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Article

Changes in Soil Microbial Community along a Chronosequence of Perennial Mugwort Cropping in Northern China Plain

by
Furong Tian
1,
Zhenxing Zhou
1,2,3,*,
Xuefei Wang
1,
Kunpeng Zhang
1,2 and
Shijie Han
3
1
School of Biological and Food Engineering, Anyang Institute of Technology, Anyang 455000, China
2
Taihang Mountain Forest Pests Observation and Research Station of Henan Province, Linzhou 456550, China
3
International Joint Research Laboratory for Global Change Ecology, School of Life Sciences, Henan University, Kaifeng 475004, China
*
Author to whom correspondence should be addressed.
Agronomy 2022, 12(7), 1568; https://doi.org/10.3390/agronomy12071568
Submission received: 28 May 2022 / Revised: 27 June 2022 / Accepted: 28 June 2022 / Published: 29 June 2022
(This article belongs to the Special Issue Advances in PGPR (Plant Growth-Promoting Rhizobacteria))
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Abstract

:
Perennial cropping plays a vital role in regulating soil carbon sequestration and thus mitigating climate change. However, how perennial cropping affects the soil microbial community remains elusive. Using a field investigation, this study was conducted to examine the effects of mugwort cropping along a chronosequence (that is, wheat–maize rotation, 3-year, 6-year, and 20-year mugwort cropping) on a soil microbial community in temperate regions of Northern China. The results showed that the highest total, actinomycete, and fungi phospholipid fatty acids (PLFAs) were found in the 3-year mugwort cropping soils. By contrast, all PLFAs of microbial groups were lowest in the 20-year mugwort cropping soils. Network complexity of the soil microbial community under each of the three durations of mugwort cropping was greater than that under the wheat–maize rotation. Changes in total nitrogen and phosphorus content as well as the ratio of ammonium nitrogen to nitrate nitrogen primarily explained the variations in soil microbial community along the mugwort cropping chronosequence. Our observations highlight the contrasting responses of soil microbial community to short-term and long-term mugwort cropping compared with conventional rotations and would have critical implications for sustainable agricultural management under perennial cropping in temperate regions.

