Next Article in Journal
Infiltration and Water Use Efficiency of Maize Fields with Drip Irrigation and Biodegradable Mulches in the West Liaohe Plain, China
Previous Article in Journal
Disentangling Relationships among the Alpine Species of Luzula Sect. Luzula (Juncaceae) in the Eastern Alps
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Comparison of Soil Bacterial Communities under Canopies of Pinus tabulaeformis and Populus euramericana in a Reclaimed Waste Dump

1
Engineering Research Center of Ministry of Education for Mine Ecological Restoration, China University of Mining and Technology, Xuzhou 221116, China
2
School of Public Policy and Management, China University of Mining and Technology, Xuzhou 221116, China
3
School of Environment Science & Spatial Informatics, China University of Mining and Technology, Xuzhou 221116, China
4
Observation and Research Station of Ecological Restoration for Chongqing Typical Mining Areas, Ministry of Natural Resources, Chongqing Institute of Geology and Mineral Resources, Chongqing 401120, China
*
Authors to whom correspondence should be addressed.
Plants 2023, 12(4), 974; https://doi.org/10.3390/plants12040974
Submission received: 20 January 2023 / Revised: 14 February 2023 / Accepted: 15 February 2023 / Published: 20 February 2023

Abstract

:
To compare the effects of different remediation tree species on soil bacterial communities and provide a theoretical basis for the selection of ecosystem function promotion strategies after vegetation restoration, the characteristic changes in soil bacterial communities after Pinus tabulaeformis and Populus euramericana reclamation were explored using high-throughput sequencing and molecular ecological network methods. The results showed that: (1) With the increase in reclamation years, the reclaimed soil properties were close to the control group, and the soil properties of Pinus tabulaeformis were closer to the control group than those of P. euramericana. (2) The dominant bacteria under the canopies of P. tabulaeformis and P. euramericana was the same. Proteobacteria, Actinobacteria, Acidobacteria, Chloroflexi, Gemmatimonadetes, Planctomycetes, Bacteroidetes, and Cyanobacteria were the dominant bacteria in the restored soil, accounting for more than 95% of the total abundance. The average values of the Shannon diversity index, Simpson diversity index, Chao 1 richness estimator, and abundance-based coverage estimator of the bacterial community in the P. euramericana reclaimed soil were higher than those in the P. tabulaeformis reclaimed soil. The influence of reclamation years on the bacterial community of samples is greater than that of species types. (3) The results of ecological network construction showed that the total number of nodes, total number of connections, and average connectivity of the soil bacterial network under P. euramericana reclamation were greater than those under P. tabulaeformis reclamation. The bacterial molecular ecological network under P. euramericana was more abundant. (4) Among the dominant bacteria, the relative abundance of Actinobacteria was negatively correlated with soil pH, soil total nitrogen content, and the activities of urease, invertase, and alkaline phosphatase, while the relative abundance of Proteobacteria and Bacteroidetes was positively correlated with these environmental factors. The relationship between the soil bacterial community of P. tabulaeformis and P. euramericana and the environmental factors is not completely the same, and even the interaction between some environmental factors and bacteria is opposite.

1. Introduction

In 2019, the Ministry of Natural Resources of the People’s Republic of China successively issued the Opinions on Establishing an Incentive Mechanism to Accelerate the Promotion of Ecological Restoration of Mines and the Opinions of the Ministry of Natural Resources on Exploring and Utilizing Marketization to Promote Ecological Restoration of Mines, to accelerate the promotion of ecological restoration of mines and solve outstanding problems, such as many historical arrears, many practical contradictions, and insufficient investment in ecological restoration of mines. It can be seen that promoting land reclamation and ecological restoration is an important way to repair damaged mine ecological functions and realize the sustainable development of the mining ecosystem [1]. From 2001 to 2019, China’s cumulative mine ecological restoration area reached more than 1 million hectares, and in 2020, the newly increased mine restoration area was approximately 48,000 hectares [2]. However, the effect of the ecosystem after ecological restoration and the resilience and adaptability of the ecosystem will be the focus of future research [3]. Soil microorganisms play an important role in maintaining ecosystem stability and vegetation succession restoration [4]. Soil bacterial communities play an important role in regulating soil nutrient cycling and plant species coexistence. The composition and structural changes of soil bacterial communities are often used to reflect the changes in soil environmental quality [5]. Therefore, the analysis of the characteristics of the soil microbial community after reclamation can provide a basis for decision making to improve the effectiveness of the soil ecosystem after reclamation.
Currently, research on the soil bacterial community after reclamation mainly focuses on the following points: first, research on the change in soil microbial characteristics after restoration. Sun et al. studied the response of soil microorganisms to vegetation restoration in coal mining subsidence areas and microbial changes [6]. Li Yuanyuan et al. studied the impact of surface subsidence on soil microbial diversity [7]. Luo et al. suggested that while mining subsidence was inhibited, vegetation rehabilitation promoted the soil physicochemical properties [8]. Dimitriu et al. suggested that the structure of soil bacteria after vegetation rehabilitation was dependent on pH and other abiotic characteristics [9]. Soil bacteria could serve as sensitive indicators of land degradation and ecological restoration [10,11]. Second, the characteristics of soil microorganisms in different remediation years: William et al. and Wanglong et al. studied the changes in soil biological communities in different recovery and evolution stages [12,13]; Hou et al. studied the change rule of soil microbial community structure in reclamation areas with reclamation years [14]. After 20 years of land reclamation in the coal mining area, the number of soil bacteria was still lower than that in an undisturbed area, but shrub coverage played a key role in ecological restoration [15]. After 5–14 years of vegetation rehabilitation, significant interactions were observed between plants and bacteria [16]. The third is about the impact of different reclamation methods on soil microbial community restoration. The diversity and composition of bacterial and fungal communities play an irreplaceable role in decomposition and nutrient cycling [17,18]. Previous studies showed that significant differences existed in the relative abundance of bacteria and fungi after restoration [19,20,21]. Zhang Lin et al. studied the impact of different plant combination planting methods on the soil bacterial community in the reclamation area [22]. Medicago sativa L. (Alfalfa) and Bromus inermis Leyss. (Smooth brome) are widely used as a community-building species for ecological restoration in northern China [19,23,24]. Alfalfa, a high-quality perennial legume, could improve the soil’s texture and nutrients with a low degree of degradation [25,26]. A short-term vegetation restoration significantly increased the complexity and stability of fungi ecological networks, but the opposite was the case with the bacteria. which confirmed that ecological restoration by sowing was favorable to the amelioration of soil fungi complexity and stability in the short term [27].
However, there are few studies on the changes in soil microorganisms in different vegetation configuration modes and different reclamation years. In the study of soil microorganisms, traditional research methods, such as various diversity indices, can only excavate the composition and abundance information of microbial communities in the surface layer; the amount of microbial information data obtained using high-throughput sequencing is rich and huge. For this reason, in this study, we selected soil with Pinus tabulaeformis and Populus euramericana as the reclamation tree species in the different waste dumps of the Heidaigou open-pit coal mine as the study area and used high-throughput technology to obtain soil microbial information. Furthermore, we used the molecular ecological network to reveal and compare the changes and characteristics of the bacterial communities in the soil reclaimed using P. tabulaeformis and P. euramericana and compared the effects of different vegetation reclamation models on soil bacterial communities, providing a theoretical basis for the selection of vegetation reclamation.

