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Article

How to Improve the Benefits of Short-Term Fallow on Soil Physicochemical and Microbial Properties: A Case Study from the Yellow River Delta

by
Yaoben Lin
1,2,†,
Yuanbo Wang
3,†,
Xingjun Lv
3,
Shuangyan Yue
3,
Hongmei Liu
3,
Guangyu Li
4,* and
Jinghui Zhao
5
1
Shaanxi Key Laboratory of Land Consolidation, Chang’an University, Xi’an 710075, China
2
School of Law and Politics, Nanjing Tech University, Nanjing 211816, China
3
Observation and Research Station of Land Use Security in the Yellow River Delta, Ministry of Natural Resources (NMR), Shandong Provincial Territorial Spatial Ecological Restoration Center, Jinan 250014, China
4
Institute of Land and Urban-Rural Development, Zhejiang University of Finance and Economics, Hangzhou 310058, China
5
Hangzhou Yuanjie Space Technology Co., Ltd., Hangzhou 310030, China
*
Author to whom correspondence should be addressed.
†
These authors contributed equally to this work.
Land 2023, 12(7), 1426; https://doi.org/10.3390/land12071426
Submission received: 25 May 2023 / Revised: 10 July 2023 / Accepted: 15 July 2023 / Published: 16 July 2023
(This article belongs to the Special Issue Advances in Land Consolidation and Land Ecology)
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Abstract

:
Fallowing is regarded as an effective method for the self-recovery management of farmland and is generally used in cultivated land management. Studies have shown that long-term fallow has many ecological and environmental benefits. However, the long-term fallowing of farmland has also caused a decline in the grain production of farmland for a period of time. Short-term fallow can reduce the risk of food insecurity, but there are few studies on short-term fallow, especially on the comparation of different fallowing management methods and their relationship with soil microbial ecology. Our study has focused on seven treatments. Firstly, the traditional farming method was set as the control group. Native vegetation and crop-pasture vegetation were set as the fallowing vegetation. There were three irrigation–fertilization levels for each vegetation. The effects of the sampling times showed that the impact of fallow management on the soil properties became gradually stronger with time. The interactions between the sampling times and treatments showed a significant impact on organic carbon and total nitrogen. There was a significant impact of fallow management on the inorganic carbon accumulation and ammonia nitrogen consumption. Microbial biomass carbon was significantly increased by fallowing. Fallowing with irrigation could enhance the soil microbial nitrogen transformation. Some genera associated with assisting diseases were significantly increased by the native vegetation fallow and grass fallow with farmyard manure. The fallow with native vegetation showed more advantageous ecological benefits than the crop-pasture vegetation fallow. Although the crop-pasture vegetation followed the principle of ecological intensification, it failed to show better ecological benefits in the short fallow period. In irrigation management, the benefits of native vegetation and crop-pasture vegetation are similar. However, considering the lower cost of crop-pasture vegetation, crop-pasture vegetation fallow with irrigation could be a better choice. If it is difficult to implement conservation measures during the fallowing process, native vegetation fallowing without management may be the only fallowing choice.

1. Introduction

The amount of fertilizer used in China’s cultivated land has accounted for one-third of the world total, and the number of insecticides is 2.5 times greater than the world average level. A large number of pesticides and fertilizers will lead to the pollution of the soil and water environment, making the productivity of cultivated land reach a bottleneck [1]. In addition, it has been pointed out in the relevant research on the “balance of occupation and compensation” of cultivated land that the promotion of this policy in many provinces has failed to improve the potential sustainable production capacity of cultivated land, and has led to the loss of a large proportion of high-quality cultivated land in some areas [2]. Farming on low-quality and newly created farmland has brought many agroecosystem risks, such as soil erosion, nutrient loss, apoptosis of soil organisms, and biodiversity loss [3,4]. Therefore, focusing on the sustainable utilization of cultivated land capacity and food security, the country started to establish the “fallow rotation” system in 2016, and promoted the pilot development of related programs.
Prior to this, China’s experience of long-term fallow cultivated land indicated that local governments and farmers participating in long-term cultivated land fallowing projects, such as Grain for Green, used a large number of pesticides and fertilizers to improve the output of non-participating cultivated land in order to maintain the original level of grain production, which resulted in reduced cultivated land fertility and a decline in cultivated land quality [5,6,7]. Short-term fallow is different from seasonal fallow to some extent. Seasonal fallow refers to the rotation mode of less than a year or only a few months, which is often considered as part of the rotation, while short-term fallow refers to the fallowing mode of less than one year and up to five years, and is longer than seasonal fallow [8]. However, there are still some deficiencies in how to carry out the short-term fallowing of cultivated land, and there is a lack of comparative analysis between the different management methods of short-term fallow. In addition, with the gradual maturity of microbial community analysis methods, microbial community changes are more easily observed, and microorganisms can provide feedback on the cultivated land quality from multiple perspectives; thus, it is more feasible to explain the impact of short-term cultivated land management on the soil quality through microbial indicators [9,10]. However, in the short-term fallowing of cultivated land, there have been relatively few studies on the impact of short-term fallow based on the analysis of microbial properties.
Based on previous studies on fallow cultivated land, this study shows that cultivated land conservation means can be mainly divided into vegetation construction, water, and fertilizer management [11,12,13,14]. Based on the commonly used vegetation types in local areas and combined with the mutualism and symbiosis of vegetation roots, different types of fallowing vegetation were constructed in our study. In addition, considering the low quality of cultivated land itself, artificial management means may be needed to intervene and protect it. We set up a variety of different water and fertilizer management methods, combined with the vegetation types, to construct a variety of short-term fallowing management models. The characteristics of the microbial community were analyzed using high-throughput sequencing technology, and the effects of different short-term fallowing management modes on the microbial community and soil physicochemical properties were determined.

