Location: Northwest Sustainable Agroecosystems Research
2023 Annual Report
Objectives
The purpose of the project is to provide information relevant to growers, agribusiness, and the USDA Climate Hub and Long-Term Agroecosystem Research (LTAR) networks, that includes the development and evaluation of: (1) cropping system diversification and intensification options; (2) practices that enhance soil health and nutrient use efficiencies, and mitigate greenhouse gas emissions; and (3) remote and proximal sensing technologies that diagnose economic and environmental.
This research will be conducted via the following objectives and sub-objectives:
Objective 1: Assess management impacts on soil degradation and link measures of soil health to agroecosystem performance in order to provide science-based decision support.
Sub-objective 1A: Evaluate linkages between agroecosystem efficiencies and greenhouse gas production.
Sub-objective 1B: Evaluate the net climate footprint of Palouse grain-fallow and annual cropping systems through life cycle assessment by further developing the CropSyst-LCA greenhouse gas accounting tool.
Sub-objective 1C: Identify field-scale drivers of soil acidification in a LTAR aspirational cropping system.
Sub-objective 1D: Develop and evaluate management practices to mitigate soil acidification in the Palouse region.
Objective 2: Link remote and proximal sensing technologies and precision agroecology concepts to quantify and diagnose ecosystem service outcomes and to inform decisions regarding agricultural practices and systems.
Sub-objective 2A: Use spatiotemporal (ST) modeling with remote and proximal sensing data to assess agroecosystem performance.
Sub-objective 2B: Assess abiotic crop stressors using above-ground visual and thermal imagery.
Objective 3: Develop cropping systems that advance intensification and diversification and further enable mitigation and adaptation to emerging weather extremes and climate change.
Sub-objective 3A: Leverage partnerships with growers and researchers throughout CAF-LTAR to study co-innovation strategies and on-farm research methodology.
Sub-objective 3B: Compare the yield and rhizosphere microbiomes of grain legumes and canola grown in intercropped stands and determine any impact on the following wheat crop.
Sub-objective 3C: Conduct a long-term trial of the perennial grain crop Kernza (Thinopyrum intermedium) in the annual, transitional, and fallow agroecological classes of the iPNW focusing on changes in seed yield performance and impact on soil water content.
Approach
Hypothesis 1A: Farming practices for site-specific locations can be designed to lower gaseous nitrogen (N) emissions while meeting N performance goals. The LTAR site (37 ha) at the CAF will be used where four N performance classes have been developed and related to nitrous oxide (N2O) and carbon dioxide (CO2) emissions.
Hypothesis 1B: Annual cropping systems have higher overall greenhouse gas emissions than grain-fallow systems. The Organic Farming Footprint model will be expanded to include more farming operations and emissions factors.
Goal 1C: Legacy soil pH data from 184 locations at the CAF will be used to assess the Very Simple Dynamic model (VSD+). Model outputs will be compared to assess N transformations, base-cation leaching, and nutrient cycling as drivers of acidification. VSD+ may be coupled with HYDRUS-1D or CropSyst-MicroBasin.
Goal 1D: Treatments with and without lime will be tested at four landscape positions at the CAF and assessed with mixed-effects ANOVA.
Goal 2A-i: The models will use Bayesian spatiotemporal modeling framework using existing modeling tools to provide estimates of predictive distributions of key variables.
Goal 2A-ii: The models developed in 2A-ii will be used to evaluate new prescription maps based on predicted N performance within a desired risk tolerance.
Goal 2A-iii: CAF datasets for soil pH, and BH method described in 2A-i, a multivariate linear model for pH will be fit on predictor variables using topographic, crop type, and remote sensing indices to find optimal soil sampling schemes.
Goal 2B-i: This work will focus on CAF Eddy Covariance (EC) tower fetches. The system will consist of low-cost thermal/RGB cameras taking hourly imagery. Predictions will be compared to EC measured ET at CAF and lysimeter data from Bushland, Texas.
Goal 2B-ii: Monthly sampling will include an LAI reading from each replicate from Sub-objective 1D. These will be coordinated with RGB imaging over the same area and resulting images will be orthomosaiced using OpenDroneMap to train a machine learning algorithm (ANN or RF) to predict LAI.
Goal 2B-iii: Measurements will be linked to the LAI sequence over the season, derived from imagery in 2B-ii of the liming test plots from 1D. A multivariate model will be developed for soil pH, fit and tested on data from Subobjective 1D.
Goal 3A-I, 3A-ii: The farmer network will be engaged using an established co-innovation storyboard agenda to quantify stakeholder reactions to ongoing research and document a consensus to direct future experimental trials. Spatio-temporal maps will be used to design and determine optimal areas to deploy large field plot studies.
Hypothesis 3B, 3Bii: Two experimental locations will be set at the PCFS. Soil water, bulk density, C, N, rhizosphere and rhizoplane sampling will assess intercrop performance and the efficiency of the through calculation of LER.
