil characteristics (including SOC content and SOCD). The results showed that SOC and SOCD decreased significantly (p < 0.01) in plateau pika outbreak areas, but SOCD increased first and then decreased with elevation in non-outbreak areas. Soil total nitrogen (TN) content decreased significantly (p < 0.01) with elevation in both plateau pika outbreak and non-outbreak areas. There were significant differences (p < 0.05) in total phosphorus (TP) at low elevations and nitrate nitrogen (NO3−-N) at high elevations between outbreak and non-outbreak areas, but other nutrients did not differ hugely between outbreak and non-outbreak areas at the same elevation. Correlation analysis revealed that belowground biomass (BGB) in the plateau pika outbreak area was significantly and positively correlated with SOC (p < 0.01); structural equation modeling (SEM) analysis revealed that altitude had a direct effect on SOC (path coefficient = −0.882, p < 0.001) in the plateau pika outbreak area, but only a reduced influence on SOC and SOCD in the non-outbreak area; nitrate nitrogen in the plateau pika outbreak area and TN were the key influencing factors, which exerted a strong direct influence on SOC and SOCD (path coefficient = −0.666 and 0.639 (p < 0.001), respectively). Therefore, increasing vegetation biomass and nitrogen nutrient content through reseeding pasture and fertilization can facilitate the accumulation and recovery of SOC and SOCD in the ecological restoration of degraded alpine meadows, and it is especially important to quickly enrich soil nitrogen content in the outbreak area of plateau pika populations at high altitudes.

1. Introduction

Soil organic carbon (SOC) represents the total carbon content derived from all organic matter in soil, encompassing plant residues, microbial byproducts, humic substances, and other organic components [1,2]. As a critical component of the global carbon pool, SOC is closely linked to soil properties and fertility dynamics. In terrestrial ecosystem carbon cycle research, the SOC pool is widely recognized as the most active and largest reservoir. Even minor fluctuations in its storage can apparently modulate atmospheric CO2 levels through carbon exchange processes, thereby influencing the delicate balance between the global carbon cycle and climate regulation [3,4].
Alpine meadows, a dominant grassland type on the Qinghai–Tibet Plateau, harbor substantial SOC pool and play a pivotal role in regional carbon cycling and global climate dynamics [5]. In recent decades, climate change-induced temperature rises and altered precipitation patterns, coupled with anthropogenic activities such as overgrazing and land reclamation, have severely degraded alpine meadow ecosystems, leading to a marked reduction in SOC pool across the Plateau [6,7]. Studies have demonstrated that SOC content and density notably decline with increasing degradation intensity [8]. Ecosystem degradation alters vegetation composition and soil properties, further impacting SOC content and density [9]. Vegetation serves as a primary source of soil carbon in alpine meadows. During degradation, the reduced vegetation cover and shifts in plant communities diminish organic carbon inputs to the soil. Concurrently, elevated surface soil temperatures accelerate microbial activity, promoting SOC mineralization and subsequent carbon loss, ultimately depleting SOC pool [10,11,12].
Additionally, outbreaks of plateau pikas (Ochotona curzoniae) exacerbate alpine meadow degradation, inducing rapid changes in SOC content and density [13]. However, the impact of plateau pikas on SOC remains inconsistently documented. Their influence exhibits complexity, being both positive and negative. Positive effects include burrowing and excavating activities that enhance organic carbon concentrations and storage in deeper soil layers, partially compensating for surface SOC loss. Negative effects are related to pika-induced vegetation degradation, which reduces litterfall and root exudate inputs, thereby constraining SOC accumulation [14,15,16,17,18].
In order to understand the mechanism of plateau pika disturbance on SOC content and density, this paper investigated the SOC content and density in plateau pika outbreak and non-outbreak areas in alpine meadows, and analyzed their relationship with vegetation characteristics and soil physicochemical properties so as to address the following scientific questions: (1) How do plateau pika outbreaks alter soil nutrient dynamics along the elevation gradient? (2) What are the interactive mechanisms between biotic disturbance (pika outbreaks) and physical gradients (elevation) in regulating soil carbon dynamics?