2. Materials and Methods

2.1. Study Area and Experimental Design

The study area is located near the Field Scientific Observation Research base (E 117°43′, N 37°48′, elevation 5 m.a.s.l). The precipitation ranges between 0 and 421.8 mm, with an average annual precipitation of 55.3 mm in 10 years. The average temperature is 13.9 °C, with variations ranging between −6.1 and 28.4 °C. The soil texture is silty loam (3% clay, 78% silt), belonging to the Yellow River alluvial soil, which can be classified as typical saline-alkali alluvial soil (alluvial soil, FAO). According to the data of the local agricultural agency, there has been more than 5 years of planting sorghum in the study area, and the planting area has declined. According to a survey by the agricultural agency, 45% of the cultivated land has been abandoned, changed to other crops, or turned into a water area. The field experiment started in April 2016. The soil texture in the experimental area was relatively uniform and the terrain was relatively flat. The soil background value was provided by the local agricultural department. The pH value was 8.43, the electrical conductivity was 1.8 μS cm−1, the soil total nitrogen content was 0.62 g kg−1, the soil organic carbon content was 8.39 g kg−1, and the available nitrogen was 24.59 mg kg−1. The available potassium was 0.11 mg kg−1, and the available phosphorus was 8.51 mg kg−1.
In the study area, we set up 6 kinds of fallowing management methods and a control groups, comprising a total of 7 treatment methods. There were 3 parallel plots for each treatment. The area of each plot was 5 × 6 m, and the plots were randomly distributed. The control group maintained the original tillage practices; that is, we continued to control the weeds through traditional tillage and herbicide, and applied fertilizer to grow sorghum in pursuit of a higher agricultural yield. The main difference between the control group and the fallow group was the difference in the benefit objectives pursued. The main purpose of the control group was to pursue the grain yield, while the main purpose of the fallow group was to improve the ecological benefits of the cultivated land. In this study, three different types of water and fertilizer management were set up for the cultivation of cultivated land, namely, no management, irrigation management and farmyard fertilizer management, and a variety of fallowing methods were constructed by combining different vegetation types. Firstly, native vegetation can be used for fallow cultivated land; that is, native vegetation fallow. Secondly, it takes into account the compensation of farmers’ economic income and the good ecological benefits of butterfly vegetation during the fallow period [15]. Therefore, the mixed sowing of alfalfa (Medicago sativa L.) and corn (Zea mays L.) was selected to construct the management mode of grain and grass fallow. Each treatment was as follows:
  • CK, traditional tillage (deep ploughing), planting sorghum, and applying nitrogen, phosphorus, and potassium fertilizer (N:P:K 3:1:3) and urea (46.2% of total nitrogen content), a total of 330 kg ha−1.
  • F-noman, no fertilizer input, no tillage (artificial weeding without tillage), and spontaneous vegetation fallow, later referred to as natural fallow.
  • M-noman, no fertilizer input, only minimal tillage (artificial weeding), mixed sowing of corn and alfalfa, referred to as grain and grass fallow.
  • F-irrig, the vegetation is naturally growing vegetation, no fertilizer input, no tillage, irrigation, irrigation to about 60% soil water content.
  • M-irrig, the vegetation was mixed with corn and alfalfa, and there was no fertilizer input. Only minimal tillage (artificial weeding) was carried out, and the soil water content was about 60%.
  • F-ferti, no tillage, natural fallow combined with the application of decomposed cow manure fertilizer (organic carbon content 400 g kg−1, total nitrogen 7.0 g kg−1, total phosphorus content 11.5 g kg−1, and total potassium content 9.8 g kg−1), a total amount of 1500 kg ha−1.
  • M-ferti, minimum tillage, grain and grass fallow (vegetation type corn and alfalfa) combined with decomposed cow manure fertilizer, a total amount of 1500 kg ha−1.

