SYNTHESIZING DATA FROM A NETWORK OF LONG-TERM DIVERSIFIED CROPPING SYSTEM EXPERIMENTS TO REDUCE PRODUCER RISK IN AN UNCERTAIN CLIMATE

• Sponsoring Institution: National Institute of Food and Agriculture
• Project Status: COMPLETE
• Funding Source: AFRI COMPETITIVE GRANT
• Reporting Frequency: Annual
• Accession No.: 1019087
• Grant No.: 2019-67019-29468
• Cumulative Award Amt.: $500,000.00
• Proposal No.: 2018-07271
• Project Start Date: May 1, 2019
• Project End Date: Apr 30, 2024
• Grant Year: 2019
• Program Code: [A1490]- BNRE Networks for Synthesis, Data Sharing and Management

Recipient Organization
AGRICULTURAL RESEARCH SERVICE
RM 331, BLDG 003, BARC-W
BELTSVILLE,MD 20705-2351

Performing Department
Sustainable Ag Sys Lab

Non Technical Summary
Climate impacts on food and environmental security present serious agricultural challenges. Understanding complex interacting biotic and abiotic factors affecting cropping systems performance requires robust spatial and temporal data uniquely available from long-term cropping systems studies.We will develop a framework for addressing serious pending challenges in agriculture byCreating a publicly accessible database of crop performance and associated data from 13 existing long-term US and Canadian cropping systems studies uniquely representing diverse geographical regions. Data from these long-term cropping systems studies will be combined into a searchable data base containing meta-data on systems management along with yields, soil physical, chemical, and biological measurements, and weather data.Appling statistical modeling to these data to assess crop rotation diversification effects on multiple facets of system performance across soil-climate gradients. Using multiple statistical and modeling approaches the data will be used to evaluate multiple interacting effects on crop production within the context of crop rotation benefits (number of crops, types of crops, crop sequence etc).Incorporating these data with the Agricultural Production Systems Simulator and statistical models, to evaluate how crop rotation affects productivity and resilience under future climate scenarios. Results will be used in scientific publications and white papers to inform the scientific community, private, public and policy entities on the roles of crop rotation in reducing producer risk associated with future climate change.We will also identify significant gaps in our understanding of mechanisms responsible for crop rotation diversity effects on multiple facets of system performance. This project will facilitate a high level of communication and collaboration among researchers, representing diverse disciplines, geographical regions, and organizations which will lead to accelerated scientific understanding for enhanced agroecosystem sustainability. Open access to the assembled data will allow other researchers from multiple disciplines to also make new discoveries that are impossible to achieve without access to rich long-term datasets.The project will result in several high impact publications that will provide valuable information to farmers, extension workers, scientists, and policy makers seeking ways to develop production and management systems that sustain high levels of productivity, profitability, and environmental qualityThe institutions participating in this proposal have invested significant funds and many years conducting long-term cropping systems research. These projects have been used to answer questions at the local and regional scale related to crop rotation length, changes in soil properties, and environmental effects on crop production. Many questions on carbon sequestration, nutrient management, conservation tillage and other areas have been addressed within these projects providing answers uniquely based on the long-term effects. This cohort of institutions has a mutual interest in sharing data to answer questions on a national scale that can only be addressed with a large pool of data.Combining the existing data will create a resource much greater than that available from any one of the institutions.

Animal Health Component

50%

Research Effort Categories

Basic

50%

Applied

50%

Developmental

(N/A)

Classification

Knowledge Area (KA)	Subject of Investigation (SOI)	Field of Science (FOS)	Percent
205	2410	1070	34%
102	0199	2080	33%
132	2410	2090	33%

Knowledge Area
102 - Soil, Plant, Water, Nutrient Relationships; 205 - Plant Management Systems; 132 - Weather and Climate;

Subject Of Investigation
0199 - Soil and land, general; 2410 - Cross-commodity research--multiple crops;

Field Of Science
2090 - Statistics, econometrics, and biometrics; 1070 - Ecology; 2080 - Mathematics and computer sciences;

Keywords

climate change

cotton

crop diversification

crop rotation

maize

soybean

wheat

Goals / Objectives
This proposal addresses critical needs defined by participants at the Cornin Context workshop held inAmes IA (July 2018). It will: 1) establish a centralized data repository for existing data and metadata; 2) determine on regional and national bases optimum practices for reducing producer risk under projected climate scenarios; and 3) evaluate, at the regional and national scale, management (number of crops, types of crops, crop sequence, tillage, etc.) interactions with biotic and abiotic factors influencing crop production under diverse rotations.Specifically, we will:Combine data from 13 long-term cropping systems projects having diverse crop rotations into a national database for conducting meta-analyses and cross-site syntheses.Assess crop yield resilience to adverse weather conditions and determine sustainable options for reducing producer risks under future weather scenarios.Evaluate how crop production risks are influenced by crop rotation length and identify significant gaps in our understanding of the mechanisms contributing to multiple facets of cropping system performance (gap analysis will be used to develop future collaborative cross-location projects to fill these gaps using coordinated, standardized sampling campaigns).

