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Article

Soil Carbohydrates and Glomalin-Related Soil Proteins Affect Aggregate Characteristics in Chinese Fir Plantations with Different Stand Types

by
Zhiyao Wang
1,
Lei Du
2,
Xianyu Yao
1,
Yili Guo
3,
Shaoming Ye
1 and
Shengqiang Wang
1,*
1
Guangxi Key Laboratory of Forest Ecology and Conservation, College of Forestry, Guangxi University, Nanning 530004, China
2
The Faculty of Geography Resource Sciences, Sichuan Normal University, Chengdu 610066, China
3
Guangxi Key Laboratory of Plant Conservation and Restoration Ecology in Karst Terrain, Guangxi Institute of Botany, Guangxi Zhuang Autonomous Region and Chinese Academy of Sciences, Guilin 541006, China
*
Author to whom correspondence should be addressed.
Forests 2025, 16(3), 444; https://doi.org/10.3390/f16030444
Submission received: 21 January 2025 / Revised: 20 February 2025 / Accepted: 27 February 2025 / Published: 28 February 2025
(This article belongs to the Special Issue Forest Plant, Soil, Microorganisms and Their Interactions—2nd Edition)
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Abstract

:
Soil carbohydrates and glomalin-related soil proteins (GRSPs), as important components of soil organic matter, are the essential basis for maintaining soil aggregate stability. They interact with each other and influence each other. Exploring the relationships and mechanisms of action between these two components and soil aggregates is of great significance for improving soil quality and promoting the sustainable development of forest stands. This study focused on investigating soil aggregate composition (including >2, 2–1, 1–0.25, and <0.25 mm fractions) and stability (as indicated by the mean weight diameter (MWD) and geometric mean diameter (GMD)) as well as aggregate-associated carbohydrates and GRSP components in Chinese fir plantations with different stand types, including Chinese fir × Michelia macclurei (stand I), Chinese fir × Mytilaria laosensis (stand II), and pure Chinese fir (stand III). The results indicated that in the 0–20 cm and 20–40 cm soil layer, the MWD and GMD of the two mixed Chinese fir stands were significantly (p < 0.05) higher than that of the pure Chinese fir stand. The contents of carbohydrates and GRSP in the soil also showed similar trends. This suggests that mixed Chinese fir stands (especially the Chinese fir × Michelia macclurei) enhance soil aggregate stability as well as the contents of carbohydrates and GRSP in the soil. The results also revealed that although both carbohydrates and GRSP significantly contribute to the formation and stability of large soil aggregates, PLS-PM analysis showed that in the 0–20 cm and 20–40 cm soil layer, the path coefficient of GRSP to aggregate stability was 0.840 and 0.576, while that of carbohydrates was 0.134 and 0.398. Therefore, compared with carbohydrates, GRSP (especially the easily extractable fraction of GRSP) has a more pronounced effect on soil aggregate stability. This finding provides a scientific basis and practical guidance for enhancing the productivity of Chinese fir plantations.

