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Article

Effects of Soil Acidification on Bacterial and Fungal Communities in the Jiaodong Peninsula, Northern China

by
Tingting Wang
,
Xiaoxu Cao
,
Manman Chen
,
Yanhong Lou
,
Hui Wang
,
Quangang Yang
,
Hong Pan
* and
Yuping Zhuge
*
National Engineering Research Center for Efficient Utilization of Soil and Fertilizer Resources, College of Resources and Environment, Shandong Agricultural University, Daizong Road, Tai’an 271018, China
*
Authors to whom correspondence should be addressed.
Agronomy 2022, 12(4), 927; https://doi.org/10.3390/agronomy12040927
Submission received: 9 March 2022 / Revised: 8 April 2022 / Accepted: 10 April 2022 / Published: 12 April 2022
Browse Figures
Review Reports Versions Notes

Abstract

:
Soil acidification has become increasingly serious due to anthropogenic activities (e.g., fertilization) throughout the world. Examining the effects of soil acidification on bacterial and fungal communities in acidic crop soils provides valuable insights for revealing the potential role of microbes in soil quality and crop yield. Here, a total of 18 samples with pH varied from 4 to 7 were collected from agricultural regions in the Jiaodong Peninsula, Shandong Province, China. High-throughput sequencing analysis was used to determine the composition and diversity of the bacterial and fungal communities. The results revealed that the α-diversity of the bacterial community was significantly decreased as the soil acidification increased, while that of fungal communities exhibited little response to soil acidification, thus indicating that bacteria rather than fungi respond sensitively to soil acidification. Principal component analysis (PCA) and canonical correlations analysis (CCA) further corroborated that pH is an essential predictor for controlling the distribution of microbial communities, and it also could alter other exchangeable base cation (e.g., EH+, EAl3+, EK+, ENa+, ECa2+, and EMg2+) contents to further drive the microbial community patterns.

1. Introduction

Soil acidification is a common phenomenon worldwide and accounts for approximately 30–50% of the total land throughout the world [1]. Ongoing soil acidification has become a major problem in soil ecosystems and has drawn significant attention from researchers [2,3,4]. The rate of soil acidification under natural conditions is very slow and occurs over hundreds to millions of years [2]. Natural processes underlying soil acidification include the accumulation and oxidation of organic matter, transformation of nitrogen and sulfur, plant uptake of cations, and deposition of weak carbonic acid [5,6]. For example, in Southern China, high temperatures combined with frequent rainfall cause water to flow over the surface of the soil. Thus, the neutralization potential of mineral soil to acid is reduced, which decreases the soil pH. Additionally, soil acidification can be caused by anthropogenic activities, such as fertilizations [7,8,9]. Barak et al., (1997) observed that the rate of soil acidification caused by excessive fertilization was 25-fold higher than that caused by natural acid deposition [10], particularly in response to nitrogen fertilization, which releases protons and accelerates soil acidification [2,11].
Soil microorganisms play an important role in promoting the transformation and maintenance of soil nutrients, material circulation, and energy flow [12,13]. For example, bacteria play an important role in the cycle of carbon and inorganic salts [14]. Fungi are also the primary microorganisms that grow on exogenous carbon, and they play the role of decomposers, mycorrhizal symbionts, and pathogens in the ecosystem [15,16]. Soil pH is known to exert an important impact on the soil microbial activity and community structure [17,18,19]. Therefore, the structure and diversity of the soil microbial community can be greatly affected by soil acidification. In view of the sensitivity of the soil microbial community to soil environmental changes, it can be used as one of the important early warning indicators of agricultural soil quality changes during the process of agricultural planting [20].
Currently, a large amount of research has been performed to examine the response of soil microbial communities to acidified soil. Previous research has demonstrated that there is a significant relationship between microbial diversity and soil pH in various types of acidified soils [21,22,23] and in soils at different geographical scales [24,25,26]. Soil pH can also alter the microbial community structure by affecting specific microbial taxa such as Proteobacteria, Actinobacteria, Chloroflexi, and Acidobacteria [27,28]. However, few studies have investigated the changes of bacterial and fungal community structures in soils possessing different degrees of acidification. Therefore, we collected soil samples exhibiting different acidification degrees (pH 4–5, pH 5–6, and pH 6–7) from the Jiaodong Peninsula in Northern China and measured the composition of bacterial and fungal communities within these soils using high-throughput sequencing. We hypothesized that the bacterial and fungal community patterns in more acidified soils (pH 4–5) would be significantly differed from those in less acidified soil (pH > 5).