2. Materials and Methods

2.1. Study Area

The research was conducted in four counties of Qinghai Province, China: Menyuan Hui Autonomous County (37°28′ N, 101°33′ E), Qilian County (38°03′ N, 100°30′ E), Gangcha County (37°32′ N, 100°17′ E), and Tianjun County (37°18′ N, 99°01′ E) (Figure 1). The key environmental parameters of these regions are illustrated in Table 1.
In July 2023, five representative sampling plots (50 m × 50 m) were selected in plateau pika (Ochotona curzoniae) outbreak areas and paired non-outbreak control areas in Menyuan and Qilian counties. In July 2024, three additional plots of identical dimensions were established in Gangcha and Tianjun counties (Figure 1). According to the literature [19,20,21,22], plateau pika outbreak areas are characterized by ≥60% patchily degraded meadow areas (in proportion) and the presence of obvious plateau pika activity. The plateau pika outbreak areas were ascertained via in situ drone observations using a DJI Phantom 4 UAV hovering 50 m above the pre-selected study area, taking isochronous photographs with an overlap of 75%. Outbreak plots were located on south-facing gentle slopes (3–5°) with a high pika population density, under year-round grazing regimes. Non-outbreak control plots contained intact vegetation and exhibited minimal pika activity. A detailed sampling site distribution, quadrat configuration, and methodologies are illustrated in Figure 1, with site characteristics summarized in Table 1. In the figure, black squares denote sampling quadrats.

2.2. Vegetation Survey

Within each sampling plot, five 50 cm × 50 cm quadrats were established along the two diagons of the plot (refer to the black squares in Figure 1). Within each quadrat, aboveground biomass (AGB) was collected by clipping all vegetation to the ground level. The harvested material was stored in paper bags for subsequent drying and weighing. For belowground biomass (BGB) measurement, soil cores (3 cm inner diameter) were collected from the 0–20 cm layer in the same quadrats using a soil auger. Three cores per quadrat were pooled into cloth bags and rinsed to remove debris while retaining the roots in the lab. All biomass samples (AGB and BGB) were oven-dried at 65 °C until reaching a constant weight.

2.3. Soil Sampling and Analysis

Following the vegetation surveys, five additional soil cores were collected per quadrat (0–20 cm). These cores were homogenized, sieved through a 2 mm mesh to remove impurities, and air-dried in ventilated conditions to prepare composite samples for physicochemical analysis. In situ soil bulk density was determined using a steel cutting ring (100 cm3 volume, inserted vertically at a constant speed to preserve soil structure. The collected samples were trimmed to ensure flat surfaces and immediately sealed. Soil moisture (M), soil temperature (T), and electrical conductivity (EC) were measured using TDR 350 at the same 0–20 cm depth in the five sample squares. Wet soil mass (including the ring) was recorded, followed by oven-drying at 105 °C to a constant weight. Bulk density (g/cm3) was calculated as dry soil mass divided by ring volume.
In the laboratory, SOC content and density were measured using precision instruments. SOC was determined via the K2Cr2O7-H2SO4 method, from which SOCD was calculated as SOCD(g/m2) = bulk density (g/cm3) × soil depth (cm) × SOC content (%) × 10. Soil total nitrogen (TN) and soil total phosphorus (TP) were extracted using concentrated sulfuric acid, with a catalyst (potassium sulfate–copper sulfate–selenium powder = 100:10:1), and the treated digestate was determined via a continuous-flow analyzer AA3 from SEAL (Norderstedt, Germany). Ammoniacal nitrogen (NH4+-N) and nitrate nitrogen (NO3−-N) were extracted using potassium chloride and then determined using an AA3 continuous-flow analyzer from SEAL (Germany) [23].

