Location: Pasture Systems & Watershed Management Research
2024 Annual Report
Objectives
Objective 1: Evaluate historical crop-livestock systems management practices and explore innovative best management strategies for adapting to changing climate and improving environmental sustainability.
Sub-objective 1.A: Determine the progress made in reducing the environmental impacts of dairy farming in the U.S. over the past 50 years (led by Rotz).
Sub-objective 1.B: Improve quantification of the global warming impacts caused by cattle systems (led by Rotz).
Sub-objective 1.C: Develop and evaluate strategies for improving the sustainability of U.S. dairy farms (led by Rotz).
Sub-objective 1.D: Evaluate the environmental and economic benefits of Kernza as a dual-purpose crop with potential application in cattle systems (led by Rotz).
Sub-objective 1.E: Characterize the adoption and effectiveness of pesticide mitigation strategies under historic and future climate impacts (led by Adler).
Objective 2: Develop and enhance computational tools to support and optimize crop-livestock systems management solutions to improve production efficiency, environmental sustainability, and economic feasibility.
Sub-objective 2.A: Develop and evaluate fusion strategies with targeted UAS imagery to improve the use of satellite imagery across space, time, and spectral range for crop nitrogen recommendations (led by Adler).
Sub-objective 2.B: Improve ecosystem service modeling and accounting capabilities to better quantify the trade-offs and synergies between agricultural production and non-market ecosystem services in diverse agricultural landscapes, resulting in more effective decision support tools (led by Goslee).
Objective 3: Holistically assess the short- and long-term impacts of contaminants such as PFAS on agroecosystems in order to innovate remediation strategies. (stretch objective, led by Veith)
Sub-objective 3.A: Assess indicators of water quality and stream health beyond achieving mandated load reduction goals for nutrients and sediment.
Sub-objective 3.B: Simulate water quality and stream health in current and future climate projections.
Approach
Managing modern, sustainable agricultural systems requires complex strategies to meet food, fuel, and fiber production goals while supporting ecosystem services and minimizing negative environmental impacts. Management strategies that meet production needs while also storing carbon, cycling nutrients, improving water quality, and providing pollinator habitats require research strategies at scales from field and farm to watershed and expanding into regional and national syntheses. Further, research approaches must address historic climatic drivers and prepare for future climatic impacts.
Integrated crop-livestock systems are a customizable alternative to highly specialized agricultural operations. These integrated systems offer holistic approaches that more closely resemble farming approaches used decades ago before modern agriculture became more specialized; approaches well-suited to the complex landscapes of the northeastern United States and provide more opportunities to realize environmental benefits. In this project, we will harness technological advances in computational speed for complex simulation programs and extensive data analysis.
In objective 1, we will apply farm-scale modeling and life cycle assessment to quantify the environmental improvements of beef and dairy farming over the past five decades and identify lower-impact management strategies. In objective 2, we will research and develop novel technologies to assess trade-offs and synergies among agricultural management strategies and related ecosystem services beyond the farm borders. In objective 3, we will collaborate across ARS locations to better understand and predict the transport of contaminants of emerging concern into, within, and from agricultural systems. We will measure per- or poly- fluorinated alkyl substances (PFAS), neonicotinoids, pharmaceuticals, and other low-level contaminants in the stream via grab sampling and in-stream passive membrane absorption. We will use low-level detection advances in analytical laboratory equipment and create contaminant transport models. Objective 3 is a bit of a stretch objective as robust collection and detection methods for these compounds of emerging concern are currently in development and interactions are not well understood.
We will collaborate with larger USDA-led research networks, including the Long-Term Agroecological Research network (LTAR), Conservation Effects Assessment Project (CEAP), and Dairy Agroecosystems Working Group (DAWG). Such networking provides expertise and data on outcomes from management strategies for cropping and crop-livestock systems that will be used to confirm results and provide a basis for extrapolation of future systems in all objectives.
Improved strategies to increase sustainable multifunctionality will benefit farmers by reducing input costs and improving soil and water quality within their farms and watersheds. It will also improve the environmental health for everyone. Regionally and nationally, data, tools, and assessments provided to NRCS, industry, and non-governmental agencies will contribute to evaluations of current progress and guide future planning.
