Climate-Driven Microbial Communities Regulate Soil Organic Carbon Stocks Along the Elevational Gradient on Alpine Grassland over the Qinghai–Tibet Plateau

Abstract

The Qinghai–Tibet Plateau, a region susceptible to global change, stores substantial amounts of soil organic carbon (SOC) in its alpine grassland. However, little is known about how SOC is regulated by soil microbial communities, which vary with elevation, mean annual temperature (MAT), and mean annual precipitation (MAP). This study integrates phospholipid fatty acid (PLFA) analysis to simultaneously resolve microbial biomass, community composition, and membrane lipid adaptations along an elevational gradient (2861–5090 m) on the Qinghai–Tibet Plateau. This study found that microbial PLFAs increased significantly with rising MAP, while the relationship with MAT was nonlinear. PLFAs of different microbial groups all had a positive effect on SOC storage. At higher altitudes (characterized by lower MAP and lower MAT), Gram-positive bacteria dominated bacterial communities, and fungi dominated the overall microbial community, highlighting microbial structural adaptations as key regulators of carbon storage. Saturated fatty acids with branches of soil microbial membrane dominated across sites, but their prevalence over unsaturated fatty acids decreased at high elevations. These findings establish a mechanistic link between climate-driven microbial community restructuring and SOC vulnerability on the QTP, providing a predictive framework for carbon–climate feedbacks in alpine systems under global warming.

1. Introduction

Soil organic carbon (SOC) constitutes the largest terrestrial carbon pool [1], exerting profound controls on global climate regulation, soil fertility, and ecosystem sustainability [2,3,4]. The stability and sequestration of SOC are controlled by complex interactions between abiotic drivers (e.g., temperature and precipitation) and biotic actors, particularly soil microorganisms, which mediate carbon mineralization, transformation, and stabilization [5,6,7]. These microbially mediated carbon cycling processes exhibit vulnerability in high-altitude ecosystems, where environmental constraints exert disproportionate selective pressures, such as alpine grasslands [8,9]. This vulnerability is acutely substantiated on the Qinghai–Tibet Plateau (QTP), the world’s highest and most extensive plateau. The plateau harbors substantial SOC stocks developed under its unique climatic and edaphic conditions. Alpine grassland soils on the QTP alone are estimated to store approximately 33.5 Pg of organic carbon at 0–0.75 m depth [10]. While the potential impacts of soil respiration and land-use change on SOC have been assessed [10], and microbial necromass contributions to SOC quantified [11], how soil microbial communities, structured along natural elevation gradients (and thus climatic gradients), respond to environmental drivers and subsequently influence SOC dynamics remains unclear.

As the primary biological agents driving decomposition and stabilization processes within the carbon cycle, soil microorganisms are profoundly influenced by these climate changes [12,13,14]. Generally, warmer temperatures at lower elevations can enhance enzymatic reaction rates and overall microbial metabolic activity, potentially accelerating the decomposition of more labile SOC fractions. For instance, certain thermophilic or warm-adapted bacterial taxa may become more abundant and active in warmer, lower-elevation soils, efficiently mineralizing complex organic compounds and releasing CO₂ [15,16]. Conversely, the colder conditions prevailing at higher altitudes impose selective pressure, selecting for psychrophilic or cold-tolerant microbial communities [17]. Alongside temperature, the variation in mean annual precipitation (MAP) along altitude gradient also plays a crucial role. Higher precipitation (and consequently higher soil moisture) at certain altitudes can drastically alter microbial community composition and function. Fungi are more adaptable to moist environments compared to bacteria. The increased soil moisture provides a more favorable habitat for fungal hyphae to spread and penetrate through soil porosity [18,19]. In addition, the shift in soil moisture also affects the balance between Gram-positive (G⁺) and Gram-negative (G⁻) bacteria. G⁻ bacteria typically have a thinner cell wall and are more sensitive to osmotic pressure. Higher precipitation can create a more stable and less stressful environment, which may favor the growth and survival of G⁻ bacteria [20].

