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Article

The Changes in Soil Microorganisms and Soil Chemical Properties Affect the Heterogeneity and Stability of Soil Aggregates before and after Grassland Conversion

by
Cheng Ren
1,†,
Kesi Liu
1,2,†,
Pengpeng Dou
1,
Jiahuan Li
1 and
Kun Wang
1,2,*
1
College of Grassland Science and Technology, China Agricultural University, Beijing 100193, China
2
Guyuan National Grassland Ecosystem Field Station, Zhangjiakou 076550, China
*
Author to whom correspondence should be addressed.
†
These authors contributed equally to this work.
Agriculture 2022, 12(2), 307; https://doi.org/10.3390/agriculture12020307
Submission received: 28 January 2022 / Revised: 18 February 2022 / Accepted: 18 February 2022 / Published: 21 February 2022
(This article belongs to the Section Agricultural Soils)
Browse Figures
Versions Notes

Abstract

:
The conversion of grasslands to croplands is common in the agro-pastoral ecotone and brings potential risks to soil health and environmental safety. As the forming unit of soil structure, the status of soil aggregates determines soil health and is affected by multiple factors. This study investigated the changes in soil aggregate and main related factors in conversion grasslands with different managed years. Grassland conversion ages were selected as experimental treatments, which included unmanaged grassland, 3 years, 10 years, 30 years, and 50 years since grassland conversion. After grassland conversion, the proportion of large macro-aggregates with a particle size of >2 mm in the 0–10 cm soil layer decreased, small macro-aggregates with a particle size of 2–0.25 mm and micro-aggregates with a particle size of 0.25–0.053 mm increased, while aggregates with a particle size of <0.053 mm had no significant change. Soil chemical properties, most microorganisms and the soil aggregate stability indices MWD and GMD decreased at the early stage (<30 years) of the managed grasslands. After about 50 years of cultivation, soil chemical properties and microorganisms returned to equal or higher levels compared to unmanaged grasslands. However, the stability of aggregates (mean weight diameter (MWD) and geometric mean diameter (GMD)) did not recover to the initial state. MWD and GMD were positively correlated with most bacterial factors (total phospholipid fatty acids (PLFAs), bacteria, Gram-positive bacteria, Gram-negative bacteria, actinomycetes and arbuscular mycorrhizal fungi (AMF)) and some soil chemical properties (carbon, nitrogen and polysaccharides). According to the partial least square structural equation model, soil organic carbon, total nitrogen and phosphorus in the 0–10 cm soil layer explained 33.0% of the variance in MWD by influencing microorganisms. These results indicated that the stability of aggregates was directly driven by microorganisms and indirectly affected by soil organic carbon, total nitrogen and phosphorus.

1. Introduction

Agro-pastoral ecotone refers to an ecological complex of natural community and artificial community, which is characterized by a large interlacing of natural grassland and cropland [1]. Agro-pastoral zone in China is mainly distributed in Inner Mongolia, northern Hebei and northwest Shaanxi, forming a transitional zone between grassland and managed land [2]. In this staggered region, a large amount of managed lands are from grasslands conversion. After the conversion of grassland, the management pattern is changed from grassland animal husbandry to crop farming [3]. As a cropland manager, he pays great attention to cropland productivity [4] and sustainability [5]. The structure and fertility of soil determine the sustainability and fertility of cultivated land to a certain extent. As the basic unit of soil structure formation, soil aggregates have attracted much attention [6,7]. The great cohesive force between soil aggregates can increase the affinity between soil particles to resist rain erosion [8] and wind erosion [9]. The particle size distribution and stability of soil aggregates affect the distribution of soil pores and the transporting mode of water in soil [10]. The status of soil aggregates also affects the contents of soil nutrients [11,12]. Therefore, understanding the changes to soil aggregates after grassland conversion and the reasons for changes will be beneficial to management of conversion grassland in the agro-pastoral ecotone.
The distribution and changes to soil aggregates can be affected by multiple factors in the soil system. For example, soil water can affect the stability of aggregates through dry-wet cycles [13] or freeze-thaw cycles [14]. Organic matter can combine with micro-aggregates or mineral components to form new and larger aggregates [10] and increase the cohesion of aggregates through reducing the wetting rate of aggregates [15]. Nitrogen can increase plant-derived carbon by stimulating the growth of plants, thus promoting the formation of organic-mineral complexes [16]. Phosphorus can promote the formation of aggregates by influencing the root growth of vegetation and the colonization of arbuscular mycorrhizal fungi [11]. Plants can change soil aggregates by rearranging soil particles through entanglement of roots, or they can release a variety of compounds, which can cement soil particles, thus enhancing soil aggregates [17]. Earthworms in soil can affect soil aggregates by burrowing, and the mucus secreted by earthworms can be used as an adhesive to increase the stability of soil aggregates [18]. Nematodes may have an indirect but positive effect on the rate of soil nitrogen mineralization and affect the stability of soil aggregates through nitrogen mineralization [19]. Bacteria can secrete biopolymers as the adhesive of micron-sized aggregates [20]. Fungi can combine with soil particles through mycelium or play the role of binding agent in soil particles by secreting insoluble extracellular compounds [21]. Actinomycetes can increase the content of water-stable aggregates by producing polysaccharides [22]. Based on these studies, we found that most of the studies used one or few factors that affect the dynamics of soil aggregates to explore the rules that affect the changes in the aggregates. However, the formation and distribution of aggregates are generally comprehensively affected by multiple factors, therefore systematic exploration of the mechanism that affects the change of aggregates may explain the change mechanism of aggregates more clearly, but relevant studies are relatively scarce at present.
In the agro-pastoral transitional area, influenced by the ecological view of “emphasizing production over ecology” [1] and the pursuit of higher economic benefits, a large number of grasslands have been managed as arable land in different periods. The agro-pastoral ecotone in northern China is in a region with rainfall less than 450 mm. It is an ecologically fragile zone [23]. Now, it was not clear how these measures of conversion grasslands affected the soil aggregates and the factors affecting the aggregates in the soil system. Understanding the internal mechanism of aggregate changes under these measures had important practical significance for the management of this type of managed grassland. Therefore, in this study, an unmanaged grassland was taken as the control; grasslands managed for 3 years, 10 years, 30 years and 50 years were selected as research objects. This study aims to explore the changes to soil aggregates in different years after grassland conversion, analyze many related factors that influence the changes in soil aggregates, and reveal the internal mechanism of the changes in soil aggregate in different years after grassland conversion.