1. Introduction

Plantation stands are the most widely distributed stand type globally, playing an irreplaceable role in promoting economic development and regulating climate [1]. However, the decline in soil quality and the difficulty in maintaining soil functions and long-term productivity during the management of plantation stands remain a worldwide challenge [2]. According to the Ninth National Stand Resources Inventory Report, China’s plantation stand area stands at 79.54 million ha, ranking first in the world in terms of planting area [3]. Among various plantation tree species, Chinese fir, the third most common plantation tree species globally, is a unique fast-growing timber species in southern China [4]. Chinese fir has the characteristics of rapid growth, strong stress resistance, and a wide range of suitable habitats [5]. Its high-quality timber has extensive applications and significant economic value, making it a popular choice for commercial timber stands in southern China [6]. Nevertheless, the development of Chinese fir plantations has been hindered by long-term practices such as pure stands, short rotation periods, and clear-cutting, leading to a decline in stand productivity and severely restricting the sustainable development of Chinese fir plantations [7]. As of 2019, Guangxi, which ranks first in Chinese fir planting area in China, has a stand stock volume of only 64 m3 ha−1, significantly lower than the national average (95 m3 ha−1) and the international average (131 m3 ha−1) [3]. Therefore, addressing this issue has become an urgent priority. Our previous research found that introducing broad-leaved tree species (e.g., Michelia macclurei and Mytilaria laosensis) into Chinese fir plantations can effectively improve soil structure and promote the accumulation of soil organic carbon and nutrients, thereby enhancing stand productivity [8,9]. However, the underlying mechanisms driving these soil structural changes remain unclear.
Soil aggregates, the basic units of soil structure, refer to the sum of soil particles with varying sizes, shapes, pore sizes, mechanical stability, and water stability [10]. Based on the aggregate size, soil aggregates can be classified into microaggregates (<0.25 mm) and macroaggregates (>0.25 mm) [11]. The formation mechanisms of these two types of aggregates differ. Specifically, microaggregates are primarily formed by mineral particles under the action of persistent binders, which typically include multivalent metal ion complexes and some humus substances in the soil [12]. In contrast, macroaggregates are formed from microaggregates under the influence of temporary binders, such as high-molecular-weight viscous substances in the soil, including polysaccharides, plant root exudates, or fungal hyphae [13].
Carbohydrates, as an essential component of soil organic matters (accounting for 5% to 25% of total organic carbon), are relatively easily degradable [14]. They cannot only indicate changes in soil organic matters and soil microorganisms but also stabilize soil structure and maintain a stable soil environment [15]. Furthermore, carbohydrates enhance soil erosion resistance by binding soil microaggregates to form macroaggregates [16]. In general, concentrated acid, dilute acid, and hot water are used to extract carbohydrates from soil to determine their component contents [17]. The compounds extracted by concentrated acid are considered total carbohydrates (TCs) in the soil; dilute-acid-extractable carbohydrates (DAECs) represent soluble carbohydrates and carbohydrates derived from plant hemicellulose, while hot-water-extractable carbohydrates (HWECs) are considered microbial-derived carbohydrates [18].
Glomalin-related soil protein (GRSP) is a crucial protein present in soil, mainly originating from arbuscular mycorrhizal fungi (AMF) [19]. Synthesized by fungi and released into the soil during mycorrhizal symbiosis, GRSP forms complex, resilient, hydrophobic, and viscous glycoproteins [20]. GRSP, a high-molecular-weight organic compound composed of proteins and lipids, primarily functions to bind fungal and plant root cell walls and binds soil mineral particles in the mycorrhizal symbiosis and soil microenvironment [21]. Most studies have shown that GRSP is relatively stable and highly resistant to microbial decomposition, contributing to soil aggregate stability [22,23]. Additionally, its metal ion content enables it to fix aggregates to hyphal surfaces through bridging, further generating stable soil structures [24,25]. Based on their availability and turnover time in soil, total GRSP (T-GRSP) can be classified into difficult-to-extract GRSP (DE-GRSP) and easily extractable GRSP (EE-GRSP) [26]. DE-GRSP represents relatively stable GRSP produced over a longer period, reflecting its accumulation level in soil. In contrast, EE-GRSP comprises newly formed or nearly decomposed portions, exhibiting strong ecological functions in enhancing soil aggregate stability.
Although existing research has preliminarily elucidated the roles of carbohydrates and GRSP in the formation of soil aggregates, most studies are still confined to the whole soil level, failing to unravel the influence of carbohydrates and GRSP on aggregates at the micro-scale of soil (from the perspective of aggregates). In view of this, based on previous research, this study takes Chinese fir × Michelia macclurei, Chinese fir × Mytilaria laosensis, and pure Chinese fir as research objects, aiming to explore different stand types in terms of (a) aggregate composition and stability characteristics; (b) distribution characteristics of carbohydrates and GRSP within aggregates; and (c) effects of carbohydrates and GRSP on aggregate composition and stability. The goal is to reveal the formation and development mechanisms of soil structure in Chinese fir plantations, thereby providing a scientific basis for enhancing the productivity of Chinese fir plantations.

2. Materials and Methods

2.1. Study Area

The experimental area was established at the Subtropical Forestry Experimental Center, Chinese Academy of Forestry. It is influenced by the south subtropical monsoon, abundant in water and heat resources, with an annual average precipitation of 1200–1500 mm and an annual average temperature of 20.5–21.7 °C. The region is dominated by low hills and mountains, with a slope of mostly 20–30°. The parent rock is mainly granite, and the soil type is mainly Ferralsols. At present, the main afforestation tree species include Chinese fir, Michelia macclurei, and Mytilaria laosensis.

2.2. Experimental Design

To reduce the influence of factors other than stand types, this study selected Chinese fir × Michelia macclurei (I stand), Chinese fir × Mytilaria laosensis (II stand), and pure stands of Chinese fir (III stand) with similar site conditions and geographical features (Figure 1). All stand types were planted in 1992 with a row spacing of 2 m × 3 m, a slope of 20–30°, and an altitude of 725–730 m (Table 1).
In the mixed stands (stand I and stand II), the ratio of main tree species to associate tree species is 3:1. In the first three years, all stand types underwent weeding and cultivation, and then were managed in a near-natural manner without artificial intervention or fertilization. Moreover, 3 standard plots (namely, 3 replicates) of 20 m × 20 m were randomly established for each stand type, totaling 9 standard plots (namely, 3 stand types × 3 replicates = 9 standard plots) (Figure 1). The distance between adjacent standard plots was more than 800 m to reduce spatial auto-correlation and prevent pseudo-replication.

