Physical and chemical properties of soil in different land-use patterns
The physical and chemical properties of the soil of the three land-use patterns are shown in Table 1. The pH of all soils was relatively alkaline, with a significant difference between grassland and plough (P<0.05), with the lowest pH value in plough and the highest pH value in grassland. The soil moisture content of the three land-use patterns was significantly different (P<0.05), with the highest soil moisture content in forest. The contents of microbial biomass carbon, microbial biomass nitrogen, total phosphorus, available phosphorus and nitrate nitrogen in plough were significantly higher than those in forest and grassland (P < 0.05). However, there was no significant difference in soil organic matter, total nitrogen, ammonium nitrogen, total potassium or available potassium.
Table 1 Physical and chemical properties of soil in different land use patterns
Land use patterns
|
pH value
|
MC(%)
|
MBC
/(mg/kg)
|
MBN
/(mg/kg)
|
SOC
/(g/kg)
|
TN
/(g/kg)
|
Forest
|
9.09±0.07ab
|
14.19±0.52a
|
140.89±36.51b
|
12.48±3.43b
|
2.01±0.51a
|
5.06±2.03a
|
Grassland
|
9.23±0.26a
|
13.66±0.27b
|
154.65±52.63b
|
9.33±5.03b
|
2.17±0.51a
|
5.29±2.77a
|
Plough
|
8.96±0.11b
|
13.48±0.82b
|
227.49±69.93a
|
19.59±6.33a
|
2.06±0.08a
|
4.34±1.11a
|
Land use patterns
|
NH4+-N
/(mg/kg)
|
NO3--N
/(mg/kg)
|
TP
/(g/kg)
|
TK
/(mg/kg)
|
AP
/(mg/kg)
|
AK
/(mg/kg)
|
Forest
|
2.76±0.42a
|
5.44±2.41b
|
0.51±0.05b
|
4.02±1.31a
|
5.71±1.74b
|
22.14±6.73a
|
Grassland
|
2.37±0.23a
|
2.93±0.79c
|
0.43±0.07c
|
3.24±1.71a
|
4.51±1.79b
|
20.09±2.51a
|
Plough
|
2.56±0.35a
|
11.42±2.33a
|
0.74±0.07a
|
3.92±1.61a
|
15.83±5.82a
|
25.78±4.35a
|
Note:Mean values (means ± SD, n=6) followed by different letters indicate significant difference between land-use types at the P < 0.05 level. The same below. MC:moisture content;MBC:micro biomass carbon; MBN: microbiomass nitrogen: SOC: soil organic carbon: TN: total nitrogen; NH4+-N: Ammonium nitrogen; NO3--N: Nitrate nitrogen; TP: total phosphorus; AP: available phosphorus; TK: total potassium; AK: available potassium.
Venn diagram of soil microorganisms in different land-use patterns
The bacterial Venn diagram of the three land-use patterns is shown in Figure 1A. There were 3,680 soil bacteria OTUs in the three land-use types of grassland, forest and plough; among them, 2,208 OTUs were in the three land-use types, accounting for 60.27% of all OTUs. The maximum number of grassland soil bacteria OTUs was 3028, accounting for 82.28% of the total, and the number of unique OTUs was 207, accounting for 5.63% of the total. The lowest number of soil bacteria OTUs was 2888, accounting for 78.48% of the total, and the number of specific OTUs was 90, accounting for 2.45% of the total. The number of plough soil bacteria OTUs was 3,018, accounting for 82.01% of the total, and the number of unique OTUs was 337, accounting for 9.16% of the total.
The fungi Venn diagram of the three land-use patterns is shown in Figure 1B. There were 1,819 soil fungal OTUs in the three land-use types of grassland, forest and plough, among which 205 OTUs were in the three land-use types, accounting for 11.26% of all OTUs. The maximum number of plough soil fungal OTUs was 1042, accounting for 57.28% of the total, and the number of unique OTUs was 545, accounting for 29.96% of the total. The lowest number of OTUs was 649, accounting for 35.68% of the total, and the number of unique OTUs was 192, accounting for 10.55% of the total. The number of forest soil fungal OTUs was 745, accounting for 40.95% of the total, and the number of unique OTUs was 228, accounting for 12.53% of the total.
