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Article

Carbon Metabolism Characteristics of Rhizosphere Soil Microbial Communities in Different-Aged Alfalfa (Medicago sativa L.) and Their Covarying Soil Factors in the Semi-Arid Loess Plateau

by
Xianzhi Wang
1,2,3,*,
Bingxue Zhou
1,2,3 and
Qian Yang
1,2,3,*
1
College of Pastoral Agriculture Science and Technology, Lanzhou University, Lanzhou 730020, China
2
State Key Laboratory of Herbage Improvement and Grassland Agro-Ecosystems, Lanzhou University, Lanzhou 730020, China
3
National Field Scientific Observation and Research Station of Grassland Agro-Ecosystems in Gansu Qingyang, Lanzhou University, Lanzhou 730020, China
*
Authors to whom correspondence should be addressed.
Agronomy 2025, 15(7), 1602; https://doi.org/10.3390/agronomy15071602
Submission received: 11 May 2025 / Revised: 24 June 2025 / Accepted: 24 June 2025 / Published: 30 June 2025
(This article belongs to the Section Grassland and Pasture Science)
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Abstract

The carbon metabolism activity of rhizosphere soil microbial communities is an essential indicator for assessing soil ecosystem health, as it directly affects soil nutrient cycling and the stability of organic matter. However, there is a limited understanding of the carbon metabolism characteristics of rhizosphere soil microorganisms in alfalfa (Medicago sativa L.) of different ages and their relationships with soil physicochemical properties. This study used Biolog EcoPlates to evaluate the carbon metabolism activity, functional diversity, and carbon-source utilization preferences of rhizosphere soil microbial communities in 5-, 7-, and 9-year-old alfalfa grasslands on the semi-arid Loess Plateau of western China. We analyzed the relationships between soil physicochemical properties and microbial carbon metabolism characteristics, considering their potential covariation. The results showed that, with the extension of alfalfa planting years, the rhizosphere soil water content decreased significantly, pH decreased slightly, but soil organic carbon, total nitrogen, and total phosphorus contents increased significantly. The rhizosphere soil microbial community of 9-year-old alfalfa exhibited the highest carbon metabolism activity, Shannon diversity index, and carbon-source utilization. Rhizosphere soil microorganisms from different-aged alfalfa showed significantly different preferences for carbon-source utilization, with microorganisms from 9-year-old alfalfa preferentially utilizing carbon sources such as N-acetyl-D-glucosamine, D-mannitol, and D-cellobiose. Redundancy analysis revealed that soil water content was among the most important factors influencing the carbon metabolism activity of rhizosphere soil microbial communities while acknowledging that the relative contributions of soil water content, organic carbon, and nitrogen require careful interpretation, owing to their potential collinearity. This study demonstrates that, under rain-fed conditions in the semi-arid Loess Plateau, the continuous cultivation of alfalfa for nine years led to a significant decrease in soil water content but enhanced the rhizosphere soil nutrient status and microbial carbon metabolism activity, with no apparent signs of microbial functional degradation, although soil water depletion was observed. These findings highlight the complex interactions among multiple soil factors in influencing microbial carbon metabolism, providing valuable microbiological insights for understanding the sustainability of alfalfa grasslands and a theoretical basis for the scientific management of alfalfa grasslands in the semi-arid Loess Plateau region. Future research should consider longer planting periods to determine the critical age of alfalfa grassland degradation under semi-arid conditions and its associated microbial mechanisms.

1. Introduction

The rhizosphere is an active interface between plant roots and soil, and it is typically defined as the soil microenvironment directly influenced by root systems [1,2,3]. In this microenvironment, the interactions between diverse microorganisms and plants profoundly affect soil biogeochemical cycling, plant growth, and plant tolerance to environmental stress [4,5,6,7,8,9]. A considerable proportion (approximately 5–21%) of carbon fixed by plants through photosynthesis is released from the roots into the soil in the form of sugars, amino acids, organic acids, and secondary metabolites [10,11,12,13]. These root exudates not only influence carbon and nutrient cycling and regulate soil physicochemical properties but also serve as key nutrients and signaling molecules for rhizosphere microbial communities [14,15,16]. Although rhizosphere soil constitutes only a small fraction of the total soil volume (typically <5%), rhizosphere microorganisms play an irreplaceable role in maintaining nutrient availability, promoting plant growth, enhancing plant stress resistance, and improving ecosystem productivity [11,17,18,19,20,21].
The Loess Plateau, located in north-central China, covers an area of approximately 640,000 square kilometers and serves as a crucial national energy base and key ecological reconstruction region [22,23]. However, this region is also a typical ecologically fragile area characterized by an arid and semi-arid climate, spatially and temporally uneven annual precipitation distribution (annual precipitation of 350–600 mm), a loose soil structure, and severe soil erosion and ecosystem degradation resulting from long-term unsustainable human activities [24,25,26]. To control soil erosion and improve the ecological environment, the Chinese government has implemented a series of large-scale environmental restoration projects on the Loess Plateau since the 1970s, including the “Three-North” Shelterbelt Program and the Grain for Green Program [27,28,29]. After decades of effort, the regional ecological environment has significantly improved, with substantial increases in vegetation coverage [30,31,32]. During the ecological restoration process, perennial leguminous plants have been widely used as pioneer species in ecological restoration projects because of their strong environmental adaptability, nitrogen-fixing ability, well-developed root systems, and high biomass production [33,34,35,36]. Among them, alfalfa (Medicago sativa L.) has become the preferred species for ecological restoration on the Loess Plateau because of its high yield, high protein content, tolerance to drought and nutrient-poor soils, well-developed root system, and symbiotic nitrogen fixation with rhizobia, playing an essential role in soil and water conservation and soil improvement [33,37,38].
Alfalfa is the most important and widely cultivated leguminous forage crop worldwide, with a global planting area of approximately 30 million hectares distributed across more than 70 countries [39,40]. The arid and semi-arid regions of northern China are the main production areas for alfalfa, accounting for approximately 90% of the national planting area, with a cultivation history of more than 2000 years in the Loess Plateau region [41,42]. Alfalfa grasslands are generally used for forage production or in situ grazing, and compared to field crops, they typically receive minimal field management and nutrient inputs. However, with the extension of planting years, coupled with changes in precipitation patterns and increased extreme climate events on the Loess Plateau due to climate change [43,44], alfalfa grasslands are facing increasingly severe degradation challenges [26,33]. Studies have shown that the degradation of alfalfa grasslands in the Loess Plateau region is primarily manifested by decreased aboveground biomass, reduced plant density, increased weed invasion, decreased root biomass and vitality, an imbalanced root-to-shoot ratio, a decreased seed germination rate, intensified autotoxicity, and an increased incidence of diseases such as root rot with increasing planting years [36,45,46,47,48]. These degradation phenomena not only affect the productive performance of alfalfa but also weaken its role in ecological restoration.
Numerous studies have shown that soil moisture is a key factor affecting the degradation and productivity decline of alfalfa grasslands on the Loess Plateau [26,49]. With increasing planting years, alfalfa’s well-developed root system and high transpiration rate lead to intensified soil moisture consumption, forming a dry soil layer with soil water content significantly decreasing below the plant wilting point [41,42,49]. Water stress reduces microbial activity and alters carbon substrate preferences, whereas nutrient limitation constrains microbial metabolic pathways, with moisture and nutrient availability creating interactive effects on microbial carbon utilization [50]. Under water stress conditions, the carbon utilization efficiency of rhizosphere microorganisms decreases, and carbon cycling processes are hindered, thereby affecting plant nutrient acquisition and growth and ultimately accelerating grassland degradation [50,51,52].
However, there is no consensus on the critical time of alfalfa grassland degradation, degradation mechanisms, or driving factors [42,45,53]. Some studies suggest that, in addition to water factors, soil nutrient imbalance, the accumulation of autotoxic substances, and changes in rhizosphere microbial community structure collectively contribute to alfalfa degradation [36,53]. Despite existing research on alfalfa degradation phenomena, understanding the characteristics of microbial carbon metabolism and their driving mechanisms in the rhizosphere soils of alfalfa of different ages remains limited. Microbial carbon utilization efficiency (CUE) is a critical indicator of soil health and ecosystem function, directly influencing nutrient cycling and plant productivity [54,55]. This study employed Biolog EcoPlate technology to assess microbial functional diversity because of its high-throughput metabolic profiling capability and cost-effectiveness for comparative studies [56,57]. We hypothesized that, with an increasing alfalfa age, the carbon metabolic activity and substrate utilization preferences of rhizosphere soil microbial communities would undergo significant changes, primarily regulated by the synergistic effects of soil moisture, nutrient status, and pH.
To explore the changes in physicochemical properties of rhizosphere soil during alfalfa growth and their effects on microbial metabolism, this study selected different-aged alfalfa grasslands in the semi-arid region of the Loess Plateau in China as research objects. We used Biolog EcoPlates microplate technology to analyze carbon-source utilization patterns and metabolic characteristics of microbial communities, combined with soil physicochemical property measurements and plant growth indicator assessments, to systematically investigate the changing patterns and driving mechanisms of rhizosphere microbial carbon metabolism in alfalfa grasslands of different ages. This study aims to answer the following key scientific questions: (1) How do the physicochemical properties of rhizosphere soil (moisture, organic matter, pH, nutrients, etc.) and microbial carbon metabolism functions (carbon-source utilization diversity, utilization intensity, and utilization efficiency) change with stand age in alfalfa of different ages? (2) Which environmental factors (soil physicochemical properties and plant characteristics) are the key drivers of changes in rhizosphere microbial carbon metabolism, and what are their relative contributions? (3) What is the relationship between the rhizosphere microbial carbon metabolism characteristics and alfalfa growth status? This study provides a new perspective on the microbiological mechanisms underlying alfalfa grassland development and a scientific basis for formulating sustainable grassland management strategies based on microbial regulation. The findings of this study will provide scientific evidence for the sustainable management of alfalfa grasslands in semi-arid regions, particularly in optimizing planting duration, improving soil health, and enhancing ecosystem stability.

