Simulating nitrogen balance in Canadian agricultural soils from 1981 to 2016

Agriculture produces food, fiber and biofuels for the world's growing population, however, agriculture can be a major contributor of nitrogen (N) losses including emissions of ammonia (NH₃), nitrous oxide (N₂O) and nitrate (NO₃^-) leaching and runoff. A Canadian Agricultural Nitrogen Budget for Reactive N (CANBNr) model was developed to estimate the soil N balance in 3487 soil landscape of Canada polygons from 1981 to 2016. The CANBNr model integrates NH₃ emission from fertilizers, manure from housing, storage and field, as well as direct/indirect N₂O emissions from fertilizers, manures, crop residues and soil organic matter. The NO₃^- leaching is estimated based on the residual soil N (RSN) at harvest and drainage derived with the DeNitrification-DeComposition (DNDC) model. From 1981 to 2016, the N input from fertilizer and N fixation increased at a greater rate than N removal in harvested crops in all provinces of Canada, resulting in an increase in the RSN and N losses. In 2016, the Prairie provinces had lower N losses (11.7 kg N ha^-1) from N₂O, NH₃ and NO₃^- compared with 43.2 kg N ha^-1 in central Canada, and 76.5 kg N ha^-1 in Atlantic Canada. However, the Prairie provinces had 84.3% of the total Canadian farmland (74.3% of the total Canadian N input), while central Canada had 12.9% of Canadian farmland (21.7% of the total Canadian N input). In the Prairie provinces, the total N₂O loss from fertilizer N ranged 4.4-8.6 Gg N whereas NH₃ loss ranged from 17.1 to 44.6 Gg N and these values were influenced by both emission intensity and total land area. Total N₂O losses from manure were highest in Alberta, Ontario and Quebec resulting in 4.8, 4.4, and 3.4 Gg N and NH₃ losses from manure were also highest in these 3 provinces at 61.1, 45.2 and 40.4 Gg N, respectively. Nitrate leaching was impacted by drainage volumes, soil type and N inputs. In the non-growing season, NO₃^- leaching losses (36-yr average) were 63.3 Gg in Ontario and 57.5 Gg N in Quebec compared with 20.8 Gg N for Ontario and 35.5 Gg N for Quebec in the growing season. In contrast, the Prairie provinces showed higher NO₃^- leaching in the growing season (23.1-37.4 Gg N) than in the non-growing season (10.4-13.7 Gg N). In summary, total fertilizer N increased the most over the 36 years in the Prairies which resulted in increased RSN and N leaching losses that will require further intervention.

How Modelers Model: the Overlooked Social and Human Dimensions in Model Intercomparison Studies

There is a growing realization that the complexity of model ensemble studies depends not only on the models used but also on the experience and approach used by modelers to calibrate and validate results, which remain a source of uncertainty. Here, we applied a multi-criteria decision-making method to investigate the rationale applied by modelers in a model ensemble study where 12 process-based different biogeochemical model types were compared across five successive calibration stages. The modelers shared a common level of agreement about the importance of the variables used to initialize their models for calibration. However, we found inconsistency among modelers when judging the importance of input variables across different calibration stages. The level of subjective weighting attributed by modelers to calibration data decreased sequentially as the extent and number of variables provided increased. In this context, the perceived importance attributed to variables such as the fertilization rate, irrigation regime, soil texture, pH, and initial levels of soil organic carbon and nitrogen stocks was statistically different when classified according to model types. The importance attributed to input variables such as experimental duration, gross primary production, and net ecosystem exchange varied significantly according to the length of the modeler's experience. We argue that the gradual access to input data across the five calibration stages negatively influenced the consistency of the interpretations made by the modelers, with cognitive bias in "trial-and-error" calibration routines. Our study highlights that overlooking human and social attributes is critical in the outcomes of modeling and model intercomparison studies. While complexity of the processes captured in the model algorithms and parameterization is important, we contend that (1) the modeler's assumptions on the extent to which parameters should be altered and (2) modeler perceptions of the importance of model parameters are just as critical in obtaining a quality model calibration as numerical or analytical details.