1. Introduction

Soil microorganisms play critical roles in regulating key and fundamental ecosystem processes, such as decomposition of organic matter, nutrient mineralization and cycling, as well as plant nutrient uptake and growth [1,2,3]. Evidence has shown that land-use types/intensities could have vital impacts on soil microbes [4,5,6,7]. For example, conversion of grasslands to arable fields can decrease fungal diversity, which could result in loss of the microbial genetic resources and thus reduction in soil fertility [8]. In addition, compared to natural ecosystems, croplands have lower bacterial diversity, consequently with regulation of carbon dioxide efflux from soil of agro-pastoral ecotone [7]. It has been well documented that perennial cropping has been demonstrated to increase soil carbon sequestration and mitigate climate change [9,10,11]. Perennial cropping can increase soil microbial biomass [12,13]. Compared to annual crops, perennial crops could enhance soil microbial community richness in a South European agricultural area [14]. However, the underlying mechanisms associated with the effects of perennial cropping on soil microbial community structure and composition remain elusive, especially at the broader and long-term scales.
Increasing evidence has accumulated and highlighted the critical role of nutrient availability on soil microbial communities under different land-use types [15,16,17]. For instance, sufficient nutrient availability could reduce soil microbial diversity in cropland [15,18]. By exacerbating soil acidification or carbon limitation, high nitrogen supply can also decrease soil microbial biomass and fungi-to-bacteria ratio in agricultural and natural ecosystems [16,19]. However, the impacts of nutrient supply on soil microbial communities may change with the background nutrient status in ecosystems. Under high ambient nutrient availability, nitrogen enrichment decreases soil fungal richness, whereas increases it under low ambient nutrient availability [20]. The finding indicates that responses of the soil microbial community to nutrient availability may be nonlinear along a nutrient gradient [21,22]. As another important nutrient for microbes, soil phosphorus availability could also mediate the abundance and diversity of arbuscular mycorrhizal fungi (AMF) and their symbiotic function in cropping systems [23,24,25]. In addition to nutrient availability, soil nutrient types (such as ammonium nitrogen (NH4+-N) vs. nitrate-nitrogen (NO3−-N)) may also have divergent impacts on soil microbial communities. For example, soil Gram-positive and negative bacterial biomass is regulated by soil NH4+-N and NO3−-N, respectively, and total microbial biomass is affected by NH4+-N rather than NO3−-N in a forest ecosystem [26]. By contrast, soil microbes prefer to use NO3−-N in agricultural systems [27].
Low soil pH induced by nitrogen enrichment has also been demonstrated to decrease soil microbial growth and thus microbial biomass [28]. Specifically, most Acidobacteria are acidophilic bacteria and their abundances rely on soil pH, indicating that changes in soil pH may select some microbial taxa [29]. This can lead to shifts in soil microbial community composition in agro-ecosystems [30,31,32]. As an important cropping type, perennial cropping could have impacts on the above factors [10,11,33] and thus have the potential to affect soil microbial community structure and composition. However, direct experimental evidence on the relative importance of various soil properties to changes in soil microbial community along a chronosequence of perennial cropping is scarce. Moreover, long-term continuous perennial cropping may not always benefit soil health due to continuous cropping obstacles [34,35,36]. Therefore, exploration of the response of the soil microbial community to short- and long-term perennial cropping is urgently needed, which is vital for the development of sustainable agricultural production.
As an important perennial medicinal plant, the demand for mugwort (Artemisia argyi) is increasing in China due to its medicinal value, and the cropping area has been increasing in recent years, especially in Henan Province, a dominant agricultural region of North China Plain. There is reduced tillage during mugwort cropping compared with conventional cropping. However, to the best of our knowledge, few studies have been conducted to explore the effects and underlying mechanisms of spatio-chronological perennial mugwort cropping on soil microbial communities, which limits our ability to better understand and develop sustainable agricultural under perennial cropping. In this study, a chronosequence (0, 3, 6, and 20 years) of perennial mugwort cropping was selected in the Northern China Plain to examine the two scientific questions: (1) How the perennial mugwort cropping affects soil microbial biomass and composition? (2) Which factors regulate soil microbial biomass and composition under the perennial mugwort cropping chronosequence?

2. Material and Methods

2.1. Site Description and Sample Collection

This study was conducted in Tangyin County (35°45′–36°01′ N, 114°13′–114°42′ E), Anyang, Henan, one of the original locations of mugwort, a genuine herb. This region has a warm temperate continental monsoon climate, with long-term mean annual temperature and precipitation of 13.4 °C and 582.0 mm, respectively. The soil is classified as cinnamon soil according to the Chinese soil classification system. The surface soil contained organic matter and total nitrogen (N) contents of 16.7 and 1.07 mg/g, respectively. With the development of the traditional Chinese medicine industry, parts of croplands were gradually converted from maize–wheat rotation to perennial mugwort cropping in Tangyin County in recent years, which provides the opportunity to assess the effects of the chronosequence of perennial mugwort cropping on a soil microbial community.
A chronosequence (continuous maize–wheat rotation (Control-Y0), perennial mugwort cropping for 3 (Y3), 6 (Y6), and 20 years (Y20)) of perennial mugwort cropping was identified and selected in this study region. In total, 375 kg of compound fertilizers (nitrogen, phosphorus, and potassium occupy 18%, 16%, and 16%, respectively) were applied per hectare and year in each of the four cropping chronosequences. In each chronosequence period, three blocks were randomly established. Three 20-cm-deep (0–10 cm, 10–20 cm) cylindrical holes were excavated using a soil auger (5 cm in diameter) in the plots. Soil samples were passed through a 0.25 mm sieve and roots were collected then oven-dried at 105 °C for 48 h. Then, soil samples were divided into two subsamples. One subsample was stored at 4 °C for measuring soil physicochemical properties. Another subsample was stored at −20 °C for measuring soil extracellular enzymatic activities and PLFAs.

