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At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

AmeriFlux FLUXNET-1F US-AR1 ARM USDA UNL OSU Woodward Switchgrass 1

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-AR1 ARM USDA UNL OSU Woodward Switchgrass 1. This is the FLUXNET version of the carbon flux data for the site US-AR1 ARM USDA UNL OSU Woodward Switchgrass 1 produced by applying the standard ONEFlux (1F) software. Site Description - The ARM USDA UNL OSU Woodward Switchgrass 1 tower is located on public land owned by the USDA-ARS Southern Plains Range Research Station in Woodward, Oklahoma. The site is on a former native prairie that is in the process of changing to switchgrass. A second companion site (ARM USDA UNL OSU Woodward Switchgrass 2) is on a former wheat field. In Spring 2009, the former native prairie site was burned, cattle were put on the pasture to graze down emergent grass, and broadleaf herbicide was sprayed. In Summer 2009, the cattle were removed from the pasture, and the site was sprayed with herbicide to kill all grass. In Spring 2010, prior to the planting of switchgrass, final herbicide was sprayed to kill cheat grass and to control broadleaf plants.

Billesbach, Dave↗
DOE OSTI2023

AmeriFlux FLUXNET-1F US-AR2 ARM USDA UNL OSU Woodward Switchgrass 2

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-AR2 ARM USDA UNL OSU Woodward Switchgrass 2. This is the FLUXNET version of the carbon flux data for the site US-AR2 ARM USDA UNL OSU Woodward Switchgrass 2 produced by applying the standard ONEFlux (1F) software. Site Description - The ARM USDA UNL OSU Woodward Switchgrass 2 tower is located on public land owned by the USDA-ARS Southern Plains Range Research Station in Woodward, Oklahoma. The site is on a former wheat field that is in the process of changing to switchgrass. A companion site (ARM USDA UNL OSU Woodward Switchgrass 1) is on a former native prairie. Previous wheat was planted in Fall 2008. In Spring 2009, herbicide was applied to kill the wheat prior to switchgrass planting. Later in the year, the site was sprayed with post-emergence herbicide. In 2010, fertilization occurred before herbicide was sprayed for broadleaf control.

Billesbach, Dave↗
DOE OSTI2024

Transforming Drainage Research Data (USDA-NIFA Award No. 2015-68007-23193)

This dataset contains research data compiled by the “Managing Water for Increased Resiliency of Drained Agricultural Landscapes” project a.k.a. Transforming Drainage. This project was funded from 2015-2021 by the United States Department of Agriculture, National Institute of Food and Agriculture (USDA-NIFA, Award No. 2015-68007-23193). Data are also available from a separate web-accessible application (drainagedata.org). At drainagedata.org, users can visualize the data with customized tools, query based on specific sites and measurements of interest, and access site photographs, maps, summaries, and publications. Additional data or edits made following the publication of this data here at USDA NAL Ag Data Commons will be posted under the Versions tab on drainagedata.org. These data began in 1996 and include plot- and field-level measurements for 39 experiments across the Midwest and North Carolina. Practices studied include controlled drainage, drainage water recycling, and saturated buffers. In total, 219 variables are reported and span 207 site-years for tile drainage, 154 for nitrate-N load, 181 for water quality, 92 for water table, and 201 for crop yield.

Modeling↗
DOE OSTI2022

AmeriFlux FLUXNET-1F US-HWB USDA ARS Pasture Sytems and Watershed Management Research Unit- Hawbecker Site

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-HWB USDA ARS Pasture Sytems and Watershed Management Research Unit- Hawbecker Site. This is the FLUXNET version of the carbon flux data for the site US-HWB USDA ARS Pasture Sytems and Watershed Management Research Unit- Hawbecker Site produced by applying the standard ONEFlux (1F) software. Site Description - Hawbecker farm is owned by Penn State University. The farming that took place was performed by their Farm Operations Division. The ground is rolling terrain, next to wooded areas, the Beef and Sheep Reasearch Farm, The University Airport, and other large fields maintained by Farm Operations. At the time of this collection period, the site housed another Meteorological Site, a Phenocam, and the GraceNet plots. Crop Rotation during period was 2 years Alfalfa, 1 year Corn for grain and 1 year Wheat.

