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Article

Glomalin-Related Soil Protein Plays Different Roles in Soil Organic Carbon Pool Maintaining among Different Grassland Types

by
Meiniu Yang
1,2,3,
Lianlian Fan
1,2,3,
Xuexi Ma
1,2,3,
Yuanye Liang
1,2,3,
Jiefei Mao
1,2,3,
Jiangyue Li
1,2,3 and
Yaoming Li
1,2,3,*
1
Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China
2
Research Center for Ecology and Environment of Central Asia, Chinese Academy of Sciences, Urumqi 830011, China
3
University of Chinese Academy of Sciences, Beijing 100049, China
*
Author to whom correspondence should be addressed.
Agronomy 2024, 14(8), 1823; https://doi.org/10.3390/agronomy14081823
Submission received: 9 July 2024 / Revised: 14 August 2024 / Accepted: 17 August 2024 / Published: 18 August 2024
(This article belongs to the Section Soil and Plant Nutrition)
Browse Figures
Versions Notes

Abstract

:
Glomalin-related soil protein (GRSP) is an important component of soil organic carbon (SOC), which can promote long-term SOC sequestration. However, GRSP distribution characteristics and its contribution to the SOC pool among different grassland types remain poorly understood. Therefore, six grassland types (alpine meadow, mountain meadow, temperate meadow steppe, temperate steppe, temperate desert steppe, and temperate desert) were chosen to evaluate the contribution of GRSP to the SOC pool and the factors that influence GRSP accumulation in the Irtysh River Basin in China. The results revealed that GRSP (EE-GRSP, T-GRSP) accumulated more in the 0–10 cm soil layer than in the 10–20 cm soil layer (p < 0.05). GRSP content was higher in alpine grasslands (15.69 mg·g−1) than in desert grasslands (5.45 mg·g−1). However, their contribution to the SOC pool exhibited an opposite trend, whereas GRSP-C/SOC even accounted for 11.88% in the desert grasslands. The redundancy analysis (RDA) showed that SOC was the top important positive regulator for GRSP accumulation both in the two layers (explanatory rate > 80%). Besides the SOC factor, the two soil layers had different factors in regulating GRSP accumulation. Changes in GRSP content in the 0–10 cm soil layer were more strongly associated with mean annual temperature (MAT), sand content, soil water content (SWC), and silt content. In contrast, in the 10–20 cm soil layer, GRSP content was more influenced by SWC, electrical conductivity (EC), and pH (p < 0.05). Additionally, the main factor in the GRSP content variation was the interaction between climate and soil in the two soil layers (explanatory rate > 80%). Our findings underscore the critical role of GRSP in facilitating SOC sequestration within desert grasslands and elucidate the primary factors driving GRSP distribution across varying soil depths.

1. Introduction

The glomalin-related soil protein (GRSP), produced by arbuscular mycorrhizal fungi (AMF), is a distinct glycoprotein that represents a stable form of microbial-derived carbon (C) in soils [1,2,3,4]. Generally, GRSP is broadly divided into easily extracted glomalin-related protein (EE-GRSP) (i.e., newly produced and unstable proteins), and total glomalin-related protein (T-GRSP) (i.e., the sum of new and old proteins) [5]. As an important binder for soil aggregate formation, GRSP can improve soil structure and promote the accumulation of C in soil [3]. GRSP is considered an essential component of the soil organic carbon (SOC) pool in terrestrial ecosystems [3,6]. To better understand the vital role of GRSP in SOC sequestration, it is crucial to investigate changes in GRSP of grassland ecosystems.
Currently, GRSP is widely studied in forest, farmland, grassland, and other ecosystems, while its distribution and contribution to the SOC pool vary in different soils [6,7,8,9]. Que et al. [10] discovered that GRSP content ranged from 1.96 to 3.12 mg·g−1 in forest, grassland, and agricultural soils, accounting for 12.5% to 29.0% of SOC. The content of GRSP was in the range from 1.49 to 5.21 mg·g−1 in the temperate steppe, and its contribution to the SOC pool was in the range from 0.83% to 2.88% [11]. Moreover, it was found that the GRSP content and its contribution to SOC decreased gradually from the surface to deeper layers in soils, mainly because soil nutrients decreased with deeper soil layers [12,13,14]. These studies further suggest that GRSP plays an important role in the SOC pool and is affected by different grassland types.
The accumulation of GRSP in the soil is influenced by various factors, such as soil properties, climatic conditions, etc. [15,16]. For example, the strong positive relationships of GRSP content with SOC, total N (TN), and total P (TP) content have been confirmed by other studies [17,18]. This is because the abundant soil nutrients can increase microbial activity for glomalin production [19]. Furthermore, temperature and precipitation are found as two important climate parameters for GRSP production and decomposition [13]. GRSP generally increases along with lower temperatures and high precipitation [13,20]. Among the soil types, acidic soils usually contain the highest GRSP content, while GRSP content decreases with increasing soil pH [21,22]. The GRSP decomposition rate in acidic soils is slow because Fe and Al sesquioxides increase its resistance to degradation. Soil pH and bulk density (BD) directly influence GRSP content, whereas electrical conductivity (EC) and soil moisture affect GRSP indirectly through pH and BD changing [23,24]. Factors, such as soil nutrients and soil properties (i.e., pH, EC) are different between 0–10 cm and 10–20 cm soil layers [25,26], which can lead to varying effects on GRSP distribution between the two soil layers. However, how these factors influence GRSP in different soil depths among grassland types is not clear.
Globally, grassland is one of the most extensive vegetation types, containing 34% of the terrestrial ecosystem’s SOC stock, which plays key roles in C cycling and C balancing [27,28]. In the Irtysh River Basin of northern Xinjiang in China, its rich natural grassland ecosystems play an important role in maintaining the regional C balance and providing ecological services. Grassland types show a clear vertical banding distribution pattern due to the disparity in elevation in this study area. With decreasing elevation, the grassland types are, in order, alpine meadow (AM), mountain meadow (MM), temperate meadow steppe (TMS), temperate steppe (TS), temperate desert steppe (TDS), and temperate desert (TD). The region is primarily characterized by traditional pastoralism, and the region has been facing severe grazing overloading since the early 2000s, exacerbating the fragility and sensitivity of the grassland ecosystem [29].
Current research on the impact of climate, vegetation, and soil factors on SOC sequestration in these grasslands is steadily growing [30]. However, the specific contribution of GRSP-C to SOC across different grassland types in the Irtysh River Basin remains unclear. Therefore, the objectives of this study are to examine the accumulation of GRSP and its contribution to the SOC pool across different grassland types, as well as to evaluate the factors influencing GRSP accumulation in grassland ecosystems. Our research aims to identify the factors affecting GRSP accumulation, which could inform GRSP-mediated soil management strategies and enable a more precise assessment of GRSP’s significance in the SOC pool within grassland ecosystems.

