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Crop rotational diversity is an important part of sustainable agricultural and soil management to improve crop yield and soil fertility including enhancing soil organic matter (SOM) stabilization. Because of the physical protection via interactions with soil minerals, SOM in mineral-associated fractions is believed to be longer-lived and more stable relative to SOM in particulate (light) fractions. However, it is still unclear how crop rotational diversity alters soil carbon distribution, composition and stabilization in soil physical fractions. To address this, we studied a 37 years’ agricultural site with different crop rotational diversity (from continuous corn or alfalfa up to four species (corn, soybean, winter wheat, and red clover)). Soil carbon analysis, targeted compound analysis and nuclear magnetic resonance spectroscopy methods were used to obtain the distribution and degradation of SOM components in light and mineral-associated (F53–2000 µm, F2–53 µm, and F) fractions. Higher soil organic carbon (SOC) concentrations were observed in F with relatively high diversified crop rotations (three and four types of crops) compared to monoculture or two crops in the rotations, which suggests that carbon storage is enhanced in mineral-stabilized pools. Higher concentrations of long-chain aliphatic compounds as well as increased accumulation and preservation of lignin-derived compounds in fine aggregates (

This study quantified fugitive methane (CH

Horticultural systems, specifically vegetable production systems, are considered intensive agricultural systems as they are characterized by high nitrogen (N) fertilizer application rate, frequent tillage, and irrigation operations. Accordingly, horticultural production in temperate climates is prone to N losses — mainly during post-harvest (during fall and winter) or pre-plant (spring) periods — such as N2O emissions and nitrate leaching. The risk for N losses is linked to low crop N use efficiency (NUE) combined with a narrow C:N and high N content of crop residues. Here we reviewed the studies conducted in Canada and similar climates to better understand the risk of N2O emission and potential agronomic management strategies to reduce N2O emissions from horticultural systems. Current knowledge on N2O emissions from horticultural systems indicate that increasing crop NUE, modifying the amount, type, time, and rate of N fertilizer inputs, and adopting cover crops in crop rotations are some of the effective approaches to decrease N2O emissions. However, there is uncertainty related to the efficiency of the existing N2O mitigation strategies due to the complex interactions between the factors (soil characteristics, type of plant species, climatic conditions, and soil microbial activity) responsible for N2O production from soil. Little research on N2O emissions from Canadian horticultural systems limits our ability to understand and manage the soil N2O production processes to mitigate the risk of N2O emissions. Thus, continuing to expand this line of research will help to advance the sustainability of Canadian horticultural cropping systems.

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 growing season, but soil freezing and thawing during spring is also an important driver in cold climates. We show that both atmospheric inversions and newly implemented bottom-up modeling approaches exhibit large N 2 O pulses in the northcentral region of the United States during early spring and this increases annual N 2 O emissions from croplands and grasslands reported in the national GHG inventory by 6 to 16%. Considering this, emission accounting in cold climate regions is very likely underestimated in most national reporting frameworks. Current commitments related to the Paris Agreement and COP26 emphasize reductions of carbon compounds. Assuming these targets are met, the importance of accurately accounting and mitigating N 2 O increases once CO 2 and CH 4 are phased out. Hence, the N 2 O emission underestimate introduces additional risks into meeting long-term climate goals.

National inventory reporting of agricultural nitrous oxide (N2O) emissions in Canada is based primarily on measurements obtained using static chambers. In regions with cold winters and an accumulated snowpack (including Canada), these measurements tend to focus on the growing season (typically May–October). However, research has shown that emissions continue throughout the non-growing season (NGS) and that these account for a significant proportion of annual emissions. In the Canadian National Inventory NGS emissions currently are assumed to be adequately captured in western Canada, while they are accounted for in eastern Canada by multiplying the growing season emissions by a correction factor of 1.4, a value that was derived based on a limited number of measurements. Here we use recent Canadian studies to validate this correction factor. We collected data from available Canadian studies that measured soil N2O emissions from agricultural systems for the entire year and determined the proportion of these emissions that occurred during the NGS. The proportion of annual N2O emissions that occurred during the NGS varied widely, ranging from −4% to 119% with a mean of 35.5%, compared to the previous estimate of 30%. Due to high variability, few differences were observed between means associated with climatic, soil, and management variables. To correct for NGS N2O emissions from Canadian agricultural soils, we suggest that the current correction factor for converting growing season to total annual emissions be changed from 1.4 to 1.55 and that this be used for all agricultural soils in Canada rather than just eastern Canada.

