Location: Soil Management and Sugarbeet Research2017 Annual Report
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.
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.
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. Two field trials to study biological amendments were established at the Colorado State University (CSU) Agricultural Research, Development and Education Center (ARDEC) and are being monitored for wheat and sugar beet crops, and a corn study was established at the Limited Irrigation Research Farm (LIRF). Preliminary studies in the greenhouse show potential to use biological 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. A study was conducted implementing the recommended rate of manure with half of the applied nitrogen coming from organic sources (manure) and half from new controlled-release fertilizers to assess the efficiency of this approach. Trace gas samples were collected from replicated field plots under different treatments to investigate the impacts of 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/dry bean rotation, polycrop). 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 Greenhouse gas Reduction through Agricultural Carbon Enhancement network (GRACEnet) and Renewable Energy Assessment Project (REAP) web-based relational database continues to expand and currently houses more than 200,000 greenhouse gas measurements from various cropping and grazing systems across the U.S. dating to the 1980s. Additional data were entered into the Excel template and assimilated into the database. The GRACEnet data system now contains crop yield, soil carbon, greenhouse gas (GHG) emission, land management, weather, and other information from 33 field sites across the U.S. The Excel template has been modified to accommodate additional types of data, and the software used to assimilate files into the system and perform quality control has been improved and streamlined. 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. 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 used to extend model input files to 2012 and test simulations performed. 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. 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 will be tested with potential ARS contributors. 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 that is being developed is connected to other databases such as GRACEnet, REAP, Agricultural Antibiotic Resistance (AgAR), the soil biology database, and the Long-Term Agroecosystem Research (LTAR) database, and will be connected to other databases related to nutrient composition of food and biomarkers of human health (i.e, the USDA Food Data System [FooDS]). Surveys were conducted in 2016 and 2017 for users of the Nitrogen Index. Responses to the survey indicate that the tool has been used to help in consulting activities or developing nutrient management or conservation management plans in at least 16 different countries and 12 U.S. states. Additionally, responses showed that the tool has been used to advise 1,639 farmers in the U.S. and international, teach students (at least 1,285 undergraduate students and 364 graduate students), and impact at least 566 professors, crop consultants, or other professional peers (national and international). Studies are aimed at continuing to improve these tools and databases and transferring these technologies to other users and customers. Objective 3. All milestones are fully met. Long-term studies were monitored at ARDEC. 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. All 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. myPhyloDB — a cutting-edge tool to aid the standardization, normalization, and technology transfer of metagenomics data. The advent of next-generation sequencing has led to a dramatic increase in analysis of genetic material for microbial populations from a variety of sources (e.g., soil, human, animal). However, current analysis platforms do not allow for the convenient storage or standardization necessary for efficient technology transfer and cross-study analyses. An ARS researcher in Fort Collins, Colorado developed myPhyloDB to fill the need for a database that includes soil biology and soil biology responses to management. This new web-based tool is a significant accomplishment that provides an easy-to-use graphical interface and adds new functionality to the DNA sequence processing capabilities of Mothur – the most widely cited bioinformatics program (4000+ citations). The first version of myPhyloDB has been downloaded or distributed via CD-ROM to more than 100 different research groups, from fields ranging from soil microbial ecology to human health and nutrition to help them resolve scientific problems. The web-based site has had 1,616 visitors from at least 73 countries.
2. The greenhouse gas reduction through agricultural carbon enhancement network (GRACEnet) project. There is a need to improve the functionality of GRACEnet by addressing widescale agricultural management impacts on soil carbon and greenhouse gas (GHG) emissions. An ARS researcher in Fort Collins, Colorado is the chair of the GRACEnet steering committee, which has contributed to historical GRACEnet product developments such as the establishment of field/laboratory measurement protocols, a standardized Excel data entry template, software to perform quality control of data entry, and a web-accessible GRACEnet database. The public portal of the data management system was improved during FY 2017 and integrated with the Natural Resource and Genomics Data Systems server. This portal now contains data from 17 ARS locations with more than 450,000 total records including 116,000 soil GHG (greenhouse gas) emission measurements and 83,000 soil measurements. Data generated by the GRACEnet project increased the accuracy of GHG emission estimates reported in the U.S. national GHG inventories, including the latest EPA (Environmental Protection Agency) inventory published during FY 2017. Additionally, project data have been used to develop scaling factors to quantify the GHG reductions for improved management practices imbedded in decision support tools. GRACEnet data are now being used to validate the underlying models used by the Natural Resources Conservation Service (NRCS) Carbon Management Evaluation Tool [COMET]- Farm decision support tool.
3. The nitrogen index. One problem of agricultural systems that receive nitrogen inputs is the need for quick tools that can assess how management practices and management 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 at http://www.ars.usda.gov/npa/spnr/nitrogentools. 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 and 2017 indicate that the tool is being used to develop nutrient management and conservation management plans for farmers from the USA and other countries. Historically, the Nitrogen Index has been downloaded or distributed over 2,190 times in 65 countries and used for at least 1,800 farmers covering over 150,000 acres. Additionally, professors use the Nitrogen Index as a teaching tool for 1,285 undergraduate students and 364 graduate students, and impacted at least 566 professors, crop consultants, or other professional peers (national and international). The tool was downloaded about 125 times during FY 2017 and used by at least 324 farmers on 39,000 acres and by 229 undergraduate students, 78 graduate students, and 177 peers.
4. Bioenergy analyses for Uruguay. Uruguay is researching the use of sweet and grain sorghum feedstocks as a source of renewable energy production to supply transportation fuels. An ARS scientist in Fort Collins, Colorado was a member of the team that conducted a life cycle assessment (LCA) to quantify the carbon intensity, and conduct engineering cost analysis to estimate the unit production cost of ethanol from grain and sweet sorghum. A significant impact of this research was the finding that using simple Tier 1 methodology to estimate soil greenhouse gas emissions would not properly represent legacy effects on emissions whereas using the DayCent model provided more realistic estimates of emissions, and showed that grain and sweet sorghum both have high potential to reduce the carbon footprint compared to gasoline, and that there are some cost savings for grain sorghum but not for sweet sorghum.
5. DayCent model testing and application. A unique accomplishment of this study was to use the model to simulate changes in soil carbon under different management practices using field data from long term (more than 80 years) conventional till wheat/fallow plots in Oregon. The model was capable of representing the observed large losses of soil carbon for plots that received no fertilizer or where residue was burned, moderate carbon losses in plots that were amended with synthetic fertilizer or pea vine residue, and carbon gains for plots fertilized with cattle manure. The model also correctly represented the observed higher yields of plots that received fertilizer compared to plots that were not fertilized. The model then was used to predict future changes in soil carbon up to the year 2080. Model results suggest the plots that were losing carbon would continue to do so under conventional tillage, but the rate of loss should decrease as soil carbon levels approach a new equilibrium. For the manure plots that were gaining carbon, the model predicts that additional carbon gains would be minimal and a new equilibrium would be reached in about the year 2020. In contrast, if the plots were converted to no till, the model predicts small to moderate C gains, depending on residue management, for plots that were amended with fertilizer, pea vine, or manure, and minimal gains for the zero-fertilizer treatment. The model will be a valuable tool to recommend management practices that increase carbon sequestration in this region of the USA.
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