Global evaluation of inhibitor impacts on ammonia and nitrous oxide emissions from agricultural soils: A meta-analysis

Inhibitors are widely considered an efficient tool for reducing nitrogen (N) loss and improving N use efficiency, but their effectiveness is highly variable across agroecosystems. In this study, we synthesized 182 studies (222 sites) worldwide to evaluate the impacts of inhibitors (urease inhibitors [UI], nitrification inhibitors [NI] and combined inhibitors) on crop yields and gaseous N loss (ammonia [NH₃ ] and nitrous oxide [N₂ O] emissions) and explored their responses to different management and environmental factors including inhibitor application timing, fertilization regime, cropping system, water management, soil properties and climatic conditions using subgroup meta-analysis, meta-regression and multivariate analyses. The UI were most effective in enhancing crop yields (by 5%) and reducing NH₃ volatilization (by 51%), whereas NI were most effective at reducing N₂ O emissions (by 49%). The application of UI mitigates NH₃ loss and increases crop yields especially in high NH₃ -N loss scenarios, whereas NI application would minimize the net N₂ O emissions and the resultant environmental impacts especially in low NH₃ -N loss scenarios. Alternatively, the combined application of UI and NI enables producers to balance crop production and environmental conservation goals without pollution tradeoffs. The inhibitor efficacy for decreasing gaseous N loss was dependent upon soil and climatic conditions and management practices. Notably, both meta-regression and multivariate analyses suggest that inhibitors provide a greater opportunity for reducing fertilizer N inputs in high-N-surplus systems and presumably favor crop yield enhancement under soil N deficiency situations. The pursuit of an improved understanding of the interactions between plant-soil-climate-management systems and different types of inhibitors should continue to optimize the effectiveness of inhibitors for reducing environmental losses while increasing productivity.

Exploring management strategies to improve yield and mitigate nitrate leaching in a typical radish field in northern China

It is currently uncertain whether process-based models are capable of assessing crop yield and nitrogen (N) losses while helping to investigate best management practices from vegetable cropping systems. The objectives of this study were to (1) calibrate and evaluate the Denitrification-Decomposition (DNDC) model in simulating crop growth and nitrate leaching in a typical field radish system; (2) optimize management practices to improve radish yield and mitigate nitrate leaching under 20-year climate variability. A five-season in-situ field experiment of spring and autumn radish in northern China was established in the autumn of 2017 and measurements of radish yield, N uptake, soil temperature, soil moisture, drainage, and nitrate leaching were obtained under different N usage. DNDC overall demonstrated "good" to "excellent" performance in simulating radish yield, total biomass, N uptake, and soil temperature across all treatments (6.4% ≤ normalized root mean square error (nRMSE) ≤ 15.5%; 0.12 ≤ Nash-Sutcliffe efficiency (NSE) ≤ 0.88; 0.80 ≤ index of agreement (d) ≤ 0.97). DNDC generally exhibited "fair" performance in estimating soil moisture and drainage (10.9% ≤ nRMSE ≤ 27.2%; -0.18 ≤ NSE ≤ 0.37; 0.69 ≤ d ≤ 0.82) and "good" performance when predicting nitrate leaching (12.4% ≤ nRMSE ≤ 26.7%; -0.59 ≤ NSE ≤ 0.51; 0.68 ≤ d ≤ 0.90). Sensitivity analyses demonstrated that optimized management practices (planting dates, irrigation amount, fertilization rate and timing) could substantially reduce N usage by 40%-50%, irrigation amount by 33%-50%, and nitrate leaching by 86%-95% compared to farmers' practice in radish planting system. This study indicated that a modelling method is helpful for evaluating the biogeochemical effects of management alternatives and identifying optimal management practices in radish production systems of China.

Assessing the impacts of diversified crop rotation systems on yields and nitrous oxide emissions in Canada using the DNDC model