2.2. Soil Sampling

In this study, soil sample collection was carried out three times, and the first sample was collected in June 2016. The second and third samples were collected in August and October 2016, respectively. Based on the principle of “S”-type sampling, a ring-knife sampler was used to collect 6 samples from the topsoil (0~20 cm) in each sample plot, and the 6 samples were mixed into one soil sample. Each sample was passed through a soil screen of less than 2 mm to remove residual roots and rocks. Then, each soil sample was divided into two parts: one stored in an ultra-low temperature freezer at −20 °C for DNA sequencing and one stored in a refrigerator at 4 °C for microbial biomass, carbon, nitrogen, and soil physical and chemical properties.

2.3. Determination of Soil Physicochemical Properties and Microbial Biomass

Soil pH values were obtained by measuring the soil solution with a glass electrode (soil: water = 1:2.5). Both the soil organic carbon (SOC) and inorganic carbon (IC) content were determined using air-dried and fine soil samples; each sample was weighed 10 mg into a small spoon, and phosphoric acid (25% w/w) was added for IC determination. The total carbon was determined using the combustion method, and the SOC content was obtained. This process was completed using a carbon and nitrogen analyzer (TOC-L analyzer and SSM-5000 A unit, Shimadsu, Japan). Total nitrogen (TN) was determined using the Kjeldahl method [16]. The C/N ratio (C/N) was calculated using the SOC and TN. The soil ammonium nitrogen content (AN) was determined using a continuous flow analyzer (Skalar San ++ continuous Flow Injection analyzer, Breda, The Netherlands).
Soil microbial biomass carbon (MBC) and microbial biomass nitrogen (MBN) were determined using the fumigation-extraction method. For each plot, 6 subsamples and 3 blanks (each consisting of 10.0 g of fresh soil, with 3 being blank controls) were fumigated with ethanol-free chloroform in an evacuated extractor at 25 °C for 24 h. The remaining samples were treated as controls. We extracted fumigated and unfumigated soil with 40 mL 0.5 M potassium sulfate (soil: extractor = 1:4), which was oscillated on a reciprocating oscillator for 1 h. We strained the extracts using Whatman No.42 filter paper with a 7 cm diameter and refrigerated them at −15 °C prior to analysis. The total organic carbon and nitrogen in the extracts was measured using the Multi N/C 3000 analyzer (Elementar Analysensysteme GmbH, Langen Selbod, Germany) [17].
MBC is calculated as follows: MBC = EC/kEC; where EC = (total organic carbon extracted from fumigated soil) − (total organic carbon extracted from non-fumigated soil) and kEC = 0.3 [11]. MBN is calculated as follows: MBN = EN/kEN; where EN = (total nitrogen from fumigated soil) − (total nitrogen from non-fumigated soil) and kEN = 0.45 [18].

2.4. 16SrDNA Sequence Analysis of Soil Microbial Communities

A total of 0.5 g was taken from each soil sample and the total genomic DNA of the soil was extracted using the PowerSoil Total DNA Isolation Kit (MoBio Labs, Solana Beach, CA, USA) according to the manufacturer’s instructions. The concentration and quality of the DNA were determined using a NanoDrop spectrophotometer. The extracted DNA was then diluted to 10 ng μL−1 and stored at minus 20 °C for downstream analysis.
Primer pairs included 515F (5′-GTGCCAGCMGCCGCGG-3′) and the reverse primer 907R (5′-CCGTCAATTCMTTTRAGTT-3′) with a unique 6nt barcode, which was used to amplify the hypervariable V4 region of the 16S rRNA gene [19]. The PCR mixture (25 μL) consisted of 1 × PCR buffer, 1.5 mM magnesium chloride, 0.4 mM of each deoxyriboside triphosphate, 1.0 mM of each primer, 0.5 U of Ex Taq (TaKaRa, Dalian, China), and 10 ng of soil DNA. The PCR amplification procedure consisted of initial denaturation at 94 °C for 3 min, followed by 30 cycles at 94 °C for 40 s, 56 °C for 60 s, and 72 °C for 60 s, and finally extended to 72 °C for 10 min. The PCR products were combined three times for each sample and loaded into 1.0% agar-gel electrophoresis. Bands with the correct size were cut and purified using the TaKaRa MiniBEST Agar-gel DNA extraction kit (TaKaRa, Dalian, China) and quantified with Nanodrop. All samples were combined together with equal molar quantities for each sample. We prepared sequenced samples using the TruSeq DNA kit according to the manufacturer’s instructions. As described in the Illumina library preparation protocol, the purified library was diluted, denatured, rediluted, mixed with PhiX (equal to 30% of the final DNA volume), and then applied to the Illumina Miseq system as described in the manufacturer’s manual for sequencing with the Reagent Kit v2 2 × 250 bp.
Microbial Ecology (QIIME) channels were used to process the original sequence obtained through Illumina sequencing [20]. We assembled and read paired ends using FLASH [21]. Readings with quality scores below 20, undefined bases, and incorrect primers were discarded prior to clustering. The resulting high-quality sequences were then clustered into operational taxonomic units with 97% similarity using the UPARSE algorithm [22]. At the same time, chimeras were examined and eliminated during clustering. The classification of representative sequences from individual OTUs was performed through the rdp classifier [23]. In order to compare the relative differences between the samples, a subset of 8260 sequences was randomly selected for each sample for downstream analysis.