2. Materials and Methods

2.1. Study Area

The study area is situated at the Qingyang Experimental Station (35°40′ N, 107°51′ E; altitude 1298 m) on the Loess Plateau in northwestern China. This region is characterized by a temperate semi-arid climate, with a long-term average annual precipitation of 561 mm, approximately 70% of which occurs during the summer months (July to September). The annual average temperature ranges from 8 to 10 °C, with recorded extreme maximum and minimum temperatures of 39.6 and −22.4 °C, respectively. The frost-free period lasts 150–190 days, and the annual growing season extends for 255 days. The soil in the study area is black loessial soil (Entisol according to the FAO classification), consisting of silt loam with 70% silt and 23% clay content. The alfalfa (Medicago sativa L.) grasslands at the experimental station were established in different years, and at the time of sampling, there were three age groups: 5-year-old (L5), 7-year-old (L7), and 9-year-old (L9) years. Each age group consisted of a single large field block established at the Qingyang Experimental Station, with each alfalfa grassland covering an area of 96 m × 48 m (4608 m2). The three age group fields (L5, L7, and L9) were spatially adjacent but separated by approximately 50 m buffer zones. All alfalfa grasslands were established using row seeding and relied entirely on natural precipitation for growth (rain-fed conditions) without irrigation, fertilization, herbicide application, or other artificial management interventions. All grasslands were subjected to the same cutting regime, with harvests in late May, late June, and late July each year, cutting to ground level for three harvests annually, with the harvested forage used as feed. No intercropping or crop rotation was implemented during the study period, maintaining a pure alfalfa monoculture. These grasslands represent the typical alfalfa planting and management patterns in the Loess Plateau region.

2.2. Rhizospheric Soil Sampling

At the end of July 2020 (after the third cutting), rhizosphere soil was collected from the selected three age groups (L5, L7, and L9) of alfalfa grasslands. Within each age group of the alfalfa grassland, seven 1 m2 quadrats were randomly established as replicates to ensure adequate statistical power. Rhizosphere soil was collected from the 0–30 cm depth range, where the root distribution was the densest. The quadrats within each age group were randomly distributed with a minimum distance of 5 m between quadrats to ensure spatial independence and avoid pseudoreplication. The spatial separation between the three age group fields was approximately 50 m to minimize potential edge effects and ensure independent sampling.
Within each quadrat, soil profiles were excavated to a depth of 30 cm, and intact alfalfa root systems were carefully extracted. Before soil collection, complete plants were carefully excavated, and loose soil was gently removed, retaining only the soil that was tightly adhered to the root surface. Roots were not washed with water to maintain the original rhizosphere microenvironment. During sampling, the plants were gently shaken to collect soil tightly adhered to the root surface (<2 mm from the root surface). Rhizosphere soil was defined as soil closely attached to the root surface within a 0–2 mm range.
Rhizosphere soil was collected by gently shaking and lightly scraping with stainless steel spatulas, with obvious plant residues and stones removed. The rhizosphere soil collected within each quadrat was uniformly mixed to form a composite sample, resulting in 21 composite samples (three age groups × seven replicates). Each composite sample was divided into two subsamples: one part was immediately passed through a 2 mm sieve and stored at 4 °C for microbial activity analysis (Biolog EcoPlate assay), and the other part was air-dried and passed through a 2 mm sieve for soil physicochemical property analysis. All samples were maintained in portable cooling boxes (4 ± 2 °C) and transferred to the laboratory within 24 h for further analysis. Sampling was conducted on the day following cutting to ensure that all grasslands were under the same management status and that plants were at similar physiological stages, minimizing the short-term effects of cutting on rhizosphere processes.

2.3. Determination of Carbon Metabolism Activity of Soil Microbial Communities in the Rhizosphere

Biolog EcoPlate microplate technology was used to analyze the carbon-source utilization patterns (CLPP) of microbial communities in rhizosphere soil samples from alfalfa grasslands of different ages. This is a kit-based phenotyping microarray method developed by Biolog EcoPlateTM (Hayward, CA, USA) to assess patterns of sole C source utilization using mixed microbial samples [56,58,59,60]. The Biolog EcoPlate microplate contains 31 different carbon-source substrates, with three replicates for each substrate, which can be used to characterize the metabolic characteristics and functional diversity of microbial communities.

2.4. Sample Pretreatment and Inoculation

Soil sample pretreatment was conducted according to the following steps: (1) 10 g of fresh soil sample was weighed and added to 90 mL of sterilized 0.85% NaCl buffer solution (1:9 ratio); (2) the mixture was placed on a rotary shaker (180 rpm) and shaken for 30 min to thoroughly homogenize the sample; (3) after standing for 30 min, the supernatant was further shaken on a shaker for 1 h to promote the release of microbial cells from the soil particle surface into the liquid phase; (4) using a sterile pipette, 2 mL of supernatant was carefully extracted and serially diluted with sterilized 0.85% NaCl solution to a concentration of 10−3; (5) 150 μL of the diluted suspension was inoculated into each well of the Biolog EcoPlate. The 10−3 dilution was selected to minimize interference from indigenous carbon sources and soil particles in the soil on the measurement results.

