3. Results
3.1 Soil Chemical Characteristics
Although some of the soil chemical characteristics were significantly affected by different farms, different vegetation types and disturbance intensity levels greatly affect the soil chemical characteristics including soil pH, soil organic matter (%), nitrate, phosphorous, potassium, calcium concentration, and CEC (Table 1). Soil pH, soil nitrate, phosphorus, and calcium contents in forest soils were significantly lower than that in crop soils. Whereas soil organic matter (%) was significantly higher in forest soils than in crop soils (Table 1).
3.2. Soil bacterial diversity and abundance
Total of 553,648 clean Illumina sequences and 1,587 OTUs were obtained from 27 samples (3 locations, 3 vegetation types, 3 replicates). The average sequence length from each sample ranges from 468 – 479 bp. The proteobacteria were most dominant phylum, followed by Acidiobacteria, Chlorofelexi, Cyanobacteria, Planctomycetales, Patescibacteria and Actinobacteria etc. (Figure 1). The relative abundance of Acidiobacteria was highest in forest and lowest in crop soils, and was significantly higher in forests soils than in transition, as well as in transition than in crop soils (Figure 2). However, the relative abundance of Proteobacteria was significantly increased in crop soils compared with transition and forest soils (Figure 2).
Compared with forest soils, agricultural practices in the crop soils significantly decreased soil bacterial richness (p = 0.04) and Shannon diversity (p = 0.02), but no effect on the evenness was observed (Table 2). There were no location or vegetation and location interaction effects for all three diversity indices (Table 2).
3.3 Soil bacterial community and relationship with environmental factors
Soil bacterial community structure was distinguished by vegetation types (Figure 3A and B). Cluster and Analysis of Similarity (ANOSIM) indicated that crop and forest soils had significantly different soil bacterial community structure (p = 0.004). Soil bacterial communities in crop soils also significantly different from those in transition soils (p = 0.011). However, there was no significant soil bacterial community structure difference between transition and forest soils (p = 0.265). Soil pH and nitrate contents together contributed to highest for the observed different bacterial community (Correlation = 0.381).
Similarity percentage breakdown (SIMPER) analysis of bacterial contribution % to each vegetation based on Illumina sequencing OTUs revealed that an uncultured bacterium OTU 1 belonging to Xanthobacteraceae dominated all three vegetation types with different disturbance intensity levels (Table 3). However, three OTUs (OUT5, OTU8, and OTU4) among the top five ranking in each vegetation type contributed differently to three vegetation types (Table 3). The relative abundance of two Acidobacteriales species (OTU5, OTU8) were decreased by agricultural practices in crop soils, which is consistent with observed high pH (Figure 4A). However, agricultural practices significantly increased Nitrobacteraceae OTU (OTU4), which is a potential bacterial species for nitrification (Figure 4B).
3.4 Soil N functional genes and relationship with environmental factors
The relative abundance of AOB amo A gene was significantly higher in crop soils than in forest and transition soils (Table 4). No significant difference was observed for the relative abundance ofnir K gene among the three different vegetation types (Table 4).
There were no differences for the biodiversity indices for AOBamo A genes. However, the richness and diversity of nir K gene were significantly higher in forest soil than in crop and transition soils (Table 5), and their community structure was significantly differentiated by the three vegetation types (ANOSIM p = 0.001), not by the farms (ANOSIM p = 0.296) (Fig. 5 A and B). Soil organic matter % and soil pH together contributed highest for the observed different nir K functional gene community (Correlation = 0.443). There was no significant difference of the diversity of denitrifying bacteria determined by nir S gene and all the environmental factors contributed less than 0.1 as correlation ecoefficiency.