|Davis, Brian - University Of Maryland|
|Needelman, Brian - University Of Maryland|
|Yarwood, Stephanie - University Of Maryland|
|Bagley, Gwendolyn - University Of Maryland|
Submitted to: Journal of Environmental Quality
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 12/9/2016
Publication Date: 12/19/2016
Citation: Davis, B.W., Mirsky, S.B., Needelman, B.A., Cavigelli, M.A., Yarwood, S.A., Maul, J.E., Bagley, G.A. 2016. A novel approach to estimating nitrous oxide emissions during wetting events from single-timepoint flux measurements. Journal of Environmental Quality. 46:247-254.
Interpretive Summary: Achieving high corn yields generally requires substantial nitrogen inputs. Application of nitrogen to soils accounts for 69% of US emissions of nitrous oxide (N2O), a greenhouse gas with 298 times the global warming potential of carbon dioxide that is also the dominant anthropogenic stratospheric ozone-depleting substance. Mitigating N2O production requires that we better understand the impacts of various agricultural management regimes on emissions. However, a lack of uniformity in greenhouse gas sampling methodologies constrains our ability to compare results among studies. Sampling frequency is particularly variable (manually sampling on a daily basis is cost prohibitive) and methods of interpolating of fluxes between sampling events have not been well studied. Therefore, we conducted an experiment that reflects many of the typical soil and fertility management practices used in field corn production. Since nitrous oxide emissions corresponds with fertilization and precipitation events, we conducted intensive sampling events following soil wetting events at select growth stages of corn to better elucidate the pattern of gas flux as a function of soil conditions at different corn growth stages. This work allowed us to develop models that extrapolate nitrous oxide flux across a seven day period of time as a function of nitrous oxide flux two days after initiation of an emissions event. Our results provide a method to target sample timing relative to soil wetting events and to interpolate emissions for seven days following each event. These results will help researchers develop standard methods for sampling frequency and extrapolating gas flux from select sampling events.
Technical Abstract: Precipitation and irrigation induce pulses of N2O emissions in agricultural soils, but the magnitude, duration, and timing of these pulses remain uncertain. This uncertainty makes it difficult to accurately extrapolate emissions from unmeasured time periods using static chambers sampled manually. Furthermore, little is known about how fertility treatments and cover crop management influence these pulses. Therefore, we developed a protocol to predict N2O emissions using a model derived from data collected daily for 7 d following wetting events. Within a cover crop-based corn (Zea mays L.) production system in Beltsville, MD, we conducted the 7 d time series during four time periods representing a range of corn growth stages in both 2013 and 2014. Treatments included mixtures and monocultures of grass and legume cover crops that were fertilized with pelletized poultry litter or UAN, 9 276 kg N ha 1. Most gas flux time series did not exhibit expected exponential decay over time (82%); therefore, cumulative emissions were calculated using trapezoidal integration over 7 days following the wetting event. We observed a wide range of fluxes ( 9.33 to 2940 g N2O N ha 1 d 1) and cumulative 7-d emissions ( 7.40 to 9080 g N2O N ha 1 week 1). Cumulative 7-d emissions were well-correlated with single point gas fluxes on the second day following a wetting event using a generalized linear mixed model (ln[emissions]=0.809·ln[flux]+2.47). Soil chemical covariates prior to or following a wetting event were weakly associated with induced cumulative emissions. The ratio of dissolved organic carbon to total inorganic nitrogen was negatively correlated with cumulative emissions (R2=0.23 0.29), while nitrate was positively correlated with cumulative emissions (R2=0.23 0.33). Our model is an innovative approach that is calibrated using site-specific time series data, which may then be used to estimate short-term N2O emissions following wetting events using only a single flux measurement.