1 Introduction

Mining activities have disturbed a large area of land in China. Processing plants discharge water with high acidity resulting in serious soil degradation, as reflected by increased soil acidity and decreased soil organic carbon (SOC) content (Zhao et al. 2014). Consequently, arable lands impacted by mining activities have lower crop yields (Nannipieri et al. 2003; Zhao et al. 2014). Therefore, a series of strategies need to be implemented to mitigate the negative effects of mining activities on the land. One effective method of improving soil quality is adding supplements to the soil (Nechitaylo et al. 2010; Yao et al. 2017). Many studies have shown that the combination of chemical fertilizers with supplements (e.g., biochar and earthworms) can effectively improve soil quality (Nechitaylo et al. 2010; Yao et al. 2017). However, empirical evidence on the effects of these supplements on bacterial community diversity and structure remains sparse (Nannipieri et al. 2003; Zhao et al. 2014).

The cultivation of crops can restore soil fertility and increase microbial diversity (Pilon-Smits 2005). This is mainly due to the interactions of plant roots and rhizosphere microorganisms (Yoshitomi and Shann 2001) which can promote the degradation of organic pollutants and promote plant growth (Reilley et al. 1996; Kirkpatrick et al. 2008). However, the role of microorganisms in restoring soil quality in mining disturbed areas remains largely unclear. In particular, the relative effect of different supplements on soil microbial community composition, structure and diversity is poorly understood.

Soil microorganisms with high abundance and microbial populations with a high diversity promote the growth of plants under adverse conditions by fixing nitrogen and secreting plant hormones, iron carriers, specific enzymes and antibiotics (Nannipieri et al. 2003). Plant growth and health are benefits derived from the result of plant interaction with many bacterial species. For example, the plant growth-promoting rhizobacteria (PGPR) can have various disease-suppressive functions (Lugtenberg and Kamilova 2009). It is important to maintain a high level of soil microbial diversity, to improve soil quality, especially for reclaiming mining disturbed areas, where microbial diversity is low (Sun et al. 2015). A shift in the bacterial community structure is normally coupled with a change in soil quality (Yao et al. 2017) and a large decline in microbial diversity due to mining activities has been reported (Ramirez et al. 2010). Hence, any strategy to mitigate the negative impact of mining activities should not only improve the soil’s abiotic properties, but also enhance soil microbial diversity.

Microbial species’ diversity and composition are two important metrics for assessing soil properties (Sun et al. 2014). Many researches have shown the structure of bacterial community was significantly changed after applying chemical fertilizer (Yao et al. 2014; Zhao et al. 2014; Sun et al. 2015). The application of chemical fertilizers to the soil inevitably changes soil pH, the content of organic carbon (OC) and other chemical properties (Wakelin et al. 2007). All of these factors would consequently alter the bacterial community structure (Nguyen et al. 2018). Interestingly, several recent studies have reported that fertilization decreased bacterial diversity (Yuan et al. 2012; Coolon et al. 2013; Sun et al. 2015; Zeng et al. 2016).

Biochar, sodium silicate and earthworms are three traditional supplements for soil restoration (Nechitaylo et al. 2010; Anderson et al. 2011; Bruun et al. 2014). The application of biochar changed the physical and physicochemical of the soil, which consequently changed the microbial community structure (Yao et al. 2017; Liu et al. 2018; Nguyen et al. 2018). Yao et al. (2017) and Zhou et al. (2019) reported that biochar changed soil physicochemical properties and soil bacterial community structure, while with no effect on the soil bacterial diversity. However, Xu et al. (2016) and Nguyen et al. (2018) found that biochar amendment increased soil bacterial diversity. These contradictory results indicate that the impact of biochar on microbes needs to be further studied. Notably, both addition of earthworm alone and earthworm plus chemical fertilizers increased bacterial diversity and abundance (Kamaa et al. 2012), which was mainly attributed to the microorganism that entered the earthworm (Egert et al. 2004). These evidences imply that earthworms may have stronger effects than biochar on the soil bacterial communities. Some researchers have reported that sodium silicate can protect plants through inhibiting plant pathogens and stimulating plant-beneficial microorganisms in the soil, via inhibiting the mycelial growth of some fungi (Bi et al. 2006; Zhou et al. 2018). However, there is little research on the response of microbial diversity to sodium silicate addition. Moreover, the relative influence of earthworms as compared to biochar and sodium silicate has not yet been assessed, particularly in the context of disturbed mine land reclamation. Therefore, investigating the response of bacterial diversity to different supplements during land reclamation is useful to develop management strategies that restore soil productivity in mining areas.