2.5. Statistical Analysis

We calculated the mean and standard deviation for the three replicates. Analysis of variance, multivariate statistical analysis, hierarchical cluster analysis, and Spearman correlation analysis were performed using the SPSS software package (version 24.0) and R language [24]. The influence of the sampling season and management effect was determined through repeated measure analysis of variance. Differences between the management of the fallow and control groups for each season were determined using one-way ANOVA. After one-way ANOVA, Duncan’s multiple comparative analysis was used to test the significance of the parameters at p < 0.05. Based on the Bray–Curtis distance, a permutation multivariate analysis of variance (PERMANOVA) was performed. Principal axis analysis (PCoA) and PERMANOVA were conducted for the bacteria with inter-group differences in the late fallow period. Based on the Bray–Curtis distance, hierarchical clustering was employed to detect samples clustering based on selected genera, and distance-based redundancy analysis (db-RDA) was performed to determine the soil factors affecting the microbial community through the positive selection of all variables. Then, by analyzing the correlation between soil factors and each different bacteria genus, the correlation between the bacteria genus and soil factors was determined.

3. Results

3.1. Effects of Seasons and Management Methods on Soil Physicochemical Properties

The results of the repeated measurement analysis of variance showed that the seasons had significant effects on the pH, organic carbon, carbon–nitrogen ratio, and ammonium nitrogen (Table 1). The pH value was also significantly affected by the management effect, indicating that the management effect was consistent in the three seasons. Following the Duncan multiple comparison, the pH value of the control group was significantly lower than that of the three fallowing methods of native vegetation management (p < 0.05). The organic carbon and carbon–nitrogen ratio showed that the organic carbon content accounted for a higher proportion in spring, and gradually decreased with the seasonal content. However, the total nitrogen content and C/N ratio showed significant differences in different seasons and were affected by the management effects. The change in the total nitrogen content in M-noman was obvious between the early and late fallow periods, and the total nitrogen content in the late fallow period was significantly lower than that in F-noman (p < 0.05). The difference in the levels of ammonium nitrogen between seasons was significant, and its content began to decline significantly in summer.
The influence of the management effects in each season was analyzed through one-way analysis of variance, and only the total nitrogen and C/N ratio in the early fallow period showed differences between the groups (Figure 1). However, in the late fallow period, the soil total nitrogen, C/N ratio, inorganic carbon, and ammonium nitrogen showed significant inter-group differences. No significant difference between the groups was found in terms of the organic carbon in this study. Considering the strong artificial intervention in the early stage of fallowing and the unstable soil environment, the changes in the soil properties in the later stage are discussed. The results of the C/N ratio and total N have been described previously, but both showed no significant difference between the fallowing management and control groups. The results of the inorganic carbon showed that the inorganic carbon content in CK was significantly lower than that in the unmanaged F-noman and M-noman (p < 0.05). The content of ammonium nitrogen showed that F-irrig and M-irrig under irrigation management were significantly lower than those under the other treatments (p < 0.05).

