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 (
- Award ID(s):
- 1832042
- PAR ID:
- 10357092
- Publisher / Repository:
- Environmental Data Initiative
- Date Published:
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
more » « less
Abstract Trifolium repens L.; before corn) and cereal rye (Secale cereale L.; 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. -
Dataset AbstractThis data set contains information about agronomic yields for the Main Cropping System Experiment which include treatments 1-4 (corn – wheat – soybean rotations) and after 1994 treatment 6 (alfalfa). Agronomic yields are measured during normal crop harvest; yields are determined by machine harvesters appropriate to each crop as described in the Agronomic protocol.original data source http://lter.kbs.msu.edu/datasets/23more » « less
-
null (Ed.)With over 65% of agronomic crops under no-till in Pennsylvania, herbicides are relied on for weed management. To lessen the environmental impact and selection pressure for herbicide resistance, we conducted a nine-year experiment to test herbicide reduction practices in a dairy crop rotation at Rock Springs, PA. The rotation included soybean (Glycine max L.) – corn (Zea mays L.) - 3-year alfalfa (Medicago sativa L.) - canola (Brassica napus L.). The following practices were used to reduce herbicide inputs: i. banding residual herbicides over corn and soybean rows and using high-residue inter-row cultivation; ii. seeding a small grain companion crop with alfalfa; iii. plowing once in six years to terminate the perennial forage. These practices were compared with standard herbicide-based weed management (SH) in continuous no-till. We hypothesized: i. There would be more weed biomass in the reduced herbicide treatment (RH), ii. leading to more weeds in RH over time, but iii. the added weed pressure would not affect yield iv. or differences in net return. We sampled weed biomass in soybean, corn, and the first two forage years. In corn and soybean, weed biomass was often greater in RH than SH and increased over the years in the RH treatments. In the forage, weed biomass did not always differ between treatments. Yield and differences in net return were similar in most crops and years. Results suggest that weed management with reduced herbicide inputs supplemented with an integrated approach can be effective but may lead to more weeds over time.more » « less
-
more » « less
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
These data are soil, CO2 efflux, dissolved organic carbon leaching, and various other measures from a mesocosm experiment performed in long-term (12-years) crop diversity experiment near Hickory Corners, MI, United States.Briefly, we tracked dual-labelled (13C and 15N), isotopically enriched wheat (Triticum aestivum) residue in situ for two years as it decomposed in three agroecosystems: maize-soybean rotation (CS), maize-soybean-wheat plus red clover and cereal rye cover crops (CSW2), and spring fallow management with regeneration of natural grassland species (7-10 species; SF). We measured losses of wheat residue (Cwheat and Nwheat) in leached soil solution and greenhouse gas fluxes, as well as how much was recovered in microbial biomass and bulk soil at 5-cm increments down to 20 cm.
COLLECTION INFORMATION:
- Time period(s): 2011 to 2013
- Location(s): Hickory Corners, MI, United States
- Long-term Experiment: Cropping Biodiversity Gradient Experiment
- Further Site Information: https://lter.kbs.msu.edu/research/long-term-experiments/biodiversity-gradient/