2.4. Data Processing

The UAV images were processed using Pix4Dmapper and ArcGIS 10.8 software, and the visual interpretation method was used for interpreting degraded patchy meadow areas. Their quantity and area were extracted from the images in ArcGIS, and the plateau pika outbreak area was determined according to the areal percentage of degraded patches, as follows [15]:
P = ∑ A i A × 100 %
where P is the areal percentage of degraded patches, Ai is the area of the ith degraded patch (i = 1, 2, …, n; n—the total number of patches), and A is the total area of the study area.
One-way ANOVA was conducted using SPSS (version 27.0) to compare vegetation biomass and soil physicochemical properties as well as SOC and SOCD in plateau pika outbreak and non-outbreak areas at different altitudes. Independent sample t-tests were conducted to determine vegetation biomass and soil physicochemical properties, as well as SOC content and density in areas of the same altitude. Vegetation and soil factors were analyzed to determine their correlation with SOC and SOCD. A redundancy analysis (RDA) was conducted using Canoco 5. A Structural Equation Model (SEM) was constructed using Amos Graphic.

3. Results and Analysis

3.1. Impacts of Plateau Pika Outbreaks on Vegetation and Soil Properties Along the Altitudinal Gradient

The analysis of vegetation and soil physicochemical properties in plateau pika outbreak areas revealed significant altitudinal trends (Table 2). The TN content at high altitudes (1.20 g·kg−1 and 1.19 g·kg−1) was markedly lower than that at low altitudes (6.34 g·kg−1 and 6.59 g·kg−1; p < 0.05). TP peaked at 3562 m. Soil pH, ammonium nitrogen (NH4+-N), nitrate nitrogen (NO3−-N), and EC all increased noticeably with altitude (p < 0.05), while SOC content exhibited an inverse trend, declining sharply from 53.97 g·kg−1 (3205 m) and 77.15 g·kg−1 (3248 m) at 3562 m to 15.52 g·kg−1 and 13.66 g·kg−1 at 3655 m, respectively. SOCD followed a similar pattern, correlating with altitude.
In non-outbreak areas, TN content also decreased considerably with increasing altitude, a trend consistent with that of the outbreak areas. Soil pH and C/N ratio remained stable, while NO3−-N levels initially increased and then decreased with altitude (p < 0.05). SOCD first increased and then noticeably declined at higher elevations (p < 0.05) in non-outbreak areas.
Comparisons between outbreak and non-outbreak areas at the same altitude showed minimal differences in TN, pH, C/N ratio, and NH4+-N. However, the TP content at 3205 m was drastically higher in non-outbreak areas than in outbreak areas (p < 0.05), and NO3−-N levels at 3655 m were notably elevated in outbreak areas. SOC content and SOCD showed no significant variations between outbreak and non-outbreak zones across all altitudes, suggesting that altitude exerts a stronger influence on SOC dynamics than pika disturbance.
As shown in Table 3, soil temperature (T) in outbreak areas increased considerably with altitude, whereas soil moisture (SM) initially rose and then declined (p < 0.05). At 3655 m, soil bulk density in outbreak areas was the lowest (0.78 g·cm−3), notably lower than the 1.18 g·cm−3 observed in non-outbreak areas (p < 0.05). Both AGB and BGB in outbreak areas decreased markedly with altitude. In non-outbreak areas, soil temperature also notably rose with altitude, and soil moisture at 3562 m (31.39%) exceeded that at other elevations (p < 0.05). AGB and BGB in non-outbreak areas initially decreased and then increased with altitude.
Comparisons of soil physical properties between outbreak and non-outbreak areas at the same altitude revealed minimal differences in soil temperature and bulk density. However, soil moisture at 3205 m was significantly higher in non-outbreak areas (p < 0.05). At high altitudes (3562 m and 3655 m), both AGB and BGB in non-outbreak areas surpassed those in outbreak areas.

