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.