Source: IOWA STATE UNIVERSITY submitted to NRP
CONFRONTING ISOTOPE-ENABLED MODELS WITH DATA TO QUANTIFY AND PREDICT SOIL CARBON CHANGE IN DIVERSIFIED CROPPING SYSTEMS
Sponsoring Institution
National Institute of Food and Agriculture
Project Status
COMPLETE
Funding Source
AFRI COMPETITIVE GRANT
Reporting Frequency
Annual
Accession No.
1024993
Grant No.
2021-67019-33424
Cumulative Award Amt.
$499,955.00
Proposal No.
2020-05075
Multistate No.
(N/A)
Project Start Date
Jan 15, 2021
Project End Date
Jan 14, 2025
Grant Year
2021
Program Code
[A1451]- Renewable Energy, Natural Resources, and Environment: Agroecosystem Management
Recipient Organization
IOWA STATE UNIVERSITY
2229 Lincoln Way
AMES,IA 50011
Performing Department
Ecology, Evolution and Org Bio
Non Technical Summary
Agricultural soils in the US Corn Belt have lost substantial amounts of carbon relative to historical conditions, contributing to decreased soil fertility while exacerbating climate change. Increasing the adoption of agricultural practices such as extended crop rotations, cover crops, and perennial vegetation provides an opportunity to regain significant soil carbon and associated ecosystem services. However, directly measuring or predicting the response of soil carbon to management changes remains difficult due to technical challenges. In this project, we will examine different forms (isotopes) of carbon in soils and plants from long-term agricultural experiments to provide a more sensitive measurement of carbon change resulting from adoption of new management practices. We will then use the isotope measurements to test and improve models that can simulate changes in soil carbon and other environmental processes. These models will be used to predict soil carbon change underpotential current and future agricultural management scenarios in the Corn Belt region. We will communicate our findings to local stakeholders via outreach events, and to the scientific community via peer-reviewed publications. The models developed here will be freely shared with the scientific community. Findings from the measurements and models will enable producers and policy makers to better understand how much carbon might be gained following adoption of specific agricultural practices. Our findings will also provide additional scientific context to inform private-sector agricultural carbon markets, which may represent an increasingly important source of revenue for producers.
Animal Health Component
40%
Research Effort Categories
Basic
40%
Applied
40%
Developmental
20%
Classification

Knowledge Area (KA)Subject of Investigation (SOI)Field of Science (FOS)Percent
1020110107075%
1010110107025%
Knowledge Area
102 - Soil, Plant, Water, Nutrient Relationships; 101 - Appraisal of Soil Resources;

Subject Of Investigation
0110 - Soil;