2.3. Litter and Soil Sampling

In each standard plot, 9 sampling points were set up using a grid method, and litter samples were collected using a mesh bag from each sampling point. These samples were then mixed thoroughly, ultimately yielding 3 (stand types) × 3 (replicates) = 9 mixed litter samples. Subsequently, soil samples were collected using a spade from the 0–20 cm and 20–40 cm soil layers, which were then mixed and homogenized to obtain 18 mixed soil samples (3 stand types × 2 soil layers × 3 replicates). Additionally, soil samples were collected using a 100 cm3 cutting ring to test bulk density (Table 2).
Each mixed litter sample was dried to a constant weight in a 70 °C oven and then weighed. Each mixed soil sample was gently broken along its natural structure, passed through a 5 mm sieve to remove small stones, plant and animal residues, and then air-dried indoors. A portion of the soil samples was crushed into fine particles using a grinder to determine the basic physicochemical properties (Table 2), and another portion of the soil samples was separated into >2, 2–1, 1–0.25, and <0.25 mm aggregates using the wet sieving method [10], and the contents of soil carbohydrates and GRSP in each aggregate were measured.

2.4. Indicator Measurements

Soil bulk density was measured using the cutting ring method [27]. Specifically, a soil corer with an inner diameter of 100 mm and a height of 100 mm was used. The soil sample was placed into the corer, compacted, and then weighed to determine the total mass of the soil and corer. After subtracting the mass of the corer, the soil was dried in an oven (DHG-9030A, Shanghai Jinghong, China) to calculate the bulk density.
Soil texture was determined using the pipette method, dividing the soil into sand (2–0.02 mm), silt (0.02–0.002 mm), and clay (<0.002 mm) fractions [27]. The soil sample was dispersed in water, and different particle sizes were separated using the pipette method. The mass of each fraction was measured to determine the texture.
Soil pH was measured using the potentiometric method [27]. Soil samples were mixed with deionized water at a soil-to-water ratio of 1:2.5 (by mass), stirred thoroughly, and then allowed to stand for 30 min. The pH of the supernatant was measured using a pH meter (PHS-3F, Leici, China).
Soil organic carbon was determined using the high-temperature external heating potassium dichromate oxidation method [28]. Briefly, 0.5 g of air-dried soil was weighed into a 250 mL Erlenmeyer flask, and 10 mL of 0.8 mol/L potassium dichromate solution and 20 mL of concentrated sulfuric acid (H2SO4) were added. The mixture was heated in a water bath at 60 °C for 30 min. After cooling, 100 mL of deionized water was added, followed by 10 mL of 0.2 mol/L ferrous sulfate solution. The solution was titrated with 0.5 mol/L ferrous sulfate solution until the color changed from yellow to blue–green. The soil organic carbon content was calculated based on the volume of ferrous sulfate solution consumed.
Soil total nitrogen was measured using the micro-Kjeldahl method [29]. Specifically, 0.5 g of air-dried soil sample was weighed and placed into a digestion tube. An amount of 10 mL of concentrated sulfuric acid and a small amount of catalyst (copper sulfate and potassium sulfate) were added. The mixture was digested on an electric stove until the solution turned transparent blue. After cooling to room temperature, the digestion solution was transferred to a 250 mL volumetric flask and diluted to the mark. An appropriate amount of the digestion solution was distilled using a Kjeldahl Apparatus (Pro-Nitro A, Selecta, Germany), and the ammonia gas was absorbed by a 0.1 mol/L boric acid solution. The total nitrogen content was determined by titration with a 0.1 mol/L hydrochloric acid standard solution.
Carbohydrate components were classified as total carbohydrates (TCs), dilute-acid-extractable carbohydrates (DAECs) and hot-water-extractable carbohydrates (HWECs). Different carbohydrate components were extracted and measured using the anthrone–sulfuric acid colorimetric method with varying extractants and concentrations [30]. Specifically, TC was extracted with 12 mol L−1 H2SO4, DAEC with 0.5 mol L−1 H2SO4, and HWEC with distilled water at 80 °C. First, 3.0 mL of anthrone–sulfuric acid solution was added to the microplate wells, followed by 1.0 mL of the extracted sample solution (such as total carbohydrates (TCs), dilute-acid-extractable carbohydrates (DAECs), or hot-water-extractable carbohydrates (HWECs)). An additional 1.0 mL of distilled water was then added to bring the total volume to 5.0 mL. The microplate was placed in a water bath at 93 °C for 15 min to allow the reaction to proceed. After cooling to room temperature, the absorbance of the sample solution was measured at 620 nm using a microplate reader (Synergy H1, BioTek, USA).
GRSP components were classified as difficult-to-extract GRSP (DE-GRSP), easily extractable GRSP (EE-GRSP) and difficult-to-extract GRSP (DE-GRSP). The contents of T-GRSP and EE-GRSP were determined using the Bradford method with 50 mol L−1 and 20 mol L−1 sodium citrate solutions (pH 8.0 and 7.0, respectively) [20]. The centrifuge tubes containing the reagents were placed in an autoclave with the caps open. The extraction conditions were set at 121 °C for 30 min for EE-GRSP and 121 °C for 60 min for T-GRSP. After extraction, the samples were removed, cooled to room temperature, and then centrifuged at 9500 r/min for 10 min to collect the supernatant. An appropriate amount of Bradford reagent was added to the microplate wells, followed by the addition of the sample solution or standard protein solution, and the mixture was thoroughly mixed. The microplate was left at room temperature for 5–10 min to allow full color development. The absorbance of the sample solution was measured at 595 nm using a microplate reader (Synergy H1, BioTek, USA). DE-GRSP was calculated by subtracting the EE-GRSP content from the T-GRSP content [21].