Nitrous oxide (N2O) emissions from soils have been widely studied in the literature — mostly with the chamber method — due to the importance of this gas to climate change. Emissions of N2O derive from biological reactions and are controlled by soil parameters, which are by nature heterogeneous (i.e., “hot spots” for N2O emissions) — a source of uncertainty in chamber-based studies. Spatial variation in N2O fluxes has been assessed in the literature, but the information is still needed for contrasting soil management practices (e.g., tillage) and for specific bioclimatic situations [e.g., non-growing seasons (NGS) under cold weather]. Here, we subsampled daily N2O data to assess within-plot and between-block spatial variation from an agronomic experiment under conventional tillage (CT) and no-tillage (NT), identifying if patterns differ between growing seasons (GS) and NGS datasets. Within-plot spatial variation in N2O fluxes was a small source of uncertainties, but half of the comparisons in GS datasets presented a slope different from 1 for the regression of N2O averages from two vs. one chamber per plot — a source of uncertainty mitigated when within-plot duplication occurred during N2O “hot moments”. Between-block spatial variation in N2O emissions was much larger than within-plot errors — an effect more accentuated for NGS and CT than GS and NT datasets. Decreasing the number of sampled blocks resulted in averages that did not represent the N2O daily average of the whole field, but exceptions occurred. The methodology proposed here may be used in other locations, after appropriate verification, for improved planning and maximization of the resources associated with N2O measurements.

The social cost of nitrous oxide does not account for stratospheric ozone depletion. Doing so could increase its value by 20%. Links between nitrous oxide and other nitrogen pollution impacts could make mitigation even more compelling.

Agriculture is a large source of greenhouse gas (GHG) emissions but changing management practices to those more beneficial to the environment could help mitigate climate change as long as they are economically and environmentally viable. This study examines the environmental (public) and economic (private) effects of adopting ten different beneficial management practices on a representative corn farm in Ontario, Canada. The study integrates changes in GHG emissions in carbon equivalents (CO2e) and changes in profit from changes in costs and revenues in two dimensions to reveal the scope and scale of different kinds of practices. 4R nitrogen management practices are smaller in scale compared to cropping practices and, therefore, have smaller potential costs and benefits. Land use changes, from practices including biomass, afforestation, crop rotation and cover cropping, have larger impacts on soil sequestration and carbon-equivalent GHG reduction, but with significantly greater costs. Seven practices were found to, at least partially, be economically and environmentally beneficial. The adoption of no-till and N-rate reduction is firmly positive, whereas the production of biomass has the largest potential economic and environmental gains. Crop rotation and diversification and cover cropping can be mutually beneficial, as can changing N-application practices. The use of inhibitors may be economically beneficial if yield gains outweigh purchase costs.

Evaluate crop rotation diversity, perenniality, carbon (C) inputs, and C input quality as predictors of soil organic carbon (SOC) concentration and aggregate mean weight diameter (MWD). At a crop rotation trial in its 37th year in Ontario, Canada, species in rotations included corn (C, Zea mays L.), alfalfa (A, Medicago sativa L.), soybean (S, Glycine max (L.) Merr.), winter wheat (W, Triticum aestivum L.), and red clover (rc, Trifolium pratense L.). Rotations were: CC, CCAA, CCSS, CCSW, CCSWrc, AA. Soils (0–20 cm) were analyzed for aggregate MWD, aggregate C, and SOC concentrations. We estimated C inputs from historical yields and C input quality (C:N, lignin: N, or NMR-derived index) from structural plant tissues. C stabilization efficiency was estimated as the ratio of SOC stock per unit total or root C input. Crop rotation diversity failed to increase SOC concentrations or aggregate MWD. Perennialized rotations (CCSWrc, CCAA, AA) maintained the numerically highest SOC concentrations, and root C input increased SOC concentration. Out of 12 statistical tests relating C input quality to C stabilization efficiency, only 3 indicated a positive effect and 6 tests indicated a negative effect. Including a perennial forage such as alfalfa and limiting soybean frequency promotes aggregate MWD and SOC concentration more so than optimizing crop rotation diversity. Quality of structural plant inputs does not explain differences in C stabilization efficiency, possibly due to overriding influence of living root inputs.

Nitrous oxide (N2 O) is a potent greenhouse gas that is primarily emitted from agriculture. Sampling limitations have generally resulted in discontinuous N2 O observations over the course of any given year. The status quo for interpolating between sampling points has been to use a simple linear interpolation. This can be problematic with N2 O emissions, since they are highly variable and sampling bias around these peak emission periods can have dramatic impacts on cumulative emissions. Here, we outline five gap-filling practices: linear interpolation, generalized additive models (GAMs), autoregressive integrated moving average (ARIMA), random forest (RF), and neural networks (NNs) that have been used for gap-filling soil N2 O emissions. To facilitate the use of improved gap-filling methods, we describe the five methods and then provide strengths and challenges or weaknesses of each method so that model selection can be improved. We then outline a protocol that details data organization and selection, splitting of data into training and testing datasets, building and testing models, and reporting results. Use of advanced gap-filling methods within a standardized protocol is likely to increase transparency, improve emission estimates, reduce uncertainty, and increase capacity to quantify the impact of mitigation practices.