2.5. Incubation and Measurement

After inoculation, the Biolog EcoPlates were incubated in a constant temperature incubator at 25 °C with relative humidity maintained at 85–90%. The culture plates were sealed with Parafilm to prevent evaporation, and optical density values were measured at 590 nm every 24 h for continuous monitoring over 168 h. During the incubation period, the optical density (OD) of each well was measured at a wavelength of 590 nm every 24 h using a Microplate Reader (Vamax, Microlog ReL 3.5). When microorganisms utilize the carbon sources in the wells, the tetrazolium violet (a redox indicator) added to the wells is reduced to insoluble purple formazan, with the color intensity being proportional to the microbial metabolic activity.

2.6. Data Calculation and Analysis

  • Average well color development (AWCD): As an indicator of the overall metabolic activity of microorganisms, it was calculated according to the formula
AWCD = Σ(C_i − R)/31
where C_i is the OD value of the i-th well containing the carbon source, R is the OD value of the control well (without carbon source), and 31 is the total number of carbon sources. During the calculation, if the value of (C_i − R) was negative, it was set to 0 [56,60,61,62].
2.
Shannon–Wiener Diversity Index (H): used to characterize the diversity of carbon-source utilization by microbial communities, calculated according to the formula
H = −Σ(P_i × lnP_i)
where P_i is the relative color development value of the i-th well, that is, the proportion of the OD value of that well to the sum of the OD values of all wells in the entire plate [63,64].
3.
Carbon-source utilization classification analysis: The 31 carbon sources were classified into six categories according to their biochemical characteristics for analysis, as follows. Amino acids (10 types): L-arginine, L-asparagine, L-phenylalanine, L-serine, glycine, L-threonine, L-glutamic acid, L-histidine, L-leucine, and L-proline. Carbohydrates (7 types): D-xylose, i-erythritol, D-mannitol, N-acetyl-D-glucosamine, D-cellobiose, α-D-lactose, and D,L-α-glycerol phosphate. Carboxylic acids (6 types): D-galacturonic acid, D-glucosamic acid, γ-hydroxybutyric acid, α-ketobutyric acid, D-malic acid, and pyruvic acid methyl ester. Polymers (4 types): Tween 40, Tween 80, α-cyclodextrin, and glycogen. Amines/amides (2 types): putrescine and phenylethylamine. Miscellaneous (2 types): 2-hydroxybenzoic acid and 4-hydroxybenzoic acid. The average utilization intensity of each carbon-source category was calculated to evaluate the preference of microbial communities for different types of carbon sources [65,66].

2.7. Determination of Soil Physical and Chemical Properties

All soil physicochemical property measurements were conducted using air-dried soil samples that passed through a 2 mm sieve, with three replicate measurements for each sample. The soil water content (SWC) was determined using the oven-drying gravimetric method. Soil pH (pH) was measured in a suspension with a soil-to-water ratio of 2.5:1 (pH meter, Remagnet PHSJ-4F, China). Soil organic carbon (SOC) was determined using the potassium dichromate external heating method [67]. The total nitrogen (TN) content in the soil was determined using the Kjeldahl method (SKD-5000, PEIOU, Shanghai, China). Soil nitrate nitrogen (NO3−-N) and ammonium nitrogen (NH4+-N) were determined through 2 mol/L KCl extraction, followed by colorimetric analysis. Total phosphorus (TP) in the soil was determined using perchloric acid-sulfuric acid digestion followed by the molybdenum antimony colorimetric method (UV-visible spectrophotometer, TU-1810PC, Beijing, China). Soil total potassium (TK) was determined by HF-HClO4 digestion, followed by flame photometry (flame photometer, FP6410, Shanghai, China).

2.8. Statistical Analysis

Data preprocessing was conducted before all data analyses, including outlier detection (box plot method) and missing value handling. Descriptive statistical analyses (mean, standard deviation, coefficient of variation, etc.) were performed for each variable. The Shapiro–Wilk and Levene’s tests were used to examine data normality and the homogeneity of variance, respectively. To assess multicollinearity among soil physicochemical variables, variance inflation factor (VIF) diagnostics were performed using the vif() function from the car package in R software (version 4.5.0) [68,69]. The results showed that all variables had VIF values < 10, with 57% of the variables having VIF < 5, indicating that multicollinearity issues were within acceptable limits. Condition index analysis further confirmed this conclusion (maximum condition index = 20.365 < 30). For data meeting the assumptions of normal distribution and homogeneity of variance, a one-way analysis of variance (ANOVA) was used to test differences in rhizosphere soil physicochemical properties and microbial metabolic indicators among alfalfa of different ages, followed by Tukey’s honestly significant difference (HSD) test for multiple comparisons (α = 0.05). For data that did not meet the above assumptions, the non-parametric Kruskal–Wallis and Mann–Whitney U tests were used for between-group comparisons. In tables and figures, different lowercase letters indicate significant differences between treatments (p < 0.05). Pearson correlation analysis (two-tailed test) was used to evaluate the correlations among soil physicochemical properties, microbial metabolic indicators (AWCD and Shannon index), and utilization intensity of different categories of carbon sources. The significance levels of the correlation coefficients (r) were set to p < 0.05 and p < 0.01.
To explore the influence of environmental factors on microbial carbon metabolism patterns, a redundancy analysis (RDA) was performed. First, detrended correspondence analysis (DCA) was performed on the utilization data of 31 carbon sources, and the results showed that the gradient length of the first axis was less than three standard deviation units. Therefore, the linear ordination method, RDA, was selected instead of canonical correspondence analysis (CCA). In the RDA analysis, the utilization intensity data of 31 carbon sources were used as response variables, and soil physicochemical properties (SWC, pH, SOC, TN, TP, TK, NO3−-N, and NH4+-N) were used as explanatory variables. To avoid the influence of variable input order on the redundancy analysis (RDA) results, the forward selection method (based on the AIC criterion) was employed to identify important environmental variables using the ordistep() function from the vegan package [70]. The significance of the RDA model and individual variables was evaluated using 999 Monte Carlo permutation tests, and partial RDA was used to analyze the independent effects of each variable after controlling for other variables. An RDA analysis was performed using CANOCO for Windows 5.0 software [71].
All statistical analyses, except for RDA, were conducted using SPSS 27.0 software (IBM Corp., Armonk, NY, USA). RDA analysis was performed using the R 4.5.0 environment. Figures were created using OriginPro 2025 (OriginLab Corporation, Northampton, MA, USA). Unless otherwise specified, all data are presented as means ± standard errors (mean ± SE).

3. Results

3.1. Physicochemical Properties of Rhizosphere Soils

Significant differences were observed in the physicochemical properties of rhizosphere soils among alfalfa grasslands of different ages (Figure 1). Soil organic carbon (SOC) and total nitrogen (TN) contents showed a significant increasing trend (p < 0.001) (Figure 1a,b). In contrast, soil water content (SWC) and pH values significantly decreased with increasing stand age (p < 0.001) (Figure 1e,f). The soil nitrate nitrogen (NO3−-N) content was significantly lower in the L7 treatment than in the L5 and L9 treatments, exhibiting a “V”-shaped change pattern of first decreasing and then increasing (Figure 1c). The ammonium nitrogen (NH4+-N) content increased with increasing stand age, with the L7 and L9 treatments being significantly higher than the L5 treatment (p < 0.05) (Figure 1d). The soil total phosphorus (TP) content also showed an increasing trend with an increasing stand age, with the L9 treatment significantly higher than the L5 treatment (p < 0.01), while the difference between the L7 treatment and the other two treatments was not significant (Figure 1g). There was no significant difference in the total potassium (TK) content among the three age treatments (p > 0.05), although it showed a slightly decreasing trend with increasing stand age (Figure 1h). Overall, with an increase in alfalfa grassland age, the rhizosphere soil nutrient status (SOC, TN, NH4+-N, and TP) significantly improved, while soil moisture conditions (SWCs) notably deteriorated, and pH values also showed a decreasing trend.