Project Methods
Obj 1: Combine data sets from 13 long-term cropping systems projects into a national database for conducting meta-analyses and cross-site data synthesesHistoric data on agronomic yields, soils, weather and managementfrom13 long-term cropping systems siteswill be combined into a data base. Historical weather data willbe obtained from nearby weather stations and includeminimum and maximum air temperature and daily precipitation. A cross-site comparison will be conducted on soil measurements of bulk density, POM-C and POM-N from selected treatments at each site at 0- to 7.5- and 7.5- to 15-cm depth increments.Obj 2: Assess crop yield resilience to adverse weather conditions and determine sustainable options for reducing producer risks under future weather scenariosStatistical modeling will be usedto evaluate crop rotation diversification effectsacross cropping systems and soil-climate gradients. The ability of diverse cropping systems to perform better than less diverse systems in high stress years will be evaluated like relative yield stability of genotypes across environments.An index of environmental stress (EI) fora given yearis defined as the mean cash crop yield in all rotations at a given site. To succinctly capture crop rotational complexity, i.e. types of crops and number of crops per year and rotation will be used to calculate a crop diversity index (CDI) for each site-rotation (average number of crops per year times total number of crops in the rotation). For instance, the CDI of a corn-clover/rye-soy/ clover-wheat-clover/rye CDI is 15 (5 crops × 3 crops yr-1). Relationships between EI and CDI across sites will be defined by linear mixed modeling (LMM). Prior to modeling, yields will be time-detrended within each site. Detrended crop yield will be a function of CDI and EI, including an interaction term to quantify how crop rotation complexity affects yield responses across years with different levels of stress. Site-specific intercepts allow yields to vary by site and plot-specific intercepts account for repeated measures design of experiments. Site-specific slopes will be included for fixed effects of CDI, EI, and their interaction. Of interest is how the CDI by EI interaction varies across sites, since this parameter tests the hypothesis - crop rotations perform differently under different environmental stresses.Models will be fit using Markov chain Monte Carlo (MCMC) estimation. Some analyses will require a more tailored use of MCMC, particularly when using a Bayesian framework to facilitate the assimilation of non-data-based expert knowledge via prior model building for some of the parameters and structure choices in that model. Particularly when hierarchical modeling is involved. A Bayesian analysis will be warranted for specific hypothesis tests and other statistical questions faced with low power in the frequentist framework because of data scarcity.To test whether crop rotational diversity provides resilience to hot and dry growing conditions, an expected EI based only on indicators of heat and drought will be calculated for key corn developmental stages (vegetative growth, flowering, grain filling, and maturity) Within each stage and 30 days prior to planting, mean, maximum, and minimum temperature, vapor pressure deficit, and total precipitation will be used in a statistical model similar to multivariate adaptive regression splines, to relate yields to weather data in each year, defined as a drought or heat years. The modeling framework above will be used to assess how crop rotational diversity affects yields across years varying in drought and heat severity. The Bayesian framework above will be applied to compute likelihood of yield benefits from rotation recommendations under various weather projections.We will correlate varying site slopes with mean annual precipitation (MAP), coefficient of variation of MAP or other measures of MAP uncertainty, and other climatic and edaphic factors to gain insight into potential factors driving differential effects of crop rotational complexity across sites. We will quantify how variation can be linked to changes in soil health (e.g. soil C pools) and other soil properties and use decades-long projections of how frequency and severity of climate extremes may increase, to make long-term projections of benefits of rotational diversity. Although yield resilience to environmental stress is an emergent property of whole agroecosystem, this will allow us to begin quantifying potential underlying drivers and their long-term effects (Objective 3).Diversified rotations contribute to reduced risk for producers will be evaluated via a "portfolio effect", e.g. where low returns in one year for one crop are combined with relatively high returns from a different crop. Regional prices will be used with yield data to calculate returns at each site. Meta data on inputs (fertilizers, pesticides, labor, fuel, etc. collected at each site) will be used. Net returns to land and management based on a unit land area basis, with land units divided in equal portions depending on the rotation length (e.g. 2 portions for a 2-year rotation or 3 portions for a 3-year rotation) will be calculated without accounting for costs of land (e.g., rent or mortgage payments), management time (e.g., marketing), or possible federal subsidies, all of which are farm specific. Average net returns over time, as well as years with particularly stressful events (e.g. the 2012 drought) will be examined using the safety-first risk assessment model to examine extent to which more diverse rotations could mitigate risk.Obj 3: Evaluate how crop production risks are influenced by crop rotation length and identify significant gaps in our understanding of the mechanisms contributing to multiple facets of cropping system performanceThe Agricultural Production Systems Simulator (APSIM), a farming-systems modeling platform, including approximately 80 crop and soil models can simulate multiple production situations, including water, nitrogen, and/or phosphorus limited plant growth. It covers more than 30 crop species and can simulate crop rotations, weed competition, and grazing systems. Modeled soil processes include carbon, nitrogen, and phosphorus dynamics, greenhouse gas emissions (CO2 and N2O), water balance using simple (cascading approach) or comprehensive (Richards' equation) modules, and soil erosion.APSIM will be calibrated and validated with a subset of sites. Site characteristics will be used to establish simulations for individual experiments using up to half of the historical dataset to adjust default values of missing model parameters. The remaining portion of the dataset will be used to test and quantify model performance in specific cases. In cases where APSIM provides satisfactory model performance, these site-specific models will function as virtual representations of the experimental sites. Known as "computer experiments", or "emulators" in various fields these model representations will be used to inform a broader-scale analysis. Using a Bayesian framework weather files containing air temperatures, precipitation, and radiation from global climate models will be used in APSIM for fifty year simulations, providing system performance metrics over time and across variable weather patterns. Weather files will be generated and downscaled to a 1 km x 1 km area.To complement EI-based approaches in Objective 2, short-term APSIM projections will estimate full probability distributions for crop yields under weather scenarios for the coming season. Several probabilistic methodologies for this type of analysis will be used to compute the probabilities of crop failures and of high yield events, including: finite mixture models of normal distributions; Bayesian hierarchical modeling with priors driven by external weather projections; and multi-level hierarchical modeling for assessing shares of various risk components.