Acidification with sulphuric acid and cleaning residual manure in tanks are promising practices for reducing methane (CH4), which is a potent greenhouse gas. To date, no data are available on CH4 reductions from acidifying only residual manure (rather than all manure). Moreover, long-term effects of manure acidification (i.e. inoculating ability of previously acidified residual manure in the subsequent storages) are not known. To address these gaps, fresh manure (FM; 150 mL) combined with treated or untreated inoculum (30 mL) were anaerobically incubated at 17°C, 20°C, and 23°C for 116 d. Acidified treatments, regardless of location of acid addition, reduced CH4 production by 81% at 17°C, 78% at 20°C, and 19% at 23°C compared to the control (untreated FM and untreated inoculum). To test long-term acidification effects, FM was inoculated with manure that had been acidified 6-months prior. This created comparable CH4 production to FM with no inoculum and reduced CH4 production by 99% at 17°C and 20°C, and 49% at 23°C compared to the control. Results indicate that residual slurries of acidified manure become poor inoculants in subsequent storage, hence manure acidification has a long-term treatment effect in reducing CH4 production. This could reduce how often acidification is needed in dairy manure tanks and also increasing its cost-effectiveness for farmers.

A novel laboratory method was developed to control soil freeze–thaw cycles and study the effects of freezing intensity on soil conditions and N2O emissions. The method created unidirectional freeze–thaw (top-down), similar to field conditions. Soil was placed in boxes that were insulated on the sides, heated from the bottom, and left open on the top. Snow was placed on the soil surface, and the boxes were placed in separate climate-controlled chambers to freeze (−9 °C) and thaw (5 °C). The method was used in an experiment to evaluate the links between freezing degree days (FDD), soil water content, carbon (C) and nitrogen (N) transformations, and N2O emissions. Results showed that N2O emissions were greatest from soils that experienced more freezing, with the 185 FDD treatment emitting significantly more N2O than the 50 FDD treatment (17.7 vs. 7.7 mg N2O-N m−2d−1). Peaks in soil water content during thaw preceded peaks in N2O flux, but increasing water content by simulating rain (in addition to snow melt) did not increase N2O emissions compared with snow melt alone. Extractable soil C and N increased in the top 5 cm when soils froze; however, greater emissions were not linked to greater C and N concentrations at individual points in time. Higher N2O emissions at 134 and 185 FDD were associated with greater C exposure (i.e., extractable soil C concentration integrated over time) than the 50 FDD treatment.

Standard life cycle assessment and economic analysis methods were used to determine the carbon footprint (CF) of milk production and financial performance of a representative sample of dairy farms in Ontario, Canada to assess if there is a trade-off between these two different sustainability measures. Across the 142 dairy farms, CF of milk varied by about 4-fold, from 0.441 to 1.732 CO2eq kg−1 FPCM, a much larger variation than estimated using spatially disaggregated statistical data. Emissions from enteric fermentation and those resulting from the production and supply of feed were the largest contributors to the CF of milk (44% and 36%, respectively). Dairy profits per cow averaged CA$4848 per year but ranged from CA$2530 to $7151 across sample farms. These financial returns were inversely correlated with the CF of milk production, suggesting that rather than a trade-off between GHG emissions intensity and economic performance, there is instead a synergy of the two sustainability indicators. Using a linear regression approach we find that a reduction in the CF of milk production can be achieved while simultaneously improving the profitability of dairy farms. This synergy was largely determined by farm characteristics related to livestock productivity (e.g. milk production per cow) and feeding practices (e.g. herd level total feed use and reliance on purchased feed). Our results suggest that in the absence of explicit GHG reduction policies targeting dairy farms, the main incentive for reducing farm-level GHG emissions could result from the economic pressure on farmers to increase their profitability per cow or per ha.

Relationships between soil fractions (their mass or carbon (C)) and soil organic carbon (SOC) have been used to develop central ideas in SOC research. However, few attempts have been made to quantify the relationship between SOC and all soil fractions, despite the potential for such an effort to address SOC stabilization processes. We identified 41 published studies that used diverse management techniques to cause a change in SOC concentration and disrupted soil into macroaggregates (>250 μm), free microaggregates (53–250 μm) and free silt + clay ( 250 μm, occluded microaggregates, and occluded silt + clay). We used linear hierarchical models to quantify relationships between mass, C concentration and total C of fractions and SOC. Soil mass redistribution toward macroaggregates was associated with SOC accumulation, however total microaggregate mass (free + occluded) did not increase with macroaggregate mass, as would be expected given de novo microaggregate formation within macroaggregates. Instead, high SOC soils exhibited a greater percent of total microaggregates occluded in macroaggregates. Occlusion in macroaggregates was also associated with increased C concentrations of microaggregates (35% higher, SE = 3.2) and silt + clay (30% higher, SE = 3.9) relative to their free counterparts. Taken together, these relationships suggest reduced macroaggregate turnover promotes SOC accumulation via the stabilization of C into occluded fractions. Rates of SOC increase with silt + clay C concentrations failed to increase with mean site-level SOC concentration, indicating of the studied soils (median SOC concentration = 14 g kg−1; max 68), SOC accumulation appears unlikely to be limited by C storage capacity in the silt + clay fraction. For each unit SOC gain, macroaggregates accounted for 83% (95% CI = 74, 91), and occluded microaggregates for 43% (95% CI = 33, 52), consistent relationships that have potential to be used as benchmarks for fraction-based SOC models.

