Objective 1: Develop novel, and improve existing, pasture and crop management strategies to improve agricultural productivity and environmental sustainability in integrated crop-pasture-livestock systems. Sub-objectives include: Sub-objective 1.A. Develop cover crop management strategies to enhance plant and animal productivity and soil health. Sub-objective 1.B. Evaluate plant and animal performance using alternative forages to extend the grazing season to compensate for periods of low perennial cool-season pasture production. Sub-objective 1.C. Evaluate soil health benefits achieved when a confinement dairy is converted to grazing-based forage production. Objective 2: Incorporate novel and existing management strategies into farm- and landscape-scale agricultural planning tools to foster sustainable intensification. Sub-objectives include: Sub-objective 2.A. Quantify the effects of managed riparian grazing on water quality, invasive species, grazing behavior, and plant and animal productivity. Sub-objective 2.B. Develop precision management strategies for perennial forage and biomass crops to increase production and profitability and minimize environmental impacts. Sub-objective 2.C. Synthesize the results of farming system and statistical modeling to develop adaptive decision support tools and to quantify the regional consequences of incorporating the novel practices evaluated in other sub-objectives into integrated crop-pasture-livestock systems.
Agriculture in the Northeastern U.S. contributes greatly to the regional economy, but is constrained by complex topography, soils, hydrology, and land use patterns, and now faces challenges due to climate change. Strategies for sustainable intensification of characteristic small farms must incorporate crop, pasture, livestock, and biomass production to efficiently use the diverse resources available. Such integration has the potential to not only increase production, but also to improve nutrient cycling, carbon storage, and soil health. This integration and optimization require improved production systems, precision management, and new tools for assessment and decision-making. At the field scale, integrative strategies will result in more efficient utilization of cropland in space and time through cover crops and interseeding. These practices can improve soil health and water quality, while also providing additional forage and increasing crop yields. Conversion from annual to perennial crops benefits soil health and mitigates climate change. At the farm scale, managed grazing of riparian areas increases forage availability and reduces invasive plants without impacting water quality. Precision agriculture techniques adapted to this region improve targeting of management practices and reduce unnecessary inputs. Simulation modeling synthesizes new knowledge of farm and regional effects of these practices on production and ecosystem services and extrapolates these effects to future climates to better plan adaptation efforts. Results at all scales will be integrated into an adaptive decision support system. Explicit guidance on management strategies for sustainable intensification of diverse farms in the northeastern U.S. will benefit farmers through increased production efficiency, will contribute to the prosperity of rural communities, and will improve environmental quality across the entire region. We will collaborate with larger USDA-led research networks, including the Long-Term Agroecological Research network (LTAR), Conservation sEffects Assessment Project (CEAP), and Dairy Agroecosystems Working Group (DAWG). Such networking provides expertise and data on outcomes from management strategies for integrated crop-pasture-livestock systems that will be used to complete the objectives of this project. With an emphasis on sustainable intensification in accord with climate predictions, our research must be approached not just on individual farms, but at landscape and regional scales. Because of the impossibility of performing experiments on multiple farms across the entire northeastern US, modeling is required to extrapolate on-farm research to a wider area, and to facilitate the development of broadly applicable decision support tools and management recommendations. To meet this objective, we will combine both on-farm studies and modeling. Outcomes of this research will support farmers directly through management strategies and decision support tools, and will provide scientifically-valid data to federal and state programs aimed at improving nutrient management, conservation, and resource use efficiency.
Under Sub-objective 1.A, we made substantial progress, primarily in establishing plots for data collection during the 2020 growing season. Cover crop plant species mixtures were established, and species biomass composition/CN, hyperspectral, and LiDAR data collected (1.A.1). Interseeded corn project was grazed with beef cattle in Nov 2019; forage yield and quality, and soil data was collected. Grazing was not conducted in spring 2020 due to COVID-19 restrictions. Soil samples were taken on all plots in Mar 2020. Corn was planted in April 2020, and annual ryegrass was planted in June 2020 in preparation for fall 2020 grazing. (1.A.2). Under Sub-objective 1.B., orchardgrass plots were established in Aug 2019. Warm-season grasses (teff, pearl millet, sorghum-sudangrass) were interseeded into the orchardgrass pastures in June 2020. These species will be monitored for biomass productivity, and stand persistence during the remainder of 2020 growing season. (1.B.1). There were no 12 month milestones for 1.B.2. There were no 12-month milestones for Sub-objective 1.C Milestones under Sub-objective 2.A. were delayed due to COVID-19 restrictions on research and travel. Final site selection and establishment of forages and monitoring equipment for the riparian management project were not completed. Planning continues with a goal to start data collection in FY21. Under Sub-objective 2.B., Miscanthus and switchgrass fields established in the Mattern watershed were maintained, and soil moisture network, biomass yield, hyperspectral, and Light Detection and Ranging ( LiDAR) data were collected. Miscanthus field biomass yield, spatial fuel use, hyperspectral, and LiDAR data were collected on commercial fields (2.B.1). Under Sub-objective 2.C., considerable work was done to improve modeling of pasture and forage systems in the northeastern United States. After several years of work with NRCS grazing experts and ARS scientists in multiple locations under the auspices of Conservation Effects Assessment Project (CEAP) Grazing Lands, it was concluded that Agricultural Policy/Environmental eXtender Model (APEX) was unsuitable for modeling grazed perennial pastures in temperate humid climates (2.C.1). Although some APEX work is ongoing, the research focus has shifted to models of forage growth and production developed in European grazing systems similar to those found in the northeastern US. The (Light Interception and Untilization Simulator-GRAss (LINGRA) and BASic GRAssland Model (BASGRA) models were parameterized using trait data obtained from global trait databases, detailed literature review, and through previously-conducted greenhouse and growth chamber studies. Seven species, orchardgrass, perennial ryegrass, timothy, Kentucky bluegrass, white clover, red clover, and chicory were parameterized. Models were tested against previous and current small plot and field trial results (2.C.2).
1. Garden plants make livestock grazing possible into the early winter. Grazing options for eastern livestock farms disappear during the fall and cold winter months, forcing farmers to feed high-cost harvested forages. Garden plants such as turnips and cabbage can grow into the early winter. USDA researchers at University Park, Pennsylvania, developed grazing systems with vegetables that provide nutritious, low-cost feed well past the traditional grazing season. Farmers and farm advisors are garden plants in dairy and livestock grazing programs to improve animal productivity, decrease feed costs, and improve farm profitability.
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