Field Of Science
1070 - Ecology;
Goals / Objectives
Diversified cropping systems including extended rotations, cover crops, and perennials present an opportunity to reverse historical losses of soil organic carbon (SOC) and increase agroecosystem sustainability. However, benefits of these practices remain difficult to quantify and upscale due to empirical challenges in detecting SOC change. Carbon stable isotopes provide an underutilized tool for data-model integration. We propose to measure carbon stable isotopes in plants/soil from three long-term field experiments comparing a wide range of diversified and conventional cropping systems in the Midwestern US. We will modify code ofmechanistic ecosystem models to track isotope values of carbon pools in these experiments. Comparisons of measured and modeled carbon isotopes and pool sizes enable calibration, modification, and validation of models to test our assumptions of how diversified cropping systems alter SOC dynamics. Validated models will be used to quantify and predict sustainability impacts of adopting diversified cropping systems across multiple spatiotemporal scales. Results will be shared with stakeholders in collaboration with producer organizations and cooperative extension. Isotope-calibrated models will be freely shared to enable future use. Findings will enhance our mechanistic understanding of how diversified cropping systems alter SOC dynamics, and the implications of these practices for SOC sequestration and related sustainability gains.(1) Measure 13C of C inputs, SOC pools, and selected fluxes among cropping systems at three field experiments. These are prescribed inputs and response variables for driving and interpreting our mechanistic models. These data will be used to calibrate and validate model outputs.(2) Revise and/or develop new model code to track the 13C values of C pools and fluxes in ecosystem models, beginning with the Dynamic Land Ecosystem Model (DLEM), and also using the Agricultural Production System Simulator (APSIM) and Agro-IBIS as points of reference.(3) Compare measured data with model predictions using the field experiments during their actual period of existence and use calibrated models for prediction under near-future scenarios. In cases of disagreement, we will test alternative model parameterizations, structures, and mechanisms to achieve improved representations of 13C measurements and improve predictive capacity among models. Using the calibrated and validated models, we will predict possible gains in SOC among cropping systems over annual to decadal scales under representative management scenarios.(4) Synthesis and outreach: Products include manuscripts that describe and analyze impacts of diversified cropping systems on SOC dynamics from a mechanistic perspective; calibrated models that represent those dynamics under current model assumptions; and, application of the models for upscaling future SOC scenarios in our region. Our results will be communicated both to regional stakeholders (Iowa Learning Farms and the Practical Farmers of Iowa) and to the broader scientific community. For future use by the scientific community, model code will be made freely available to the scientific community.
Project Methods
Objective 1: Empirical measurements of plant and soil 13C values and selected fluxesWe will analyze the chemical composition of plant biomass collected from our focal cropping systems experiments. Dried and ground subsamples of above- and below-ground plant material from each crop (or biomass mixture, in the case of the prairies) will be combusted in an elemental analyzer coupled to an isotope ratio mass spectrometer (EA-IRMS) to measure d13C, d15N, and C and N concentrations.The d13C values of SOC (and soil respiration from incubated samples) will also be measured. Briefly, soil will be sampled at increments of 0-15, 15-30, 30-60, and 60-100 cm in each plot from replicate cores. Bulk density will be measured using the intact core method. Samples will be composited by plot and depth increment, dried, and ground for analysis of d13C of SOC by EA-IRMS. Inorganic C (i.e., carbonate) and its 13C values will be analyzed if present by acidification.Soil incubations will be conducted using soil cores from the same depth increments as above, collected from a subset of sites, using the automated apparatus described in Ye & Hall (2020). Cores will be amended with water to achieve 65% water-filled pore space and maintained at 21 d13C are measured over a several-month period. Pool sizes and decomposition rate constants of fast- and slow-cycling C3 and C4 pools will be measured using exponential models fit to the cumulative CO2 production data.Objective 2: Enable d13C predictions of C pools/fluxes in mechanistic models We will refine or add code to track the d13C values for each modeled C pool (e.g., fast- and slow-cycling litter C, and fast, slow, and passive SOC). This will be accomplished by prescribing the d13C values of plant C inputs based on our measurements (Objective 1), and then moving C with defined 13C values through the litter and SOC pools according to the established governing equations, with losses as CO2 and via biomass or grain harvest. Initial 13C values of each modeled pool will be determined using a spin-up run as described below. The SOC pool sizes and d13C values in each model will be "spun up" to the beginning of each field experiment by prescribing previous prairie vegetation row-crop agriculture, with representative NPP and 13C values based on prior empirical work and model-data comparisons. Briefly, prescribed 13C of biomass and SOC from prairie and long-term corn/soybean soils will be inferred from measurements near the ISU sites. After the spin-up period, the passive pool 13C value will comprise a mixture of prairie and agricultural inputs, and the slow pool 13C will comprise mostly corn/soybean-derived C from the late 20th century. The mass-weighted d13C values of the modeled SOC pools will be compared against bulk d13C measurements of SOC from time-zero samples collected from each field plot prior to initiation of the field experiments, and spin-up parameters will be adjusted as necessary. Historical site-level weather data will be used to drive the models during the experimental period, and previous measurements of soil temperature and moisture will be used to validate the biophysical predictions of the model based on the prescribed boundary conditions. Objective 3: Iterative model-data comparisons for calibration, validation, prediction, and model improvementWe will use the d13C and C pool/flux measurements collected in Objective 1 to compare with model predictions generated in Objective 2 to address the overarching questions regarding the magnitude of soil carbon change that could be achieved under various possible cropping systems and management scenarios. These comparisons will allow us to explore the model parameter space and/or structure to test predictions with observations. The measured amount and 13C values of litter from diversified cropping systems will be used to drive the mechanistic models. For each pool (including litter, microbial, and soil pools) and each flux, model output will be tagged with a known δ13C value. Half of the lab incubation and in-situ measurement data will be used for model parameterization, and the remaining half will be used to validate model performance. We will use three types of empirical measures to validate the model-predicted 13C values. First, we will compare measured bulk 13C of SOC with the mass-weighted 13C value of the sum of the multiple modeled C pools. We will use the d13C values, pool sizes, and decomposition rate constants derived from the field and lab measurements as another approach to compare with the 13C values of CO2 fluxes from pools predicted by the model. We will compare pre- and post-isotope-enabled model estimates and quantify whether and to what extent the prediction accuracy of SOC pool and fluxes has been improved in agricultural soils under various cropping systems. Individual model estimates and model-ensemble mean and standard deviation will be synthesized and compared with measurements to identify model incapability (i.e., mismatch between model and data) and uncertainty (i.e. where large estimation discrepancy exists among models). We will then model the impacts of multiple diversified cropping systems at regional scales to predict how SOC storage could be increased under different scenarios. For example, what gains in SOC could be achieved under varying extents of producer adoption of cover crops, perennials, and/or extended rotations?

