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Abstract Crop N decision support tools are typically based on either empirical relationships that lack mechanistic underpinnings or simulation models that are too complex to use on farms with limited input data. We developed an N mineralization model for corn that lies between these endpoints; it includes a mechanistic model structure reflecting microbial and texture controls on N mineralization but requires just a few simple inputs: soil texture soil C and N concentration and cover crop N content and carbon to nitgrogen ratio (C/N). We evaluated a previous version of the model with an independent dataset to determine the accuracy in predictions of unfertilized corn (Zea maysL.) yield across a wider range of soil texture, cover crop, and growing season precipitation conditions. We tested three assumptions used in the original model: (1) soil C/N is equal to 10, (2) yield does not need to be adjusted for growing season precipitation, and (3) sand content controls humification efficiency (ε). The best new model used measured values for soil C/N, had a summertime precipitation adjustment, and included both sand and clay content as predictors ofε(root mean square error [RMSE] = 1.43 Mg ha⁻¹;r² = 0.69). In the new model, clay has a stronger influence than sand onε, corresponding to lower predicted mineralization rates on fine‐textured soils. The new model had a reasonable validation fit (RMSE = 1.71 Mg ha⁻¹;r² = 0.56) using an independent dataset. Our results indicate the new model is an improvement over the previous version because it predicts unfertilized corn yield for a wider range of conditions. 

ABSTRACT This study investigated the differences in microbial community abundance, composition, and diversity throughout the depth profiles in soils collected from corn and soybean fields in Iowa (United States) using 16S rRNA amplicon sequencing. The results revealed decreased richness and diversity in microbial communities at increasing soil depth. Soil microbial community composition differed due to crop type only in the top 60 cm and due to location only in the top 90 cm. While the relative abundance of most phyla decreased in deep soils, the relative abundance of the phylum Proteobacteria increased and dominated agricultural soils below the depth of 90 cm. Although soil depth was the most important factor shaping microbial communities, edaphic factors, including soil organic matter, soil bulk density, and the length of time that deep soils were saturated with water, were all significant factors explaining the variation in soil microbial community composition. Soil organic matter showed the highest correlation with the exponential decrease in bacterial abundance with depth. A greater understanding of how soil depth influences the diversity and composition of soil microbial communities is vital for guiding sampling approaches in agricultural soils where plant roots extend beyond the upper soil profile. In the long term, a greater knowledge of the influence of depth on microbial communities should contribute to new strategies that enhance the sustainability of soil, which is a precious resource for food security. IMPORTANCE Determining how microbial properties change across different soils and within the soil depth profile will be potentially beneficial to understanding the long-term processes that are involved in the health of agricultural ecosystems. Most literature on soil microbes has been restricted to the easily accessible surface soils. However, deep soils are important in soil formation, carbon sequestration, and providing nutrients and water for plants. In the most productive agricultural systems in the United States where soybean and corn are grown, crop plant roots extend into the deeper regions of soils (>100 cm), but little is known about the taxonomic diversity or the factors that shape deep-soil microbial communities. The findings reported here highlight the importance of soil depth in shaping microbial communities, provide new information about edaphic factors that influence the deep-soil communities, and reveal more detailed information on taxa that exist in deep agricultural soils.