2. Materials and Methods

2.1. Study Site and Experimental Design

The research was carried out in the National Field Station of Grassland Ecosystem at Guyuan County, Hebei Province, China (41°44′ N, 115°42′ E, 1430 m a.s.l.) (Figure 1). The climate of the experimental area is a typical semiarid continental monsoon climate. The average annual temperature is 1.4 °C, with the lowest temperature of −18.6 °C in January and the highest temperature of 17.6 °C in July. The average annual precipitation is 430 mm, 80% of which is concentrated from June to August, and the frost-free period is 80–110 days. The soil type is Calcisols. The dominant plant of this grassland is Leymus chinensis (Trin.) Tzvelev, mainly accompanied by Stipa krylovii Roshev., Potentilla chinensis Ser., and Thermopsis lanceolala R.Br.
To evaluate the dynamic changes in soil aggregates and related soil system factors under different years of continuous cropping after conversion, the unmanaged grassland was selected as the control (C0), and the reclaimed grasslands for 3 years (C3), 10 years (C10), 30 years (C30) and 50 years (C50) were selected as the experimental plots. The crop planted after conversion was naked oat, which was sown at the end of April and harvested at the end of August each year. Diammonium phosphate at a rate of 75 kg ha−1year−1 and dried cow dung at a rate of 20 × 103 kg ha−1year−1 were applied at the initial stage of plant growth. Six sampling points were randomly selected from each experimental plot, and the minimum distance between each sampling point was 25 m, and there were 30 sampling points in 5 treatments. At each sampling point, a sampling area of 2 m by 2 m was set. In the sampling area, 6 soil sample points were randomly selected to collect from the 0–10 cm soil layer with a soil drill and mixed to form a whole sample. The mixed samples were divided into three parts, one part was placed in an aluminum box for soil water determination, the second part was air-dried for physicochemical analysis, and the third part was stored at −20 °C for microbial analysis.

2.2. Distribution and Stability of Aggregates

The collected samples used to determine the physical and chemical properties of the soil were passed through a 5 mm sieve to remove the roots and gravel of plants and air-dried. First, 100 g dry soil samples were taken and graded by a set of sieves consisting of three apertures. Four aggregate fractions were separated, including >2000 μm (large macro-aggregate), 250–2000 μm (small macro-aggregate), 53–250 μm (micro-aggregate), and <53 μm (silt + clay) [24]. Then, the stability of soil aggregates was calculated by using the separated aggregates with different particle sizes.
The stability of soil aggregates reflects the resistance of the soil structure to destructive physical stress [6]. Mean weight diameter (MWD) and geometric mean diameter (GMD) [10] were selected as indicators to describe the stability of aggregates. The calculation methods were as follows:
MWD = ∑ i = 1 n ( X i ¯ · W i )
GMD = exp ∑ i = 1 n W i · ln X i ¯
where X i ¯ represents the average particle size of a certain grade of aggregate, and Wi represents the proportion of i-size aggregate mass to total aggregate mass.

2.3. Physical and Chemical Properties of Soil

The physical and chemical properties of soil mainly measured soil bulk density, soil porosity, soil water content, soil maximum hygroscopicity, soil clay content, pH, electrical conductivity, total carbon (C), soil organic carbon (SOC), total nitrogen (N), ammonium nitrogen, nitrate nitrogen, total phosphorous (P), soil polysaccharide, free iron oxide and complex iron oxide.
The cutting ring method was used to measure the soil bulk density, and total soil porosity was calculated from the soil bulk density:
P t = 1 − B d / d s × 100
where Pt is the total soil porosity (%); Bd is the bulk soil density (g cm−3); ds is the soil density of 2.65 g cm−3.
Soil water content was determined by the drying method, soil maximum hygroscopicity was determined by the saturated potassium sulfate method [25], and soil clay content was determined by straw method [26]. The pH and EC of soil were measured by a pH meter and electrical conductivity meter (Mettler Toledo, Greifensee, Switzerland). C and N were measured by a C/N elemental analyzer (Thermo Fisher Scientific, Milan, Italy), and SOC was determined by potassium dichromate titration [27]. The soil was diluted with KCl solution at a ratio of 5:1, then filtered to measure ammonium and nitrate nitrogen using a flow chemical analyzer (FIA Compact, Radebeul, Germany). P was measured by the sodium hydroxide fusion-molybdenum antimony colorimetric method (Jinghua, China) [28]. The anthrone-sulfuric acid method was used to determine soil polysaccharides [29]. Free iron oxide was extracted by dithionite-citrate-bicarbonate, complex iron oxide was extracted by sodium-pyrophosphate, both of them were determined by ICP-OES (AVIO 200 PerkinElmer, Waltham, MA, USA) after dilution [30].