Progress 01/15/21 to 01/14/25

Outputs
Target Audience:The project's outreach and dissemination efforts targeted a diverse audience spanning academic researchers, scientific professionals, agricultural practitioners, and policy makers. Engagement with the scientific community included presentations at major conferences such as the American Geophysical Union Fall Meetings (2022 and 2023) and the USDA-NIFA-hosted session at the ACES Conference, as well as peer-reviewed publications in journals such as Nature Sustainability, Geoderma and Biogeochemistry. In addition, the data product, including lab incubation data and estimated SOC decomposition rate from three process-based models, were published with a DOI to support open research. Efforts to reach practitioners and stakeholders in agriculture were reflected in presentations at forums like the Iowa Learning Farms seminar and the Practical Farmers of Iowa annual meeting, where results were framed around soil carbon and nitrogen dynamics in diversified cropping systems. A broader public and stakeholder audience was reached through media engagement, including a recent news article summarizing the findings with a title "Diversified cropping systems boost nitrogen supply but not soil carbon." Changes/Problems: Nothing Reported What opportunities for training and professional development has the project provided?The project has provided a wide range of training and professional development opportunities for researchers at multiple career stages, including graduate students, early-career scientists, and undergraduates: Graduate Training: The project supported Ph.D. student Bo Yi, who received extensive mentorship and training in ecosystem modeling, particularly the development and application of the isotope-enabled Dynamic Land Ecosystem Model (DLEM). His work involved model improvement, field-to-regional model scaling, and data/model intercomparisons using soil samples from diversified cropping systems. Postdoctoral and Early-Career Development: The project funded Dr. Wenjuan Huang, initially as a postdoctoral researcher and later as a research scientist and an assistant professor. Under the guidance of PD Hall, she led data/model synthesis efforts, enhanced her skills in modeling, computation, public speaking, and scientific writing, and participated in professional workshops. She later presented project findings as a faculty member at the 2024 ACES Conference, highlighting her transition to an independent research career. This project also partially supports one research Scientist, Isaiah Huber to improve SOC modeling. Undergraduate Involvement: The project supported undergraduate technicians who contributed to soil sampling and laboratory analyses. In addition, project-generated samples were used in an undergraduate lab course, allowing students to gain hands-on experience conducting soil incubations and analyses. How have the results been disseminated to communities of interest?The results were published in Nature Sustainability, Geoderma, and Biogeochemistry, and disseminated through platforms like EurekAlert!, ScienceDaily, and Iowa State Research News. The research team also engaged with practitioners and policy makers, notably through presentations at the American Geophysical Union (AGU) meetings and the Practical Farmers of Iowa annual meeting, enhancing the impact and relevance of the findings beyond academia. What do you plan to do during the next reporting period to accomplish the goals? Nothing Reported