The aim of this research was to compare the relative importance of biochar, sodium silicate and earthworms combined with chemical fertilization in improving the reclamation of disturbed mine land, particularly on how they affect soil bacterial communities. A field experiment with soybean was performed for 45 days. The effects of chemical fertilization, with or without biochar, sodium silicate and earthworms addition on microbial community were analyzed. We hypothesized: (1) NPK fertilizer application increases bacterial diversity in reclaimed mining areas, and (2) earthworm rather than biochar or sodium silicate addition, combined with chemical fertilization, increases bacterial diversity in mining areas.

2 Materials and methods

2.1 Experiment design

A field experiment with soybean was conducted in Pingyuan County (117° 98′ N 24° 57′ E), Guangdong Province, China, where rare earth mining activities have lasted for more than 100 years and soils in the area have low OC content (0.67 g kg−1) and are strongly acidified. The experimental fields were set up in the spring of 2016 and planted with soybean. Each experimental plot had a size of 2 × 5 m. The planting density was 30 × 15 cm (row ledge × planting distance). This study included five treatments with three replicates: (1) control (no fertilization); (2) nitrogen, phosphorus and potassium fertilization (NPK), The NPK fertilizer was composed of urea (217 mg kg−1), superphosphate (219 mg P2O5 kg−1) and potassium chloride (86 mg K2O kg−1). (3) NPK fertilization plus biochar, at a rate of 1 kg m−2 (NPK + B), which were calculated as mass ratios (50 t ha−1) of the top 20 cm of the soil; (4) NPK fertilization plus sodium silicate added at a rate of 1 kg m−2 (NPK + NaSi), which were also calculated as mass ratios (50 t ha−1) of the top 20 cm of the soil; and (5) NPK fertilization plus 30 earthworms/m2 (Amynthas robustus, of 1.2-2.9 g fresh weight per earthworm) (NPK + E).

2.2 Soil sampling

Soil samples were collected at a depth of 10 cm from three positions by auger boring in each plot on 20 August 2016, 45 days after the sowing of soybean. Five gram soil sample for each plot was put in a centrifuge tube (15 mL) and refrigerated at − 80 °C for DNA extraction. Another portion of the soil was used to measure the soil properties after air drying.

2.3 Soil chemical properties measurement

Soil pH was determined using a pH meter (FE20-FiveEasy™ pH, German). Soil TN was measured by the Elemental Analyser (VarioEL III, Germany). Soil total phosphorus (TP), nitrate nitrogen (NO3−) and ammonium nitrogen (NH4+) were measured by a continuous flow analytical system (SKALAR SAN ++, Netherlands). The AK was determined by Flame photometry (FP640, China). Available phosphorus (AP) was determined by the molybdenum blue method. Total potassium (TK) was measured by the inductively coupled plasma-atomic emission spectrometry (ICPS-7500, Japan).

2.4 DNA extraction and quantitative real-time PCR

Fast DNA Spin Kit for Soil (MP Biomedicals, USA) was used for DNA extraction. The bacterial abundance was quantified by targeting the bacterial 16S rRNA gene using q-PCR in an ABI 7500 Real-Time PCR System with primer 338F (5′-ACTCCTACGGGAGGCAGCAG-3′) and 518R (5′-ATTACCGCGGCTGCTGG-3′) (Muyzer et al. 1993). The following q-PCR reaction program consists of an initial denaturation at 96 °C for 45 s, 35 amplification cycles of 96 °C for 10 s, 60 °C for 35 s, 75 °C for 15 s, then 50 °C for 45 s for cooling. The DNA in the negative controls was replaced by sterilized water. A standard curve was used to calculate the bacterial 16S rRNA gene.