2.4. The Main Biological Factors and Enzymes

After preliminary investigation, earthworms were not found in the sample plots, so the main biological factors determined in this study were soil nematodes and soil microorganisms. Sucrase, urease and alkaline phosphatase in soil were determined as related enzymes.
The sucrose density-gradient centrifugation method was used to determine soil nematodes [31]. The microbial community of soil was determined by the phospholipid fatty acid method [32]. Eight grams of dry soil was extracted with a single-phase mixture of chloroform/methanol/citrate buffer (23 mL at a 1:2:0.8 volume ratio), and after shaking for 2 h, the supernatant was collected by centrifugation and transferred to a silica solid-phase extraction column. The lipids and glycolipids in the extract were washed with 5 mL chloroform and 10 mL acetone, successively. Then the phospholipids were eluted with 5 mL methanol and dried under N2; The phospholipid fraction was methylated with 1 mL methanol-toluene solution (1:1) and 1 mL 0.2 M potassium hydroxide solution (40 mL 0.5 M KOH + 60 mL CH3OH) before 2 mL ultra-pure water and 0.3 mL acetic acid were added. The methylated fatty acid methyl ester was extracted with chromatographic grade n-hexane and dried under N2. Using 19:0 methyl ester as an internal standard, the obtained fatty acid methyl ester was analyzed on a gas chromatograph (Hewlett-Packard 6890 Series GC, FID) using a MIDI software system to determine the content of phospholipid fatty acid (PLFA) components [33]. Details are as follows: the bacterial biomass was estimated as the sum of 14:0iso, 14:00, 15:0iso, 15:0anteiso, 15:00, 16:0iso, 16:00, 16:1w9c, 16:1w7c, 17:0iso, 17:0anteiso, 17:00, 17:0cyclow7c, 17:1isow9c, 18:00, 18:1w7c, 18:1w5c and 19:0cyclow7c [34,35,36]; The biomass of Gram-positive bacteria was estimated with the sum of 14:0iso, 15:0anteiso, 15:0iso, 16:0iso, 17:0iso and 17:0anteiso [37]; The biomass of Gram-negative bacteria was estimated with the sum of 16:1w9c, 16:1w7c, 17:0cyclow7c, 19:0cyclow7c, 18:1w7c and 18:1w5c [35,38,39]. Fungal biomass was estimated by the sum of 18:2w6c and 18:1w9c [35], arbuscular mycorrhizal fungi (AMF) biomass was represented by 16:1w5c [39], actinomycetes biomass was estimated by the sum of 16:10 methyl, 17:10 methyl and 18:10 methyl [40], total PLFAs was estimated as the sum of bacteria, fungi, actinomycetes and AMF.
The contents of microbial biomass carbon and microbial biomass nitrogen in the soil were determined by the fumigation-leaching method [41]. Ten grams of fresh soil was fumigated in alcohol-free chloroform at 25 °C in the dark for 24 h, and each sample was set with a non-fumigated control, which was also placed in the dark for 24 h. Then it was extracted with 40 mL 0.25 mol/L K2SO4 for 30 min. The filtrate was filtered and determined by Multi N/C 3100 analyzer (Jena, Germany). AMF hyphae in soil were measured by vacuum pump microfiltration membrane extraction [42]. The method described by An et al. [43] was used to measure urease and alkaline phosphatase, and the method described by Gianfreda et al. [44] was used to measure sucrase.

2.5. Statistical Analysis

Univariate analysis of variance and Tukey test (p < 0.05) (IBM SPSS STATISTICS 25.0) were used to determine the significant differences of soil aggregate stability and related factors in different tillage years after the grassland was converted to arable land. Before the corresponding calculation, the normality and homogeneity of the data were checked. In view of the strong collinearity among variables, the application of multiple regression in data analysis was greatly restricted. In addition, more than one index was used to evaluate the aggregate stability. Partial least squares (SIMCA 14.1 Umetrics company, Malmö, Sweden) was used to further explore the relationship between the soil aggregate stability index and related variables [45]. The structural equation model (SmartPLS 3 GmbH, Oststeinbek, Germany) based on the partial least squares method was used to explore the relationship between different variables and the comprehensive influence of these variables on the stability of aggregates.
MWD is one of the best methods to present the distribution data of soil aggregates [46], which is easy to calculate and highly visible [47]. Therefore, based on the results of previous studies, SmartPLS 3 software was used to design the model and determine the path coefficient with MWD as the response variables. Bootstrap analysis was run 10,000 times to test the significance of the path. The model was evaluated using the following criteria: (1) Model internal consistency reliability, composite reliability should generally be higher than 0.70; (2) Indicator reliability, indicator loadings should be higher than 0.70; (3) Convergent validity, the average variance extracted should be higher than 0.50. Expected latent variables, which were not consistent due to low indicator loadings or low average variance, were modified by removing nonsignificant indicator variables [48].

3. Results

3.1. Distribution and Stability of Soil Aggregates in Conversion Grasslands with Different Managed Years

After grassland conversion, the composition proportion of soil aggregates of different sizes changed (Figure 2). The proportion of large macro-aggregates (>2 mm) in unmanaged grassland was higher than that in any managed grassland, which was 55.85% in unmanaged grassland and 33.31% to 36.57% in managed grasslands. The proportion of the small macro-aggregates with a particle size of 2–0.25 mm in managed grassland was greater than that in unmanaged grassland. With the increase in conversion years, the proportion of the aggregate of this size increased at first and then decreased. Under unmanaged grassland, the proportion of micro-aggregates with a particle size of 0.25–0.053 mm was lower than that in the managed grassland, which was 5.87% under the unmanaged grassland, and 8.01–11.05% under the managed grassland. The aggregates with a particle size of <0.053 mm had no significant changes among treatments, 0.71% under unmanaged conditions and ranging from 0.60% to 0.74% under managed grasslands with different conversion years (Figure 1).
The stability index of aggregates also changed after grassland conversion (Figure 3). MWD and GMD decreased significantly after grassland conversion. The MWD and GMD were 2.39 and 1.85 in unmanaged land, respectively, and decreased to 1.81–1.90 and 1.29–1.38, respectively, after grasslands were managed. Among managed lands with different years of conversion, MWD tended to slightly increase with the increase in conversion years, which was 1.82 after conversion for 3 years and 1.90 after conversion for 50 years, with an increase of 4.40%. GMD had little overall change with the increase in conversion years (Figure 3).