Process-based models are effective tools for assessing the sustainability of agricultural productivity and environmental health under various management practices and rotation systems. The objectives of this study were to (1) calibrate and evaluate the DeNitrification-DeComposition (DNDC) model using measurements of yields, nitrogen (N) uptake, soil inorganic N, soil temperature, soil moisture and nitrous oxide (N₂O) emissions under long-term fertilized continuous corn (CC) and corn-oats-alfalfa-alfalfa (COAA) rotation systems in southwest Ontario from 1959 to 2015, Canada, and (2) explore the impacts of four diverse rotation systems (CC, COAA, corn-soybean-corn-soybean (CSCS) and corn-soybean-winter wheat (CSW)) on corn yields and annual N₂O emissions under long-term climate variability. DNDC demonstrated "good" performance in simulating corn, oats and alfalfa yield (normalized root mean square error (nRMSE) < 20%, Nash-Sutcliffe efficiency (NSE) > 0.5 and index of agreement (d) > 0.8). The model provided "fair" to "good" simulations for corn N uptake and soil inorganic N (NSE > 0.2 and d > 0.8), and also daily soil temperature and soil moisture (nRMSE <30% and d > 0.7) for both calibration and validation periods. The model demonstrated "good" performance in estimating daily and cumulative N₂O emissions from both the continuous and rotational corn, whereas it produced "poor" to "good" predictions for N₂O emissions from the rotational oats and alfalfa crops, however, the emissions from these crops were very low and the relative magnitude of these emissions between all crops investigated were well predicted. The lowest N₂O emissions were from COAA followed by CSCS, CSW then CC. The highest corn yields were from COAA, followed by CSW, CSCS, then CC. This study highlights how modelling approaches can help improve the understanding of the impacts of diversified rotations on crop production and greenhouse gas emissions and contribute towards developing policies aimed at improving the sustainability and resiliency of cropping systems.

Ensemble modelling, uncertainty and robust predictions of organic carbon in long-term bare-fallow soils

Simulation models represent soil organic carbon (SOC) dynamics in global carbon (C) cycle scenarios to support climate-change studies. It is imperative to increase confidence in long-term predictions of SOC dynamics by reducing the uncertainty in model estimates. We evaluated SOC simulated from an ensemble of 26 process-based C models by comparing simulations to experimental data from seven long-term bare-fallow (vegetation-free) plots at six sites: Denmark (two sites), France, Russia, Sweden and the United Kingdom. The decay of SOC in these plots has been monitored for decades since the last inputs of plant material, providing the opportunity to test decomposition without the continuous input of new organic material. The models were run independently over multi-year simulation periods (from 28 to 80 years) in a blind test with no calibration (Bln) and with the following three calibration scenarios, each providing different levels of information and/or allowing different levels of model fitting: (a) calibrating decomposition parameters separately at each experimental site (Spe); (b) using a generic, knowledge-based, parameterization applicable in the Central European region (Gen); and (c) using a combination of both (a) and (b) strategies (Mix). We addressed uncertainties from different modelling approaches with or without spin-up initialization of SOC. Changes in the multi-model median (MMM) of SOC were used as descriptors of the ensemble performance. On average across sites, Gen proved adequate in describing changes in SOC, with MMM equal to average SOC (and standard deviation) of 39.2 (±15.5) Mg C/ha compared to the observed mean of 36.0 (±19.7) Mg C/ha (last observed year), indicating sufficiently reliable SOC estimates. Moving to Mix (37.5 ± 16.7 Mg C/ha) and Spe (36.8 ± 19.8 Mg C/ha) provided only marginal gains in accuracy, but modellers would need to apply more knowledge and a greater calibration effort than in Gen, thereby limiting the wider applicability of models.

Regional climate influences manure temperature and methane emissions - A pan-Canadian modelling assessment

This study explores the variation of liquid manure temperature (T_m) and CH₄ emissions associated with contrasting regional climates, inter-annual weather variation, and manure storage emptying. As a case-study, six regions across Canada were used, spanning 11°32' latitude and 58°30' longitude. Annual average air temperatures ranged from 3.9 °C (prairie climate) to 10.5 °C (maritime climate), with an overall average of 6.6 °C. A model predicted T_m over 30 years, using daily weather (1971-2000), and over one "normal" year (30-year average weather). Modelled T_m was then used in Manure-DNDC to model daily CH₄ emissions. Two manure storage emptying scenarios were simulated: (i) early spring and autumn, or (ii) late spring and autumn. Regional differences were evident as average T_m ranged from 8.9 °C to 14.6 °C across the six locations. Early removal of stored manure led to warmer T_m in all regions, and the most warming occurred in colder regions. Regional climate had a large effect on CH₄ emissions (e.g. 1.8× greater in the pacific maritime and great lakes regions than the prairie region). Inter-annual weather variability led to substantial variation in inter-annual CH₄ emissions, with coefficient of variation being as high as 20%. The large inter-annual range suggests that field measurements of CH₄ emissions need to compare the weather during measurements to historical normals. Early manure storage emptying reduced CH₄ emissions (vs late removal) in some regions but had little effect or the opposite effect in other regions. Overall, the results from this modelling study suggest: i) T_m differs substantially from air temperature at all locations, ii) accurate estimates of manure storage CH₄ emissions require region-specific calculations using T_m (e.g. in emission inventories), iii) field measurements of CH₄ emissions need to consider weather conditions relative to climate normal, and iv) emission mitigation practices will require region-specific measurements to determine impacts.