Effects of land-use patterns on alpha diversity of soil bacteria and fungi
There was no significant difference between the Shannon index and Simpson index of soil bacteria. However, the soil bacterial Ace and Chao1 indexes of the three land-use patterns were significantly different (P < 0.05). Among them, the Ace index showed plough > forest > grassland, and there were significant differences between grassland, forest, and plough (P < 0.05). The Chao1 index result was plough > forest > grassland, and the three land-use types had significant differences (P<0.05). The number of soil bacteria OTUs was significantly different and showed plough > forest > grassland.
The soil fungal Shannon index, Simpson index, Ace index, Chao1 index, and OTU index were significantly different (Table 2). The OTU index was ranked plough > forest > grassland; the Shannon diversity index was plough > grassland > forest; the Simpson index was forest > grassland> plough; the Ace index was plough > forest > grassland; and the Chao1 index was plough > forest > grassland.
Table 2 Diversity index of soil bacterial and fungal communities in different
land use patterns
|
Land use types
|
Shannon
|
Simpson
|
Ace
|
Chao1
|
Bacterial
|
Forest
|
6.34±0.19a
|
0.0045±0.0012a
|
2292.25±141.12a
|
2284.91±139.51ab
|
Grassland
|
6.08±0.30a
|
0.0077±0.0041a
|
1977.76±397.36b
|
1990.98±391.46b
|
Plough
|
6.32±0.49a
|
0.0126±0.0199a
|
2401.35±131.88a
|
2408.77±140.43a
|
Fungal
|
Forest
|
2.73±0.48b
|
0.1506±0.0639a
|
380.89±238.18b
|
358.88±11.91b
|
Grassland
|
3.09±0.46b
|
0.1205±0.0808a
|
242.13±30.06c
|
111.91±24.81c
|
Plough
|
4.04±0.34a
|
0.0597±0.0353b
|
465.72±39.03a
|
468.18±23.50a
|
Effects of land-use patterns on beta diversity of soil bacteria and fungi
The beta diversity of bacterial and fungal communities in different land-use patterns was measured by the h-cluster and PCoA of the Bray-Curtis distance. The beta diversity of the bacterial community is shown in Figures 2A and 2B, with significant differences between bacterial community structures in different land-use patterns (PERMANOVA: r=0.43, P<0.01). This result indicates that the differences within samples are not significant, and the differences mainly come from the different samples. Long-term changes in land use will lead to significant changes in bacterial community structure. The beta diversity of fungal communities is shown in Figures 2C and 2B, with significant differences between fungal community structures in different land-use patterns (PERMANOVA: r=0.54, P<0.01). This result indicates that the differences within samples are not significant, and the differences mainly come from the different samples. Long-term changes in land use will lead to significant changes in fungal community structure.
Analysis of soil bacterial and fungal community structure in different land-use patterns
From the perspective of the overall bacterial community structure, all OTUs belong to 55 bacterial phyla. If the sequence cannot be classified to the known phylum level, the phylum can be uniformly classified into "others". According to the relative abundance of all phylum levels of the three land-use patterns, the dominant bacteria in the samples were Proteobacteria, Acidobacteria and Actinobacteria (Figure 3A). The relative abundance of actinomycetes among the dominant bacteria in the original grassland soil was 30.01%, the relative abundance of Acidobacteria was 29.52%, and the relative abundance of Proteobacteria was 17.57% (Figure 3B). The dominant phylum in plough soil was Proteobacteria, with a relative abundance of 31.22%; additionally, the relative abundance of Actinomycota was 8.73%, and the relative abundance of Acidobacteria was 21.42% (Figure 3C). The dominant phylum in forest was Acidobacteria, with a relative abundance of 35.7%; additionally, the relative abundance of Proteobacteria was 20.53%, and the relative abundance of Actinomycota was 15.8% (Figure 3D).