3.2. Changes in Soil Physicochemical Properties in Conversion Grasslands with Different Managed Years

Soil bulk density and total soil porosity did not change much before and after conversion, soil bulk density was between 1.23 g cm−3 and 1.28 g cm−3, and total soil porosity was between 51.74% and 53.70 % (Table 1). The soil clay content was 25.92% in the unmanaged area, decreased with the increase in conversion years after grassland conversion, and reached the minimum value of 18.63% after 50 years of conversion. In the unmanaged state, soil water content was 13.60%, but with the increase in conversion years, soil water content fluctuated between 10.57% and 16.52%. Under the condition of unmanaged land, soil maximum hygroscopicity was 7.91%, which was much higher than that under managed grasslands. Meanwhile, the maximum hygroscopicity of managed grassland showed an overall downward trend with the increase in conversion years, and the minimum value was 5.07% after 50 years of conversion (Table 1). Soil pH and electrical conductivity increased after grasslands were managed.
The content of SOC in unmanaged land was 24.56 g kg−1, which was higher than that of grassland managed for 3 years or 10 years. As for managed grassland, SOC increased with the increase in conversion years, reaching the highest value of 34.37 g kg−1 in managed grassland for 50 years. C and N of unmanaged grassland were 39.62 g kg−1 and 2.65 g kg−1, respectively, which were higher than those of managed grassland for 3 years, 10 years and 30 years, and similar to those of managed grassland for 50 years (Table 1). After conversion, C and N in soil increased with the increase in conversion years, and C and N reached the maximum of 43.15 g kg−1 and 3.34 g kg−1 in 50 years of conversion, respectively. There was no obvious difference in C:N before and after grassland conversion. After grassland conversion, C:N tended to decrease with the increase in conversion years. The soil ammonium nitrogen under unmanaged grassland was 13.48 mg kg−1, which was higher than that in 3 years and 10 years of conversion, but lower than over 30-year managed grasslands. After grassland conversion, soil ammonium-nitrogen increased with the increase in conversion years and reached 24.49 mg kg−1 in 50 years of conversion grassland. Soil nitrate-nitrogen tended to increase with an increase in the year of conversion and reached 54.55 mg kg−1 after 50 years of conversion, which was greater than that in unmanaged grassland. Under the unmanaged grassland, P in soil was 0.64 g kg−1, which was greater than that under the grassland managed for 3 years, 10 years and 30 years. After grassland conversion, P in soil tended to increase with the increase in conversion years and reached 1.13 g kg−1 under 50-year managed grassland. The content of soil polysaccharides of unmanaged grassland was 1.82 mg g−1, which was higher than that in any conversion grassland. After grassland conversion, with the increase in conversion years, the content of soil polysaccharides first decreased and then increased, with the lowest of 1.00 mg g−1 at 10 years and the highest of 1.47 mg g−1 at 50 years. The complex iron and free iron oxide in soil changed little before and after grassland conversion (Table 1).

3.3. Changes in Main Biological Factors and Enzymes in Conversion Grasslands with Different Managed Years

Soil nematodes did not change much before and after grassland conversion. Microbial biomass carbon and microbial biomass nitrogen in unmanaged grassland were higher than those in any conversion grassland, and they tended to decrease with the increase in conversion years (Table 2). The conversion of grassland led to the changes in soil microbial community to some extent. In the initial stage of conversion (3-year), the amount of microbial community (total PLFA) decreased compared with that in unmanaged grassland. However, with the increase in conversion years, the microbial community had increased to a certain extent, and the microbial biomass had reached a higher level in the 50 years of conversion than that of the original grassland (Table 2). In terms of specific microbial changes, the trends of bacteria, fungi, AMF, actinomycetes, Gram-negative bacteria and Gram-positive bacteria were consistent with the changes in the microbial community. In the initial stage of conversion (3–10 years), these microbes decreased, but with the increase in cultivation years, they increased and reached a higher amount of microbial population in the 50 years of conversion than that in the original grassland. Bacteria, Gram-positive bacteria, Gram-negative bacteria, fungi, AMF and actinomycetes reached 39.30 nmol g−1, 12.70 nmol g−1, 12.93 nmol g−1, 5.12 nmol g−1, 2.46 nmol g−1 and 6.33 nmol g−1 after 50 years of conversion, respectively. The AMF hyphae in unmanaged grassland was higher than those in any conversion grassland, and the AMF hyphae decreased with the increase in conversion years.
Before and after grassland conversion, urease and alkaline phosphatase changed slightly, ranging from 21.56 NH4+-N mg/(100 g·24 h) to 26.10 NH4+-N mg/(100 g·24 h) and from 2082.17 phenol μg/(g·24 h) to 2390.50 phenol μg/(g·24 h), respectively. Sucrase decreased sharply in the initial stage of grassland conversion (3 years) but increased with the increase in conversion years, reaching the maximum of 7.24 glucose mg/g·24 h after 50 years of conversion (Table 2).