Identifying N fertilizer management strategies to reduce ammonia volatilization: Towards a site-specific approach

Concerns about ammonia (NH₃) losses from nitrogen (N) mineral fertilizers have forced policymakers to set emission reduction commitments across Europe. Although best available techniques (BATs) have been recommended, large uncertainties still exist due to poorly targeted site-specific approaches that might compromise their effectiveness. Here we proposed and tested a conceptual framework designed to identify most effective BATs that reduce NH₃ at the site-specific level. The study was conducted in the Veneto region, northeast Italy. After the mapping of NH₃ emission potential areas, BATs and business-as-usual N fertilization scenarios were assessed using a modified version of the DNDC agroecosystem model and compared with urea broadcast distribution under different pedo-climatic conditions. The most promising practices were further tested in a field experiment using a wind tunnel combined with a FTIR gas analyzer. Results showed that closed-slot injection reduced NH₃ emissions with any type of mineral or organic fertilizers. Injected application, with ammonium nitrate or organic fertilizers, reduced NH₃ loss in maize by 75% and 96%, respectively, and in winter wheat by 87% and 98%, compared to surface broadcast. Injection was the most promising technology to support, being already available to farmers. However, some increase in nitrate leaching was observed, mostly in case of winter wheat (+24% for AN injection; +89% for organic fertilizers). By contrast, urea incorporation with hoeing, the most common technique used by farmers in spring crops, did not show satisfactory results, because the partial burial of urea caused strong NH₃ emissions that were even higher compared to surface broadcast. Recommended NH₃ reduction techniques should be tailored to local pedo-climatic and management conditions, and evaluated, in a holistic approach, considering all N fluxes in the environment.

Modelling climate change impacts on maize yields under low nitrogen input conditions in sub-Saharan Africa

Smallholder farmers in sub-Saharan Africa (SSA) currently grow rainfed maize with limited inputs including fertilizer. Climate change may exacerbate current production constraints. Crop models can help quantify the potential impact of climate change on maize yields, but a comprehensive multimodel assessment of simulation accuracy and uncertainty in these low-input systems is currently lacking. We evaluated the impact of varying [CO₂ ], temperature and rainfall conditions on maize yield, for different nitrogen (N) inputs (0, 80, 160 kg N/ha) for five environments in SSA, including cool subhumid Ethiopia, cool semi-arid Rwanda, hot subhumid Ghana and hot semi-arid Mali and Benin using an ensemble of 25 maize models. Models were calibrated with measured grain yield, plant biomass, plant N, leaf area index, harvest index and in-season soil water content from 2-year experiments in each country to assess their ability to simulate observed yield. Simulated responses to climate change factors were explored and compared between models. Calibrated models reproduced measured grain yield variations well with average relative root mean square error of 26%, although uncertainty in model prediction was substantial (CV = 28%). Model ensembles gave greater accuracy than any model taken at random. Nitrogen fertilization controlled the response to variations in [CO₂ ], temperature and rainfall. Without N fertilizer input, maize (a) benefited less from an increase in atmospheric [CO₂ ]; (b) was less affected by higher temperature or decreasing rainfall; and (c) was more affected by increased rainfall because N leaching was more critical. The model intercomparison revealed that simulation of daily soil N supply and N leaching plays a crucial role in simulating climate change impacts for low-input systems. Climate change and N input interactions have strong implications for the design of robust adaptation approaches across SSA, because the impact of climate change in low input systems will be modified if farmers intensify maize production with balanced nutrient management.