2.5. Data Processing

The mean weight diameter (MWD) and geometric mean diameter (GMD) are commonly utilized to characterize the stability of soil aggregates. Specifically, larger MWD and GMD values indicate higher degree of soil aggregation and more stable soil structure. MWD and GMD of soil aggregates were calculated using the following formulas [10]:
MWD = ∑ i = 1 4 X i W i ,
GMD = exp ∑ i = 1 4 W i lnX i ∑ i = 1 4 W i ,
where Xi is the average diameter (mm) of the ith aggregates, and Wi is the proportion (% in weight) of the ith aggregates in bulk soil.
Experimental data were statistically analyzed using Excel (version 2019) and R software (version 4.3.2). The data are the mean ± standard deviation of multiple replicated experimental data (n = 3). Specifically, one-way analysis of variance (ANOVA) was used to analyze litter and bulk soil indicators, while two-way ANOVA was applied to analyze aggregate-related indicators. Redundancy analysis (RDA) was used to screen out the key components of soil carbohydrates and GRSP that play crucial roles in soil aggregate composition and stability. Partial least squares path modeling (PLS-PM) was adopted to analyze the direct and indirect effects of soil carbohydrates and GRSP on soil aggregate composition and stability. The credibility of the PLS-PM model is supported by the following criteria: (i) composite reliability >0.6 and loading of observed variables >0.8; (ii) average variance extracted ≥0.5 as an indicator of convergent validity; (iii) diagonal loadings in the cross-loadings matrix being greater than the other values in the same row. Moreover, due to the insignificant contribution of T-GRSP, it was excluded from the RDA and PLS-PM.

3. Results

3.1. Soil Aggregate Characteristics

In the 0–20 cm depth, the proportion of >2 mm aggregates ranged from 25% to 37% across the different stands, with higher proportions in mixed stands than pure stands, showing a trend of I > II > III (Table 3). Conversely, the proportion of <0.25 mm aggregates ranged from 15% to 27% across the different stands, with higher proportions in pure stands than mixed stands, showing a trend of III > II > I. Within different soil layers of the same stand, the proportions of >2 mm and 2–1 mm aggregates were greater in the 0–20 cm depth than the 20–40 cm depth. Conversely, for 1–0.25 mm and <0.25 mm aggregates, the proportions were greater in the 20–40 cm depth than the 0–20 cm depth.
In the 0–20 cm depth, the variation ranges of MWD and GMD were 1.39–1.80 mm and 0.74–1.12 mm across the different stands, respectively (Table 3). Both MWD and GMD were significantly higher in mixed stands than pure stands, showing a trend of I > II > III. Within different soil layers of the same stand, both MWD and GMD were greater in the 0–20 cm depth than the 20–40 cm depth.

3.2. Soil Aggregate-Associated Carbohydrates

Regardless of the depth and stand, soil carbohydrate (including TC, DAEC, and HWEC) contents increased with the decrease in aggregate size (Figure 2). Specifically, the average contents of TC, DAEC, and HWEC in <0.25 mm aggregates were 3.75 g kg−1, 2.40 g kg−1, and 1.30 g kg−1, respectively; meanwhile, the average contents of TC, DAEC, and HWEC in >2 mm aggregates were 2.99 g kg−1, 2.00 g kg−1, and 1.05 g kg−1, respectively.
In both the depths, soil carbohydrate contents in Chinese fir plantations were significantly higher in mixed stands than pure stands, showing a trend of I > II > III (Figure 2). In the 0–20 cm depth, TC content ranged from 2.71 to 4.18 g kg−1 across the different stands, DAEC content ranged from 1.90 to 2.57 g kg−1, and HWEC content ranged from 0.93 to 1.50 g kg−1. In the 20–40 cm depth, TC content ranged from 2.42 to 3.98 g kg−1 across the different stands, DAEC content ranged from 1.83 to 2.47 g kg−1, and HWEC content ranged from 0.85 to 1.47 g kg−1.

3.3. Soil Aggregate-Associated GRSP

Regardless of the depth and stand, GRSP (including T-GRSP, DE-GRSP, and EE-GRSP) contents increased with the decrease in aggregate size (Figure 3). Specifically, the average contents of T-GRSP, DE-GRSP, and EE-GRSP in <0.25 mm aggregates were 3.82 g kg−1, 2.08 g kg−1, and 1.74 g kg−1, respectively; meanwhile, the average contents of TC, DAEC, and HWEC in >2 mm aggregates were 2.79 g kg−1, 1.51 g kg−1, and 1.28 g kg−1, respectively.
In both depths, GRSP contents were significantly higher in mixed stands than pure stands, showing a trend of I > II > III (Figure 3). In the 0–20 cm depth, T-GRSP content ranged from 2.51 to 4.81 g kg−1 across the different stands, DE-GRSP content ranged from 1.25 to 2.68 g kg−1, and EE-GRSP content ranged from 1.26 to 2.31 g kg−1. In the 20–40 cm depth, T-GRSP content ranged from 2.20 to 4.38 g kg−1 across the different stands, DE-GRSP content ranged from 1.20 to 2.45 g kg−1, and EE-GRSP content ranged from 1.01 to 1.93 g kg−1.