3.2. Activity and Diversity of Microbial Carbon Metabolism in Rhizosphere Soils

The carbon metabolism activity of rhizosphere soil microbial communities in alfalfa of different ages showed significant differences (Figure 2). Throughout the entire incubation period, microbial community activity (AWCD values) significantly increased with increasing alfalfa grassland age (p < 0.001), following the trend of L9 > L7 > L5 (Figure 2a). From the perspective of incubation time dynamics, in the early stage of incubation (12 h), the differences in microbial activity among the three treatments were not significant (p > 0.05); however, as the incubation time was extended, differences gradually emerged and remained substantial (p < 0.001) (Figure 2b). Notably, the microbial community in the L9 treatment consistently exhibited the highest carbon-source utilization capacity throughout the incubation process. In contrast, the L5 treatment showed the lowest value.
The functional diversity indices of microbial carbon metabolism also increased with alfalfa grassland age (Figure 3). In terms of the carbon-source utilization richness index, the L9 treatment was significantly higher than the L5 and L7 treatments (p < 0.001). However, there was no significant difference between the L5 and L7 treatments (Figure 3a). The Shannon diversity index showed significant differences among all three treatments (p < 0.05), decreasing in the order of L9 > L7 > L5 (Figure 3b). This indicates that, with an increase in alfalfa grassland age, the rhizosphere soil microbial communities not only utilized more types of carbon sources but also showed improved evenness in carbon-source utilization.
Overall, the rhizosphere soil microbial communities in long-established (L9) alfalfa exhibited higher carbon metabolism activity and functional diversity, which might be related to changes in the rhizosphere environment during long-term cultivation and the selective pressure on microbial communities.

3.3. Utilization Preferences of Specific Carbon Substrates by Soil Microbial Communities in the Rhizosphere

Significant differences were observed in the utilization patterns of the six categories of carbon substrates by rhizosphere soil microbial communities in alfalfa of different ages (Figure 4). Except for miscellaneous compounds, the utilization of carbohydrates, carboxylic acids, amino acids, polymers, and amides by microbial communities showed significant age effects (p < 0.05). Overall, the microbial community in the L9 treatment exhibited a higher utilization capacity for all six categories of carbon substrates than the L5 and L7 treatments. Notably, except for polymer substrates, there were no significant differences between the L5 and L7 treatments in the utilization of the other five categories of carbon substrates, indicating that the carbon-source utilization capacity of microbial communities remained relatively stable during the 5–7 years of alfalfa cultivation, while significant changes occurred during the 7–9-year period.
Further analysis of the utilization patterns of 31 specific carbon sources (Figure 5a) revealed that the rhizosphere soil microbial communities in alfalfa of different ages exhibited distinct carbon-source utilization preferences. The top six carbon sources with the highest utilization rates by the microbial community in the L9 treatment were N-acetyl-D-glucosamine, D-mannitol, D-cellobiose, D-xylose, L-asparagine, and Tween 80, with an average utilization rate of 25.43%. The top six dominant carbon sources for the L7 treatment were L-asparagine, N-acetyl-D-glucosamine, D-mannitol, L-serine, Tween 40, and D-galacturonic acid, with an average utilization rate of 19.71%. L5 treatment preferentially utilized D-galacturonic acid, L-serine, L-asparagine, D-mannitol, N-acetyl-D-glucosamine, and itaconic acid, with an average utilization rate of 20.07%.
A correlation analysis (Figure 5b) showed that soil physicochemical factors, except for pH, were significantly correlated with the utilization rates of multiple carbon sources (p < 0.05). In particular, soil organic carbon (SOC), total nitrogen (TN), ammonium nitrogen (NH4+-N), and total phosphorus (TP) were significantly positively correlated with the utilization rates of various carbon sources, including 2-hydroxy benzoic acid, D-malic acid, D-galactonic acid γ-lactone, γ-hydroxybutyric acid, D-glucosaminic acid, itaconic acid, α-D-lactose, D-xylose, L-phenylalanine, Tween 40, Tween 80, α-cyclodextrin, glycogen, and phenyl ethylamine. Soil water content (SWC) was significantly and negatively correlated with the utilization rates of these carbon sources. This indicates that soil nutrient status and moisture conditions are key factors affecting the carbon-source utilization patterns of microbial communities.
Overall, with an increase in alfalfa grassland age, the total carbon-source utilization by rhizosphere soil microbial communities increased, and their preferences for specific carbon sources also changed, exhibiting a stronger utilization capacity for polysaccharides and amino acid compounds. This may be related to changes in the rhizosphere environment during long-term cultivation and the selection pressure on microbial communities.

3.4. Relationship Between Metabolic Activity of Soil Microbial Communities in the Rhizosphere and Soil Physicochemical Factors

A correlation analysis revealed that the metabolic activity (AWCD) of rhizosphere soil microbial communities in alfalfa of different ages was significantly correlated with multiple soil physicochemical properties (Figure 6). Microbial metabolic activity was significantly positively correlated with soil organic carbon (SOC) (R2 = 0.73, p < 0.001), total nitrogen (TN) (R2 = 0.63, p < 0.001), ammonium nitrogen (NH4+-N) (R2 = 0.31, p = 0.01), and total phosphorus (TP) (R2 = 0.36, p < 0.001), indicating that these nutrients promote microbial activity. In contrast, microbial metabolic activity was significantly negatively correlated with soil water content (SWC) (R2 = 0.79, p < 0.001) and pH (R2 = 0.67, p < 0.001), suggesting that decreased soil moisture and increased acidification enhanced microbial metabolic activity. Among these factors, the correlation between microbial metabolic activity and SWC was the strongest, indicating that soil moisture is a key factor affecting rhizosphere microbial metabolism.
A redundancy analysis (RDA) further revealed the relationship between the carbon metabolism activity of rhizosphere soil microorganisms and soil physicochemical factors in alfalfa of different ages (Figure 7). Monte Carlo permutation test results showed that the significance of all canonical axes was p = 0.0017, confirming that soil characteristics had a significant impact on the carbon metabolism activity of rhizosphere soil microorganisms in alfalfa of different ages. The first two axes of the RDA explained 45.67% and 10.28% of the total variation, respectively, accounting for 55.95% of the total variation (Figure 7a). The RDA ordination diagram showed that the sample points of the three age treatments were separated, indicating significant differences in carbon-source utilization patterns among rhizosphere microbial communities in alfalfa of different ages. The L5 treatment samples were mainly distributed in the lower left of the diagram, aligning with the direction of the SWC and NO3−-N vectors; the L7 treatment samples were more dispersed; and the L9 treatment samples were concentrated in the upper right of the diagram, consistent with the direction of the SOC, TN, and NH4 +-N vectors.
According to the variable importance analysis (Figure 7b), soil water content (SWC) was the most important variable explaining the differences in microbial carbon metabolism activity, with a relative importance of approximately 40%, which was substantially higher than that of other soil factors. This was followed by nitrate nitrogen (NO3−-N), total nitrogen (TN), and pH, with relative importance between 10% and 20%. These results further confirmed that soil moisture was the dominant factor affecting the carbon metabolism activity of rhizosphere microbial communities in alfalfa, which may be related to the adaptive evolution of microbial communities under water-limited conditions on the arid Loess Plateau.
In summary, with an increase in alfalfa grassland age, rhizosphere soil nutrient content (primarily carbon and nitrogen) increased, whereas water content decreased. This environmental change drove the transformation of the microbial community’s carbon metabolism function, resulting in higher metabolic activity and broader carbon-source utilization capacity. While soil water content (SWC) emerged as the primary factor in the RDA analysis, this likely reflects its broad influence on overall microbial activity rather than its specific role in steering particular metabolic pathways. Individual correlation analyses revealed that soil organic carbon and nitrogen compounds showed strong associations with specific carbon-source utilization patterns (Figure 6b), suggesting a multifactorial regulatory framework where SWC acts as a master variable controlling general activity levels, while SOC and nitrogen forms exert more nuanced control over metabolic pathway selection.