Modifying fertilizer rate and application method reduces environmental nitrogen losses and increases corn yield in Ontario

Nitrogen (N) use in corn production is an important driver of nitrous oxide (N₂O) emissions and 4R (Right source, Right rate, Right time and Right place) fertilizer practices have been proposed to mitigate emissions. However, combined 4R practices have not been assessed for their potential to reduce N₂O emissions at the provincial-scale while also considering trade-offs with other N losses such as leaching or ammonia (NH₃) volatilization. The objectives of this study were to develop, validate, and apply a Denitrification-Decomposition model framework at 270 distinct soil-climate regions in Ontario to simulate corn yield and N₂O emissions across eleven fertilizer management scenarios during 1986-2015. The results show that broadcasting fertilizer at the surface without incorporation had the highest environmental N loss which was primarily caused by NH₃ volatilization. When injected at planting or at sidedress, the NH₃ loss was reduced considerably. However, because more N was left in the soil, injection and sidedressing induced more losses by nitrate leaching and N₂O emissions. Reduction of N rate as proposed by the DNDC model did not affect crop yield but decreased leaching and N₂O emissions. Addition of inhibitors promoted a further reduction in N₂O emission (11-16%) although lesser than the reduction in N rate. Overall, our results emphasize that N rate adjustment following improvements in placement, use of inhibitors, and application timings can mitigate N₂O emissions by 42-57% and result in 3-4% greater yields compared to baseline scenario in Ontario corn production.

Assessing the effects of manure application rate and timing on nitrous oxide emissions from managed grasslands under contrasting climate in Canada

It is uncertain whether process-based models are currently capable of simulating the complex soil, plant, climate, manure management interactions that influence soil nitrous oxide (N₂O) emissions from perennial cropping systems. The objectives of this study were (1) to calibrate and evaluate the DeNitrification DeComposition (DNDC) model using multi-year datasets of measured nitrous oxide (N₂O) fluxes, soil moisture, soil inorganic nitrogen, biomass and soil temperature from managed grasslands applied with manure slurry in contrasting climates of Canada, and (2) to simulate the impact of different manure management practices on N₂O emissions including slurry application i) rates (for both single vs. split); and ii) timing (e.g., early vs. late spring). DNDC showed "fair" to "excellent" performance in simulating biomass (4.7% ≤ normalized root mean square error (NRMSE) ≤ 29.8%; -9.5% ≤ normalized average relative error (NARE) ≤ 16.1%) and "good" performance in simulating soil temperature (13.2% ≤ NRMSE ≤ 18.1%; -0.7% ≤ NARE ≤ 10.8%) across all treatments and sites. However, the model only showed "acceptable" performances in estimating soil water and inorganic N contents which was partially attributed to the limitation of a cascade water sub-model and inaccuracies in simulating root development/uptake. Although, the DNDC model only demonstrated "fair" performance in simulating daily N₂O fluxes, it generally captured the impact of the timing and rate of slurry application and soil texture (loam vs. sandy loam) on total N₂O emissions. The DNDC model simulated N₂O emissions from spring better than split manure application (fall and spring) at the Manitoba site partially due to the overestimation of available substrates for microbial denitrification from fall application during the wet spring periods. Although DNDC performed adequately for simulating most of the manure management impacts considered in this study we recommend improvements in the simulation of soil freeze-thaw cycles, manure decomposition dynamics, soil water storage, rainfall canopy interception, and microbial denitrification and nitrification activities in grasslands.

Understanding the Fertilizer Management Impacts on Water and Nitrogen Dynamics for a Corn Silage Tile-Drained System in Canada

Effective management of dairy manure is important to minimize N losses from cropping systems, maximize profitability, and enhance environmental sustainability. The objectives of this study were (i) to calibrate and validate the DeNitrification-DeComposition (DNDC) model using measurements of silage corn ( L.) biomass, N uptake, soil temperature, tile drain flow, NO leaching, NO emissions, and soil mineral N in eastern Canada, and (ii) to investigate the long-term impacts of manure management under climate variability. The treatments investigated included a zero-fertilizer control, inorganic fertilizer, and dairy manure amendments (raw and digested). The DNDC model overall demonstrated statistically "good" performance when simulating silage corn yield and N uptake based on normalized RMSE (nRMSE) < 10%, index of agreement () > 0.9, and Nash-Sutcliffe efficiency (NSE) > 0.5. In addition, DNDC, with its inclusion of a tile drainage mechanism, demonstrated "good" predictions for cumulative drainage (nRMSE < 20%, > 0.8, and NSE > 0.5). The model did, however, underestimate daily drainage flux during spring thaw for both organic and inorganic amendments. This was attributed to an underestimation of soil temperature and soil water under frequent soil freezing and thawing during the 2013-2014 overwinter period. Long-term simulations under climate variability indicated that spring applied manure resulted in less NO leaching and NO emissions than fall application when manure rates were managed based on crop N requirements. Overall, this study helped highlight the challenges in discerning the short-term climate interactions on fertilizer-induced N losses compared with the long-term dynamics under climate variability.