2. Material and Methods

2.1. Study Area

The study area is located in the Irtysh River Basin in the northern part of the Xinjiang Uygur Autonomous Region, China (44°40′–49°30′ N, 84°50′–90°53′ E) (Figure 1). Grassland is the main vegetation type in the study area, showing a clear vertical zonal distribution pattern depending on elevation, with a fragile ecosystem that is unusually sensitive to global change. The region experiences a temperate continental cold climate, with an elevation ranging from approximately 300 to 4000 m. In the mountainous areas, the average annual precipitation is 400–600 mm, and the average annual temperature ranges from −4 to −2 °C [31]. The plains are influenced by desert climate, with annual precipitation as low as 120–200 mm and an average temperature of about 6 °C (detailed environmental information is presented in Table 1). The grassland soil types in the study area belong to the “Chinese soil classification system”. The soil is brown calcic soil, black calcic soil, and chestnut calcic soil with silty and sandy texture [31]. Among six grassland types, the soil pH and BD values are 4.39–10.25 and 0.49–1.89 g cm−3, respectively. Moreover, the SOC, TN, and TP contents are 1.61–108.70 g kg−1, 0.03–10.39 g kg−1, and 0.21–2.78 g kg−1 (Table 2). In this study, alpine and mountainous grasslands are grazed in summer and temperate desert grasslands are grazed in spring and fall, and the animal species are dominated by sheep and cattle.
The study area is characterized by natural grassland with native species. The dominant species of alpine meadows include Festuca kurtschumica, Carex stenocarpa, Alchemilla pinguis, Leontopodium leontopodioides, etc.; the dominant species of mountain meadows include Poa alpina, Festuca kurtschumica, Carex stenocarpa, Achillea mille-folium, etc.; the dominant species of temperate meadow grassland mainly include Seriphidium gracilescens, Stipa glareosa, Rosa spinosissima, etc.; and the temperate desert grassland is dominated by short-lived plants.

2.2. Site Selection and Sampling Collection

Based on Xinjiang grassland distribution map, 69 sampling sites in six major grassland types were selected according to the elevation gradient: AM, n = 10, MM, n = 18, TMS, n = 8, TS, n = 14, TDS, n = 6, and TD, n = 13 (Figure 1). In this study, we conducted sample collection at different sites in different grassland types, with samples representing different ecological conditions and soil contexts to cover the range of natural variation.
The 1 m × 1 m quadrat was randomly placed in each plot at the peak plant biomass from May to August 2022. Within each quadrat, the presence of aboveground plant species was recorded as plant species richness and vegetation cover. The aboveground plant biomass was harvested by clipping at ground level, then, all plant biomass was oven-dried at 65 °C for 48 h and then weighed to determine aboveground biomass (AGB).
After removing the aboveground vegetation and litter by trimming 0.5 cm from the soil surface, we collected five soil cores from both the 0–10 cm and 10–20 cm depths using a 3 cm diameter soil auger along the diagonal of each 1 m × 1 m quadrat. The soil cores were then combined into a composite sample, resulting in three replicates per site. Additionally, we used a ring cutter with a volume of 60 cm3 to take in bulk soils in two soil depths, 0–10 cm and 10–20 cm, and then brought them back to the laboratory for oven drying. The BD value (g cm−3) is the drying soil weight ratio of 60. The 207 samples were transported back to the laboratory for further analysis of soil properties.

2.3. Soil Physicochemical Properties Analysis

The air-dried samples were sieved through a 2 mm mesh to remove all visible roots, residues, and stones. Soil properties were determined using the methods described by Carter [32]. Soil pH and EC were measured in a 1:2.5 (w/w) soil: water suspension with a digital pH meter and a 5:1 water: soil, respectively. The soil water content (SWC) was determined by using a portable soil three-parameter meter (Stevens HydraGo, FLEX, in Portland, OR, USA). SOC was analyzed by the K2Cr2O7 oxidation method. TN and TP were measured by the Kjeldahl method and colorimetric method after H2SO4−HClO4 digestion, respectively. The soil texture was measured with Malvern 2000 (Malvern Instruments Ltd., Malvern, UK), which was divided into clay, silt, and sand.