2.2. Soil Chemical Property Measurements and PLFA Analysis

Soil total N was measured using an elemental analyzer with a dry combustion method (Vario MAX CN, Elementar Co., Hanau, Germany). The total phosphorus (P) content was determined by H2SO4-HClO4 digestion and then P molybdenum blue colorimetric analysis. The concentrations of ammonium (NH4+) and nitrate-nitrogen (NO3−) were extracted with 2M KCl solution and measured by a flow injection analyzer (SAN-System, Netherlands). Soil pH was measured with a combination glass-electrode [soil:water = 1:2.5 (w/v)]. The results of soil properties along the chronosequences of mugwort cropping were shown in another manuscript which is under review.
Soil microbial community was analyzed with PLFA analysis. Lipids were extracted from 8 g freeze-dried soil using a mixture of chloroform–methanol–phosphate buffer (1:2:0.8 v/v/v) and separated into phospholipids, glycolipids, and neutral lipids using an LCSi SPE silica column. The phospholipids were subjected to mild alkaline methanolysis, and the fatty acid methyl esters were identified on a gas chromatograph fitted with the MIDI Sherlock Microbial Identification System. Methyl nonadecanoate fatty acid (19:0) was used as the internal standard for quantifying the abundances of individual fatty acids for each sample by converting GC peak areas to nmol·g−1 dry soil.
The PLFAs 16:1w7c, 18:1w7c, cy19:0w7c, and cy17:0w7c were regarded as Gram-negative bacteria (GN), a15:0, a17:0, i15:0, i16:0, i17:0, and i17:1w9c were considered as Gram-positive bacterial (GP). Two fatty acids, 18:1w9c and 18:2w6c, were biomarkers for fungi and 16:1w5c was used to represent arbuscular mycorrhizal fungi (AMF). 10Me16:0, 10Me18:0, and 10Me18:1w7c were actinomycetes biomarkers. The ratio of fungi to bacteria (F:B ratio, the sum of GP, GP, and unspecific bacteria biomarkers 16:0 and 18:0) was also calculated.

2.3. Statistical Analyses

Two-way ANOVAs were used to explore the effects of soil depth and cropping year on all the variables included in the study. In addition, changes in soil chemical properties among the four cropping types were assessed using one-way ANOVA with Duncan multiple comparisons. Principal components analysis (PCA) was performed to explore microbial variation among the four cropping types using OriginPro 2022 (OriginLab Corporation, Northampton, MA, USA). The co-occurrence network was constructed and visualized by Gephi (v.0.9.2). The correlations among variables were explored by the Pearson correlation method. Significant differences were evaluated at the 0.05 probability level. Then, we used Random Forest (RF) models to partition relative influences of NH4+, NO3−, NH4+/NO3−, TN, TP, and pH on microbial variation. Statistical analyses were performed using SAS 8.0 (SAS Institute Inc., Cary, NC, USA) and R v.4.1.1 (R Development Core Team). GraphPad Prism 9.0 (GraphPad Inc., San Diego, CA, USA) was used to plot the graphs.

3. Results

3.1. Soil Microbial Biomass and Composition

There were significant differences in total PLFAs between the two soil depths (Table 1, p < 0.01). Similar differences in bacteria, fungi, Gram-negative bacteria, and arbuscular mycorrhizal fungi (AMF) PLFAs were also found between the two soil depths across the four cropping types (Table 1, all p < 0.01). In addition, all PLFAs showed variations among the four cropping types across the two depths (all p < 0.05). The highest total, actinomycetes, and fungi PLFAs were found in the 3-year mugwort cropping soils. No differences in Gram-positive and Gram-negative bacteria PLFAs were detected among the conventional rotation, 3- and 6-year mugwort cropping soils. All PLFAs were lowest in the 20-year mugwort cropping soils (Table S1, Figure 1). Significant interactions between soil depth and cropping years on total, bacteria, and Gram-negative bacteria PLFAs were detected (Table 1, all p < 0.05). In addition, the proportion of fungi under the 3-year mugwort cropping was higher than that under the other cropping types (Figure S1). Similarly, the proportion of Gram-negative bacteria under the 3-year mugwort cropping was 3.00% higher than the 20-year mugwort cropping. There were no differences in actinomycetes composition under the conventional rotation, 3- and 6-year mugwort cropping, all of which showed higher actinomycetes composition than that under the 20-year mugwort cropping (Figure S1).