2. Materials and Methods

2.1. Overview of the Study Area

The study area is located in the Heidaigou open-pit coal mine in the Zhungeer Coalfield, east of Zhungeer County, Ordos City, Nei Monggol Autonomous Region, with coordinates 111°12′53″–111°20′02″ E and 39°43′11″–39°47′41″ N (Figure 1). The mining area is located east of Ordos. The main geomorphic type is low mountains and hills, and the overall terrain is high in the west and low in the east. The branch ditches of the Heidai Valley and Dajiaoshao Valley are the main valleys in the area. The mining area has a semi-arid continental climate in the middle temperate zone. The soil is mainly castanozems, the zonal vegetation is typical grassland, and most of the artificial forests are sparse forests made up of vegetation types, such as P. tabulaeformis, P. euramericana, and Platycladus orientalis (L.) Francoptmxjjkmsc. The farmland is mainly dry and dispersed. The surface is directly damaged due to open-pit mining. The method of landform reconstruction and vegetation reconstruction is adopted for restoration. The soil cover is sourced from topsoil stripped from open-cut mining, with a thickness of approximately 1.0 m. The soil is mainly loess, characterized by a relatively infertile, paucity of humus, and has not undergone any processes of maturation. The vegetation species to be restored are mainly P. tabulaeformis and P. euramericana.
This sampling object was used to select the reclaimed land under different restoration years and different tree species. The north waste dump (15 years of reclamation), the east and west waste dump (12 years of reclamation), the inner waste dump (9 years of reclamation), and the Yinwan waste dump (6 years of reclamation) after the restoration of the Heidaigou open-pit coal mine were selected as the sampling sites, and the sites not affected by coal mining subsidence were selected as the control sites. The locations of the sampling sites are shown in Figure 1.

2.2. Sample Collection and Analysis

From 17–21 July 2019, sample sites rehabilitated using P. tabulaeformis and P. euramericana were set up in five waste dump sites; the control site, which was not affected by mining, was set up with P. tabulaeformis and P. euramericana (Table 1). Five samples were collected from each sample area, and a total of 60 samples were collected. Five hundred grams of 0–10 cm mixed soil samples was collected using the five-point sampling method. The ring knife was used for measuring the soil bulk density. The soil samples were collected with a sterile shovel. After being mixed evenly, part of the soil samples was put into an aluminum box for measuring the soil moisture, part was put into a special sterile sealed bag, and part was put into a sterile test tube. The soil samples in the test tube were immediately put into the vehicle-mounted refrigerator for storage at −20 °C and then mailed to Shanghai Personalbio Biotechnology Co., Ltd. (Shanghai, China) for high-throughput sequencing.
A pH meter (Alipay Biotechnology Co., Ltd., Hangzhou, China) was used to measure the soil pH; a Topsizer laser particle size analyzer (OMCC Instrument Co., Ltd., Zhuhai, China) was used to measure soil clay, silt, and sand contents; and an Automatic Kjeldahl nitrogen meter (Qingdao Jingcheng Instrument Co., Ltd., Qingdao, China) was used to measure soil total nitrogen. Furthermore, an ultraviolet absorption spectrophotometer (Qingdao Jingcheng Instrument Co., Ltd., Qingdao, China) was used to measure the soil total phosphorus content, soil organic matter content, soil alkali hydrolyzable nitrogen, soil urease, soil alkaline phosphatase, and soil sucrase activity. Soil total potassium was measured using a flame spectrophotometer (Shanghai Changxi Instrument & Meters Co., Ltd., Shanghai, China).

2.3. DNA Extraction and High-Throughput Sequencing

The 16S rRNA genes of soil bacteria were sequenced within three days of sampling. The DNA of soil samples was extracted using the E.Z.N.A® Soil DNA Kit (Omega Bio-tek, Norcross, GA, USA) according to the manufacturer’s protocols. The V4–V5 area of the 16S rRNA of soil bacteria was amplified via polymerase chain reaction (PCR). The applied degenerate primers were 515F 5′-barcode-GTGCCAGCMGCCGCGG-3′ and 907R 5′-CCGTCAATTCMTTT RAGTTT-3′.
The PCR amplification products were detected using electrophoresis, the target fragments were cut and recycled, and the fluorescence quantification was performed based on the electrophoresis detection results. The TruSeq Nano DNA LT Library Prep Kit of Illumina Company was used to prepare the sequencing library and to perform purification, quality inspection, and quantification. The qualified library was diluted by gradient and mixed according to the required sequencing amount in the corresponding proportion, and finally, the MiSeq Agent Kit V3 (600 cycles) was used as the reagent for computer sequencing. The optimal sequencing length of the target fragment was 200–450 bp.

2.4. Molecular Ecological Network Analysis

Based on the reclaimed vegetation, the samples were divided into two groups: P. tabulaeformis and P. euramericana, and the OTU with the highest abundance of 75% was selected for each group to construct and analyze the molecular ecological network. The construction process of the ecological network is found in MENA (http://ieg4.rccc.ou.edu/mena, 15 August 2019). The specific analysis process is as follows: High-throughput sequencing data were obtained to determine the number of different OTUs for each sample; the relevant abundance of OTU numbers was standardized. The Spearman correlation coefficient was used to calculate the pairwise similarity of each OTU and to generate the similarity matrix. Based on the random matrix theory (RMT), the derived threshold was determined, and the adjacency matrix was constructed.
After the construction of the molecular ecological network, the topological structure and modular analysis of the network were performed. Topological analysis was used to verify whether the results of network construction meet the scale-free, small-world, and modular characteristics of molecular ecological networks, and to test the reliability of the construction results [28]. Modularization analysis was used to judge the role of nodes in the network by calculating and comparing the connectivity between modules and connectivity within modules of nodes, dividing the functions of network nodes [29], and finally, visualizing the molecular ecological network using Cytoscape software.