SOC dynamics on the QTP are intricately linked to elevation-driven variations in microbial community characteristics. Studies demonstrate that altitude significantly alters microbial community structure (PLFA-based) and carbon substrate utilization patterns [13]. Elevation serves as a powerful natural experiment integrating changes in key climatic variables. For example, phospholipid fatty acid analyses reveal that forest soil microorganisms adapt to natural or experimental warming by increasing membrane saturated fatty acids [21]. However, a critical knowledge gap persists: although PLFA profiling has been used to study elevational responses of microbial community structure and physiological adaptations (e.g., membrane lipid remodeling), no study has systematically integrated microbial biomass, community structure, and biochemical mechanisms to decipher climate-driven microbial regulation of SOC stocks on the QTP grassland. The phospholipid fatty acid (PLFA) approach is uniquely positioned to address this integrative gap. PLFAs, present in all living cell membranes except Archaea, are taxon-specific. This approach not only quantifies microbial biomass (G⁺, G⁻, fungi) and functional balances (e.g., G⁺/G⁻, F/B ratios) but also directly reflects stress adaptations (e.g., increased unsaturated fatty acids maintaining membrane fluidity under cold stress [22]), capturing changes undetectable by DNA-based methods. This integrative capacity—simultaneously capturing biomass, community structure, and biochemical mechanism—makes PLFA analysis particularly suited to investigate the multidimensional microbial drivers of SOC dynamics. Therefore, climate-driven variations in microbial biomass and community structure and membrane lipid composition are likely fundamental determinants of SOC dynamics on the Qinghai–Tibet Plateau.

Here, we surveyed 35 sites along the altitude gradient on the Qinghai–Tibet Plateau. Using phospholipid fatty acid (PLFA) analysis to characterize microbial biomass and community composition, alongside measurements of SOC and key environmental variables, this study specifically addresses the following critical questions: (1) How do the combined and potentially interacting effects of MAT and MAP shape the biomass (abundance) and community structure (e.g., F/B ratio, G⁺/G⁻ ratio) of soil microorganisms in alpine grasslands? (2) Do shifts in F/B dominance or key functional groups and associated microbial membrane lipid adaptations directly regulate SOC stocks independent of climate?

2. Materials and Methods

2.1. Study Area

The Qinghai–Tibet Plateau (QTP) spans from 74° E to 104° E and 25° N to 40° N, covering approximately 2.6 × 10⁶ km² with an average elevation of more than 4500 m above sea level [23]. Its annual average temperature ranges from −4 °C to 13.4 °C, and its precipitation varies significantly across different regions [24]. Grasslands on the QTP account for 54–70% of the total area of the QTP [25]. The main vegetation types in the study are alpine steppe and alpine meadow. Among which, the dominant plants in the alpine steppe are Kobresia pygmaea and Kobresia humilis, while the alpine meadow is dominated by Kobresia tibetica, Poa crymophila, and Kobresia pygmaea. The soil types in the study region were mainly classified into alpine steppe soil (as Cambisols in FAO taxonomy) and alpine meadow soil (as Cambisols in FAO taxonomy) [26].

2.2. Soil Sampling

Sampling was conducted from July to August 2021, with a total of 35 sampling sites established (85°14′17″ E–97°51′11″ E, 28°53′38″ N–35°31′23″ N) along an elevational gradient (2861–5090 m above sea level) on the Qinghai–Tibet Plateau (Figure S1). Three replicate soil samples (0–10 cm) were collected in each site. The sampling sites were selected in areas with minimal human disturbance, limited grazing interference, and well-preserved natural vegetation. Additionally, care was taken to ensure that the sampling sites adequately represented the vegetation and soil type characteristics of their respective regions. At each sampling site, seven soil cores (2.5 cm in diameter) were randomly collected from the surface (0–10 cm) and mixed as one composite sample per quadrat (1 m × 1 m). Soil samples were stored at 4 °C until analysis.

2.3. Climate and Soil Factors

The mean annual precipitation (MAP) and temperature (MAT) were obtained from the National Tibetan Plateau Science Data Center (https://data.tpdc.ac.cn (accessed on 9 December 2024)). Soil organic C (SOC) was measured using the potassium dichromate oxidation method. We characterized soil physicochemical properties including pH values, total nitrogen (TN), total phosphorus (TP), ammonium nitrogen (NH₄⁺-N), and nitrate nitrogen (NO₃⁻-N). Details are shown in Methods S1 (Supplementary Materials).

