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Creators/Authors contains: "Roley, Sarah S."

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  1. Biological nitrogen fixation is the conversion of dinitrogen (N2) gas into bioavailable nitrogen by microorganisms with consequences for primary production, ecosystem function, and global climate. Here we present a compiled dataset of 4793 nitrogen fixation (N2-fixation) rates measured in the water column and benthos of inland and coastal systems via the acetylene reduction assay, 15N2 labeling, or N2/Ar technique. While the data are distributed across seven continents, most observations (88%) are from the northern hemisphere. 15N2 labeling accounted for 67% of water column measurements, while the acetylene reduction assay accounted for 81% of benthic N2-fixation observations. Dataset median area-, volume-, and mass-normalized N2-fixation rates are 7.1 μmol N2-N m−2 h−1, 2.3 × 10−4 μmol N2-N L−1 h−1, and 4.8 × 10−4 μmol N2-N g−1 h−1, respectively. This dataset will facilitate future efforts to study and scale N2-fixation contributions across inland and coastal aquatic environments. 
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    Free, publicly-accessible full text available January 23, 2026
  2. Biological nitrogen fixation converts inert di-nitrogen gas into bioavailable nitrogen and can be an important source of bioavailable nitrogen to organisms. This dataset synthesizes the aquatic nitrogen fixation rate measurements across inland and coastal waters. Data were derived from papers and datasets published by April 2022 and include rates measured using the acetylene reduction assay (ARA), 15N2 labeling, or the N2/Ar technique. The dataset is comprised of 4793 nitrogen fixation rates measurements from 267 studies, and is structured into four tables: 1) a reference table with sources from which data were extracted, 2) a rates table with nitrogen fixation rates that includes habitat, substrate, geographic coordinates, and method of measuring N2 fixation rates, 3) a table with supporting environmental and chemical data for a subset of the rate measurements when data were available, and 4) a data dictionary with definitions for each variable in each data table. This dataset was compiled and curated by the NSF-funded Aquatic Nitrogen Fixation Research Coordination Network (award number 2015825). 
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  3. null (Ed.)
    In nitrogen (N)-limited terrestrial ecosystems, plants employ various strategies to acquire and conserve N, including translocation of N in perennial tissues and stimulation of N fixation in roots and soils. Switchgrass (Panicum virgatum) is a genotypically and phenotypically diverse perennial grass with two distinct ecotypes (lowland and upland) and numerous genotypes. It grows well in low-N soils, likely because of its ability to translocate N and to associate with N-fixing microbes, but little is known about variation in these traits among cultivars or even ecotypes. We measured N translocation, N fixation potential in roots and soils, soil net N mineralization, soil net nitrification, and biomass yields in 12 switchgrass cultivars grown in a replicated block experiment in southwestern Michigan, United States. Lowland cultivars had higher yields, rates of N translocation, soil net N mineralization, and N fixation potentials on washed, nonsterile roots, while upland cultivars exhibited higher N fixation potentials in root-free soil. N resorption efficiencies averaged 53 ± 5% (± standard error) for lowland versus 29 ± 3% for upland cultivars. Additionally, there were significant among-cultivar differences for all response variables except mineralization and nitrification, with differences likely explained by cultivar-specific physiologies and microbial communities. The ideal cultivar for biofuels is one that can maintain high yields with minimal fertilizer addition, and there appear to be several cultivars that meet these criteria. In addition, results suggest substantial N cycle differences among cultivars that might be exploited by breeders to create new or improved high-yielding, N-conserving switchgrass lines. 
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  4. Abstract Although time series in ecosystem metabolism are well characterized in small and medium rivers, patterns in the world's largest rivers are almost unknown. Large rivers present technical difficulties, including depth measurements, gas exchange (, ) estimates, and the presence of large dams, which can supersaturate gases. We estimated reach‐scale metabolism for the Hanford Reach of the Columbia River (Washington state, USA), a free‐flowing stretch with an average discharge of 3173 . We calculated from semi‐empirical models and directly estimated it from tracer measurements. We fixed at the median value from these calculations (0.5 ), and used maximum likelihood to estimate reach‐scale, open‐channel metabolism. Both gross primary production (GPP) and ecosystem respiration (ER) were high (GPP range: 0.3–30.8 g , ER range: 0.8–30.6 g ), with peak GPP and ER occurring in the late summer or early fall. GPP increased exponentially with temperature, consistent with metabolic theory, while light was seasonally saturating. Annual average GPP, estimated at 1500 g carbon , was in the top 2% of estimates for other rivers. GPP and ER were tightly coupled and 90% of GPP was immediately respired, resulting in net ecosystem production near 0. Patterns in the Hanford Reach contrast with those in small‐medium rivers, suggesting that metabolism magnitudes and patterns in large rivers may not be simply scaled from knowledge of smaller rivers. 
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  6. null (Ed.)
    Abstract. The active fraction of soil organic carbon is an important component of soil health and often isquickly assessed as the pulse of CO2 released by re-wetting dried soils in short-term(24–72 h) assays. However, soils can lose carbon (C) as they dry and, if soil samples vary in moisture content at sampling, differential C loss during the pre-assay dry-down period maycomplicate the assay's interpretations. We examined the impact of pre-assay CO2 loss ina long-cultivated agricultural soil at initial moisture contents of 30 %, 50 %, and 70 %water-filled pore space (WFPS). We found that 50 % and 70 % WFPS treatments lost more C duringdrying than did those in the 30 % WFPS treatment and that dry-down losses led to a 26 %–32 % underestimate of their CO2 pulses. We developed a soil-specificcorrection factor to account for these initial soil moisture effects. Future C mineralizationstudies may benefit from similar corrections. 
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  7. null (Ed.)
    Microbial communities help plants access nutrients and tolerate stress. Some microbiomes are specific to plant genotypes and, therefore, may contribute to intraspecific differences in plant growth and be a promising target for plant breeding. Switchgrass (Panicum virgatum) is a potential bioenergy crop with broad variation in yields and environmental responses; recent studies suggest that associations with distinct microbiomes may contribute to variation in cultivar yields. We used a common garden experiment to investigate variation in 12 mature switchgrass cultivar soil microbiomes and, furthermore, to examine how root traits and soil conditions influence microbiome structure. We found that average root diameter varied up to 33% among cultivars and that the cultivars also associated with distinct soil microbiomes. Cultivar had a larger effect on the soil bacterial than fungal community but both were strongly influenced by soil properties. Root traits had a weaker effect on microbiome structure but root length contributed to variation in the fungal community. Unlike the soil communities, the root bacterial communities did not group by cultivar, based on a subset of samples. Microbial biomass carbon and nitrogen and the abundance of several dominant bacterial phyla varied between ecotypes but overall the differences in soil microbiomes were greater among cultivars than between ecotypes. Our findings show that there is not one soil microbiome that applies to all switchgrass cultivars, or even to each ecotype. These subtle but significant differences in root traits, microbial biomass, and the abundance of certain soil bacteria could explain differences in cultivar yields and environmental responses. 
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  8. null (Ed.)