Location: Soil Management and Sugarbeet Research2018 Annual Report
1a. Objectives (from AD-416):
Objective 1: Develop and refine management practices for enhanced yields, nitrogen use efficiencies, carbon sequestration, soil biodiversity and function, and reduced greenhouse gas emissions from agricultural systems of the Great Plains. Sub-objective 1.1: Improve nutrient (especially nitrogen) management. Sub-objective 1.2: Reduce greenhouse gas emissions (CO2, N2O, CH4). Sub-objective 1.3: Characterize soil C and N stocks, fractions, isotopic signatures, and SOC chemistry with depth to develop BMPs that increase C-Seq. Sub-objective 1.4: Evaluate the effect of management practices on soil microbial structure and function. Sub-objective 1.5: Increase long-term productivity and economic returns. Objective 2: Improve procedures for national agricultural greenhouse gas inventories and indices to assess soil biology, soil health, and nutrient management. Sub-objective 2.1: Develop a new USDA ARS Nutrient Uptake and Outcome (NUOnet) database and improve nutrient indices and tools. Sub-objective 2.2: Improve procedures and tools for assessment of greenhouse gas emissions (CO2, N2O, CH4), NUE and C-Seq. Sub-objective 2.3: Develop a new national soil biology database. Sub-objective 2.4: Develop a new soil biology (soil health) index to quantify beneficial bacteria in soil. Objective 3: Assess the long-term consequences of management practices and cropping systems on nitrogen use efficiencies, greenhouse gas emissions, carbon sequestration, soil biodiversity and functions. Sub-objective 3.1: Implement a data management plan and procedures to facilitate data archiving and retrieval in the national databases developed in Objective 2 (NUOnet, GRACEnet, soil biology). Sub-objective 3.2: Improve long-term nutrient (especially nitrogen) management, while reducing the long-term emissions of greenhouse gases (CO2, N2O, CH4), increasing C-Seq, and enhancing soil health.
1b. Approach (from AD-416):
Often the management of agricultural lands has led to degradation of the soil resource, including the depletion of soil carbon and the loss of natural and synthetic nutrients. The lost carbon and nutrients negatively impact producer’s profit margins and have negative environmental impacts (lead to increased buildup of greenhouse gases (GHG) in the atmosphere and pollution of surface and ground water resources). Improved agricultural management can reverse this degradation, improve profit margins and minimize or even mitigate the negative environmental impacts. The overall goal of this project is to develop new and/or improved best management practices (BMPs), new and/or improved models, tools and databases, and sustainable production systems that can help us adapt to and/or mitigate climate change. We will use a combined approach that incorporates field applied studies to develop BMPs (Objective 1); develop and/or improve models, databases, and analytical tools (Objective 2); and conduct field analysis of long-term patterns and processes to assess if the performance of the BMPs is maintained, or improved, over time, and if the models and/or other tools can simulate measured values over decades (Objective 3). The scientific approach includes using different key performance variables of plant productivity such as crop yields; and soil health, nitrogen use efficiency, greenhouse gas emissions, soil carbon sequestration, and soil biological structure and function. A full economic analysis of each BMP will also be conducted. Additionally, basic mechanistic research to increase our knowledge of the basic science and processes of soil chemistry, soil physics, and soil biology, is also being conducted. The Soil Management and Sugar Beet Research Unit scientists have unique skills in each of these fields, and also bring outside collaborators together as part of a comprehensive and multi-faceted research program. As a result of this research, new and viable solutions are developed that address the complexities associated with soil and air management. Tools and information are provided to producers, land managers, and policy makers helping to ensure productive and healthy soils, climate change mitigation and adaptation, and improved air and water quality. Farm sustainability and profitability are improved while improving conservation and minimizing negative environmental impact.