Liquid dairy manure storages are sources of methane (CH), nitrous oxide (NO), and ammonia (NH) emissions. Both CH and NO are greenhouse gases (GHGs), whereas NH is an indirect source of NO emissions. Manure acidification is a strategy used to reduce NH emissions from swine manure; however, limited research has expanded this strategy to reducing CH and NO emissions by acidifying dairy manure. This study compared control dairy manure (pH 7.4) with two treatments of acidified manure using 70% sulfuric acid (HSO). These included a medium pH treatment (pH 6.5, 1.4 mL acid L manure) and a low pH treatment (pH 6, 2.4 mL acid L manure). Emissions were measured using replicated mesoscale manure tanks (6.6 m) enclosed by large steady state chambers. Both CH and NO were continuously measured (June-December 2017) using tunable diode laser trace gas analyzers. Ammonia emissions were measured three times weekly for 24 h using acid traps. On a CO equivalent basis, the medium pH treatment reduced total GHG emissions by 85%, whereas the low pH treatment reduced emissions by 88%, relative to untreated (control) manure. Total CH emissions were reduced by 87 and 89% from medium and low pH tanks, respectively. Ammonia emissions were reduced by 41 and 53% from medium and low pH tanks, respectively. Additional research is necessary to make acidification an accessible option for farmers by optimizing acid dosage. More research is need to describe the manure buffering capacity and emission reductions and ultimately find the best approaches for treating farm-scale liquid dairy manure tanks.

Dairy rotations rely on corn silage, which is estimated to have significant nitrous oxide (N2O) emissions. This study examined whether including legumes within rotations can reduce N2O emissions from the soil surface and dissolved in tile-drainage water. Emissions of N2O were measured from the soil surface and in tile drainage. Cropping systems were: corn–corn (CC), corn + cover crop-corn (C + cc), soybean–corn (SC) and alfalfa–alfalfa (AA) on a clay soil. Liquid dairy manure provided 2-year total N inversely related to legume cropping: 310 (CC), 280 (C + cc), 110 (SC), 50 kg N ha−1 (AA). Losses of N2O via tile drainage were 0.1–0.3% of total emissions. Ratios of N2O-N to NO3−-N in drainage were at least 63% lower than the IPCC default value (0.0075). Reductions of N2O emissions were only observed from established alfalfa in year 2. Compared to the SC treatment, which had the highest emissions in year 2, the AA treatment had 62% lower surface N2O and 88% lower dissolved N2O flux. Alfalfa had low yield in the first year, which led to high yield-scaled N2O emissions; thus, alfalfa may need to be grown 4 years to achieve a similar average yield scaled emission factor as CC. Silage corn had consistently high yield, averaging 317 kg ha−1 yr−1 for N yield, which was 36% higher than AA. As a result, CC had the lowest N2O emissions scaled by N-yield over the 2 years, averaging 2.6% of N-yield, which was 59% lower than AA on average.

Agricultural ecosystems are one of the largest global contributors to nitrate (NO3−) contamination of surface- and groundwater through fertilizer application. Improved fertilizer practices are needed to manage crop nutrient supply in corn (Zea mays L.) while minimizing impacts to clean water reserves. The goal of this study was to compare current nitrogen (N) fertilizer practices (urea at planting) with “packages” of improved management practices (a combination of right timing and product) that farmers potentially use. We conducted measurements in a continuous corn system from November 2015 to May 2017 at a large field scale (four 4 ha plots). Nitrate concentration was measured below the root zone and drainage estimated using a soil water budget approach in which evapotranspiration was measured using the eddy covariance method. The objective was to compare NO3−-N leaching from fields receiving urea vs. urea + combination of nitrification and urease inhibitors (NUI) fertilizer applications at planting, urea–ammonium nitrate (UAN) vs. UAN + NUI applied at sidedress, and a combination of these practices: urea + NUI at planting vs. UAN at sidedress. Drainage was only significant in the non-growing season. Neither fertilizer products applied with NUI at planting or sidedress proved to significantly reduce NO3−-N leaching. The combination of delaying fertilization to sidedress and applying UAN significantly reduced the soil water NO3−-N concentration compared with urea + NUI at planting (mean of 5.2 vs. 6.7 mg L−1) but only in 2015–2016. Based on these results, applying UAN at sidedress is recommended, although additional study years are needed to confirm those results.

Micrometeorological methods are ideally suited for continuous measurements of N2O fluxes, but gaps in the time series occur due to low-turbulence conditions, power failures, and adverse weather conditions. Two gap-filling methods including linear interpolation and artificial neural networks (ANN) were utilized to reconstruct missing N2O flux data from a corn–soybean–wheat rotation and evaluate the impact on annual N2O emissions from 2001 to 2006 at the Elora Research Station, ON, Canada. The single-year ANN method is recommended because this method captured flux variability better than the linear interpolation method (average R2 of 0.41 vs. 0.34). Annual N2O emission and annual bias resulting from linear and single-year ANN were compatible with each other when there were few and short gaps (i.e., percentage of missing values 20 d), the bias error in annual fluxes varied between 0.082 and 0.344 kg N2O-N ha−1 for linear and 0.069 and 0.109 kg N2O-N ha−1 for single-year ANN. Hence, the single-year ANN with lower annual bias and stable approach over various years is recommended, if the appropriate driving inputs (i.e., soil temperature, soil water content, precipitation, N mineral content, and snow depth) needed for the ANN model are available.