Progress Report
Under Sub-objective 1A, dairy farms were modeled throughout the United States in 1971 and 2020 to determine the progress made in reducing environmental impacts. Nutrient losses and farmgate life cycle assessments of greenhouse gas (GHG) emissions, fossil energy use, and blue (ground and surface) water use were determined for six regions and the full U.S. For all environmental metrics studied, intensities expressed per unit of fat and protein corrected milk produced were reduced over the 50 year period, but the total impacts over all farms or milk produced increased for 5 of the 13 environmental metrics. Reductions in the impacts of dairy farms in the eastern U.S. were offset by large increases in western regions because of a major increase in cow numbers in the west. Although much progress has been made in improving production efficiency, continued improvement with new strategies and technologies are needed to meet the demand for dairy products while mitigating total environmental impacts, particularly in view of projected climate variability.
Under Sub-objective 1A, a major effort was given to interfacing the inventory data created with the use of the Integrated Farm System Model (IFSM) to OpenLCA for a more comprehensive life cycle assessment of U.S. dairy production in 2020. Existing dairy lifecycle inventory model structure and input data from the SimaPro life cycle assessment software was transferred to OpenLCA. After transfer and verification, modifications to the model were made to correct instances of double counting. We also updated the background database sources within the OpenLCA model to increase regional precision and to capture improvements in upstream processes (e.g., fuel efficiency and electricity fuel mix). Efforts are currently underway to update the data values in the model with the latest data from IFSM simulations of U.S. dairy farms.
Under Sub-objective 1B, different metrics for combining the warming effects of greenhouse gases (GHG) were compared for assessing global warming impact of U.S. dairy farms. Use of global warming potential (GWP) with time horizons of 20, 100 and 500 years gave carbon footprints for U.S. milk of 2.18, 0.97 and 0.48 kg CO2e/kg of fat and protein corrected milk. Compared to the use of GWP with a 100-year time horizon (GWP-100), the use of global temperature potential (GTP), combined global temperature potential (CGTP) and models for GWP* reduced the warming effect of methane relative to other GHG, which reduced the carbon footprint of U.S. milk production by 38 to 55%. Use of GWP-100 metrics indicated that warming from GHG emissions of U.S. dairy farms increased 10-15% between 1971 and 2020, while the use of GTP metrics indicated little or no effect on global temperature change over the 50-year period. While all approaches for representing the warming impact of dairy farms have benefits and challenges, approaches such as CGTP and GWP* that account for the rate of methane emission relative to the oxidation rate in the atmosphere provide a more realistic assessment of the long-term impact of dairy farms on global climate.
Under Sub-objective 1C, representative dairy farms were modeled in five regions of the U.S. with the help of selected experts in each region. A wide range of potential mitigation strategies were modeled on each farm to determine their potential for reducing the carbon footprint of the milk produced. Strategies were then combined to determine the potential reduction toward net-zero GHG emission. Strategies included the use of an enteric methane inhibitor, precision feeding of protein, increased feed efficiency, increased milk production, reduced cow replacement rate, reduced animal mortality, photovoltaics to produce electricity, nitrification inhibitor, vermifiltration, subsurface fertigation, no-till crop establishment, and reduced emission in the production of purchased feeds. Individual strategies reduced the carbon footprint by 0 to 20%. When combined, the carbon footprint for individual farms was reduced by 40-60%. This analysis illustrates that major reductions in the carbon footprint of milk production in the U.S. can be achieved but net-zero production remains a major challenge.
Work on Sub-objectives 1D and 1E are scheduled for years 3-5 of the project.
Under Sub-objective 2.A, field sites were identified, nitrogen rate experiments were established, and baseline soil data was collected.
Under Sub-objective 2.B, a complete workflow linking the python InVEST ecosystem services modeling tools with multi-criterion optimization algorithms in R has been developed and tested and presented to SCINet researchers. Two manuscripts on the workflow and testing are in progress (2.B.1). The Long-Term Agroecosystem Research (LTAR) Regionalization Project has completed the first sets of network-wide regionalizations for environment, cropping patterns, livestock systems, and human dimensions, and a special issue for the journal Landscape Ecology is in progress (2.B.2).
Under Objective 3, collaborations with other ARS and university researchers have been created and strengthened by participation national symposiums and workshops. Field sites for data collection have been identified and initial data in soil, water, and plant biomass are being collected. Watershed-level modeling of baseline conditions and concentrated flow pathways has begun.