2. Materials and Methods

2.1. Field Description and Soil Sampling

Soil samples were collected from the Muping District, Yantai City, Shandong Province, China (37°7′–37°19′ N, 121°29′–121°45′ E) (Figure 1). This area possesses a warm and temperate East Asian monsoon continental climate. The annual average temperature and precipitation were 11.6 °C and 737.2 mm, respectively. The frost-free period lasted for 180 days. The soil type was classified as brown soil (Udic Luvisols). A total of 45 samples were collected. Each sample was combined from three duplicates. After the preliminary analysis, we chose 18 scattered samples from the 45 samples, as the 18 samples shared the same bedrock, soil type, climate [29], and cropping pattern (maize–wheat rotation). The 18 samples were separated into three pH ranges (pH 4–5, pH 5–6, and pH 6–7), and each range included six samples. Topsoil (0–20 cm) sampling was conducted using a standard soil auger (5 cm in diameter). After removing the aboveground plant material, ant nests, and visible insects, the soil samples were transported to the laboratory on ice. All of the soil samples were sieved (2 mm), and a small portion was stored at −80 °C for DNA extraction and molecular analysis. The remainder was air-dried for analysis of the chemical characteristics.

2.2. Determination of Soil Chemical Characteristics

Soil pH was measured using potentiometry (the rate of soil to deionized water was 1:2.5). Soil organic carbon (SOC) content was determined using the dichromate oxidation method [30]. Total nitrogen (TN) was measured using the Kjeldahl method [31]. Available phosphorus (AP) was extracted using 0.05 mol L−1 HCl and 0.025 mol L−1 (1/2 H2SO4) and then measured using a UV–visible spectrophotometer. Available potassium (AK) was extracted using ammonium acetate and determined by flame photometry [32]. The cation exchange capacity (CEC) was determined using the ammonium acetate exchange method described by Jiang et al., (2018) [33]. Exchangeable base cations were extracted using 1 mol L−1 CH3COONH4 (pH 7.0) [34]. The contents of exchangeable Ca2+ (ECa2+) and exchangeable Mg2+ (EMg2+) were measured using an atomic absorption spectrophotometer, and the contents of exchangeable K+ (EK+) and exchangeable Na+ (ENa+) were measured using flame photometry. Exchangeable acidity (EA), exchangeable H+ (EH+), and exchangeable Al3+ (EAl3+) were leached with 1 mol L−1 KCl, and the contents were determined according to the NaOH neutralization titration method [33].