Impacts
What was accomplished under these goals? This project produced significant scientific and practical contributions by uncovering a key trade-off in diversified cropping systems: while they enhance nitrogen supply through accelerated soil organic carbon (SOC) decomposition, they do not necessarily increase long-term SOC storage. Using field observations, laboratory incubations, and isotope-enabled modeling, the research challenged prevailing assumptions about carbon sequestration in diversified systems and provided new insights into carbon and nitrogen cycling. Key findings include: Diversified cropping systems increased nitrogen mineralization through stimulated SOC decomposition, particularly from carbon pools with residence times of months to years. SOC accumulation did not increase in long-term diversified systems due to enhanced decomposition offsetting increased root carbon inputs. The climate benefits of diversified systems in the Midwest stem more from reduced nitrogen fertilizer use than from carbon sequestration. The project developed and calibrated isotope-enabled modules for three major ecosystem models (CN-SIM, APSIM, Agro-IBIS), which improved simulation of SOC processes and reduced uncertainty in model parameter estimates. Model-data comparisons revealed that failure to account for system-specific carbon decay rates can lead to substantial underestimates of CO? emissions in extended crop rotations. In addition to its scientific contributions, the project advanced measurement techniques and process-based SOC modeling by: Developing a new method to measure d13C of organic carbon by measuring total carbon and inorganic carbon separately, which avoids the biases that we detected using the carbonate removal method. Integrating isotope feature into three process-based SOC models and tracing CO2 source by constraining model estimates with the lab measurements of CO2 emission and d13C values of CO2 from 36 soil samples from long-term experimental sites with diversified cropping system.

Publications


    Progress 01/15/24 to 01/14/25

    Outputs
    Target Audience:The project's funded postdoctoral researcher, Dr. Wenjuan Huang, now an Assistant professor at Iowa State University, presented our findings in a USDA-NIFA-hosted session at the ACES Conference in December 2024, titled "A Trade-off Between Soil Carbon Storage and Nitrogen Supply in a Diversified Cropping System," as well as at the Iowa Learning Farms seminar with the title of "Can diversified cropping systems help increase soil carbon storage?". Besides, the lab incubation data using 36 soils in the Marsden agroecosystem diversification experiment and estimated SOC decomposition rate from three process-based model were published with a doi. An news article was released to report our research findings with a title "Diversified cropping systems boost nitrogen supply but not soil carbon, study finds." Changes/Problems: Nothing Reported What opportunities for training and professional development has the project provided?This project partially supports one graduate student, Bo Yi, to complete his dissertation, and one research Scientist, Isaiah Huber to improve SOC modeling. It also partially support Dr. Wenjuan Huang, an assistant professor to present our findings at the 2024 ACES conference. How have the results been disseminated to communities of interest?Media Coverage: Iowa State Research News: Diversified Cropping Systems Boost Nitrogen Supply But Not Soil Carbon, Study Finds https://research.iastate.edu/2025/01/14/diversified-cropping-systems-boost-nitrogen-supply-but-not-soil-carbon-study-finds/ EurekAlert! https://www.eurekalert.org/news-releases/1070649 ScienceDaily https://www.sciencedaily.com/releases/2025/01/250115164833.htm What do you plan to do during the next reporting period to accomplish the goals? Nothing Reported

    Impacts
    What was accomplished under these goals? Based on field observations, laboratory incubations, and isotope-enabled model comparisons, our work identified a critical trade-off between carbon storage and nitrogen supply in diversified cropping systems, challenging the prevailing hypothesis that these systems enhance soil organic carbon sequestration. Our findings indicate that diversified systems accelerate the decomposition of SOC, leading to a substantial increase in nitrogen mineralization rate and supply. Isotope-enabled models further confirmed that the increased carbon decomposition primarily originates from carbon sources with residence times of months to years. This increased decomposition offsets higher carbon inputs while simultaneously enhancing nitrogen availability. Consequently, the primary climate benefits of these systems in the Midwest arise from reduced nitrogen fertilizer use rather than SOC accumulation. This work has been published in Nature Sustainability and was featured in Iowa State Research News under the title "Diversified cropping systems boost nitrogen supply but not soil carbon, study finds." It has also been widely disseminated through research media, including EurekAlert! and ScienceDaily.