Goslee, Sarah↗
DOE OSTI2024

Small Hydropower Energy for USDA REAP [Slides]

This presentation informs U.S. Department of Agriculture (USDA) staff on hydropower technologies which can provide clean energy for agricultural producers and rural small business owners.

13 HYDRO ENERGY↗
DOE OSTI2022

Mentoring in the USDA Forest Service: A Survey of Aquatic Professionals

Abstract Mentoring is suggested as an important strategy to promote workplace inclusivity and is shown to be positively associated with high employee morale, yet mentee needs and experiences may not be universal. To evaluate mentoring impacts from the perspective of USDA Forest Service employees, we conducted an online survey of 251 aquatic professionals, including managers and scientists. 70% of respondents had mentors, and mentorship status did not vary across demographic characteristics. Previous mentoring relationships were most frequently identified as “informal” rather than “formal”; female employees were more likely to desire formal mentoring. Mentored respondents found their work more challenging, fulfilling, and valuable than unmentored respondents. Mentees looked for mentors who could provide constructive feedback, speak candidly, use active listening skills, and who cared about their careers. Overall, respondents were satisfied with their mentors’ skills. Despite strong demand for mentoring, access to mentors among aquatic professionals appears low across all categories.

Forestry↗
DOE OSTI2022

Unraveling the effects of management and climate on carbon fluxes of U.S. croplands using the USDA Long-Term Agroecosystem (LTAR) network

Understanding the carbon fluxes and dynamics from a broad range of agricultural systems has the potential to improve our ability to increase carbon sequestration while maintaining crop yields. Short-term, single-location studies have limited applicability, but long-term data from a network of many locations can provide a broader understanding across gradients of climate and management choices. Here we examine eddy covariance measured carbon dioxide (CO 2 ) fluxes from cropland sites across the United States Department of Agriculture's Long-Term Agroecosystem Research (LTAR) network. The dataset was collected between 2001 and 2020, spanning 13 sites for a total of 182 site-years. Average seasonal patterns of net ecosystem CO 2 exchange (NEE), gross primary productivity (GPP), and ecosystem respiration (R eco ) were determined, and subsequent regression analysis on these “flux climatologies” was used to identify relationships to mean annual temperature (MAT), mean annual precipitation (MAP), cropping systems, and management practices. At rainfed sites, carbon fluxes were better correlated with MAP (r2 ≤ 0.5) than MAT (r2 ≤ 0.22). Net carbon balance was different among cropping systems (p < 0.001), with the greatest net carbon uptake occurring in sugarcane (Saccharum spp. hybrids) and the least in soybean (Glycine max) fields. Crop type had a greater effect on carbon balance than irrigation management at a Nebraska site. Across cropping systems, grain crops often had higher GPP and were more likely to have net uptake when compared to legume crops. This multi-site analysis highlights the potential of the LTAR network to further carbon flux research using eddy covariance measurements.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Morphological Characterization of Fresh and 20-Yr-Old Fixed Nematode Specimens of Sauertylenchus maximus (Allen, 1955) Siddiqi, 2000 Deposited in the USDA Nematode Collection from Arlington National Cemetery, VA, USA

Sauertylenchus maximus was discovered during a survey conducted at the Arlington National Cemetery, Virginia, for the type specimens of Hoplolaimus galeatus. Besides the fresh material, the fixed specimens of S. maximus were also studied by molecular and morphological means. The morphological and morphometric characteristics of the recovered fresh material were consistent with the original and other description(s) of this species. The fixed specimens used in this study were preserved in a 3% formaldehyde and 2% glycerin solution for over 20 yr. Molecular analyses of the fresh and fixed specimens were performed using internal transcribed spacer, D2–D2 expansion segments of 28S large subunits, and 18S small subunit ribosomal DNA sequences. To our knowledge, this represents the first report of S. maximus from Virginia and the first report of a successful DNA extraction from fixed nematode specimens.