4. Discussion

The metabolic activity of plant rhizosphere soil microbial communities is influenced by multiple factors, including plant species, growth stage, soil physicochemical properties, and environmental conditions [9,14,16]. These microbial metabolic characteristics are crucial for predicting plant productivity and soil health. In this study, by analyzing changes in physicochemical properties and microbial community carbon metabolism activity in rhizosphere soils of alfalfa of different ages (5, 7, and 9 years), we found that, with increasing planting years, the content of nutrients such as organic carbon, total nitrogen, and total phosphorus in rhizosphere soil increased significantly. The carbon metabolism activity and functional diversity of the microbial communities also increased accordingly. In particular, the rhizosphere soil microorganisms of 9-year-old alfalfa exhibited the highest AWCD values, the Shannon diversity index, and carbon-source utilization richness. These parameters showed no signs of degradation but indicated that long-term alfalfa cultivation might have promoted the optimization of microbial community function by altering the rhizosphere environment. This finding extends the existing research on rhizosphere microorganisms in dryland alfalfa grasslands. Previous studies have shown that rhizosphere soil microbial metabolic activity is sensitive to changes in soil moisture [26,42,49,72,73], but there is no consensus on the critical age of alfalfa grassland degradation and its main driving factors [49,53,74].

4.1. Physico-Chemical Properties of the Rhizosphere Soil

Typically, as the planting years of plants extend, soil systems undergo degradation at a certain point; however, the critical time for degradation varies depending on plant species, environmental conditions, and management practices [26,37,53,75]. Our research shows that compared to 5/7-year-old alfalfa grasslands, the rhizosphere soil of 9-year-old alfalfa had the highest content of organic carbon, total nitrogen, ammonium nitrogen, and total phosphorus, while soil water content and pH values significantly decreased (Figure 1). These results indicate that under rain-fed conditions in the semi-arid region of the Loess Plateau, even without water and fertilizer management, the rhizosphere soil of 9-year-old alfalfa maintained high nutrient levels, showing no apparent signs of nutrient degradation. Because the physicochemical properties of rhizosphere soil are closely related to plant–soil feedback, this relatively high nutrient status can provide a material basis for the continued growth of alfalfa [14,33,76].
Soil nutrient availability is important for maintaining soil health and system productivity [33,77,78]. In this study, the carbon, nitrogen, and phosphorus contents in the rhizosphere soil of 9-year-old alfalfa were significantly higher than those of 5- and 7-year-old alfalfa, which is inconsistent with some existing research results. Previous studies on alfalfa planting years, land use conversion, and management practices have shown that SOC changes typically exhibit a trend of initial increase followed by a decrease, with the timing of the transition from accumulation to depletion varying depending on the study duration, environmental conditions, and management practices [26,36,75]. The continuous growth trend observed in our study likely reflects that the 9-year timeframe has not yet reached the critical point where microbial metabolic activity begins to remove SOC faster than alfalfa can supply it through carbon inputs. This interpretation is consistent with the enhanced microbial metabolic activity observed in 9-year-old alfalfa (Section 4.2), suggesting that the soil system is still in the carbon accumulation phase rather than the depletion phase. The sustained increase in SOC observed in our study can be attributed to several factors. First, as a leguminous plant, alfalfa forms a symbiotic relationship with rhizobia in its root system for biological nitrogen fixation, continuously adding nitrogen to the soil [79,80,81]. Second, the well-developed root system of alfalfa continuously inputs organic matter into the soil, including root exudates, shed roots, and nodules, thereby promoting the accumulation of soil organic carbon [11,82]. Third, this study specifically focused on rhizosphere soil, rather than bulk soil, and as the most active area of plant–soil interaction, the nutrient accumulation effect is more pronounced in the rhizosphere [53,73,83]. The balance between carbon inputs from alfalfa and carbon losses through enhanced microbial activity ultimately determines the long-term SOC trajectory, with the transition point likely occurring beyond the 9-year timeframe examined in this study.
Notably, although the total phosphorus content in the rhizosphere soil of 9-year-old alfalfa was still higher than that of 5-year-old alfalfa, this result differs from the general understanding. As phosphorus plays a crucial role in energy conversion during nodule nitrogen fixation, leguminous plants typically have a higher demand for phosphorus [84,85,86], and as the growth years extend, phosphorus limitation often occurs in the soil. The continuous increase in phosphorus content observed in this study may be related to the following factors: On one hand, alfalfa root exudates (such as organic acids) may have promoted the activation of insoluble phosphorus in the soil [2,21,87]; On the other hand, changes in microbial communities may have enhanced phosphorus mineralization and dissolution [88,89,90]; Additionally, the rhizosphere sampling method may also have affected the results, as nutrient dynamics in the rhizosphere microenvironment differ from those in large-scale soil profiles [46,53,73].
In contrast to the nutrient accumulation trend, the soil water content in the rhizosphere of 9-year-old alfalfa was significantly lower than that of 5/7-year-old alfalfa, which is consistent with previous observations in arid regions [26,42,72,91]. As the planting years of alfalfa increase, its root system continuously penetrates deeper into the soil, reaching depths of 3–5 m, thereby enhancing its ability to access deep soil moisture. Meanwhile, the increased aboveground biomass leads to enhanced canopy transpiration, collectively resulting in a continuous decrease in soil moisture content, even forming dry soil layers. This change in moisture conditions may be a key factor limiting the long-term productivity of alfalfa and may also affect the composition and function of rhizosphere microbial communities.

