Abstract The transition from conventional to more regenerative cropping systems can be economically risky due to variable transition period yields and unforeseen costs. We compared yields and economic returns for the first 3 years of the transition from a business as usual (BAU) conventional corn (Zea mays)–soybean (Glycine max) rotation to an aspirational (ASP) five‐crop (corn‐soybean‐winter wheat [Triticum aestivum]–winter canola [Brassica napus]‐forage) rotation in the Upper Midwest United States. Regenerative ASP cropping practices included the more diverse crop rotation, continuous no‐till, cover crops, precision inputs, and livestock (compost) integration. For the first two transition years, BAU corn yields were 8%–12% higher than ASP while in the third transition year, BAU corn yields were 5% lower. Soybean yields were similar for the first 2 years but higher in BAU in the third year due to an ASP pest outbreak. Equivalent yields for other ASP crops were lower than BAU in the first 2 years but similar in the third year except for canola, which suffered from slug damage. Whole‐system economic returns narrowed across years; by year three, whole system comparisons for the ASP corn and soybean entry points (corn‐soybean‐wheat and soybean‐wheat‐canola, respectively) showed equivalent economic returns for BAU and ASP, despite yield differences, owing largely to the ASP system's reduced operational costs. Overall findings suggest that early regenerative systems can be as profitable as conventional systems with careful attention to rotation entry points and inputs. 
                        more » 
                        « less   
                    
                            
                            The LTAR Cropland Common Experiment at the Kellogg Biological Station
                        
                    
    
            Abstract The Kellogg Biological Station Long‐term Agroecosystem Research site (KBS LTAR) joined the national LTAR network in 2015 to represent a northeast portion of the North Central Region, extending across 76,000 km2of southern Michigan and northern Indiana. Regional cropping systems are dominated by corn (Zea mays)–soybean (Glycine max) rotations managed with conventional tillage, industry‐average rates of fertilizer and pesticide inputs uniformly applied, few cover crops, and little animal integration. In 2020, KBS LTAR initiated the Aspirational Cropping System Experiment as part of the LTAR Common Experiment, a co‐production model wherein stakeholders and researchers collaborate to advance transformative change in agriculture. The Aspirational (ASP) cropping system treatment, designed by a team of agronomists, farmers, scientists, and other stakeholders, is a five‐crop rotation of corn, soybean, winter wheat (Triticum aestivum), winter canola (Brassicus napus), and a diverse forage mix. All phases are managed with continuous no‐till, variable rate fertilizer inputs, and integrated pest management to provide benefits related to economic returns, water quality, greenhouse gas mitigation, soil health, biodiversity, and social well‐being. Cover crops follow corn and winter wheat, with fall‐planted crops in the rotation providing winter cover in other years. The experiment is replicated with all rotation phases at both the plot and field scales and with perennial prairie strips in consistently low‐producing areas of ASP fields. The prevailing practice (or Business as usual [BAU]) treatment mirrors regional prevailing practices as revealed by farmer surveys. Stakeholders and researchers evaluate the success of the ASP and BAU systems annually and implement management changes on a 5‐year cycle. 
        more » 
        « less   
        
    
                            - Award ID(s):
- 2224712
- PAR ID:
- 10576966
- Author(s) / Creator(s):
- ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; more »
- Publisher / Repository:
- Wiley Blackwell (John Wiley & Sons)
- Date Published:
- Journal Name:
- Journal of Environmental Quality
- Volume:
- 53
- Issue:
- 6
- ISSN:
- 0047-2425
- Format(s):
- Medium: X Size: p. 893-903
- Size(s):
- p. 893-903
- Sponsoring Org:
- National Science Foundation
More Like this
- 
            