2.3. Soil DNA Extraction and Illumina MiSeq-Sequencing

Approximately 0.20 g of fresh soil was used to extract the total microbial genomic DNA according to the manufacturer’s instructions using the DNeasy PowerSoil Kit (Qiagen, Hilden, Germany). The extraction amount and quality of DNA were determined using a NanoDrop ND-2000 spectrophotometer (Thermo, Waltham, MA, USA) and 0.7% agarose gel electrophoresis, respectively. DNA samples were stored at −20 °C prior to further analysis.
The V3–V4 region of the bacterial 16S rRNA gene was amplified using the primers 338F (5′-ACTCCTACGGGAGGCAGCAG-3′) and 806R (5′-GGACTACHVGGGTWTCTAAT-3′). The ITS1 region of the fungal 16S rRNA gene was amplified using the primers ITS5F (5′-GGAAGTAAAAGTCGTAACAAGG-3′) and ITS1R (5′-GCTGCGTTCTTCATCGATGC-3ʹ). The total volume of the reaction mixture was 25 μL, and it contained 0.25 μL of Q5 high-fidelity DNA polymerase, 5 μL of Reaction Buffer, 5 μL of High GC Buffer, 2 μL of dNTP (10 mM), 2 μL of DNA template, 1 μL of forward and reverse primers (10 μM), and 8.75 μL of double-distilled water.
The thermal cycling for the bacterial community analysis consisted of an initial denaturation at 98 °C for 2 min that was followed by 25 cycles consisting of denaturation at 98 °C for 15 s, annealing at 55 °C for 30 s, and extension at 72 °C for 30 s. A final extension was performed for 5 min at 72 °C. Thermal cycling consisted of an initial denaturation at 98 °C for 5 min that was followed by 25 cycles consisting of denaturation at 98 °C for 30 s, annealing at 52 °C for 30 s, and extension at 72 °C for 1 min, with a final extension of 5 min at 72 °C.
PCR amplicons were purified with Agencourt AMPure Beads (Beckman Coulter, Indianapolis, IN, USA) and quantified using the PicoGreen dsDNA Assay Kit (Invitrogen, Carlsbad, CA, USA). The amplicons were pooled in equal amounts, and then paired-end 2 × 300 bp sequencing was performed using the Illumina MiSeq platform with MiSeq Reagent Kit V3.

2.4. Statistical Analysis

The sequencing data were processed using QIIME (version 1.8.0), and low-quality sequences that were deleted included [35,36]: (1) sequences that possessed a length less than 150 bp, (2) sequences exhibiting average Phred scores of less than 20, (3) sequences containing ambiguous bases, and (4) sequences containing more than 8 bp mononucleotide repeats. The remaining high-quality sequences were clustered into operational taxonomic units (OTUs) at 97% sequence identity using UCLUST (Edgar 2010). OTU classification was conducted by BLAST searching of the representative sequences against the Greengenes database [37] using the best hit [38]. OTUs containing less than 0.001% of the total sequences across all samples were discarded. The OTU table of bacteria and fungi was detailed in Table S1.

2.5. Sequence Analysis

All data were processed using Microsoft Excel 2019 and Origin 8.5. Statistical analyses were performed using SPSS 22.0. Standard deviations (SDs) in parallel samples were shown as error bars. Data comparisons between groups were analyzed by one-way analysis of variance (ANOVA) followed by Duncan’s test at a significance level of p < 0.05. α-diversity was used to analyze the complexity of the species diversity for each sample using the Shannon, Simpson, Chao1, and abundance-based coverage estimator (ACE) indices that were calculated using QIIME (version 1.8.0). β-diversity was assessed by principal component analysis (PCA) based on the unweighted UniFrac distances between the samples [39,40]. Concurrently, canonical correlation analysis (CCA) was performed to analyze the relationships between the microbial communities and environmental factors. The sequencing data for bacteria and fungi were uploaded to the Sequence Read Archive (SRA) database of the NCBI. The retrieval numbers are PRJNA611682 and PRJNA61692, respectively.

3. Results

3.1. Soil Chemical Characteristics

The soil properties varied with different soil pH values (Table 1). EA refers to the total amount of EH+ and EAl3+ that is adsorbed on the surface of the soil colloid. In our study, the EA content increased significantly with an increase in the soil acidification degree. The contents of EH+ and EAl3+ were significantly higher at pH 4–5 than those at pH 5–6 and pH 6–7. CEC is the primary index of soil exchangeability and reflects the bioavailability of ions. In our study, the contents of CEC, EK+, ECa2+, and EMg2+ were significantly higher at pH 6–7 than those at the other two pH ranges. ENa+ exhibited the highest value at pH 5–6. Additionally, soil acidification also affects nutrient availability. In this study, the contents of SOC and AK were significantly higher in soils with pH 6–7 than those in soils with pH 4–6, while the contents of TN and AP followed the opposite trend.

3.2. The α-Diversity of Bacterial and Fungal Communities

The Chao1, Shannon, Simpson, and ACE indices were used to characterize the richness and diversity of the microbial species. For the bacterial community, the Chao1, Shannon, and ACE indices in pH 4–5 soils were significantly (p < 0.05) lower than those in the other two soils possessing pH ranges at pH 5–6 and pH 6–7 (Figure 2a). Additionally, there were no significant differences in the Simpson index values among the three pH ranges. In regard to the fungal community, no significant differences were observed of the four α-diversity indices among the three different pH ranges (Figure 2b).