2.4. Extraction and Determination of GRSP in Soil

The analyses of the soil samples for GRSP were conducted by the citrate extraction-Komassar staining method as described by Wright and Upadhyaya [33].
The 0.5 g of soil was added with 4 mL of 20 mmol L−1 sodium citrate solution (pH 7.0), autoclaved at 121 °C for 60 min, and centrifuged at 10,000 rpm for 6 min; the suspension was then used to measure EE-GRSP. Meanwhile, the 0.5 g of soil was added with 4 mL of 50 mmol L−1 sodium citrate solution (pH 8.0), autoclaved at 121 °C for 60 min, and centrifuged at 10,000 rpm for 6 min; six repeated extractions of suspension were then used to measure T-GRSP.
The standard curve was constructed by using bovine serum albumin (BSA) as the standard material for GRSP content determination (mg·g−1). Briefly, 0.5 mL of the suspension was mixed with 5 mL of distilled water for dilution and 5 mL of Komassar brilliant blue G250 solution. After coloring for 5 min, the mixture was spectrophotometrically measured at 595 nm. The rest was immediately freeze-dried in a −80 °C refrigerator. Both EE-GRSP and T-GRSP were expressed as mg·g−1 dry soil.

2.5. Meteorological Data Extraction

The mean annual precipitation (MAP, mm), mean annual temperature (MAT, °C), and moisture index (MI) data for the study area were obtained from a data platform for the three poles (http://poles.tpdc.ac.cn) from 1 January 2000 to 31 December 2021. Moreover, annual actual evapotranspiration (AET, mm/a) and potential evapotranspiration (PET, mm/a) were extracted from the 1 km × 1 km resolution climate database provided by the Consultative Group for International Agricultural Research (http://www.cgiar-csi.org/). All meteorological data were averaged over the period from 1 January 2000 to 31 December 2021. More detailed information is shown in Table 1.

2.6. Data Calculation and Statistical Analysis

A value of 12% C was used to estimate the C in the GRSP of grasslands [3,34]. The calculation formula of GRSP-C contribution to SOC (EE-GRSP-C/SOC, T-GRSP-C/SOC, %) is as follows:
EE-GRSP-C/SOC = E E - G R S P × 12 % S O C × 100
TT-GRSP-C/SOC = T - G R S P × 12 % S O C × 100
where EE-GRSP (T-GRSP) stands for the content of EE-GRSP (T-GRSP) (mg·g−1), SOC is the soil organic carbon (mg·g−1), and 12% is the conversion factor for C in GRSP.
All data were analyzed by using Excel (Office, 2013) and SPSS 23.0 software, and the charts and Figures were generated by ArcGIS10.5, Origin 2021. The data were consistent with homogeneity of variance. A one-way ANOVA was conducted to compare GRSP variations across different grasslands and soil depths, followed by Duncan’s test for multiple comparisons at p < 0.05. Redundancy analysis (RDA) was employed using Canoco 5.0 to illustrate the ordination of various factors influencing GRSP characteristics across different soil layers. The effects of climatic conditions, and soil properties on the GRSP were further clarified by using a variance decomposition analysis (VPA) in the R package “vegan”.

3. Results

3.1. Content of GRSP among Different Grassland Types

The contents of the EE-GRSP and T-GRSP showed significant differences in both grassland types and soil depths (p < 0.05) (Figure 2). EE-GRSP and T-GRSP content gradually decreased from MM to TD (p < 0.05). The GRSP content varied from 0.06 mg·g−1 to 22.03 mg·g−1, with an average of 6.78 ± 6.10 mg·g−1. Specifically, the highest concentrations of EE-GRSP and T-GRSP were found in the MM (4.59 ± 0.89 and 18.18 ± 3.06 mg·g⁻¹, respectively), followed by AM, TMS, TS, TDS, and TD within the 0–10 cm soil depth. A similar distribution pattern of GRSP content was observed at the 10–20 cm soil depth among the different grassland types. In the 10–20 cm soil depth, the highest contents of EE-GRSP and T-GRSP were also distributed in the MM (3.77 ± 0.90 and 15.17 ± 2.64 mg·g−1). Furthermore, the EE-GRSP content in the 0–10 cm soil layer was higher than that in the 10–20 cm soil layer among all grassland types (p < 0.05). T-GRSP decreased with the soil depth increased in the AM, MM, TMS, and TS (p < 0.05), but there were no significant differences in the two soil layers in the TDS and TD (p > 0.05) (Figure 2).

3.2. Contribution of GRSP-C to SOC among Different Grassland Types

The GRSP-C contribution to the SOC pool and GRSP content distribution showed an opposite trend among different grassland types (Figure 3). In the 0–10 cm soil depth, the highest proportions of EE-GRSP-C/SOC and T-GRSP-C/SOC were found in the TDS (2.39 ± 0.43% and 6.77 ± 1.06%), followed by TS, TD, TMS, MM, and AM. In the 10–20 cm depth, the highest EE-GRSP-C/SOC ratio was similarly found in the TDS (2.67 ± 0.94%), and the relatively high value of T-GRSP-C/SOC was observed in the TDS (5.82 ± 2.04%) and TS (5.29 ± 2.52%). However, the T-GRSP-C/SOC ratio showed no significant differences in different soil depths (p > 0.05). The TS and TD had significantly higher EE-GRSP-C/SOC ratios in the 0–10 cm than those in the 10–20 cm soil layer (p < 0.05). Furthermore, Figure 3c–f demonstrated that the EE-GRSP-C/SOC and T-GRSP-C/SOC ratios decreased as SOC increased at both soil depths (p < 0.01), with no significant difference observed between the two depths.