3.2. Effects of Seasons and Management Methods on Soil Microbial Biomass

There were significant differences in the content of soil microbial biomass carbon and nitrogen between different seasons (Table 2). The microbial biomass carbon content was high in the early fallow period and declined in some treatments as the fallow period was extended. However, considering that this was significantly influenced by the interaction of the season and management method (p < 0.05), the significance indicates that the microbial biomass carbon was affected differently by the management methods in different seasons; that is, there were seasonal variations in the differences between the groups. The results of the microbial biomass nitrogen were similar to those of microbial biomass carbon, as it was also affected by this interaction, and the differences between the groups varied in different seasons. However, the content of microbial biomass nitrogen was low in spring, which then showed a significant increasing trend. The C/N ratio of the microbial biomass was only significantly affected by the seasons (p < 0.05).
In the early fallow period, the differences between the groups in terms of the soil microbial biomass carbon were not significant; however, from summer onward, differences between the groups began to appear (Figure 2). The results of the microbial biomass carbon in the middle and late fallow periods showed that the microbial biomass carbon content of CK in the control group was significantly lower than that of all the fallowing treatments. The results of the late fallowing were similar to those of the middle fallowing; thus, the results of the late fallowing could be mainly analyzed. Compared with the other treatments, the content of microbial biomass carbon in F-irrig and M-irrig under irrigation was higher, especially in M-irrig, where it was significantly higher than that in F-noman and M-noman without management (p < 0.05). There were significant inter-group differences in the microbial biomass nitrogen in spring, mainly as follows: M-noman and M-irrig were significantly lower than M-ferti (p < 0.05), but, in the middle fallow period, the microbial biomass nitrogen content in M-irrig gradually increased, while that in M-ferti decreased, and that in CK was significantly lower than that in F-irrig, M-irrig, F-ferti, and M-ferti (p < 0.05). In the later stage of fallowing, the difference in the microbial nitrogen between groups changed again; the difference between M-ferti and CK became insignificant, but the difference between F-ferti and CK became larger. The C/N ratio of the microbial biomass showed that the ratio of F-ferti was always low in the middle and late fallow periods, and the content of microbial biomass N was higher than that of microbial biomass C.

3.3. Effects of Seasons and Different Treatments on Soil Microbial Communities

The microbial community structure was significantly different in different seasons (Table 3), and the interaction effect showed that the management effect had different effects on the microbial community structure with the seasonal changes (p < 0.05). However, the independent analysis of the effects of the management effects on different seasons showed that the effects of the management effects on the microbial community structure were not significant. As can be seen from the variation of statistic F, although the effect of the management effect is not significant in autumn, its effect tends to gradually increase. Therefore, the analysis of the microbial community in the late fallow period is emphasized.

3.4. Relationship between Soil Properties and Microbial Communities in Autumn

The analysis of the microbial genera with significant differences between the groups in the late fallow period showed that the management effect had a significant influence (Figure 3). The results of the PCoA showed that F-noman and M-noman without management were concentrated in the third and fourth quadrants, while those in the control group were in the second and third quadrants. In the control group, CK was significantly different from F-irrig and M-irrig of irrigation management, F-noman and M-noman without management, and M-ferti of farmhouse fertilizer management, but the difference between CK and F-ferti was not significant. In addition, the results of the db-RDA and hierarchical clustering were also similar to those of the PCoA (Figure 4a,b). Further, the difference between the control group and F-ferti was insignificant.
In the late fallow period, inorganic carbon and microbial biomass carbon had significant effects on the microbial community (p < 0.05). Among them, CK in the control group showed a negative relationship with soil inorganic carbon and microbial biomass carbon (Figure 4a). F-noman and M-noman without management were more closely related to inorganic carbon, while F-irrig, M-irrig, F-ferti, and M-ferti with management were more closely related to microbial biomass carbon.
Based on the results of the relative abundance and variance analysis of different bacteria genera (Figure 4b), the higher species included Blastococcus, Chthonomonas/Armatimonadetes gp3, Algoriphagus, WPS-2 genera incertae sedis, Aquabacterium, Pseudorhodoferax, and Steroidobacter (relative abundance > 0.1%). According to the single factor variance analysis, the proportion of Blastococcus in CK was significantly lower than that in F-ferti and M-ferti under farm manure management (p < 0.05). The bacterial Chthonomonas/Armatimonadetes gp3 showed that CK was significantly lower than that without management in the F-noman and M-noman (p < 0.05). The relative abundance of Algoriphagus in CK was higher than that in F-noman and M-noman without management and F-irrig and M-irrig under irrigation management (p < 0.05). The WPS-2 genera incertae sedis in F-noman was significantly higher than that in CK (p < 0.05). The proportion of Aquabacterium in F-ferti and M-noman was significantly higher than that in CK (p < 0.05). The proportion of Pseudorhodoferax in F-ferti, F-irrig, and M-irrig was significantly higher than that in CK (p < 0.05). The Steroidobacter content in CK was significantly higher than that in F-noman, F-irrig, M-irrig, and M-ferti (p < 0.05). In the late fallow period, the Spearman correlation analysis showed (Figure 4c) that there was a significant positive correlation between organic carbon and total nitrogen, and also a significant positive correlation between microbial biomass carbon and nitrogen (p < 0.05). There was a significant positive correlation between inorganic carbon and microbial biomass C/N, while there was a significant negative correlation between ammonium nitrogen and microbial biomass C (p < 0.05). Bacterial Chthonomonas/Armatimonadetes gp3 and inorganic carbon and microbial biomass carbon and nitrogen present a significant positive correlation (p < 0.05). Algoriphagus had a significant negative correlation with inorganic carbon (p < 0.05). The bacterium Pseudorhodoferax had a significant positive correlation with microbial biomass nitrogen, and a significant negative correlation with ammonium nitrogen (p < 0.05). Steroidobacter was significantly negatively correlated with microbial biomass C and the microbial biomass C/N ratio (p < 0.05) (see Supplementary Materials).