3. Progress Report:
This report is for a new project which began in February 2017. It continues the research from 3012-11000-011-00D. Objective 1. All milestones are fully met. Studies about management practices related to long-term productivity of Great Plains agriculture continue. Studies on increasing the sustainability of these systems to sequester soil carbon, reduce greenhouse gas emissions, increase nitrogen use efficiencies and economic returns, prevent soil/water degradation, enhance yields, and maintain soil biology continue to be conducted. Various management strategies, such as use of right nitrogen fertilizer source, type, and rate, are being studied. The use of cover crops, crop residue management, and tillage practices that minimize soil disturbance is also being monitored. The use of cropping systems as management practices (e.g., polycrops, sorghum sudangrass, and other rotations) is being assessed. These studies are providing information about how to improve long term management of cropping systems to be more sustainable with higher yields and higher nutrient use efficiencies. Research on the influence of a microbial inoculant in improving drought tolerance in winter wheat has been established at Colorado State University (CSU) Agricultural Research, Development and Education Center (ARDEC). Study includes the use of various delivery systems for applying the microbial inoculant and its efficacy on multiple wheat varieties. Effects of management practices on soil microbial abundance and biodiversity are being monitored for irrigated corn (Colorado), wheat (Colorado, Oregon, and Idaho), and potato (Colorado). Preliminary greenhouse studies show the potential for biological soil amendments to increase drought resistance. A new method of inorganic carbon removal was implemented for quick analysis of stable isotopes, expanding the laboratory’s capacity to measure deep soil carbon in calcareous soils. Trace gas samples were collected from replicated field plots under different treatments to investigate the impacts of management practices including: fertilizer source (synthetic nitrogen, manure, enhanced efficiency fertilizer), fertilizer application rate (0 – 180 kg N/ha), residue management (50% removal, no removal), and crop rotation (continuous corn, corn/barley rotation). Crop nitrogen uptake and use efficiencies were measured for all the long-term studies at ARDEC, and studies to assess long-term nitrogen budgets to determine long-term nitrogen use efficiencies and the potential to reduce losses of reactive nitrogen are progressing on schedule. Objective 2. All milestones are fully met. Carbon sequestration and greenhouse gas emissions: The publically available Greenhouse gas reduction through Agricultural Carbon Enhancement network/ Resilient Economic Agricultural Practices (GRACEnet/REAP) platform has been enhanced and currently houses more than 120,000 greenhouse gas measurements from various cropping and grazing systems across the U.S. dating to the 1980s. The GRACEnet data system now contains crop yield, soil carbon, greenhouse gas (GHG) emission, land management, weather, and other information from 35 field sites across the U.S. Greenhouse gas models continue to be developed and tested. Long-term harvested biomass, soil carbon stock, and nitrous oxide emissions data from studies in Colorado and other regions continue to be collected to improve and evaluate the DayCent model. Recent observational evidence shows that N2O emissions during springtime melting events are substantial in some northern regions. A snow melt N2O pulse algorithm was recently implemented in the DayCent ecosystem model. Tests using nearly continuous gas flux data from tower based micrometeorological methods in Ontario and Manitoba showed that the improved model performed better than the previous version. The new model is currently being evaluated against N2O observations across the U.S. calculated using atmospheric inversions. In addition to improving model algorithms, the databases needed to derive model input files have been enhanced. The National Resources Inventory (NRI) is a statistically-based sample of all non-federal land in the U.S. and provides land cover and use information needed as model inputs for simulations conducted for the national GHG inventory. Newly available NRI data from 2008-2012 for over 350,000 points representing agricultural land were compiled, entered in the model input database, and quality controlled for accuracy. The database was then used to extend model input files to 2012, simulations were performed, and results reported in the most recent national GHG inventory published by EPA in 2018.The soil biology system (myPhyloDB) has been optimized to increase the speed for all data uploading and handling procedures. Several new univariate and multivariate analyses have also been added. 