Brian B Grant

Agriculture and Agri-Food Canada | AAFC · Science and Technology Branch

Two prominent process-based models, DNDC (i.e., Denitrification–Decomposition) and DayCent, were investigated for their ability to capture the inter-annual variability in spring wheat grain yields, soil carbon change, and trace gas emissions for three long-term experiments conducted on the Canadian prairies. The cropping systems included continuous...

Agricultural management practices which promote soil organic C (SOC) sequestration can contribute to the long-term productivity of soils, thus research must quantify and predict SOC dynamics in response to crop management. Using long-term (1967-2009) data from 10 cropping systems on a Brown Chernozem (Aridic Haploboroll) in the Canadian semiarid pr...

Crop residues can be a viable source for biofuel production and other industrial products; however, their removal from agricultural land may negatively impact productivity and environmental quality. In this study three process-based models (CENTURY, DAYCENT, and DNDC) and the CAMPBELL empirical model were used to simulate soil organic carbon (SOC)...

The Denitrification-Decompostion (DNDC) model was used to estimate the impact of change in management practices on N2O emissions in seven major soil regions in Canada, for the period 1970 to 2029. Conversion of cultivated land to permanent grassland would result in the greatest reduction in N2O emissions, particularly in eastern Canada wherethe mod...

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...

Multi-model ensembles are becoming increasingly used for estimation of agricultural carbon-nitrogen fluxes, productivity and sustainability. There is mounting evidence that with some site-specific observations available for model calibration (with vegetation data as a minimum requirement), median outputs assimilated from biogeochemical models (mult...

The soybean industry in Canada aimed to extensively expand soybean production to benefit from new early-maturing varieties and the warming climate. However, setbacks in the soybean industry since 2017 demonstrated the impacts of climate risk and global market uncertainty. Therefore, a better understanding of future climate conditions that will impa...

Application of urease and nitrification inhibitors is an effective strategy for decreasing nitrogen (N) losses without negatively impacting yields, but the long-term impacts of inhibitors and N placement on N dynamics remains unclear. The objectives of this study were to 1) use a 3-year maize experiment in southwestern Ontario to evaluate the Denit...

There is a growing realisation that the complexity of model ensemble studies depends not only on the models used, but also on the experience and approach used by modellers 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 modeller...

Nitrous oxide (N 2 O) is an important greenhouse gas (GHG) that also contributes to depletion of ozone in the stratosphere. Agricultural soils account for about 60% of anthropogenic N 2 O emissions. Most national GHG reporting to the United Nations Framework Convention on Climate Change assumes nitrogen (N) additions drive emissions during the grow...

Calibration and validation are standardized practices to establish the credibility of biogeochemical models for understanding agroecosystem nutrient dynamics. We evaluated three automatic calibration approaches, including simultaneous, sequential, and separate, for the calibration of model parameters of the biogeochemical DeNitrification DeComposit...

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...

Crop residue input plays a central role in regulating soil organic carbon (SOC) storage. Ten long-term field experiments were used to ascertain the changes in SOC in response to differing rates of crop residues. The amount of C input from crop residues varied significantly between and within sites due to soil-environmental conditions, management an...

To better understand how climate change might influence global canola production, scientists from six countries have completed the first inter-comparison of eight crop models for simulating growth and seed yield of canola, based on experimental data from six sites across five countries. A sensitivity analysis was conducted with a combination of fiv...

Methane emissions from liquid manure management in Canada are an important greenhouse gas source. A wide range of seasonal temperatures, distribution of livestock farms, and various management practices in Canada means that regional methane conversion factors (MCF) that account for spatially discrete climate and management should be used. This stud...

An accurate estimation of crop yield under climate change scenarios is essential to quantify our ability to feed a growing population and develop agronomic adaptations to meet future food demand. A coordinated evaluation of yield simulations from process-based eco-physiological models for climate change impact assessment is still missing for soybea...

Municipal wastewater sludge may be processed into biosolids and applied to farmland for crop production, rather than be disposed of in landfills. Biosolids supply plant nutrients and increase soil organic carbon but also contribute to the production of greenhouse gases (GHGs). Computational models must therefore be refined to estimate the contribut...

Nitrate (NO 3 −) leaching has negative human and environmental health consequences that can be attributed to and mitigated by agricultural decision making. The purpose of this study is to examine the economic and environmental nitrogen (N) leaching reduction from 4R (Right Rate, Right Source, Right Time, Right Placement) agricultural management pra...

Tillage and crop residue management can have large impacts on soil organic carbon (SOC) sequestration, as well as additional feedbacks on crop productivity and agricultural sustainability. The objectives of this study were to (i) evaluate the effects of summer fallow, legume green manure, pea or canola in rotation with spring wheat on crop yields,...