    Publications

    • Type: Peer Reviewed Journal Articles Status: Published Year Published: 2025 Citation: Yi, B., Huang, W., Liebman, M. et al. Diversified cropping systems with limited carbon accrual but increased nitrogen supply. Nat Sustain 8, 152161 (2025). https://doi.org/10.1038/s41893-024-01495-4
    • Type: Conference Papers and Presentations Status: Other Year Published: 2024 Citation: Huang, W. A Trade-off between soil carbon storage and nitrogen supply in a diversified cropping systems. ACES, December 912, 2024, Austin, Texas
    • Type: Other Status: Other Year Published: 2024 Citation: Huang, W. Can diversified cropping systems help increase soil carbon storage? Iowa Learning Farms Webinar, November 13, 2024
    • Type: Theses/Dissertations Status: Other Year Published: 2024 Citation: Yi, B., 2024. Impacts of Substrate Quality on Soil Organic Carbon Decomposition Dynamics: Modeling Representation and Data-Model Integration. Iowa State University Dissertations & Theses @ Iowa State University; ISBN 9798382802794.


    Progress 01/15/23 to 01/14/24

    Outputs
    Target Audience:We presented results from our project to the scientific community at the 2023 American Geophysical Union Fall Meeting in San Francisco, CA. Additionally, two journal articles encapsulating some of our key findings has been published in research journals of "Geoderma" and 'Biogeochemistry'. Detailed information about the paper and presentation can be found in the "Products" section of the report. Changes/Problems:The original Principal Investigator (PI), Dr. Steven Hall, departed from ISU in the summer of 2023. This departure resulted in some delays due to the necessary project transfer and personnel changes, including the relocation of a senior personnel, Dr. Wenjuan Huang. We are requesting a one-year no-cost extension to complete this project. During the proposed extended period, our focus will be on the enhancement of the soil organic carbon (SOC) module in three agroecosystem models. This enhancement involves the integration of δ13C values of SOC pools and fluxes, which have already been tested by comparing them with lab incubation results. In the upcoming year, our objective is to assess whether these models can effectively simulate SOC stock and changes in the field. To achieve this, we plan to utilize historical records of weather patterns, cropping choices, and in-field management practices to drive the model. We aim to develop "real-world" scenarios, wherein the model-estimated values will be compared with field measurement data. This process will demonstrate the efficacy of isotope-enabled agroecosystem models in tracking soil carbon sequestration and loss over time. What opportunities for training and professional development has the project provided?This project funded the salary of Dr. Wenjuan Huang, an early-career Research Scientist and former postdoc, who has undertaken extensive data/model synthesis under PD Hall's guidance. Dr. Huang has enhanced her modeling and computational skills through specialized workshops, and has gained additional training in public speaking and writing abilities via Hall's lab mentorship. Additionally, the project has also supported the training and mentorship of a PhD candidate Bo Yi. His research centers on the isotope-enabled Dynamic Land Ecosystem Model (DLEM) development, focusing on model improvement, data/model inter-comparisons using soil samples from Marsden field, and working on the model upscaling to from model from field-level analyses to regional-scale applications. How have the results been disseminated to communities of interest? Academic publication and International conferences We published two peer-reviewed papers in academic journals and presented our research findings at the 2023 AGU fall meetings. Outreach/Extension Practical Farmers of Iowa 2023 Annual Conference, Ames, IA (January 2023). Reframing the conversations around soil carbon (60-minute presentation and discussion targeted to farmers, policymakers, and landowners). What do you plan to do during the next reporting period to accomplish the goals?We will continue working on refining the manuscript (ready to submit), delineating our insights into the tradeoff between carbon sequestration and nitrogen supply from diversified cropping systems in Marsden experiment. Furthermore, the SOC modules, calibrated with lab data, have been extended to field-level simulations. The field simulations are driven by historical records on land use, fertilizer management, and climate data. Currently, we are engaged in calibrating these models with field-measurement, e.g., crop yields, for regional simulations. The isootope-enabled agroecosystem models will be used to project the long-term soil carbon dynamics under various cropping systems.