Progress 05/01/19 to 04/30/24

Outputs
Target Audience:Our primary target audience has been scientists conducting research related to crop rotations and cropping systems diversity, those concerned with provisioning of ecosystem services, and others interested in climate change impacts on cropping systems. A second audience has been policy experts who contribute to decisions about crop support programs within government and financial institutions. A third audience has been the commodity support groups who benefit from understanding how diverse cropping systems contribute to their members' profitability. The final target audience has been scientists and managers working with long-term research projects, where data collection, organization, and dissemination are critical for accomplishing project goals. Changes/Problems:Challenges faced initially were primarily administrative but also included impacts from the global COVID19 pandemic. Limited availability of agreements and HR staff support delayed establishment of the funding agreement and the postdoc hiring process for nearly a year. As a result, the CoPI who developed the Objective 3 approach took a position elsewhere leaving us with the need to find other postdocs to work on the project. The COVID19 pandemic slowed project progress as people were isolated and interactions were primarily via Zoom. The nature of this project allowed us to successfully deal with this challenge as the scientists in the core group are located in several states and remote interactions were anticipated. Interactions with the scientists at the cooperating locations were also carried out via Zoom. These challenges required two no cost extensions to complete the primary portion of the project. We would have benefited from an additional six months so as to complete website and database development using the remaining funds allocated for the project. Consequently, we are completing this work using ARS base funds.? What opportunities for training and professional development has the project provided?Training activities The main training efforts have focused on increased proficiency in data management and data analysis for the two postdocs. To this end, the two postdocs have received one-on-one training on Bayesian statistics from one of the project's PIs and through online educational tutorials. The proficiency they attained can be measured by the fact that they took the lead on the project's statistical modeling and analysis, developing an original data structure which resulted in stronger predictive performance and sharper uncertainty quantification for the models. The two postdocs increased their coding skills through self-study of R and Python coding. They also gained skills in data management by working to develop a data entry template to accommodate 20 diverse cropping systems studies. As often stated, this was not an undertaking for the faint of heart. A necessity to accompany the data entry template was a data dictionary to define various categories of data being added to the database. In creating the data dictionary, the postdocs received on the job training about regional differences in crop production practices. They gained grant proposal development experience as part of the DRIVES team developing the successful NIFA proposal to succeed this expiring grant. That grant was rated outstanding by the review panel. In addition, two undergraduates assisted with populating the databases and generating new data from a library of publications related to each study location. Finally, a computer science doctoral student was mentored by the post docs and increased her skills in data manipulation and quality control. Professional development Professional development opportunities have included workshops, professional conferences, individual and group study, and mentoring. Leadership opportunities have been provided and encouraged both inside and outside the project that also provided professional development. The two postdocs attended and presented research at the joint meeting of the American Society of Agronomy, the Crop Science Society of America, and the Soil Science Society of America in 2022 and 2023. One of the postdocs co-organized the "Long Term Experiments: Meeting Future Challenges Conference" at Rothamsted Experiment Station (England) in June 2023 and was invited to lead a workshop on acquisition and use of long-term research. The two postdocs increased their knowledge of cropping systems during preparation of manuscripts from the project and led development of the two manuscripts submitted using results from the project. The two postdocs have gained skills for leading large team collaborations (the larger collaborator network of DRIVES experiments) and smaller teams of scientists (core coPIs). They have developed project timelines, written descriptions of the project and made presentations (oral and poster). They worked together to develop a data sharing agreement to make the data collected within this project become publicly available in the future. Both have had opportunities to improve their personal and professional communication skills while working with the participating locations. The two post-docs also received training and mentorship in project management skills. They took courses related to managing teams and executing timelines. To this end, and by developing original team management strategies of their own, they have been able to manage a continent-wide network that brings together leaders/managers of LTEs, including the third oldest (1888) experiment in the world, and many of the foremost experiments in North America. How have the results been disseminated to communities of interest?Dissemination of our results has been mainly to the scientific community as described