2.4. Microbial Community Structure

Phospholipid fatty acids (PLFAs) were extracted from each soil subsample using the Bossio and Scow method [27]. A chloroform-methanol-phosphate buffer solution (1:2:0.8, volume ratio) was used to extract lipids from 8 g of freeze-dried soil. The extracted lipids were fractionated on a 0.5 g silicic acid column [28]. The methanol fraction containing phospholipids was methylated to fatty acids methyl esters using mild alkaline methanolysis. Fatty acid 19:0 was used as an internal standard to add to fatty acid methyl esters. In addition, samples were analyzed and identified by an Agilent 6850 series Gas Chromatograph (Agilent Technologies, Santa Clara, CA, USA) with MIDI peak identification software (MIDI Inc., Newark, NJ, USA). The PLFAs i-14:0, i15:0, α15:0, i16:0, 17:1ω9c, i17:0, and α17:0 were used to calculate the relative biomass of Gram-positive (G⁺) bacteria [29,30]. The PLFAs 16:1ω9c, 16:1ω7c, 17:1ω8c, cy-17:0ω7c, 18:1ω7c, 18:1ω6c, 18:1ω5c, cy-19:0ω9c, cy-19:0ω7c, 20:1ω9c were used to calculate the relative biomass of Gram-negative (G⁻) bacteria [31]. The sum of the G⁺ and G⁻ bacteria was expressed as the bacterial biomass [29]. The PLFAs 18:3ω6c, 18:2ω6c, and 18:1ω9c indicated fungal biomass [31,32,33]. The G⁺ bacterial PLFA to G⁻ bacterial PLFA ratio (G⁺/G⁻) and the fungal to bacterial PLFA ratio (F/B) were used to evaluate the microbial community structure. We also divided the soil microbial PLFAs into three categories: saturated fatty acids with branches (BRFAs), saturated fatty acids without branches (SAFAs) and unsaturated fatty acids (UNFAs) to characterize the lipid composition of the microbial cell membrane [18]. The PLFAs 14:0 iso, 15:0 iso, 15:0 anteiso, 16:0 iso, 17:0 iso, 17:0 anteiso, 18:0 iso and 19:0 iso were used to calculate the abundance of BRFAs. The PLFAs 14:0, 15:0, 16:0, 17:0, 18:0 and 20:0 were used to calculate the abundance of SAFAs. The PLFAs 14:1ω5c, 15:1ω6c, 16:1OH, 16:1ω5c, 16:1ω7c, 17:1ω8c, 18:1ω7, 18:1ω9c and 18:2ω6c were used to calculate the abundance of UNFAs. The concentration of PLFAs was expressed as nmol g⁻¹ dry soil.

2.5. Data Analyses

Data were analyzed using R4.4.3. Before statistical analysis, all data were tested for normality and homoscedasticity of variance. To reveal the altitudinal distribution of soil organic carbon (SOC), the relationship between elevation and SOC was fitted using lasso regression, followed by 1000 bootstrap iterations of piecewise regression. Linear and nonlinear fitting were employed to examine the relationships between climate factors (MAT and MAP) and SOC content. Furthermore, regression analysis was used to explore the relationships between environmental factors (elevation, MAT, MAP) and microbial PLFA content (G⁺, G⁻, bacteria, fungi, BRFAs, SAFAs and URFAs). Redundancy analysis (RDA) was used to visualize the relationships between the response variable values (PLFAs) and soil environmental factors (TN, TP, NH₄⁺-N, NO₃⁻-N and pH). For microbial community structure, the PLFA pattern was analyzed using principal component analysis (PCA). Linear and nonlinear fitting were used to assess the relationships between climate factors and the ratios of G⁺/G⁻ bacteria and fungi/bacteria (F/B). Finally, ordinary least squares (OLS) regression was performed to determine the relationships between microbial PLFAs, the G⁺/G⁻ ratio, the F/B ratio, and SOC content.

3. Results

3.1. Relationships Between Climate Factors and Soil Organic Carbon Content

There were significant negative responses of the MAT to elevation (Figure 1B, R² = 0.27, p = 0.00). The SOC content increased with MAT, peaking at ca. 2.5 °C, and declined gradually after this threshold (Figure 1C, p = 0.00). The SOC content increased with the increasing MAP (Figure 1E, R² = 0.51, p = 0.00).