    Impacts
    What was accomplished under these goals? We made major progress on each of the four goals outlined above, which I will summarize for each. (1) Measure d13C of C inputs, SOC pools, and selected fluxes among cropping systems at three field experiments In our comprehensive assessment of diversified cropping systems at Marsden, we have measured soil textures (including loam, sandy loam, and clay content) and soil nitrogen mineralization rates. This evaluation aims to understand the impact of these systems on soil carbon and nitrogen, thereby informing model improvements. Our findings indicated a lack of change in soil organic carbon (SOC) within the 20-year Marsden diversified cropping systems experiment. This could be attributed to a trade-off between carbon sequestration and nitrogen supply. Specifically, despite increased root input in diversified systems, there is an acceleration in soil carbon decomposition, which increase carbon loss in older pools and enhances soil nitrogen supply. These insights, coupled with our model analysis, have been synthesized into a manuscript that is ready for submission and peer review. (2) Revise and/or develop new model code to track the d13C values of C pools and fluxes in ecosystem models The δ13C values of C pools and fluxes were integrated and coded into the SOC modules of three ecosystem models--the Dynamic Land Ecosystem Model (DLEM), the Agricultural Production System Simulator (APSIM), and the agricultural version of the Integrated Biosphere Simulator (Agro-IBIS), to develop isotope-enabled carbon cycling modules. We calibrated these SOC modules using 406-day lab incubation data from Marsden. This data encompassed CO2 fluxes and corresponding δ13C values, providing constraints on the decay rates of root and soil carbon pools. A strategic approach was employed to assess the significance of isotope features in diversified cropping systems by calibrating models both with and without isotope values. 3) Compare measured data with model predictions Models comparison revealed that decay rates of root and soil carbon pools differ across various cropping systems. Notably, soil carbon pools with 'month to decade' residence times were effectively simulated by diversified cropping systems, supporting our finding in lab incubations. Additionally, our research identified distinct parameter values for the decay rates of root and soil carbon pools among different cropping systems. Crucially, models that did not account for these parameter variations tended to underestimate CO2 emissions from more diversified rotational cropping systems by approximately 25%. These results were featured in an AGU presentation led by a PhD candidate Bo Yi.

    Publications

    • Type: Journal Articles Status: Published Year Published: 2023 Citation: Huang, W., Mirabito, A.J., Tenesaca, C.G. et al. Controls on organic and inorganic soil carbon in poorly drained agricultural soils with subsurface drainage. Biogeochemistry 163, 121137 (2023). https://doi.org/10.1007/s10533-023-01026-x
    • Type: Journal Articles Status: Published Year Published: 2023 Citation: Leeford M, Mavi MS, Liptzin D, Hall SJ. 2023. Potential carbon mineralization assays are confounded by different soil drying temperatures. Geoderma 437: 116596