Greenhouse gas sampling from agricultural fields is laborious and time-consuming. Soil and topographical heterogeneity cause spatiotemporal variations, making nitrous oxide (N

Nitrous oxide (N

The positive effect of soil organic matter (SOM) on crop yield has historically been attributed to the ability of SOM to supply crops with nitrogen and water. Whether management-induced increases in SOM meaningfully supplement water supply has received recent scrutiny, introducing uncertainty to the mechanisms by which SOM benefits crops. Here, we posit that to benefit crops SOM does not need to increase the supply of a growth-limiting resource; it only needs to facilitate root access to extant resource stocks. We highlight evidence for the ability of SOM to alleviate negative impacts of inadequate aeration (mainly waterlogging) and compaction on roots. Waterlogging, even if transient, can permanently downregulate root biosynthesis and call for expensive growth of new roots. Management practices that promote SOM reduce waterlogging by accelerating water infiltration and may promote aeration in non-saturated soils. Compaction as a restriction to root development manifests in drying soils, when mechanical impedance (MI) inflates photosynthate required to extend root tips, leading to short, thick, and shallow roots. SOM reduces MI in dry soils and is associated with root channels to subsoil, granting crops access to deep soil water. Both waterlogging and compaction necessitate additional belowground investment per unit resource uptake. In this framework, crop response to SOM depends on interactions of crop susceptibility to inadequate aeration or compaction, soil moisture, and “baseline” soil aeration and compaction status. By exploring the proposition that SOM catalyzes resource uptake by permitting root development, future research may constrain crop yield improvements expected from SOM management.

Crops can uptake only a fraction of nitrogen from nitrogenous fertilizer, while losing the remainder through volatilization, leaching, immobilization and emissions from soils. The emissions of nitrogen in the form of nitrous oxide (N2O) have a strong potency for global warming and depletion of stratospheric ozone. N2O gets released due to nitrification and denitrification processes, which are aided by different environmental, management and soil variables. In recent years, researchers have focused on understanding and simulating the N2O emission processes from agricultural farms and/or watersheds by using process-based models like Daily CENTURY (DAYCENT), Denitrification-Decomposition (DNDC) and Soil and Water Assessment Tool (SWAT). While the former two have been predominantly used in understanding the science of N2O emission and its execution within the model structure, as visible from a multitude of research articles summarizing their strengths and limitations, the later one is relatively unexplored. The SWAT is a promising candidate for modeling N2O emission, as it includes variables and processes that are widely reported in the literature as controlling N2O fluxes from soil, including nitrification and denitrification. SWAT also includes three-dimensional lateral movement of water within the soil, like in real-world conditions, unlike the two-dimensional biogeochemical models mentioned above. This article aims to summarize the N2O emission processes, variables affecting N2O emission and recent advances in N2O emission modeling techniques in SWAT, while discussing their applications, strengths, limitations and further recommendations.

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 biogeochemical model, DNDCv.CAN, at three case-study locations in Canada, we quantified the impact of using commonly employed simplified modelling approaches on model estimates of crop yields, soil organic carbon (SOC) change and nitrogen (N) losses across 4 time periods (1981-2010, 2011-2040, 2041-2070, and 2071-2100). These approaches included using climate with only temperature and precipitation data, annual re-initialization of soil status, fixed fertilizer application rates, and fixed planting dates. These simplified approaches were compared to a more comprehensive reference approach that used detailed climate drivers, dynamic planting dates, dynamic fertilizer rates, and had a continuous estimation of SOC, N and water budgets. Alternative cultivars and rotational impacts were also investigated. At the semi-arid location, the fixed fertilizer, fixed planting date, and soil re-initialization approaches reduced spring wheat (Triticum aestivum L.) yield estimates by 40%, 25%, and 29%, respectively, in the 2071-2100 period relative to the comprehensive reference approach. At both sub-humid locations, the re-initialization of soil status significantly altered SOC levels, N leaching and N runoff in all three time periods from 2011 to 2100. At all locations, SOC levels were impacted when using simplified approaches relative to the reference approach, except for the fixed fertilizer approach at the sub-humid locations. Results indicate that simplified approaches often lack the necessary characterization of the feedbacks between climate, soil, crop and management that are critical for accurately assessing crop system behavior under future climate. We recommend that modellers improve their capabilities of simulating expected changes in agronomy over time and employ tools that consider robust soil-plant-atmospheric processes.