in theProducts sectionof this report. We have made presentations to various commodity groups and continue to seek out venues to share the results of the research. One notable outreach effort was our presentations at the 85thmeeting of the Association of Southeastern Biologists. Our presentations at this meeting extended outreach beyond the agriculture community as this meeting brings together botanists, ecologists, and biologists from the many institutions in the region. Our presence at the 2023 Rothamsted conference and the 2024 Agricultural Research Service's Long-Term Agroecosystem Research network (LTAR) Annual Science meeting helped us connect with other researchers working on networking long-term experiments. Thanks to interactions at the LTAR meeting, one of the LTAR site leads included DRIVES in an NSF proposal to cover meeting costs for a 2-year synthesis working group. If funded, this working group will foster collaborations among the LTAR network, the Long-Term Ecological Research network (LTER), and The Nutrient Network (NutNet). 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 NIFA funded project supported the creation of the Diverse Rotations Improve Valuable Ecosystem Services (DRIVES) Project, to assemble and use legacy data from North American Long-term agricultural field experiments (LTFEs) to address research questions about the multifunctionality of agriculture. The Network consists of United States Department of Agriculture (USDA), university, and International Maize and Wheat Improvement Center (CIMMYT) scientists (20+ people) who manage and collect primary data from LTFEs and a core team (DRIVERS, 9 scientists) who worked to organize the network, curate network data, and synthesize cross-network findings. The DRIVES Project has created a community of scientists who share experiences and generate research questions during bi-monthly meetings using various formats of brainstorming, breakout sessions, and mapping exercises. Many DRIVES collaborators knew each other or had worked together previously. One-on-one virtual meetings between collaborators established trust and a willingness to share data within the network. This trust was formalized with a data-sharing agreement, which is a contract detailing 1) expectations of how the DRIVES Project would use site data, 2) authorship guidelines, 3) what data would be shared by sites, and 4) the level of data access granted (e.g., available to the public or only to DRIVES researchers). Meetings are supplemented by bi-monthly email updates. This community serves as a valuable forum where experiential knowledge about managing LTFEs (e.g., obtaining funding, managing experimental treatments) can be shared. Under Objective 1, we far exceeded the goals of this objective by assimilating data from more than 20 long-term experiments (LTEs) in the U.S., Canada and Mexico. This number continues to expand with at least 2 additional experiments joining our efforts in 2024. The database containscrop yields, daily local weather station data, daily gridded weather data, planting and harvest dates, crop varieties, experiment designs, replicates, number of harvests, crop information, additional management treatments including preliminary specificationsof fertility and tillage treatments. Not yet organized but collected are data on soil organic carbon (SOC), bulk density, manure/carbon inputs.We have partnered with the Precision Sustainable Agriculture project to convert our initial database to a more permanent relational database structure and host this database on their website. Metadata for the experiments have been added to the Global Long-Term Experiments Network website hosted at Rothamsted, England. Most of the DRIVES' data were included in a manuscript 'Agrichange: fingerprinting the effects of global environmental change on agriculture using LTEs' that includes nearly 120 locations around the world. The existence and availability of the database was presented in an Agronomy Journal article (see products) that also serves as a recruitment tool for more LTEs. As of 2024, the DRIVES Project database contains 495 site-years of crop yields, daily weather, soil analysis, and management information. Under Objective 2, we met this goal with a groundbreaking publication using the assimilated DRIVES data to evaluate the effects of crop rotation diversity on output for individual crops and complete rotations. This allows us to quantify the portfolio effect and better understand benefits and trade-offs from diversification. The analysis used Bayesian statistics and evaluated environmental influences on outcomes.We explored multiple approaches to include environmental influences in our analysis, which led to the development of a new hypothesis that was included in our latest proposal funded by NIFA in 2024. This new funding ensures the DRIVES Project will continue through 2027. Some of the work on environmental influences is being incorporated into a manuscript which will be completedin late 2024. As we explained in our 2023 progress report, Objective 3 could not be fully accomplished due to the absence of one of the initial co-PIs who was to undertake evaluation of cropping system diversity with the APSIM model. We were fortunate enough to have Dr. Eunjin Han, from the ARS Adaptive Cropping Systems Laboratory (ACSL) join our team. Dr. Han is using process-based crop and soil models developed within ACSL to evaluate crop rotation systems performance with data from a limited set of locations in the DRIVES database. Dr. Han is evaluating how cropping system diversity impacts long-term soil properties and related hydrological processes. This will provide insights into how cropping systems responsesduring extreme weather years are related to water availability.