2.5. Data Analysis and Processing

Python’s matplotlib package was used to draw a bar graph of bacterial abundance at the phylum level and a heat map of bacterial abundance at the class level in the soil samples. The Pearson correlation between soil physical and chemical properties and enzyme activity was analyzed using SPSS 25.0. Common indices for calculating alpha diversity include the Simpson diversity index, Shannon diversity index, Chao 1 richness index, and abundance-based coverage estimator (ACE) richness index. Principal component analysis (PCA) and nonmetric multidimensional scaling (NMDS) were used to reflect the beta diversity of the bacterial communities.

3. Results

3.1. Physical and Chemical Properties and Enzyme Activity Characteristics of Soil under Different Reclamation Tree Species and Different Years

The soil physical and chemical properties of different reclamation tree species are shown in Figure 2. There are certain differences in soil physical and chemical properties and enzyme activities under P. tabulaeformis and P. euramericana. There is no significant difference in the physical properties of the soil under the two types of plants. The average soil water content under P. tabulaeformis is 1.12% higher than that under P. Euramericana, while the average values of bulk density and sand content under P. tabulaeformis are 0.05 g/cm2 and 2.63% lower than that under P. euramericana. The average pH value and average cation exchange capacity (CEC) of the soil under P. tabulaeformis are higher than those of P. euramericana by 0.01 and 1.25 coml/kg, respectively, while the average total nitrogen, total phosphorus, total potassium, and soil organic matter contents are relatively low by 0.01%, 0.06 g/kg, 0.33 g/kg, and 1.89 g/kg, respectively. The activities of soil urease, sucrase, and alkaline phosphatase under P. tabulaeformis are 0.18 mg/g, 3.72 mg/g, and 0.22 mg/g lower than those under P. euramericana, respectively. After 15 years of reclamation, the soil organic matter content and urease activity were significantly different from the control group, and bulk density, soil water content, pH, cation exchange capacity, total nitrogen, total phosphorus, total potassium, and invertase activity were basically close to the control group. In short, with the increase in reclamation years, the reclaimed soil properties were close to those of the control group, and the soil properties of P. tabulaeformis were closer to those of the control group than those of P. euramericana.
With the increase in reclamation years, the soil bulk density gradually decreased from 2.45 g/cm2 to 2.17 g/cm2, and the proportion of soil sand particles gradually increased from 64.32% to 75.29%, while the soil water content had no obvious change. The soil pH gradually decreased from 8.29 to 8.2 with the increase in reclamation years. The cation exchange capacity, soil organic matter, total nitrogen, and total potassium content increased significantly with the increase in reclamation years, from 11.5 coml/kg, 7.09 g/kg, 0.03%, and 12 g/kg to 14.45 coml/kg, 11.73 g/kg, 0.05%, and 12.35 g/kg, respectively. The total phosphorus of the soil did not change significantly with the increase in reclamation years. The activities of urease, sucrase, and alkaline phosphatase increased significantly with the increase in reclamation years, from 0.13 mg/g, 8.44 mg/g, and 0.52 mg/g to 0.47 mg/g, 45.26 mg/g, and 0.81 mg/g, respectively.

3.2. Characteristics of Bacterial Community Structure and Diversity in the Reclaimed Soil of P. tabulaeformis and P. euramericana

3.2.1. Characteristics of the Bacterial Community Structure in the Reclaimed Soil of P. tabulaeformis and P. euramericana

The bacterial community composition of each sample at the phylum level was statistically analyzed (Figure 3). At the phylum level of the samples from the waste dump of the Heidaigou open-pit coal mine and the control area, the bacterial community with high abundance mainly includes Proteobacteria, Actinobacteria, Acidobacteria, Chloroflexi, Gemmatimonadetes, Planctomycetes, Bacteroidetes, and Cyanobacteria, accounting for more than 95% of the total abundance.
The relative abundance of Proteobacteria was the largest, ranging from 27.34% to 39.34%. In 12 a and 15 a of reclamation, the relative abundance of Proteobacteria in P. euramericana was higher than that of P. tabulaeformis. However, the relative abundance of P. tabulaeformis was lower than that of P. euramericana in 6 a and 9 a of reclamation. Proteobacteria participate in the soil nitrogen cycle process and help to restore the improvement of soil quality. The relative abundance of Actinobacteria was 16.55–36.82%, which was increasing with the increase in reclamation years. Actinobacteria was a saprophytic aerobic bacterium that preferred neutral or slightly alkaline, promoting the growth of rhizosphere bacteria, symbiotic bacteria, and endophytic bacteria. The relative abundance of Acidobacterium was 7.32–17.12%. In the samples of P. tabulaeformis, the abundance was increasing with the increase in reclamation years. This bacterium plays an important role in the degradation of plant residues. The abundance of Chloroflexi in P. tabulaeformis samples decreased with the increase in reclamation years. The nutrition mode of Chloroflexi was extremely diverse. From the perspective of vegetation type, at the phylum level, the relative abundance of Actinobacteria in the reclaimed soil of P. tabulaeformis is 0.04% higher than that in the reclaimed soil of P. euramericana. Furthermore, the relative abundance of Acidobacteria and Cyanobacteria in the reclaimed soil of P. tabulaeformis is 0.02% lower than that in the reclaimed soil of P. euramericana.
From the perspective of the changing trend of bacterial community structure, Proteobacteria, Actinobacteria, Acidobacteria, Gemmatimonadetes, and Cyanobacteria have a high response to the change in reclamation years. The relative abundance of Proteobacteria, Gemmatimonadetes, and Cyanobacteria decreased by 2.43%, 3.73%, and 7.61% on average each year, while the relative abundance of Actinobacteria and Acidobacteria increased by 8.31% and 3.08% on average each year.

