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The attribution of N2O emission factors to N inputs from chemical fertilizers requires an understanding of how those inputs affect the biological processes from which these emissions are generated. We propose a detailed model of soil N transformations as part of the ecosystem model ecosys for use in attributing N2O emission factors to fertilizer use. In this model, the key biological processes—mineralization, immobilization, nitrification, denitrification, root, and mycorrhizal uptake—controlling the generation of N2O were coupled with the key physical processes—convection, diffusion, volatilization, dissolution—controlling the transport of the gaseous reactants and products of these biological processes. Physical processes controlling gaseous transport and solubility caused large temporal variation in the generation and emission of N2O in the model. This variation limited the suitability of discontinuous surface flux chambers measurements used to test modeled N2O emissions. Continuous flux measurements using micrometeorological techniques were better suited to the temporal scales at which variation in N2O emission occurred and at which model testing needed to be conducted. In a temperate, humid climate, modeled N2O emissions rose nonlinearly with fertilizer application rate once this rate exceeded the crop and soil uptake capacities for added N. These capacities were partly determined by history of fertilizer use, so that the relationship between N2O emissions and current N inputs depended on earlier N inputs. A scheme is proposed in which N2O emission factors rise nonlinearly with fertilizer N inputs that exceed crop plus soil N uptake capacities.

Nitrous oxide fluxes from soils are inherently variable in time and space. An improved understanding of this variability is needed to make accurate estimates of N2O fluxes at a regional scale. The objectives of this work were to (i) characterize the influence of soil–landscape combinations and N application rates on N2O emissions and to (ii) determine the contribution of these influences on the estimation of N2O emissions at the field scale. We used static chambers and gas chromatography methods to measure N2O fluxes and collected ancillary data (mineral N, water soluble C, soil water content, soil temperature) in Canada at Mundare (AB) in the aspen parkland ecoregion and at Swift Current (SK) in the short‐grass prairie ecoregion. At Mundare, measurements were taken in 1995 and 1996 by landscape position and land use. At Swift Current, data were collected in 1999 and 2000 by landscape position and N rate. At Mundare, landscape position affected N2O emissions but the pattern varied seasonally. During a 46‐d period in summer 1995, a flux of 430 g N2O‐N ha−1 measured in a backslope was greater than the 60 g N2O‐N ha−1 measured on average in shoulder and depressional areas. The flux pattern changed during a 43‐d spring thaw of 1996 when fluxes from depressional areas were greatest (1710 g N2O‐N ha−1). Nitrous oxide emissions from natural areas were small. The emission pattern during summer 1996 was similar to that of 1995 but the fluxes were an order of magnitude larger. At Swift Current, N2O fluxes in summer 1999 were affected by topography and N rate. Fluxes were greatest in depressional areas receiving N at 110 kg ha−1 (3140 g N2O‐N ha−1). Use of the area fraction occupied by each landscape position to calculate N2O flux increased the estimates of N2O fluxes at the field scale in five out of six cases. Further research of N2O fluxes in variable landscapes should help elucidate factors controlling N2O fluxes from pedon to field scale and thus translate into improved flux estimates at regional scales.

a b s t r a c tThe timing of seedling emergence greatly affects growth and yield of wheat (Triticum aestivum L.) and a good growth model should predict it accurately. The Cropping System Model of the Decision Support System for Agrotechnology Transfer (DSSAT-CSM) is used worldwide for many different applications, but its simulation of the timing of seedling emergence of wheat is not satisfactory under certain circumstances. In order to improve the prediction of seedling emergence, we incorporated a newly developed non-linear model, the Beta model, into DSSAT-CSM. Simulation performances were tested using observations in spring wheat (cv. Thatcher) from 24 sites across North America over the period 1930-1954, which totalled 244 site-years. Observed days from sowing to 50% seedling emergence (DSE) ranged from 5 to 39. The DSSAT-CSM model underestimated DSE in most cases. The Beta model using daily air temperature markedly improved prediction of seedling emergence. When using hourly air temperature, the Beta model generally resulted in predictions similar to when daily air temperature was used. However, calculated hourly temperature improved the simulation when the daily air temperature was near the base temperature for germination/emergence. When temperature was adjusted using a DSSAT-CSMcalculated soil moisture factor for germination/emergence (WFGE), the prediction was not improved, which could be related to the inaccurate simulation of near-surface soil moisture and the calculation of WFGE. The performance of the Beta model using soil temperature at sowing depth was not as good as simulations using air temperature, suggesting that the simulated soil temperature might not have been accurate. To further improve the prediction it is necessary to improve the simulation of near-surface soil moisture and temperature and the calculation of WFGE. Further work could also be done to simulate the dynamics of seedling emergence.

Estimating storm erosion with a rainfall simulator. Can. J. Soil Sci. 77: 669-676. Interpreting soil loss from rainfall simulators is complicated by the uncertain relationship between simulated and natural rainstorms. Our objective was to develop and test a method for estimating soil loss from natural rainfall using a portable rainfall simulator (1 m 2 plot size). Soil loss from 12 rainstorms was measured on 144-m 2 plots with barley residue in conventional tillage (CT), reduced tillage (RT) and zero tillage (ZT) conditions. A corresponding "simulated" soil loss was calculated by matching the simulator erosivity to each storm's erosivity. High (140 mm h -1 ) and low (60 mm h -1 ) simulation intensities were examined. The best agreement between simulated and natural soil loss occurred using the low intensity, after making three adjustments. The first was to compensate for the 38% lower kinetic energy of the simulator compared with natural rain. The second was for the smaller slope length of the simulator plot. The third was to begin calculating simulator erosivity only after runoff began. After these adjustments, the simulated soil loss over all storms was 99% of the natural soil loss for CT, 112% for RT and 95% for ZT. Our results show that rainfall simulators can successfully estimate soil loss from natural rainfall events. . Les déperditions correspondantes en conditions simulées étaient calculées en appariant les valeurs d'érosivité du simulateur au pouvoir érosif réel de chaque épisode pluvial. On utilisait une forte (140 mm h -1 ) et une basse (60 mm h -1 ) intensité de précipitations simulées. La meilleure concordance entre les déperditions de sol causées entre les pluies réelles et les pluies simulées s'observait au régime d'intensité pluviale inférieure, moyennant toutefois 3 corrections, la première, pour compenser la moindre (38 %) énergie cinétique du simulateur par rapport aux précipitations naturelles; le second pour tenir compte de la pente plus courte de la parcelle sous simulateur de pluie, tandis que la troisième consistait à ne commencer à calculer l'érosivité en régime simulé qu'après le début du ruissellement. Moyennant ces trois corrections, les déperditions de sol en simulation, tous épisodes pluviaux confondus, correspondaient à 99 % des déperditions par pluie naturelle observées en régime TC, à 112 % en régime TR et à 95 % en régime CST. Il semble que les simulateurs de pluie permettent parfaitement d'estimer les déperditions de sol causées par les épisodes de pluie naturelle.