3.1. Impacts of the pesticides on soil bacterial flora
To analyze the species diversity of the soil samples, all Effective Reads were grouped by 97% DNA sequence similarity into the same operational taxonomic units (OTUs). By comparing the number of OTUs and detected species (Fig. 1), it can be concluded that soil microbial diversity was significantly affected by chlorpyrifos and deltamethrin contaminants (Fig. S1, Supplementary Materials). Both of the pesticides showed considerable negative impacts on soil microbial diversity but chlorpyrifos had stronger effect on reducing OTU and observed species numbers in all soil samples regardless of the soil microbial activity and salinity. The effect of chlorpyrifos on diversity of soil microbial community was analyzed using high-density DNA microarray (PhyloChip) and demonstrated that chlorpyrifos is able to destroy a vast number of soil microorganisms (Storck et al. 2018).
Comparing the number of observed species between different salinity soils reveals a direct effect of soil salinity on microbial diversity in no-pesticide control microcosms, as the number of species decreased from 1131 to 609 by increasing salinity from 0 to 4 percent (Fig. 1). Using a 16S rRNA Miseq-sequencing study phylogenetic compositions, diversity and structure of soil microbial communities under different salinity conditions and shown that soil prokaryotic diversity decreased with salinity (Zheng et al. 2017). In another study, impacts of salinity on the soil microbial community along a natural salinity gradient was investigated in Gurbantunggut Desert, Northwestern China. The findings revealed that the microbial diversity linearly decreased in higher salinities, and community dissimilarity significantly increased with salinity differences (Zhang, Shi, et al. 2019). The addition of the pesticides to the soil microcosms (C and D microcosms) drastically decreased the soil bacterial diversity which is exhibited in lower OTU numbers in pesticide contaminated microcosms in comparison to the correspondent uncontaminated soil (Fig. 1). The higher OTU count for the 1% salinity microcosms could be due to higher biological activity of the soil (Jiang et al. 2006).
3.2. Soil microbial community structure
The soil bacterial community analysis has been extensively used to evaluate the environmental side effects of common chemicals which are applied to soil such as pesticide in agricultural industry. As indicated in Fig. 2, exposing the soil samples to deltamethrin (DM) and chlorpyrifos (CP), considerably changed the community at the genus level by relative abundance. Therefore, Sphingomonas which was the dominant genus in the control samples (group S), was dramatically reduced to about 0.6% and 0.8% in relative abundance by addition of CP and DM, respectively. While, the abundance of genus Bacillus with about 3.3% in the control samples, significantly increased to more than 37% in the group C.
From the results it may be concluded that genus Bacillus is one of the main CP degraders in the studied soil samples. The current findings is in consistent with Anwar et al. who found that Bacillus pumilus strain was able to degrade CP within 10 d (Anwar et al. 2009). There are lots of studies on the biodegradation of CP by genus Bacillus which prove the results (Aceves-Diez, Estrada-Castañeda, and Castañeda-Sandoval 2015; Zhu, Zhao, and Ruan 2019; Oladipo, Burt, and Maboeta 2019; Chandrashekar et al. 2017). However, studying the sample C0 (chlorpyrifos-contaminated non-saline soil) revealed that in non-saline soil sample, relative abundance of Bacillus surprisingly increased to more than 97%, while the other genera were about to completely disappear.
In comparison to C0, the sample D0 was rich in Pseudomonas genus (60% abundance) and it should be due to the deltamethrin natural attenuation ability of this genus (Yang et al. 2018).
The results, as shown in Fig. 2, indicated that the microbial diversity of the non-saline soil is more affected by the pesticide amendment in comparison to other saline soils. This phenomena could be somehow related to the adaptation of the halophiles to the extreme environment (Sato 1987). According to the results, Paenibacillus (D2), Bacillus (C4), Paeniclostridium (D1, C2) and Lachnospiraceae (C1) were the dominant genera which showed 77%, 50%, 41% and 39% relative abundance, respectively.
In this context, investigating the microbial biodiversity at phylum level revealed that the Firmicutes, Proteobacteria, Bacteroidetes and Actinobacteria were the dominant phyla which were selected by DM and CP chemicals (Fig. 3).
The study has confirmed the findings of Li et al. (2017) who reported that Firmicutes and Proteobacteria were the deltamethrin-resistant bacteria (Li et al. 2017). This resistance to DM is due to hydrolysis of ester bond by esterase/carboxyl esterase enzyme which provide DM as a carbon and nitrogen source for microbial growth and activity (Bhatt, Huang, et al. 2019; Bhatt, Bhatt, et al. 2019). Fig. S2 (supplementary materials) presents further information on the soil samples microbial diversity.