3.4. Regulation of Carbohydrates and GRSP on Soil Aggregates

In both depths, carbohydrate contents showed significant (p < 0.05) positive correlations with MWD and GMD, and exhibited significant (p < 0.05) negative correlations with the proportion of <0.25 mm aggregates (Figure 4). Among carbohydrate components, TC played a dominant role in soil aggregate composition and stability, contributing 6.1% and 12.2% in the 0–20 cm and 20–40 cm depths, respectively (Figure 5).
In both depths, GRSP contents also showed significant (p < 0.05) positive correlations with MWD and GMD, and exhibited significant (p < 0.05) negative correlations with the proportion of <0.25 mm aggregates (Figure 4). Among carbohydrate components, EE-GRSP played a dominant role in soil aggregate composition and stability, contributing 73.8% and 70.4% in the 0–20 cm and 20–40 cm depths, respectively (Figure 5).
In both depths, stand types can indirectly affect aggregate composition and stability through carbohydrates and GRSP, while carbohydrates and GRSP can directly affect aggregate composition and stability (Figure 6). Among carbohydrates and GRSP, TC and EE-GRSP play pivotal roles, significantly affecting soil aggregates. Moreover, the total explanatory power of carbohydrates on soil aggregate stability is 0.231 in the 0–20 cm depth and 0.476 in the 20–40 cm depth, while that of GRSP is 0.840 and 0.576, respectively (Figure 6).

4. Discussion

4.1. Soil Aggregate Characteristics

In this study, compared to pure stands, mixed stands of Chinese fir increased the proportion of >2 mm aggregates, particularly stand I (Table 3). Most studies have shown that an increase in the proportion of macroaggregates significantly improves soil aggregate stability [5,6,22,23]. For example, Mao et al. [6] found that increases in MWD and GMD are primarily caused by the formation of macroaggregates, thus establishing a positive correlation between macroaggregates and aggregate stability. In this study, MWD and GMD were significantly higher in mixed stands (especially stand I) compared to pure stands (Table 3), indicating that mixed planting with broad-leaved species could enhance soil aggregate stability by increasing the proportion of >2 mm aggregates.
Based on the hierarchical concept of soil aggregates, plant litter returns to the soil, its decomposition products are unevenly distributed among different-sized aggregates, ultimately affecting soil aggregate composition [31]. In this study, mixed stands, particularly stand type I, had an advantage in litter quantity (Table 1). The litter of Chinese fir tends to remain in the canopy before falling, contributing to the lower litter quantity in pure stands compared to mixed stands [9]. During litter decomposition, a large number of easily decomposed products (as indicated by the lower litter C/N ratio, Table 1) in mixed stands readily bind with soil microaggregates to form macroaggregates, thereby enhancing aggregate stability [32]. Additionally, the abundant litter on the ground in mixed stands provides physical protection to the soil, reducing soil erosion caused by rainfall and runoff, further mitigating the fragmentation of macroaggregates and increasing soil aggregate stability [8]. Across different stand types, MWD and GMD were significantly higher in the 0–20 cm depth than the 20–40 cm depth (Table 3), primarily due to the greater accumulation of >2 mm aggregates in the upper soil layer.