3.2. Effects of Plateau Pika Outbreaks on Soil Organic Carbon Along Altitudinal Gradient

In areas affected by plateau pika outbreaks (Figure 2a), SOC content exhibited highly significant negative correlations with altitude, TP content, pH, ammonium nitrogen (NH4+-N), nitrate nitrogen (NO3−-N), temperature, and soil bulk density (p < 0.001), respectively, and a significant negative correlation with EC (p < 0.05). Conversely, it showed highly significant positive correlations with TN content and BGB (p < 0.001). SOCD demonstrated highly significant negative correlations with altitude, pH, ammonium nitrogen, nitrate nitrogen, and temperature, respectively (p < 0.001), significant negative correlations with TP content (p < 0.01) and soil bulk density (p < 0.05), and highly significant positive correlations with TN and SOC content (p < 0.001).
In non-outbreak areas (Figure 2b), SOC content displayed highly significant negative correlations with altitude, TP content, pH, ammonium nitrogen, nitrate nitrogen, and temperature, respectively (p < 0.001), while showing highly significant positive correlations with bulk density and EC (p < 0.001). SOCD was remarkably and negatively correlated with altitude, TP content, pH, ammonium nitrogen, nitrate nitrogen, and temperature, respectively (p < 0.001), and significantly positively correlated with TN and SOC content, and EC (p < 0.001).

3.3. Key Drivers of SOC and SOCD

RDA revealed distinct drivers of SOC and SOCD in pika outbreak and non-outbreak areas. In outbreak areas (Figure 3a), nitrate nitrogen (NO3−-N), soil moisture, and altitude exerted the strongest influences on SOC and SOCD, explaining 74.5%, 10.2%, and 3.2% of their variability, respectively. In non-outbreak areas (Figure 3b), altitude emerged as the most dominant factor, followed by C/N ratio and EC, accounting for 77.7%, 4.8%, and 4.4% of the variability, respectively. These results suggest that pika activity reduces the sensitivity of SOC and SOCD to altitude while amplifying their dependence on nitrogen availability.

3.4. Pika Outbreak Impacts on SOC and SOCD

According to the SEM results (Figure 4a), NO3−-N and altitude imposed strong direct negative effects on SOC (path coefficients: −0.666 and −0.342, respectively; p < 0.001) in pika outbreak areas. SOC and TN exerted highly significant positive effects on SOCD (path coefficients: 1.118 and 0.639; p < 0.001) directly, while bulk density showed a moderate positive effect (path coefficient: 0.319; p < 0.001). Indirectly, NO3−-N influenced SOCD through modulating TN levels.
In non-outbreak areas (Figure 4b), altitude strongly and directly reduced SOC (path coefficient: −0.882, p < 0.001) and moderately decreased SOCD (path coefficient: −0.175, p < 0.001). EC positively influenced SOC (path coefficient: 0.591; p < 0.001) and indirectly affected SOCD via SOC. A robust direct positive linkage existed between SOC and SOCD (path coefficient: 0.557; p < 0.001). Ammonium nitrogen (NH4+-N) and pH exerted minor but significant negative effects on SOCD (path coefficients: −0.152 and −0.161; p < 0.001). Collectively, pika activity diminished the sensitivity of SOC and SOCD to altitude but heightened their responsiveness to nitrogen dynamics, with TN accumulation promoting SOCD enhancement.

