Variation in Vegetation Characteristics
The composition, diversity, coverage and biomass of herb communities were strongly affected by land use from abandoned farmland (Tables 1 and 2). The significant increase in canopy closure from grassland (GL) to macrophanerophyte forest (MF) resulted in population classification changed from shady plants to light plants. The light plants such as Lespedeza floribunda B. and Tripolium vulgare N. were the dominant species in GL. The Dendranthema indicum and Patrinia heterophylla B. were gradually becoming the dominant species to replace the xerophytic species in SF. The shady plants such as Poa sphondylodes T. increased significantly in MF. The LB, FRB, and HPlant of undergrowth plant community increased significantly from GL to MF. The herb coverage (HC) of shrub forest (SF) was 51.75% and 97.72% higher than that of GL and MF, respectively. In addition, the HB and SPlant of SF were the largest compared to the other two land uses.
Table 2
The vegetation characteristics in the three land types.
Land types
|
HC (%)
|
HB (kg·m− 2)
|
LB (kg·m− 2)
|
FRB (kg·m− 2)
|
HPlant
|
SPlant
|
GL
|
53.33 ± 5.88b
|
0.29 ± 0.04ab
|
0.12 ± 0.01c
|
0.13 ± 0.01c
|
2.54 ± 0.13b
|
4.51 ± 0.10b
|
SF
|
80.93 ± 4.30a
|
0.40 ± 0.06a
|
0.31 ± 0.01b
|
0.16 ± 0.01b
|
2.50 ± 0.04b
|
4.78 ± 0.06a
|
MF
|
40.93 ± 4.04b
|
0.22 ± 0.01b
|
0.51 ± 0.01a
|
0.18 ± 0.01a
|
2.68 ± 0.11a
|
4.67 ± 0.33ab
|
The values are mean ± standard error. Different letters indicate significant differences (p < 0.05) among different land use types based on a one-way ANOVA followed by an LSD test. HC: herb coverage; HB: herb biomass; LB: litter biomass; FRB: fine root biomass; HPlant: Shannon-Wiener diversity index; SPlant: Margalef richness index; GL: grassland; SF: Caragana korshinskii; MF: Robinia pseudoacacia. |
Variation In Soil Properties
The SOC, STN, DOC, SNN, SW, and Clay were significantly different among different secondary succession patterns (Table 3). The contents of SW and SAN were greater in MF sites, relative to GL and SF sites. Compared with GL sites, Clay, STN and SNN contents were higher in SF and MF sites, while SBD was inverted. Furthermore, compared with the GL sites, the SOC contents increased by 14.89% and 17.80% in the SF and MF sites, respectively; the DOC contents increased by 75.42% and 102.76% in the SF and MF sites, respectively. In addition, STP, SAP, and pH did not differ significantly among different land use patterns.
Table 3
The soil physicochemical properties in the three land types.
Land types
|
GL
|
SF
|
MF
|
SW (%)
|
8.32 ± 0.46b
|
8.81 ± 0.36b
|
11.56 ± 0.36a
|
SBD (g.cm− 3)
|
1.21 ± 0.01a
|
1.18 ± 0.01b
|
1.16 ± 0.01b
|
Clay (%)
|
19.12 ± 0.42b
|
20.79 ± 0.51a
|
21.84 ± 0.42a
|
pH
|
8.35 ± 0.01a
|
8.32 ± 0.02a
|
8.30 ± 0.03a
|
SOC (g.kg− 1)
|
6.18 ± 0.17c
|
7.10 ± 0.33b
|
7.28 ± 0.24a
|
STN (g.kg− 1)
|
0.54 ± 0.03b
|
0.63 ± 0.01a
|
0.67 ± 0.03a
|
STP (g.kg− 1)
|
0.44 ± 0.01a
|
0.45 ± 0.01a
|
0.45 ± 0.01a
|
DOC (mg.kg− 1)
|
97.56 ± 3.94c
|
171.14 ± 4.87b
|
197.81 ± 3.90a
|
SAN (mg.kg− 1)
|
1.70 ± 0.02b
|
1.65 ± 0.02b
|
2.08 ± 0.01a
|
SNN (mg.kg− 1)
|
10.26 ± 0.22b
|
11.53 ± 0.32a
|
12.00 ± 0.13a
|
SAP (mg.kg− 1)
|
4.71 ± 0.03a
|
4.60 ± 0.01a
|
4.60 ± 0.12a
|
The values are mean ± standard error. Different letters indicate significant differences (p < 0.05) among different land use types based on a one-way ANOVA followed by an LSD test. SWC: soil water content; SBD: soil bulk density; SOC: soil organic carbon; STN: soil total nitrogen; STP: soil total phosphorus; DOC: soil dissolved organic carbon; SAN: soil ammonia nitrogen; SNN: soil nitrate nitrogen; SAP: soil available phosphorus; GL: grassland; SF: Caragana korshinskii; MF: Robinia pseudoacacia. |
Variation In Microbial Indexes
Soil Microbial Biomass and Enzyme Activities
Soil microbial biomass and enzyme activities significantly differed among different secondary succession patterns (Table 4). Compared with GL, MBC, MBN, MBP, BG, NAG + LAP, and ALP increased by 2.22, 2.02, 1.26, 1.15, 0.94, and 1.76 times after the artificial secondary succession, respectively, and those of MF were the largest. In addition, MBC, MBN, and ALP showed significant differences between grassland and afforestation. Notably, the NAG + LAP value was the lowest in SF than GL and MF.
Table 4
The soil microbial biomass and enzyme activity in the three land types.