4. Discussion

Compared with previous studies, our study has improved the management practices of fallowing, with a strong comparison of the effects between different fallowing management methods in saline-alkali soil. The study supports the results from previous studies that fallowing cultivated land does not significantly affect the soil organic carbon and microbial community structure in the short term [25]. However, there are some differences in the results for different seasons.

4.1. Soil Carbon and Nitrogen Content Were Affected by Fallowing Management Methods

This study found significant effects on the soil inorganic carbon, ammonium nitrogen, microbial carbon and nitrogen, and some bacteria in the later fallow period, as a result of the intervention of the management measures. The results showed that the soil inorganic carbon was relatively stable in the non-management fallowing condition, compared with the other management practices. This is different from a long-term study (over 5 years) that showed that inorganic carbon decreased during the conversion of farmland to grassland [26]. However, the phenomenon occurred in high-quality farmland because reasonable agricultural management could improve the microbial biomass, which increased carbon mineralization [26]. Our results also showed a positive correlation between inorganic carbon and the microbial biomass C/N ratio, whereas the overtilling in CK caused a lower microbial biomass carbon and inorganic carbon content than fallowing. At the same time, the accumulation of inorganic carbon is usually related to the accumulation of calcium and magnesium ions in alkaline soil [27]. This indicates that soil alkali metal ions may be more easily absorbed by vegetation during irrigation and fertilization than with no management, resulting in a low inorganic carbon content in F-irrig, M-irrig, F-ferti, and M-ferti. Therefore, the accumulation of inorganic carbon could be related to the improvement in the microbial conversion efficiency of carbon and the slow nutrient consumption by vegetation. The content of ammonium nitrogen showed a significant declining trend in irrigation, while microbial biomass carbon showed a negative correlation with it. Considering the significant positive correlation between microbial biomass nitrogen and microbial biomass carbon, the decrease in ammonium nitrogen caused by irrigation may be caused by two aspects: runoff caused by irrigation, which leads to the dissolution and loss of part of the ammonium nitrogen, or the proliferation of soil microorganisms, which leads to the consumption of ammonium nitrogen and the change in the nitrogen form [28]. Therefore, fallow management could restore low-quality farmland, and the nutrient consumption caused by the optimization measures should be considered.

4.2. Microbial Properties Changes Caused by Fallow Management

In terms of microbial biomass carbon and nitrogen, our results also proved previous claims that short-term fallowing can significantly increase soil microbial biomass carbon, which is mainly attributable to the protective effect of the reduced tillage intensity on soil microbial proliferation [29]. At the same time, our study found that fallowing with irrigation could remarkably promote microbial biomass C and N. It has explained that irrigation decreases the ammonium nitrogen content, because the irrigation promoted the utilization of nutrients by microorganisms [30]. It should be noted that native vegetation fallow with manure also increased microbial biomass N because plant diversity could promote nutrient-use efficiency [31]. In existing studies, this management method is also considered to be a relatively effective fallowing management method; however, considering its high cost, there may be some resistance in its actual implementation [13,25]. The analysis results of the different bacteria genera between the groups in the late fallow period showed that F-irrig, M-irrig, and M-ferti had the most obvious differences from the control group. The bacteria of high proportions were analyzed to determine the ecological benefits of the bacteria in soil. Blastococcus has the ability to resist soil-borne diseases; therefore, management with farm manure can improve the resistance of soil to soil-borne diseases [32,33]. Bacterial Chthonomonas/Armatimonadetes gp3 also has the ability to resist soil-borne disease, improving soil resistance and promoting soil nitrogen nitrification [34,35]. Algoriphagus can promote nitrate reduction and the decomposition of organic matter; thus, it is known that in the absence of external nutrient input, this bacterium is subject to certain inhibition [36,37]. The bacteria genera WPS-2 genera incertae sedis only show sensitivity to heavy-metal lead pollution and a negative correlation with the pH, which indicates that in the completely unmanaged native vegetation method, the soil is subject to minimal external intervention and the pH tends to decrease [38]. Aquabacterium is associated with the decomposition of organic pollutants, indicating that the decomposition ability of organic pollutants has been enhanced in unmanaged grain and grass vegetation and non-managed native vegetation of farm manure [39]. The bacterium Pseudorhodoferax has the effect of inhibiting nitrate reduction and promoting the growth of surface vegetation. Combined with the relationship between the bacterium and microbial nitrogen, it can be seen that the increase in microbial nitrogen can inhibit nitrogen consumption and promote the growth of surface vegetation [40,41]. The bacterium Steroidobacter is closely related to denitrification, and it is negatively correlated with the microbial biomass carbon content and the microbial biomass carbon-nitrogen ratio, indicating that the control group is more likely to cause the emergence of denitrification, and the microbial biomass carbon content is low [13,42].