3.3. Relationship between GRSP and Environmental Factors in the Different Soil Depths

We used GRSP contents as response variables and environmental factors as explanatory variables for RDA. According to the RDA results, the two axes explained 91.8% of the GRSP variation in the 0–10 cm soil depth and 89.38% in the 10–20 cm soil depth (Figure 4). In the 0–10 cm soil depth, the major variables affecting GRSP content were SOC, MAT, sand content, SWC, AGB, and silt content, with explanatory values of 80.4%, 3.3%, 2.1%, 1.6%, 1%, and 0.7%, respectively. The influencing factors, including SOC, silt content, SWC, and AGB were positively correlated with GRSP, whereas MAT and sand content were negatively correlated with GRSP (p < 0.05). At the 10–20 cm soil depth, the primary factors influencing GRSP content were SOC, SWC, EC, and pH, with explanatory values of 83.5%, 1.4%, 1.8%, and 0.8%, respectively. GRSP content showed a positive correlation with SOC and SWC, while it was negatively correlated with EC and pH (p < 0.05, details in Table 3).

3.4. Variation Partitioning of Influencing Factors in the Different Soil Depths

The VPA results showed that the combination of climate and soil properties could explain 89.7% (0–10 cm) and 87.1% (10–20 cm) of the variance in GRSP (Figure 5). Soil properties alone accounted for 12.8% of the total variance in the 0–10 cm soil depth, with climate explaining 1.5% and the interaction between climate and soil properties contributing to 75.4% of the variance. At the 10–20 cm soil depth, the interaction between climate and soil properties explained 72.1% of the GRSP variation, while soil properties alone accounted for 15%. Notably, there was a stronger interaction between climate and soil properties, exceeding 80%, across both soil layers.

4. Discussion

4.1. GRSP Distribution Characteristics and Its Contribution to SOC among Different Grassland Types

In our study, the average GRSP content across different grassland types ranged from 0.1 to 22.03 mg·g−1 in the 0–10 cm soil depth and from 0.06 to 19.14 mg·g−1 in the 10–20 cm soil depth (Figure 2). The GRSP values observed in our study were significantly higher than those reported in desert environments (2.51–12.01 mg·g−1) [22], agricultural lands (0.41–4.9 mg·g−1) [35], and meadow steppe (1.25–3.6 mg·g−1) [36]. Figure 2 showed a significant increasing trend in the content of EE-GRSP and T-GRSP from the TD to the MM (p < 0.05). A possible explanation for this is that the abundant vegetation in meadow grasslands can promote plant productivity, providing more available C to AMF for glomalin production [37,38,39]. Notably, some of the alpine grasslands are located in the national nature reserves of the study area [40]. These grasslands are characterized by high vegetation cover and low human disturbances. The abundant vegetation not only increases the carbon stock in the soil but also promotes microbial activity, which further enhances GRSP production. Furthermore, human activities (e.g., heavy grazing) often result in the loss of SOC, but the reduction in these activities can help to maintain or increase SOC stocks as soil structure and vegetation are maintained, thus allowing GRSP accumulation in nature reserves [40]. Additionally, we found that the BD values for desert grassland types were notably high (1.89 g cm−3), indicating smaller soil pores. Small soil pores with a weak water-holding capacity, can limit plant growth and microbial processes, reducing the accumulation of GRSP. Moreover, we found that GRSP accumulated more in the 0–10 cm soil layer than in the 10–20 cm soil layer, which was consistent with the results of previous studies [10,41]. This is because the higher inputs of dead leaves, root secretions, and microbial biomass can lead to more soil nutrients in the shallow soil layer, resulting in stronger AMF activity, the infestation rate, and the spore density of AMF.
GRSP is recognized as a stable form of microbial-derived C that contributes to the long-term accumulation of SOC [42,43]. In this study, the contributions of EE-GRSP-C and T-GRSP-C to SOC ranged from 0.27% to 4.77% and 0.59% to 9.61%, respectively (Figure 3). This suggests that T-GRSP-C contributes more significantly to SOC than EE-GRSP-C, likely due to the greater stability of T-GRSP compared to EE-GRSP. Moreover, these results (average 3.03%) are lower than previous studies suggesting the ratio of GRSP-C/SOC in the Songnen grassland and woodland (average 5.8% and 8.71%, respectively) [36]. This may be due to differences in soil properties and biomes under different land uses, leading to differences in the growth of AM fungi and in the secretion of glomalin. Interestingly, our analysis revealed that the contribution of GRSP-C to the SOC pool exhibited an opposite trend compared to GRSP content across different grassland types, which contrasts with the findings reported by Pei et al. [44]. Our results suggested that GRSP played an active role in the preservation of C in desert grasslands in the study area. This may be because of the difference in plant litter input among different grasslands [39,45]. For example, abundant vegetation resources, high growth rates, and more plant litter in high altitudes can be decomposed and converted to SOM, thus potentially reducing the relative contribution of GRSP-C to SOC [46,47]. Moreover, as altitude increases, temperature decreases, which can limit the growth rate and metabolic activities of mycorrhizal fungi. Consequently, this reduction in temperature leads to a decrease in mycorrhizal fungi biomass and the C source available for GRSP production. Furthermore, the GRSP-C/SOC ratio increases because of grazing activities in low-altitude areas, which has also been evidenced in several previous studies [44,48]. In addition, we observed that the contribution of GRSP-C to SOC was relatively high, despite the overall low SOC levels in the soil (Figure 3c–f). This finding suggests that GRSP plays a crucial role in C accumulation and sequestration, even under conditions where the C sink function is limited [24].