4.2. Soil Aggregate-Associated Carbohydrates and GRSP

Regarding carbohydrates, we observed an increasing trend in their content as soil aggregate size decreased, regardless of the depth and stand (Figure 2). Our previous studies found that microaggregates contain more clay [7], facilitating the adsorption of carbohydrates and enhancing their biological stability, thus favoring their preservation in the microaggregates. Moreover, most studies have shown that the adsorption capacity of different-sized aggregates for organic matters is proportional to their specific surface area [33,34,35]. Under equal mass, smaller aggregate sizes have larger surface areas, stronger adsorption capacity, and higher organic matter contents [36]. In this study, therefore, the higher carbohydrate contents in microaggregates maybe attributed to their larger specific surface areas and stable internal environments.
In Chinese fir plantations, soil carbohydrate contents were significantly higher in mixed stands than pure stands (Figure 2). Compared to pure stands, mixed stands increased litter quantity and quality (Table 1), thereby enhancing soil carbohydrate contents [13]. Moreover, the relatively high stability of soil aggregates in mixed stands (as indicated by the higher MWD and GMD) could provide physical protection for soil carbohydrates and promote their accumulation [36]. Across different stand types, soil carbohydrate contents were significantly higher in the 0–20 cm depth than the 20–40 cm depth (Figure 2), because plant litter, as an important precursor of soil organic matters, can effectively promote the secretion of carbohydrates by soil microorganisms and make the carbohydrates accumulate in the soil surface [37].
GRSP acts as a “super glue” and has a turnover time of 6–24 years in soil [38]. It could bind fine mineral particles into microaggregates and eventually form macroaggregates and stable soil structure [39]. In this study, GRSP content significantly increased with decreasing aggregate size, and was mainly concentrated in the microaggregates (Figure 3), likely due to the stronger adsorption capacity of microaggregates with larger specific surface areas. Most studies have shown that the adsorption capacity of aggregates is proportional to their specific surface area [22,34]. Wang et al. [40] and Wu et al. [41] emphasized the critical role of litter decomposition in soil organic carbon and nutrient cycling in profoundly affecting the activity of AMF and the content of GRSP. Also, their findings showed a positive correlation between GRSP content and plant litter quantity. In this study, the higher GRSP content in mixed stands (Figure 3) can be attributed to the greater litter quantity on the soil surface (Table 1). Within different soil layers of the same stand, GRSP content was greater in the 0–20 cm depth than the 20–40 cm depth (Figure 3), with this distinct difference and variation related to the spatial distribution and heterogeneity of soil AMF activity and litter decomposition products [24]. Specifically, the lower AMF activity and the less litter decomposition products in the deeper soil layer may explain the lower GRSP content in this layer [42].
As common broad-leaved species in southern China, Michelia macclurei and Mytilaria laosensis are often mixed with timber stands to improve stand productivity and soil nutrient levels [43]. In terms of habit, Michelia macclurei is a deciduous species, while Mytilaria laosensis is evergreen [44]. Therefore, Michelia macclurei produces more litter than Mytilaria laosensis during stand growth. In this study, Chinese fir with Michelia macclurei had higher carbohydrate and GRSP contents than those with Mytilaria laosensis (Figure 2 and Figure 3), because the decomposition of more litter from Michelia macclurei produced more organic matters, thus increasing soil carbohydrate contents and nutrient levels [45]. Moreover, the fibrous roots of Michelia macclurei are thicker and can easily form associations with AMF, thus increasing AMF biomass in soil [46]. Compared to Chinese fir × Mytilaria laosensis, Chinese fir × Michelia macclurei may have higher AMF biomass, contributing to their higher GRSP content [47].

4.3. Regulation of Carbohydrates and GRSP on Soil Aggregates

Soil carbohydrates serve as the primary carbon source for microbial metabolic diversity in soil aggregates, significantly promoting aggregate formation [36]. Most studies discovered a significant positive correlation between soil carbohydrates and aggregate stability, suggesting that carbohydrates, as binding agents, contribute significantly to the stability of soil aggregates [13,48,49]. In this study, RDA revealed that among carbohydrate components, TC had the most substantial contribution to soil aggregate composition and stability, explaining 6.1% (0–20 cm) and 12.2% (20–40 cm) of the aggregate variations; however, DAEC and HWEC have little influence on the aggregates (Figure 5). Carbohydrates, comprising 50%–70% of the dry weight of most plant tissues, are abundantly introduced into soil as plant residues [15]. The influence of binding agents on soil aggregates depends on both their aggregation efficiency and content [50]. As the most abundant carbohydrate component, TC has the characteristics of high contents and long persistence, thus enhancing aggregate stability by increasing binding agents and improving soil structure [51]. Carrizo et al. [52] also found that soil TC was more closely related to aggregate stability than DAEC and HWEC. In contrast, DAEC and HWEC, including soluble polysaccharides and other organic substances, are vulnerable to external factors and thus considered unstable, having a lesser impact on soil aggregate stability.
Previous studies have highlighted the role of GRSP in improving soil aggregate stability and expanding soil organic carbon pools [5,25,35]. Similarly, our study also found a significant positive correlation between soil aggregate stability (as indicated by the MWD and GMD) and GRSP content (including T-GRSP, EE-GRSP, and DE-GRSP) across different stand types (Figure 4). RDA indicated that EE-GRSP, as the most substantial contribution, explained 73.8% (0–20 cm) and 70.4% (20–40 cm) of aggregate variations, respectively (Figure 5), thus emphasizing EE-GRSP’s dominance in the processes of aggregate formation and stability. Liu et al. [53] and Sun et al. [54] also noted that EE-GRSP has a stronger effect on soil aggregate stability than DE-GRSP. EE-GRSP, an active substance newly produced by AMF, enhances soil aggregate stability, while DE-GRSP, derived from EE-GRSP turnover, is an older and more stable protein contributing to stabilize soil carbon pool [21]. Although EE-GRSP has a lower content than DE-GRSP in soil, its greater activity and binding capacity are more crucial for macroaggregate formation, while DE-GRSP plays a primary role in stabilizing aggregate external morphology due to its stability.
The PLS-PM model revealed that stand types significantly influenced soil carbohydrate and GRSP contents; meanwhile, the total effects of soil carbohydrate and GRSP contents on aggregate stability were 0.231 and 0.840 in the 0–20 cm depth, and were 0.476 and 0.576 in the 20–40 cm depth (Figure 6). Regardless of the depth, GRSP had a more profound impact on soil aggregate stability than carbohydrates (Figure 5 and Figure 6). As a glycoprotein secreted by AMF, GRSP exhibits high binding capability, tightly binding with soil mineral particles to form stable aggregate structures [22]. This binding capability not only enhances cohesion among soil mineral particles but also improves aggregates’ resistance to external disruptions like water dispersion and mechanical stress [55]. GRSP’s longer persistence in soil leads to its cumulative effect over time, further strengthening aggregate stability [56]. In contrast, carbohydrates are more sensitive to environmental changes and are more easily decomposed and utilized by soil microorganisms [26]. Therefore, GRSP exerts a more pronounced influence on soil aggregate stability compared to carbohydrates.

