Research Project: Linkages Between Crop Production Management and Sustainability in the Central Mississippi River Basin

Location: Cropping Systems and Water Quality Research

2025 Annual Report

Objectives
Objective 1: Determine linkages between plant available water, evapotranspiration, and crop yields. 1a: Determine the relationship between crop yields and available soil water. 1b: Develop spatially explicit field-scale water budgets using remote sensing. 1c: Determine the ability of the APEX model to simulate the spatial variability of crop yields and soil moisture. Objective 2: Characterize and quantify the sub-daily variability in water quality and identify the drivers of that change. 2a: Identify and quantify stream sub-daily water quality variability. 2b: Identify the drivers for phosphorus sub-daily variability. Objective 3: Determine and characterize the effects of management on water use efficiency, nutrient use efficiency, GHG emissions, productivity, and ecology. 3a: Compare WUE and water budget components of different crops and cropping systems. 3b: Integrate corn incremental N use efficiency (NUE) into fertilizer recommendations. 3c: Determine the effects of conservation practices and crop rotations on greenhouse gas and productivity, and the potential trade-offs. 3d: Determine how conservation practices and crop rotations affect above ground biomass and ecology. Objective 4: Evaluate ASP (aspirational) and BAU (business-as-usual) production systems for water quantity, water quality, soil, biological, production and profitability outcomes. 4a: Investigate trade-offs between productivity and environmental metrics for more diverse cropping systems. 4b: Create publicly accessible data holdings for publishing CMRB production and environmental data. 4c: Extrapolate the BAU and ASP water budgets developed at field scale to larger scales.

Approach
The overall purpose of the project is to identify how conservation practices affect outcomes, what cropping systems improve short- and long-term sustainability, and the trade-offs between environmental and production outcomes; and provide that information to producers to help them move toward more sustainable agricultural systems. Objective 1 focuses on the relationship between crop yields, soil moisture content, and evapotranspiration within the context of these soils. Objective 3 compares multiple outcomes of different agricultural systems. The conclusions of these two objectives will help identify important processes that improve agricultural sustainability, provide the information necessary to develop metrics that describe this sustainability, and evaluate trade-offs between environmental and production outcomes of agricultural systems. Objective 4 connects to these two objectives by bringing the information to stakeholders. It will also scale results related to water availability and movement to a larger scale. The research in Objective 2 is needed to incorporate issues of phosphorus transport when scaling phosphorus losses from the edge-of-field to the watershed scale and evaluate environmental impacts. The project will conduct experiments at multiple scales ranging from small plots to watersheds, adding measurements and continuing those already underway. The project builds upon the research infrastructure developed in collaboration with the University of Missouri at our research farm in Centralia and elsewhere, which was enhanced for the Central Mississippi River Basin (CMRB) site of the Long-Term Agroecosystem Research Network (LTAR) starting in 2015. This infrastructure includes small plots, large plots, and fields on which the Common Experiment—a coordinated experiment across LTAR—has been implemented, and the observatory, which provides long-term data of weather and stream flow quantity and quality in multiple nested watersheds. The proposed research focuses on surface and soil water in row crop production systems in the CMRB, with simultaneous consideration of productivity, nitrogen use, greenhouse gas emissions, soil health, and biodiversity. Specifically, research will address the immediate and long-term relationships between row-crop production practices and water budgets, surface water quality, hazardous algae blooms, GHG emissions, ecology, and aboveground and soil biodiversity. The project will result in information that producers and policy makers can use to incite changes in cropping systems.