Assessing uncertainties in crop and pasture ensemble model simulations of productivity and N2 O emissions

Simulation models are extensively used to predict agricultural productivity and greenhouse gas emissions. However, the uncertainties of (reduced) model ensemble simulations have not been assessed systematically for variables affecting food security and climate change mitigation, within multi-species agricultural contexts. We report an international model comparison and benchmarking exercise, showing the potential of multi-model ensembles to predict productivity and nitrous oxide (N₂ O) emissions for wheat, maize, rice and temperate grasslands. Using a multi-stage modelling protocol, from blind simulations (stage 1) to partial (stages 2-4) and full calibration (stage 5), 24 process-based biogeochemical models were assessed individually or as an ensemble against long-term experimental data from four temperate grassland and five arable crop rotation sites spanning four continents. Comparisons were performed by reference to the experimental uncertainties of observed yields and N₂ O emissions. Results showed that across sites and crop/grassland types, 23%-40% of the uncalibrated individual models were within two standard deviations (SD) of observed yields, while 42 (rice) to 96% (grasslands) of the models were within 1 SD of observed N₂ O emissions. At stage 1, ensembles formed by the three lowest prediction model errors predicted both yields and N₂ O emissions within experimental uncertainties for 44% and 33% of the crop and grassland growth cycles, respectively. Partial model calibration (stages 2-4) markedly reduced prediction errors of the full model ensemble E-median for crop grain yields (from 36% at stage 1 down to 4% on average) and grassland productivity (from 44% to 27%) and to a lesser and more variable extent for N₂ O emissions. Yield-scaled N₂ O emissions (N₂ O emissions divided by crop yields) were ranked accurately by three-model ensembles across crop species and field sites. The potential of using process-based model ensembles to predict jointly productivity and N₂ O emissions at field scale is discussed.

Review and analysis of strengths and weaknesses of agro-ecosystem models for simulating C and N fluxes

Biogeochemical simulation models are important tools for describing and quantifying the contribution of agricultural systems to C sequestration and GHG source/sink status. The abundance of simulation tools developed over recent decades, however, creates a difficulty because predictions from different models show large variability. Discrepancies between the conclusions of different modelling studies are often ascribed to differences in the physical and biogeochemical processes incorporated in equations of C and N cycles and their interactions. Here we review the literature to determine the state-of-the-art in modelling agricultural (crop and grassland) systems. In order to carry out this study, we selected the range of biogeochemical models used by the CN-MIP consortium of FACCE-JPI (http://www.faccejpi.com): APSIM, CERES-EGC, DayCent, DNDC, DSSAT, EPIC, PaSim, RothC and STICS. In our analysis, these models were assessed for the quality and comprehensiveness of underlying processes related to pedo-climatic conditions and management practices, but also with respect to time and space of application, and for their accuracy in multiple contexts. Overall, it emerged that there is a possible impact of ill-defined pedo-climatic conditions in the unsatisfactory performance of the models (46.2%), followed by limitations in the algorithms simulating the effects of management practices (33.1%). The multiplicity of scales in both time and space is a fundamental feature, which explains the remaining weaknesses (i.e. 20.7%). Innovative aspects have been identified for future development of C and N models. They include the explicit representation of soil microbial biomass to drive soil organic matter turnover, the effect of N shortage on SOM decomposition, the improvements related to the production and consumption of gases and an adequate simulations of gas transport in soil. On these bases, the assessment of trends and gaps in the modelling approaches currently employed to represent biogeochemical cycles in crop and grassland systems appears an essential step for future research.