500 soil samples from the NRCS Soil Health Assessment Initiative have been received and the first 300 samples have been analyzed for microbial community composition and beneficial gene abundance. These samples in addition with nearly 1000 samples from ongoing research projects analyzed under this research project are being used to develop indicator curves for selected beneficial genes (e.g., nitrogen fixation) and a general molecular assessment of soil health. A new prototype of the Excel Data Entry Template (DET) for the Nutrient Uptake and Outcome network (NUOnet) was developed and will be used to collect and upload data from cooperators across the U.S. to the recently developed web-based prototype of NUOnet. The DET is currently being tested with potential ARS contributors and international contributors, and data from 14 field sites has already been collected and is in the process of being uploaded to the NUOnet site for fall 2018 release. The new DET contains data on the impact of nutrient management, including how it affects yields and nutrient uptake, as well as data on how conservation practices affect off-site transport of nutrients via leaching, ammonia volatilization, surface runoff, and other loss pathways. The NUOnet DET was developed to connect to other databases such as GRACEnet, REAP, Agricultural Antibiotic Resistance (AgAR), the soil biology database, and the Long-Term Agroecosystem Research (LTAR) database. It will also interface with the USDA Food Data System (FooDS), which relates nutrient composition of food and biomarkers of human health. Objective 3. All milestones are fully met. Long-term studies were monitored at the Colorado State University Agricultural Research, Development and Education Center. Field sampling of nitrogen fertilization, no-tillage, and organic matter addition studies was completed for the 2017 field year, and laboratory analyses are in progress. Long-term data analysis is in progress and has resulted in one peer-reviewed publication on deep soil carbon under long-term no-tillage compared to strip tillage. Although strip-tillage improved yield by 13%, soil carbon was lost even with low-impact tillage. Laboratory analyses for field sampling of nitrogen fertilization, no-tillage, and organic matter addition studies are underway. Data analysis has resulted in 1 peer-reviewed publication on the impact of residue removal on soil microbial communities and soil C fractions. This publication was recently featured in the tri-society magazine CSA News in June. All of the long-term analysis of the nitrogen fertilizer plots using a nitrogen budget approach shows that nitrogen deposition is an important pathway for an irrigated no-till continuous corn rotation at this site in Northern Colorado. Additional long-term analyses of nitrogen budgets are being conducted for other crop rotations. Studies on the long-term effects on soil biological diversity and function, greenhouse gas emissions, carbon sequestration, nitrogen use efficiencies, and macro- and micro-nutrient dynamics are being conducted. Studies are aimed at continuing to assess the long-term effects of fertilizer, soil, and crop management to transfer best management practices that contribute to sustainability, higher resource use efficiencies, and increased economic returns. In cooperation with U.S. Agency for International Development (USAID), Virginia Tech, and Penn State, we are analyzing data from long-term studies conducted in the Andean region of Ecuador assessing the potential of conservation agriculture, using-no till, crop residue management and nitrogen fertilization, to increase sustainability and economic returns for farmers.
1. The Nitrogen Index. One problem of agricultural systems that receive nitrogen inputs is the need for tools that can rapidly assess how management practice decisions can contribute to reduced losses of reactive nitrogen and increased nitrogen use efficiencies. An ARS researcher in Fort Collins, Colorado developed the Nitrogen Index 4.5.1, which includes different versions of the tool for California, Kentucky, South Dakota, Mexico, the Caribbean, Ecuador, Brazil, Bolivia, and other regions and is available online for download by users. This tool can be used to conduct quick assessments of the effects of management practices on nitrogen use efficiencies. Surveys of the Nitrogen Index users conducted in 2016, 2017 and 2018 indicate that the tool is being used to develop nutrient management and conservation management plans for farmers from the U.S. and other countries. Historically, the Nitrogen Index has been downloaded or distributed over 2,000 times in 65 countries and used for at least 4,500 farmers covering over 240,000 acres. Additionally, professors use the Nitrogen Index as a teaching tool for 1,516 undergraduate students and 432 graduate students, and the tool has impacted at least 566 professors, crop consultants, or other professional peers (national and international). The tool was downloaded over 100 times in FY 2018, impacting over 2,820 customers during 2018.
2. Reducing uncertainty in biofuel assessments. The simple methods typically used to calculate the greenhouse gas intensity of biofuel feedstocks are characterized by high uncertainty. An ARS scientist in Fort Collins, Colorado was a member of the team that compared different approaches for calculating soil N2O emissions, which are a large portion of the overall biofuel greenhouse gas footprint. A significant impact of this research was the finding that using the typical methodology to estimate soil greenhouse gas emissions tends to over-estimate N2O emissions and leads to large uncertainties. In contrast, the recommended method using the DayCent ecosystem model provides more accurate estimates and uncertainties can be minimized to acceptable levels by aggregating results, thus reducing the uncertainty penalties imposed on producers.
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