3.4. Relationship between Soil Aggregate Stability and Soil Physicochemical Properties, Main Biological Factors and Enzymes

Among these factors, most of the soil physicochemical properties showed a low correlation with soil aggregates stability index MWD, such as soil bulk density, soil total porosity, soil clay content, soil water content, pH, soil oxides, SOC, ammonium-nitrogen, nitrate-nitrogen, etc. However, C, N and soil polysaccharides showed significant correlation with MWD (Figure 4a). As for biological factors, MWD had positive correlation with most of the microorganisms, including AMF, Gram-positive bacteria, total PLFAs, bacteria, actinomycetes, microbial biomass nitrogen and Gram-negative bacteria. The relationships between GMD and potential related factors showed similar trends to MWD with these factors. GMD was positively correlated with a few soil physicochemical properties (C, N, and polysaccharides) and most biological factors (total PLFAs, bacteria, Gram-positive bacteria, Gram-negative bacteria, AMF and actinomycetes) (Figure 4b).
The partial least square structural equation model (PLS-SEM) showed that the physicochemical properties of soil explained 33.0% of the variance in the stability of soil aggregates through soil microorganisms (Figure 5), and the interpretation level was at a moderate level [49]. Organic carbon, total phosphorus and total nitrogen significantly affected actinomycetes, Gram-negative bacteria and fungi, and thus significantly affected MWD, while organic carbon, total phosphorus and total nitrogen had no significant effect on MWD. The model showed that the stability of soil aggregates in 0–10 cm soil layer under different cultivation years was greatly influenced by biological factors, especially, fungi, actinomycetes and Gram-negative bacteria played a major role in microorganisms (Figure 5).

4. Discussion

4.1. Distribution and Stability of Soil Aggregates under Different Conversion Years

After the relatively stable grassland soil system is conversed as managed land, the original soil aggregate structure and stability will generally change due to human interference, which has been confirmed in our research. Our results showed that compared with unmanaged grassland, the proportion of large macro-aggregates with a particle size of >2 mm decreased, the proportion of soil aggregates with a particle size of 2–0.053 mm increased, and soil aggregates with a particle size of <0.053 mm had little change in managed grassland (p < 0.05). At the same time, with the increase in conversion years after grassland conversion, large macro-aggregates (>2 mm) first decreased and then increased, small macro-aggregates (2–0.25 mm) first increased and then decreased, while the micro-aggregates (0.25–0.053) mm and the silt + clay (<0.053 mm) had little change. These changes were probably due to the destruction of macro-aggregates and the increase in micro-aggregates during the cultivation process [50]. However, with the increase in tillage years, the accumulation of crop root residues in the soil will increase, which will increase the content of soil organic matter and promote the formation of macro-aggregates [51].
Compared to the original grassland, the stability of soil aggregates (MWD and GMD) decreased after conversion. Meanwhile, MWD tended to increase with the increase in conversion years, while GMD did not change significantly. This change is similar to some experimental results [52,53,54] but different from some experimental results [50,55]. MWD and GMD are quantitative indicators of soil structure. At the initial stage of grassland conversion, the soil structure was destroyed, the content of large aggregates decreased, the degree of aggregation reduced, and the stability worsened, which led to a decrease in MWD and GMD. However, with the increase in conversion years, the residual nutrients in cattle dung are slowly released [52], and the residual roots in soil gradually increase [51], which may improve soil structure and promote the increase in MWD to a certain extent.

4.2. Effects of Soil Physical and Chemical Properties on Soil Aggregate Stability

In our research, most of the soil physical properties showed a low correlation with the stability of soil aggregates, such as soil bulk density, soil total porosity, soil clay content, soil water content, pH, soil oxides, etc. The trade-off effects of these soil physical properties on soil aggregates were the possible reason that alleviated the correlation between them. For instance, the low correlation between soil bulk density and soil aggregates might be due to the increase in compaction that led to the collapse of aggregates [56], but the mixing of dispersed soil particles under compaction might also lead to the formation of aggregates [57]. Although soil porosity is the result of soil particle recombination to form aggregates, high porosity will reduce the stability of aggregates [58]. As a cementitious material, soil clay is combined with humified soil organic matter and polyvalent metal cations [59], which contributes to the stability of soil aggregates. However, clayey particles may mainly combine with particles in micro-aggregates, thus negatively affecting the stability of aggregates [60]. The low correlation between the stability of aggregates and soil water content and soil maximum hygroscopicity might be due to the fact that the dry-wet cycle promoted the formation of aggregates on the one hand [61] and accelerated the decomposition of aggregates on the other hand [62], and these two different effects weakened the influence of soil moisture on aggregates. Similarly, soil pH may increase the stability of soil aggregates by positively inducing plant organic matter [63], but free H+ in soil solution may replace Ca2+/Mg2+, induce leaching of Ca2+ and Mg2+, and inhibit the formation of organic-mineral complexes by inhibiting the formation of cation bridges, thus reducing the stability of soil aggregates [16]. Igwe et al. [64] found that complex iron oxide seems to have a positive effect on particle aggregation, Zhao et al. [65] found that iron oxide may form stable organic-mineral complexes with organic matter, thereby improving the structure and stability of soil aggregates. However, our research found that the correlation between soil oxides and soil aggregate stability was low, which might be due to the fact that sesquioxides mainly play a role in microaggregates [66]. In addition, Duiker et al. [67] also found that free iron oxide was not correlated with MWD, and Yin et al. [68] found that free iron oxide was not significantly correlated with aggregate stability.
The stability of soil aggregates was closely related to some chemical properties of soil, such as C, N and soil polysaccharides. The C and N in the soil can increase the input of organic residues by promoting plant growth, thereby promoting the formation of organic-mineral complexes to build large soil aggregates, and then improve the stability of soil aggregates [16]. Soil polysaccharides, as an unstable part of soil organic matter, are important binding agents for soil aggregates [69], which may improve soil structure by adhering soil particles [17] and improving soil water holding capacity [70]. However, we also found that some soil chemical properties, such as SOC, ammonium-nitrogen, nitrate-nitrogen, C:N and P, had little correlation with the stability of soil aggregates. Some studies have emphasized the key role of organic matter in the formation of soil, such as Wick et al. [71] and Zhu et al. [12]. However, these relationships are not always tenable, because only part of the organic matter is responsible for water-stable aggregates, such as carbohydrates, which are involved in the stabilization of soil aggregates [72]. In addition, by controlling the quantity and level of microorganisms in the soil, soil organic matter may also play an indirect role in macro-aggregates [73]. The effects of nitrate and ammonium nitrogen on soil aggregates also varied. Fonte et al. [74] and Bossuyt et al. [75] found that the addition of inorganic nitrogen reduced the stability of soil aggregates, while Zhu et al. [8] found that appropriate inorganic nitrogen is beneficial to produce basidiomycetes and ascomycetes which contribute to the formation of aggregates. The decrease in soil C:N may accelerate humification, and microaggregates and mineral particles can gather around humic substances to form larger aggregates [76]. However, the increase in soil C:N may also limit the activity of microorganisms related to the mineralization of soil organic matter, thus affecting the formation of soil aggregates [77], resulting in a low correlation between C:N and aggregate stability. The low correlation between P and soil aggregate stability may be due to the indirect effect of P on soil aggregates. For example, the availability of P affects the aggregates via affecting the colonization of AMF [17], but the colonization of AMF is also affected by other factors, such as cultivation [78].