Land types
|
MBC
(mg.kg− 1)
|
MBN
(mg.kg− 1)
|
MBP
(mg.kg− 1)
|
BG
(nmol.g− 1.h− 1)
|
NAG + LAP
(nmol.g− 1.h− 1)
|
ALP
(nmol.g− 1.h− 1)
|
GL
|
157.57 ± 6.33c
|
28.26 ± 1.53c
|
8.60 ± 0.31b
|
30.47 ± 0.93b
|
80.63 ± 2.96a
|
72.28 ± 1.36c
|
SF
|
248.56 ± 5.21b
|
43.15 ± 0.87b
|
9.80 ± 0.35b
|
29.11 ± 0.52b
|
66.80 ± 1.65b
|
87.91 ± 1.32b
|
MF
|
449.10 ± 2.51a
|
71.15 ± 0.78a
|
11.87 ± 0.35a
|
41.19 ± 0.55a
|
84.48 ± 3.08a
|
166.74 ± 3.18a
|
The values are mean ± standard error. Different letters indicate significant differences (p < 0.05) among different land use types based on a one-way ANOVA followed by an LSD test. MBC: soil microbial biomass carbon; MBN: soil microbial nitrogen; MBP: soil microbial phosphorus; BG: ꞵ-1,4-glucosidase; NAG: ꞵ-1,4-N-acetylglucosaminidase; LAP: leucine aminopeptidase; ALP: alkaline phosphatase; GL: grassland; SF: Caragana korshinskii; MF: Robinia pseudoacacia. |
Diversity And Composition Of Microbial Communities
The HBacteria was the lowest at GL and then increased at SF with a maximum of 7.36 at MF (Fig. 1a). The SBacteria of GL, SF, and MF were 2.52×103, 2.98×103, and 3.33×103, respectively. Compared with MF, SFungi decreased by 11.72 and 10.15% at GL and SF, respectively (Fig. 1b).
The soil bacteria was dominated by Actinobacteria (29.76%) and Acidobacteria (22.42%), followed by Proteobacteria (20.39%), Chloroflexi (11.94%), Gemmatimonadetes (8.87%), and Nitrospirae (2.86%) (Fig. 2a). The relative abundance of Actinobacteria was the highest in the GL than the SF and MF. The relative abundance of Proteobacteria was greatest in MF compared to the other three land uses. However, the relative abundance of Acidobacteria showed different changes, and that of SF (26.59%) was higher relative to GL (19.67%) and MF (21.01%). In addition, Ascomycota (40.11%), Basidiomycota (17.09%), Zygomycota (6.64%), and Cercozoa (1.09%) dominated the fungal community composition in all sites (Fig. 2b). Compared with GL, the relative abundance of Ascomycota increased by 1.60 and 1.70 times in SF and MF, respectively. The relative abundance of Basidiomycota decreased significantly from GL to MF. The relative abundances of Zygomycota, and Cercozoa were higher in MF compared to those in the other land uses.
The PCA method, employed to assess the variations in community composition and structure among the sites, and soil microbial communities differ significantly at each land use (Fig. 3). The analysis reinforces the view that the soil bacterial and fungal communities were significantly different from each other at the sites of the three land uses.
Relationships Between Plant Characteristics, Soil Variables, And Microbial Communities
Plant characteristics significantly affected the diversity of soil bacteria (Figs. 4 and 5). The LB and FRB were significantly positively correlated with SPlant, soil microbial biomass (MBC, MBN, and MBP), and enzyme activity (BG and ALP) (Fig. 4 and S2). LB and FRB were significantly positively correlated with Proteobacteria, Zygomycota and Cercozoa, while negatively correlated with Actinobacteria and Basidiomycota (Fig. 5).
Soil properties have important effects on the diversity and composition of soil microorganisms (Figs. 4 and 5). SFungi, soil microbial biomass, and enzyme activity were significantly positively correlated with SW, SOC, STN, DOC, and SNN, and negatively correlated with SBD and SAP (Figs. 4 and S2). However, HBacteria reversed. In addition, Acidobacteria showed significant negative correlation with SW, Clay, SOC, STN, STP, DOC, SAN, and SNN, and positive correlation with SBD, pH, and SAP, but Proteobacteria and Nitrospirae were reversed (Fig. 5). DOC and SAN were significantly negatively correlated with Basidiomycota and positively correlated with Zygomycota and Cercozoa.
The responses of soil bacterial and fungal communities to plant characteristics and soil properties were heterogeneous (Figs. 6 and 7). The contributions of plant and soil can explain 76.95% of soil bacterial diversity and 90.64% of bacterial composition (Figs. 6a and 7a), in which the effect of plant characteristics on diversity was more intense. The relative effects of HB, HC, SPlant, and HPlant on the diversity of soil bacteria were 10.84, 10.43, 10.30, and 10.19%, respectively, which were more significant than other variables (Fig. 6a). The contributions of plant and soil can explain 88.14% of the diversity of soil fungi and 71.39% of the composition of fungi (Figs. 6b, 7b). The effect of soil properties on composition was more obvious. The relative effects of LB, SAN, and SW on the composition of soil fungal communities were 6.71, 6.41, and 6.25%, respectively, which were more significant than other variables (Fig. 7b). According to the PLS-PM, we found that restoration patterns significantly regulated plant characteristics (HC, HB, LB, and FRB) and soil properties (SW, pH, SOC, STN, and SNN) (Fig. 8). Notably, soil properties significantly affected the diversity of soil bacterial and fungal communities, and plant characteristics were closely related to the dominant phyla of soil microbial communities.