Study sites
This study was located in Wudi County, which is part of the YRD in northern Shandong on the southern shore of the Bohai Sea (37°54′60″N, 117°57′33″E, elevation 1 m). This area has a semi-humid continental climate characterized by a mean annual precipitation and air temperature of 600 mm and 12°C, respectively. We selected five different salinity levels from low to extreme salinization 29. In brief, maize croplands with low salinity were selected as the control (CK) and are mainly affected by freshwater flooding. Land covered by Setaria viridis, low salt-tolerant vegetation, was selected as low salinity level (S1). Saline-alkali land dominated by Suaeda salsa, medium salt-tolerant vegetation, was selected as medium salinity level (S2). Saline-alkali land without vegetation growth but with salt crystallization was selected as high salinity level (S3), and extreme salinity level (S4) was the saline-alkali land with salt crystallization. The soil electrical conductivity value ranged from 0.92 ds/m (CK) to 1.78 ds/m (S1), 3.16 ds/m (S2), 17.26 ds/m (S3), and finally 34.41 ds/m (S4) (Fig. 5).
Soil collection
Four transects across a distance of approximately 3 km represented four repetitions, and in each transect, five plots (CK, S1, S2, S3, and S4), which were spaced at least 500 m part, were randomly selected. In each plot (5 × 5m2), the topsoil (0–15 cm) was collected using five-spot sampling in October 2019. The plant debris was removed, and we mix the five-point sample into one sample. Hence, a total of 20 samples (5 salinity levels × 4 repetitions) were collected, and we divided the soil samples into two subsamples. One subsample was air-dried for the analysis of basic soil properties, and the other part was placed in a −80℃ freezer for microbiological analysis 24. The physical and chemical properties and measurement methods of the soil are listed in the Supplementary Materials. Some basic characteristics for the soils in Table S1 were cited from our previous study 29.
High-throughput sequencing of soil bacteria
The genomic DNA was extracted from 0.30 g of soil using the MoBio PowerSoil DNA Isolation Kit (QIAGEN, Ins., USA). The V3-V4 regions of the bacterial 16S rRNA gene were amplified using universal primers 338F (5’-ACTCCTACGGGAGGCAGCAG-3’) and 806R (5’-GGACTACHVGGGTWTCTAAT-3’) 30. The PCR analysis included pre-denaturation at 95°C for 3 min, 27 cycles at 95°C for 30 s, annealing at 55°C for 30 s, elongation at 72°C for 45 s, and an extension at 72°C for 10 min.
Illumina MiSeq sequencing produced double-ended sequence data (2 × 300) according to standard protocols performed by MajorBio Bio-Pharm Technology Co. Ltd. (Shanghai, China). The obtained sequences were first filtered using the quantitative insights into microbial ecology. Raw FASTQ files were de-multiplexed and quality-filtered with the following criteria: (i) 300-bp reads were truncated at any site with an average quality score <20 over a 50-bp sliding window, and truncated reads shorter than 50 bp were discarded; (ii) exact barcode matching, less than two nucleotide mismatches in the primer, and no ambiguous characters in the read; (iii) only overlapping sequences longer than 10 bp were assembled according to their overlapped sequence. Then, we used UPARSE ver. 7.1 to cluster the high-quality sequences with 97% identity threshold into operational taxonomic units (OTUs) 31.
Statistical analysis
The α-diversity indices, including the coverage, Sobs (the actual observed richness), ACE (Ace index of species richness), Chao1 (Chao1 index of species richness), and Shannon diversity index, were classified using MOTHUR software. The Shannon diversity at the phylum level was calculated as follows 24:
where Shannon phyla is the bacterial diversity at the phylum level, N is the total number of OTUs in each bacterial phylum, and Ni is the number of individuals in group i.
The significant differences in the soil total bacterial α-diversity, bacterial Shannon diversity at the phylum level, bacterial community, and soil physicochemical properties of the five salinization levels were analyzed using one-way ANOVA in SPSS (ver. 19.0). The significance was analyzed at p < 0.05 using DUNCAN’s test.
Nonmetric multidimensional scaling (NMDS) based on Bray-Curtis similarity matrices was performed to identify the response of soil bacteria to salinity. The significance was tested by analysis of similarities (ANOSIM) in PAST (ver. 3.25).
The relationships between soil physicochemical properties and the soil bacterial communities were analyzed by redundancy analysis (RDA) using CANOCO (ver. 4.5). The significance of the effect of each property was examined using the Monte Carlo permutation test (permutation = 499), and the significance was analyzed by the F- and p-values. Spearman analyses were performed to identify the correlations between the soil physicochemical properties and the relative abundances and diversity of bacterial phyla.
Data availability
Sequence data supporting the findings of this study have been deposited at NCBI database under Sequence Read Archive (SRA) accession number SRP268965.