Representative subsets of global climate models (GCMs) are often used in climate change impact studies to account for uncertainty in ensemble climate projections. However, the effectiveness of such subsets has seldom been assessed for the estimations of either the mean or the spread of the full ensembles. We assessed two different approaches that w...

Fertilizer has revolutionized crop production, but a lack of evidence-based fertilizer usage has resulted in negative economic and environmental ramifications, particularly for smallholder farmers. This study aimed at developing an innovative nutrient recommendation approach, Nutrient Expert (NE), for improving yields of maize, wheat, and rice whil...

Accurate estimates of soil organic carbon (SOC) are critical for evaluating the impacts of crop and nutrient management practices on soil sustainability and global climate change. Temporal and spatial variations in topsoil (0–0.20 m) SOC were analyzed using 43,743 soil samples in China’s croplands. The soil database in our study was collected from...

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 nitrat...

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, soi...

Large scale adoption of nitrogen (N) management practices, including the 4Rs, could lead to beneficial environmental and economic outcomes, but only if they improve agricultural profit or are driven by policy and legislation. This study uses a spatial economic maximization and environmental simulation model to examine the economic and environmental...

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. To do this, we evaluated SOC simulated from an ensemble of 26 process‐based C models b...

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 p...

Methane emissions from liquid manure were modelled in 6 climate zones over 30 years • Warmer climate increased manure temperature and lengthened warm season storage time • CH 4 emissions differed up to 80% between regions. Inter-annual variability was also high. • Field measurements of CH 4 emissions need to consider weather relative to climate nor...

Canada is one of the top wheat grain exporters, with a share of more than 10% in the world wheat market. The majority of Canadian wheat production takes place in the Prairies where 6.2 million ha of the area is seeded to spring wheat. The climate is semiarid with an estimated precipitation deficit of about 300 mm during the crop growing season, ind...

In this study, Life Cycle Assessment (LCA) methodology was combined with the agro-ecosystem model DNDC to assess the climate and eutrophication impacts of perennial grass cultivation at five different sites in Sweden. The system was evaluated for two fertilisation rates, 140 and 200 kg N ha −1. The climate impact showed large variation between the...

Purpose This paper presents an improved methodological approach for studying life cycle impacts (especially global warming) from changes in crop production practices. The paper seeks to improve the quantitative assessment via better tools and it seeks to break down results in categories that are logically separate and thereby easy to explain to far...

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 multi‐model assessment of simulation accuracy and uncertainty i...

Internal climate variability (ICV) is one of the major sources of uncertainty in climate projections, yet it is seldom quantified for projections of crop production. Our study focuses on quantifying the uncertainty due to ICV in projections of crop productions in Canada. We utilize climate scenarios from two large ensembles (LEs, CanESM2-LE and Can...

Measurements of nitrous oxide (N2O) emissions from agriculture are essential for understanding the complex soil‐crop‐climate processes, but there are practical and economic limits to the spatial and temporal extent over which measurements can be made. Therefore, N2O models have an important role to play. As models are comparatively cheap to run, th...

Assessment of the impact of climate change on agricultural sustainability requires a robust full system estimation of the interdependent soil-plant-atmospheric processes coupled with dynamic farm management. The simplification or exclusion of major feedback mechanisms in modelling approaches can significantly affect model outcomes. Using a biogeoch...

Croplands and grasslands are agricultural systems that contribute to land–atmosphere exchanges of carbon (C). We evaluated and compared gross primary production (GPP), ecosystem respiration (RECO), net ecosystem exchange (NEE=RECO-GPP) of CO2, and two derived outputs - C use efficiency (CUE=-NEE/GPP) and C emission intensity (IntC= -NEE/Offtake [gr...

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...

The goal of most fertilizer decision support tools is to help maize farmers estimate the most profitable nitrogen (N) rate for a given fertilizer N/grain price ratio, known as the economically optimum N rate (EONR). While maximizing profitability, to our knowledge the environmental performance of the EONR has not been fully assessed using a process...

Agricultural activities can lead to either losses or gains of soil organic carbon (SOC) in croplands and grasslands. Increasing SOC stocks improves soil fertility and is seen as a short- to mid-term solution to mitigate greenhouse gas (GHG) emissions. Emerging ecological and societal challenges (climate change, food security, ecosystem sustainabili...

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...

Nitrogen (N) fertilizer additions are typically necessary to maintain high crop yields but are also largely responsible for agricultural soils being the primary source of anthropogenic nitrous oxide (N2O) emissions [1]. N2O is a greenhouse gas with approximately 265-298 times the global warming. potential of CO2 on a per mole basis [2]. N2O is also...