4. Discussion

4.1. Impacts of Plateau Pika Outbreaks on Vegetation and Soil Physicochemical Properties

Systematic comparative analysis revealed statistically significant differences in vegetation’s spatial heterogeneity between pika outbreak and non-outbreak areas (Table 2). Total ABG and BGB in outbreak areas exhibited a systematic reduction compared to non-outbreak zones, a finding that is aligned with those of Su et al. on rodent-mediated ecological disturbances [24]. At high elevations, pika burrowing activities displace soil to the surface, forming overlays that progressively suffocate vegetation near burrow entrances, leading to localized plant disappearance. Selective foraging on both aerial tissues and root systems by pika populations further drives biomass decline in outbreak areas [25].
Vertical gradient differentiation profoundly influenced vegetation distribution, particularly in outbreak plots, where both AGB and BGB decreased exponentially with elevation. This trend reflects the compounded physiological stresses of low temperatures, hypoxic conditions, and intense UV radiation in alpine zones [26]. Low-elevation regions, benefiting from favorable thermal–hydrological conditions (e.g., higher accumulated temperatures and precipitation), supported increased vegetation productivity. In contrast, high-elevation areas experienced a severe reduction in biomass due to thermal constraints on plant metabolism [27].
Mechanistically, elevation gradients modulate soil nutrient cycling rates, acting as an “invisible hand” that indirectly regulates vegetation growth. TN content in high-elevation soils was ostensibly lower than its counterpart in low-elevation zones, potentially impairing nitrogen use efficiency and slowing plant growth. These observations resonate with Dong et al.’s results, which elucidate how pika overpopulation disrupts alpine meadow stability through direct herbivory and cascading habitat interactions [28]. The vertical stratification of soil nutrients was further evidenced by Zhang et al. who reported stark contrasts in organic matter, TN, and TP between surface (0–10 cm) and deeper layers (20–40 cm), with strong negative correlations with soil depth (R2 > 0.40) and surface enrichment patterns [29]. Chang et al. emphasized that SOC dynamics in the Three-River-Source Region are co-driven by vegetation shifts, climate fluctuations, and anthropogenic pressures [8].
Soil pH, nutrient availability, and EC critically govern soil fertility and vegetation performance [30,31]. Comparative analyses showed significant disparities in these parameters between outbreak and non-outbreak areas. Along the vertical profile, TN content declined with elevation, suggesting a mechanism whereby low-temperature and hypoxic conditions suppress microbial activity, slowing nitrogen mineralization and disrupting N cycling (Table 1) [32,33,34]. Conversely, the warmer temperatures and adequate rainfall at lower elevations enhance organic matter turnover, sustaining higher nitrogen levels—a pattern supported by prior studies [35,36].
In non-outbreak areas, elevation–nitrogen relationships diverged markedly. Pika disturbances likely mitigate elevation-related soil degradation through two mechanisms: the enhanced aeration porosity caused by burrow-mediated soil structural improvement and the water infiltration capacity that creates microhabitats that stimulate microbial functionality and boost organic matter conversion and directional nutrient accumulation, particularly at high elevations [37,38,39].

4.2. Effects of Plateau Pika Outbreaks on SOC Content and Density

The SOC pool in alpine meadows is pivotal for soil fertility regulation and carbon sequestration. SOC variability is synergistically controlled through elevation, temperature fluctuations, soil moisture, vegetation dynamics, and nutrient cycling. Vertical gradient data revealed a significant decline in SOC content with increasing elevation (p < 0.05), corroborating the findings by Wang et al. [40,41]. This decline stems from low-temperature constraints and shortened growing seasons, which reduce ecosystem productivity and organic matter inputs, ultimately depleting SOC pool [42].
High-elevation soils exhibited reduced microbial metabolic activity, with organic matter mineralization rates 25% slower than those in mid–low-elevation zones. This sluggish process likely impedes humification, exacerbating SOC loss. Although pika herbivory transiently reduces ABG, their excreta introduce labile nutrients that accelerate litter decomposition, partially offsetting carbon loss. Consequently, SOC content showed spatially homogeneous distributions between outbreak and non-outbreak areas (p > 0.05).
Deep-linkage analysis reveals a strong positive correlation between SOC and TN content (R2 = 0.68, p < 0.001), suggesting co-evolutionary carbon–nitrogen coupling. Nitrogen enrichment stimulates root exudates and litter production, elevating organic matter inputs—a mechanism consistent with Qiu et al.’s carbon–nitrogen synergy model in alpine meadows [43,44]. On the Qinghai–Tibet Plateau, nitrogen availability emerged as the dominant regulator of SOC dynamics. Key observations of elevation–SOCD relationships indicate that SOCD in outbreak areas linearly decreased with elevation. In non-outbreak areas, it followed a unimodal trend (peak at mid-elevation). This divergence underscores ecosystem complexity, where pika activity accelerates SOC decomposition in outbreak zones, while high-elevation stressors (low temperature and hypoxia) suppress microbial activity, further reducing SOCD. In this process, nitrogen availability is identified as the primary driver because TN content showed a highly significant positive correlation with SOC density (R2 = 0.72, p < 0.01), particularly in outbreak areas. This aligns with the findings of Wang et al. [45], Liu et al. [46], and Xu et al. [47]. They all confirmed nitrogen as a critical limiting factor for alpine vegetation biomass. Elevated nitrogen levels enhance plant productivity, increasing organic carbon inputs and SOCD.
The mechanistic insights into pika–microbe interactions indicate that frequent pika activities in outbreak areas accelerate organic matter decomposition, reducing SOCD. Concurrently, high-elevation conditions inhibit microbial biochemical processes, compounding SOC loss. Along the vertical nutrient gradient, the contrast of SOC, TN, and TP distributions across soil depths (0–40 cm) highlights depth-dependent nutrient dynamics, with the surface layer exhibiting significant enrichment due to vegetation–climate interactions [8,29]. Pika outbreaks reshape SOC dynamics via dual pathways: direct biomass consumption and the indirect modulation of soil–microbe–plant feedbacks. These findings advocate for elevation-specific management strategies to enhance carbon sequestration in alpine meadows, emphasizing nitrogen supplementation and targeted vegetation restoration in plateau pika outbreak areas.