4.3. Effects of the Main Biological Factors on Soil Aggregate Stability

Different biological factors have different effects on the stability of soil aggregates. Fungi can improve the stability of aggregates by entangling particles with hyphae [17] and can also produce a large amount of extracellular substances to combine soil particles into aggregates [21]. However, in this study, the correlation between fungi and aggregate stability (MWD and GMD) was low. Sall et al. [79] found that the influence of fungal activity on aggregates is greater than that of fungal population density. In this study, fungal population density had an increase to some degree, but AMF hyphae decreased. This was probably the reason for low correlation. Lehmann et al. [80] also reported that the aggregation ability of different fungi to soil varies greatly, including positive effects and neutral effects. Total PLFAs, bacteria, Gram-positive bacteria, Gram-negative bacteria, actinomycetes, and AMF in this study showed a positive correlation with MWD. Total PLFAs are generally used to evaluate the total amount of microorganisms in the soil [81], and microorganisms are closely related to aggregates and affect the stability of aggregates in various ways [59]. Bacteria can secrete biopolymers, which can be used as the adhesive of micron-scale aggregates [20], Gram-negative bacteria may form aggregates by producing extracellular polysaccharides [82], and Gram-positive bacteria and Gram-negative bacteria may also aggregate into curly coarse aggregates [83]. At the same time, the total charge of the cell wall of both Gram-positive and Gram-negative bacteria is negative, which may enhance their ability to adhere to surfaces, such as clay particles and soil aggregates [84]. Actinomycetes may increase the content of water-stable aggregates by producing polysaccharides [22]. Meanwhile, actinomycetes can effectively improve soil water impact resistance [85]. AMF can increase the stability of aggregates through mycelial entanglement of soil particles [86], and AMF can also promote soil agglomeration by secreting glomalin-related soil protein as a binder for soil particles [87]. However, urease, sucrase and alkaline phosphatase in our research had low correlations with aggregate stability (MWD and GMD). Kanazawa and Filip [88] found that aggregate size was positively correlated with soil enzyme activity, and Allison and Jastrow [89] found that aggregate size was negatively correlated with soil enzyme activity. The increase in soil enzyme activity can decompose relatively refractory substrates in soil [7], thus providing more organic matter to the soil. However, Shi [90] found that the increase in soil enzyme activity may also accelerate the decomposition rate of organic matter in the soil, leading to the decrease in organic matter in the soil, thus affecting the stability of soil aggregates. Therefore, the relationship between soil enzymes and aggregates was complex, so it was necessary to study the effects of soil enzymes on aggregates from different ecosystem perspectives.

5. Conclusions

Grassland conversion utilization changed the proportion of soil aggregates with different particle sizes in the 0–10 cm soil layer. Compared to unmanaged grassland, the proportion of large macro-aggregates (>2 mm) decreased and small macro-aggregates (2–0.25 mm) and micro-aggregates (0.25–0.053) mm increased after conversion. The soil aggregate stability index MWD and GMD, soil chemical properties and most microorganisms decreased rapidly at the early stage (<30 years) of the conversion of grasslands. After about 50 years of conversion, soil chemical properties and microorganisms returned to equal or higher levels compared to unmanaged grasslands. However, the stability of aggregates (MWD and GMD) did not recover to the initial state. Partial least squares path model showed that soil chemical properties (organic carbon, total nitrogen and phosphorus) in 0–10 cm soil layer indirectly affected the stability of soil aggregates (MWD) by affecting microorganisms (R2 = 0.33), especially actinomycetes, fungi and Gram-negative bacteria. Therefore, increasing soil chemical properties (such as adding nitrogenous and phosphate fertilizer, or phosphate fertilizer with farm manure) to improve soil microbial composition may be an effective way to improve the stability of soil aggregates in managed grassland.