18S rDNA↗
DOE OSTI2022

Comparison of Infiltration Test Methods for Soil Health Assessment

Infiltration rate (IR) has been commonly used as a metric to evaluate soil quality and health. For the USDA Soil Quality Test Kit, a 15-cm (6-in) diameter (ID) cylinder is used to measure IR with 444 cm 3 (equivalent to 2.54 cm or 1 in) of water while other standard IR procedures require substantially larger volumes of water. The general objective of this study was to compare different methods for IR measurement. Using three replications, IR measurements were conducted along a 9-m (27-ft) long transect in two different soil types by the double-ring infiltrometer (DRI) using 25- and 50-cm (10-and 20-in, respectively) cylinders, single-ring infiltrometer (SRI) using 25- and 50-cm cylinders, Cornell sprinkle infiltrometer (CSI) using a 24.1-cm (9.5-in) cylinder, the USDA recommended procedure using a 15-cm diameter cylinder (hereafter referred to as USDA-15 method), and a modified USDA method using a 24.1-cm diameter cylinder. Although the USDA-15 method is simple and requires a small amount of water, based on high variability among replications and significant reduction in IR during early stages of water entry into the soil, the procedure does not offer an accurate estimate of the soil infiltration potential. The CSI procedure was reproducible, but it is more cumbersome to perform than other methods. The DRI, SRI, and CSI methods required a much greater volume of water than the USDA-15 method but produced results that are more consistent. The most consistent results were obtained by the CSI and DRI methods. The modified USDA method results were similar to the SRI method and were an improvement over the original USDA-15 method. For assessing soil health, additional investigations should be conducted to evaluate a modified version of the USDA procedure using a larger cylinder.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Biofuels Information Center

The purpose of the Biofuels Information Center (BIC) task is to provide relevant data, information, reports, and web-based tools to all bioenergy stakeholders. The BIC task began in FY08 to meet the requirement under Title II, Sec. 229 of the Energy Independence and Security Act of 2007 (EISA) requires DOE to develop a "Biofuels and Biorefinery Information Center". The BIC task supports biofuels pages content on the EERE's most visited website - the Alternative Fuels Data Center (AFDC http://www.afdc.energy.gov) and the Bioenergy Atlas tools (currently archived) (previous address https://maps.nrel.gov). This task results in more than 1.7 million web pageviews (an instance of an internet user visiting a webpage) per year. In FY22, the task completed the final year of the 5 year USDA Biofuels Infrastructure Partnership (BIP). The USDA BIP expanded infrastructure for E15 and/or E85 to approximately 850 stations and NREL received and reviewed data for quality analyzed all infrastructure and sales data collected by USDA. Stations are privately held and previously it was difficult to ascertain infrastructure and sales data. This unique dataset allows insight into infrastructure data (number of pumps and tanks, costs to install new equipment) and sales data (price and volume for E10, E15, E85, and diesel by month). The 2021 USDA BIP National Summary Report is with DOE for review prior to publication. Future work will include the biannual Bioenergy Industry Status Report (4 previous versions have been published) . The task also supports the principal investigator's time to engage stakeholders on infrastructure and deployment of biofuels. This includes leading, membership, and participation in the following roles: member Board of Advisors at the Fuels Institute, voting member for multiple UL standards committees, Co-Chair of the Infrastructure team at Agriculture/Auto/Ethanol, Member of Coordination Research Council's ULSD Corrosion Committee. The Principal investigator routinely responds to industry inquires to assist in deployment of biofuels regularly.

