Understanding soil production of the trace gas carbonyl sulfide (OCS) is key to its use as a tracer of ecosystem function. Underlying its application is the observation that vascular plants consume atmospheric OCS via their stomatal pores in proportion with CO 2 photosynthesis and that soil fluxes of OCS are negligible in comparison. Recent soil-centered studies demonstrate that soils can produce OCS and contribute as much as a quarter of the atmospheric terrestrial flux. Despite the potential widespread importance of soil OCS emissions, insufficient data exist to predict variations in OCS production across ecosystems, and the chemical and biological drivers of OCS production are virtually unknown. In this study, we address this knowledge gap by investigating variables controlling OCS soil production including soil physical and chemical properties, microbial community composition, and sulfur speciation in two independent surveys. We found that soil OCS production was nearly ubiquitous across the 58 sites, increased exponentially with temperature, and was insensitive to visible light conditioning. Soil pH, N, and C/N were predictors of OCS soil production rates in both soil surveys. Patterns in soil S speciation and predicted microbial S-cycling pathways both pointed to S-containing amino acids such as cysteine and methionine and their derivatives as potential precursors for OCS production. Elevated sulfate levels were associated with OCS production in some soils. This study provides new mechanistic insight into OCS production in soils and presents strategies to represent soil OCS fluxes that facilitate the use of OCS as a tracer for leaf-level processes related to carbon and water cycling.

A field experiment was conducted at three sites (New York, Pennsylvania, and Maryland) in 2016 to test the effects of drill interseeding a cover crop mixture consisting of cereal rye (Secale cereale L.), annual ryegrass (Lolium multiflorum Lam.), hairy vetch (Vicia villosa Roth), and red clover (Trifolium pratense L.) into organically managed corn (Zea mays L.). We quantified the effects of corn density on weed biomass, cover crop biomass, and corn grain yield. Increasing corn density had a direct negative effect on interseeded cover crop biomass as well as indirect effects that were mediated by light transmission and weeds. At two sites, corn grain yield at the low corn density (3.71 plants m-2) did not differ from corn grain yield at the standard density (7.41 plants m-2). We also compared plots with and without interseeded cover crops at the same standard corn planting density. Corn grain yield did not differ, but weed biomass at the October sample date was 31% lower in plots with interseeded cover crops compared to plots without. Our results suggest that organic farmers may be able to (i) improve weed suppression in corn by interseeding cover crops and (ii) optimize cropping system performance by planting corn at a slightly lower rate (e.g., 5-10%) than what is typically used when interseeding cover crops. Additional research should be conducted across a wider range of environments to determine corn planting rate recommendations that optimize corn yield, cover crop growth, weed suppression, and profitability in organic cropping systems.

Core Ideas Corn silage and grain yield monitors collect yield data of relevance to farmers. Evaluation of quality of yield monitor data is essential, especially for silage. A data cleaning protocol, consistent across fields, farms, and years, is needed. Semi‐automation is needed for quick and consistent processing of whole‐farm data. Yield monitor data are being used for a variety of purposes including conducting on‐farm studies, assessing nutrient balances, determining yield potential, and creating management zones. However, standardization of raw data processing is needed to obtain comparable data across fields, farms, and years. Our objective was to evaluate the impact of data cleaning protocols on corn (Zea mays L.) grain and silage yield data at the whole field (with and without headlands) and within field (soil map unit) scales. Corn silage data from 145 fields (three farms) and grain data from 88 fields (three farms) were processed. Comparisons were made to evaluate yields among three levels of cleaning: (i) none; (ii) automated cleaning (“Auto”) with filter settings derived for 10 fields per farm; and (iii) automated cleaning with manual inspection for unrepresentative patterns, after the automated cleaning step was completed (“Auto+”). The Auto+ cleaning process was conducted separately by three individuals to evaluate person‐to‐person differences. Spatial Management System software was used to read raw data and transfer to Ag Leader format. Yield Editor software was used to clean data (Auto and Auto+). Results showed the necessity of data cleaning, especially for corn silage. However, considering less than 5% deviation between methods at three spatial scales, the Auto and Auto+ cleaning resulted in similar output, as long as (i) each field or subfield included at least 100 harvester measurement points, and (ii) a moisture filter was applied for corn silage data.

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The conversion of forest to agricultural soils is a widespread activity in tropical systems, and its link to nitrous oxide (N 2 O) fluxes and nitrogen cycling gene abundance is relevant to understand environmental drivers that may interact with climate change. A current challenge to estimating N 2 O emissions from land use conversion is an incomplete understanding of crop-specific impacts on denitrifier communities and the N 2 O fluxes driven by differences in the above-and below-ground inputs with crop type. To address this knowledge gap in tree crops, we evaluated N 2 O fluxes and denitrification gene abundance and their relationships with soil and plant residue characteristics in citrus and eucalyptus plantations in the field and in soil incubations. We found that the accumulated N 2 O fluxes from soil were lower for the two agricultural field sites than those for their adjacent forest sites in dry and wet seasons. The N 2 O fluxes were higher in the wet season, and this seasonal difference persisted even when the soils collected from both seasons were incubated under the same moisture and temperature conditions in the lab for 30 days. Increased N 2 O fluxes in the wet season were accompanied by an increase in soil nirK and nosZ gene abundance, the dissolved organic carbon (DOC) concentration, and the total soil carbon (C) and nitrogen (N) content. In turn, the abundance of denitrifiers, as indicated by nirK, nirS, and nosZ gene copy numbers, showed a low but significant positive correlation with soil bulk density. Our results suggest that soil moisture, leaf litter, and crop residues influence the seasonal differences in both N 2 O fluxes and abundance of denitrifiers in citrus-and eucalyptus-cultivated soils, likely through effects on soil physicochemical characteristics. These findings highlight the overwhelming role of environmental drivers that can make investigating microbial drivers difficult in the field and open the possibility for a better understanding of N cycling processes in tropical soils based on paired field-and incubation-based experimentation.