3.3. Soil Bacterial and Fungal Community Compositions

Actinobacteria (27.82–32.94%), Proteobacteria (28.11–29.23%), Acidobacteria (9.45–13.05%), and Chloroflexi (8.93–14.40%) were the dominant bacterial phyla across the three pH ranges (Figure 3a). Aggravation of soil acidification led to an increase in the relative abundances of Actinobacteria, Firmicutes, and Saccharibacteria. Specifically, the relative abundance of Actinobacteria was decreased from 32.94% in pH 4–5 soils to 27.82% in pH 6–7 soils (p < 0.05). In contrast, aggravation of soil acidification led to a decrease in the relative abundance of Chloroflexi and Bacteroidetes. The relative abundance of Chloroflexi was increased from 8.93% at pH 4–5 to 14.40% at pH 6–7. Similarly, the relative abundance of Bacteroidetes increased from 1.95% at pH 4–5 to 3.30% at pH 6–7. The relative abundances of Acidobacteria, Gemmatimonadetes, Verrucomicrobia, and Planctomycetes reached the highest levels of 13.05%, 4.29%, 4.59%, and 1.98% in pH 5–6 soils, respectively. In contrast, the relative abundance of Proteobacteria reached the lowest level of 28.11% in pH 5–6 soils. Ascomycota (66.95–75.03%) and Basidiomycota (16.49–23.26%) were the dominant fungal phyla within the acidified soils across the three pH ranges (Figure 3b). No linear increase or decrease in the relative abundances of Ascomycota and Basidiomycota were detected in response to aggravation of soil acidification. The relative abundance of Ascomycota increased initially and then decreased in response to increasing the soil pH value, and it reached the highest abundance of 75.03% in pH 5–6 soils. In contrast, the relative abundance of Basidiomycota decreased initially and then increased in response to the increasing soil pH, and it reached the lowest abundance of 16.49% in pH 5–6 soils. However, for the phyla Zygomycota, Chytridiomycota, and Glomeromycota, aggravation of soil acidification led to a significant decrease in their relative abundances. The relative abundance of Zygomycota was increased from 2.61% at pH 4–5 to 5.60% at pH 6–7. Similarly, the relative abundance of Chytridiomycota was increased from 0.11% at pH 4–5 to 0.67% at pH 6–7 and that of Glomeromycota was increased from 0.06% at pH 4–5 to 0.72% at pH 6–7.
PCA was used to assess the distribution characteristics of the bacterial and fungal communities in acidified soils. For the bacterial communities, the first principal component (PC1) accounted for 29.86% of the total variation, and PC2 accounted for 26.27% of the variation (Figure 4a). For the fungal community, the first principal coordinate axis accounted for approximately 32.71% of the total variation, and the second accounted for approximately 25.42% (Figure 4b). Notably, both bacterial and fungal communities in more acidic soils (pH 4–5) were separated from those in less acidic soils (pH > 5).
CCA was performed to examine the association between edaphic factors and microbial communities. For the bacterial community, the first two principal coordinates accounted for 38.07% and 30.00% of the overall variance of the soil bacterial community, respectively (Figure 5a). The soil pH values (p < 0.001), TN (p < 0.001), AP (p < 0.001), AK (p < 0.001), EA (p < 0.001), EH+ (p < 0.001), EMg2+ (p < 0.001), EAl3+ (p < 0.01), and ECa2+ (p < 0.05) were all significantly associated with the bacterial community. For the fungal community, soil pH (p < 0.001), EMg2+ (p < 0.01), EAl3+ (p < 0.01), EH+ (p < 0.01), EA (p < 0.01), AP (p < 0.01), AK (p < 0.01), EK+ (p < 0.05), TN (p < 0.05), and SOC (p < 0.05) were significantly correlated with the fungal community (Figure 5b).