5. Conclusions

In plateau pika outbreak areas on the Qinghai–Tibet Plateau, a higher altitude significantly reduced SOC and SOCD in alpine meadows. Pika activities elevated soil TP and NH4+-N at low altitudes but lowered NO3−-N at high altitudes, and plateau pika activities at lower elevations had a more enhanced effect on SOC than at a higher elevation. Key drivers of SOC and SOCD differed between outbreak and non-outbreak areas: in outbreak areas, BGB and TN were strongly correlated with SOC/SOCD, heightening the role of nitrogen accumulation in carbon sequestration. In non-outbreak areas, altitude was the dominant driver of SOC/SOCD variability (path coefficient: −0.882). Pika activities reduced SOC/SOCD sensitivity to altitude but increased its reliance on soil nitrogen, particularly NO3−-N and TN (path coefficients: −0.666 and 0.639, respectively). To enhance SOC and SOCD in outbreak regions, ecological restoration should prioritize forage reseeding to boost biomass production and targeted fertilization to elevate soil nitrogen. These strategies are critical for improving the soil’s carbon sink capacity in degraded alpine meadows.

Author Contributions

Author contributions: W.Y., X.L. and J.Z. conceptualized the topic of the manuscript and were responsible for the overall direction and planning. W.Y. participated in the field data collection. W.Y. also analyzed the data and drafted the manuscript. X.L. and J.Z. reviewed and revised the first draft. All authors have read and agreed to the published version of the manuscript.

Funding

This study was supported by the project of Science and Technology Department of Qinghai Province (No. 2023-QY-210), the National Natural Science Joint Foundation of China (No. U23A20159, U21A20191), and the Discipline Innovation and Intelligence Program of Higher Education Institutions, the 111 Project of China (No. D18013) and the project of Ecosystem Succession and Management Direction in the World-Class Discipline of Ecology at Qinghai University.

Data Availability Statement

The datasets are available from the corresponding author upon reasonable request.

Acknowledgments

All authors sincerely appreciate the invaluable feedback provided by all those who contributed to the refinement of this manuscript.

Conflicts of Interest

The authors declare no conflicts of interest.