Progress Report
Progress was made on all four objectives, which correspond to the four components of National Program 211. In support of Sub-objective 1A, which falls under Component 1 (Effective water management in agriculture) the soil moisture sensors installed in 18 of the 600-feet long experimental plots near Centralia, Missouri have been and are sending data, which have been reviewed and approved through 2024. Soil moisture data from the field were reviewed and certified through 2024. ARS scientists at Columbia, Missouri are part of the advising committee for the development of a Soil Moisture Network for the State of Missouri. Data collected at the research farm near Centralia is useful for this committee. In support of Sub-objective 1B, the collaboration with ARS scientists in Beltsville, Maryland, has resulted in remotely sensed evapotranspiration (ET) images validated with local measurements at field scale from 2017 to 2023. A manuscript on that topic is in preparation. Data analysis and a manuscript to relate remotely sensed ET and crop yields is in progress. In support of Sub-objective 1C, which addresses Problem 1E (Develop and Improve Simulation Modeling, Data, and Decision Support Tools for Water Management), ARS scientists in Columbia, Missouri, parameterized new models of the plots with more accurate spatial and temporal information of crop management. As a result, ARS scientists submitted a manuscript on the sensitivity of model parameters to dry and wet weather, showing that some of these parameters have different and very distinct ranges of values depending on the soil moisture status. An additional outcome of this project is a more accurate database of field operations for selected plots and fields for 2007-2024. In support of Objective 2 (Erosion, Sedimentation, and Water Quality Protection), ARS scientists in Columbia, Missouri, continue to collect stream high-frequency dissolved phosphorus data as well as pH, dissolved oxygen, electrical conductivity, and turbidity. This supports Problem Statement 2B, which aims to determine in-stream processes affecting contaminant fate, transport, and biological elements. Monthly water samples continue to be collected at that location from June to October and sent to Oxford, Mississippi collaborators for algal content determination and collaboration in a cross-site study, which investigates the sensitivity and limitation of algae growth to nutrient concentrations. Several presentation abstracts were submitted. ARS scientists in Columbia, Missouri, also started collaboration with a small business to assess the accuracy of dissolved phosphorus measured from an optical sensor lowered into the water from a drone. Progress was made in all sub-objectives of Objective 3, which evaluates conservation practices in agricultural watersheds (Component 3). The four sub-objectives all aim to improve our understanding of chemical, physical, and biological processes that affect implementation of conservation practices (Problem Statement 3A) and assess and implement conservation practices in agricultural landscapes (Problem Statement 3B). In support of Sub-objective 3A2, scientists at Columbia, Missouri, have continued to collect and process eddy flux data, which are going to the AmeriFlux site. Using this data, ARS scientists analyzed the eddy flux and soil moisture data for a full rotation of maize-soybean-wheat prior to and after a hay crop. The results showed that the grain crops following the hay crop had more growth, higher yields, and less sensitivity to soil moisture. The manuscript is drafted, with a planned submission date this fiscal year. Although work under Sub-objective 3B is complete, work carried on, based on 2022 findings that applying nitrogen at a rate slightly below the economic optimal nitrogen rate can improve the Nitrogen Use Efficiency with minimal forgone profits. This on-going effort evaluates the utility of using unfertilized and high nitrogen fertilized areas to inform in-season and post-season nitrogen fertilizer management strategies. This work is being conducted in the research field near Centralia, Missouri, along with farmers’ fields. Data was collected on ten fields during the 2023 and 2024 growing seasons, with data collection on six more fields planned for the 2025 growing season. Data collection to support Sub-objective 3C (i.e., agronomic and carbon dioxide, nitrous oxide, and methane emission data at the Soil Productivity Assessment for Renewable Energy and Conservation (SPARC) plots, process physical samples) continued in FY25. However, the measurement site shifted from the SPARC site at Columbia, Missouri, to the plots located at the main experimental site near Centralia, Missouri, which better characterize the cropping systems under study (larger plots, real working fields). The site at