4. Discussion

4.1. Effects of Soil Acidification on Bacterial and Fungal Diversity

The results of the present study demonstrated that soil acidification significantly reduced bacterial community α-diversity and exerted little effect on fungal α-diversity (Figure 2). Compared to observations at pH 4–5, the Shannon, Chao 1, and ACE indices were increased significantly at pH 5–6 and pH 6–7, and this was generally consistent with the results of previous studies [17,24]. This could be attributed to the observation that fungi prefer a wider pH range than bacteria for optimal growth [24]. These results further corroborated that bacteria were more sensitive than fungi to soil acidification in agricultural soils.

4.2. Effects of Soil Acidification on Bacterial and Fungal Community Composition

The bacterial community was predominantly composed of Actinobacteria, Proteobacteria, Acidobacteria, and Chloroflexi, which is in agreement with the results of previous studies examining acidified soils [41]. Actinobacteria is a type of saprophytic bacteria present in soil that has the ability to decompose complex substrates [6]. However, it is also a type of bacteria that is limited by the nitrogen content, and its relative abundance increases in response to an increase in the total nitrogen content [42]. In the present study, the nitrogen content increased in response to the decreasing pH value (Table 1), and based on this, the relative abundance of Actinobacteria was highest in more acidic soils (pH 4–5) (Figure 3a). Chloroflexi is a type of oligobacteria that exhibits a lower growth rate under conditions of higher nutrient utilization rates [43]. Therefore, the response of its relative abundance to soil acidity was opposite to that of Actinobacteria, which decreased with the decreasing of the pH (Figure 3a). Proteobacteria abundance was increased in environments that were rich in nutrients [44]. In this area, the SOC content was decreased in response to the aggravation of soil acidification (Table 1), and thus, Proteobacteria exhibited the highest relative abundance in soils at pH 6–7 (Figure 3a). Acidobacteria was the most abundant bacterial phylum in soils at pH 5–6 (Figure 3a), which was in agreement with a previous study that observed that Acidobacteria prefers to live in an environment possessing weak acidity (pH 5.5) [45].
For fungal communities, Ascomycota and Basidiomycota were the primary fungal phyla, and Ascomycota accounted for greater than 66% of the fungal communities (Figure 3b). This was similar to levels that were reported in other agricultural soils [46] and forest soils [47]. Previous reports have demonstrated that the majority of the identified dominant fungal phylotypes belong to Ascomycota in soil systems globally [48], as Ascomycota tend to be better equipped to withstand environmental stresses and are able to utilize a higher number of resources that allow them to utilize more generalist strategies that may contribute to their increased dominance in soils [48]. The relative abundance of Basidiomycota was decreased in response to the increasing soil acidification, and this was likely due to the significantly higher SOC in soils at pH 6–7 compared to that observed in the other two acidic soils (Table 1) [49]. Additionally, Basidiomycota can form ectomycorrhiza with plants and accelerate the absorption of nutrients by crops [50], thus affecting the growth of host plants. Therefore, it is speculated that plant growth will be affected in areas exhibiting increased acidification.

4.3. Factors Affecting Bacterial and Fungal Community Structure

PCA revealed that the microbial communities present in more acidic soils (pH 4–5) were separated from those in less acidic soils (pH 5–6 and pH 6–7) (Figure 4), thus indicating that the soil acidification degree exerted a strong impact on the structure of the soil microbial community. CCA analysis further indicated that soil pH was a considerable factor in driving the microbial community composition (Figure 5), and this was supported by Choma et al., (2020), who proposed that the majority of the explained variability could be ascribed to the pH [47]. What is noteworthy is that exchangeable base cation, including EH+, EAl3+, EK+, ENa+, ECa2+, and EMg2+, were also major environmental variables controlling the bacterial and fungal community patterns. It has been reported that the soil pH exerted greater effects on the species diversity and bacterial community patterns than did other physicochemical properties in acidic soils [51,52]. Soil pH is regarded as a good predictor of microbial community patterns both across biomes and within an individual soil type based on the knowledge that microbes are directly affected by soil pH, where most species prefer relatively narrow growth tolerances. Another explanation we first proposed is that soil pH could alter other exchangeable base cation contents to further drive the microbial community patterns (Figure 5). Therefore, pH is a key factor driving the diversity and community structure of bacterial and fungal communities in acidic soils.