5. Conclusions

In this study, mixed Chinese fir stands (especially Chinese fir × Michelia macclurei) improve soil aggregate stability as well as enhance soil carbohydrate and GRSP contents. Both carbohydrates and GRSPs significantly contribute to the macroaggregate formation and aggregate stability. Specifically, GRSP (especially EE-GRSP) exerts a more prominent effect on soil aggregates compared to carbohydrates. These results show that mixed Chinese fir stands (especially Chinese fir × Michelia macclurei) have a good effect on improving soil structure, which provides a scientific basis and practical guidance for improving the productivity of Chinese fir plantations in China and other regions with similar natural conditions, such as subtropical and warm temperate zones with comparable climate and soil types.

Author Contributions

S.W. and S.Y. designed the experiments; Z.W. and L.D. carried out the experiments; X.Y. and Y.G. analyzed the experimental results; Z.W., L.D., S.W. and S.Y. wrote and edited the manuscript. All authors have read and agreed to the published version of the manuscript.

Funding

This study was supported by the Guangxi Natural Science Foundation of China (2025GXNSFAA069845), the Open Foundation of Guangxi Key Laboratory of Forest Ecology and Conservation (20241201), the Fund of Guangxi Key Laboratory of Plant Conservation and Restoration Ecology in Karst Terrain (22-035-26), the Innovation Project of Guangxi Graduate Education (YCSW2025102), and the International Cooperation Fund of the Key Laboratory of Land Resources Evaluation and Monitoring in Southwest, Ministry of Education (TDSYS202417).

Data Availability Statement

The data supporting the discovered information here can be presented by the relevant author based on reasonable requests.

Acknowledgments

The authors would like to express their gratitude to the editors and innominate reviewers for giving useful advice and optimizing this article.

Conflicts of Interest

The authors declare no conflicts of interest.