4.2. Effects of Variables on GRSP in the Different Soil Depths

The explanatory rate of each factor (MAT, MAP, SOC, pH, BD, EC, etc.) was further ranked by RDA to specifically reveal the factors influencing GRSP in different soil layers. SOC was the top important regulator for GRSP accumulation in the soil (>80%). As shown in the result, the EE-GRSP and T-GRSP concentrations were positively correlated with SOC in all soil depths (p < 0.05) (Table 3, Figure 4). A similar correlation between GRSP and SOC has been well shown in several studies [12,23]. Figure S1 revealed a negative correlation between BD and SOC content. This may be due to the fact that the soil pore space reduces with an increase in BD, which inhibits the mixing of organic matter, limiting the storage of SOC [49]. Moreover, the SOC content could be influenced by C sources secreted by plant roots, as these root-secreted substances can stimulate the growth and metabolism of soil microorganisms, leading to increased GRSP production. In addition, microorganisms may prefer other organic compounds to glomalin, so high SOC content inhibits glomalin decomposition [38]. This also further proves that GRSP is an important source of soil C pool, with similar biochemical characteristics among them and intricate interactive effects [5,50]. However, in addition to the SOC factor, we found that the regulating mechanism of GRSP accumulation differed from the 0–10 cm and 10–20 cm soil depths (Table 3). In the 0–10 cm soil depth, GRSP content decreased with high temperatures, which was similar to other findings [16,51]. This finding may be associated with higher temperatures, which stimulate microbial activity and, in turn, accelerate the mineralization of organic matter, leading to a decrease in GRSP content [16,52]. Moreover, GRSP positively correlated with silt content, and SWC (p < 0.05). Higher silt content can reduce microbial decomposition by stabilizing SOC and decreasing C leaching [53], thus leading to an accumulation of GRSP. Our findings indicate that SWC is an important parameter for GRSP production in natural grassland, and possible because high SWC may increase the permeability of the top soil layer, thus enhancing the growth and vitality of roots, and the activity of AMF [44]. In addition, we found that GRSP content was less distributed in desert grasslands, which are dominated by sandy soils due to the lack of precipitation and vegetation. The sandy soil with lower moisture content can cause rapid infiltration and loss of nutrients [44,54], potentially leading to a reduction in microbial activity, thereby decreasing GRSP accumulation. Furthermore, clay content had no significant influence on GRSP change, likely due to the low clay content in this study area.
However, in the 10–20 cm soil depth, SWC was the second regulating factor of GRSP content differently from MAT (0–10 cm), which was also positively correlated with GRSP (p < 0.05) (Table 3). Moreover, consistent with the results of Li et al. [19], this study revealed that pH has a great effect on GRSP in the deeper soil layer (10–20 cm). The pH is a very important abiotic determinant of AMF colonization and GRSP production [12,55]. Previous studies have shown that neutral and weakly acidic sediments favor the accumulation of GRSP [17,51]. This is because soil acidification induces an increase in iron (Fe) and aluminum (Al) oxides, which, in turn, decreases the rate of decomposition of GRSP, and they are more conducive to the accumulation of GRSP in the soil [16]. In addition, there is a negative correlation between EC and GRSP content in this study (p < 0.05), which is consistent with previous research [12]. Our results revealed that soils with higher organic matter content typically exhibit lower EC values in alpine grasslands (Table 2). This is because the soil cation exchange capacity increases with the increase in organic matter, which allows for the adsorption and immobilization of soil cations (e.g., K+, Na+, Ca2+, Mg2+, etc.) by the organic matter [56], consequently reducing the concentration of dissolved salt ions. Thus, the low soil salinity can promote plant growth and soil microbial activity [57,58], resulting in more GRSP content. Therefore, future assessments of GRSP accumulation mechanisms should incorporate multiple soil depths for a more precise evaluation. Additionally, our variance partitioning analysis (VPA) revealed that GRSP changes are predominantly influenced by the interaction between climatic conditions and soil properties across both soil depths (Figure 5). This indicates that it is challenging for a single factor, such as climate or soil properties alone, to fully explain the complexity of GRSP variations. Instead, the intricate combination of these factors plays a significant role in GRSP dynamics. For example, high precipitation can impact microbial activity and biochemical reaction rates by increasing soil water content.

5. Conclusions

GRSP was widely distributed across different grasslands, with higher accumulation observed in the 0–10 cm soil layer compared to the 10–20 cm soil layer (p < 0.05). The relatively higher EE-GRSP and T-GRSP contents were mainly distributed in the alpine grasslands without human disturbance. However, the GRSP-C contribution to the SOC pool showed an opposite trend compared with the GRSP contents distribution. The GRSP-C/SOC ratio accounted for 11.88% in desert grasslands, indicating that GRSP plays a significant role in SOC sequestration within these ecosystems. SOC was the primary factor influencing GRSP content in both soil depths. Besides the SOC factor, the factors for regulating GRSP accumulation in the two soil depths were not similar. The interactions between climate and soil properties accounted for more than 80% of the GRSP variations in both soil layers. Our study enhances the understanding of GRSP and GRSP-C/SOC dynamics across different grasslands. Future research focusing on the role of AMF would be valuable for further elucidating the underlying causes of GRSP variations.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/agronomy14081823/s1, Figure S1. Relationships between BD and SOC in different soil depths.

Author Contributions

Writing—original draft preparation, data analysis, methodology, software, M.Y.; data curation, investigation, resources, validation, L.F.; investigation, methodology, resources, validation, X.M.; investigation, formal analysis, Y.L. (Yuanye Liang); writing—review and editing, J.M. and J.L.; supervision, project administration, funding acquisition, Y.L. (Yaoming Li). All authors have read and agreed to the published version of the manuscript.

Funding

This work was funded by the Third Xinjiang Scientific Expedition Program (2021xjkk0603), National Natural Science Foundation of China (42077327), and Natural Science Foundation for Distinguished Young Scholars of Xinjiang Uygur Autonomous Region, China (Grant No.2022D01E97).

Data Availability Statement

The original contributions presented in the study are included in the article/Supplementary Material, further inquiries can be directed to the corresponding author.

Conflicts of Interest

The authors declare no conflict of interest.