Columbia was more convenient when monitoring equipment required more labor with unpredictable timing needs. Newer equipment that can be automated gave the ability to move measurements further from the office. Carbon dioxide, nitrous oxide, methane flux and all agronomic data (e.g. aboveground biomass, grain yield, and nutrient concentration) have been processed and are undergoing final quality checks. Methane and nitrous oxide data analysis has started, along with development of the corresponding manuscript. Similarly, data collection to support Sub-objective 3D1 (i.e., agronomic and aboveground biomass at the Long-Term Agroecosystem Research (LTAR) site) was completed for the FY24 crop in the plots that have prevailing and alternative management practices; it continues with the FY25 crop. In support of Sub-objective 3D2, collection of monthly data and samples continued until the end of the 2024 growing season to characterize biodiversity in the native prairie and the prevailing and alternative cropping systems. These measurements stopped in 2025, data analyses were completed, and manuscripts are in preparation. Objective 4 is directly related to LTAR objectives of evaluating the cropping systems with prevailing and alternative practices for a suite of indicators. ARS scientists contributed to the development of the LTAR indicator framework, supporting Objective 4A1. In collaboration with several LTAR working groups, scientists at Columbia, Missouri, have led and published (on protocols.io) a collection of 35 measurement protocols for the measurement, quality assurance, and quality control procedures for the metrics needed to evaluate LTAR agroecosystems. These metrics are being used to calculate indicators of production, environmental, and economic performance for the prevailing and alternative practice systems. A manuscript on the comparison between the two systems, and the identification of trade-offs is in progress. In support of Objectives 4A2 and 4A3, agronomic data was collected, and off-site nitrogen losses were calculated based on water quantity and quality monitoring data, biomass samples were collected and processed to quantify nitrogen content in biomass, and quality control was performed. In support of Sub-objective 4B1 and under the leadership of the LTAR Research Data Advisory Team (RDAT), scientists at Columbia, Missouri, have developed the internal LTAR DataHub on the Socrata data management platform. This platform enables the different LTAR sites to upload, share and publish data. Scientists and data managers at Columbia, Missouri, have led the development of data governance and data flow documentation, which will guide data sharing within the LTAR network. Requests for information show that these efforts will have an impact beyond LTAR. This work resulted in a paper on the LTAR data infrastructure. Data managers at Columbia, Missouri, have uploaded meteorological data from the Central Mississippi River Basin LTAR site to the internal LTAR DataHub. Common Experiment and long-term observatory data on production, soil, weather, flow, and water quality are ready to be uploaded to this platform. Over the summer, scientists and data managers will continue to work with LTAR to define the templates for the upload of this data. Scientists at Columbia, Missouri, have certified all water and carbon flux, soil moisture, flow, and water quality data (Sub-objective 4A2) up to December 2024, as well as production data (crop yields) in the alternative practice field and in the plots. Total nutrients (nitrogen and phosphorus) from FY19 and later are now processed and certified up to December 2023. Eddy flux data, flow and water quality, and production data were uploaded to Ameriflux, Stewards, and Socrata, respectively. In support of Objectives 4C1 and 4C2, scientists at Columbia, Missouri, have published a paper that explains how the prevailing and alternative practices for the LTAR Common Experiment at the Central Mississippi River Basin were defined with input from stakeholders. Additionally, a network-wide paper describing these common practices at each site has been published for scientists to assess tradeoffs across regions for environmental and productivity indicators. These two papers were part of a Special Issue in the Journal of Environmental Quality. An agreement with the University of Missouri is in place to conduct a survey and assess the representativeness of these two management systems throughout the region. Overall, the team has met all its commitments to the LTAR network, which means that cross-site data analysis between LTAR sites can include our data. In addition, the team continues to produce data analyses of direct interest to our stakeholders, who have requested more information on how management affects outcomes given the local soil context.