Cover cropping is a practice with potential to reduce post-harvest surplus of soil nitrate (NO3-), a mobile form of nitrogen naturally susceptible to losses. Increased soil NO3- leaching occurs when high soil NO3- coincides with high drainage events – a common occurrence during the non-growing season in cold and humid climates. The potential of cover crops to reduce NO3- leaching can be affected by the performance of the cover crop and by edaphic-climatic conditions (e.g., freeze-thaw cycles, soil type) and is subjected to interannual variation. Here, we evaluate soil type and crop rotation effects on soil parameters (i.e., NO3- concentration, temperature, water content) and on NO3- leaching under freeze-thaw conditions, using a high-frequency weighing lysimeter system. The soil type consisted of silt loam (SIL) and loamy sand (LS) soils and the crop rotation consisted of a rotation with a mixture of leguminous/non-leguminous cover crops (+CC) and no cover crop (-CC). This research was conducted during periods of 2017/2018 and 2018/2019 subjected to significant drainage. Our results indicated that cover crops did not affect drainage but affected soil temperature, with warmer soils observed over the winter when cover crops were used (+CC) than without cover-crops (-CC). Moreover, the cereal-crucifer-legume mixture after spring wheat reduced soil NO3- content by 80% compared to -CC during 2017/2018. For 2018/2019, due to poor establishment of the cereal-legume mixture under-seeded to corn, no reduction in soil NO3- content was observed. The reduction in soil NO3- in +CC plots for 2017/2018 translated to a significant reduction (by 67%) in NO3- leaching averaged across soil types. Soil drainage, NO3- content and NO3- leaching were not affected by soil type, an effect in part influenced by the boundary controls of the lysimeter system which mimicked soil conditions of a non-LS adjacent/reference field. To expand our results, we estimated the potential drainage of a hypothetical excessively drained LS (ED-LS) – a soil naturally subjected to high hydraulic conductivity and low water holding capacity. Overall, our results indicated that cover cropping can reduce NO3- leaching independent of soil type but the effect can be pronounced for ED-LS.

Quantification of soil organic carbon (SOC) pool fractions under different tillage systems is important in understanding SOC dynamics and storage. Two major pools of SOC that can be isolated are the light (LF) and heavy fractions (HF). Few studies have quantified the effect of tillage systems on the hydrolysable (HYF) and non-hydrolysable fractions (NHF) which comprise the HF. The objective of this study was to evaluate if there were significant changes in the quantity and δ13C of the HF, HYF, and NHF fractions of SOC after six years of no-tillage (NT), on arable soils that were previously under conventional tillage (CT). Our study used 13C natural abundance (rotation of C3 and C4crops) on a calcareous Typic Hapludalf soil in southern Ontario, Canada. The HF (>1.7 g cm−3) was isolated using density fractionation and separated into its HYF and NHF using acid hydrolysis (6 M HCl) for three soil depths: 0–10, 10–20, and 20–30 cm. The HF pool (90–93% of SOC) was significantly greater (P

Anaerobic digestion (AD) and solid-liquid separation (SLS) are manure treatment strategies used on dairy farms. These treatments change manure characteristics, such as pH, dry matter, and total ammoniacal nitrogen (TAN) which affect ammonia (NH3) emissions after field application. This study used eight wind tunnels (1 m2 each) to compare the effects of application season and dairy manure treatment (AD vs SLS) on NH3 emissions. The highest cumulative NH3 emissions were seen in the spring from the AD manure treatment, which had higher TAN and pH compared to SLS. On the other hand, when normalized by TAN application rate there was no significant difference between AD and SLS manure in either spring (52 and 54% of TAN after 22 d, respectively) or fall (26% and 27% of TAN after 15 d, respectively). This suggests that if farmers adjusted application rates based on TAN content, NH3 emissions from applied AD manure could be minimized. Results were compared to the Ammonia Loss from Field Applied Manure (ALFAM) model. The model characterized the temporal pattern of emissions reasonably well in spring, but not fall. The model generally overestimated NH3 emissions during the first 24 h after application, and underestimated emissions after incorporation from day 2 to 22.

Conventional manure storages are an important source of methane (CH4), a potent greenhouse gas. Anaerobic digestion is an alternative manure management practice potentially able to provide environmental benefits, including the reduction of CH4 emissions from slurry storage. This study was conducted at a commercial farm in Ontario where a biodigester system became operational in May 2012. The purpose was to quantify year-round CH4 emissions from a digestate storage tank, examine the relationship between emissions and its driving factors, and compare these results to a similar emissions dataset from untreated manure measured during one year before the biodigester became operational. A micrometeorological mass balance approach was used to measure CH4 fluxes. Total annual CH4 emissions from digestate were 1.0 kg m−3 y−1, which was 85% lower compared to untreated manure. Monthly average volatile solids (VS) mass in the storage tank was 73 ± 24 Mg for digestate and 107 ± 30 Mg for manure, representing a 32% VS reduction in the tank, suggesting that lower emissions were not only due to VS mass reduction after biodigestion and solid-liquid separation. The annual CH4 emissions scaled by VS were 26 g kg−1 VS y−1 for digestate and 76 g kg−1 VS y−1 for manure, suggesting that VS in the digestate were less suitable for CH4 production (less digestible). This was also verified when investigating the relationship between fluxes and its driving factors: VS concentration did not correlate with CH4 emissions per volume for digestate (r = 0.37; p = 0.29), but did for untreated manure (r = 0.95; p = 0.002). However, the correlation of temperature with emission was stronger for digestate than manure at all depths with no lag, especially at 2 m depth (r = 0.98, p