3.2. Soil Microbial Network Analysis

PLFA-based soil microbial composition showed variations in the two soil depths and different cropping years (Figure 2). The first and second principal components accounted for 75.80% and 13.70% of the variations, respectively. To describe the co-occurrence patterns of soil microbial communities, the ecological networks were examined. The results revealed 32 nodes and 102 edges under the conventional rotation, with the node degree and average path length of 3.29 and 2.10, respectively. The edge of the conventional rotation was lower than that of the 3-year (141), 6-year (141), and 20-year mugwort cropping (127). In addition, node degrees were 4.58, 5.04, and 4.23 under the 3-year, 6-year, and 20-year mugwort cropping, respectively (Figure 3).

3.3. Driving Factors of Soil Microbial Community

Bacteria biomass increased with increasing soil NH4+-N (R2 = 0.20, p = 0.03), total N (R2 = 0.56, p < 0.001) linearly, whereas decreased with increasing soil pH (R2 = 0.23, p = 0.02). In addition, bacteria biomass showed quadratic relationships with NH4+/NO3− (R2 = 0.51, p < 0.001) and total P (R2 = 0.41, p < 0.01, Figure 4). Similarly, quadratic relationships of ACT biomass with soil pH (R2 = 0.50, p < 0.001), NH4+ (R2 = 0.39, p < 0.01), NH4+/NO3− (R2 = 0.44, p < 0.01), and total P (R2 = 0.71, p < 0.001) were observed across the four cropping types. ACT biomass linearly increased with increasing total N (R2 = 0.72, p < 0.001, Figure 5). Fungi biomass showed quadratic dependences on NH4+/NO3− (R2 = 0.23, p = 0.06), total N (R2 = 0.41, p < 0.01) and P (R2 = 0.29, p = 0.03, Figure 6) only, respectively. Gram-positive bacteria biomass negatively correlated with soil pH (R2 = 0.21, p = 0.02), but positively correlated with total N (R2 = 0.40, p < 0.001). In addition, Gram-positive bacteria biomass showed quadratic relationships with NH4+/NO3− (R2 = 0.50, p < 0.001) and total P (R2 = 0.38, p < 0.01, Figure 7). There were significantly linear relationships of Gram-negative biomass with soil NH4+ (R2 = 0.22, p = 0.02) and total N (R2 = 0.61, p < 0.001), whereas a quadratic relationship with soil pH (R2 = 0.25, p = 0.05), NH4+/NO3− (R2 = 0.47, p < 0.01), and total P (R2 = 0.40, p < 0.01, Figure 8). Similar relationships of arbuscular mycorrhizal fungi biomass (AMF biomass) with soil pH (R2 = 0.29, p = 0.03), NH4+/NO3− (R2 = 0.55, p < 0.001), and total P (R2 = 0.35, p = 0.01) were also detected, respectively (Figure 9).
The random forest model revealed that the ratio of NH4+ to NO3−, total N and P contributed more than the other soil properties to the changes in microbial community along the chronosequence of perennial mugwort cropping (F = 6.49, p < 0.01, Table 2). When analyzed by each PLFA, the ratio of NH4+ to NO3−, total N and P were also the most important factors affecting the bacteria (F = 8.47, p < 0.001), fungi (F = 5.30, p < 0.01), Gram-positive (F = 5.15, p < 0.01), Gram-negative (F = 9.17, p < 0.001), and AMF PLFAs (F = 5.56, p < 0.01). By contrast, total N and P, as well as pH were more important than the other three soil properties in terms of impact on the ACT PLFAs (F = 19.16, p < 0.001, Table 2).

