3.2 Soil quality index
PCA results showed that the first three components with eigenvalues ≥1.0
explained 87% of the total variation of soil properties (Table S1).
According to the Norm value, SOC,
BD, DOC, TN, NH4+, C/N, ACPT, ACP and
ALP were the highly weighted variables in the PC1 and highly correlated
with each other. Thus, SOC was selected in the PC1 with the highest
eigenvector. Similarly, GLS and TP were selected for PC2 and PC3,
respectively. In short, SOC, GLS and TP were the three important
indicators selected for MDS2. The SQI was calculated after scoring and
weighting the four indicators (Table S2). The SQI values derived with
the MDS method ranged from 0.16 to 0.92. After conversion, the SQI of
Forest decreased sharply by 65%. Within four plantations, the highest
values were observed in the Peach, the lowest in the Oil (Fig. 2).
3.3 Diversity, composition and functional guilds of the
fungal community
After quality filtering, we obtained
1,252,350 sequences for downstream
analysis (range, 83,490 ± 369
reads per sample) from a total of
1,251,620 raw sequencing reads. A
total of 3,933 OTUs were clustered with ≥ 97% identity from
good-quality sequences. Rarefaction curves demonstrated that the
sequencing depth was sufficient to capture species richness of the
community (Fig. S1). Following forest conversion,
Observed species, Shannon-Wiener
and Chao1 indices of α-diversity increased by
3.5%, 6.5% and 2.9%,
respectively. All indices were higher in Berry and Peach than the other
three plantations (p < 0.05; Fig. 3a, 3b, 3c).
Moreover, Chao1, Observed species, and Shannon-Wiener indices increased
with pH, UR and Mg (p <0.05; Table S3). According to
NMDS analysis, the dissimilarity of the fungal community structure
changed substantially after conversion (Fig. 3d).
In total, 15 fungal phyla and 696 genera were identified but only 4
phyla and 20 genera were recorded with relative abundances of over 1%.
Ascomycota, Basidiomycota, Glomeromycota and Zygomycota were dominant
phyla, accounting for approximately 87% of the fungal sequences (Fig.
4a). After conversion, phyla such as
Ascomycota, Zygomycota, and
Glomeromycota increased, but Basidiomycota and Rozellomycota decreased
by 57% and 32%, respectively
(Fig. 4a). Ascomycota increased with
TK, but decreased with
NO3-(p < 0.05; Table S5). Basidiomycota declined with
SOC, DOC, C/N,
NH4+, GLS and ACP, and
Rozellomycota fell with
NO3-,
UR, GLS and Ca, while Glomeromycota increased with BD (p<0.05; Table S5). At the genus level, relative abundance ofPseudochaetosphaeronema and Russula decreased by
approximately 99%, while Pseudophialophora, Rhytisma andLepidostroma increased after conversion (Fig. 4b; Table S4).
Most fungi were classified as saprotrophs (35%), undefined saprotrophs
(29%) or ectomycorrhizal fungi (13%). Comparisons within the top 35
guilds revealed that three functional guilds (ectomycorrhizal, wood
saprotroph, fungal parasites) were more abundant in Forest than in
plantations, whereas undefined saprotrophs, arbuscular mycorrhizal,
bryophyte parasite and plant pathogen fungi were enriched in plantations
(Fig. 5).
The majority of the top 50 OTUs were either broadly dispersed across
five sites (32%) or only occurred in the plantations (32%) (Fig. 6).
Specific OTUs for Forest, Oil, Peach, Berry and Fir plantations were
six, five, one, four and two, respectively. Specifically,Pseudochaetosphaeronema OTU_4 and Russula OTU_7 were
distinct from others for Forest. Biscogniauxia OTU_55 andInocybe OTU_25 were special to Oil. Cistella OTU_100 was
unique to Peach. Simplicillium OTU_48, SubulicystidiumOTU_125, Dendrochytridium OTU_90 and MelanogasterOTU_88 were four particular taxa for Berry. Lepidostroma OTU_38
and Tomentella OTU_17 were specific for Fir (Fig. 6). LDA
analysis showed that the Agaricomycetes class and Russulaceae family
were identified as biomarkers between Forest and Oil, Berry,
respectively. Compared with the Forest, Russulales order (belonging to
Basidiomycota) was identified as a biomarker in Peach and Fir
plantations (Fig. S2).