The effects of manure management practices on ammonia (NH3) emissions were evaluated using a micrometeorological technique at four contrasting dairy storage facilities: untreated raw manure slurry (RM), solid-liquid separation with storage of separated liquids (SL), anaerobic digestion of manure and off-farm materials (AD), and anaerobic digestion with solid-liquid separation and storage of the liquid fraction (ADL). Annual average NH3 emissions per surface area were lowest for RM (2.7 g m−2 d−1), followed by SL (4.5 g m−2 d−1), AD (10.0 g m−2 d−1), and ADL (15.5 g m−2 d−1). Lower NH3 emissions from the RM storage were partly due to the 30 cm thick surface crust which formed on the storage surface in summer (wood shavings was used as bedding). Greater surface crusting at the AD storage compared to the ADL storage was also likely the reason for higher emissions at the ADL storage. Relationships between NH3 emissions, temperature, and wind-speed were observed at all sites but were strongest at sites with minimal crusting (SL, ADL) and weak at the RM storage with a crust cover. Total NH3 emissions from each storage facility (kg y−1) did not simply track the differences in fluxes; rather, facilities with greater storage (RM, AD, ADL) had higher emissions than the facility with less storage (SL) due to removal of solids and more frequent field application. Overall, bedding material, manure processing, and storage management all have important effects on NH3 emissions from manure storage.

Liquid dairy manure storage is favourable for methane (CH4) production and a significant source of this greenhouse gas. Manure storage in cold climates faces large temperature variations over the course of a year, and added on-farm complexities in manure loading require year-round measurements which are currently lacking. The objectives of this study were to 1) quantify CH4 emissions from farm-scale liquid dairy manure storage in a cold climate, 2) investigate the effect of manure temperature on CH4 emissions, and 3) compare measured CH4 emissions with values derived from the USEPA temperature model. Methane fluxes were measured from Aug 2010 to early Nov 2011 on a commercial farm in Ontario, Canada, using a micrometeorological mass balance method which relied on 3 towers with air intakes at 4 heights placed around the storage tank. Manure temperature and volatile solid content (VS) were also measured. Monthly CH4 emissions scaled by VS decreased from 43.8 g CH4 kg−1 VS in Sep 2010 to 5.3 g CH4 kg−1 VS in Jan 2011, and were correlated with temperature (r2 = 0.94). Manure temperature increased starting in Feb 2011, but the increase in CH4 emissions was delayed to Jul 2011. Hence, the response of CH4 emissions to temperature showed a hysteretic pattern where emissions in the warming branch after the winter (Apr-Jun) were significantly lower than emissions in the cooling branch after the summer (Sep-Nov) despite similar temperatures. The temperature model predicted emissions during the cooling phase well, but overpredicted emissions during the warming phase, indicating other limiting factors for microbial CH4 production. Thus, the annual predicted CH4 emissions were about 2.3× larger than the measured values. The newly observed hysteresis effect should be considered when predicting CH4 emissions from stored manure.

Stored liquid dairy manure is a hotspot for methane (CH) emission, thus effective mitigation strategies are required. We assessed sodium persulfate (NaSO), potassium permanganate (KMnO), and sodium hypochlorite (NaOCl) for impacts on the abundance of microbial communities and CH production in liquid dairy manure. Liquid dairy manure treated with different rates (1, 3, 6, and 9 g or mL L slurry) of these chemicals or their combinations were incubated under anoxic conditions at 22.5 ± 1.3°C for 120 d. Untreated and sodium 2-bromoethanesulfonate (BES)-treated manures were included as negative and positive controls, respectively, whereas sulfuric acid (HSO)-treated manure was used as a reference. Quantitative real-time polymerase chain reaction was used to quantify the abundances of bacteria and methanogens on Days 0, 60, and 120. Headspace CH/CO ratios were used as a proxy to determine CH production. Unlike bacterial abundance, methanogen abundance and CH/CO ratios varied with treatments. Addition of 1 to 9 g L slurry of NaSO and KMnO reduced methanogen abundance (up to ∼28%) and peak CH/CO ratios (up to 92-fold). Except at the lowest rate, chemical combinations also reduced the abundance of methanogens (up to ∼17%) and CH/CO ratios (up to ninefold), although no impacts were observed when 3% NaOCl was used alone. With slurry acidification, the ratios reduced up to twofold, whereas methanogen abundance was unaffected. Results suggest that NaSO and KMnO may offer alternative options to reduce CH emission from stored liquid dairy manure, but this warrants further assessment at larger scales for environmental impacts and characteristics of the treated manure.

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 were utilized to evaluate the performance of three models for their water partitioning capabilities: denitrification–decomposition (DNDC), Holos, and versatile soil moisture budget (VSMB). To assess the likely model performance at an upscaled national level, the models were applied at the site level with no water component-specific calibration. Evapotranspiration (ET) was found to be the dominate component of the water budget at the prairie sites (89%–149% of precipitation) (i.e., in comparison to runoff, tile drainage, and deep percolation), while both ET (37%–73% of precipitation) and drainage (19%–61% of precipitation) represented most of the water outflow bud...