Alfalfa (Medicago sativa L.) is the predominant forage legume species in Canada and is considered a prioritized option for sustainable cropping under climate change. Crop growth models provide an opportunity to explore the potential impacts of climate change on alfalfa and for evaluating potential adaptation options. For this study, six experimenta...

Supplementary material for "Development of the DNDC model to improve soil hydrology and incorporate mechanistic tile drainage: A comparative analysis with RZWQM2"

The Denitrification Decomposition model (DNDC) has known limitations for simulating soil hydrology which can strongly influence biogeochemical processes. For this study, DNDC’s soil hydrological framework was enhanced by including a new sub-model for mechanistic tile drainage, improved water flux, root growth dynamics, and a deeper and heterogeneou...

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 mult...

The DeNitrification-DeComposition (DNDC) model was developed to better simulate alfalfa (Medicago sativa L.) production with winterkill effects in eastern Canada. The pre-development DNDC produced “fair” simulations of alfalfa yield and biomass (index of agreement (d) > 0.7, Nash-Sutcliffe efficiency (NSE) > 0) but normalized root mean square error...

The Denitrification Decomposition (DNDC) model is a widely used process-based model for simulating greenhouse gas emissions and soil carbon change. The model, however, has known limitations for simulating soil hydrology, which is a crucial driver influencing biogeochemical processes. The purpose of this study was to improve DNDC for simulating hydr...

Science-based assessments of climate change impacts on cropping systems under different levels of global warming are essential for informing stakeholders which global climate targets and potential adaptation strategies may be effective. A comprehensive evaluation of climate change impacts on Canada's crop production under different levels of global...

There is an incentive for dairy farmers to maximize crop production while minimizing costs and environmental impacts. In cold climates, farmers have limited opportunity to balance field activities and manure storage requirements while limiting nutrient losses. A revised DeNitrification DeComposition (DNDC) model for simulating tile drainage was use...

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 (Zea mays L.) biomass, N uptake, soil temper...

As part of benchmarking actions at international level (FACCE-JPI project CN-MIP), the C-MIP action was initiated in 2016 to address the question of whether ensemble modelling could bring some improvement to the simulation of soil organic carbon (SOC) dynamics. A multi-model ensemble with 25 process-based integrated C-N models was implemented to co...

As part of benchmarking actions at international level (FACCE-JPI project CN-MIP), the C-MIP action was initiated in 2016 to address the question of whether ensemble modelling could bring some improvement to the simulation of soil organic carbon (SOC) dynamics. A multi-model ensemble with 25 process‐based integrated C-N models was implemented to co...

Supplementary Material for: Comparing hydrological frameworks for simulating crop biomass, water and nitrogen dynamics in a tile drained soybean-corn system: Cascade vs computational approach

Biophysical agricultural models are needed for assessing science-based mitigation options to improve the efficiency and sustainability of agricultural cropping systems. It is crucial that they can accurately simulate soil hydrology and nutrient flows which strongly influence crop growth, biogeochemical processes and water quality. The purpose of th...

Agricultural practices such as including perennial alfalfa ( Medicago sativa L.), winter wheat ( Triticum aestivum L.), or red clover ( Trifolium pratense L.) in corn ( Zea mays L.) rotations can provide higher crop yields and increase soil organic C (SOC) over time. How well process‐based biogeochemical models such as DeNitrification‐DeComposition...

Accurately accounting for water budgets within regional agroecosystems is becoming an increasingly important practice, as both climate change and water consumption pressures have the potential for influencing agro-productivity and other water use activities. In this study, water budget measurements from 10 rainfed experimental sites across Canada w...

Simulation models are extensively used to predict agricultural productivity and greenhouse gas (GHG) emissions. However, the uncertainties of (reduced) model ensemble simulations have not been assessed systematically for variables affecting food security and climate change mitigation, within multispecies agricultural contexts. We report an internat...

Supplemental Material Long-term trends in corn yields and soil carbon under diversified crop rotations Jarecki et al., 2018. Journal of Environmental Quality

Process-based models are useful tools for estimating the complex interactions between plant, soil and climate systems, assessments which are necessary for improving nutrient cycling and reducing trace gas emissions. Incorporation of knowledge gained through new research is ongoing, thus there is a need for evaluation of model processes and process...

A water footprint considers both the water volumes involved in production processes and the resulting waste water generated. The grey water (GW) footprint represents the volume of fresh water required to assimilate pollutants to acceptable concentrations—a concept proposed by the water footprint network—but it faces several difficulties when applie...