4.3. Implications for Fallow Management

Based on the above research results, it can be seen that the benefits generated in different fallow management methods are different, and the specific performance can be summarized as follows:
  • Unmanaged native vegetation fallow (F-noman) improved the inorganic carbon storage, soil nitrification, and disease resistance, and adjusted the soil pH to inhibit denitrification, nitrate reduction, and organic decomposition.
  • Unmanaged grain and grass fallow (M-noman) also improved the inorganic carbon content, soil nitrification, and disease resistance, and enhanced the decomposition ability of organic pollutants, inhibiting nitrate reduction and organic decomposition. However, this management method resulted in a reduction in the total nitrogen content and an increase in the carbon–nitrogen ratio to a certain extent.
  • Native vegetation fallow under irrigation management (F-irrig) reduced the content of ammonium nitrogen, inhibited nitrate reduction, denitrification, and organic decomposition, increased the content of microbial nitrogen, and promoted the growth of surface vegetation.
  • Crop and pasture vegetation fallow under irrigation management (M-irrig) had the same effect as F-irrig, which reduced the content of ammonium nitrogen, inhibited nitrate reduction, denitrification, and organic decomposition, increased the content of microbial nitrogen, and promoted the growth of surface vegetation.
  • Native vegetation fallow under the management of farm manure (F-ferti) improved the microbial biomass nitrogen, the ability to resist soil-borne diseases, the decomposition of organic pollutants, and the ability to promote vegetation growth. In terms of nitrate reduction, the effects of different bacteria were cancelled out, so the effect was not considered.
  • Crop and pasture vegetation fallow managed using farmyard manure (M-ferti) only improved the soil’s ability to resist soil-borne diseases and inhibited denitrification, but the other effects were not significant.

5. Conclusions

This study constructed different short-term fallow management measures through vegetation, water, and fertilizer management, and compared them with traditional tillage. The results showed that short-term fallow could effectively increase the microbial biomass carbon content. Native vegetation showed more advantageous ecological benefits in both the non-management and manure management methods, while grain and grass vegetation did not show better ecological benefits despite complying with the requirements of ecological intensive construction. In irrigation management, the benefits of native vegetation and grain and grass vegetation were similar. However, considering that grain and grass vegetation has greater advantages in terms of cost control, using crop and grass vegetation under irrigation management for short-term fallow according to the actual needs should be considered. If it is difficult to implement the corresponding conservation measures during the fallowing process, relying only on native vegetation fallow should be considered. Therefore, the choice of a short-term cultivated land fallow management mode should be based on the actual demand. However, the study time was relatively short. In addition, alfalfa is perennial vegetation; therefore, the ecological benefits of grain and grass vegetation may not be represented. In a follow-up study, we will continue to strengthen the monitoring of this vegetation type to further determine its ecological benefits.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/land12071426/s1, Figure S1: Relative abundance of bacteria at the phylum level.

Author Contributions

Conceptualization, G.L. and Y.L.; methodology, G.L. and Y.L.; software, Y.L. and Y.W.; validation, Y.W., G.L. and Y.L.; formal analysis, Y.W.; investigation, Y.W.; resources, Y.W.; data curation, G.L. and J.Z.; writing—original draft preparation, Y.L. and Y.W.; writing—review and editing, G.L.; visualization, Y.W., X.L., S.Y. and H.L.; supervision, Y.L.; project administration, Y.L.; funding acquisition, Y.L. and G.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 number 42201288, the Observation and Research Station of Land Use Security in the Yellow River Delta, MNR, grant number YWZ-202204, and the Fundamental Research Funds for the Central Universities, CHD, grant number 300102353504.