From the perspective of the overall composition of the fungal community structure, all OTUs belong to 35 bacterial phyla, and the sequences that cannot be classified to a known phylum level are uniformly classified as "others". From the relative abundance of all levels of the three land-use patterns, the dominant phyla in the sample were Ascomycota, Basidiomycota, and Zygomycota (Figure 4A). The relative abundance of Ascomycota is grassland was 62.74%, making it the dominant soil fungi; additionally, the relative abundance of Basidiomycota was 2.60%, and the relative abundance of Zygomycota was 0.86% (Figure 4B). After the grassland was converted to plough, the dominant mycoplasma was still Ascomycota, with an abundance of 46.63%, the abundance of Basidiomycota was 11.87%, and the abundance of Zygomycota was 7.28% (Figure 4C). The dominant phylum of the forest was Basidiomycota, with an abundance of 76.68%; it was followed by Ascomycota, with an abundance of 15.90%, and Zygomycota, with an abundance of 1.18% (Figure 4D).
One-way ANOVA and two-sample T-test method were used to analyse the difference in abundance of bacterial community gates in different land-use patterns. A total of 7 gates had significant differences in the three land-use patterns (Figure 5A). These included Acidobacteria (P<0.05), Actinobacteria (P<0.001), Gemmatimonadetes (P<0.05), Bacteroidetes (P<0.001), Planctomycete (P<0.001), unclassified_k_norank (P<0.05), and Latescibacteria (P<0.01). There were significant differences between the 4 gates of forest and grassland (Figure 5B), mainly in Actinobacteria (P<0.001), Bacteroidetes (P<0.001), unclassified_k_norank (P<0.05), and Latescibacteria (P<0.01). There were significant differences between the 9 forest and plough gates (Figure 5C), mainly in Acidobacteria (P<0.05), Proteobacteria (P<0.05), Chloroflexi (P<0.05), Gemmatimonadetes (P<0.05), Acteroidetes (P<0.001), Saccharibacteria (P<0.05), Planctomycetes (P<0.001), Parcubacteria (P<0.05), and Latescibacteria (P<0.001). There were significant differences between 7 gates in grassland and plough (Figure 5D), including Proteobacteria (P<0.05), Actinobacteria (P<0.001), Gemmatimonadetes (P<0.05), Bacteroidetes (P<0.001), Saccharibacteria (P<0.05), Planctomycetes (P<0.001), and Parcubacteria (P<0.05).
Based on the difference in the level abundance of the fungal community gates in the three land-use patterns (Figure 6), there were 6 gates with significant differences in the three land-use patterns: Ascomycota (P<0.001), Basidiomycota (P<0.001), Zygomycota (P<0.01), Glomeromycota (P<0.01), and Chytridiomycota (P<0.05). There were significant differences between the two gates of plough and grassland (Figure 6B), mainly in Basidiomycota (P<0.05) and Zygomycota (P<0.01). There were significant differences between the four gates of forest and plough (Figure 6C), mainly in Basidiomycota (P<0.001), Ascomycota (P<0.01), Zygomycota (P<0.01), and Glomeromycota (P<0.05). There were significant differences between the 7 gates in grassland and forest (Figure 6D), mainly in Basidiomycota (P<0.001), Ascomycota (P<0.001), and Glomeromycota (P<0.05).
From the differences in the composition of the bacterial communities in the three land-use patterns, there were a total of 9 classifications that had significant differences among the three land-use patterns (Figure 7A): c__Acidobacteria, g__RB41, f__Nitrosomonadaceae, o__Acidimicrobiales, g__Sphingomonas, o__Gaiellales, c__Actinobacteria, f__JG34-KF-161, and c__KD4-96. There were significant differences between the four classifications of forest and grassland (Figure 7B): c__Acidobacteria, o__Acidimicrobiales, f__Nitrosomonadaceae, and f__Elev-16S-1332. There were significant differences between the 8 classifications of forest and plough (Figure 7C): c__Acidobacteria, g__RB41, g__Sphingomonas, f__JG34-KF-161, o__Acidimicrobiales, c__Gemmatimonadetes, c__Actinobacteria, and c__KD4-96. There were significant differences between the 9 classifications of grassland and plough (Figure 7D): g__RB41, f__Gemmatimonadacese, o__Acidimicrobiales, g__Sphingomonas, f__Nitrosomonadaceae, o__Gaiellales, c__Actinobacteria, f__JG34-KF-161, and p__Saccharibacteria.