5. Conclusions

In conclusion, the compositions of the bacterial and fungal communities in the Jiaodong Peninsula were sharply defined by the degree of soil acidification. Soil acidification significantly reduced bacterial α-diversity and exerted little effect on fungal α-diversity. The bacterial community was primarily composed of Actinobacteria, Proteobacteria, Acidobacteria, and Chloroflexi, and the fungal community predominantly included Ascomycota and Basidiomycota. The relative abundances of Actinobacteria, Firmicutes, and Ascomycota were the highest in more acidic soils (pH < 5). In contrast, Acidobacteria, Chloroflexi, and Basidiomycota were the highest in less acidic soils (pH > 5). As expected, the microbial community composition and the relative abundance of microbial phyla were largely predicted by soil pH and exchangeable base cation in acidified crop soils, particularly in regard to the bacterial communities. These findings are significant for evaluating the effects of pH on soil microbial communities in acidic crop lands and may explain the reason underlying the decrease in crop yield and the risk of soil-borne diseases.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/agronomy12040927/s1.

Author Contributions

Conceptualization, H.P. and Y.Z.; methodology, Y.L. and H.W.; software, T.W.; validation, Q.Y.; formal analysis, T.W., X.C. and M.C.; investigation, T.W.; resources, Y.L., H.P. and Y.Z.; data curation, T.W.; writing—original draft preparation, T.W.; writing—review and editing, H.P. and Y.Z.; supervision, H.W.; project administration, Y.Z.; and funding acquisition, Y.Z. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the Natural Science Foundation of China (41771273).

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Data is contained within the article.

Conflicts of Interest

The authors declare no conflict of interest.

Abbreviations

SOC: soil organic carbon; TN, total nitrogen; AP, available phosphorus; AK, available potassium; CEC, cation exchange capacity; EA, exchangeable acidity; EH+, exchangeable H+; EAl3+, exchangeable Al3+; EK+, exchangeable K+; ENa+, exchangeable Na+; ECa2+, exchangeable Ca2+; EMg2+, exchangeable Mg2+.