Publications

• Type: Conference Papers and Presentations Status: Accepted Year Published: 2024 Citation: Muller, K., Bybee-Finley, K. A, Bowles, T., Cavigelli, M., Han, E., Schomberg, H., Snapp, S., Viens, F., White, K.. (2024, May 21) The DRIVES Project: a network of long-term agricultural experiments to determine how diverse rotations improve valuable ecosystem services. Poster presented at LTAR Annual Meeting. Tuscon, AZ.
• Type: Conference Papers and Presentations Status: Accepted Year Published: 2024 Citation: Bybee-Finley, K. A and Muller, K. (2024, March) The DRIVES Project: Synthesizing and analyzing a network of legacy data for crop rotation diversity. Invited poster at the 85th Annual Meeting of the Association of Southeastern Biologists, Chattanooga, TN.
• Type: Conference Papers and Presentations Status: Accepted Year Published: 2024 Citation: Muller, K., Bybee-Finley, K. A, Bowles, T., Cavigelli, M., Han, E., Schomberg, H., Snapp, S., Viens, F., White, K.. (2024, May 20) Diverse Rotations Improve Valuable Ecosystem Services. Presented talk at Common Cropland Experiment Working Group. LTAR Annual Meeting. Tuscon, AZ.
• Type: Conference Papers and Presentations Status: Accepted Year Published: 2024 Citation: Muller, K. and Bybee-Finley, K. A. (2024, March) Crop rotational diversity as a climate adaptation strategy. Invited presentation at the 85th Annual Meeting of the Association of Southeastern Biologists, Chattanooga, TN.
• Type: Conference Papers and Presentations Status: Accepted Year Published: 2024 Citation: Bybee-Finley, K. A (2024, March) Crop rotation diversity enhances resilience of cropping systems under adverse conditions. Invited presentation at the Department of Soil and Crop Sciences at Colorado State University, Fort Collins, CO.
• Type: Conference Papers and Presentations Status: Accepted Year Published: 2024 Citation: Bybee-Finley, K. A. and Muller, K. (2024, March) The DRIVES Project: Synthesizing and analyzing a network of legacy data for crop rotation diversity. Invited presentation at the United States Department of Agriculture Long-term Agricultural Research Network March Meeting. Online.
• Type: Conference Papers and Presentations Status: Accepted Year Published: 2023 Citation: Bybee-Finley, K. A. and Muller, K. (2023, October) Benefits and tradeoffs of various metrics to quantify crop rotations. Paper presented at the ASA, CSSA & SSSA International Annual Meeting, St. Louis, MO.
• Type: Conference Papers and Presentations Status: Accepted Year Published: 2023 Citation: Muller, K., Bybee-Finley, K. A., White, K. (2023, October) A Case study on integrating and analyzing data from long-term agricultural experiments. Paper presented at the ASA, CSSA & SSSA International Annual Meeting, St. Louis, MO.
• Type: Journal Articles Status: Awaiting Publication Year Published: 2024 Citation: Bybee-Finley, K.A., Muller, K., White, K., Cavigelli, M., Han, E., Schomberg, H., Snapp, S., Viens, F., Correndo, A., Deiss, L., Fonteyne, S., Garcia y Garcia, A., Gaudin, A., Hooker, D., Jin, V., Johnson, G., Karsten, H., Liebman, M., McDaniel, M., Sanford, G., Schmer, M.R., Strock, J., Sykes, V., Verhulst, N., Wilke, B., Bowles, T. Rotation-level yield is greater with increased rotational complexity under poor growing conditions. One Earth.
• Type: Journal Articles Status: Accepted Year Published: 2024 Citation: Bybee-Finley, K.A., Muller, K., White, K., Bowles, T., Cavigelli, M., Schomberg, H., Snapp, S., Viens, F. Deriving general principles of agroecosystem multifunctionality with the Diverse Rotations Improve Valuable Ecosystem Services (DRIVES) Network. Agronomy Journal.
• Type: Conference Papers and Presentations Status: Accepted Year Published: 2023 Citation: Bybee-Finley, K. A., Muller, K., Bowles, T., Cavigelli, M., Han, E., Schomberg, H., Snapp, S., Viens, F., White, K. (2023, October) Rotation-level yield is greater with increased rotational complexity under poor growing conditions in a network of long-term cropping systems experiments. Paper presented at the ASA, CSSA & SSSA International Annual Meeting, St. Louis, MO.