From the difference in the abundance of the classification of fungal communities in the three land-use patterns, a total of five classifications had significant differences (Figure 8A): k_Fungi, Inocybe, p_Ascomycota, Mortierella, and Guehomyces. There were significant differences between 15 classifications of forest and grassland (Figure 8B): Inocybe, p_Ascomycota, k_Fungi, o_Geoglosssales, Cortinarius, f_Thelephraceae, Rhizoplagus, IIyonectria, Myrothecium, o_Sebacineles, o_Microascales, o_SoCCAriales, Paraphoma, Ramicandelaber, and Apodus. There were significant differences between 15 classifications of forest and plough (Figure 8C): Inocybe, k_Fungi, Morticrella, Chaetomium, f_Lasioshaenaceae, Fusarium, Guehomyces, Cortinatius, Microdochium, o_Lpeosporales, o_Lpeosporales, f_Davidellaceae, f_Glomeraceae, Cryptococcus, and Schizothecium. There were significant differences between the 15 classifications of grassland and plough (Figure 8D): p_Ascomycota, Mortierella, Chaetomium, f_Lasioshaenaceae, Guehomyces, o_Geoglossales, o_Lpeosporales, o_Lpeosporales, Microdochium, Geopora, Cryptococcus, Schizothecium, Stachypotrys, f_Thelephraceae, and Talaromyces.
Functions of soil bacterial and fungal communities in different land-use modes
Using the PICRUSt function prediction software to analyse the soil bacterial community functions in different land-use patterns, it can be seen from Figure 9A that the bacterial community functions are mainly amino acid transport and metabolism; energy production and conversion; signal transduction mechanisms; cell wall/membrane biogenesis; transcription; carbohydrate transport and metabolism; inorganic ion transport and metabolism; translation, ribosomal structure and biogenesis; lipid transport and metabolism; posttranslational modification, protein turnover; coenzyme transport and metabolism; secondary metabolite biosynthesis, transport and catabolism; nucleotide transport and metabolism; defence mechanisms; cell cycle control, cell division, chromosome partitioning; RNA processing and modification; and chromatin structure and dynamics. It can be seen from Table 3 that except for the three functions of intracellular trafficking, secretion, and vesicular transport, cytoskeleton, and extracellular structures, there were no significant differences in the other functions.
Table 3 Functional categories of soil bacterial communities in different land uses patterns
Functional categories
|
Grassland
|
Forest
|
Grassland
|
p
|
Amino acid transport and metabolism
|
2156599.2±108447.2
|
2120358.2±116315.2
|
1748427.5±205193.5
|
0.000**
|
Energy production and conversion
|
1928593.2±107958.5
|
1908954.6±90947.3
|
1528709.8±219359.1
|
0.000**
|
Signal transduction mechanisms
|
1803505.5±137977.5
|
1923574.2±68798.7
|
1535812.2±264067.1
|
0.005**
|
Cell wall/membrane/envelope biogenesis
|
1729648.6±169565.4
|
1852972.3±88768.4
|
1548832.8±227847.3
|
0.025**
|
Transcription
|
1779757.8±133546.2
|
1641553.8±94778.1
|
1340401.2±140126.1
|
0.000**
|
Carbohydrate transport and metabolism
|
1595887.6±117559.2
|
1558833.6±67370.7
|
1255254.2±117630.2
|
0.000**
|
Replication, recombination and repair
|
1386877.8±95824.8
|
1462371.2±37611.2
|
1212317.6±105834.3
|
0.000**
|
Inorganic ion transport and metabolism
|
1319226.6±48655.4
|
1335140.6±54643.4
|
1186993.3±131597.2
|
0.019**
|
Translation, ribosomal structure and biogenesis
|
1301982±66153.5
|
1344664.6±47191.1
|
1160419.5±100831.4
|
0.002**
|
Lipid transport and metabolism
|
1206223.8±72042.6
|
1101692.2±73651.1
|
915392.6±157000.6
|
0.001**
|
Posttranslational modification, protein turnover
|
1050106.8±77086.9
|
1093560.5±29778.8
|
915481±137360.9
|
0.012**
|
Coenzyme transport and metabolism
|
1073806.2±62419.2
|
1086196.8±43176.4
|
869490.5±116424.1
|
0.000**
|
Secondary metabolites biosynthesis, transport and catabolism
|
689507.2±54717.2
|
604978.6±45849.2
|
515565±104471.65
|
0.003**
|
Nucleotide transport and metabolism
|
603415.3±30170.3
|
606498.6±23482.8
|
508177.6±39370.8
|
0.000**
|
Intracellular trafficking, secretion, and vesicular transport
|
537396±63154.4
|
596019.2±41039.5
|
501255±90025.5
|
0.081
|
Defense mechanisms
|
568486±63298.95
|
587746.8±28131.8
|
460686.3±52408.5
|
0.001**
|
Cell motility
|
354935.2±50017.4
|
418557.2±34696.3
|
349513±63870.7
|
0.060
|
Cell cycle control, cell division, chromosome partitioning
|
248219.3±8540.1
|
256330.6±10094.2
|
221646.2±20168.9
|
0.002**
|
RNA processing and modification
|
15313.8±1803.7
|
14234.6±1124.5
|
10122.8±2365.9
|
0.000**
|
Chromatin structure and dynamics
|
12625.6±1368.4
|
13349±445.5
|
10521±2049.6
|
0.011**
|
Cytoskeleton
|
4539.8±903.2
|
5484.8±723.7
|
5335.5±1080.1
|
0.191
|
Extracellular structures
|
17±11.5
|
12.5±6.1
|
19.1±12.7
|
0.584
|
Note:Mean values (means ± SD, n=6) , Significant levels are indicated at the *P < 0.05; **P < 0.01.