3.2. Relationships Between Environmental Factors and Soil Microbial Biomass

With increasing elevation, the abundance of G⁺ bacterial PLFA and bacterial PLFAs first decreased gradually, then increased moderately to a peak at ca. 4300 m, before decreasing (Figure 2A,C, p = 0.02, p = 0.02). The abundance of G⁻ bacterial and fungal PLFAs peaked at ca. 3700 m, then declined (Figure 2B,D, p = 0.05, p = 0.02). The abundance of G⁺ bacterial, G⁻ bacterial, bacterial, and fungal PLFAs increased with MAT, peaking at ca. 2.5 °C and declined after this threshold (Figure 2E–H, p = 0.04, p = 0.02, p = 0.03, p = 0.05). The abundance of G⁺ bacterial, G⁻ bacterial, bacterial, and fungal PLFAs increased with the increasing MAP (Figure 2I–L, p = 0.00).

To elucidate the soil environmental factors driving changes in microbial PLFA abundance, redundancy analysis was performed (Figure S2). The results showed that the first and second axes explained 98.28% and 1.66% of the variation, respectively. The abundances of G⁺ bacterial, G⁻ bacterial, and fungal PLFAs were positively correlated with the contents of total nitrogen (TN), total phosphorus (TP), ammonium nitrogen (NH₄⁺-N), and nitrate nitrogen (NO₃⁻-N), but negatively correlated with soil pH. Axis 1 correlated most strongly with TN, followed by TP, NH₄⁺-N, pH, and NO₃⁻-N. Soil environmental factors exhibited distinct responses to climate change (Figure S3). The contents of TN, TP, NH₄⁺-N and NO₃⁻-N increased with MAP, and pH decreased with MAP. The contents of TN and TP reached relatively high values around 2.5 °C.

Both the abundance of BRFAs and UNFAs decreased linearly with increasing elevation; the abundance of SAFAs also showed an overall decreasing trend with elevation. (Figure 3A, p = 0.01, p = 0.04, p = 0.02). The abundance of UNFAs and SAFAs increased initially, peaking at ca. 2.5 °C, and then decreased with increasing MAT (Figure 3B, p = 0.03). The abundance of BRFAs increased with MAT, peaking at ca. 4 °C, and then decreased (Figure 3B, p = 0.03). The abundance of BRFAs, UNFAs and SAFAs all increased with increasing MAP (Figure 3C, R² = 0.40, R² = 0.48, R² = 0.40). BRFAs consistently being more abundant than UNFAs across all gradients. The difference between BRFAs and UNFAs gradually decreased with increasing elevation. In contrast, the difference increased with rising MAT and MAP.

3.3. Soil Microbial Community Composition

The first principal component (PC1) explained about 94.61% of the variation in the data set, while the second, PC2, only explained 3.20% (Figure 4A,B). The loadings for the abundance of G⁺ bacterial, G⁻ bacterial, and fungal PLFAs on PC1 were 0.973, 0.968, and 0.977, respectively. On PC2, the loadings were −0.163, 0.250, and −0.085 for the abundance of G⁺ bacterial, G⁻ bacterial, and fungal PLFAs, respectively. The first PC increased with MAT, peaking at ca. 2.5 °C, and then deceased (Figure 4A). Both the fungal PLFA, G⁺ bacterial PLFA and G⁻ bacterial PLFA vectors were aligned with and positioned closer to sample points characterized by higher MAP (Figure 4B). This indicates that sites with greater annual precipitation exhibited elevated levels of both fungal and bacterial PLFA biomarkers. The first PC increased with MAP (Figure 4B, R² = 0.41, p = 0.00). The ratio of G⁺/G⁻ increased with the increasing MAT (Figure 4C, p = 0.00). The ratio of F/B decreased with increasing MAT, reaching its lowest point at ca. 2.5 °C, and then increased slowly thereafter (Figure 4D). The ratio of G⁺/G⁻ decreased with the increasing MAP (Figure 4E, p = 0.00). The ratio of F/B decreased with the increasing MAP (Figure 4F, R² = 0.47, p = 0.00)

3.4. The Contribution of Microbial Community to Soil Organic Carbon

The soil organic carbon content increased with the abundance of G⁺ bacterial, G⁻ bacterial, fungal, and bacterial PLFAs (Figure 5A,B,D,E) but decreased with the increasing ratios of G⁺/G⁻ and F/B (Figure 5C,F).

The soil organic carbon content increased with the abundance of unsaturated fatty acids, saturated fatty acids with branches, and saturated fatty acids without branches (Figure 6).