    Progress 01/15/22 to 01/14/23

    Outputs
    Target Audience:To communicate results from our project to practitioners and policy makers, Hall gave an hour-long presentation and discussion titled "Reframing the conversations around soil carbon" in the Practical Farmers of Iowa annual meeting in January 2023, which was focused on soil carbon and associated environmental issues in agroecosystems. This presentation largely focused on results from our current NIFA project. We presented results from our project to the scientific community in three presentations (two talks and a poster) at the 2022 American Geophysical Union Fall Meeting in Chicago, IL. Details for these presentations are as follows are provided in the "Products" section of the report. Some of the findings from this third talk are included in a manuscript under review in Biogeochemistry (major revisions were requested), with the following details (included here because it is not yet officially accepted). However, the data from this study have been published, with doi provided in the "Other Products" section Controls on organic and inorganic soil carbon distribution in a poorly drained agroecosystem. Huang W, Mirabito A, Tenesaca CG, Mejia-Garcia WF, Lawrence N, Kaleita AL, VanLoocke A, Hall SJ. Changes/Problems: Nothing Reported What opportunities for training and professional development has the project provided?This project funded the salary of an early-career Research Scientist (formerly, a postdoc), Dr. Wenjuan Huang, who has conducted much of the data/model synthesis work under the supervision of PD Hall. She has gained additional training through workshops on modeling/computational skills, and in public speaking and writing through mentorship by Hall's lab group. The project also supported the training and mentorship of a PhD student, Bo Yi, who is focusing his research on the isotope-enabled DLEM model and data/model intercomparison using soils from cropping systems along with natural ecosystems as a benchmark. The project provided direct support for undergraduate technicians who assisted with soil sampling and laboratory measurements. Finally, samples from this project were also used in an undergraduate lab course taught by PD Hall, where students conducted their own soil incubations and soil analyses. How have the results been disseminated to communities of interest?The presentations and publications associated with this project are described along with the specific research objectives in the "Major goals" section, as well as in the "Products" section What do you plan to do during the next reporting period to accomplish the goals?We will finish the empirical analyses of soils from the COBS experiment. We will continue the data-model comparison and calibration/validation work described above. We will continue working on the manuscripts describing our initial results from the Marsden experiment and the new methods for carbonate detection and analysis described above. We will begin work to upscale our modeling analyses for comparison with existing d13C data available from other published field experiments.

    Impacts
    What was accomplished under these goals? We made major progress on each of the four goals outlined above, which I will summarize for each. (1) Measure d13C of C inputs, SOC pools, and selected fluxes among cropping systems at three field experiments. We finished sampling soils from the three field experiments, and we have finished laboratory incubations and analyses of samples from two of the experiments. Incubations and soil analyses are ongoing for the Comparison of Biofuel Systems (COBS) samples. Perhaps our most important finding thus far was a lack of change in soil organic carbon (SOC) in the 20-year Marsden diversified cropping systems experiment, despite large differences in the d13C values of soil respiration and detectable differences in the d13C of SOC. Together, these data indicated that increased root inputs in the diversified cropping systems stimulated the decomposition of existing SOC, thus preventing additional SOC gains. This interpretation is further supported by our data-model comparison described below. These results were presented in an AGU poster led by Research Scientist Dr. Wenjuan Huang. While comprehensively measuring the d13C values of organic carbon pools and fluxes in these soils, we also became aware of critical issues regarding the treatment of inorganic carbon. With our detailed isotopic measurements, we have uncovered systematic biases associated with a common protocol for removing inorganic carbon from soils, which is typically a prerequisite for measuring organic carbon. We have developed a new method to measure d13C of organic carbon by measuring total carbon and inorganic carbon separately, which avoids the biases that we detected using the carbonate removal method. In short, the common acid fumigation method used to remove carbonate can fail to completely remove carbonate, and it can also destroy a significant amount of organic carbon. These results were presented in an AGU talk by PD Hall and are in preparation for publication. Finally, our C isotope measurements in a long-term corn-soybean cropping experiment enabled us to test explanations for spatial variation in SOC associated with topography and cropped depressional wetlands. In conjunction with other biogeochemical measurements, the C isotope data showed that increased SOC in poorly drained depressional soils was likely derived from pre-agricultural plant inputs and erosion of topsoil from the adjacent field. We found no evidence that ongoing C inputs from corn and soybean were accumulating in these depressions, despite their poor drainage characteristics, and we suggest that gaining additional SOC in these systems will require fundamental management changes. These results were presented in a separate AGU talk by PD Hall and are described in a manuscript submitted to Biogeochemistry that was led by Research Scientist Dr. Wenjuan Huang (in second review, major revisions requested). (2) Revise and/or develop new model code to track the d13C values of C pools and fluxes in ecosystem models We have now successfully added and/or improved the capacity to track d13C values of C pools and fluxes to the three ecosystem models described in the proposal, the Dynamic Land Ecosystem Model (DLEM), the Agricultural Production System Simulator (APSIM) and the agricultural version of the Integrated Biosphere Simulator (Agro-IBIS). In the process, we have also improved the basic representation of soil C fluxes in Agro-IBIS, as including d13C enabled us to find subtle inconsistencies in the existing model code for C fluxes. (3) Compare measured data with model predictions. We have begun to use our field and laboratory data to calibrate and validate the isotope-enabled models. We have focused so far on modeling the Marsden diversified crop rotation experiment, which had the largest variation in carbon isotope values of the experiments that we sampled. When modeling the data from our laboratory soil incubation, we found that including d13C values of C fluxes as an additional constraint during parameterization greatly reduced the uncertainty around parameter estimates, while also changing the values of several key parameters. Our model/data comparison also shed light on the intriguing finding of no change in SOC in the Marsden diversified cropping systems experiment. The isotope-enabled DLEM and Agro-IBIS models both suggested that an increase in decomposition of older SOC pools in the extended rotations (three and four-year rotations) can explain the lack of SOC gains in these systems, despite greater root inputs. We are finalizing the explicit representation of d13C of CO2 in APSIM so we can include this model in the comparison as well. (4) Synthesis and outreach: To communicate results from our project to practitioners and policy makers, Hall gave an hour-long presentation and discussion titled "Reframing the conversations around soil carbon" in the Practical Farmers of Iowa annual meeting in January 2023, which was focused on soil carbon and associated environmental issues in agroecosystems. This presentation largely focused on results from our current NIFA project. Details surrounding our conference presentations and manuscripts in review and in preparation are described above.