3.2.1. Alpha diversity analysis
To measure the number of different species (as the species richness) alpha diversity analysis was applied. Comparing the number of observed species, the highest species was observed in the sample S0 (non-saline, clean soil). While, the lowest observed species was detected in the presence of DM (at 1% salinity) and CP (at 4% salinity).
To determine the species richness and evenness, Shannon, Simpson, Chao1 and ACE indexes were used. According to the results shown in Table 2, the maximum indexes were observed in the group S samples (uncontaminated soils). It indicates that the microorganisms were distributed in all the samples and higher species with the same abundance level exist in the group S. Vast number of studies have been performed on the toxicological impacts of pesticide contaminants, but none considered the salinity as an effective factor on the soil microbial community composition and pesticide remediation (Wang et al. 2019; Wahla et al. 2019; Essa et al. 2019; Regar et al. 2019).
Shannon index was significantly affected by chlorpyrifos in 4% salinity microcosm. This pattern was also observed in other microcosms indicating lower richness in contaminated microcosms. The differences between CP and DM microcosms are highlighted in Table 2. The Chao1 and ACE indexes showed that species richness in deltamethrin amended microcosms was significantly lower than the richness of the chlorpyrifos-contaminated soils in 1 and 2% salinity microcosms but in non-saline and 4% salinity microcosms deltamethrin amendment increases the richness.
Overall, the results suggest that Shannon and Simpson indexes are more sensitive to the microbial community evenness, while, Chao1 and ACE indexes are changed by the community abundance which were in consistent with Zhang et al. (Zhang, Wang, et al. 2019).
3.2.2. Beta diversity Analysis
The differences between the microbial communities based on their composition was studied by principal coordinates analysis (PCoA). Beta diversity analysis at 36.24% and 25.6% of total variation for PC1 and PC2, respectively (Fig. 4.a) proved the results obtained from alpha diversity analysis which showed that the higher diversity richness was dedicated to the group S (non-contaminated soil). The most exciting part of the results was the effect of soil salinity which changed the soil microbial community resistance to the chemical contaminants.
As illustrated in Fig. 4a, the samples C1 and D4 were separated from the other samples which indicate their higher richness than the other contaminated soil samples. The other quantitative results also showed acceptable consistency with alpha diversity results. Moreover, studying the qualitative results by unweighted UniFrac PCoA revealed that the diversity composition of the samples S1 and S0 in 1% and 0% salinity were relatively same. While, the highest detrimental effects of deltamethrin and chlorpyrifos were observed in D0 and C0 microcosms, respectively which is shown in Fig. 4.b. The results verify the data presented in Fig. 3 on the samples relative abundances. Further information on the sample's beta diversity is provided in Fig. S3 (supplementary materials).
3.4. Chlorpyrifos and deltamethrin natural attenuation
To monitor the pesticide natural attenuation in soil microcosms the remained chlorpyrifos and deltamethrin concentrations in the samples were measured by gas chromatography-mass spectrometry (GC/MS). Figure 6 illustrates the CP and DM natural attenuation in the soil media by microbial activities. The results showed the higher contaminant natural attenuation of CP in slightly saline soils with 1% and 2% saline soils and faster removal of DM in 1% saline soil in comparison to non-saline control microcosm. As indicated in Fig. 6, it took more than 50 days for complete DM and CP natural removal from non-saline soil microcosms, while, only 20 and 25 d was needed for their natural degradation in 1% salinity, respectively.
However, increasing the soil salinity from 1–4% resulted in dramatic decrease in the natural attenuation efficiency. As shown in Fig. 6, the optimum condition for the natural attenuation was 1% salinity of the soil. By consuming the contaminants more than 40% of them were removed within first 10 d. After that, the natural attenuation slope was dramatically reduced and the remaining pesticides were slowly removed till end of the test. Previous studies showed that by increasing salinity, the microbial composition of the soil changed to halotolerant- bacteria and lots of species which was able to remediate DM and CP were disappeared (Storck et al. 2018).
Hence, CP and DM natural attenuation is a time consuming process that takes more than two months for complete remediation (Fig. 6), accelerated-remediation of deltamethrin and chlorpyrifos from soil would be helpful in achieving faster contaminant removal and lower environmental impacts (Budarz et al. 2019; Aswathi, Pandey, and Sukumaran 2019; Fatima, Tallat, and Singh 2019). There is several physical, chemical and biological approaches for xenobiotic removal from soil, in which, biological methods (bioremediation) are considered more economical and clean processes (Dar, Kaushik, and Chiu 2020). For further investigation, application of biostimulation and bioaugmentation methods is suggested for contaminated sites bioremediation.