3.4. Functional diversity of soil microorganisms
Changes in soil microbial activity and functional metabolic indices
under different straw return amounts after 192 h of incubation are
presented in Fig. S2. The AWCD values of all treatments increased
gradually with the extension of incubation time in the following
sequence: S2 > S1 > S1/2 > S0,
indicating that soil microbial metabolic activity increased with an
increased amount of straw returned. The AWCD of each treatment increased
rapidly at 24–72 h and stabilised after 120 h of incubation.
Concurrently, the AWCD in S2 was significantly increased by 94.6% and
70.8% (P < 0.05) compared with those in S0 and S1/2
(Fig. S3a). The Shannon and Simpson indices demonstrated a progressive
increase with increasing levels of straw returned, and significant
differences were noted among the treatments (P < 0.05).
No significant difference (P > 0.05) in the Pielou
index was observed among the treatments (Fig. S3d). Principal component
and 2-way cluster heatmap analyses were performed based on the AWCD
values of 31 carbon sources at 120 h (Figs 3 and S4). Both analyses
revealed similar carbon source utilisation patterns across the
treatments, with S1/2 distinguishing between S0 and S1 and S2
distinguishing between all treatments. Based on the PCA, the correlation
strength between the three principal components and each type of carbon
source was further analysed (Table S3). The carbon sources with an
absolute loading value >0.6 were the main carbon sources for
soil microbial metabolism. The results revealed that the types of carbon
sources contributing to the heterogeneity of soil microbial carbon
metabolism were primarily carbohydrates, amino acids, and carboxylic
acids, consistent with the cluster heatmap results.
3.5. Correlation between soil carbon and nitrogen fractions
and soil microorganisms
Straw application affected the soil carbon and nitrogen fractions and
soil microorganisms. It indirectly affected the soil carbon and
reservoirs by affecting soil microorganisms. Bacteria and fungi with
high relative abundances at the phylum and genus levels were selected
for RDA (Fig. 4) and Pearson correlation heatmap analyses (Fig. 5),
respectively. The correlation between the two was explained based on
these analyses. The RDA results revealed that among the soil bacteria,
Proteobacteria played a major role (P = 0.002) in explaining the
changes in soil carbon fractions, whereas Acidobacteriota was the main
factor (P = 0.004) causing changes in the soil nitrogen
fractions. Among the soil fungi, Mortierellomycota explained 30.1 % and
29.3 % (P < 0.05) of the changes in soil carbon and
nitrogen fractions, respectively. Compared to other carbon sources,
carbon sources of amino acids had the highest explanatory power for the
changes in soil carbon and nitrogen fractions (54.3 % and 48.5 %,
respectively, P < 0.01).
Results of the correlation heatmap analysis were consistent with those
of the RDA (Fig. 5). A significant (P < 0.05) or highly
significant (P < 0.001) positive correlation was
observed between Proteobacteria and the soil carbon and nitrogen
fractions and a significant (P < 0.05) or highly
significant (P < 0.001) negative correlation was
observed between Acidobacteriota and the soil carbon and nitrogen
fractions. There was a strong correlation between the two bacteria and
the DOC, MBC, and LFON variables (P < 0.001).
Significant positive (P < 0.05) and negative (P < 0.05) correlations in the soil fungi and soil carbon and
nitrogen fractions were observed between Mortierellomycota and
Ascomycota, respectively, with a significant positive correlation
(P < 0.01) between Mortierellomycota and DON. Carbon
sources with strong correlations with the soil carbon and nitrogen pools
were concentrated in amino acids, carbohydrates, carboxylic acids, and
polymers (particularly amino acids). For example, amino acid carbon
sources such as glycyl-L-glutamic acid and L-asparagine exhibited
significant (P < 0.05 and P < 0.01) or
highly significant positive correlations (P < 0.001)
with DOC, MBC, and LFON. The PLS-PM results revealed that straw return
was the main factor affecting the soil carbon and nitrogen fractions
(Fig. 6). Moreover, straw return significantly (P <
0.05) affected the soil carbon fraction by influencing soil bacterial
diversity.