biofuels↗
DOE OSTI2023

Registration of ‘Cedar Creek’ switchgrass

‘Cedar Creek’ (Reg. no. CV-290, PI 700113) switchgrass (Panicum virgatum L.) was selected for increased winter survivorship for three cycles, using surviving plants from ‘Kanlow’. The first two cycles were conducted at multiple locations in Wisconsin, and the third cycle was conducted at the Cedar Creek Ecosystem Science Reserve, East Bethel, MN. All seed production and increases were conducted by either Illinois State University or the University of Illinois. Field evaluations of the third-cycle population were conducted at five locations in Wisconsin between 2017 and 2021, located within USDA hardiness zones 3–5. Field experiments were planted in both 2016 and 2017. Averaged over the five locations and all trial years, Cedar Creek had 91% ground cover, compared with 96% for Cave-in-Rock, 95% for Shawnee, and 91% for Liberty. Biomass yield of Cedar Creek averaged 12.17 Mg ha –1 , which was 20% higher than Liberty, 30% higher than Cave-in-Rock, 31% higher than Shawnee, and 520% higher than Kanlow. Cedar Creek is a high-biomass lowland-type of switchgrass and is the first lowland-type adapted to USDA hardiness zones 3–5. Cedar Creek was released to the public by USDA-ARS in 2021.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Application of multi-criteria decision analysis techniques and decision support framework for informing select agent designation for agricultural animal pathogens

The United States Department of Agriculture (USDA), Division of Agricultural Select Agents and Toxins (DASAT) established a list of biological agents and toxins (Select Agent List) that potentially threaten agricultural health and safety, the procedures governing the transfer of those agents, and training requirements for entities working with them. Every 2 years the USDA DASAT reviews the Select Agent List, using subject matter experts (SMEs) to perform an assessment and rank the agents. To assist the USDA DASAT biennial review process, we explored the applicability of multi-criteria decision analysis (MCDA) techniques and a Decision Support Framework (DSF) in a logic tree format to identify pathogens for consideration as select agents, applying the approach broadly to include non-select agents to evaluate its robustness and generality. We conducted a literature review of 41 pathogens against 21 criteria for assessing agricultural threat, economic impact, and bioterrorism risk and documented the findings to support this assessment. The most prominent data gaps were those for aerosol stability and animal infectious dose by inhalation and ingestion routes. Technical review of published data and associated scoring recommendations by pathogen-specific SMEs was found to be critical for accuracy, particularly for pathogens with very few known cases, or where proxy data (e.g., from animal models or similar organisms) were used to address data gaps. The MCDA analysis supported the intuitive sense that select agents should rank high on the relative risk scale when considering agricultural health consequences of a bioterrorism attack. However, comparing select agents with non-select agents indicated that there was not a clean break in scores to suggest thresholds for designating select agents, requiring subject matter expertise collectively to establish which analytical results were in good agreement to support the intended purpose in designating select agents. The DSF utilized a logic tree approach to identify pathogens that are of sufficiently low concern that they can be ruled out from consideration as a select agent. In contrast to the MCDA approach, the DSF rules out a pathogen if it fails to meet even one criteria threshold. Both the MCDA and DSF approaches arrived at similar conclusions, suggesting the value of employing the two analytical approaches to add robustness for decision making.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Application of multi-criteria decision analysis techniques and decision support framework for informing plant select agent designation and decision making

The United States Department of Agriculture (USDA) Division of Agricultural Select Agents and Toxins (DASAT) established a list of biological agents (Select Agents List) that threaten crops of economic importance to the United States and regulates the procedures governing containment, incident response, and the security of entities working with them. Every 2 years the USDA DASAT reviews their select agent list, utilizing assessments by subject matter experts (SMEs) to rank the agents. We explored the applicability of multi-criteria decision analysis (MCDA) techniques and a decision support framework (DSF) to support the USDA DASAT biennial review process. The evaluation includes both current and non-select agents to provide a robust assessment. We initially conducted a literature review of 16 pathogens against 9 criteria for assessing plant health and bioterrorism risk and documented the findings to support this analysis. Technical review of published data and associated scoring recommendations by pathogen-specific SMEs was found to be critical for ensuring accuracy. Scoring criteria were adopted to ensure consistency. The MCDA supported the expectation that select agents would rank high on the relative risk scale when considering the agricultural consequences of a bioterrorism attack; however, application of analytical thresholds as a basis for designating select agents led to some exceptions to current designations. A second analytical approach used agent-specific data to designate key criteria in a DSF logic tree format to identify pathogens of low concern that can be ruled out for further consideration as select agents. Both the MCDA and DSF approaches arrived at similar conclusions, suggesting the value of employing the two analytical approaches to add robustness for decision making.

59 BASIC BIOLOGICAL SCIENCES↗