Progress 05/01/22 to 04/30/23

Outputs
Target Audience:In the reporting period for2022-2023we reached target audiences of undergraduate and graduate students through departmental seminars at Michigan State University and Cornel. We also reached target audiences of scientists and policy personnel at the ASA-CSSA-SSSA meetings in Baltimore, MDand at the ARS Long-term Agricultural Research Network annual meeting. These efforts were through poster and oral presentations. An oral presentation on the project was made to the general scientific community at the ARS Beltsville Agricultural Research Center and followed up with an in-depth discussion of the project with Sarah Beebout of the ARS National Program Staff. Changes/Problems:The approach described in the proposal for Objective 3 will not be fully accomplished due to the absence of co-PI Dr. Renea Dietzel. She was to apply theAPSIM cropping systems modelto evaluate crop rotation responses to future climate scenarios. Model output would have been used toassessproducer risk to climate change. We have incorporated into our work onobjective 2assessment of producer risk within current climate conditions. In addition, we focused on developing/refiningindices used to characterize diversity of crop / plant components. We found that the widely used Simpson's index is not adequate for describingagricultural cropping systems diversity and explored alternative indices. Similarly, some of the environmental indices appear to be inadequate for fully identifying environmental conditions. We believe our efforts to present alternative approaches of these indices will be broadly valuable to the scientific community. We are using these findings to guide our future efforts in understanding crop rotation responses to complexity and environment. In addition, Dr. Eunjin Han, who is with the ARS Adaptive Cropping Systems Laboratory (ACSL)joined the project to do some cropping systems modeling. She will be using models developed within ACSL to evaluate crop rotation system performance for a limited set of locations. Her interest is in evaluating cropping system complexityimpacts on soil water use. This will provide us insights into how the cropping systems repones during extreme weather years can be attributed to water availability. What opportunities for training and professional development has the project provided?The two post-doctoral participants in the project have been provided opportunities to develop leadership and networking skills. ABF, was invited to participate in the development of a workshop on acquisition and use of long-term research data which was held at Rothamsted Experiment Station (England) during June 2023. Both Post docs are leading development of manuscripts to present results of the project.Two undergraduates assisted with populating the databases and generating new data from a library of publications related to each study location. A doctoral student in CS was provided an opportunity to increase her skills in data base manipulation and development. How have the results been disseminated to communities of interest?Presentations have been made at professional meetings. Manuscripts are in the final stages of preparation and will be submitted to journals in the summer of 2023. What do you plan to do during the next reporting period to accomplish the goals?We will complete objective 2 and address additional questions related to components of objective 3 using the same approach as in objective 2. We plan to submit 3 to 5 manuscripts by the winter of 2024. Additional data on soils from the 20 locations will be added to the data base. A user interface to the database will be developed to provide collaborators access to the data for further analyses. Meta information for all locations will be added to the GLten (Global Long-term Experiments Network) data base website using the meta information from the DRIVES database. The meta information for each location will be added to the DRIVES web portal on the AGCROS platform. We will also develop a manuscript to submit to Data In Brief to point to the various locations where the data will be accessible.