3.2.2. Diversity of the Bacterial Community in the Reclaimed Soil of P. tabulaeformis and P. euramericana

The alpha diversity index can measure the community diversity of samples. At the same time, the Simpson diversity index, Shannon diversity index, Chao 1 richness estimator index, and ACE were selected for comparative analysis of soil bacterial community diversity in different vegetation reclamation models and different reclamation years. As shown in Figure 4, the Shannon index of the two tree species has a significant difference (p < 0.1), while the differences in other indices are not significant (p > 0.1), but the average values of the four indices of the bacterial community in the reclaimed soil of P. tabulaeformis are higher than those in that of P. tabulaeformis.

3.2.3. Beta Diversity of the Bacterial Community in the Reclaimed Soil of P. tabulaeformis and P. euramericana

Beta diversity analysis can measure the similarity between different community composition samples. The PCA method based on the Euclidean distance was used to analyze the OTU of each sample, and the results are shown in Figure 5a. The PCA1 axis can explain 35.55% of the difference in the results of the sample, and the PCA2 axis can explain 15.73% of the difference in the results of the sample. There are obvious differences between the sample points (C, W, E, and N) with longer reclamation years and the sample points (Y and I) with shorter reclamation years (Figure 5a). The distance between the samples with the same reclamation years is closer, indicating that they are more similar. The sample points of the same reclamation vegetation are scattered, indicating that the impact of the reclamation vegetation type on the soil bacterial community is less than the impact of the reclamation years. The difference in bacterial community composition with P. tabulaeformis as the reclamation vegetation is relatively larger than that with P. euramericana as the reclamation vegetation.
Based on the phylogenetic tree, we comprehensively considered the changes in species and species abundance, calculated the weighted unifrac distance between samples, and performed an NMDS analysis. The results are shown in Figure 5b. The sample points of P. tabulaeformis and P. euramericana are scattered, and the distance between samples with the same reclamation years is closer. This may be because the influence of reclamation years on the bacterial community of samples is greater than that of vegetation types, and this result is consistent with the result of the PCA method.

3.3. Analysis of Bacterial Molecular Ecological Network in the Reclaimed Soil of P. tabulaeformis and P. euramericana

3.3.1. Topological Structural Analysis of the Molecular Ecological Network

Topological analysis was used to verify whether the results of the network construction meet the scale-free, small-world, and modular characteristics of the molecular ecological network and to test the reliability of the network construction. The samples were divided into the P. tabulaeformis group and the P. euramericana group, and the number of OTUs in each group was 725 and 818, respectively. Based on the RMT theory, the two groups of data were used to derive an adjacency matrix and to generate a network at the threshold level of 0.960. Under this threshold, the chi-square value of the P. tabulaeformis group is 60.779, and that of the P. euramericana poplar group is 69.672, which belongs to the appropriate threshold level. The analysis of the network topology (Table 2) shows that the number of ecological network nodes in P. tabulaeformis and P. euramericana is 642 and 746, respectively. The number of ecological network connections in P. tabulaeformis and P. euramericana is 1518 and 2003, respectively. The R2 values of both groups are greater than 0.7, which conforms to the power law distribution and reflects the scale-free characteristics of the molecular ecological network. The average connectivity of P. tabulaeformis and P. euramericana is 4.729 and 5.370, respectively. The average clustering coefficients of P. tabulaeformis and P. euramericana are 0.541 and 0.579, respectively. The results reflect the small-world and modular characteristics of the molecular ecological network. The average connectivity, average clustering coefficient, and average path distance of the P. euramericana group are greater than those of the P. tabulaeformis group, indicating that the connection of the soil bacterial molecular ecological network of the P. euramericana group is more complex, and the nodes in the network are more closely connected with the adjacent nodes.

3.3.2. Modularization Analysis of the Molecular Ecological Network

The inter- and intra-module connectivity of nodes were calculated and compared to determine the role of nodes in the network. The modular analysis results are shown in Figure 6. The soil bacterial ecological network under P. tabulaeformis has six module hubs, of which OTU 19,113 and OTU 22,783 belong to Chloroflexi, OTU 12,216 and OTU 30,681 belong to Planctomycetes, OTU 8668 belongs to Proteobacteria, and OTU 979 belongs to Actinomycetes. The soil bacterial ecological network under P. euramericana has six module hubs, of which OTU 485, OTU 19,889, and OTU 2,580 belong to Planctomycetes, OTU 14,346 and OTU 6293 belong to Actinobacteria, and OTU 15,619 belong to Gemmatimonadetes. The soil bacterial ecological network under P. tabulaeformis has four connection nodes, among which OTU 24,802, OTU 25,594, and OTU 185 belong to Actinobacteria, and OUT 79,908 belongs to Proteobacteria. The soil bacterial ecological network under P. euramericana has one connection node, OTU 5057, which belongs to Actinobacteria.

3.3.3. Results of the Molecular Ecological Network Construction

The visualization results directly show the relationship between nodes and modules. After modularization analysis, 61 modules are generated in the P. tabulaeformis group, with a module index of 0.862, and 65 modules are generated in the P. euramericana, with a module index of 0.841. The module indices of both groups are high, indicating that the two groups of network systems have high stability against external changes. Based on the results of the module analysis, Cytoscape was used to visualize the molecular ecological network (Figure 7). The nodes of the same module are distributed on the same circle, the color of the point represents the phylum types to which it belongs, the connecting line represents the interaction between nodes, the blue connecting line between nodes represents the positive interaction between them, and the red connecting line represents the negative interaction between them.
Comparing the molecular ecological network of soil bacteria under P. tabulaeformis and P. euramericana, the bacterial molecular ecological network under P. tabulaeformis is less than the bacterial molecular ecological network under P. euramericana by six modules, indicating that the bacterial molecular ecological network under P. euramericana is more abundant. The number of connections between and within the bacterial molecular ecological network modules under P. euramericana is greater, and the proportion of red connection lines is higher than that of P. tabulaeformis, indicating that the negative interaction between bacterial communities is stronger under P. euramericana. The proportion of green connection lines under P. tabulaeformis is higher than that of P. euramericana, indicating that the positive interaction between bacterial communities is stronger. Therefore, the relationship between bacterial communities under P. euramericana is more complex, and the relationship between and within modules is closer.

