During the post-relaxation period, the population genetic distance of HA in the three countries showed a highly significant increase compared to the pre-pandemic period (comparison between post-relaxation vs. pre-pandemic period, p < 0.001).
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One-way ANOVA detected highly significant treatment effects for the four β -lactams AML ( F = 19.54, p = 0.001), AUG ( F = 19.04, p = 0.001), PP ( F = 29.72, p = 0.0002) and CTX ( F = 19.60, p = 0.001); no differences emerged for cefpirome, carbapenems or quinolones ( p > 0.05) ( Supplementary Figure S2d ).
After 60 d of ensiling, pH exhibited a highly significant negative correlation with LA content ( r = -0.89, p < 0.001) and a strong significant positive correlation with AN content ( r = 0.86, p < 0.001).
In contrast, an extremely significant negative correlation was observed between soil salt, EC, and BD and Chao richness ( p < 0.001); however, soil salt, EC, and BD had an extremely significant positive correlation with β diversity ( p < 0.001; Figure 9 ).
Correlation analysis ( Figure 8A ) revealed the following relationships: AMF colonization rate was significantly positively correlated with soil pH ( p < 0.05) and highly significantly positively correlated with AP ( p < 0.001), whereas it was significantly negatively correlated with SOM ( p < 0.05); colonization intensity showed a highly significant positive correlation with AP ( p < 0.001); spore density was significantly positively correlated with SOM ( p < 0.05) and urease (highly significant, p < 0.001), but highly significantly negatively correlated with TN ( p < 0.001).
Finally, the correlation analysis between gut microbiota and metabolites also confirmed that the abundance of the genus Alistipes exhibited a highly significant negative correlation with lithocholate sulfate levels ( p < 0.001).
Differences were considered as significant ( ∗ p < 0.05), very significant ( ∗∗ p < 0.01), highly significant ( ∗∗∗ p < 0.001), or very highly significant ( ∗∗∗∗ p < 0.0001).
The overall model was highly significant ( F 23,48 = 2548.420, p < 0.001, R 2 = 0.999).
All of these factors had highly significant ( P ≤ 0.001) effects.
For the bacteria, the interaction effect between biochar addition and time was extremely significant ( p < 0.001).
The Shannon and Simpson indices peaked in the 100%SS group, with highly significant differences among all groups ( p < 0.001).
The Pearson correlation analysis also demonstrated a highly significant association between the ESBL phenotype and resistance to cephalosporins such as CRO (r = 0.886), FEP (r = 0.821), and CFX (r = 0.794), all with p < 0.001.
This difference was highly significant (Fisher’s exact test, p < 0.001).
The PERMANOVA test again demonstrated highly significant differences among clusters ( p = 0.001) with higher explanatory power (R 2 = 0.358 for K-Means and R 2 = 0.343 for Agglomerative), suggesting that three-cluster solutions captured more refined structural variations within the microbial community.
The differences between these two groups in the number of unique OTUs were highly significant ( Table 2 ; P < 0.001).
Estimates of beta diversity and dispersion suggested that the highly significant differences in diversity observed between age and location groups ( P < 0.001) are not due to the variation in homogeneity between the groups ( P > 0.1).
Differences between groups were considered significant if p < 0.05 (indicated with *), highly significant if p < 0.01(indicated with **) and extremely significant if p < 0.001 (indicated with ***).
“ns” indicated no significant difference; P < 0.05 was considered as a significant difference; P < 0.01 was moderately significant; P < 0.001 was extremely significant. *, P < 0.05; **, P < 0.01; ***, P < 0.001 using a one-way analysis of variance (ANOVA) followed by Tukey’s HSD test.
LEfSe was carried out with the linear discriminant analysis (LDA) threshold score of 3.00, to find which specific fungal communities caused the highly significant differences ( p = 0.001) in fungal communities between PM samples at different depths ( Figures 5C,D ).
In addition, pairwise ANOSIM analyses suggested that there were extremely significant differences between the CN and LC groups (global R = 0.4905, P = 0.001), between the CN and HC groups (global R = 0.3245, P = 0.001), and between the LC and HC groups (global R = 0.2366, P = 0.008) ( Table 5 ).
While the community structure was clearly shaped by soil type as indicated by a PERMANOVA test that showed a highly significant effect ( p = 0.001), a shift in community composition with consecutive sampling times could also be observed.
and Nitrosomonadaceae were highly significant ( P ≤ 0.001); Acidobacteria, Nocardioides, and Roseiflexaceae were significantly different ( P ≤ 0.01); and Pyrinomonadaceae, Gemmatimonadaceae, Actinobacteria, and Chloroflexi were also significantly different ( P ≤ 0.05).
Variations in amino sugars and MNC content in soil LMM analysis showed that land-use type had a highly significant main effect on all four amino sugars ( p < 0.001), whereas soil depth alone had no significant main effect on any of them.
Despite this conservative approach, the difference between treatments was highly significant (Wilcoxon Rank Sum test, p <0.001; Figure 4 ).
The combined effect of water treatment and cultivar had a significant effect on AP levels ( P < 0.05) and extremely significant effect on S-CAT levels ( P < 0.001).