Impacts
What was accomplished under these goals? Objective 1: A majority of the data from the 20 locations has been accumulated, vetted, and placed in the relational data base. Significant progress was made toward meeting the goals of objective 2 and partially for objective 3. We are using Bayesian statistical approaches to evaluate rotational complexity effects on cropping systems responses. To that end, we completed over 100 model iterations to assess yield and yield stability of specific crops and at the whole rotation-level, incorporated site-specific management categories into the analyses, and evaluated a diversity index, proportion cover, and their combination to determine management effects. A manuscript is in the final stage of preparation for submission.

Publications

• Type: Conference Papers and Presentations Status: Published Year Published: 2022 Citation: Bybee-Finley, K. A., Muller, K., Bowles, T., Cavigelli, M., Han, E., Schomberg, H., Snapp, S., Viens, F., White, K. (2022, November) The DRIVES Network: Combining long-term experiments to quantify ecosystem services from diverse cropping systems. Poster presented at the ASA, CSSA & SSSA International Annual Meeting, Baltimore, MD.
• Type: Conference Papers and Presentations Status: Published Year Published: 2022 Citation: Bybee-Finley, K. A., Muller, K., Bowles, T., Cavigelli, M., Han, E., Schomberg, H., Snapp, S., Viens, F., White, K. (2022, November) Role of rotational complexity on yield and yield stability. Paper presented at the ASA, CSSA & SSSA International Annual Meeting, Baltimore, MD.
• Type: Other Status: Other Year Published: 2022 Citation: Bybee-Finley, K. A. (2022, November) DRIVES Project: Public database of long-term experiments focused on understanding the role of rotational complexity. Beltsville Agricultural Research Center, Beltsville, MD.
• Type: Other Status: Other Year Published: 2022 Citation: Giving a second-life to long-term agroecosystem experiments, Katherine Muller, Presentation to Horticulture Department, Cornell University. October 4 2022.
• Type: Conference Papers and Presentations Status: Published Year Published: 2022 Citation: Muller, K. E., & Bybee-Finley, K. A. (2022) The Drives Network: Combining Long-Term Experiments to Quantify Ecosystem Services from Diverse Cropping Systems. [Abstract]. ASA, CSSA, SSSA International Annual Meeting, Baltimore, MD. https://scisoc-aws.confex.com/scisoc/2022am/meetingapp.cgi/Paper/143180

Progress 05/01/21 to 04/30/22

Outputs
Target Audience:In FY2021 we reached target audiences of undergraduate and graduate students through departmentalseminars at Michigan State University and Cornel. We also reached target audiences of scientists and policy personnel at the ASA-CSSA-SSA meetings held virtually and at the ARS Long-term Agricultural Research Network annual meeting. These efforts were through poster and oral presentations. Changes/Problems:We were slow to implement the project due to problems with establishing the agreement and hiring postdocs. At this point our full team is in place and good progress has been made in the past 6 months. COVID19 has limited our ability to engage in one-on-one interactions, but use of zoom and other on-line media has helped overcome some of those limitations. One of our core Co-PIs (Dr. Snapp) has taken a position at CYMMT for 2 years which will have some impact on our interactions with her. Our team is fully committed to make significant progress in the coming year. We applied for an received a one-year no cost extension. We may need to do this again or at least a 6-month extension to complete all project objectives. What opportunities for training and professional development has the project provided?The two post-docs working on the project have gained skills of leading a large team of collaborators, communicating clearly with this team both as a group and in one-on-one sessions with each location. The Lead Post Doc- ABF, has developed leadership skills for the smaller team of scientists, two post-docs, and an undergraduate. She has developed project timelines, written descriptions of the project and made presentations (oral and poster). She has recruited new participants. TShe led the development and implementation ofa data sharing agreement to make the data collected within this project become publicly available in the future. Our Data Management Post Doc has developed her data base management skills and communication skills while working with the participating locations. She has also had an opportunity to develop communication skills through formal presentations within and outside the group.Our undergraduate intern has had opportunities to learn about the research process, data base management, compiling literature and extracting information from that literature that describes the meta and real data from the multiple locations involved in the project. How have the results been disseminated to communities of interest?We have no results to diseminate as of this report. However we have engauged a large number of people in our outreach efforts to engage additional locations with the project. What do you plan to do during the next reporting period to accomplish the goals?We will complete the steps needed to analyze the assembled data and write the first publication related to the effects of crop rotation on system performance. We will continue to assimilate new data on variables beyond crop yield and biomass so that we can explore environmental and management factors influencing yield stability in diverse crop rotations.We will expand the number of locations participating in the project. We will continue disseminating results to the scientific community. We will engage with collaborators from European institutions with a similar interest to apply models developed by both groups to determine rotational responses and their causes.