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Figure 1. Location of the study area and soil sampling sites. The red part is the Irtysh River Basin (a); the black dots represent soil sampling sites in (b). AM: Alpine meadow, MM: Mountain meadow, TMS: Temperate meadow steppe, TS: Temperate steppe, TDS: Temperate desert steppe, TD: Temperate desert.
Figure 1. Location of the study area and soil sampling sites. The red part is the Irtysh River Basin (a); the black dots represent soil sampling sites in (b). AM: Alpine meadow, MM: Mountain meadow, TMS: Temperate meadow steppe, TS: Temperate steppe, TDS: Temperate desert steppe, TD: Temperate desert.
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Figure 2. The EE-GRSP (a) and T-GRSP (b) content in the different soil depths among different grassland types. Different uppercase letters indicate significant differences among different soil depths (p < 0.05), and different lowercase letters indicate significant differences among six grassland types (p < 0.05). Error bars are standard errors (SE). AM: Alpine meadow, MM: Mountain meadow, TMS: Temperate meadow steppe, TS: Temperate steppe, TDS: Temperate desert steppe, TD: Temperate desert.
Figure 2. The EE-GRSP (a) and T-GRSP (b) content in the different soil depths among different grassland types. Different uppercase letters indicate significant differences among different soil depths (p < 0.05), and different lowercase letters indicate significant differences among six grassland types (p < 0.05). Error bars are standard errors (SE). AM: Alpine meadow, MM: Mountain meadow, TMS: Temperate meadow steppe, TS: Temperate steppe, TDS: Temperate desert steppe, TD: Temperate desert.
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Figure 3. The contribution of EE-GRSP-C to SOC (EE-GRSP-C/SOC, (a)) and the contribution of T-GRSP-C to SOC (T-GRSP-C/SOC, (b)) in the different soil depths among different grassland types. Different uppercase letters indicate significant differences in different soil depths (p < 0.05), and different lowercase letters indicate significant differences among six grassland types (p < 0.05). Error bars are standard errors (SE). Relationships between SOC and GRSP-C/SOC (c–f) in different soil depths. The red dots and black lines represent the linear relationship between EE-GRSP-C/SOC (c) and T-GRSP-C/SOC (d) and SOC in the 0–10 cm soil layer; the blue dots and red lines represent the linear relationship between EE-GRSP-C/SOC (e) and T-GRSP-C/SOC (f) and SOC in the 10–20 cm soil layer. AM: Alpine meadow, MM: Mountain meadow, TMS: Temperate meadow steppe, TS: Temperate steppe, TDS: Temperate desert steppe, TD: Temperate desert.
Figure 3. The contribution of EE-GRSP-C to SOC (EE-GRSP-C/SOC, (a)) and the contribution of T-GRSP-C to SOC (T-GRSP-C/SOC, (b)) in the different soil depths among different grassland types. Different uppercase letters indicate significant differences in different soil depths (p < 0.05), and different lowercase letters indicate significant differences among six grassland types (p < 0.05). Error bars are standard errors (SE). Relationships between SOC and GRSP-C/SOC (c–f) in different soil depths. The red dots and black lines represent the linear relationship between EE-GRSP-C/SOC (c) and T-GRSP-C/SOC (d) and SOC in the 0–10 cm soil layer; the blue dots and red lines represent the linear relationship between EE-GRSP-C/SOC (e) and T-GRSP-C/SOC (f) and SOC in the 10–20 cm soil layer. AM: Alpine meadow, MM: Mountain meadow, TMS: Temperate meadow steppe, TS: Temperate steppe, TDS: Temperate desert steppe, TD: Temperate desert.
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Figure 4. RDA for the relationship between variables and GRSP content in the different soil depths. The red lines represent different environmental indexes, the blue lines represent GRSP content, and the black line is a proxy. MAP: annual mean precipitation, MAT: annual mean air temperature, MI: moisture index, AET: annual actual evapotranspiration, PET: potential evapotranspiration, SOC: soil organic carbon, TN: total soil nitrogen, TP: soil total phosphorus concentration, EC: electrical conductivity, BD: bulk density, SWC: soil water content, Cov: vegetation coverage, AGB: aboveground biomass.
Figure 4. RDA for the relationship between variables and GRSP content in the different soil depths. The red lines represent different environmental indexes, the blue lines represent GRSP content, and the black line is a proxy. MAP: annual mean precipitation, MAT: annual mean air temperature, MI: moisture index, AET: annual actual evapotranspiration, PET: potential evapotranspiration, SOC: soil organic carbon, TN: total soil nitrogen, TP: soil total phosphorus concentration, EC: electrical conductivity, BD: bulk density, SWC: soil water content, Cov: vegetation coverage, AGB: aboveground biomass.
