Publications by authors named "Steven W Culman"

Intensive crop production on grassland-derived Mollisols has liberated massive amounts of carbon (C) to the atmosphere. Whether minimizing soil disturbance, diversifying crop rotations, or re-establishing perennial grasslands and integrating livestock can slow or reverse this trend remains highly uncertain. We investigated how these management practices affected soil organic carbon (SOC) accrual and distribution between particulate (POM) and mineral-associated (MAOM) organic matter in a 29-y-old field experiment in the North Central United States and assessed how soil microbial traits were related to these changes.

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Flooding can reduce corn growth and yield, but nitrogen (N) management practices may alter the degree to which plants are negatively impacted. Damage caused by flooded conditions may also affect the utilization of a post-flood N application to increase yield. The objectives of this study were to evaluate how pre-plant and pre-plant plus post-flood N applications contribute to corn growth and yield following flood conditions and to quantify the partial return of employing different N management strategies in the event of a flood.

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Plant breeders are increasing yields and improving agronomic traits in several perennial grain crops, the first of which is now being incorporated into commercial food products. Integration strategies and management guidelines are needed to optimize production of these new crops, which differ substantially from both annual grain crops and perennial forages. To offset relatively low grain yields, perennial grain cropping systems should be multifunctional.

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Soil management in urban areas faces dual challenges of reducing public exposure to soil contaminants, such as lead (Pb) and polycyclic aromatic hydrocarbons, and maintaining soil function. This study evaluated three management options for an urban lot in Cleveland, OH, containing 185 to 5197 mg Pb kg and 0.28 to 5.

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Background: Despite increasing popularity and improvements in terminal restriction fragment length polymorphism (T-RFLP) and other microbial community fingerprinting techniques, there are still numerous obstacles that hamper the analysis of these datasets. Many steps are required to process raw data into a format ready for analysis and interpretation. These steps can be time-intensive, error-prone, and can introduce unwanted variability into the analysis.

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