4. Discussion

4.1. Differences in Response of Soil Bacterial Communities to Different Vegetation Types

Land reclamation can improve the structure of the soil bacterial community, increase the number and diversity of soil microorganisms, and enhance the abundance of functional genes [30]. However, different vegetation types have different impacts on soil microorganisms in the reclamation area [31], and different types of reclamation vegetation are suitable for different climatic conditions. Li found that the shrub soil in the mining area of the Loess Plateau has better biochemical characteristics and higher microbial diversity than the soil of trees and grasslands, which is more suitable for reclamation [32]. Wang J found that the number of bacteria and fungi in the rhizosphere of trees in the western mining area is higher than that of shrubs and herbs, and the ecological restoration effect is also better [33]. Therefore, the influence of vegetation on soil characteristics is different under different climatic conditions. This study found that there are some differences in soil microbial community diversity and community composition under P. tabulaeformis and P. euramericana. The results of this study are consistent with those of Helong [34]. P. euramericana is conducive to the development of soil bacterial diversity. Therefore, the reclamation vegetation selection of the Heidaigou open-pit waste dump is more conducive to the improvement of soil quality to increase the planting proportion of P. euramericana.

4.2. Differences in Soil Bacterial Community Response to Different Reclamation Years

From the perspective of reclamation years, the longer the reclamation year, the higher the diversity of soil bacterial communities. The change in the OTU number of each sample also conforms to this law. According to the PCA of each sample at the phylum level, the distance between samples with the same reclamation period is closer, and the similarity between soil samples with the same reclamation period is stronger. The diversity of the soil bacterial community also increases with an increase in reclamation time. For example, Ezeokoli et al. surmised that the structure of soil bacterial communities can reflect the potential differences between different soil ecosystems and that the bacterial diversity and function of reclaimed soil will recover over time [35]. Buta et al. surmised that vegetation restoration can significantly improve soil quality and have a significant impact on the activity of soil microorganisms [36]. Morrien et al. supposed that in the process of reclamation, the relative abundance of Actinobacteria and Acidobacteria would increase with an increase in reclamation years [37], and the diversity of soil bacterial communities with longer reclamation years was higher [38]. Therefore, the reclamation period is an important factor affecting the restoration of the soil bacterial community in the reclamation area.

4.3. Driving Mechanisms of Bacterial Community Structure Change in the Reclaimed Soil

RDA analysis was conducted on environmental factors and the main bacteria in the waste dump samples of the Heidaigou open-pit coal mine (Figure 8). The results show that the relative abundance of Actinobacteria is positively affected by soil alkaline nitrogen content, total nitrogen content, alkaline phosphatase activity, invertase activity, and urease activity. The relative abundance of Proteobacteria, Bacteroidetes, and Armatimonadetes is also strongly negatively affected by these environmental factors. The total phosphorus content of the soil has a significant positive correlation with the relative abundance of Chloroflexi and a strong negative correlation with the relative abundance of Planctomycetes. CEC is positively correlated with the relative abundance of Planctomycetes and negatively correlated with the relative abundance of Chloroflexi. The total potassium content of the soil is positively correlated with the relative abundance of Acidobacteria and negatively correlated with the relative abundance of Gemmatimonadetes and Cyanobacteria. The proportions of clay and silt in the soil are negatively correlated with the relative abundance of Deinococcus-Thermus.
To explore the interaction between the soil bacterial community and environ-mental factors under P. tabulaeformis and P. euramericana, the top 200 OTUs of soil bac-terial abundance under P. tabulaeformis and P. euramericana were selected, and the en-vironmental factors were used as nodes to build an interaction network between the soil bacterial species composition and environmental factors. The results are shown in Figure 9. Proteobacteria and Actinobacteria still occupy the dominant position (Figure 9). In the molecular ecological network diagram (Figure 9a) of soil bacterial species com-position and environmental factors under P. tabulaeformis, there are better connections between environmental factors, such as soil water content, CEC, soil total nitrogen, soil organic matter, and soil urease activity, and other nodes. Among them, soil organic matter, CEC, and soil urease activity mainly have positive interactions with bacteria, while soil water content and soil total nitrogen mainly have negative interactions with bacteria. In the molecular ecological network diagram (Figure 9b) of soil bacterial species composition and environmental factors under P. euramericana, there are many connections between environmental factors, such as soil total nitrogen, soil organic matter, soil invertase activity, and soil alkaline phosphatase activity, and other nodes. Soil total nitrogen, soil organic matter, soil invertase activity, and soil alkaline phosphatase activity mainly have positive interactions with bacteria. It can be concluded that the relationship between the soil bacterial community of P. tabulaeformis and P. euramericana and the environmental factors is not completely the same, and even the interaction between some environmental factors and bacteria is opposite, which also shows that the growth environment required by P. tabulaeformis and P. euramericana is different, which needs further exploration.

5. Conclusions

(1) According to the analysis of the structure and diversity of the soil bacterial community, Proteobacteria, Actinobacteria, and Acidobacteria are the main bacteria in the soil. The relative abundance of Actinobacteria is greater in the soil samples under P. tabulaeformis than in the soil samples under P. euramericana, and the relative abundance of Acidobacteria is less in the soil samples under P. tabulaeformis than in the soil samples under P. euramericana. The soil bacterial diversity is relatively higher under P. euramericana than under P. tabulaeformis, and the difference in bacterial community composition among samples is smaller, which is more conducive to the restoration of soil bacterial diversity. The activities of soil enzymes are higher under P. euramericana than under P. tabulaeformis.
(2) The total number of nodes, total number of connections, and average connectivity of the soil bacterial network under P. euramericana are greater than those under P. tabulaeformis. Based on the connectivity between nodes, it can be concluded that the relationship between bacterial communities under P. euramericana is more complex, and the relationship between different modules is also closer. Therefore, P. euramericana is more conducive to the restoration of soil bacterial diversity than P. tabulaeformis.
(3) Among the major bacteria, the relative abundance of Actinobacteria is negatively correlated with soil pH, soil total nitrogen content, urease activities, invertase activities, and alkaline phosphatase activities, while the relative abundance of Proteobacteria, Bacteroidetes, and Armatimonadetes is positively correlated with these environmental factors. Soil total nitrogen content, soil organic matter content, and the activities of urease, invertase, and alkaline phosphatase have a greater impact on the bacterial community.
(4) The influence of P. euramericana and P. tabulaeformis on soil bacterial community structure is related to the mechanisms of plant growth, which we will continue to study in our follow-up work.
Different restoration tree species have different effects on the soil bacterial community and the ecological function of restoration of reclaimed land. Therefore, through the experimental study of the change rule of soil microorganisms, we can timely understand the reasons for soil quality changes and select the appropriate repair tree species, which is more conducive to accelerating the selection of vegetation configuration on the reclaimed land and the speed of ecosystem restoration. However, the differences between the tree species that they derive from have not been studied in depth, and the mechanism will continue to be studied in the future.

