Environmental factors function as constraints on soil nitrous oxide fluxes in bioenergy feedstock cropping systems. Issue 2 (25th October 2018) - Duncan, David S.; Oates, Lawrence G.; Gelfand, Ilya; Millar, Neville; Robertson, G. Philip; Jackson, Randall D.
Abstract: Nitrous oxide (N2 O) is a potent greenhouse gas and major component of the net global warming potential of bioenergy feedstock cropping systems. Numerous environmental factors influence soil N2 O production, making direct correlation difficult to any one factor of N2 O fluxes under field conditions. We instead employed quantile regression to evaluate whether soil temperature, water‐filled pore space (WFPS), and concentrations of soil nitrate ( NO 3 − ) and ammonium ( NH 4 + ) determined upper bounds for soil N2 O flux magnitudes. We collected data over 6 years from a range of bioenergy feedstock cropping systems including no‐till grain crops, perennial warm‐season grasses, hybrid poplar, and polycultures of tallgrass prairie species each with and without nitrogen (N) addition grown at two sites. The upper bounds for soil N2 O fluxes had a significant and positive correlation with all four environmental factors, although relatively large fluxes were still possible at minimal values for nearly all factors. The correlation with NH 4 + was generally weaker, suggesting it is less important than NO 3 − in driving large fluxes. Quantile regression slopes were generally lower for unfertilized perennials than for other systems, but this may have resulted from a perpetual state of nitrogen limitation, which prevented other factors from being clear constraints. This framework suggests efforts to reduce concentrations of NO 3 − in the soil may be effective at reducing high‐intensity periods—"hot moments"—of N2 O production. Abstract : Quantile regression between soil N2 O fluxes and environmental parameters. Lines indicate the quantile regression relationship between parameters at τ = 0.95, approximately reflecting the relationship that determines the 95th percentile of fluxes. Regressions were calculated independently for each environmental parameter. Flux data and soil inorganic N concentration data were inverse hyperbolic sine (IHS) transformed for regression and are presented on a transformed scale. Individual observations are partially transparent to illustrate observation density. All slope and intercept terms were significant at p < 0.05.