Author Contributions

Conceptualization, K.W., C.R. and K.L.; formal analysis, investigation, and resources, C.R., J.L. and P.D.; data curation, C.R. and P.D.; writing—review and editing, C.R. and K.L.; supervision, project administration, and funding acquisition, K.W. and K.L. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the National Natural Science Foundation of China (Grant No. 31772654) and the National Key Research and Development Program of China (No. 2021YFD1300503).

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Not applicable.

Conflicts of Interest

The authors declare no conflict of interest.

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Figure 1. The map of the sample location.
Figure 1. The map of the sample location.
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Figure 2. Distribution of soil aggregates in managed grasslands with different managed years. C0: Unmanaged grassland; C3: managed grassland for 3 years; C10: managed grassland for 10 years; C30: managed grassland for 30 years; C50: managed grassland for 50 years.
Figure 2. Distribution of soil aggregates in managed grasslands with different managed years. C0: Unmanaged grassland; C3: managed grassland for 3 years; C10: managed grassland for 10 years; C30: managed grassland for 30 years; C50: managed grassland for 50 years.
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Figure 3. Variation of stability index of aggregates in managed grasslands with different managed years. Different lowercase letters indicate significant differences between treatments with different years of conversion. C0: Unmanaged grassland; C3: managed grassland for 3 years; C10: managed grassland for 10 years; C30: managed grassland for 30 years; C50: managed grassland for 50 years (p < 0.05).
Figure 3. Variation of stability index of aggregates in managed grasslands with different managed years. Different lowercase letters indicate significant differences between treatments with different years of conversion. C0: Unmanaged grassland; C3: managed grassland for 3 years; C10: managed grassland for 10 years; C30: managed grassland for 30 years; C50: managed grassland for 50 years (p < 0.05).
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Figure 4. Relationships between soil aggregate stability index MWD (a) and GMD (b) and soil physicochemical properties, main biological factors and enzymes. (p < 0.05).
Figure 4. Relationships between soil aggregate stability index MWD (a) and GMD (b) and soil physicochemical properties, main biological factors and enzymes. (p < 0.05).
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Figure 5. The relationships between soil aggregate stability, microbes and soil physicochemical properties in 0–10 cm soil layer under PLS-SEM. The circles represent latent variables, the squares represent observed variables, the thick arrows between latent variables represent significant relationships, and the numbers on the arrows represent path coefficients. The number on the thin arrows between each latent variable and observed variables represent loadings at the 0.05 level; the numbers in the circles are R2 values; Significant effect is indicated by blue solid line, while non-significant effect is indicated by red dashed line; Coefficients in the measurement models vary between −1.0 (absolute negative correlation) and 1.0 (absolute positive correlation). (p < 0.05).
Figure 5. The relationships between soil aggregate stability, microbes and soil physicochemical properties in 0–10 cm soil layer under PLS-SEM. The circles represent latent variables, the squares represent observed variables, the thick arrows between latent variables represent significant relationships, and the numbers on the arrows represent path coefficients. The number on the thin arrows between each latent variable and observed variables represent loadings at the 0.05 level; the numbers in the circles are R2 values; Significant effect is indicated by blue solid line, while non-significant effect is indicated by red dashed line; Coefficients in the measurement models vary between −1.0 (absolute negative correlation) and 1.0 (absolute positive correlation). (p < 0.05).
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Table
Table 1. Variations of soil physicochemical parameters in managed grasslands with different managed years.
Table 1. Variations of soil physicochemical parameters in managed grasslands with different managed years.
Soil Physicochemical Parameter Managed Year
C0C3C10C30C50
Bulk density (g cm−3)1.25 ± 0.05 a1.28 ± 0.03 a1.28 ± 0.07 a1.23 ± 0.04 a1.26 ± 0.03 a
Total soil porosity (%)52.72 ± 1.74 a51.74 ± 1.22 a51.63 ± 2.74 a53.70 ± 1.39 a52.30 ± 1.03 a