4. Discussion

4.1. Changes in Soil Microbial Community along the Chronosequence of Perennial Mugwort Cropping

Previous studies have shown that perennial cropping can increase soil microbial biomass [12,37]. In this study, our results demonstrated that short-term mugwort cropping indeed increased soil microbial biomass (i.e., actinomycetes and fungal biomass, Figure 1, Table S1). By contrast, long-term mugwort cropping decreased biomass of all microbial groups (Figure 1, Table S1), which is inconsistent with the findings in previous studies [12,37]. In this study, short-term mugwort cropping increased the complexity of the co-occurring network among the microbial groups (Figure 3), which indicates the stimulated microbial growth and activities under the short-term mugwort cropping. Although the complexity of the co-occurring network under long-term mugwort cropping was greater than that under the conventional cropping, both plant biomass and soil nutrients were lower under the long-term mugwort cropping, which could restrain the growth and thus biomass of microbial groups through nutrient limitation [20,38].
In addition, our finding showed that biomass of most microbial groups at the depth of 10–20 cm was lower than that at the depth of 0–10 cm. This observation could be attributed to three reasons. First, it has been demonstrated that root exudations associated with root biomass can supply nutrients for microbial growth [39,40]. In this study, the lower root biomass (data not shown) of mugwort at the depth of 10–20 cm compared to that at the depth of 0–10 cm may supply less nutrients or root exudations for microbes, leading to the lower microbial biomass at the depth of 10–20 cm. The causal relationships of microbial biomass with root biomass could support this speculation (Figure S2). Second, except for root exudations, soil nutrient availability also plays a critical role in regulating microbial biomass and structure [16,20,38,41]. In fact, most available nutrients at the depth of 10–20 cm were lower than that at the depth of 0–10 cm. The lower nutrient availability could limit the soil microbial activities and growth [17,20]. Third, different microbial community composition and structure may result in various competitions for nutrients [42], which can also lead to changing microbial biomass among diverse microbial groups. The PLFA-based soil microbial composition was significantly different among the two soil depths and may support the speculation (Figure 2).
Our findings indicate that long-term mugwort cropping may not benefit for the sustainability of soil microbial biodiversity and functioning and that rotations should be considered when mugwort cropping for about 11 years (Figure S3). Given the limited understanding of long-term perennial cropping on soil microbial community, our findings of the contrasting responses of soil microbial biomass and composition to short- vs. long-term cropping could have critical implications for the sustainable agricultural management in temperate regions.

4.2. Driving Factors of Soil Microbial Community along the Chronosequence of Perennial Mugwort Cropping

In the current study, soil properties (especially soil NH4+, total N and P) decreased significantly under the long-term mugwort cropping (Y20). The findings may be attributed to three reasons. First, it has been demonstrated that long-term no-tillage management could lead to increased pathogens in soil [43]. In this study, reduced tillage management was applied during mugwort cropping, which may result in increased soil pathogens and thus the risk of root rot, consequently suppressing the nutrient absorption efficiency of mugwort roots. Second, tiller number increased significantly with the mugwort cropping year, which can lead to intra-specific competition for resources and nutrients, and thus have disadvantages for plant growth and development. Given the importance of fungi and AMF for nutrient uptake and plant growth, the lower fungi and AMF PLFAs (Figure 1) combined with the decreased aboveground and root biomass under the 20-year mugwort cropping provides further support for the above discussion. Third, regarding the results of the above two potential reasons, soil nutrients cannot be absorbed by mugwort plants effectively, which may result in nutrient loss through leaching with precipitation, and consequently cause the significant reduction in soil nutrients under the long-term mugwort cropping.
Previous studies have shown that pH is an important factor affecting the microbial community in agro-ecosystems [31,32,44]. However, it was observed that negative relationships of microbial PLFAs with soil pH (except for fungi PLFAs) are inconsistent with those found in previous studies [2,32]. The difference may result from the different soil types, crops, as well as management. Mugwort has strong tillering ability and thus can efficiently absorb soil NH4+ and NO3−, both of which are main drivers of soil acidification. This could alleviate the soil acidification process under fertilization in the short-term. By contrast, previous studies have demonstrated that most soil microbes favor acidic or neutral environments [2,45], which could lead to the negative dependence of microbial PLFAs on soil pH in this study.
It has been well documented that soil nutrient availability has critical impacts on microbial communities [20,38,41,46]. High nutrient availability in soil can supply diverse substrates and thus stimulate high microbial abundance and growth [17,47]. In this study, the findings of positive dependence of different microbial PLFAs with soil NH4+, total N and P are consistent with those found in previous studies. Interestingly, the observations of the causal dependence of changes in fungi and AMF PLFAs rather than bacteria PLFAs on soil NH4+ under the mugwort cropping chronosequence indicates a significant difference in nutrient use strategies between fungi and bacteria. In addition, all microbial groups in this study are not sensitive to soil NO3− (Figure 4, Figure 5, Figure 6, Figure 7, Figure 8 and Figure 9), which suggests that NH4+ fertilizer rather than NO3− fertilizer should be considered in mugwort cropping to improve soil microbial function. The evidence of quadratic relationships between microbial PLFAs and the ratio of NH4+ to NO3− provides further support for the above discussion. Nevertheless, nitrification inhibitors should be applied combined with NH4+ fertilizer to prevent nitrification associated with NH4+. These findings can have critical implications for sustainable development of mugwort cropping in the future. Nevertheless, microbial community composition and structure may change with vegetation seasons [48,49]; future studies should be conducted to explore the seasonal dynamics of soil microbial communities under perennial cropping systems.