Agro-ecosystem models, such as the DNDC (DeNitrification and DeComposition) model are useful tools when assessing the sustainability of agricultural management. Accuracy in soil temperature estimations is important as it regulates many important soil biogeochemical processes that lead to greenhouse gas emissions (GHG). The objective of this study was to account for the effects of snow cover in terms of the measured snow depth (mm of water), soil texture and crop management in temperate latitudes in order to improve the surface soil temperature mechanism in DNDC and thereby improve GHG predictions. The estimation of soil temperature driven by the thermal conductivity and heat capacity of the soil was improved by considering the soil texture under frozen and unfrozen conditions along with the effects of crop canopy and snow depth. Calibration of the developed model mechanisms was conducted using data from Alfred, ON under two contrasting soil textures (sandy loam vs. clay). Independent validation assessments were conducted using soil temperatures at different depths for contrasting managements for two field sites located in Canada (Guelph, ON and Glenlea, MB). The validation results indicated high model accuracy (R 2 > 0.90, EF ≥ 0.90, RMSE 2 O emissions during spring thaw and provide a foundation for future studies aimed at improving simulations in DNDC for better representations of other biogeochemical processes.

Nitrous oxide (N2O) fluxes measured using the eddy-covariance method capture the spatial and temporal heterogeneity of N2O emissions. Most closed-path trace-gas analyzers for eddy-covariance measurements have large-volume, multi-pass absorption cells that necessitate high flow rates for ample frequency response, thus requiring high-power sample pumps. Other sampling system components, including rain caps, filters, dryers, and tubing, can also degrade system frequency response. This field trial tested the performance of a closed-path eddy-covariance system for N2O flux measurements with improvements to use less power while maintaining the frequency response. The new system consists of a thermoelectrically cooled tunable diode laser absorption spectrometer configured to measure both N2O and carbon dioxide (CO2). The system features a relatively small, single-pass sample cell (200 mL) that provides good frequency response with a lower-powered pump ( ∼ 250 W). A new filterless intake removes particulates from the sample air stream with no additional mixing volume that could degrade frequency response. A single-tube dryer removes water vapour from the sample to avoid the need for density or spectroscopic corrections, while maintaining frequency response. This eddy-covariance system was collocated with a previous tunable diode laser absorption spectrometer model to compare N2O and CO2 flux measurements for two full growing seasons (May 2015 to October 2016) in a fertilized cornfield in Southern Ontario, Canada. Both spectrometers were placed outdoors at the base of the sampling tower, demonstrating ruggedness for a range of environmental conditions (minimum to maximum daily temperature range: −26.1 to 31.6 °C). The new system rarely required maintenance. An in situ frequency-response test demonstrated that the cutoff frequency of the new system was better than the old system (3.5 Hz compared to 2.30 Hz) and similar to that of a closed-path CO2 eddy-covariance system (4.05 Hz), using shorter tubing and no dryer, that was also collocated at the site. Values of the N2O fluxes were similar between the two spectrometer systems (slope = 1.01, r2 = 0.96); CO2 fluxes as measured by the short-tubed eddy-covariance system and the two spectrometer systems correlated well (slope = 1.03, r2 = 0.998). The new lower-powered tunable diode laser absorption spectrometer configuration with the filterless intake and single-tube dryer showed promise for deployment in remote areas.

Soil freeze-thaw (FT) and dry-wet (DW) cycles are brief transitory biophysical changes, but these events have important implications in determining the timing and magnitude of N2O emissions and may represent a significant proportion of annual N2O emissions from agricultural systems. It is often assumed that FT and DW cycles influence the processes of N2O production and emission in a similar manner, however, research has yet to systematically identify the similarities and differences in the mechanisms which lead to potentially higher N2O fluxes during FT compared to DW cycles. Herein, we present the first review to do so; in addition, we identify strategic research areas required for improving the understanding of FT and DW processes leading to N2O emissions. There are key differences between the mechanisms that contribute to N2O fluxes during FT and DW cycles, centered on the duration and spatial extent of anaerobiosis, temperature sensitivity of microbial activity, relative gas diffusivity, and soil water dynamics. These differences might increase the risk of N2O emissions during FT cycles relative to soil DW cycles. Current research gaps include (i) the identification of organic substrates made available due to FT and DW cycles, and their contribution to ensuing N2O fluxes, (ii) an understanding of how cryosuction dynamics potentially influence N2O production and emission, (iii) understanding and predicting the air-entry potential of soil as it relates to N2O fluxes, (iv) identifying the relative significance of dissolved N2O in soil water and its solubility changes during FT and DW phases, and (v) determining microbial community and functional changes across soil spatial and temporal scales. Advances in these areas are recommended for improving process descriptions in biogeochemical models in order to more accurately predict N2O emissions from soils prone to FT and DW cycles.