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Greenhouse Gas Emissions in the Transition from Traditional to Organic Dairy Farming: An Education and Research Collaboration


The goal of our proposed research is to develop a decision support tool for quantitatively evaluating the best management practices (BMPs) to enhance the ecosystem services produced by livestock systems at the site and regional scale for the Northeast U.S.<P> Our specific objectives are: <OL> <LI> Test and improve Manure-DNDC using farm-level observational data. A suite of research farms at UNH will be used as primary sites for testing the applicability of Manure-DNDC for the Northeastern livestock farms. Some additional sampling and chemical analysis will be conducted to quantify the primary of C and N biogeochemical stocks and flows across farm facility components. Data will be utilized for modifying, calibrating, and validating Manure-DNDC. <LI>. Quantify the impacts of baseline and alternative management practices on the ecosystem services of the selected farm with Manure-DNDC. A baseline scenario and a group of alternative management scenarios will be designed based on the current and prospective management practices for the UNH farms. BMP scenarios will be identified and evaluated based on their ecosystem service and economic incentives for the farm. <LI> Develop Northeastern U.S. GIS database to support Manure-DNDC applications at regional scale. To make Manure-DNDC useful for dairy farms in the Northeast, we will create a GIS database containing necessary input information of climate/weather data, soil properties, livestock and crop parameters, and default management practices required to run Manure-DNDC for the region. The data will be collected from a variety of sources and stored in a geo-referenced database in the Manure-DNDC required format. <LI>Develop a decision support tool by developing a user-friendly interface to link Manure-DNDC to regional database. The interface will allow the user to select a specific location or a region, automatically extracting the required information from the database, allow the user to modify the default data to their own site specific conditions, execute Manure-DNDC, and provide modeled results in graphical and tabular form. <LI>Evaluate the decision support tool. A two-day workshop will be held during the third year of the project to teach interested parties to use the decision support tool and to get their assessment of its usefulness and potential improvements. After reviewing the feedback from the users, the decision support tool will be modified and finalized.<LI>Integrate the research objectives with an educational initiative that partners a graduate student with science teachers and their students. A partnership between middle and high school science teachers and a Ph.D. level graduate student will be established to enable the graduate student to build communication skills around greenhouse gas inventories, organic farming and sustainable agriculture and promote authentic inquiry-based research projects with middle and high school teachers and students.

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Non-Technical Summary: Conversion from conventional to organic dairy farming in Northeast United States will result in enhanced ecosystem services and improved environmental benefits through the reduction in nitrate leaching and greenhouse gas emissions and increases in soil organic matter. Through an integrated research and education approach we plan to measure and model the greenhouse gas emission inventory of traditional and organic dairy practices at the University of New Hampshire. Field measurements of greenhouse gas emission from all components of the dairy farms will be completed. Manure-DNDC, a biogeochemical model, will be calibrated and validated for the UNH sites then applied to other organic dairy sites throughout the region. A decision support tool will be developed to in collaboration with stakeholders, Organic Valley and Stonyfield Farms, to provide farmers training in using the tool, assistance with accessing data and information regarding the ecosystems services and environmental benefits from organic farming. We will engage not only with stakeholders in the dairy industry but with the K-12 community in an effort to educate both the users and the public about greenhouse gas emission inventories, organic farming and sustainable agriculture. A graduate student will work with science teachers to develop and implement inquiry based authentic research in their classrooms. <P> Approach: The University of New Hampshire (UNH) offers two very different livestock-crop systems which cover the range of current systems in the region and provide a rigorous test for the generality of the model to be produced. The UNH Organic Dairy Research Farm (ODRF) encompasses the adjacent Burley-Demerrit and Bartlett-Dudley farms in Lee, NH, about 7 km from the UNH campus. The two holdings include 40 hectares of certified organic pastures, and 65 hectares of woodlands. The farm currently supports a herd of 43 milking cows and 18 heifers, all Jerseys ( UNH also supports an advanced, conventional dairy system. The Fairchild Dairy Teaching and Research Center (DTRC, houses about 125 milking-age Holsteins and approximately 70 growing, replacement animals. These two facilities offer a diverse set of feed/manure systems for development and testing of the Manure-DNDC model, and will be utilized in the following way. Firstly, systematic sampling and chemical analysis will be conducted across all the farm facility components to establish a relatively complete framework of the N biogeochemical cycle for the prototype ecosystems. Secondly, contributions to ecosystem services of each of the farm facility components (feed, housing, compost, lagoon, anaerobic digester or crop field) will be quantified by identifying its efficiency and leaks within the N cycling framework. Some of the ecosystem N cycling or individual components studies have been carried out within the on-going projects. The results from the on-going projects will be used to calibrate and validate Manure-DNDC for the livestock-crop ecosystem. Data gaps will be identified, and additional sampling and analysis will be conducted to complete the description of the manure life cycle for the entire livestock-crop ecosystems. To allow the farmers or resource managers to utilize Manure-DNDC without having to acquire and organize necessary input data, we will collect and organize all necessary input data for the domain region and link them to the model in advance. For our selected domain, the livestock-crop ecosystems in the Northeast US, we will develop a georeferenced database containing relevant data on climate and soil properties, as well as necessary parameterizations characterizing Northeastern U.S. livestock, crop and farm management. The decision support tool will extract relevant data for a specific user (daily weather for one or more years from station data which we will have acquired from the National Climate Data Center database, soil properties which we will have acquired from the USDA NRCS soil STATSGO2 and SSURGO databases, and default or characteristic farm management information - herd size, housing, manure management, etc., which we will have prescribed in consultation with UNH agronomists). The user can then review this information and make any adjustments needed to match their own soils and livestock operation through the model interface.

Varner, Ruth
University of New Hampshire
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