The Yellow River Delta (YRD) region is an important production base in Shandong Province. It encompasses an array of diversified crop systems, including the corn–wheat rotation system (Wheat–Corn), soybean–corn rotation system (Soybean–Corn), fruits or vegetables system (Fruit), cotton system (Cotton) and rice system (Rice). In this study, the communities of ammonia oxidizer–, denitrifier– and nitrogen (N)–fixing bacteria in those cropping systems were investigated by Illumina Miseq sequencing. We found that Rice soil exhibited significantly higher diversity indices of investigated N–cycling microbial communities than other crop soils, possibly due to its high soil water content. Wheat–Corn soils had higher abundances of nitrification gene amoA and denitrification genes nirK and nirS, and exhibited higher soil potential nitrification rate (PNR), compared with Soybean–Corn, Cotton and Fruit soils. Consistently, redundancy analysis (RDA) showed that soil water content (SWC), electrical conductivity (EC), and total nitrogen (TN) were the most important influencing factors of the diversity and structure of the investigated N–cycling microbial.

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Investigating the phosphorus (P) sources, pathways, and final sinks are important to reduce P pollution and improve P management. In this study, substance flow analysis (SFA) was performed for P flow analysis from 1995 to 2016 in different crops of Dongying District, a core region of the alluvial delta at the estuary of the Yellow River. The results showed that P input steadily increased from 1.48 × 104 t in 1995 to 2.16 × 104 t in 2007, and then decreased from 1.90 × 104 t in 2010 to 1.78 × 104 t in 2016. Chemical fertilizers made the highest contribution to P input. The cotton with the highest P load was on the top of P load risk ranks. More importantly, this study applied the Partial Least Squares Path Modeling (PLS-PM) model for P flow analysis and established the numerical relationship between the variables (including fertilizers, straws return-to-field, harvested grains, discarded straw, and P erosion and runoff), P use efficiency (PUE) and P load. The analysis revealed that fertilizer and crop production are the key factors affecting the PUE. Therefore, optimizing the use of P-fertilizer whilst maintaining yields can be an effective strategy to improve the local region PUE.