Scenario analysis of fertilizer management practices for N2O mitigation from corn systems in Canada

Effective management of nitrogen (N) fertilizer application by farmers provides great potential for reducing emissions of the potent greenhouse gas nitrous oxide (N₂O). However, such potential is rarely achieved because our understanding of what practices (or combination of practices) lead to N₂O reductions without compromising crop yields remains far from complete. Using scenario analysis with the process-based model DNDC, this study explored the effects of nine fertilizer practices on N₂O emissions and crop yields from two corn production systems in Canada. The scenarios differed in: timing of fertilizer application, fertilizer rate, number of applications, fertilizer type, method of application and use of nitrification/urease inhibitors. Statistical analysis showed that during the initial calibration and validation stages the simulated results had no significant total error or bias compared to measured values, yet grain yield estimations warrant further model improvement. Sidedress fertilizer applications reduced yield-scaled N₂O emissions by c. 60% compared to fall fertilization. Nitrification inhibitors further reduced yield-scaled N₂O emissions by c. 10%; urease inhibitors had no effect on either N₂O emissions or crop productivity. The combined adoption of split fertilizer application with inhibitors at a rate 10% lower than the conventional application rate (i.e. 150kgNha^-1) was successful, but the benefits were lower than those achieved with single fertilization at sidedress. Our study provides a comprehensive assessment of fertilizer management practices that enables policy development regarding N₂O mitigation from agricultural soils in Canada.

Impact of management strategies on the global warming potential at the cropping system level

Estimating the greenhouse gas (GHG) emissions from agricultural systems is important in order to assess the impact of agriculture on climate change. In this study experimental data supplemented with results from a biophysical model (DNDC) were combined with life cycle assessment (LCA) to investigate the impact of management strategies on global warming potential of long-term cropping systems at two locations (Breton and Ellerslie) in Alberta, Canada. The aim was to estimate the difference in global warming potential (GWP) of cropping systems due to N fertilizer reduction and residue removal. Reducing the nitrogen fertilizer rate from 75 to 50 kg N ha(-1) decreased on average the emissions of N2O by 39%, NO by 59% and ammonia volatilisation by 57%. No clear trend for soil CO2 emissions was determined among cropping systems. When evaluated on a per hectare basis, cropping systems with residue removal required 6% more energy and had a little change in GWP. Conversely, when evaluated on the basis of gigajoules of harvestable biomass, residue removal resulted in 28% less energy requirement and 33% lower GWP. Reducing nitrogen fertilizer rate resulted in 18% less GWP on average for both functional units at Breton and 39% less GWP at Ellerslie. Nitrous oxide emissions contributed on average 67% to the overall GWP per ha. This study demonstrated that small changes in N fertilizer have a minimal impact on the productivity of the cropping systems but can still have a substantial environmental impact.

A Greenhouse Gas and Soil Carbon Model for Estimating the Carbon Footprint of Livestock Production in Canada

To assess tradeoffs between environmental sustainability and changes in food production on agricultural land in Canada the Unified Livestock Industry and Crop Emissions Estimation System (ULICEES) was developed. It incorporates four livestock specific GHG assessments in a single model. To demonstrate the application of ULICEES, 10% of beef cattle protein production was assumed to be displaced with an equivalent amount of pork protein. Without accounting for the loss of soil carbon, this 10% shift reduced GHG emissions by 2.5 TgCO₂e y(-1). The payback period was defined as the number of years required for a GHG reduction to equal soil carbon lost from the associated land use shift. A payback period that is shorter than 40 years represents a net long term decrease in GHG emissions. Displacing beef cattle with hogs resulted in a surplus area of forage. When this residual land was left in ungrazed perennial forage, the payback periods were less than 4 years and when it was reseeded to annual crops, they were equal to or less than 40 years. They were generally greater than 40 years when this land was used to raise cattle. Agricultural GHG mitigation policies will inevitably involve a trade-off between production, land use and GHG emission reduction. ULICEES is a model that can objectively assess these trade-offs for Canadian agriculture.

Use of a flotation tank to sling horses and cattle undergoing surgery to the limbs

A system using a suitably sized flotation tank has been developed to reduce the weight that horses and cattle place upon their legs after undergoing surgery to their limbs. The system overcomes the need for the patient to lie down for long periods, thus preventing decubitus. The system is well tolerated with few side effects; after prolonged flotation alopecia may occur on those parts of the patient which remain continuously immersed in water. The method is now commonly referred to as the 'Queensland Sling'.