Author Contributions

All authors made significant contributions to the preparation of this manuscript. Methodology, H.H.; software, H.L.; conceptualization, Z.D.; validation, C.W.; formal analysis, S.Z.; writing—review and editing, J.X. All authors have read and agreed to the published version of the manuscript.

Funding

This work was supported by the National Social Science Fund (No. 22BJY064).

Institutional Review Board Statement

Exclude this statement.

Informed Consent Statement

Not applicable.

Data Availability Statement

Not applicable.

Acknowledgments

This study was funded by the National Social Science Fund (No. 22BJY064). We thank LetPub (www.letpub.com, 16 January 2023) for its linguistic assistance during the preparation of this manuscript.

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.

References

  1. Hu, Z.Q. The 30 years’ land reclamation and ecological restoration in China: Review, rethinking and prospect. Coal Sci. Technol. 2019, 47, 25–35. [Google Scholar] [CrossRef]
  2. Ministry of Natural Resource of the People’s Republic of China. China Mineral Resources (2020) [EB/OL]. Available online: http://www.mnr.gov.cn/sj/sjfw/kc_19263/zgkczybg/202010/t20201022_2572964.html (accessed on 22 October 2020).
  3. Du, J.P.; Shao, J.G.; Tan, S.J.; Cao, F. The research of land reclamation in coal mining area: Prospects and progress. J. Chongqing Norm. Univ. (Nat. Sci.) 2018, 35, 131–140. [Google Scholar] [CrossRef]
  4. Wang, G.; Ren, Y.; Bai, X.; Su, Y.; Han, J. Contributions of beneficial microorganisms in soil remediation and quality improvement of medicinal plants. Plants 2022, 11, 3200. [Google Scholar] [CrossRef]
  5. Veen, G.F.; Wubs, E.J.; Bardgett, R.D.; Barrios, E.; Bradford, M.A.; Carvalho, S.; De Deyn, G.B.; De Vries, F.T.; Giller, K.E.; Kleijn, D.; et al. Applying the aboveground-belowground interaction concept in agriculture: Spatio-temporal scales matter. Front. Ecol. Evol. 2019, 7, 300. [Google Scholar] [CrossRef] [Green Version]
  6. Sun, S.; Sun, H.; Zhang, D.; Zhang, J.; Cai, Z.; Qin, G.; Song, Y. Response of soil microbes to vegetation restoration in coal mining subsidence areas at huaibei coal mine, China. Int. J. Environ. Res. Public Health 2019, 16, 1757. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  7. Li, Y.Y. Microbial Diversity and Enzyme Activity of Soil Reclaimed by Hydraulic Dredge Pump in Coal-Mining Subsidence Areas; China University of Mining and Technology: Xuzhou, China, 2015. [Google Scholar]
  8. Luo, Z.; Ma, J.; Chen, F.; Li, X.; Zhang, Q.; Yang, Y. Adaptive development of soil bacterial communities to ecological processes caused by mining activities in the Loess Plateau, China. Microorganisms 2020, 8, 477. [Google Scholar] [CrossRef] [Green Version]
  9. Dimitriu, P.A.; Prescott, C.E.; Quideau, S.A.; Grayston, S.J. Impact of reclamation of surface-mined boreal forest soils on microbial community composition and function. Soil Biol. Biochem. 2010, 42, 2289–2297. [Google Scholar] [CrossRef]
  10. Pascual, J.A.; Garcia, C.; Hernandez, T.; Moreno, J.L.; Ros, M. Soil microbial activity as a biomarker of degradation and remediation processes. Soil Biol. Biochem. 2000, 32, 1877–1883. [Google Scholar] [CrossRef]
  11. Harris, J.A. Measurements of the soil microbial community for estimating the success of restoration. Eur. J. Soil Sci. 2003, 54, 801–808. [Google Scholar] [CrossRef]
  12. Eaton, W.D.; Shokralla, S.; McGee, K.M.; Hajibabaei, M. Sing metagenomics to show the efficacy of forest restoration in the New Jersey Pine Barrens. Genome 2017, 60, 825–836. [Google Scholar] [CrossRef] [Green Version]
  13. Sun, W.; Liu, X.; Tian, Z.; Shao, X. Analysis on characteristics of vegetation and soil bacterial community under 20 Years’ restoration of different tree species: A case study of the qinling mountains. Forests 2021, 12, 562. [Google Scholar] [CrossRef]
  14. Hou, H.; Wang, C.; Ding, Z.; Zhang, S.; Yang, Y.; Ma, J.; Chen, F.; Li, J. Variation in the soil microbial community of reclaimed land over different reclamation periods. Sustainability 2018, 10, 22867. [Google Scholar] [CrossRef] [Green Version]
  15. Mummey, D.L.; Stahl, P.D.; Buyer, J.S. Soil microbiological properties 20 years after surface mine reclamation: Spatial analysis of reclaimed and undisturbed sites. Soil Biol. Biochem. 2002, 34, 1717–1725. [Google Scholar] [CrossRef]
  16. Dangi, S.R.; Stahl, P.D.; Wick, A.F.; Ingram, L.J.; Buyer, J.S. Soil Microbial Community Recovery in Reclaimed Soils on a Surface Coal Mine Site. Soil Sci. Soc. Am. J. 2012, 76, 915–924. [Google Scholar] [CrossRef]
  17. Strickland, M.S.; Lauber, C.; Fierer, N.; Bradford, M.A. Testing the functional significance of microbial community composition. Ecology 2009, 90, 441–451. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  18. Waldrop, M.P.; Firestone, M.K. Seasonal dynamics of microbial community composition and function in oak canopy and open grassland soils. Microb. Ecol. 2006, 52, 470–479. [Google Scholar] [CrossRef] [PubMed]
  19. Wang, C.; Zhang, W.; Zhao, C.; Shi, R.; Xue, R.; Li, X. Revegetation by sowing reduces soil bacterial and fungal diversity. Ecol. Evol. 2020, 10, 431–440. [Google Scholar] [CrossRef] [Green Version]
  20. Li, Y.; Jia, Z.; Sun, Q.; Zhan, J.; Yang, Y.; Wang, D. Ecological restoration alters microbial communities in mine tailings profiles. Sci. Rep. 2016, 6, 25193. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  21. Yan, D.; Mills, J.G.; Gellie, N.J.; Bissett, A.; Lowe, A.J.; Breed, M.F. High-throughput eDNA monitoring of fungi to track functional recovery in ecological restoration. Biol. Conserv. 2018, 217, 113–120. [Google Scholar] [CrossRef]