2.5 16S rRNA gene amplification and next-generation sequencing

For next-generation sequencing, primers 338F/518R were used to amplify the V3–V4 region of the 16S rRNA gene. All the PCR products were pooled together and sequenced (Caporaso et al. 2010). After sequencing, the primary raw FASTQ data was processed with the QIIME1 (V 1.9.0). Low-quality sequences with the length < 200 bp and quality score of < 20 were removed. Sequences clustered to operational taxonomic unit (OTUs) at a sequence similarity threshold of 97%. The taxonomic information was annotated using the SILVA database. All the raw sequences have been uploaded to NCBI (SRP116775).

2.6 Statistical analysis

Chao 1 indices and Shannon diversity were calculated in QIIME1. Based on OTU level, principal coordinate analysis (PCoA) and canonical correspondence analysis (CCA) were carried out in program R (V 3.5.2). The Spearman’s correlation coefficients and the predictive importance of soil properties to bacterial characteristics were calculated using the SPSS 24.0 software (Hauke and Kossowski 2011). ANOVA of Least-Significant Difference (LSD) was used to assess the differences among the treatments.

3 Results

3.1 Effects of supplements on soil chemical properties

There were significant differences of SOC and soil pH among the treatments (Table 1). Application of NPK fertilizer with biochar, sodium silicate and earthworms increased the soil pH (p < 0.05), from 4.49 ± 0.03 (mean ± SE) to 4.77 ± 0.07, and SOC (p < 0.01), from 6.78 ± 0.79 to 9.22 ± 0.61 g kg−1, when compared with the control (Table 1). Similar trends were found with total N and P.

Table 1 Effect of five treatments on soil chemical properties in a mining soil
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The TN and NO3− were increased by fertilizer application (p < 0.05), and were further increased by the addition of biochar, sodium silicate and earthworms (Table 1). Application of NPK fertilizer also increased soil AK; however, this effect was mitigated with the addition of biochar, sodium silicate and earthworms. The treatments also affected AP (p < 0.05), with the control showing the lowest AP value. Taken together, the results indicate that use of biochar, sodium silicate and earthworms together with the NPK fertilizer generally improve the soil’s nutritional status.

3.2 Soil bacterial abundance

The bacterial abundances across all samples ranged from 3.13 × 1011 to 6.33 × 1011 gene copies g−1 dry soil (Fig. 1a). Compared to the control, the application of NPK increased bacterial abundance (p < 0.05), and the addition of biochar, sodium silicate and earthworms further enhanced it. The bacterial abundance in the NPK treatment was 1.7 times the control. The addition of biochar, sodium silicate and earthworms increased bacterial abundance by 2.9-, 2.6- and 4.3-fold, respectively, relative to the control.

Fig. 1
figure 1

Bacterial abundance (a), relative abundance of bacterial phyla for each treatment (b) and principal Coordinates Analysis (CoA) based on Bray–Curtis distance (c) of the five treatments. Error bars represent the standard error. Control refer to no fertilization; NPK refer to nitrogen, phosphorus and potassium fertilization; NPK + B refer to fertilization plus biochar application; NPK + NaSi refer to fertilization plus sodium silicate; NPK + E refer to fertilization plus earthworms

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3.3 Bacterial community structure

Approximately 99.3% of 432,867 sequences (22484–37244 sequences per sample) were classified as bacteria affiliated to 40 phyla, 87 classes, 197 orders, 401 families and 965 genera. The relative abundance of the six most dominant phyla across all samples were Proteobacteria, Chloroflexi, Actinobacteria, Bacteroidetes, Acidobacteria and Saccharibacteria, which accounted for more than 39.1%, 9.9%, 5.4%, 2.5%, 3.5% and 4.7% of total bacteria, respectively (Fig. 1b). Overall, compared to the control, the abundance of Proteobacteria and Bacteroidetes were decreased in the NPK + NaSi and NPK + E treatments (p < 0.05). Moreover, the abundance of Saccharibacteria was increased in the NPK + B, NPK + NaSi and NPK + E treatments, and the abundance of Verrucomicrobia was increased in NPK, NPK + NaSi and NPK + E treatments, while Acidobacteria only increased in the NPK + E treatment (p < 0.05).