Clay content (%)25.92 ± 1.99 a,b29.07 ± 1.34 a27.60 ± 1.76 a22.95 ± 0.92 b18.63 ± 2.77 b
Soil water content (%)13.60 ± 1.42 a,b13.17 ± 1.17 a,b12.69 ± 0.50 a,b16.52 ± 1.38 a10.57 ± 0.58 b
Maximum hygroscopicity (%)7.91 ± 0.68 a8.92 ± 0.38 a5.67 ± 0.24 b5.81 ± 0.33 b5.07 ± 0.17 b
pH9.55 ± 0.19 a9.21 ± 0.11 a8.70 ± 0.02 a,b8.62 ± 0.03 b8.06 ± 0.10 c
Electrical conductivity (μs cm−1)388.92 ± 77.20 a,b143.54 ± 22.23 a,b103.19 ± 4.23 b123.67 ± 6.51 b253.28 ± 25.44 a
Soil organic carbon (g kg−1)24.56 ± 2.45 a,b,c15.44 ± 1.33 b,c16.74 ± 0.60 c19.56 ± 0.46 b34.37 ± 1.71 a
Total carbon (g kg−1)39.62 ± 3.23 a28.06 ± 1.87 b20.63 ± 1.38 b26.60 ± 1.31 b43.15 ± 0.96 a
Total nitrogen (g kg−1)2.65 ± 0.28 a,b1.41 ± 0.08 b1.61 ± 0.06 b1.79 ± 0.10 b3.34 ± 0.08 a
C:N15.20 ± 0.61 a,b,c20.06 ± 1.36 a12.82 ± 0.64 b,c14.92 ± 0.37 a,b12.91 ± 0.12 c
Soil ammonia-nitrogen (mg kg−1)13.48 ± 0.96 b10.74 ± 0.93 b12.44 ± 0.93 b23.51 ± 0.54 a24.49 ± 0.46 a
Soil nitrite-nitrogen (mg kg−1)9.98 ± 1.56 b10.18 ± 0.98 b9.22 ± 0.43 b14.42 ± 1.35 b54.55 ± 2.53 a
Total phosphorus (g kg−1)0.64 ± 0.02 b0.49 ± 0.04 c0.47 ± 0.02 c0.63 ± 0.02 b1.13 ± 0.04 a
Polysaccharides (mg g−1)1.82 ± 0.21 a1.18 ± 0.08 b1.00 ± 0.12 b1.09 ± 0.11 b1.47 ± 0.07 a,b
Complex Fe oxides (g kg−1)0.18 ± 0.02 a0.14 ± 0.01 a0.18 ± 0.02 a0.17 ± 0.02 a0.19 ± 0.02 a
Free Fe oxides (g kg−1)6.87 ± 0.50 a,b6.11 ± 0.34 a,b7.45 ± 0.18 a7.54 ± 0.13 a6.26 ± 0.12 b
Note: Different lowercase letters within the same parameter indicate significant differences between treatments. C0: Unmanaged grassland; C3: managed grassland for 3 years; C10: managed grassland for 10 years; C30: managed grassland for 30 years; C50: managed grassland for 50 years. (p < 0.05).
Table
Table 2. Variations of soil biological parameters in managed grasslands with different managed years.
Table 2. Variations of soil biological parameters in managed grasslands with different managed years.
Soil Biological Parameter Managed Year
C0C3C10C30C50
Nematode (individuals/100 g dry soil)420.33 ± 26.80 a448.67 ± 7.90 a506.83 ± 17.78 a479.00 ± 23.82 a555.67 ± 39.89 a
Soil microbial biomass carbon (mg kg−1)1870.83 ± 177.26 a1639.64 ± 165.25 a,b966.88 ± 60.84 b983.34 ± 70.83 b858.12 ± 20.04 b
Soil microbial biomass nitrogen (mg kg−1)177.53 ± 22.30 a131.44 ± 25.91 a,b81.39 ± 6.56 a,b70.14 ± 6.89 b62.92 ± 4.78 b
Total PLFA (nmol g−1)43.15 ± 5.40 a23.11 ± 2.94 b23.55 ± 1.49 b25.02 ± 1.80 b53.21 ± 1.84 a
Bacteria (nmol g−1)32.39 ± 3.98 a17.43 ± 2.36 b17.53 ± 1.12 b18.05 ± 1.27 b39.30 ± 1.10 a
Fungi (nmol g−1)3.55 ± 0.62 b2.69 ± 0.13 b2.34 ± 0.19 b2.80 ± 0.22 b5.12 ± 0.38 a
Actinomycetes (nmol g−1)5.70 ± 0.69 a2.74 ± 0.27 b2.88 ± 0.26 b3.44 ± 0.29 b6.33 ± 0.16 a
Gram-negative bacteria(G−) (nmol g−1)14.24 ± 1.78 a6.26 ± 1.23 b4.84 ± 0.47 b4.98 ± 0.57 b12.93 ± 0.88 a
Gram-positive bacteria (G+) (nmol g−1)9.23 ± 1.11 b4.51 ± 0.64 c4.92 ± 0.32 c6.25 ± 0.45 c12.70 ± 0.41 a
Arbuscular mycorrhizal fungi (nmol g−1)1.50 ± 0.26 a,b0.69 ± 0.09 b0.80 ± 0.09 b0.73 ± 0.09 b2.46 ± 0.28 a
AMF hyphae (m g−1)1.33 ± 0.03 a0.99 ± 0.02 b0.99 ± 0.02 b0.90 ± 0.03 b0.63 ± 0.06 c
Urease (NH4+-N mg/ (100 g·24 h))21.56 ± 2.03 a,b22.85 ± 0.64 b21.70 ± 0.46 b23.23 ± 0.51 b26.10 ± 0.19 a
Alkal phosphates (phenol μg/(g·24 h))2283.83 ± 232.35 a,b2129.67 ± 44.94 b2082.17 ± 36.77 b2139.67 ± 61.30 a,b2390.50 ± 29.63 a
Sucrase (glucose mg/g·24 h)5.22 ± 0.39 b3.10 ± 0.43 c4.98 ± 0.27 b5.18 ± 0.37 b7.24 ± 0.24 a
Note: Different lowercase letters within the same parameter indicate significant differences between treatments. C0: Unmanaged grassland; C3: managed grassland for 3 years; C10: managed grassland for 10 years; C30: managed grassland for 30 years; C50: managed grassland for 50 years. (p < 0.05).
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Ren, C.; Liu, K.; Dou, P.; Li, J.; Wang, K. The Changes in Soil Microorganisms and Soil Chemical Properties Affect the Heterogeneity and Stability of Soil Aggregates before and after Grassland Conversion. Agriculture 2022, 12, 307. https://doi.org/10.3390/agriculture12020307

AMA Style

Ren C, Liu K, Dou P, Li J, Wang K. The Changes in Soil Microorganisms and Soil Chemical Properties Affect the Heterogeneity and Stability of Soil Aggregates before and after Grassland Conversion. Agriculture. 2022; 12(2):307. https://doi.org/10.3390/agriculture12020307

Chicago/Turabian Style

Ren, Cheng, Kesi Liu, Pengpeng Dou, Jiahuan Li, and Kun Wang. 2022. "The Changes in Soil Microorganisms and Soil Chemical Properties Affect the Heterogeneity and Stability of Soil Aggregates before and after Grassland Conversion" Agriculture 12, no. 2: 307. https://doi.org/10.3390/agriculture12020307

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