Impacts
What was accomplished under these goals? The following information was listed in prevous entries but is summarized here: In this past year, we held five participatory meetings with collaborating sites in which we shared project goals, generated hypotheses, and discussed the intricacies of managing long-term experiments. We created the structure for a relational database for ecosystem services data from sites, focusing on elements pertaining to rotational diversity. We have built a citation database which contains publications from each site and organized reported agronomic management of cropping systems. We have generated a sample dataset using crop yield and weather data from five sites for exploratory data analysis. Finally, we have given presentations about the DRIVES Project efforts to several organizations, including Dept of Soil and Crop Sciences at Cornell University, the Center for Global Change & Earth Observations at Michigan State University, and the Sustainable Intensification Community at ASA-CSSA-SSSA Annual Meeting.We are in the final stages of preparing the DRIVES yield dataset targeted for the project's first publication. This publication will establish the group within the cropping systems science community and provide an opportunity to increase the impact of your site's data.

Publications

• Type: Conference Papers and Presentations Status: Published Year Published: 2021 Citation: Bybee-Finley, K. A., Muller, K., Bowles, T., Cavigelli, M., Schomberg, H., Snapp, S., Viens, F., White, K. (2021, November) DRIVES: A collaborative longitudinal and spatial study of rotational crop diversity and its value. Poster presented at the ASA, CSSA & SSSA International Annual Meeting, Salt Lake City, UT.
• Type: Other Status: Other Year Published: 2021 Citation: Snapp, S. and Bybee-Finley, K. A. (2021, December) Learning about agricultural resilience - emerging approaches. Center for Global Change and Earth Observations, Michigan State University, Lansing, MI.
• Type: Other Status: Other Year Published: 2022 Citation: Bybee-Finley, K. A. (2022, January) Advances in crop diversification strategies to enhance resilience. Department of Plant, Soil, and Microbial Sciences Seminar Series, Michigan State University, Lansing, MI.

Progress 05/01/20 to 04/30/21

Outputs
Target Audience: Nothing Reported Changes/Problems:Our major setback has been in processing the agreement and identifying personnel to complete the project. Hiring process through HR has been cumbersome with my delaysthat were unexpected. We believe that most of those hurdles have been overcome and we will be making good progress on the research in the coming year. What opportunities for training and professional development has the project provided?We will be training one post-doc in the coming years. 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?As stated above we will have personnel in place to address all three objectives. Under objective 1. we will build a data base structure and begin populating it with data from the 13 cooperating locations. Data base quires will be developed for accessing the data. Under objective 2. we will begin exploring data from 3 to 5 locations to develop the models needed to analyze data from all 13 locations. We will also begin interactions with Risk Management Agency to identify any customer needs they mayhave in relation to our risk analysis, Objective 3 will be addressed in the following year.

Impacts
What was accomplished under these goals? Due to problems with hiring, we are just now ready to begin addressing the objectives in this proposal. We have identified and started the hiring of a post-doc to address objectives 2 and 3. We also have identified one of two data managers to address objective 1. We believe that the project will be well underway by early summer.

Publications

Progress 05/01/19 to 04/30/20

Outputs
Target Audience: Nothing Reported Changes/Problems:Hiring of the data manager and post-doc has been hendered due to a backlog of positions being processed through ARS HR. Currently the post-doc position is being recriuited and the Data manger positon is being processed through the HR system. We hope to begin recruiting for that position early summer. What opportunities for training and professional development has the project provided? Nothing Reported 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 hire the post doc and data manager. Once hired they will begin to accumulate the data necessary for meeting the goals outlined in the three objectives. The primary focus for the next year will be in creating the common data base for shareing data across locations.

Impacts
What was accomplished under these goals? The initiation of the project has been delayed as we search for a post-doc and data manager who will be responsible for conducting the majority of the work.

Publications