4. Discussion

Based on sampling at 35 sites (elevation: 2800–5200 m) using PLFA analysis, this study reveals distinct climatic controls on soil microbial biomass, community structure, and soil organic carbon (SOC) storage across an elevational gradient on the Qinghai–Tibet Plateau. Key findings include the following: (1) a linear increase in microbial biomass (PLFAs) and SOC with rising mean annual precipitation (MAP); (2) a unimodal response of microbial biomass and SOC to mean annual temperature (MAT), peaking at mid-elevations; (3) shifts in microbial community structure (F/B and G⁺/G⁻ ratios) driven by MAP and MAT, reflecting adaptations to water and temperature stress; and (4) a strong mechanistic link between microbial community adaptations (biomass, structure, membrane lipids) and SOC dynamics.

4.1. Response of Microbial Biomass to Climatic Gradients

Our results demonstrate a significant positive relationship between mean annual precipitation (MAP) and the abundance of key microbial groups (G⁺ bacteria, G⁻ bacteria, total bacteria, fungi), as quantified by PLFA biomarkers (Figure 2I–L). This finding aligns with a large body of research emphasizing water availability as a primary driver of soil microbial biomass in terrestrial ecosystems [34,35]. The observed pattern is consistent with a previous comprehensive meta-analysis, which reported that increased precipitation significantly enhanced soil microbial biomass by an average of 21.40% in drier regions (MAP < 600 mm [34]. The underlying mechanism is intuitive yet multifaceted. Adequate moisture facilitates not microbial activity and diffusion of dissolved nutrients and substrates. It also improves overall cell hydration for enzymatic function and membrane integrity. Furthermore, water availability governs plant productivity and thus the input of root exudates and litter—key energy sources fueling microbial growth and reproduction [36]. The RDA results revealed a positive correlation between microbial PLFA and soil nutrients (e.g., nitrogen and phosphorus content; Figure S2), which increased with rising MAP (Figure S3). This further suggests that the positive effect of MAP on microbial PLFA may be mediated by soil nutrients. This precipitation-driven microbial proliferation acts as a key intermediary in the soil carbon sequestration processes observed across the gradient. Furthermore, our results also demonstrate that this precipitation dependence is universal across microbial functional groups (G⁺ bacteria, G⁻ bacteria, and fungi). This universality suggests water limitation affects broad physiological processes rather than specific taxa.

In contrast to the relatively linear response to MAP, the influence of mean annual temperature (MAT) on microbial PLFA abundance exhibited a pronounced nonlinear pattern across the elevational gradient (Figure 2A–H). At the lower end of our study’s elevational gradient (corresponding to relatively higher MAT), an increase in elevation (and consequent decrease in MAT) was associated with a rise in microbial biomass (PLFAs). This initial increase could be attributed to several interacting factors, potentially alleviating metabolic stress compared to warmer conditions. Lower temperatures may reduce maintenance respiration costs and slow decomposition rates. This could lead to a transient accumulation of microbial biomass or favor microbial communities adapted to cooler conditions with potentially higher biomass yields [37]. Furthermore, complex interactions among co-varying environmental factors (e.g., shifts in vegetation, soil moisture regimes, organic matter quality) along the elevational gradient likely contribute to this pattern. The more favorable hydrothermal conditions at mid-elevations in our study might promote microbial growth by alleviating nitrogen and phosphorus limitations (Figure S3).

However, this trend reversed at the highest elevations (>ca. 4250 m). Further reductions in MAT, coupled with significantly lower MAP (Figure 1B,D), imposed severe physiological constraints on microbial communities. The combined extreme cold and aridity stress strongly limits microbial activity and growth. Under such harsh conditions, microbial communities are forced to allocate more of their energy budget towards maintenance and survival (e.g., osmoregulation, repair, stress response proteins) rather than growth and biomass production. This trade-off is reflected in declining microbial metabolic efficiency with increasing environmental stress, as evidenced by studies showing increases in microbial metabolic quotient (respiration per unit biomass) and decreases in carbon use efficiency at higher altitudes or under colder conditions [38]. Consequently, the observed decline in PLFA abundance at the highest, coldest, and driest sites represents an explicit limitation imposed by the harshest climatic extremes within our study region. The increased proportional representation of unsaturated fatty acids (UNFAs) within microbial membrane lipids at high altitudes (Figure 3A) is a cold-adaptation mechanism. Saturated fatty acids have higher melting points [39], and microbes incorporate them under warmth to stabilize membranes [18]. At low temperatures, however, rigid membranes impede transmembrane protein function [22]. Unsaturated lipids maintain fluidity, preserving nutrient transport capacity. The adaptive strategies of membrane components to temperature changes may further influence microbial regulatory processes, such as respiration. Consequently, lipid remodeling represents a key trade-off between stress tolerance and biomass production. This trade-off is a previously underemphasized constraint on SOC sequestration in alpine systems.