5. Conclusions

Using a field investigation, we demonstrated that soil microbial biomass and composition showed various changes along the mugwort cropping chronosequence. The changes in soil properties, especially total nitrogen and phosphorus content, as well as the ratio of ammonium nitrogen to nitrate nitrogen explained the observations. In addition, the observations that the contrasting impacts of short-term and long-term mugwort cropping on soil microbial community compared with conventional rotations indicate that mugwort cropping has a key role in sustaining the abundance and structure of soil microbial communities, which may be an advantage for preventing the degradation of the soil microbial community structure and function in the short-term. Our findings suggest that short-term perennial mugwort cropping can have the potential to increase microbial biomass and rotations with other crops should be considered when cropping mugwort for approximately 11 years to maintain soil microbial community structure and function under mugwort cropping in temperate regions.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/agronomy12071568/s1, Table S1. Mean values (±1SE) of the total, bacteria, actinomycetes (ACT), fungi, gram-positive bacteria (GP), gram-negative bacteria (GN), arbuscular mycorrhizal fungi (AMF) PLFAs, and the ratio of fungi to bacteria (F:B ratio) across the two soil depths under the four cropping years. Y0: continuous maize-wheat rotation in recent decades; Y3: mugwort cropping for 3 years (since 2017); Y6: mugwort cropping for 6 years (since 2014); Y20: mugwort cropping for 20 years. Different letters indicate significant differences among the four cropping years at p < 0.05. Figure S1. The variations of microbial composition of gram-positive bacteria (GP), gram-negative bacteria (GN), fungi, actinomycetes (ACT), and general FAME under the four different cropping years of mugwort. Y0: continuous maize-wheat rotation; Y3: mugwort cropping for 3 years; Y6: mugwort cropping for 6 years; Y20: mugwort cropping for 20 years. Figure S2. Relationships of PLFAs with root biomass (Total PLFA, a; Bacteria PLFA, b; ACT PLFA, c; Fungi PLFA, d; GP PLFA, e; GN PLFA, f; AMF PLFA, g; F:B ratio, h). See abbreviations in Table S1. Figure S3. Changes in PLFAs along the chronosequences (Total PLFA, a; Bacteria PLFA, b; ACT PLFA, c; Fungi PLFA, d; GP PLFA, e; GN PLFA, f; AMF PLFA, g; F:B ratio, h). See abbreviations in Table S1.

Author Contributions

Conceptualization, Z.Z.; methodology, Z.Z., F.T. and X.W.; formal analysis, Z.Z. and F.T.; data curation, Z.Z. and F.T.; warming—original draft preparation, F.T. and Z.Z.; writing—review and editing, Z.Z., F.T., K.Z. and S.H.; funding acquisition, Z.Z. All authors have read and agreed to the published version of the manuscript.

Funding

This work was financially supported by the Postdoctoral Innovation and Practice Base of Anyang Institute of Technology (BSJ2020021, BHJ2021007).

Data Availability Statement

The data can be obtained from the corresponding author.

Acknowledgments

We thank Mingdong Chen and Qingfeng Li for their help in the field sampling.