Accomplishments
1. Fifty years of environmental progress for United States dairy farms. USDA-ARS scientists in University Park, Pennsylvania, simulated dairy farms across the United States to determine how technological and management changes over the past 50 years have impacted environmental and economic performance. Efficiency in milk production has increased greatly with about 20% fewer cows producing about twice the milk today. Across all environmental metrics assessed, intensities expressed per unit of milk produced decreased substantially over this period but totals over all milk produced showed increases in emissions of ammonia, methane, and other volatile organic compounds. Life cycle greenhouse gas emissions increased 13% with little change in fossil energy use. Emissions of ammonia, methane, and volatile organic compounds have increased while nutrient losses to ground and surface waters have decreased. Expansion in the dry climate of the west contributed to a 40% increase in water use, perhaps the greatest threat to future sustainability of dairy farms. Although much progress has been made in improving production efficiency and reducing or controlling environmental impacts, further mitigation is needed to continue improving the sustainability of the dairy industry.
Review Publications
Chen, D., Carley, D.S., Munoz-Carpena, R., Ferruzzi, G., Yuan, Y., Henry, E., Blankinship, A., Veith, T.L., Breckels, R., Fox, G., Luo, Y., Osmond, D., Preisendanz, H.E., Tang, Z., Armbrust, K., Costello, K., McConnell, L.L., Rice, P., Westgate, J., Whiteside, M. 2024. Incorporating the benefits of vegetative filter strips into risk assessment and risk management of pesticides. Integrated Environmental Assessment and Management. 20(2):454-464. https://doi.org/10.1002/ieam.4824.
Gardezi, M., Abuayyash, H., Adler, P.R., Alvez, J.P., Anjum, R., Raju Badireddy, A., Brugler, S., Carcamo, P., Clay, D., Dadkhah, A., Emery, M., Faulkner, J.W., Joshi, B., Joshi, D.R., Hameed Khan, A., Koliba, C., Kumari, S., Mcmaine, J., Merrill, S., Mitra, S., Musayev, S., Oikonomou, P.D., Pinder, G., Prutzer, E., Rathore, J., Ricketts, T., Rizzo, D.M., Ryan, B.E., Sahraei, M., Schroth, A.W., Turnbull, S., Zia, A. 2024. The role of living labs in cultivating inclusive and responsible innovation in precision agriculture. Agricultural Systems. 216:103908. https://doi.org/10.1016/j.agsy.2024.103908.
Kammerer, M., Iverson, A.L., Li, K., Goslee, S.C. 2024. Not just crop or forest: an integrated land cover map for agricultural and natural areas. Earth System Science Data. 11(1):137. https://doi.org/10.1038/s41597-024-02979-w.
Rohith, A. N., Karki, R., Veith, T.L., Preisendanz, H., Duncan, J.M., Kleinman, P.J., Cibin, R. 2024. Prioritizing conservation practice locations for effective water quality improvement using the Agricultural Conservation Planning Framework (ACPF) and the Soil and Water Assessment Tool (SWAT). Journal of Environmental Management. 349:119514. https://doi.org/10.1016/j.jenvman.2023.119514.
Rotz, C.A., Beegle, D., Bernard, J.K., Leytem, A.B., Feyereisen, G.W., Hagevoort, R., Harrison, J., Aksland, G., Thoma, G. 2024. Fifty years of environmental progress for United States dairy farms. Journal of Dairy Science. 107(6):3651-3668. https://doi.org/10.3168/jds.2023-24185.
Soder, K.J., Dell, C.J., Adler, P.R., Laboski, C.A., Williamson, B. 2024. The LTAR Common Experiment at Upper Chesapeake Bay: Integrated. Journal of Environmental Quality. 53(6):832-838. https://doi.org/10.1002/jeq2.20591.
Gray, D., Goslee, S.C., Kammerer, M., Grozinger, C.M. 2024. Effective pest management approaches can mitigate honey bee (Apis mellifera) colony winter loss across a range of weather conditions in small-scale, stationary apiaries. Journal of Insect Science. 24(3):15. https://doi.org/10.1093/jisesa/ieae043.
McNeil, D.J., Goslee, S.C., Kammerer, M., Lower, S.E., Tooker, J.F., Grozinger, C.M. 2024. Illuminating patterns of firefly abundance using citizen science data and machine learning models. Science of the Total Environment. 929:172329. https://doi.org/10.1016/j.scitotenv.2024.172329.