References

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Forests 16 00444 g001
Figure 1. Location of the experimental site.
Figure 1. Location of the experimental site.
Forests 16 00444 g001
Forests 16 00444 g002
Figure 2. Soil aggregate-associated carbohydrates in different stand types of Chinese fir. Different lower-case letters represent significant differences (p < 0.05) among different stand types. Different upper-case letters represent significant differences (p < 0.05) among different aggregate sizes.
Figure 2. Soil aggregate-associated carbohydrates in different stand types of Chinese fir. Different lower-case letters represent significant differences (p < 0.05) among different stand types. Different upper-case letters represent significant differences (p < 0.05) among different aggregate sizes.
Forests 16 00444 g002
Forests 16 00444 g003
Figure 3. Soil aggregate-associated GRSP in different stand types of Chinese fir. Different lower-case letters represent significant differences (p < 0.05) among different stand types. Different upper-case letters represent significant differences (p < 0.05) among different aggregate sizes.
Figure 3. Soil aggregate-associated GRSP in different stand types of Chinese fir. Different lower-case letters represent significant differences (p < 0.05) among different stand types. Different upper-case letters represent significant differences (p < 0.05) among different aggregate sizes.
Forests 16 00444 g003
Forests 16 00444 g004
Figure 4. Correlation between soil carbohydrates, GRSP, and aggregates in different stand types of Chinese fir. *, **, and *** stand for significant differences at p < 0.05, p < 0.01, and p < 0.001, respectively.
Figure 4. Correlation between soil carbohydrates, GRSP, and aggregates in different stand types of Chinese fir. *, **, and *** stand for significant differences at p < 0.05, p < 0.01, and p < 0.001, respectively.
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Forests 16 00444 g005
Figure 5. Redundancy analysis showing the influence of soil carbohydrates and GRSP on aggregates in different stand types of Chinese fir.
Figure 5. Redundancy analysis showing the influence of soil carbohydrates and GRSP on aggregates in different stand types of Chinese fir.
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Forests 16 00444 g006
Figure 6. Partial least squares path model showing the influence of soil carbohydrates and GRSP on aggregates in different stand types of Chinese fir.
Figure 6. Partial least squares path model showing the influence of soil carbohydrates and GRSP on aggregates in different stand types of Chinese fir.
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Table 1. Basic information of sample plots. Different lower-case letters indicate significant differences (p < 0.05) among different stand types.
Table 1. Basic information of sample plots. Different lower-case letters indicate significant differences (p < 0.05) among different stand types.
ItemStand Type
IIIIII
Altitude (m)730723726
Slop (°)282429
AspectSouthSouthSouth
Stand age (year)303030
Crown density0.90.90.9
Litter quantity (g m−2)324 ± 46 b455 ± 24 a504 ± 22 a
Litter C/N ratio35 ± 4 a33 ± 1 a32 ± 2 a
Table 2. Soil properties in different stand types of Chinese fir. Different lower-case letters indicate significant differences (p < 0.05) among different stand types.
Table 2. Soil properties in different stand types of Chinese fir. Different lower-case letters indicate significant differences (p < 0.05) among different stand types.
Soil DepthItemStand Type
IIIIII
0–20 cmSand (%)26 ± 1 a20 ± 2 b15 ± 1 c
Silt (%)60 ± 1 b62 ± 2 b66 ± 2 a
Clay (%)14 ± 2 c18 ± 3 b19 ± 3 a
Bulk density (g m−3)1.17 ± 0.03 b1.26 ± 0.01 a1.28 ± 0.02 a
pH4.31 ± 0.02 a4.28 ± 0.04 ab4.22 ± 0.04 b
Organic carbon (g kg−1)23.0 ± 1.1 a19.7 ± 1.1 b17.3 ± 0.60 c
Total nitrogen (g kg−1)1.10 ± 0.04 a0.98 ± 0.05 b0.84 ± 0.07 c
20–40 cmSand (%)21 ± 3 a15 ± 1 b19 ± 3 ab
Silt (%)62 ± 2 ab64 ± 2 a58 ± 2 b
Clay (%)17 ± 1 c21 ± 1 b23 ± 1 a
Bulk density (g m−3)1.19 ± 0.03 b1.27 ± 0.03 a1.30 ± 0.02 a
pH4.29 ± 0.03 a4.25 ± 0.04 ab4.21 ± 0.02 b
Organic carbon (g kg−1)17.5 ± 1.5 a14.4 ± 1.8 a10.9 ± 1.7 b
Total nitrogen (g kg−1)0.91 ± 0.13 a0.87 ± 0.08 ab0.72 ± 0.06 b
Table 3. Soil aggregate characteristics in different stand types of Chinese fir. Different lower-case letters indicate significant differences (p < 0.05) among different stand types. Different upper-case letters indicate significant differences (p < 0.05) among different aggregate sizes.
Table 3. Soil aggregate characteristics in different stand types of Chinese fir. Different lower-case letters indicate significant differences (p < 0.05) among different stand types. Different upper-case letters indicate significant differences (p < 0.05) among different aggregate sizes.
Soil DepthStand TypeSoil Aggregate CompositionSoil Aggregate Stability
>2 mm (%)2–1 mm (%)1–0.25 mm (%)<0.25 mm (%)MWD (mm)GMD (mm)
0–20 cmI37 ± 3
Aa		23 ± 2
Ba		25 ± 1
Bab		15 ± 2
Cb		1.80 ± 0.09 a1.12 ± 0.07 a
II28 ± 1
Ab		26 ± 2
ABa		22 ± 3
ABb		24 ± 3
Ba		1.54 ± 0.04 b0.86 ± 0.05 b
III25 ± 1
ABb		22 ± 2
Ba		26 ± 0
Aa		27 ± 2
Aa		1.39 ± 0.02 c0.74 ± 0.03 c
20–40 cmI32 ± 1
Aa		20 ± 1
Ba		29 ± 3
Aab		19 ± 1
Bb		1.60 ± 0.04 a0.93 ± 0.01 a
II23 ± 2
Bb		24 ± 2
Ba		26 ± 1
ABb		27 ± 3
Aa		1.35 ± 0.07 b0.73 ± 0.05 b
III18 ± 2
Cc		22 ± 2
Ba		30 ± 1
Aa		30 ± 3
Aa		1.17 ± 0.08 c0.63 ± 0.06 c
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Wang, Z.; Du, L.; Yao, X.; Guo, Y.; Ye, S.; Wang, S. Soil Carbohydrates and Glomalin-Related Soil Proteins Affect Aggregate Characteristics in Chinese Fir Plantations with Different Stand Types. Forests 2025, 16, 444. https://doi.org/10.3390/f16030444

AMA Style

Wang Z, Du L, Yao X, Guo Y, Ye S, Wang S. Soil Carbohydrates and Glomalin-Related Soil Proteins Affect Aggregate Characteristics in Chinese Fir Plantations with Different Stand Types. Forests. 2025; 16(3):444. https://doi.org/10.3390/f16030444

Chicago/Turabian Style

Wang, Zhiyao, Lei Du, Xianyu Yao, Yili Guo, Shaoming Ye, and Shengqiang Wang. 2025. "Soil Carbohydrates and Glomalin-Related Soil Proteins Affect Aggregate Characteristics in Chinese Fir Plantations with Different Stand Types" Forests 16, no. 3: 444. https://doi.org/10.3390/f16030444

APA Style

Wang, Z., Du, L., Yao, X., Guo, Y., Ye, S., & Wang, S. (2025). Soil Carbohydrates and Glomalin-Related Soil Proteins Affect Aggregate Characteristics in Chinese Fir Plantations with Different Stand Types. Forests, 16(3), 444. https://doi.org/10.3390/f16030444

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