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Agronomy 12 00927 g001 550
Figure 1. Locations of the sampling sites. The red spots represent the 45 sites where soil samples were collected in Yantai City, Shandong Province, China.
Figure 1. Locations of the sampling sites. The red spots represent the 45 sites where soil samples were collected in Yantai City, Shandong Province, China.
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Figure 2. α-diversity of bacterial (a) and fungal (b) communities in soil with different acidification degrees. The columns were colored according to the α-diversity index. As for the same α-diversity index, the data of the three pH ranges are marked without the same letters to indicate significant differences (p < 0.05).
Figure 2. α-diversity of bacterial (a) and fungal (b) communities in soil with different acidification degrees. The columns were colored according to the α-diversity index. As for the same α-diversity index, the data of the three pH ranges are marked without the same letters to indicate significant differences (p < 0.05).
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Figure 3. Composition of the top 10 bacterial (a) and fungal (b) phyla detected from acidified soil. Data were depicted by Circos software. Length of the bars (pH ranges) represents the percentage of the respective phyla from each sample. Length of the bars (phyla) represents the percentage the sample contributes to the proportion of each bacterial or fungal phyla.
Figure 3. Composition of the top 10 bacterial (a) and fungal (b) phyla detected from acidified soil. Data were depicted by Circos software. Length of the bars (pH ranges) represents the percentage of the respective phyla from each sample. Length of the bars (phyla) represents the percentage the sample contributes to the proportion of each bacterial or fungal phyla.
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Figure 4. PCA was used to analyze the bacterial (a) and fungal (b) community structure, and two-dimensional images were used to describe the natural distribution characteristics among the samples. Each dot represents a sample, and dots of different colors belong to different pH ranges.
Figure 4. PCA was used to analyze the bacterial (a) and fungal (b) community structure, and two-dimensional images were used to describe the natural distribution characteristics among the samples. Each dot represents a sample, and dots of different colors belong to different pH ranges.
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Figure 5. CCA of the relationships between bacterial (a) and fungal (b) communities with environmental factors. Each dot represents a sample, and dots of different colors belong to different pH ranges. The black arrows represent environmental factors. ***: p < 0.001, **: p < 0.01, and *: p < 0.05.
Figure 5. CCA of the relationships between bacterial (a) and fungal (b) communities with environmental factors. Each dot represents a sample, and dots of different colors belong to different pH ranges. The black arrows represent environmental factors. ***: p < 0.001, **: p < 0.01, and *: p < 0.05.
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Table
Table 1. Soil chemical characteristics under soil with different acidification degrees.
Table 1. Soil chemical characteristics under soil with different acidification degrees.
pH RangespHSOC
(g kg−1)		TN
(g kg−1)		AP
(mg kg−1)		AK
(mg kg−1)		CEC
(cmol kg−1)
pH 4–54.53 ± 0.15 c 4.81 ± 0.24 c0.40 ± 0.02 a33.05 ± 0.81 a54.67 ± 1.13 c12.17 ± 0.74 b
pH 5–65.58 ± 0.11 b6.51 ± 0.33 b0.30 ± 0.03 b12.63 ± 0.67 b73.08 ± 0.89 b12.67 ± 0.95 b
pH 6–76.49 ± 0.11 a11.10 ± 0.37 a0.23 ± 0.01 c6.84 ± 0.27 c94.44 ± 0.77 a15.74 ± 0.49 a
pH RangesEA
(cmol kg−1)		EH+
(cmol kg−1)		EAL3+
(cmol kg−1)		EK+
(cmol kg−1)		ENa+
(cmol kg−1)		ECa2+
(cmol kg−1)		EMg2+
(cmol kg−1)
pH 4–51.81 ± 0.07 a0.31 ± 0.02 a1.56 ± 0.14 a0.27 ± 0.01 b0.37 ± 0.03 b3.51 ± 0.09 b0.89 ± 0.01 b
pH 5–60.81 ± 0.09 b0.17 ± 0.02 b0.60 ± 0.10 b0.29 ± 0.03 b0.48 ± 0.03 a4.21 ± 0.34 a1.33 ± 0.05 a
pH 6–70.42 ± 0.07 c0.12 ± 0.01 b0.36 ± 0.13 b0.37 ± 0.02 a0.33 ± 0.02 b4.42 ± 0.13 a1.39 ± 0.04 a
Note: Abbreviation: SOC—soil organic carbon; TN—total nitrogen; AP—available phosphorus; AK—available potassium; CEC—cation exchange capacity; EA—exchangeable acidity; EH+—exchangeable H+; EAl3+—exchangeable Al3+; EK+—exchangeable K+; ENa+—exchangeable Na+; ECa2+—exchangeable Ca2+; EMg2+—exchangeable Mg2+. Data are presented as the means ± SDs, n = 3. Different letters indicate significant differences at p < 0.05.
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Wang, T.; Cao, X.; Chen, M.; Lou, Y.; Wang, H.; Yang, Q.; Pan, H.; Zhuge, Y. Effects of Soil Acidification on Bacterial and Fungal Communities in the Jiaodong Peninsula, Northern China. Agronomy 2022, 12, 927. https://doi.org/10.3390/agronomy12040927

AMA Style

Wang T, Cao X, Chen M, Lou Y, Wang H, Yang Q, Pan H, Zhuge Y. Effects of Soil Acidification on Bacterial and Fungal Communities in the Jiaodong Peninsula, Northern China. Agronomy. 2022; 12(4):927. https://doi.org/10.3390/agronomy12040927

Chicago/Turabian Style

Wang, Tingting, Xiaoxu Cao, Manman Chen, Yanhong Lou, Hui Wang, Quangang Yang, Hong Pan, and Yuping Zhuge. 2022. "Effects of Soil Acidification on Bacterial and Fungal Communities in the Jiaodong Peninsula, Northern China" Agronomy 12, no. 4: 927. https://doi.org/10.3390/agronomy12040927

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