The treatment effects on the dominant bacterial community (relative abundance above 0.3%) existed mainly in 39 genera belonging to nine phyla (Table 2). Negative responses, which reflected the decreases of the relative abundance, to the supplements addition occurred in several genera such as Burkholderia, Dyella, Rhizomicrobium, Unclassified_Rhodospirillales, Pandoraea, Sinomonas, Leifsonia, Telmatobacter, Mucilaginibacter and Bacillus. However, positive responses observed in the genera have no consistent trend among treatments. For instance, Novosphingobium and Pseudospirillum affiliated to Proteobacteria were only significantly increased in the NPK and NPK + B treatment, respectively. Moreover, five genera including Devosia, Pseudospirillu, Arenimonas and Altererythrobacter belonged to Proteobacteria and Uncultured_Acidimicrobiales belonged to Chloroflexi were significantly increased in the NPK + B treatment, and five genera including Bradyrhizobium, Arenimonas affiliated to Proteobacteria, Subgroup_2 affiliated to Acidobacteria, Uncultured_Acidimicrobiales affiliated to Chloroflexi and norank_Cyanobacteria affiliated to Cyanobacteria were significantly increased by the NPK + E treatment (Table 2).

Table 2 Relative abundances of soil bacteria at the genera level
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For PCoA of Bray–Curtis distance, control samples clustered together far from the chemical fertilizer, with or without the biochar, sodium silicate and earthworm treatments (Fig. 1c), indicating a significant impact of these additions on the soil bacterial community (per-MANOVA tests, p < 0.05). The first two axis explained 29.8% and 14.5%, respectively, of the variance (Fig. 1c).

Rarefaction analysis related to Shannon’s diversity and the Chao 1 index, showed that the two measures consistently displayed higher levels of diversity in the bacterial communities in the control and fertilization with biochar, sodium silicate and earthworm treatments compared to the fertilization alone treatment (Fig. 2).

Fig. 2
figure 2

Shannon’s diversity (a) and Chao 1 index (b) of the five treatments. Control refer to no fertilization; NPK refer to nitrogen, phosphorus and potassium fertilization; NPK + B refer to fertilization plus biochar application; NPK + NaSi refer to fertilization plus sodium silicate; NPK + E refer to fertilization plus earthworms

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3.4 Relationships between bacterial communities and soil physicochemical properties

Spearman’s correlation analysis showed that SOC, TP, TN and NO3–N were positively correlated with bacterial abundance (Table 3). Bacterial community structure and the environmental factors have a strong relationship as revealed by the CCA analysis (Fig. 3). In particular, SOC, pH, TN, TK, AP, NH4+–N and NO3−–N were linked to bacterial community (Table 4). Moreover, SOC and soil pH were the two most important predictors of soil bacterial community (Fig. 4). The results suggest that SOC and soil pH were factors mediating the shifts in the bacterial community structure after earthworms were added to the soil. In addition, NH4+–N and AP played a minor role in changing bacterial community composition (Fig. 4).

Table 3 Spearman’s correlations between bacterial community and soil properties
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Fig. 3
figure 3

Canonical correspondence analysis (CCA) of bacterial community changes with a soil chemical property. Control: no fertilization; NPK: nitrogen, phosphorus and potassium fertilization; NPK + B: fertilization plus biochar application; NPK + NaSi: fertilization plus sodium silicate; NPK + E: fertilization plus earthworm

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Table 4 Mantel test of the correlation between environmental factors and bacterial community structure
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Fig. 4
figure 4

Predictive importance of soil chemical property to bacterial abundance (a), bacterial community structure (b), Chao 1 index (c) and the number of OTUs (d)

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4 Discussion

Comprehensive strategies need to be implemented to improve soil quality in the disturbed landscape in the face of increasing mining activities (Pilon-Smits 2005). The purpose of this work is to explore the effects of different types of supplements on the soil quality restoration, with a focus on the soil bacteria. Our results showed that earthworms were more effective than biochar and sodium silicate in increasing the bacterial diversity and improving soil fertility (Fig. 2). This is probably attributed to the ability of earthworms to increase the contact between organic matter and microorganisms, alter soil properties, and subsequently increase the mineralization rate of soil and fresh organic matter in the short term (Jouquet et al. 2010; Bernard et al. 2012; Naveed et al. 2014).