    Publications

    • Type: Conference Papers and Presentations Status: Published Year Published: 2022 Citation: Diversified Cropping Systems Do Not Necessarily Increase Soil Organic Carbon. W Huang, SJ Hall, MD McDaniel, M Liebman. American Geophysical Union Fall Meeting, December 2022.
    • Type: Conference Papers and Presentations Status: Published Year Published: 2022 Citation: Quantify Carbonate Directly (Rather Than Removing it) When Measuring Soil Organic Carbon. SJ Hall, BW Johnson, W Huang. American Geophysical Union Fall Meeting, December 2022.
    • Type: Conference Papers and Presentations Status: Published Year Published: 2022 Citation: Follow the Water: Using Sub-Field Hydrologic Variation to Inform Climate-Smart Agricultural Practices. SJ Hall, W Huang, A Mirabito, CG Tenesaca, W Mejia-Garcia, N Lawrence, AL Kaleita, E Heaton, A VanLoocke. American Geophysical Union Fall Meeting, December 2022.


    Progress 01/15/21 to 01/14/22

    Outputs
    Target Audience:We hired staff for the project and began data collection, synthesis, and modeling efforts but have not yet presented any findings to our target audience Changes/Problems: Nothing Reported What opportunities for training and professional development has the project provided?A PhD student has been mentored in data/model integration as a result of this project. How have the results been disseminated to communities of interest? Nothing Reported What do you plan to do during the next reporting period to accomplish the goals?We will continue with our measurement and modeling activities to address objectives 1 and 2, and given sufficient progress, we will be able to begin objective 3. The outreach objective will be addressed via presentations to stakeholders (Practical Farmers of Iowa Annual Meeting) planned for early 2023.

    Impacts
    What was accomplished under these goals? 1) We addressed objective one by collecting soil from local experiments for measurements of C isotope pools/fluxes, which are in progress. To better initialize our models, we also conducted a literature survey to compile existing C isotope data and environmental covariates from other studies in the Corn Belt region. 2) We addressed objective two by preparing input data for our cropping systems model, and by preparing a simple spreadsheet model of C isotope flow to validate equations prior to incorporating them into the existing models. we have not yet begun to address objectives 3/4

    Publications