Accomplishments
1. Protocol collection published for widespread implementation across the national LTAR network. The USDA-ARS Long-Term Agroecosystem Research (LTAR) network includes a Common Experiment that tests innovative agricultural practices with potential to promote sustainability of cropland and grazing land agriculture. ARS researchers at Columbia, Missouri, and other sites in the LTAR network collaboratively developed 35 standardized protocols for the biophysical measurements (e.g., plant productivity, soil, water, biodiversity, pests) collected in the Common Experiment. This set of protocols was developed for cropland systems, but some are also useful for grazing and integrated systems. Standardized protocols ensure that data collected within the network is robust and comparable across sites. Furthermore, this collection serves as a reference for other research networks and projects that seek to quantify biophysical metrics on farm or grazing lands. This collection of protocols represents a major advancement for the LTAR network through standard, transparent, and publicly available methods that allow producers and stakeholders to confidently apply the data in their own production systems.

2. Improving an index to classify cropland vulnerability to envrionmental loss. Identifying vulnerable crop fields that present a risk for water quality helps rank fields in terms of conservation needs. The Soil Vulnerability Index (SVI) uses slope and soil data to rank cropland into four levels of vulnerability to sediment and nutrient losses: low, moderate, moderately high, and high. Previous work has identified a concern that precipitation may influence vulnerability. ARS researchers in Columbia, Missouri, in collaboration with the University of Missouri, used computer simulation models of four watersheds in Missouri, Ohio, Pennsylvania, and Mississippi to determine if rainfall characteristics influence the SVI classification. Results showed that increasing vulnerability rating by one class was warranted where winter rainfall is equal or greater than summer rainfall. Doing so would alert conservation managers and landowners to the need for conservation practices that protect against winter erosion such as cover crops, a winter cash crop, appropriate residue management, and careful winter grazing. This evaluation, which highlighted the specific role of winter precipitation, helps soil conservationists interpret the SVI with respect to rainfall and contributed to NRCS efforts toward incorporating rainfall characteristics into the SVI.

3. In-season nitrogen diagnostic tool improves corn nutrient management across the U.S. Midwest. Unpredictable weather and variable soils make corn nitrogen fertilizer management difficult for Midwest farmers. Optimizing nitrogen fertilizer use requires accurate in-season diagnostics of plant nitrogen levels. ARS researchers at Columbia, Missouri, in collaboration with university scientists around the Midwest evaluated various Nitrogen Nutrition Indices (NNI) as a dynamic tool to diagnose corn nitrogen status during the growing season. Using field experiments from eight states, they validated the use of previously developed NNI models for use across the Midwest. In addition, they identified three distinct yield response patterns to NNI and determined that pre-plant nitrate, rainfall timing, and rainfall distribution were key factors governing these responses. Findings demonstrated the efficacy of NNI for guiding in-season nitrogen management by discerning when nitrogen fertilization would be beneficial or a waste of resources. This research supports precision agriculture strategies that enhance economic return for farmers while improving nitrogen use efficiency.

4. Native grasses restore many aspects of soil health. Perennial grass is known to maintain and improve soil health compared with annual row crop systems and can be leveraged to restore the productivity and sustainability of degraded soil resources. However, little is known about the potential recovery trajectory of soil health following incorporation of perennials on degraded landscapes. An ARS scientist at Columbia, Missouri, in collaboration with University of Missouri colleagues, examined soil health and biodiversity across a continuum of restored prairie systems representing remnant (never cultivated) prairie, prairie at several stages (years) of restoration, and active row crop and biofuel production agriculture. Results found that after two to three decades, above-ground floral diversity and below-ground soil microbial community diversity remained divergent from the native prairie state. However, several fundamental soil health indicators such as active carbon recovered. In addition, the comparison of a native with a non-native perennial biofuel grass found that the native grass achieved greater soil health recovery than the non-native grass. These results demonstrate the potential soil health benefits of long-term, perennial biofuel cropping systems and suggest that native grasses offer the best opportunity to recover soil health and restore the productivity of degraded soil resources within a few decades. Producers and landowners can incorporate this information in their decision-making process for degraded land on their farm.

5. Lost-cost cameras can be used to monitor crop productivity. Crop growth is sensitive to changes in management, environment, and genetics, but untangling the impact of these factors is difficult due to complex relationships and feedback loops. Frequent measurements (i.e., daily or sub-daily) of crop growth provide valuable data to help researchers separate the impacts of various stressors due to management, environment, and/or genetics. The gold standard for high frequency measurements of crop productivity is eddy covariance, but these measurements are expensive to make and require considerable expertise to complete. Therefore, ARS researchers at Columbia, Missouri, and other sites in the LTAR network used greenness metrics from standard red-green-blue (RGB) digital images obtained from phenocams to predict gross primary production (GPP) and evapotranspiration. Comparison with eddy covariance measurements showed that in croplands, RGB images can predict GPP with high accuracy (r2 = 0.91). This could provide a low-cost method for researchers, crop advisors, and producers to monitor crop growth, which can be used to adjust fertilizer applications based on crop needs, improving production and profitability.