Using FUNGuild software to analyse soil fungal community functions under different land-use patterns, it can be seen from Figure 9B that the fungal community functions in the three land patterns are: ectomycorrhizal; animal pathogen; endophyte; dung saprotroph; plant pathogen; arbuscular mycorrhizal; fungal parasite; endomycorrhizal-plant pathogen; bryophyte parasite-ectomycorrhizal; and clavicipitaceous endophyte-plant pathogen. As seen from Table 4, there are significant differences in the functions of the five communities in terms of ectomycorrhizal, animal pathogen, endophyte, dung saprotroph, and fungal parasite. After the grassland was transformed into forest, the ectomycorrhizal functional group increased significantly. After the grassland was transformed into plough, the functional groups of animal pathogens, endoparasites, and faecal saprophytic organisms increased significantly.
Table 4 Functional categories of soil fungal communities in different land use patterns
Functional categories
|
Grassland
|
Forest
|
Grassland
|
p
|
Ectomycorrhizal
|
46.3±52.8
|
25381.6±5074.5
|
647.5±271.8
|
0.000**
|
Animal Pathogen
|
414.6±286.6
|
337.5±281.2
|
3374.1±2621.5
|
0.005**
|
Endophyte
|
430.6±447.8
|
425.6±287.2
|
2532.5±772.1
|
0.000**
|
Dung Saprotroph
|
56.3±92.4
|
28±20.1
|
3004.6±2592.9
|
0.005**
|
Plant Pathogen
|
320.5±279.3
|
70.3±40.2
|
1822.1±2106.1
|
0.054
|
Arbuscular Mycorrhizal
|
603.8±622.7
|
20.33±31.15
|
725.8±708.1
|
0.088
|
Fungal Parasite
|
209.6±312.4
|
53.1±53.6
|
378.8±148.1
|
0.043*
|
Endomycorrhizal-Plant Pathogen
|
271±387.9
|
40.8±30.2
|
27±14.8
|
0.142
|
Bryophyte Parasite-Ectomycorrhizal
|
6.5±9.4
|
1±1.09
|
0±0
|
0.122
|
Clavicipitaceous Endophyte-Plant Pathogen
|
0±0
|
0±0
|
1.66±4.8
|
0.391
|
Redundancy analysis of soil bacterial and fungal communities and physicochemical properties in different land-use patterns
The relationship between soil physical and chemical properties and the community composition of bacteria and fungi at the OTU level was analysed using CCA, and the results are shown in Figure 10. The first sequence axis of bacteria explained 29.61% of all information, and the second sequence axis explained 21.07% of all information. pH is the main factor affecting the composition of grassland bacterial communities, and soil nutrients such as O3--N, TP, AP, and NH4+-N are the main factors affecting the composition of bacterial communities in forests and ploughs. The first sequence axis of fungi explained 15.93% of all information, and the second sequence axis of fungi explained 14.41% of all information. pH is the main factor affecting the composition of grassland fungal communities, MC is the main factor affecting the composition of forest fungal communities, and NO3--N, TP and AP are the main factors affecting the composition of plough fungal communities.