4.2. Response of Soil Organic Carbon to Climatic Gradients

The response of soil organic carbon (SOC) content to climatic gradients (MAT and MAP) closely mirrored that of microbial biomass (PLFAs) (Figure 1C,E). This parallel suggests a strong mechanistic link between microbial activity and SOC dynamics in these alpine grassland ecosystems. Our data revealed a significant positive correlation between the abundance of all major microbial groups (G⁺ bacteria, G⁻ bacteria, fungi, total bacteria) and SOC content (Figure 5A,B,D,E). These relationships underscore the multifaceted role of soil microbes in SOC formation and stabilization. Firstly, enhanced plant productivity is stimulated under more favorable environmental conditions (moderate MAT and higher MAP) [40,41,42]. Increased inputs of plant-derived organic matter (litter, root exudates) provide the fundamental substrate for microbial metabolism and SOC accumulation. Secondly, a larger standing microbial biomass inherently represents a larger pool of potential microbial necromass. Microbial necromass, derived from dead microbial cells, is increasingly recognized as a critical and persistent component of stable SOC [11,43]. Global and regional syntheses support this, demonstrating that microbial necromass carbon can contribute substantially—approximately 47% in global grasslands [44] and 45% in Tibetan alpine grassland topsoils [11]—to the total SOC pool. Therefore, the accumulation of microbial necromass under the more conducive climatic conditions found at mid-elevations in our study likely represents a key pathway contributing to the observed peak in SOC content. The combined effect of increased plant inputs and enhanced microbial biomass/necromass production under optimal conditions synergistically promotes SOC storage.

Our analysis of microbial membrane lipids reinforces this climatic dependency: the abundances of BRFAs, SAFAs, and UNFAs all increased with MAP and followed unimodal responses to MAT (Figure 3B,C), mirroring trends in total PLFAs and SOC. This parallel underscores that climatic drivers govern not only microbial biomass but also lipid composition of cell membranes. The PCA results further reinforce the regulatory role of climate-driven microbial community on SOC: PC1 (accounting for 94.61% of variance) showed correlation with MAT/MAP gradients and aligned with SOC trends (Figure 1C,E and Figure 4A,B), suggesting a coordinated community-wide mechanism in SOC accumulation.

4.3. Shifts in Microbial Community Structure and Implications for Carbon Cycling

Beyond total biomass, our study revealed significant shifts in microbial community composition (structure) in response to climatic factors, with important implications for SOC dynamics. We found a negative correlation between MAP and the fungal-to-bacterial biomass ratio (F/B) (Figure 4F). This result aligns with observations that bacterial communities often exhibit greater sensitivity to water stress compared to fungal communities [5,34,35]. Fungi possess several adaptations conferring superior tolerance to low moisture conditions. Their filamentous hyphal networks enable them to bridge air gaps and access water and nutrients in soil micropores unavailable to bacteria [18,19]. They can also accumulate compatible solutes for osmoregulation, and their often K-selected strategy allows them to persist under resource limitation [45,46,47,48,49]. Consequently, during drought or in inherently drier environments (low MAP), fungi maintain their relative abundance better than bacteria, leading to an elevated F/B ratio. Conversely, as MAP increases, creating moister and potentially more resource-rich conditions, fast-growing bacteria (often characterized as r-strategists or copiotrophs) can rapidly exploit labile substrates. This increases their biomass proportionally more than fungi, thereby decreasing the F/B ratio [20,50,51]. This shift may accelerate labile carbon mineralization because bacteria exhibit faster turnover times than fungi [52,53].