Review Publications
Tsegaye, T., Marlen, E., Hapeman, C.J., Kleinman, P.J., Baffaut, C., Browning, D.M., Coffin, A.W., Spiegal, S.A. 2024. The Long-Term Agroecosystem Research Network: Cross-site transdisciplinary science to support a sustainable and resilient agriculture. Journal of Environmental Quality. 53(6):777-786. https://doi.org/10.1002/jeq2.20649.
Lee, K., Sudduth, K.A., Zhou, J. 2024. Evaluating UAV-based remote sensing for hay yield estimation. Sensors. 24(16). Article 5326. https://doi.org/10.3390/s24165326.
Abendroth, L.J., Schreiner-McGraw, A.P., Ransom, C.J., Baffaut, C., Sudduth, K.A., Veum, K.S. 2024. The LTAR Cropland Common Experiment at Central Mississippi River Basin. Journal of Environmental Quality. 53(6):968-977. https://doi.org/10.1002/jeq2.20614.
Liebig, M.A., Abendroth, L.J., Robertson, G., Augustine, D.J., Boughton, E.H., Bagley, G.A., Busch, D.L., Clark, P., Coffin, A.W., Dalzell, B.J., Dell, C.J., Fortuna, A., Freidenreich, A.S., Heilman, P., Helseth, C.M., Huggins, D.R., Johnson, J.M., Khorchani, M., King, K.W., Kovar, J.L., Locke, M.A., Mirsky, S.B., Schantz, M.C., Schmer, M.R., Silveira, M.L., Smith, D.R., Soder, K.J., Spiegal, S.A., Stinner, J.H., Toledo, D.N., Williams, M.R., Krecker-Yost, J.L. 2024. The LTAR Common Experiment: Facilitating improved agricultural sustainability through coordinated cross-site research. Journal of Environmental Quality. 53(6):787-801. https://doi.org/10.1002/jeq2.20636.
Sutton, D., Veum, K.S., Davis, M.P., Lord, S., Ransom, C.J., Sudduth, K.A. 2025. Soil health benefits of perennial biofuel crops on claypan soils. Soil Security. 19. Article 100193. https://doi.org/10.1016/j.soisec.2025.100193.
Wynne, K.C., Parker-Smith, M.J., Murdock, E.M., Sullivan, L.L. 2024. Quantifying seed rain patterns in a remnant and a chronosequence of restored tallgrass prairies in north central Missouri. Journal of Applied Ecology. 61:3017-3027. https://doi.org/10.1111/1365-2664.14806.
Baffaut, C., Thompson, A., Phung, Q., Veith, T.L., Witthaus, L.M., Aloysius, N., Duriancik, L. 2024. Modification of the Soil Vulnerability Index to account for increased erosion risk from winter precipitation in the southern United States. Journal of Soil and Water Conservation. 79(5):247-260. https://doi.org/10.2489/jswc.2024.00088
Bosche, L., Gomez, F., Palmero, F., Kerns, A., Hefley, T., Ransom, C.J., Prasad, P., Woestyne, B., Ciampitti, I. 2025. Nitrogen nutrition index as an in-season N diagnostic method for maize yield response to N fertilization. Field Crops Research. 328. Article 109941. https://doi.org/10.1016/j.fcr.2025.109941
Li, D., Croft, H., Duveiller, G., Schreiner-Mcgraw, A.P., Belwalkar, A., Cheng, T., Zhu, Y., Cao, W., Yu, K. 2025. Global retrieval of canopy chlorophyll content from Sentinel-3 OLCI TOA data using a two-step upscaling method integrating physical and machine learning models. Remote Sensing of Environment. 328. Article 114845. https://doi.org/10.1016/j.rse.2025.114845.