Data Availability Statement

The data presented in this study are available on request from the corresponding author. The data are not publicly available due to requirements of government non-disclosure agreement.

Conflicts of Interest

The authors declare no conflict of interest.

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Land 12 01426 g001 550
Figure 1. Results of one-way ANOVA of soil physicochemical properties. Values within each subplot followed by the same letter are not significantly different at p < 0.05.
Figure 1. Results of one-way ANOVA of soil physicochemical properties. Values within each subplot followed by the same letter are not significantly different at p < 0.05.
Land 12 01426 g001
Land 12 01426 g002 550
Figure 2. Results of one-way ANOVA of soil microbial properties. Values within each subplot followed by the same letter are not significantly different at p < 0.05.
Figure 2. Results of one-way ANOVA of soil microbial properties. Values within each subplot followed by the same letter are not significantly different at p < 0.05.
Land 12 01426 g002
Land 12 01426 g003 550
Figure 3. Results of PCoA of genera that present significant differences among groups in Autumn.
Figure 3. Results of PCoA of genera that present significant differences among groups in Autumn.
Land 12 01426 g003
Land 12 01426 g004 550
Figure 4. Relationship between soil factors and specific genera based on db-RDA, * p < 0.05, *** p < 0.001 (a); The relative abundance of genera and hierarchical clustering (b); relationship of soil factors and the relationship between soil factors and each genus based on Spearman rank correlation analysis, only showed p < 0.05 (c).
Figure 4. Relationship between soil factors and specific genera based on db-RDA, * p < 0.05, *** p < 0.001 (a); The relative abundance of genera and hierarchical clustering (b); relationship of soil factors and the relationship between soil factors and each genus based on Spearman rank correlation analysis, only showed p < 0.05 (c).
Land 12 01426 g004
Table
Table 1. Results of repeated measures ANOVA of soil physicochemical properties.
Table 1. Results of repeated measures ANOVA of soil physicochemical properties.
Soil Physicochemical PropertiesSample Times’ EffectsTreatments’ EffectsThe Interactions
pH53.011 ***4.588 **1.614
SOC (g kg−1)24.190 ***0.5201.577
Total N (g kg−1)3.7590.5345.311 ***
C/N73.854 ***1.4243.983 ***
Inorganic C (g kg−1)0.9942.1290.485
Ammonium N (mg kg−1)145.253 ***2.5590.943
Note: The values in the table are F statistics; ** p < 0.01, *** p < 0.001.
Table
Table 2. The results of repeated measures ANOVA of soil microbial properties.
Table 2. The results of repeated measures ANOVA of soil microbial properties.
Microbial PropertiesSample Times’ EffectsTreatments’ EffectsInteractions
Microbial biomass C185.161 ***4.302 *6.365 ***
Microbial biomass N346.459 ***7.535 ***6.554 ***
Microbial biomass C/N198.435 ***2.0771.950
Note: The values in the table are F statistics; * p < 0.05, *** p < 0.001.
Table
Table 3. Results of PERMANOVA of soil microbial community structure.
Table 3. Results of PERMANOVA of soil microbial community structure.
FactorsF-Statisticsp Values
Sample times effects12.7820.001
Treatments effects0.7310.575
Interactions12.1430.001
Spring
Treatments effects0.8240.553
Summer
Treatments effects1.1850.272
Autumn
Treatments effects1.1960.245
Note: The significance values less than 0.05 are highlighted in bold.
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Lin, Y.; Wang, Y.; Lv, X.; Yue, S.; Liu, H.; Li, G.; Zhao, J. How to Improve the Benefits of Short-Term Fallow on Soil Physicochemical and Microbial Properties: A Case Study from the Yellow River Delta. Land 2023, 12, 1426. https://doi.org/10.3390/land12071426

AMA Style

Lin Y, Wang Y, Lv X, Yue S, Liu H, Li G, Zhao J. How to Improve the Benefits of Short-Term Fallow on Soil Physicochemical and Microbial Properties: A Case Study from the Yellow River Delta. Land. 2023; 12(7):1426. https://doi.org/10.3390/land12071426

Chicago/Turabian Style

Lin, Yaoben, Yuanbo Wang, Xingjun Lv, Shuangyan Yue, Hongmei Liu, Guangyu Li, and Jinghui Zhao. 2023. "How to Improve the Benefits of Short-Term Fallow on Soil Physicochemical and Microbial Properties: A Case Study from the Yellow River Delta" Land 12, no. 7: 1426. https://doi.org/10.3390/land12071426

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