The activity of microorganisms determines the conversion of SOC (Pascault et al. 2013; Lian et al. 2017). The greater SOC in the NPK + E than that in other treatments was associated with the bacterial community structure. PCoA plots from each treatment were separated from each other, indicating that the addition of supplements significantly changed the soil bacterial community structure.

The application of supplements to the soil usually alters the relative abundance of bacterial groups (Yao et al. 2016; Bruun et al. 2014). In this study, there was a greater number of genera in the NPK + B and NPK + E treatment than in control, NPK and NPK + NaSi treatments. Among them, several PGPRs that are beneficial to plants were also increased in response to the treatments. For instance, Pseudospirillum belonged to the order Oceanosporillales, and only a significant increase in the NPK + B treatment may have a positive effect on the cycling of C. This is because Pseudospirillum have strong abilities to degrade complex organic compounds, and then provide absorbable nutrients to plants (Beinart et al. 2014). Moreover, Bradyrhizobium belonging to Proteobacteria was markedly increased in the NPK + E treatment, and that might provide more N for plants, because this genus is a bacterium that lives in the root nodule that fixes nitrogen (Bourebaba et al. 2016). Together, the greater number of increased genera and the higher bacterial diversity in the NPK + E treatment highlight that the addition of earthworms to soil might be a proper strategy to mitigate the detrimental effects of mining activities.

Soil chemical properties play important roles in the formation of microbial community structure (Horner-Devine et al. 2004). Many studies have reported that pH is one of the most critical factors in changing bacterial community structure and diversity (Hartman et al. 2008; Zhang et al. 2016). This is probably because the pH homeostasis in bacterial cells and availability of soil nutrients shift with pH (Zhalnina et al. 2015). In this study, an increased pH and SOC content was observed in the NPK + B, NPK + NaSi and NPK + E treatments, with the highest SOC content in the NPK + E treatment. Combined with the result of CCA and automatic linear modelling, this finding suggests that soil pH and SOC were the two most essential factors in determining the structure and diversity and bacterial community structure in this study. This result is consistent with several studies, which related to different types of supplements and soils (Yuan et al. 2012; Sun et al. 2015; Lian et al. 2017; Nguyen et al. 2018).

Applying fertilizers changed the availability of some of the nutrients, such as SOC, TN and AK, that can be utilized by microorganisms which subsequently changed the microbial community structure and diversity (Yao et al. 2014; Sun et al. 2015). In this work, the bacterial diversity increased after the application of fertilizers which is inconsistent with the results of Sun et al. (2015), who showed that the application of chemical fertilizer significantly decreased bacterial diversity. We speculate that there may be two probable reasons to explain the difference in our results. One is that soils from the control treatment possessed low levels of soil nutrients and bacterial diversity (Table 1, Fig. 2). The addition of chemical fertilizers increased bacterial diversity due to the direct and fast provision of nutrients in a short time (Sun et al. 2016). Another reason is the duration of fertilizer application. Long-term chemical fertilization, which causes an imbalance of nutrients in the soil, was used in the research of Sun et al. (2015), while chemical fertilizers were applied for only a few months in our study.

5 Conclusions

Application of chemical fertilizer increased the bacterial diversity. The additions of biochar, sodium silicate and earthworms further increased soil bacterial diversity, especially in the fertilizer plus earthworm treatment. Furthermore, a greater number of genera were found in the NPK + B and NPK + E treatments than in the control, NPK and NPK + NaSi treatments. This change in bacterial community was associated with the cycling of nutrients, such as C and N. Moreover, SOC and pH were the most dominant factors in shaping the soil bacterial community structure and diversity. Taken together, our results indicate that, among the treatments studied, the addition of earthworms to soil rather than biochar and sodium silicate was the best strategy to mitigate the negative effects of mining activities on bacterial diversity in the soil.