  22. Zhang, L. Effect of Different Combination of Phytoremediation on Soil Ecological Restoration at the Exploited Rare Earth Mine Site; Zhongkai University of Agriculture and Engineering: Guangzhou, China, 2017. [Google Scholar]
  23. Xu, R.; Zhao, H.; Liu, G.; You, Y.; Ma, L.; Liu, N.; Zhang, Y. Effects of nitrogen and maize plant density on forage yield and nitrogen uptake in an alfalfa-silage maize relay intercropping system in the North China Plain. Field Crops Res. 2021, 263, 108068. [Google Scholar] [CrossRef]
  24. Zhou, Z.; Zhang, Y.; Zhang, F. Abundant and rare bacteria possess different diversity and function in crop monoculture and rotation systems across regional farmland. Soil Biol. Biochem. 2022, 171, 108742. [Google Scholar] [CrossRef]
  25. Dong, W.H.; Zhang, S.; Rao, X.; Liu, C.A. Newly-reclaimed alfalfa forage land improved soil properties comparison to farmland in wheat-maize cropping systems at the margins of oases. Ecol. Eng. 2016, 94, 57–64. [Google Scholar] [CrossRef]
  26. Xu, R.; Zhao, H.; Liu, G.; Li, Y.; Li, S.; Zhang, Y.; Liu, N.; Ma, L. Alfalfa and silage maize intercropping provides comparable productivity and profitability with lower environmental impacts than wheat-maize system in the North China plain. Agric. Syst. 2022, 195, 103305. [Google Scholar] [CrossRef]
  27. Xu, H.; Chen, C.; Pang, Z.; Zhang, G.; Wu, J.; Kan, H. Short-term vegetation restoration enhances the complexity of soil fungal network and decreased the complexity of bacterial network. J. Fungi 2022, 8, 1122. [Google Scholar] [CrossRef] [PubMed]
  28. Zhou, J.; Deng, Y.; Luo, F.; He, Z.; Tu, Q.; Zhi, X. Functional molecular ecological networks. MBio 2010, 1, e00169-10. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  29. Deng, Y.; Jiang, Y.H.; Yang, Y.; He, Z.; Luo, F.; Zhou, J. Molecular ecological network analyses. BMC Bioinformaics 2012, 13, 113. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  30. Zhao, Y.; Zhang, F.; Yang, L.; Wang, D.; Wang, W. Response of soil bacterial community structure to different reclamation years of abandoned salinized farmland in arid China. Arch. Microbiol. 2019, 201, 1219–1232. [Google Scholar] [CrossRef]
  31. Du, J.P.; Shao, J.A.; Zhou, C.R.; Sun, J.; Jiang, J.J. Study on reconstruction technology of concave convex landform of temporary construction land in coal mine-taking chongqing mulang coal mine as an example. J. Southwest Univ. (Nat. Sci. Ed.) 2018, 40, 140–148. [Google Scholar] [CrossRef]
  32. Li, P.F. Study on Soil Quality Restoration and Changes in Microbial Characteristics of Reconstructed Soil in Mining Area of Shanxi-Shaanxi-Inner Mongolia Adjacent Region; Chinese Academy of Science and Ministry of Education (Research Center of Soil and Water Conservation and Ecological Environment): Shangxi, China, 2019. [Google Scholar]
  33. Wang, J. Impacts of Coal Mining Disturbance on Rhizosphere Microecological and Microbial Reclamation Effect in Western Area of China; China University of Mining and Technology (Beijing): Beijing, China, 2015. [Google Scholar]
  34. He, L.; Li, Y.Q.; Li, B.C.; Li, J.J. Effects of different vegetation types and reclamation years on soil bacterial community structure in reclaimed mine areas. Environ. Sci. 2017, 38, 752–759. [Google Scholar] [CrossRef]
  35. Ezeokoli, O.T.; Bezuidenhout, C.C.; Maboeta, M.S.; Khasa, D.P.; Adeleke, R.A. Structural and functional differentiation of bacterial communities in post-coal mining reclamation soils of South Africa: Bioindicators of soil ecosystem restoration. Sci. Rep. 2020, 10, 17591. [Google Scholar] [CrossRef] [Green Version]
  36. Buta, M.; Blaga, G.; Paulette, L.; Păcurar, I.; Roșca, S.; Borsai, O.; Grecu, F.; Sînziana, P.E.; Negrușier, C. Soil reclamation of abandoned mine lands by revegetation in northwestern part of transylvania: A 40-year retrospective study. Sustainability 2019, 11, 3393. [Google Scholar] [CrossRef] [Green Version]
  37. Morriën, E.; Hannula, S.E.; Snoek, L.B.; Helmsing, N.R.; Zweers, H.; De Hollander, M.; Soto, R.L.; Bouffaud, M.L.; Buée, M.; Dimmers, W.; et al. Soil networks become more connected and take up more carbon as nature restoration progresses. Nat. Commun. 2017, 8, 14349. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  38. Ngugi, M.R.; Dennis, P.G.; Neldner, V.J.; Doley, D.; Fechner, N.; McElnea, A. Open-cut mining impacts on soil abiotic and bacterial community properties as shown by restoration chrono sequence. Restor. Ecol. 2018, 26, 839–850. [Google Scholar] [CrossRef]
Figure 1. Location of the study area.
Figure 1. Location of the study area.
Plants 12 00974 g001
Figure 2. Soil physicochemical properties and enzyme activities. Note: Y is the Yinwang waste dump, I is the inner waste dump, W is the west waste dump, E is the east waste dump, N is the north waste dump, and C is the control site. (a) is bulk denisity, (b) is soil water content, (c) is sand content, (d) is PH, (e) is cation exchange capacity, (f) is soil organic content, (g) is total nitrogen, (h) is total phosphorus, (i) is total potassium, (j) is urease activity, (k) is invertase activity, (l) is alkaline phosphatase activity.
Figure 2. Soil physicochemical properties and enzyme activities. Note: Y is the Yinwang waste dump, I is the inner waste dump, W is the west waste dump, E is the east waste dump, N is the north waste dump, and C is the control site. (a) is bulk denisity, (b) is soil water content, (c) is sand content, (d) is PH, (e) is cation exchange capacity, (f) is soil organic content, (g) is total nitrogen, (h) is total phosphorus, (i) is total potassium, (j) is urease activity, (k) is invertase activity, (l) is alkaline phosphatase activity.