The Gram-positive-to-Gram-negative bacteria (G⁺/G⁻) ratio also displayed systematic variation along the environmental gradients. We observed a positive correlation between the G⁺/G⁻ ratio and MAT (Figure 4C), and a negative correlation with MAP (Figure 4E). More importantly, the G⁺/G⁻ ratio exhibited a significant negative relationship with SOC content (Figure 5C). This pattern can be interpreted within the framework of microbial life-history strategies and resource availability. Gram-negative bacteria (G⁻) are typically associated with copiotrophic conditions. They thrive on readily available, labile organic compounds. These compounds are often derived from recent plant inputs or root exudates, which are more abundant in productive, less stressed environments [20,54,55]. In contrast, Gram-positive bacteria (G⁺), with their thicker peptidoglycan cell walls offering greater resistance to desiccation [45,56], and often possessing capabilities to degrade more complex organic matter, tend to become relatively more dominant under conditions of environmental stress (e.g., lower moisture, nutrient limitation, or potentially colder temperatures that slow decomposition of complex organics). Therefore, the ratio (G⁺/G⁻) serves as a sensitive indicator of the prevailing environmental stress level and the associated quality of organic matter substrates, reflecting the status and potentially the vulnerability of the soil organic carbon pool in these sensitive alpine ecosystems.

Our analysis of membrane lipid groups provides further mechanistic insight into these community-level adaptations and their physiological underpinnings. The consistent dominance of BRFAs across all gradients (Figure 3) suggests a pervasive strategy among soil microbes to increase membrane stability via branched chains under the generally harsh conditions of the QTP. The narrowing gap between BRFAs and UNFAs abundance at higher elevations (Figure 3A) indicates intensified physiological stress, where reduced metabolic activity and energy limitation likely constrain investment in unsaturated lipids needed to maintain fluidity in the cold. Conversely, the widening BRFA-UNFA divergence under higher MAT and MAP (Figure 3B,C) reflects greater resource availability enabling diverse membrane strategies. Increased UNFAs (e.g., prevalent in Gram-negative bacteria) support higher membrane fluidity and metabolic activity in favorable conditions. Simultaneously, the sustained dominance of BRFAs highlights the retained importance of stress-resilient traits even in milder microclimates, possibly reflecting the legacy of adaptation or ongoing need for membrane stability. This partitioning of lipid investment aligns cohesively with the shifts in F/B and G⁺/G⁻ ratios, collectively depicting a microbial community that is structurally and physiologically optimized for carbon processing under the prevailing climatic constraints. The inverse relationship between G⁺/G⁻ and SOC powerfully underscores the functional link between microbial community structure adaptation and carbon storage outcomes in these high-altitude ecosystems.

4.4. Limitations and Outlook

While our study provides mechanistic insights into climate–microbe–SOC linkages in alpine grasslands, several limitations warrant consideration. First, the elevational gradient approach inherently co-varies multiple environmental factors (e.g., atmospheric pressure, UV radiation, soil parent material, vegetation composition) beyond MAT and MAP. Second, the observational nature of our study constrains causal inference; experimental manipulations (e.g., warming/watering) are needed to validate predicted SOC responses to climate change. Finally, future work should address seasonal dynamics, as microbial biomass and lipid composition may fluctuate substantially with freeze-thaw cycles and plant phenology, potentially altering SOC formation pathways.

5. Conclusions

This study demonstrates that climate-driven changes in soil microbial communities critically regulate soil organic carbon (SOC) storage on the Qinghai–Tibet Plateau. The findings indicate the following:

(1)

Microbial biomass (indicated by PLFA) increases with mean annual precipitation but shows a unimodal response to mean annual temperature, peaking then declining. Crucially, higher microbial biomass corresponds to increased SOC.

(2)

At higher elevations (lower MAP/MAT), shifts in microbial community structure (higher G⁺/G⁻ ratio and F/B ratio) adapt to harsher conditions. The increased G⁺/G⁻ and F/B ratios correlate negatively with SOC storage, highlighting their role as key mediators of carbon storage.

(3)

Microbial membrane lipid composition also adapts to harsher condition: branched saturated fatty acids (BRFAs) prevail across sites, but the narrowing abundance gap between BRFAs and unsaturated fatty acids (UNFAs) at high elevations reflects costly energy allocation toward maintaining membrane fluidity under cold/dry stress.

These findings increase our understanding of how future changes in precipitation and temperature may regulate soil organic carbon storage through microbial community restructuring in alpine grasslands on the Qinghai–Tibet Plateau. Projected warming and precipitation shifts will restructure microbial communities, potentially reducing SOC storage in high-elevation grasslands. Future work should incorporate seasonal microbial dynamics and necromass turnover to reduce uncertainties in carbon–climate model predictions and validate these findings through experimental approaches.