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.