Plants 12 00974 g002
Figure 3. Composition and relative abundance of bacterial community at the phylum level of each sample in the Heidaigou open-pit coal mine dump and control area.
Figure 3. Composition and relative abundance of bacterial community at the phylum level of each sample in the Heidaigou open-pit coal mine dump and control area.
Plants 12 00974 g003
Figure 4. Alpha diversity index of each sample under the reclamation of P. tabulaeformis and P. euramericana. (a) is Simpason diversity index, (b) is Shannon diversity index, (c) is Chao 1 richness estimator, (d) is Abundance based coverage estimator.
Figure 4. Alpha diversity index of each sample under the reclamation of P. tabulaeformis and P. euramericana. (a) is Simpason diversity index, (b) is Shannon diversity index, (c) is Chao 1 richness estimator, (d) is Abundance based coverage estimator.
Plants 12 00974 g004
Figure 5. PCA and NMDS analysis of each sample in the Heidaigou open-pit coal mine dump and control area. (a) is PCA, (b) is NMDS.
Figure 5. PCA and NMDS analysis of each sample in the Heidaigou open-pit coal mine dump and control area. (a) is PCA, (b) is NMDS.
Plants 12 00974 g005
Figure 6. Z-P plot of soil bacterial molecular ecological networks under the reclamation of P. tabulaeformis and P. euramericana.
Figure 6. Z-P plot of soil bacterial molecular ecological networks under the reclamation of P. tabulaeformis and P. euramericana.
Plants 12 00974 g006
Figure 7. Soil bacterial molecular ecological networks under Pinus tabulaeformis and Populus euramericana.
Figure 7. Soil bacterial molecular ecological networks under Pinus tabulaeformis and Populus euramericana.
Plants 12 00974 g007
Figure 8. RDA analysis of environmental factors and major bacteria in the Heidaigou open-pit coal mine dump and control area. Note: AKP, soil alkaline phosphatase activity; CEC, soil cation exchange capacity; pH, soil pH; TK, soil total potassium; TN, soil total nitrogen; TP, soil total phosphorus; and WC, soil water content.
Figure 8. RDA analysis of environmental factors and major bacteria in the Heidaigou open-pit coal mine dump and control area. Note: AKP, soil alkaline phosphatase activity; CEC, soil cation exchange capacity; pH, soil pH; TK, soil total potassium; TN, soil total nitrogen; TP, soil total phosphorus; and WC, soil water content.
Plants 12 00974 g008
Figure 9. Molecular ecological network of bacterial species composition and environmental factors under P. tabulaeformis and P. euramericana. Note: AKP, soil alkaline phosphatase activity; CEC, soil cation exchange capacity; OM, soil organic matter; pH, soil pH; TK, soil total potassium; TN, soil total nitrogen; TP, soil total phosphorus; and SWC, soil water content. The blue line represents positive interaction between nodes, and the red line represents negative interaction between nodes.
Figure 9. Molecular ecological network of bacterial species composition and environmental factors under P. tabulaeformis and P. euramericana. Note: AKP, soil alkaline phosphatase activity; CEC, soil cation exchange capacity; OM, soil organic matter; pH, soil pH; TK, soil total potassium; TN, soil total nitrogen; TP, soil total phosphorus; and SWC, soil water content. The blue line represents positive interaction between nodes, and the red line represents negative interaction between nodes.
Plants 12 00974 g009
Table 1. Information on sampling and control areas.
Table 1. Information on sampling and control areas.
Site NameSpeciesSample NumberReclamation Year (a)Site NameSpeciesSample NumberReclamation Year (a)
North waste dumpPinus tabulaeformisN115Inner waste dumpPinus tabulaeformisI19
Populus euramericanaN215 Populus euramericanaI29
East waste dumpPinus tabulaeformisE112Yinwang waste dumpPinus tabulaeformisY16
Populus euramericanaE212 Populus euramericanaY26
West waste dumpPinus tabulaeformisW112Control areaPinus tabulaeformisC1
Populus euramericanaW212 Populus euramericanaC2
Table 2. Comparison of the topological properties of soil bacterial molecular ecological networks under the reclamation of P. tabulaeformis and P. euramericana.
Table 2. Comparison of the topological properties of soil bacterial molecular ecological networks under the reclamation of P. tabulaeformis and P. euramericana.
Network IndexP. tabulaeformis (0.960)P. euramericana (0.960)
Total number of nodes642746
Total number of connections15182003
Power law R2 value0.7010.712
Average connectivity4.7295.370
Average clustering coefficient0.5410.579
Average path distance9.42511.582
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Hou, H.; Liu, H.; Xiong, J.; Wang, C.; Zhang, S.; Ding, Z. Comparison of Soil Bacterial Communities under Canopies of Pinus tabulaeformis and Populus euramericana in a Reclaimed Waste Dump. Plants 2023, 12, 974. https://doi.org/10.3390/plants12040974

AMA Style

Hou H, Liu H, Xiong J, Wang C, Zhang S, Ding Z. Comparison of Soil Bacterial Communities under Canopies of Pinus tabulaeformis and Populus euramericana in a Reclaimed Waste Dump. Plants. 2023; 12(4):974. https://doi.org/10.3390/plants12040974

Chicago/Turabian Style

Hou, Huping, Haiya Liu, Jinting Xiong, Chen Wang, Shaoliang Zhang, and Zhongyi Ding. 2023. "Comparison of Soil Bacterial Communities under Canopies of Pinus tabulaeformis and Populus euramericana in a Reclaimed Waste Dump" Plants 12, no. 4: 974. https://doi.org/10.3390/plants12040974

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop