Location: Pasture Systems & Watershed Management Research
2023 Annual Report
Objectives
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.
Approach
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 Effects 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.
Progress Report
Plant species mixtures were established, and species biomass yield and quality measurements and multi- and hyperspectral imagery collected (1.A.1). We developed a hyperspectral pixel unmixing method that uses a Latent Variational Autoencoder within an analysis-synthesis loop to (1) construct pure spectra of the materials present in an image and (2) infer the mixing ratios of these materials in hyperspectral pixels without the need of labelled data. We also continued work on developing artificial intelligence models to characterize plant species in mixtures and to extend the spatial and temporal coverage and to extend spectral range of Unmanned Aircraft System (UAS) imagery, providing a complementary role for both UAS and satellite imagery in precision management strategies for perennial forage and biomass crops. Interseeded corn project was planted in soybeans in May 2022 to rotate crops and control weeds. Cereal rye was planted after forage soybean harvest in September. Cattle were not grazed in Fall 2022 due to this planting schedule but were grazed in Spring 2023. Forage yield and quality and soil data were collected on all crops. (1.A.2).
Under Sub-Objective 1.B, year 2 of warm-season grasses (teff, pearl millet, sorghum-sudangrass) were planted as monocultures or interseeded into previously established orchardgrass pastures in June 2022. These species will be monitored for biomass productivity and persistence during the remainder of the 2023 growing season (1.B.1). Sub-objective 1.B.2 has been indefinitely delayed. Due to restrictions during the COVID pandemic and FY22 Maximized Telework, the University of New Hampshire (UNH) was not able to conduct the research, and ARS personnel were not able to travel to UNH to assist with data collection. Other research projects (including grant-funded projects) have taken priority at UNH, therefore land and animals are not available at this time.
Under Sub-objective 1.C, pandemic travel restrictions and FY22 Maximized Telework prevented travel to the University of New Hampshire (UNH). Additionally, complications with the 2010 baseline dataset have been discovered and on-site meetings with UNH researchers are needed to develop a new plan for sampling to evaluate soil health.
Under Sub-Objective 2.A, the riparian grazing sub-objective is on indefinite delay. FY22 Maximized Telework prevented ARS researchers from traveling to potential farms to identify a suitable site for this research. In addition, the lead investigator on this project took another position (at another location) within ARS and is no longer able to lead this project. Commitments by other researchers and current vacancies prevent anyone else from taking the lead on this project (2.A.1).
Under Sub-objective 2.B, Machine learning models were developed from high resolution biomass yield data over three years and Sentinel-2 imagery to describe the spatial variation of Miscanthus yield across space and time on a commercial farm with several thousand acres of Miscanthus planted on marginal lands. We found that including a time series of Sentinel-2 images improved model performance (2.B.1).
Under Sub-objective 2.C, preliminary evaluation and a change in project and NRCS priorities led to a reassessment of model implementations, and a shift away from the Agricultural Policy/Environmental eXtender (APEX) model for use in developing pasture tools described in 2.C.1. Instead, a suite of pasture-specific models developed for similar climates and management regimes was identified and parameterized for use with the chosen crops. These models were linked with climate change projections, and with species distribution models developed under previous milestones, to produce maps of potential future agricultural scenarios for the northeastern United States, and consequences for ecosystem services including production, soil erosion, and pollination services (2.C.2). Economic consequences beyond forage biomass are not as comprehensively modeled by this suite of tools, so that aspect is undergoing additional research. Research scientists are working with university partners to incorporate findings into existing online decision support tools, and with NRCS to develop a novel online tool for assessing pasture conservation needs based on environmental factors and management.
Accomplishments
1. Can chicory delay maturation of orchardgrass?. Harvesting forages at proper maturity is critical to maintaining high levels of nutrition for cattle but can be a challenge during wet spring weather. ARS researchers at University Park, Pennsylvania, evaluated whether planting chicory, a tall-growing, high-quality forage, with orchardgrass would delay orchardgrass maturity and improve forage quality during the spring. Results showed that while chicory did delay orchardgrass maturity and increased the yield and nutritive quality of the pasture, most chicory died out over the first winter.
2. Feeding flaxseed to dairy cows. Feeding flaxseed to dairy cows improves fatty acids in milk that may have human health benefits, decrease methane produced in the rumen, but may have negative impacts on nutrient digestibility due to changes in the rumen microbes. ARS researchers at University Park, Pennsylvania, and the University of New Hampshire fed four levels of flaxseed (0, 5, 10, and 15% of diet dry matter) to dairy cows consuming a forage and grain diet. Results showed that feeding increasing amounts of flaxseed decreased the abundance of ruminal bacteria populations that digest fiber which may be associated with the observed tendency for decreased methane production. However, the tradeoff may be that fiber digestion may be decreased, resulting in reduced milk production.
3. Red seaweed fed to dairy cows. Feeding red seaweed reduces methane produced by cattle, but the effects on nutrient digestibility are unknown. ARS scientists at University Park, Pennsylvania, and the University of New Hampshire supplemented a pasture-based diet with three levels of red seaweed to evaluate effects on ruminal fermentation and methane production. Results showed that methane production was almost completely suppressed at all levels of seaweed supplementation compared to the pasture-only diet (no seaweed), but animal production may be reduced due to impaired nutrient digestibility. Further research is needed to identify an optimal dose of seaweed to maintain animal production and to address issues such as cost and scale of production.
4. Identifying bioactive compounds in brassicas. Brassica forages contain compounds called glucosinolates that can impact animal production and health when grazed, but current laboratory procedures to identify specific glucosinolates are lacking. ARS researchers at University Park, Pennsylvania, developed and validated a simple and accurate laboratory method to identify specific glucosinolates in brassicas. This work resulted in a rapid and accurate identification and quantification of glucosinolates that will allow for improved selection of brassicas to reduce enteric methane emissions, minimize animal health and productivity issues while providing a highly nutritious forage source, and biofumigation to control soil-borne pests. Future research is needed to further characterize the biological activity of individual glucosinolates to develop and apply specific brassica species for various agricultural applications.
5. Life cycle inventory of Miscanthus production on a commercial farm. Miscanthus has attracted interest for its potential in reducing greenhouse gas [GHG] emissions in bioenergy production, however, there is limited data on its large-scale commercial production and consequently the true impact on GHG emissions. ARS researchers at University Park, Pennsylvania, conducted an inventory of energy use on a large commercial Miscanthus farm and found that harvest consumed the most energy and satellites could be used to understand factors contributing to yield variation across fields. Through modeling we found that yields need to be above a certain level for positive carbon storage in the soil. Research on commercial farms provides valuable insights for the bioenergy industry to promote practices which reduce the environmental impact of farming practices.
Review Publications
Andreen, D.M., Billman, E.D., Brito, A.F., Soder, K.J. 2023. Effect of incremental amounts of Asparagopsis taxiformis on ruminal fermentation and methane production in continuous culture with orchardgrass herbage. Animal Feed Science and Technology. 299:115641. https://doi.org/10.1016/j.anifeedsci.2023.115641.
McDowell, R., Rotz, C.A., Oenema, J., Maclntosh, K. 2022. Limiting grazing periods combined with proper housing can reduce nutrient losses from dairy systems. Nature Food. 3:1065-1074. https://doi.org/10.1038/s43016-022-00644-2.
Casler, M.D., Mitchell, R., Adler, P.R. 2022. Biomass quality responses to selection for increased biomass yield in perennial energy grasses. BioEnergy Research. 15:3. https://doi.org/10.1007/s12155-022-10513-2.
Mercier, K.M., Billman, E.D., Soder, K.J., Jaramillo, D.M., Goslee, S.C., Adler, P.R. 2023. Managing interspecies competition to improve spring pasture maturity, nutritive value, and biomass. Crop Science. 63(2):974–986. https://doi.org/10.1002/csc2.20892.
Soder, K.J., Brito, A.F. 2023. Enteric methane emissions in grazing dairy systems. Journal of Dairy Science. 4(4):324-328. https://doi.org/10.3168/jdsc.2022-0297.
Kleves, A., Resende, T., Silva, L., Dorich, C., Pereira, A., Soder, K.J., Brito, A. 2023. Feeding incremental amounts of ground flaxseed: Effects on diversity and relative abundance of ruminal microbiota and enteric methane emissions in dairy cows. Journal of Dairy Science Communications. 7(1):1-8. https://doi.org/10.1093/tas/txad050.
Adler, P.R. 2023. Life cycle inventory of Miscanthus production on a commercial farm in the US. Front. Plant Science. 14:1029141. https://doi.org/10.3389/fpls.2023.1029141.