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Land 14 00981 g001
Figure 1. Sample plots and sampling quadrats (black squares) setup.
Figure 1. Sample plots and sampling quadrats (black squares) setup.
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Figure 2. Correlation of soil environmental factors with SOC and SOCD. (a) Outbreak areas; (b) non-outbreak area. Note: * signifies p < 0.05; ** indicates p < 0.01; *** means p < 0.001.
Figure 2. Correlation of soil environmental factors with SOC and SOCD. (a) Outbreak areas; (b) non-outbreak area. Note: * signifies p < 0.05; ** indicates p < 0.01; *** means p < 0.001.
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Figure 3. RDA of environmental factors with SOC and SOCD. (a) outbreak areas; (b) non-outbreak area.
Figure 3. RDA of environmental factors with SOC and SOCD. (a) outbreak areas; (b) non-outbreak area.
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Figure 4. SEM analysis results showing the effects of altitude and various soil properties on SOC and SOCD. (a) Outbreak areas; (b) Non-outbreak areas. Note: Blue lines indicate negative effects, red lines denote positive effects, and line thickness is proportional to the magnitude of effects. *** denotes p < 0.001.
Figure 4. SEM analysis results showing the effects of altitude and various soil properties on SOC and SOCD. (a) Outbreak areas; (b) Non-outbreak areas. Note: Blue lines indicate negative effects, red lines denote positive effects, and line thickness is proportional to the magnitude of effects. *** denotes p < 0.001.
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Table 1. Basic information of sample plots.
Table 1. Basic information of sample plots.
Serial NumberSample SiteLongitudesLongitudeElevation (m)Slope Direction (°)Average Annual Rainfall
(mm)		Average Annual Temperature
(°C)		Proportion of Patchily Degraded Areas in an Alpine Meadow
1Menyuan county101.587937.45723221259.695517.61.564%
2Menyuan county101.586137.45733194223.091517.61.567%
3Menyuan county101.621337.46263476247.011517.61.563%
4Menyuan county101.56137.4743152120.619517.61.569%
5Menyuan county101.564937.48183182115.427517.61.561%
6Qilian county100.532938.05323248186.71420163%
7Qilian county100.836337.99183312208.413420168%
8Qilian county100.515938.05723147166.504420179%
9Qilian county100.830937.9814328018.4349420177%
10Qilian county100.87137.98213361136.042420165%
11Gonchak county100.469037.52463589248.166360−1.587%
12Gonchak county100.408937.67473711257.671360−1.591%
13Gonchak county100.502937.34943384243.361360−1.589%
14Tianjun county98.470837.4863673191.174409.30.495%
15Tianjun county98.412337.4917370596.1188409.30.490%
16Tianjun county98.611537.46033584160.623409.30.487%
Table 2. Soil chemical properties at four elevations.
Table 2. Soil chemical properties at four elevations.
Elevation/mTreatmentsTN/g·kg−1TP/g·kg−1pHC/NAmmonium Nitrogen/mg·kg−1Nitrate Nitrogen/mg·kg−1ECSOC/g·kg−1SOCD/g·m3
3205Outbreak areas6.34 ± 2.32 aA0.30 ± 0.07 bB7.42 ± 0.27 bA10.20 ± 6.19 aA1.30 ± 0.91 bA0.96 ± 0.60 bA0.09 ± 0.03 bB53.97 ± 6.54 bB4.22 ± 1.24 bA
Non-outbreak area6.68 ± 1.11 aA0.61 ± 0.19 bA7.75 ± 0.34 aA11.59 ± 5.59 aA0.99 ± 0.42 bA1.01 ± 0.59 dA0.32 ± 0.27 aA73.97 ± 29.88 aA5.56 ± 2.38 bA
3248Outbreak areas6.59 ± 1.09 aA0.47 ± 0.04 bA7.35 ± 0.46 bA11.80 ± 3.09 aA1.25 ± 0.59 bA4.00 ± 1.88 bA0.16 ± 0.03 aA77.15 ± 7.24 aA7.40 ± 0.84 aA