4.2. Carbon Metabolism Activity and Diversity of Soil Microbial Communities in the Rhizosphere

Complex interactions exist between plant roots and soil microorganisms, with root exudates significantly influencing the composition and function of soil microbial communities by providing carbon sources and energy substrates, thereby regulating metabolic activity and carbon utilization patterns [9,50,92,93]. This study employed Biolog EcoPlate technology for community-level physiological profiling (CLPP), a method that can effectively distinguish spatiotemporal changes in microbial community metabolic activity and carbon-source utilization preferences [8,58,59,94,95]. The results showed that the carbon metabolism activity of rhizosphere soil microbial communities in 9-year-old alfalfa was significantly higher than that in 5-year-old and 7-year-old alfalfa (Figure 2, Table S1), indicating that long-term alfalfa cultivation did not decrease rhizosphere microbial activity. This higher metabolic activity is typically closely related to plant root vitality, soil nutrient availability, and element cycling rates, suggesting that 9-year-old alfalfa still maintains a healthy root system and a relatively favorable root environment under rain-fed conditions in the semi-arid region of the Loess Plateau.
Microbial community functional diversity is an essential indicator for assessing soil ecosystem health [96,97,98,99]. In this study, the richness and Shannon diversity indices of carbon metabolism in the rhizosphere soil microbial communities of 9-year-old alfalfa were significantly higher than those of 5-year-old and 7-year-old alfalfa (Figure 3 and Figure S2 and Table S2). This result differs from that of some existing studies, which generally suggest that microbial diversity decreases with increasing planting years [38,42,53]. This difference may stem from the highly dynamic nature of rhizosphere microbial communities, which are strongly influenced by plant growth stage and root exudate composition [100,101]. As alfalfa growth years increase, the composition and quantity of root exudates may change, selectively promoting the growth of specific functional microorganisms, thereby enhancing the diversity of carbon metabolism in microbial communities. This increase in the richness and diversity of microbial community carbon metabolism reflects the enhanced functional complexity and metabolic potential of microbial communities, which may have important implications for nutrient acquisition and environmental adaptability in alfalfa [10,101].
Significant differences were observed in the carbon-source utilization preferences among rhizosphere soil microbial communities in alfalfa of different ages (Figure 4, Figure 5, and Figure S3). Except for miscellaneous compounds, the rhizosphere microbial communities in 9-year-old alfalfa showed significantly higher utilization activity for carbohydrates, carboxylic acids, amino acids, polymers, and amines than those in 5- and 7-year-old alfalfa. Among the 31 specific carbon sources, rhizosphere microorganisms in 9-year-old alfalfa preferentially utilized N-acetyl-D-glucosamine, D-mannitol, D-cellobiose, and other carbon sources, with an average utilization rate of 25.43%, whereas those in 5-year and 7-year-old alfalfa tended to utilize D-galacturonic acid, L-serine, and L-asparagine, with average utilization rates of 20.07% and 19.71%, respectively. This difference in carbon-source utilization preferences may reflect changes in the microbial community composition and function [56,61,102]. The preference of 9-year-old alfalfa for N-acetyl-D-glucosamine may be related to soil nitrogen accumulation and structural changes in the microbial community caused by long-term cultivation, as this aminosugar compound typically originates from microbial cell wall degradation products. High utilization rates of carboxylic acids may be related to soil pH and organic acid accumulation, preferences for carbohydrates and polymers may reflect the enhanced decomposition capacity of complex organic matter in the soil, and high utilization rates of amino acids and amines indicate increased participation of microbial communities in nitrogen cycling [10,63,94,103].
These results collectively indicate that with the extension of alfalfa planting years, rhizosphere microbial communities not only maintained high metabolic activity but also enhanced the diversity and specificity of carbon-source utilization, which may be a critical microbiological mechanism for alfalfa adaptation to the semi-arid environment of the Loess Plateau. The differences in carbon metabolism characteristics of rhizosphere microbial communities in alfalfa of different ages reflect changes in soil nutrient status and carbon-nitrogen cycling patterns, which may further affect alfalfa’s productive performance and ecosystem functions.
It should be acknowledged that the Biolog EcoPlate method, while cost-effective and suitable for comparative studies, involves inherent limitations. This approach primarily captures the metabolic activity of fast-growing, culturable, aerobic heterotrophs and may not fully represent the in situ functional potential of the entire microbial community, particularly in ecologically complex environments such as the rhizosphere. Important microbial groups, including slow-growing taxa, anaerobes, and obligate symbionts, may be underrepresented or entirely excluded. Additionally, the results may diverge from actual in situ microbial activity due to the artificial conditions of the assay. Future studies would benefit from integrating complementary approaches such as metagenomics, metatranscriptomics, or enzyme assays to provide a more comprehensive understanding of rhizosphere microbial functionality. Another limitation of this study is the lack of microbial community composition data (e.g., 16S rRNA or ITS sequencing). While our functional findings provide valuable insights into changes in metabolic activity, the lack of taxonomic information limits our ability to directly link metabolic traits to specific microbial taxa and to determine whether functional changes reflect changes in community composition or changes in physiological adaptations of existing taxa. Future studies integrating microbial analytical techniques will improve the interpretive power of functional metabolic data.

4.3. Relationship Between Soil Properties and Carbon Metabolism Activity of Rhizosphere Microbial Communities

Soil microorganisms not only participate in nutrient cycling and organic matter transformation but also alter soil habitats through various biochemical and biophysical mechanisms, thereby influencing plant growth and ecosystem functions [99,104,105]. These microbe-mediated changes in soil properties affect the composition and function of microbial communities, forming a complex plant–soil–microbe feedback system [106,107,108]. In this study, the metabolic activity of rhizosphere soil microbial communities in alfalfa of different ages showed significant correlations with soil physicochemical factors, being positively correlated with soil carbon, nitrogen, and phosphorus and negatively correlated with SWC and pH (Figure 5, Figure 6, and Figure S1). This correlation pattern suggests that, with the extension of alfalfa planting years, the accumulation of nutrients and reduction in moisture in rhizosphere soil jointly shape the carbon metabolism characteristics of the microbial communities. The utilization preferences of microbial communities for different carbon sources reflect the accumulation, utilization, turnover, and dynamic equilibrium of soil nutrients during plant growth. Baldrian pointed out that focusing on the functional traits of soil microorganisms (such as carbon-source utilization patterns), rather than merely conducting taxonomic studies, may be a better approach to gaining a deeper understanding of soil biochemical processes [109]. In this study, the rhizosphere soil microbial communities in 9-year-old alfalfa exhibited higher carbon metabolism activity, which indicates that, from a soil biological perspective, 9-year-old alfalfa grasslands still maintain high levels of soil nutrients and biological activity, showing no apparent signs of functional degradation.
Redundancy analysis (RDA) further revealed the influence of soil physicochemical properties on microbial carbon metabolism activity (Figure 7). Among all measured soil factors, SWC was the most important variable explaining the differences in the carbon metabolism activity of rhizosphere soil microorganisms in alfalfa. Correlation analysis also showed that SWC had significant negative correlations with 9 of 31 carbon sources (mainly polymers and carboxylic acids). This result is partially consistent with existing findings on alfalfa in arid regions. Long-term alfalfa cultivation has been reported to reduce soil nutrient and moisture content, suggesting that water and fertilizer management should be implemented from the third year after planting to maintain sustainable high yields [53]. Other studies have found that continuously planted 9-year-old alfalfa grasslands can still maintain high productivity and good soil conditions, but suggest that the optimal growth period for alfalfa should not exceed 9 years [42]. Our research results show that, although 9-year-old alfalfa grasslands maintain good soil nutrients, SWC significantly decreases, which is consistent with the above-mentioned research results.
Soil moisture plays a crucial role in plant root growth, carbon release, and distribution of root exudates [110,111,112,113,114]. Under moisture-limited conditions, plants may adapt to environmental stress by adjusting the composition and quantity of root exudates, which directly affect the composition and activity of rhizosphere microbial communities [4,72,115]. Interestingly, despite the significantly reduced soil moisture content in the rhizosphere of 9-year-old alfalfa, microbial metabolic activity increased, which may reflect the adaptive response of the microbial communities to moisture stress. Under drought conditions, certain drought-tolerant microorganisms may be selectively enriched, maintaining their activity by improving the efficiency of carbon-source utilization and diversifying carbon-source utilization strategies [113,116,117].
Notably, there is no consensus on the degradation mechanism of continuous alfalfa planting. In addition to soil moisture and nutrient factors, some studies suggest that the accumulation of alfalfa rhizosphere exudates, especially phenolic acid substances, leads to root rot, which may be the main cause of degradation [40]. This view emphasizes the importance of plant–microbe interactions in grassland degradation. While RDA analysis identified SWC as the primary driver of overall microbial metabolic activity, it is important to acknowledge that this may represent an oversimplification of the complex interactions governing rhizosphere carbon metabolism. Individual correlation analyses (Figure 5b) revealed that soil nitrogen compounds (TN, NO3−-N, and NH4+-N) were strongly correlated with specific carbon-source utilization patterns, particularly for amino acids and nitrogen-containing compounds, suggesting that nitrogen availability may play a more central role in regulating the metabolism of specific carbon forms than indicated through RDA ordination. Similarly, SOC showed significant positive correlations with overall carbon metabolism activity (Figure 6), indicating its fundamental role in driving the microbial carbon processing capacity. The apparent dominance of SWC in the RDA may reflect its role as a master variable controlling overall microbial activity levels, whereas SOC and nitrogen compounds may exert a more nuanced control over metabolic pathway selection and carbon-source preferences. This multilayered regulatory framework suggests that sustainable alfalfa management should consider not only moisture management but also strategies to maintain soil organic carbon pools and optimize nitrogen cycling to support diverse microbial metabolic functions. Since the productivity and health status of alfalfa grasslands in arid regions have evident background dependence, such as site conditions, climate change, and management measures, future research needs to explore the microbiological mechanisms of alfalfa grassland degradation over a longer time scale, combining multi-omics methods such as metabolomics and metagenomics to provide a theoretical basis for formulating scientific management measures. The results of this study indicate that soil water content is the primary factor driving changes in rhizosphere microbial carbon metabolism in alfalfa, whereas the interactive effects of drought stress and nutrient changes collectively contribute to alfalfa grassland degradation. This provides important evidence for distinguishing between different degradation drivers.
It should be noted that this study focused exclusively on soil microbial function and did not include direct measurements of plant performance metrics such as alfalfa biomass, root development, forage quality, or yield trajectories. While our findings provide insights into rhizosphere microbial dynamics, the absence of plant productivity data limits our ability to establish direct correlations between microbial function and aboveground agronomic outcomes. Future studies should integrate plant performance indicators to strengthen the connection between microbial activity and alfalfa sustainability.