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Figure 5. The results of variation partitioning analyses (VPA) illustrating the climate and soil properties to GRSP change in the 0–10 cm soil depth (a) and 10–20 cm soil depth (b), respectively. Climate: MAP, annual mean precipitation + MAT, annual mean air temperature + MI, moisture index + AET, annual actual evapotranspiration + PET, potential evapotranspiration. Soil properties: pH + SOC, soil organic carbon + TN, total soil nitrogen + TP, soil total phosphorus concentration + EC, electrical conductivity + BD, bulk density + SWC, soil water content.
Figure 5. The results of variation partitioning analyses (VPA) illustrating the climate and soil properties to GRSP change in the 0–10 cm soil depth (a) and 10–20 cm soil depth (b), respectively. Climate: MAP, annual mean precipitation + MAT, annual mean air temperature + MI, moisture index + AET, annual actual evapotranspiration + PET, potential evapotranspiration. Soil properties: pH + SOC, soil organic carbon + TN, total soil nitrogen + TP, soil total phosphorus concentration + EC, electrical conductivity + BD, bulk density + SWC, soil water content.
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Table 1. Soil sampling sites background information.
Table 1. Soil sampling sites background information.
SiteLongitude (°)Latitude (°)Altitude (m)MAP (mm)MAT (℃)AET (mm/a)PET (mm/a)MIAGB (g m−2)Cov (%)
190.4846.972457.00432.75−6.22176.69743.20−41.7749.6485.07
288.3548.032107.97439.84−5.23281.441903.87−76.9055.2993.67
387.5548.622358.11536.44−9.83214.52873.41−38.5837.0886.00
488.3747.972406.00454.13−5.70319.49832.14−43.8150.0597.67
585.6347.172484.00467.56−5.07315.201166.49−61.4283.1588.00
686.0847.022403.00449.98−5.19192.51531.79−21.4838.0480.00
790.3147.192232.00417.56−3.09184.70531.79−27.3442.2589.33
890.2647.172136.00386.40−6.43152.67767.45−43.5616.0783.67
990.8546.832619.00433.14−6.74146.38767.45−42.9227.1986.67
1090.8846.762655.00438.03−2.92186.04683.06−74.2724.1749.00
1190.3247.091902.00175.76−2.92186.04−683.06−74.27104.4192.17
1290.4746.922049.00191.10−3.08176.69−1013.21−81.14106.1096.20
1389.4247.552050.00182.10−3.06195.25−2220.98−91.8056.8791.33
1489.5847.311790.00175.33−0.64173.02−1103.62−84.1141.7579.00
1588.6447.771094.00177.712.80215.59−2114.79−91.6025.9135.00
1688.5847.731546.00184.481.71220.45−1223.42−84.9232.7376.33
1787.1348.341579.68319.95−0.19234.60−1023.76−68.75279.49102.33
1888.2948.011784.00237.57−2.42286.88−1903.87−87.52215.5472.00
1987.6348.121517.00251.901.27238.43−977.06−74.22119.5978.00
2086.1247.121889.70394.430.69265.34−2052.23−80.7879.8293.00
2186.9348.741635.00342.76−1.12235.47−728.23−52.93245.7497.33
2287.1248.561186.20313.480.53234.09−1667.02−81.20395.6795.33
2387.4848.561287.31253.24−0.90225.50−571.42−55.68279.2994.33
2486.7048.501099.56323.951.86254.48−801.10−59.56311.3890.00
2587.0648.422104.84351.62−2.80237.57−1030.33−65.8718.2292.00
2685.9246.931593.00347.762.39276.68−986.72−64.7628.4957.00
2784.8446.802199.00415.05−1.45282.82−1396.61−70.2842.8587.67
2884.8746.761920.00407.48−0.11218.68−1032.71−60.5426.4875.67
2990.2346.961609.00301.342.68152.82875.34−65.5766.0089.73
3089.9347.211297.00277.154.36163.83879.06−68.4713.9635.67
3189.8947.221219.00252.796.00165.73879.06−71.2416.7256.33
3287.0248.201144.24298.385.28226.751179.57−74.7021.2940.00
3388.1447.931007.00265.646.28275.491514.54−82.4621.4520.67
3485.9147.211662.59345.292.01264.95852.59−59.5082.5070.67
3586.1347.181780.77332.162.62265.34976.30−65.9866.2086.33
3687.3148.441062.45319.714.21235.66797.58−59.92248.9570.33
3790.3246.851396.00267.874.91148.70922.41−70.9687.3854.33
3890.6046.681456.00283.463.82128.86936.11−69.7261.6865.00
3990.0246.821600.00299.663.09144.121261.34−76.2423.3188.83
4090.7746.581429.00247.696.17123.93976.26−74.6367.8636.33
4189.8147.181211.00249.656.29159.32874.18−71.4433.9153.00
4289.1047.401092.00249.086.69180.291201.82−79.2717.1343.37
4389.2447.321358.00276.884.79180.771200.04−76.9222.4838.03
4489.7446.981401.00274.104.86160.311104.02−75.1726.7447.37
4588.8447.57915.00225.408.38188.921114.67−79.779.0533.67
4688.2347.69663.00197.1110.55217.681201.98−83.6061.9335.00
4787.5748.071293.00314.043.57225.50977.06−67.8524.1841.67
4886.1047.231383.00300.694.74248.83976.30−69.2020.3248.33
4986.7348.461112.00322.644.64242.55801.10−59.7218.4341.67
5086.2846.941513.00304.984.40244.071142.89−73.3140.5570.17
5187.7547.81759.00219.929.34231.681001.49−78.0456.4343.00
5285.7646.801287.00274.647.07150.781160.03−76.320.000.00
5387.0847.04621.00165.8213.09219.811391.10−88.070.000.00
5490.0246.531190.00232.897.92137.391343.76−82.6638.9927.13
5587.2447.88749.90226.919.24220.291401.28−83.8036.5647.33
