The integration of appropriate tillage practices with straw returning can effectively mitigate soil degradation in Northeast China. However, limited research has explored the impacts of different tillage practices combined with varying straw incorporation depths on the structure and diversity of soil microbial communities. In 2016, a field experiment was initiated using a two-factor split-plot design, featuring six treatments: two tillage depths of 10 cm (D10) and 30 cm (D30) combined with three straw management practices—straw mixing incorporation (SM), straw deep burial (SB), and straw removal (SR). Soil samples collected in 2019 were analyzed for multiple soil properties and microbial indices. Results indicated that both straw returning and tillage depth significantly influenced soil organic carbon (SOC), soil total nitrogen (STN), total phosphorus (TP), and total potassium (TK), with the D30 treatment combined with straw returning optimizing soil nutrient contents most effectively. Under straw returning, D10 significantly increased urease activity in the 0–10 cm soil layer, whereas D30 enhanced this enzyme activity in the 10–30 cm soil layer, while β-glucosidase activity was less responsive to tillage depth. For the D10 treatment with straw returning, acid phosphatase activity was markedly higher than that in the straw removal treatment, whereas N-acetyl-β-D-glucosaminidase activity exhibited the opposite trend. Straw-returning methods had no significant effects on the bacterial and fungal Chao1 indices, while the Shannon index was positively correlated with key soil properties. Redundancy analysis (RDA) of microbial community composition at the phylum level and soil environmental factors revealed that soil nutrients in the 0–10 cm soil layer were positively correlated with Actinobacteriota, Ascomycota, and Basidiomycota, whereas the explanatory power of soil nutrients for microbial community variation decreased in the 10–30 cm soil layer. Our results highlight that tillage depth and straw returning can regulate soil microbial community composition and enhance soil nutrient cycling, thereby providing a theoretical basis for optimizing the combined application mode of tillage and straw-returning practices in Northeast China.

Soil quality assessment is crucial for understanding soil heterogeneity and guiding appropriate agricultural practices. This study selected optimal soil indicators and MDS in the black soil area of Jilin Province, comparing different scoring methods, indicators and datasets to clarify soil quality spatial distribution characteristics and their relationship with environmental factors. Firstly, the IDS of soil indicators was screened via the correlation between yield and soil indexes. Then, PCA was used to select the MDS of the IQI derived from the LS method as the optimal evaluation model for assessing soil quality in the study area. The MDS included BD, SOM, AN and AK. The results showed that soil quality was mainly moderate (Grades II, III, IV), accounting for 70.28% and 78.38% of IDS and MDS, respectively, with IQI gradually increasing from northwest to southeast. Finally, environmental factors were integrated to analyze key drivers of regional soil quality differences: in the EHM region, the main influencing factors (in descending order) were Pre, TWI, Temp, Slope and PM; in the CEH region, they were Pre, Slope, PM, TWI and Temp; in the WSP region, they were Temp, TWI, PM, Pre and Slope.