5. Conclusions

This study analyzed the physicochemical properties and microbial carbon metabolism activity in the rhizosphere soils of alfalfa across three age classes (5, 7, and 9 years) and found that with the extension of planting years, soil organic carbon, total nitrogen, and total phosphorus content significantly increased, while soil water content notably decreased. The rhizosphere microbial communities in 9-year-old alfalfa exhibited the highest carbon metabolism activity and functional diversity, utilizing various carbon sources at higher rates than those in younger plants. Redundancy analysis indicated that soil water content was the most critical factor affecting microbial-C metabolism. The results suggest that, under rain-fed conditions in the arid region of the Loess Plateau, 9-year-old alfalfa grasslands have not yet shown obvious signs of microbial functional degradation. However, the deterioration of soil moisture conditions may be a potential risk that limits their long-term productivity. These findings provide a new perspective for understanding the degradation mechanism of alfalfa grasslands and offer a scientific basis for developing sustainable grassland management strategies based on microbial regulation.

Supplementary Materials

The following supporting information can be downloaded at https://www.mdpi.com/article/10.3390/agronomy15071602/s1, Figure S1: Heat map showing the Pearson correlation between metabolic activity of the alfalfa rhizosphere soil microbial community and soil physicochemical factors. The color intensity represents the strength of correlation, with red indicating positive correlations and blue indicating negative correlations. Significant correlations are marked with asterisks (* p < 0.05); Figure S2: Relationships between the richness index (S), the Shannon-Weaver diversity index (H) of soil microbial communities in the rhizosphere of alfalfa at different age classes, and Average Well Color Development (AWCD). Panel (a) shows the relationship between richness index (S) and AWCD, where S increases rapidly with AWCD initially and then gradually plateaus (R2 = 0.95, p < 0.001); Panel (b) shows the relationship between diversity index (H) and AWCD, which exhibits a positive correlation (R2 = 0.81, p < 0.001). Data points include samples from 5-year (L5), 7-year (L7), and 9-year (L9) alfalfa rhizosphere soil. AWCD represents the overall carbon utilization capacity of the microbial community; Figure S3: Heat map of carbon utilization clustering in rhizosphere soil microbial communities of alfalfa of different age classes. The carbon sources (C1–C31) are as follows: C1, β-methyl-D-glucoside; C2, D-galactonic acid γ-lactone; C3, L-arginine; C4, pyruvic acid methyl ester; C5, D-xylose; C6, D-galacturonic acid; C7, L-asparagine; C8, Tween 40; C9, i-erythritol; C10, 2-hydroxybenzoic acid; C11, L-phenylalanine; C12, Tween 80; C13, D-mannitol; C14, 4-hydroxybenzoic acid; C15, L-serine; C16, α-cyclodextrin; C17, N-acetyl-D-glucosamine; C18, γ-hydroxybutyric acid; C19, L-threonine; C20, glycyl-L-glutamic acid; C21, D-glucosaminic acid; C22, itaconic acid; C23, glycogen; C24, D-cellobiose; C25, glucose-1-phosphate; C26, α-ketobutyric acid; C27, phenylethylamine; C28, α-D-lactose; C29, D,L-α-glycerol phosphate; C30, D-malic acid; C31, putrescine. Color intensity indicates the relative utilization level of each carbon source, with red representing higher utilization and blue representing lower utilization; Table S1: Carbon metabolism activity of rhizosphere soil microbial communities in alfalfa of different ages; Table S2: Shannon-Weaver diversity index (H) and richness index (S) of carbon metabolism of rhizosphere soil microbial communities in alfalfa of different ages.

Author Contributions

X.W.: conceptualization, design, investigation, the maintenance of the experiments, data analysis, and the writing of the original draft. B.Z.: design and investigation. Q.Y.: conceptualization, investigation, and supervision. All authors have read and agreed to the published version of the manuscript.

Funding

This study was funded by the National Key Research and Development Program of China (2022YFD1300803), the Key Program of the National Natural Science Foundation of China (72033009), and the National Natural Science Foundation of China (32171679).

Data Availability Statement

Data are available upon scientific request.

Conflicts of Interest

The authors declare no conflicts of interest.

Abbreviations

AWCDaverage well color development
CLPPcommunity-level physiological profiling
SWCsoil water content (%)
SOCsoil organic carbon (g/kg)
TNtotal nitrogen (g/kg)
NO3−-Nnitrate (mg/kg)
NH4+-Nammonium (mg/kg)
TPtotal phosphorus (g/kg)
TKtotal potassium (g/kg)