5686.2447.301099.10251.947.84215.101170.41−78.4735.4840.33
5785.9646.43772.00191.8613.02130.771358.19−85.8735.6831.70
5885.9246.32605.00173.0414.59130.731510.92−88.5435.6831.70
5988.3347.65733.00200.5610.26214.191165.65−82.7976.1048.83
6089.5046.79873.00198.7810.24178.371334.63−85.1076.7847.40
6190.0945.161190.00226.6811.91154.771487.82−84.7635.6831.70
6286.2747.84463.20182.2713.00196.521417.92−87.1435.6831.70
6385.8947.56784.10219.9510.58202.071468.21−85.0170.8748.67
6489.5646.27877.00159.1319.77179.001711.60−90.7025.7936.67
6589.5245.66945.00207.5112.51139.111482.02−85.9950.3928.67
6689.4945.39328.00220.9812.55147.581557.53−85.810.000.00
6789.3245.13989.00227.3013.35137.141830.05−87.570.000.00
6886.8445.41362.00161.7418.62251.631770.76−90.8616.5430.67
6988.5245.01602.00196.9417.04179.461589.04−87.6033.4947.67
Notes: MAP: annual mean precipitation, MAT: annual mean temperature, AET: annual actual evapotranspiration, PET: potential evapotranspiration, MI: moisture index, AGB: aboveground biomass, Cov: vegetation coverage.
Table 2. Soil properties of the six grassland types.
Table 2. Soil properties of the six grassland types.
Grassland
Type		Soil Depth (cm)pHBD (g cm−3)EC (μS cm−1)SOC (g kg−1)TN (g kg−1)TP (g kg−1)
AM0–105.02 ± 0.431.01 ± 0.1459.37 ± 14.9172.40 ± 19.356.96 ± 1.321.66 ± 0.33
10–205.09 ± 0.421.08 ± 0.1354.54 ± 53.0352.36 ± 13.705.94 ± 1.481.52 ± 0.26
MM0–106.29 ± 0.711.06 ± 0.2490.28 ± 61.5167.65 ± 18.896.98 ± 1.801.24 ± 0.37
10–206.26 ± 0.701.16 ± 0.2176.26 ± 43.9456.35 ± 13.926.21 ± 1.541.20 ± 0.38
TMS0–107.00 ± 0.201.22 ± 0.2580.18 ± 43.3643.58 ± 20.223.94 ± 1.270.81 ± 0.12
10–207.10 ± 0.281.23 ± 0.1873.19 ± 42.3034.54 ± 15.103.81 ± 1.390.71 ± 0.10
TS0–106.92 ± 0.261.39 ± 0.2873.18 ± 75.5620.13 ± 9.272.98 ± 1.260.81 ± 0.34
10–207.32 ± 0.371.35 ± 0.2462.65 ± 42.5517.54 ± 8.942.67 ± 0.950.74 ± 0.25
TDS0–108.25 ± 0.851.64 ± 0.0767.48 ± 23.7610.37 ± 3.461.30 ± 0.341.20 ± 0.75
10–208.45 ± 0.741.56 ± 0.0884.95 ± 58.406.69 ± 3.981.28 ± 0.460.91 ± 0.75
TD0–108.81 ± 0.731.59 ± 0.12128.38 ± 112.144.30 ± 1.980.70 ± 0.500.54 ± 0.24
10–208.79 ± 0.721.53 ± 0.15129.23 ± 98.885.10 ± 4.040.78 ± 0.600.51 ± 0.25
Note: AM: Alpine meadow, MM: Mountain meadow, TMS: Temperate meadow steppe, TS: Temperate steppe, TDS: Temperate desert steppe, TD: Temperate desert. BD: bulk density, EC: electrical conductivity, SOC: soil organic carbon, TN: total soil nitrogen, TP: soil total phosphorus concentration. All values represent mean ± standard deviation.
Table 3. The relative contributions of various explanatory variables to GRSP variation and differences between 0–10 cm and 10–20 cm soil depths.
Table 3. The relative contributions of various explanatory variables to GRSP variation and differences between 0–10 cm and 10–20 cm soil depths.
Soil Depth (cm)VariablesExplanatory Rate (%) %Contribution Rate (%) Tion %Pseudo-F Fp
0–10SOC80.487.62750.002
MAT3.33.613.50.002
Sand2.12.313.30.002
SWC1.61.76.80.014
AGB11.15.20.026
Silt0.70.83.80.050
AET0.60.74.20.056
PET0.20.21.50.208
MI0.40.42.50.108
Cov0.10.10.70.432
TP<0.1<0.10.60.456
MAP<0.1<0.10.30.600
pH<0.1<0.1<0.10.852
TN<0.1<0.1<0.10.862
EC<0.1<0.1<0.10.912
BD<0.10.11.30.254
10–20SOC83.593.13390.002
MAT0.30.31.60.180
Sand0.10.20.80.357
SWC1.41.66.90.006
AGB<0.1<0.10.20.728
Silt0.50.62.70.126
AET0.20.20.90.348
PET<0.1<0.10.20.750
MI<0.1<0.10.20.740
Cov<0.1<0.10.20.714
TP0.30.41.70.192
MAP<0.1<0.1<0.10.922
pH0.80.94.30.038
TN0.10.20.80.368
EC1.827.90.010
BD0.10.10.50.500
Note: MAP: annual mean precipitation, MAT: annual mean air temperature, MI: moisture index, AET: annual actual evapotranspiration, PET: potential evapotranspiration, SOC: soil organic carbon, TN: total soil nitrogen, TP: soil total phosphorus concentration, EC: electrical conductivity, BD: bulk density, SWC: soil water content, Cov: vegetation coverage, AGB: aboveground biomass.
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Yang, M.; Fan, L.; Ma, X.; Liang, Y.; Mao, J.; Li, J.; Li, Y. Glomalin-Related Soil Protein Plays Different Roles in Soil Organic Carbon Pool Maintaining among Different Grassland Types. Agronomy 2024, 14, 1823. https://doi.org/10.3390/agronomy14081823

AMA Style

Yang M, Fan L, Ma X, Liang Y, Mao J, Li J, Li Y. Glomalin-Related Soil Protein Plays Different Roles in Soil Organic Carbon Pool Maintaining among Different Grassland Types. Agronomy. 2024; 14(8):1823. https://doi.org/10.3390/agronomy14081823

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Yang, Meiniu, Lianlian Fan, Xuexi Ma, Yuanye Liang, Jiefei Mao, Jiangyue Li, and Yaoming Li. 2024. "Glomalin-Related Soil Protein Plays Different Roles in Soil Organic Carbon Pool Maintaining among Different Grassland Types" Agronomy 14, no. 8: 1823. https://doi.org/10.3390/agronomy14081823

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