Hypothesis 3Ci, 3Cii, 3Ciii: Three experimental locations will be established at PCFS, WSU Wilke Farm, and the Horse Heaven Hills to assess Kernza establishment, yield and related resource use. A modified staggered-start design will be used to investigate the potential to grow Kernza.
Progress Report
This report documents the first year of progress for project 2090-11000-010-000D, titled, “Advancing Soil Health and Agricultural Performance to Promote Sustainable Intensification and Resilience of Northwest Dryland Cropping Systems”.
In support of Objective 1, a peer-reviewed paper was published on linking soil health to ecological resilience theory to aid assessment of management impacts on soil health (see accomplishment 1). In addition, ARS researchers in Pullman, Washington, initated field studies at the Cook Agronomy Farm and other locations to assess mitigation of soil acidification and to assess greenhouse gas emissions from various agricultural management practices. Long-term data at the Cook Agronomy Farm were used to assess filed-scale outcomes of the nitrogen balance index, a field measure of how efficient nitrogen fertilizers are used. This assessment will serve to identify field locations where greenhouse gas emissions will be monitored in the future.
Also, in support of Objective 1, long-term data on soil acidification at the Cook Agronomy Farm were modeled using soil, crop, management, and terrain variables and applied to a cooperative farmer’s field to target field sampling to assess soil acidity.
In support of Objective 2, spatio-temporal modeling was used to assess and publish long-term yield patterns at the Cook Agronomy Farm. In addition, remote and proximal sensing methods and equipment were field tested in relation to crop senescence, weed pressure and other field outcomes.
In support of Objective 3, over ten dryland agricultural farmers were identified and supported by ARS researchers to establish trials of alternative crops including sorghum, millet and Kernza, a variety of perennial wheat. In addition, intercropping trials were established involving canola with peas and canola with garbanzo beans and monitored for yield, effects on the soil microbiome, water use and other performance outcomes.
Accomplishments
1. New method provides yardstick to assess key soil health properties over time. Healthy soil is critical for global food security but is threatened by processes of soil degradation, with at least 33% of global croplands estimated to be moderately or highly degraded. Current soil health assessments provide insight into soil capabilities but often lack diagnostic criteria that assess management effects on soil capabilities over time. ARS researchers in Pullman, Washington, proposed integrating soil health assessments with ecological resilience theory to provide a conceptual framework for understanding management impacts on soil capabilities and sustainable agricultural intensification. ARS researchers explored this conceptual framework using the Palouse River Watershed of the Pacific Northwest as a working example, with its soil degradation problems of erosion, organic matter loss, and acidification being relevant worldwide. The researchers also demonstrated how increasing management options, or adaptive capacity, can help reverse soil degradation and minimize effects of climate change. These results will be useful for farmers, the USDA, Natural Resource Conservation Service (NRCS), and scientists interested in assessing soil health.
Review Publications
Casanova, J.J., Carlson, J.L., LeTourneau, M. 2023. Remote-sensing-based sampling design and prescription mapping for soil acidity. Remote Sensing. 15(12). Article 3105. https://doi.org/10.3390/rs15123105.
Phillips, C.L., Tekeste, M., Ebrahimi, E., Logsdon, S.D., Malone, R.W., O'Brien, P.L., Emmett, B.D., Karlen, D.L. 2023. Thirteen-year stover harvest and tillage effects on soil compaction in Iowa. Agrosystems, Geosciences & Environment. 6(2). Article e20361. https://doi.org/10.1002/agg2.20361.
Gent, D.H., Block, M., Massie, S.T., Phillips, C.L., Richardson, B.J., Shellhammer, T.H., Trippe, K.M., Wiseman, M.S. 2023. Nitrogen and sulfur fertility practices: Influences on hop chemistry, aroma, and nitrate accumulation. Journal of the American Society of Brewing Chemists. https://doi.org/10.1080/03610470.2023.2204412.
Phillips, C.L., Wang, R., Mattox, C., Trammell, T.L., Young, J., Kowalewski, A.R. 2022. High soil carbon sequestration rates persist several decades in turfgrass systems: A meta-analysis. Science of the Total Environment. 858(3). Article 159974. https://doi.org/10.1016/j.scitotenv.2022.159974.
Wang, R., Mattox, C.M., Phillips, C.L., Kowalewski, A.R. 2022. Carbon sequestration in turfgrass-soil systems. Plants. 11(19). Article 2478. https://doi.org/10.3390/plants11192478.
Wulfhorst, J., Bruno, J., Toledo, D.N., Wilmer, H.N., Archer, D.W., Peck, D.E., Huggins, D.R. 2022. Infusing ‘long-term’ into social science rangelands research. Rangelands. 44(5):299–305. https://doi.org/10.1016/j.rala.2022.06.001.