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Figure 1. Physicochemical properties of rhizosphere soils in alfalfa grasslands of different ages: (a) soil organic carbon (SOC), (b) total nitrogen (TN), (c) nitrate nitrogen (NO3−-N), (d) ammonium nitrogen (NH4+-N), (e) soil water content (SWC), (f) pH value, (g) total phosphorus (TP), and (h) total potassium (TK). In the box plots, the boxes represent the range from the first to the third quartile, the horizontal lines represent the median, the white squares represent the mean, and the whiskers represent the data range that does not exceed 1.5 times the interquartile range. The circles represent the outliers. A statistical analysis was performed using one-way ANOVA, followed by Tukey’s HSD test (n = 7). p-values are indicated above the box plots.
Figure 1. Physicochemical properties of rhizosphere soils in alfalfa grasslands of different ages: (a) soil organic carbon (SOC), (b) total nitrogen (TN), (c) nitrate nitrogen (NO3−-N), (d) ammonium nitrogen (NH4+-N), (e) soil water content (SWC), (f) pH value, (g) total phosphorus (TP), and (h) total potassium (TK). In the box plots, the boxes represent the range from the first to the third quartile, the horizontal lines represent the median, the white squares represent the mean, and the whiskers represent the data range that does not exceed 1.5 times the interquartile range. The circles represent the outliers. A statistical analysis was performed using one-way ANOVA, followed by Tukey’s HSD test (n = 7). p-values are indicated above the box plots.
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Figure 2. Changes in average well color development (AWCD) of rhizosphere soil microbial communities in alfalfa of different ages during the entire incubation period (a) and at different incubation time intervals (b). Data are presented as means ± SEs, with the shaded area in panel b representing SEs.
Figure 2. Changes in average well color development (AWCD) of rhizosphere soil microbial communities in alfalfa of different ages during the entire incubation period (a) and at different incubation time intervals (b). Data are presented as means ± SEs, with the shaded area in panel b representing SEs.
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Figure 3. Richness index (a) and diversity index (b) of microbial carbon metabolism in the rhizosphere soil of alfalfa of different ages. Box plots consist of the first, median, and third quartiles; dots represent means, and whiskers represent the range from minimum to maximum values. Statistical analysis was performed using one-way ANOVA, followed by Tukey’s HSD test for multiple comparisons (n = 7), with p-values indicated above the box plots.
Figure 3. Richness index (a) and diversity index (b) of microbial carbon metabolism in the rhizosphere soil of alfalfa of different ages. Box plots consist of the first, median, and third quartiles; dots represent means, and whiskers represent the range from minimum to maximum values. Statistical analysis was performed using one-way ANOVA, followed by Tukey’s HSD test for multiple comparisons (n = 7), with p-values indicated above the box plots.
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Figure 4. Box plots showing differences in the utilization of six categories of carbon substrates by rhizosphere soil microorganisms in alfalfa of different ages. The boxes represent the first, second, and third quartiles. Dots represent means. The whiskers represent the 10–90% distribution range of the data. Lowercase letters indicate significant differences between alfalfa age groups (p < 0.05).
Figure 4. Box plots showing differences in the utilization of six categories of carbon substrates by rhizosphere soil microorganisms in alfalfa of different ages. The boxes represent the first, second, and third quartiles. Dots represent means. The whiskers represent the 10–90% distribution range of the data. Lowercase letters indicate significant differences between alfalfa age groups (p < 0.05).
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Figure 5. Utilization rates of 31 carbon sources in six categories by rhizosphere soil microorganisms in alfalfa of different ages (a) and their correlation with soil physicochemical factors (b). The asterisk (*) indicates a significant correlation between soil physicochemical factors and the utilization of 31 carbon sources (p < 0.05).
Figure 5. Utilization rates of 31 carbon sources in six categories by rhizosphere soil microorganisms in alfalfa of different ages (a) and their correlation with soil physicochemical factors (b). The asterisk (*) indicates a significant correlation between soil physicochemical factors and the utilization of 31 carbon sources (p < 0.05).
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Figure 6. Correlation between the carbon metabolism activity (AWCD) of rhizosphere microorganisms and soil physicochemical properties in alfalfa grasslands of different ages: (a) soil organic carbon (SOC), (b) total nitrogen (TN), (c) ammonium nitrogen (NH4+-N), (d) total phosphorus (TP), (e) soil water content (SWC), and (f) pH. Gray shading represents the 95% confidence intervals.
Figure 6. Correlation between the carbon metabolism activity (AWCD) of rhizosphere microorganisms and soil physicochemical properties in alfalfa grasslands of different ages: (a) soil organic carbon (SOC), (b) total nitrogen (TN), (c) ammonium nitrogen (NH4+-N), (d) total phosphorus (TP), (e) soil water content (SWC), and (f) pH. Gray shading represents the 95% confidence intervals.
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Figure 7. Soil property differences in microbial carbon metabolism activity in alfalfa rhizosphere soils of different age classes. (a) Redundancy analysis (RDA) shows the differences in microbial carbon-source utilization in alfalfa rhizosphere soils of different age classes. Two RDA axes explained 55.95% of the variation in carbon utilization differences. Vectors indicate statistically significant soil predictors of plant diversity. (b) According to the RDA, SWC was the most important variable explaining the variation in carbon metabolic activity. The weight of each variable is the sum of all principal components and, therefore, does not depend on the order. * p < 0.05. SWC: soil water content; SOC: soil organic carbon; TN: total soil nitrogen; TK: total soil potassium; TP: total soil phosphorus; NH3−-N: nitrate nitrogen; NH4+-N: ammonium nitrogen; pH: soil pH. C1–C31 are carbon-source species. C1, β-Methyl-Dglucoside; C2, D galactonic acid γ-lactone; C3, L-arginine; C4, pyruvic acid methyl ester; C5, D-xylose; C6, D-galacturonic acid; C7, L-asparagine; C8, tween 40; C9, i-erythritol; C10, 2-hydroxy benzoic acid; C11, L-phenylalanine; C12, tween 80; C13, D-mannitol; C14, 4-hydroxy benzoic acid; C15, L-serine; C16, α- cyclodextrin; C17, N-acetyl-D-glucosamine; C18, γ-hydroxy butyric acid; C19, L-threonine; C20, glycogen; C21, D-glucosaminic acid; C22, itaconic acid; C23, glycyl-L-glutamic acid; C24, D-cellobiose; C25, glucose-1-phosphate; C26, α-keto butyric acid; C27, phenyl ethylamine; C28, α-D-Lactose C29, D, L-α-glycerol phosphate; C30, D-malic acid; C31, putrescine.
Figure 7. Soil property differences in microbial carbon metabolism activity in alfalfa rhizosphere soils of different age classes. (a) Redundancy analysis (RDA) shows the differences in microbial carbon-source utilization in alfalfa rhizosphere soils of different age classes. Two RDA axes explained 55.95% of the variation in carbon utilization differences. Vectors indicate statistically significant soil predictors of plant diversity. (b) According to the RDA, SWC was the most important variable explaining the variation in carbon metabolic activity. The weight of each variable is the sum of all principal components and, therefore, does not depend on the order. * p < 0.05. SWC: soil water content; SOC: soil organic carbon; TN: total soil nitrogen; TK: total soil potassium; TP: total soil phosphorus; NH3−-N: nitrate nitrogen; NH4+-N: ammonium nitrogen; pH: soil pH. C1–C31 are carbon-source species. C1, β-Methyl-Dglucoside; C2, D galactonic acid γ-lactone; C3, L-arginine; C4, pyruvic acid methyl ester; C5, D-xylose; C6, D-galacturonic acid; C7, L-asparagine; C8, tween 40; C9, i-erythritol; C10, 2-hydroxy benzoic acid; C11, L-phenylalanine; C12, tween 80; C13, D-mannitol; C14, 4-hydroxy benzoic acid; C15, L-serine; C16, α- cyclodextrin; C17, N-acetyl-D-glucosamine; C18, γ-hydroxy butyric acid; C19, L-threonine; C20, glycogen; C21, D-glucosaminic acid; C22, itaconic acid; C23, glycyl-L-glutamic acid; C24, D-cellobiose; C25, glucose-1-phosphate; C26, α-keto butyric acid; C27, phenyl ethylamine; C28, α-D-Lactose C29, D, L-α-glycerol phosphate; C30, D-malic acid; C31, putrescine.
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Wang, X.; Zhou, B.; Yang, Q. Carbon Metabolism Characteristics of Rhizosphere Soil Microbial Communities in Different-Aged Alfalfa (Medicago sativa L.) and Their Covarying Soil Factors in the Semi-Arid Loess Plateau. Agronomy 2025, 15, 1602. https://doi.org/10.3390/agronomy15071602

AMA Style

Wang X, Zhou B, Yang Q. Carbon Metabolism Characteristics of Rhizosphere Soil Microbial Communities in Different-Aged Alfalfa (Medicago sativa L.) and Their Covarying Soil Factors in the Semi-Arid Loess Plateau. Agronomy. 2025; 15(7):1602. https://doi.org/10.3390/agronomy15071602

Chicago/Turabian Style

Wang, Xianzhi, Bingxue Zhou, and Qian Yang. 2025. "Carbon Metabolism Characteristics of Rhizosphere Soil Microbial Communities in Different-Aged Alfalfa (Medicago sativa L.) and Their Covarying Soil Factors in the Semi-Arid Loess Plateau" Agronomy 15, no. 7: 1602. https://doi.org/10.3390/agronomy15071602

APA Style

Wang, X., Zhou, B., & Yang, Q. (2025). Carbon Metabolism Characteristics of Rhizosphere Soil Microbial Communities in Different-Aged Alfalfa (Medicago sativa L.) and Their Covarying Soil Factors in the Semi-Arid Loess Plateau. Agronomy, 15(7), 1602. https://doi.org/10.3390/agronomy15071602

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