Calcification of membranes isolated from Bacterionema matruchotii

Lytic cultures of Bacterionema matruchotii were found to release vesicular membranes into the medium which could be obtained virtually free of other cell structures by differential centrifugation. Suspension of the membrane fraction in a metastable calcium phosphate solution resulted in the formation of both amorphous mineral and hydroxyapatite. Examination by electron microscopy showed that mineralization was associated with the membrane bilayers. The results provide further evidence that calcification of B matruchotii is related to intracytoplasmic membranes.

Calcification of selected strains of Streptococcus mutans and Streptococcus sanguis

Nine strains of cariogenic Streptococcus mutans and two strains of Streptococcus sanguis were tested for their ability to form hydroxyapatite. The cells were examined by X-ray diffraction and electron microscopy for apatite crystals after growth in a synthetic calcification medium. Each of the test isolates, except for one strain of S. sanguis, produced intracellular mineral. Two strains of S. mutans formed both intra- and extracellular crystals. There was no apparent relationship between calcifiability and serotype.

Characteristics of an induced variant of Bacterionema matruchotii

Bacterionema matruchotii, a calcifiable filamentous organism, was treatetl ultrasonically. The disrupted cells produced typical colonies that developed macroscopic globular structures. A nonfilamentous, pleomorphic variant was derived from the globules. The variant retained the calcification potential of the filament, as well as fermentation and ultrastructural similarities.

Distribution of mucosubstances in the developing rat heart

Mucosubstances (MS) were examined in 10½-14½-day embryonic rat hearts utilizing nonaqueous fixatives or formaldehyde vapor-fixed frozen sections hydrated in concentrated solutions of cetylpyridinium chloride. Ribonuclease-resistant, polyanionic sites were limited to the extracellular cardiac jelly, endocardium and fibroblastic cells (cushion tissue) associated with the endocardium. The cardiac jelly and endocardium of day 10½ embryos principally contained a hyaluronic acid-like carboxylated mucosubstance whose alcianophilia at pH 2.5 was abolished by hyaluronidase but was resistant to NaOH extraction and neuraminidase and trypsin digestion. A critical electrolyte concentration of 0.2 M MgCl2 abolished alcianophilia. On days 13½-14½ carboxylated MS were restricted to cushion tissue and partially resisted mild methylation. Sulfated MS were limited to primitive endocardial cells which gave origin to cushion tissue. Dye deposits of aldehyde fuchsin, high iron diamine or Alcian Blue (pH 1.0) were localized on cell surfaces and such staining was prevented by strong (60°C) methylation. Hyaluronidase sensitivity of sulfated MS decreased with gestation. The critical electrolyte concentration varied from 0.5-0.7 M MgCl2 on days 11½-12½ to 0.8-0.9 M MgCl2 after day 12½. The sulfated MS of endocardial cells were preceded by a transitory accumulation of diastase-resistant, periodic acid-Schiff-positive material. Possible roles of MS in normal and abnormal cardiac septation processes are discussed.

Isolation of Bacillary and Streptococcal Variants from Bacterionema matruchotii

Bacterionema matruchotii , an oral filamentous organism, dissociated to form unusual flat colonies. Subculture of the flat colonies, composed of diphtheroids, yielded pure cultures of bacillary and streptococcal variants.

Influence of testosterone upon sexual maturation in the rat

1. Testosterone injected into the neonatal female rat induces permanent sterility. This study was carried out in an endeavour to determine where this change is induced.2. Hypophysectomized, but otherwise normal, female rats bearing anterior pituitary transplants from androgen-sterilized female rats under the median eminence of the hypothalamus and vascularized from it, show oestrous cycles in the vaginal smear, have corpora lutea in the ovaries and are fertile.3. Hypophysectomized androgen-sterilized female rats bearing anterior pituitary transplants from normal female rats under the median eminence and vascularized from it show persistent oestrus in the vaginal smear, have small ovaries containing large follicles but no corpora lutea and are sterile.4. Testosterone injected into the female rat, and leading to sterility and ovarian malfunction, does not act at the level of the anterior pituitary, which retains the ability to function normally. It is considered that it may act upon the central nervous system to cause a disturbance of the gonadotrophin-releasing mechanism.