- 
            Dataset Abstract This dataset includes information about the LTER main site treatments, agronomic practices carried out on the treatments and approved site use requests. Most long-term hypotheses associated with the KBS LTER site are being tested within the context of the main cropping systems study. This study was established on a 48 ha area on which a series of 7 different cropping systems were established in spring 1988, each replicated in one of 6 ha blocks. An eighth never-tilled successional treatment, is located 200 m off-site, replicated as four 0.06 ha plots. Cropping systems include the following treatments: T1. Conventional: standard chemical input corn/soybean/wheat rotation conventionally tilled (corn/soybean prior to 1992) T2. No-till: standard chemical input corn/soybean/wheat rotation no-tilled (corn/soybean prior to 1992) T3. Reduced input: low chemical input corn/soybean/wheat rotation conventionally tilled (ridge till prior to 1994) T4. Biologically based: zero chemical input corn/soybean wheat rotation conventionally tilled (ridge till prior to 1994) T5. Poplar: Populus clones on short-rotation (6-7 year) harvest cycle T6. Alfalfa: continuous alfalfa, replanted every 6-7 years (converted to switchgrass in 2018) T7. Early successional community: historically tilled soil T8. Mown grassland community: never-tilled soil. For specific crops in a given year see the Annual Crops Summary Table. In 1993 a series of forest sites were added to the main cropping system study to provide long-term reference points and to allow hypotheses related to substrate diversity to be tested. These include: TCF. Coniferous forest: three conifer plantations, 40-60 years old TDF. Decidious forest: three deciduous forest stands, two old-growth and one 40-60 years post-cutting TSF. Mid-successional forest: three old-field (mid-successional) sites 40+ years post-abandonment. All share a soil series with the main cropping system treatments, and are within 5 km of all other sites. For each system (and for a number of microplot treatments nested within the main treatment plots) the following baseline variates are being measured (described in greater detail in other data set descriptors): plant characteristics, including species distributions and abundances, net aboveground productivity by functional group (crop vs. non dominant biomass, selected non dominant biomass), economic yields, tissue C and N contents, seed bank composition; soil chemical and physical characteristics, including soil moisture, pH, inorganic N and P pools, total C, N, and P pools, bulk density; soil biological characteristics, including microbial biomass C and N, N mineralization rates (buried bags), microbial populations, invertebrate populations; and insect and pathogen dynamics, including distributions and abundances of major insect pests and predators and of Fusarium pathogens. original data source http://lter.kbs.msu.edu/datasets/7more » « less
- 
            Soil nitrous oxide (N2O) emissions exhibit high variability in intensively managed cropping systems, which challenges our ability to understand their complex interactions with controlling factors. We leveraged 17-years (2003-2019) of measurements at the Kellogg Biological Station LTER/LTAR site to better understand controls of N2O emissions in four corn–soybean–winter wheat rotations employing Conventional, No-till, Reduced input, and Biologically-based/organic inputs. We used a Random Forest machine learning model to predict daily N2O fluxes, trained separately for each system with 70% of observations, using variables such as crop species, daily air temperature, cumulative 2-day precipitation, water-filled pore space, and soil nitrate and ammonium concentrations. The model explained 29 to 42% of daily N2O flux variability in test data, with greater predictability for the corn phase in each system. The long-term rotations showed different controlling factors and threshold conditions influencing N2O emissions. In the Conventional system, the model identified ammonium (>15 kg N ha-1) and daily temperature (>23 °C) as the most influential variables; in the No-till system, climate variables, precipitation, and temperature were important variables. In low input and organic systems, where red clover (Trifolium repens L.; before corn) and cereal rye (Secale cereale L.; before soybean) cover crops were integrated, nitrate was the predominant variable, followed by precipitation and temperature. In low input and biologically-based systems, red clover residues increased soil nitrogen availability to influence N2O emissions. Long-term data facilitated machine learning for predicting N2O emissions in response to differential controls and threshold responses to management, environmental, and biogeochemical drivers.more » « less
- 
            Abstract Soil nitrous oxide (N2O) emissions exhibit high variability in intensively managed cropping systems, which challenges our ability to understand their complex interactions with controlling factors. We leveraged 17 years (2003–2019) of measurements at the Kellogg Biological Station Long‐Term Ecological Research (LTER)/Long‐Term Agroecosystem Research (LTAR) site to better understand the controls of N2O emissions in four corn–soybean–winter wheat rotations employing conventional, no‐till, reduced input, and biologically based/organic inputs. We used a random forest machine learning model to predict daily N2O fluxes, trained separately for each system with 70% of observations, using variables such as crop species, daily air temperature, cumulative 2‐day precipitation, water‐filled pore space, and soil nitrate and ammonium concentrations. The model explained 29%–42% of daily N2O flux variability in the test data, with greater predictability for the corn phase in each system. The long‐term rotations showed different controlling factors and threshold conditions influencing N2O emissions. In the conventional system, the model identified ammonium (>15 kg N ha−1) and daily air temperature (>23°C) as the most influential variables; in the no‐till system, climate variables such as precipitation and air temperature were important variables. In low‐input and organic systems, where red clover (Trifolium repensL.; before corn) and cereal rye (Secale cerealeL.; before soybean) cover crops were integrated, nitrate was the predominant predictor of N2O emissions, followed by precipitation and air temperature. In low‐input and biologically based systems, red clover residues increased soil nitrogen availability to influence N2O emissions. Long‐term data facilitated machine learning for predicting N2O emissions in response to differential controls and threshold responses to management, environmental, and biogeochemical drivers.more » « less
- 
            Abstract Agricultural researchers are increasingly encouraged to engage with stakeholders to improve the usefulness of their projects, but iterative research on the design and assessment of stakeholder engagement is scarce. The USDA Long‐Term Agroecosystem Research (LTAR) Network recognizes the importance of effective engagement in increasing the utility of information and technologies for future agriculture. Diverse stakeholders and researchers at the Kellogg Biological Station (KBS) LTAR site co‐designed the KBS LTAR Aspirational Cropping System Experiment, a process that provides a testing ground and interdisciplinary collaborations to develop theory‐driven assessment protocols for continuous stakeholder engagement. Informed by prior work, we designed an assessment protocol that aims to measure participant preferences, experiences, and perceived benefits at various stages of this long‐term project. Two online surveys were conducted in 2021 and 2022 among participants of LTAR engagement events at KBS, using a pre‐post design, resulting in 125 total responses. Survey respondents had positive perceptions of the collaboratively designed research experiment. They had a strong expectation that the research would generate conservation and environmental advances while also informing policy and programs. Respondents also indicated a desire to network with other stakeholders. The research team noted the significant role of a long‐term stakeholder engagement specialist in inviting participants from diverse backgrounds and creating an open and engaging experience. Overall, results highlight an interdisciplinary path of intentional and iterative engagement and evaluation to build a program that is adaptive and responsive to stakeholder needs.more » « less
 An official website of the United States government
An official website of the United States government 
				
			 
					 
					