Conflicts of Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

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Figure 1. Total (a), bacterial (b), fungi (c), actinomycetes (ACT, (d)), Gram-positive bacteria (GP, (e)), Gram-negative bacteria (GN, (f)), arbuscular mycorrhizal fungi (AMF, (g)), and the ratio of fungi to bacteria (F:B ratio, (h)) under different cropping years of mugwort. Y0: continuous maize–wheat rotation; Y3: mugwort cropping for 3 years; Y6: mugwort cropping for 6 years; Y20: mugwort cropping for 20 years.
Figure 1. Total (a), bacterial (b), fungi (c), actinomycetes (ACT, (d)), Gram-positive bacteria (GP, (e)), Gram-negative bacteria (GN, (f)), arbuscular mycorrhizal fungi (AMF, (g)), and the ratio of fungi to bacteria (F:B ratio, (h)) under different cropping years of mugwort. Y0: continuous maize–wheat rotation; Y3: mugwort cropping for 3 years; Y6: mugwort cropping for 6 years; Y20: mugwort cropping for 20 years.
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Figure 2. The principal components analysis (PCA) representing the variation in microbial community among different soil depths (a) and cropping years (b). Each datapoint represents the microbial community of the soil sample in each plot. Solid circles represent the 95% confidence intervals. See Figure 1 for abbreviations.
Figure 2. The principal components analysis (PCA) representing the variation in microbial community among different soil depths (a) and cropping years (b). Each datapoint represents the microbial community of the soil sample in each plot. Solid circles represent the 95% confidence intervals. See Figure 1 for abbreviations.
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Figure 3. Network analysis of co-occurring PLFAs under different mugwort cropping years. Nodes with different colors represent the individual PLFA biomarkers. Solid red and blue lines represent positive and negative correlations, respectively. General FAME: unspecific biomarkers. See Figure 1 for abbreviations.
Figure 3. Network analysis of co-occurring PLFAs under different mugwort cropping years. Nodes with different colors represent the individual PLFA biomarkers. Solid red and blue lines represent positive and negative correlations, respectively. General FAME: unspecific biomarkers. See Figure 1 for abbreviations.
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Figure 4. Relationships of bacteria biomass (nmol·g−1) with soil properties (pH, (a); NH4+, (b); NO3−, (c); NH4+/NO3−, (d); TN, (e); TP, (f)). See abbreviations in Table 2.
Figure 4. Relationships of bacteria biomass (nmol·g−1) with soil properties (pH, (a); NH4+, (b); NO3−, (c); NH4+/NO3−, (d); TN, (e); TP, (f)). See abbreviations in Table 2.
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Figure 5. Relationships of actinomycetes biomass (ACT biomass, nmol·g−1) with soil properties (pH, (a); NH4+, (b); NO3−, (c); NH4+/NO3−, (d); TN, (e); TP, (f)). See abbreviations in Table 2.
Figure 5. Relationships of actinomycetes biomass (ACT biomass, nmol·g−1) with soil properties (pH, (a); NH4+, (b); NO3−, (c); NH4+/NO3−, (d); TN, (e); TP, (f)). See abbreviations in Table 2.
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Figure 6. Relationships of fungi biomass (nmol·g−1) with soil properties (pH, (a); NH4+, (b); NO3−, (c); NH4+/NO3−, (d); TN, (e); TP, (f)). See abbreviations in Table 2.
Figure 6. Relationships of fungi biomass (nmol·g−1) with soil properties (pH, (a); NH4+, (b); NO3−, (c); NH4+/NO3−, (d); TN, (e); TP, (f)). See abbreviations in Table 2.
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Figure 7. Relationships of Gram-positive bacterial biomass (GP biomass, nmol·g−1) with soil properties (pH, (a); NH4+, (b); NO3−, (c); NH4+/NO3−, (d); TN, (e); TP, (f)). See abbreviations in Table 2.
Figure 7. Relationships of Gram-positive bacterial biomass (GP biomass, nmol·g−1) with soil properties (pH, (a); NH4+, (b); NO3−, (c); NH4+/NO3−, (d); TN, (e); TP, (f)). See abbreviations in Table 2.