Non-outbreak area6.25 ± 0.70 aA0.39 ± 0.04 cA7.50 ± 0.37 aA11.33 ± 2.10 aA0.80 ± 0.35 bA2.72 ± 1.04 cA0.19 ± 0.05 bA71.07 ± 8.70 aA7.07 ± 0.57 aA
3562Outbreak areas1.20 ± 0.16 bA1.33 ± 0.36 aA7.67 ± 0.12 abA12.95 ± 2.80 aA59.83 ± 11.58 aA83.45 ± 19.70 aA0.18 ± 0.02 aA15.52 ± 3.99 cA1.67 ± 0.42 cA
Non-outbreak area1.35 ± 0.17 bA1.04 ± 0.28 aA7.89 ± 0.06 aA11.37 ± 4.38 aA64.98 ± 7.80 aA66.23 ± 14.34 aA0.18 ± 0.02 bA14.95 ± 4.66 bA1.42 ± 0.47 cA
3655Outbreak areas1.19 ± 0.20 bA0.46 ± 0.22 bA8.12 ± 0.24 aA11.79 ± 2.38 aA63.22 ± 25.88 aA71.35 ± 12.18 aA0.20 ± 0.11 aA13.66 ± 2.03 cA1.61 ± 0.24 cA
Non-outbreak area1.18 ± 0.33 bA0.46 ± 0.15 bcA8.12 ± 0.19 aA12.70 ± 3.21 aA68.54 ± 22.87 aA47.52 ± 8.84 bB0.13 ± 0.03 cA14.12 ± 2.29 bA1.41 ± 0.23 cA
Note: Lowercase letters indicate significant differences (p < 0.05) between altitudes in the same pika activity category (outbreak), while uppercase letters denote differences between pika activity categories at the same altitude.
Table 3. Soil physical properties and vegetation characteristics at four elevations.
Table 3. Soil physical properties and vegetation characteristics at four elevations.
Elevation/mTreatmentsT/°CSM/%Volume Weight/g·cm3Above-Ground Biomass/g·m2Below-Ground Biomass/g·m2
3205Outbreak areas11.89 ± 1.66 cA16.33 ± 3.80 bB0.78 ± 0.19 bA2.26 ± 0.74 cA1.88 ± 6.84 bA
Non-outbreak area10.94 ± 1.84 bA25.87 ± 11.32 bA0.78 ± 0.19 aA3.11 ± 1.11 cA5.68 ± 4.37 cB
3248Outbreak areas15.11 ± 4.74 bA25.57 ± 3.42 aA0.96 ± 0.08 abA5.36 ± 1.45 aB5.17 ± 1.15 aB
Non-outbreak area13.53 ± 4.77 bA26.14 ± 4.81 bA1.01 ± 0.13 aA11.99 ± 1.45 aA13.21 ± 1.18 bA
3562Outbreak areas18.24 ± 1.94 abA27.79 ± 2.52 aA1.09 ± 0.16 abA4.28 ± 1.41 bB0.68 ± 0.17 cB
Non-outbreak area18.83 ± 1.65 aA31.39 ± 1.72 aA0.96 ± 0.11 aA8.04 ± 1.20 bA6.48 ± 1.80 cA
3655Outbreak areas22.55 ± 2.91 aA17.83 ± 5.88 bA1.18 ± 0.11 aA3.12 ± 1.47 cB0.52 ± 0.28 cB
Non-outbreak area22.23 ± 3.52 aA22.62 ± 3.78 bA1.00 ± 0.11 aA8.15 ± 2.16 bA11.53 ± 1.36 aA
Note: Lowercase letters indicate significant differences (p < 0.05) between altitudes in the same pika activity category (outbreak), while uppercase letters denote differences between pika activity categories at the same altitude.
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Yao, W.; Zhang, J.; Li, X. Soil Organic Carbon Content and Density in Response to Pika Outbreaks Along the Altitudinal Gradient in Alpine Meadows of the Qinghai–Tibet Plateau, West China. Land 2025, 14, 981. https://doi.org/10.3390/land14050981

AMA Style

Yao W, Zhang J, Li X. Soil Organic Carbon Content and Density in Response to Pika Outbreaks Along the Altitudinal Gradient in Alpine Meadows of the Qinghai–Tibet Plateau, West China. Land. 2025; 14(5):981. https://doi.org/10.3390/land14050981

Chicago/Turabian Style

Yao, Wenzhi, Jing Zhang, and Xilai Li. 2025. "Soil Organic Carbon Content and Density in Response to Pika Outbreaks Along the Altitudinal Gradient in Alpine Meadows of the Qinghai–Tibet Plateau, West China" Land 14, no. 5: 981. https://doi.org/10.3390/land14050981

APA Style

Yao, W., Zhang, J., & Li, X. (2025). Soil Organic Carbon Content and Density in Response to Pika Outbreaks Along the Altitudinal Gradient in Alpine Meadows of the Qinghai–Tibet Plateau, West China. Land, 14(5), 981. https://doi.org/10.3390/land14050981

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