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Figure 8. Relationships of Gram-negative bacterial biomass (GN biomass, nmol·g−1) with soil properties (pH, (a); NH4+, (b); NO3−, (c); NH4+/NO3−, (d); TN, (e); TP, (f)). See abbreviations in Table 2.
Figure 8. Relationships of Gram-negative bacterial biomass (GN biomass, nmol·g−1) with soil properties (pH, (a); NH4+, (b); NO3−, (c); NH4+/NO3−, (d); TN, (e); TP, (f)). See abbreviations in Table 2.
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Figure 9. Relationships of arbuscular mycorrhizal fungi biomass (AMF biomass, nmol·g−1) with soil properties (pH, (a); NH4+, (b); NO3−, (c); NH4+/NO3−, (d); TN, (e); TP, (f)). See abbreviations in Table 2.
Figure 9. Relationships of arbuscular mycorrhizal fungi biomass (AMF biomass, nmol·g−1) with soil properties (pH, (a); NH4+, (b); NO3−, (c); NH4+/NO3−, (d); TN, (e); TP, (f)). See abbreviations in Table 2.
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Table
Table 1. Results (F- and p-values) of two-way ANOVAs on the effects of soil depth (Depth), cropping year (Year), and their interactions on the total, bacteria, actinomycetes (ACT), fungi, Gram-positive bacteria (GP), Gram-negative bacteria (GN), arbuscular mycorrhizal fungi (AMF) PLFAs, and the ratio of fungi to bacteria (F:B ratio). The bold numbers indicate the significance at p ≤ 0.05.
Table 1. Results (F- and p-values) of two-way ANOVAs on the effects of soil depth (Depth), cropping year (Year), and their interactions on the total, bacteria, actinomycetes (ACT), fungi, Gram-positive bacteria (GP), Gram-negative bacteria (GN), arbuscular mycorrhizal fungi (AMF) PLFAs, and the ratio of fungi to bacteria (F:B ratio). The bold numbers indicate the significance at p ≤ 0.05.
VariationsDepthYearDepth × Year
FpFpFp
Total11.440.0049.57<0.0013.520.04
Bacteria14.300.00211.29<0.0013.180.05
ACT2.860.1118.82<0.0010.690.57
Fungi9.900.0063.360.041.530.25
GP3.840.075.350.012.530.09
GN24.41<0.00115.13<0.0013.510.04
AMF10.470.0056.970.0033.030.06
F:B ratio3.430.080.830.500.570.64
Table
Table 2. Relative contributions (increase in mean squared error (MSE), %) of soil properties to PLFAs based on Random Forest analysis. NH4+: soil ammonium-nitrogen content; NO3−: nitrate-nitrogen content; NH4+/NO3−: the ratio of NH4+ to NO3−; TN: total nitrogen content; TP: total phosphorus content.
Table 2. Relative contributions (increase in mean squared error (MSE), %) of soil properties to PLFAs based on Random Forest analysis. NH4+: soil ammonium-nitrogen content; NO3−: nitrate-nitrogen content; NH4+/NO3−: the ratio of NH4+ to NO3−; TN: total nitrogen content; TP: total phosphorus content.
VariablesTotalBacteriaACTFungiGPGNAMF
FpFpFpFpFpFpFp
6.49<0.018.47<0.00119.16<0.0015.30<0.015.15<0.019.17<0.0015.56<0.01
pH3.93%9.67%11.46%1.28%7.82%8.77%5.76%
NO3−8.08%8.14%6.20%5.41%2.81%6.41%3.31%
NH4+0.24%2.40%6.38%1.99%1.65%1.72%2.00%
NH4+/NO3−13.37%13.29%6.51%9.61%13.47%12.05%12.61%
TN14.59%16.63%16.72%13.23%9.67%18.47%9.64%
TP13.70%11.53%16.96%10.41%8.65%11.20%9.22%
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Tian, F.; Zhou, Z.; Wang, X.; Zhang, K.; Han, S. Changes in Soil Microbial Community along a Chronosequence of Perennial Mugwort Cropping in Northern China Plain. Agronomy 2022, 12, 1568. https://doi.org/10.3390/agronomy12071568

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Tian F, Zhou Z, Wang X, Zhang K, Han S. Changes in Soil Microbial Community along a Chronosequence of Perennial Mugwort Cropping in Northern China Plain. Agronomy. 2022; 12(7):1568. https://doi.org/10.3390/agronomy12071568

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Tian, Furong, Zhenxing Zhou, Xuefei Wang, Kunpeng Zhang, and Shijie Han. 2022. "Changes in Soil Microbial Community along a Chronosequence of Perennial Mugwort Cropping in Northern China Plain" Agronomy 12, no. 7: 1568. https://doi.org/10.3390/agronomy12071568

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