Spring Thaw Research Articles

Response of forage plants to alteration of temperature and spring thaw date: implications for geese in a warming Arctic

AbstractChanges in summer temperatures in Arctic Alaska have led to longer and warmer growing seasons over the last three decades. Corresponding with these changes in climate, the abundance and distributions of geese have increased and expanded over the same period. We used an experimental approach to assess the response of goose forage plants to simulated environmental change. We subjected Carex subspathacea, a preferred goose forage growing on the Arctic Coastal Plain (ACP) of Alaska, to manipulations of temperature and timing of spring thaw to measure potential effects in terms of plant nitrogen concentration, aboveground biomass, and total nitrogen availability. Carex subspathacea responded to warming in a dynamic fashion. Increases in temperature led to decreases in leaf nitrogen concentration but increases in aboveground biomass. The increase in biomass was stronger than the decline in nitrogen concentration such that total nitrogen availability was increased with temperature for the first 35–40 d of the season. Grazing removal accounted for only minimal offtake of biomass, and we found no indication that grazing maintained elevated levels of nitrogen concentration longer in the season as reported in other studies. Based on demonstrated relationships in the literature between forage nitrogen concentrations and gosling growth rates, we conclude that there is currently abundant high‐quality forage available across the ACP. This finding fits with recent evidence of high gosling growth rates and increasing trends in goose abundance on the ACP. Our results suggest that with climate warming of a few degrees, nitrogen concentration of forage may decrease, but forage biomass and total nitrogen availability will increase. Our data suggest that nitrogen concentration will not fall below the minimum threshold required by geese in the near future. As such, we suggest that there is currently no bottom‐up limitation to goose numbers on the ACP.

Hydrological and catchment controls on event‐scale dissolved organic carbon dynamics in boreal headwater streams

AbstractHydrological events transport large proportions of annual or seasonal dissolved organic carbon (DOC) loads from catchments to streams. The timing, magnitude and intensity of these events are very sensitive to changes in temperature and precipitation patterns, particularly across the boreal region where snowpacks are declining and summer droughts are increasing. It is important to understand how landscape characteristics modulate event‐scale DOC dynamics in order to scale up predictions from sites across regions, and to understand how climatic changes will influence DOC dynamics across the boreal forest. The goal of this study was to assess variability in DOC concentrations in boreal headwater streams across catchments with varying physiographic characteristics (e.g., size, proportion of wetland) during a range of hydrological events (e.g., spring snowmelt, summer/fall storm events). From 2016 to 2017, continuous discharge and sub‐daily chemistry grab samples were collected from three adjacent study catchments located at the International Institute for Sustainable Development‐Experimental Lakes Area in northwestern Ontario, Canada. Catchment differences were more apparent in summer and fall events and less apparent during early spring melt events. Hysteresis analysis suggested that DOC sources were proximal to the stream for all events at a catchment dominated by a large wetland near the outlet, but distal from the stream at the catchments that lacked significant wetland coverage during the summer and fall. Wetland coverage also influenced responses of DOC export to antecedent moisture; at the wetland‐dominated catchment, there were consistent negative relationships between DOC concentrations and antecedent moisture, while at the catchments without large wetlands, the relationships were positive or not significant. These results emphasize the utility of sub‐daily sampling for inferring catchment DOC transport processes, and the importance of considering catchment‐specific factors when predicting event‐scale DOC behaviour.

Spring thaw pulses decrease annual N2O emissions reductions by nitrification inhibitors from a seasonally frozen cropland

Nitrification inhibitors (NIs) have been widely demonstrated to reduce soil nitrous oxide (N2O) and nitric oxide (NO) emissions from nitrogen (N)-fertilized croplands. However, few studies have evaluated the efficacy of NIs during the cold nongrowing season, especially the spring thaw – a period that may dominate the annual emissions. We conducted an experiment to examine the effects of three types of NIs (DCD, DMPP, and nitrapyrin) on soil N2O and NO emissions from a seasonally frozen cropland in northeast China in two experimental years with contrasting snowfall. In 2017–2018, DCD significantly decreased growing season N2O emissions by 54%, DMPP achieved a non-significant reduction of 32% but nitrapyrin had no inhibition effect. In the winter following this growing season, there was high snowfall and large pulses of N2O fluxes during spring thaw were observed across all treatments totaling 1.1–4.2 kg N ha−1 and contributing 54–76% of annual emissions. NIs did not significantly affect the spring thaw emissions, which partly offset the decreased emissions during growing season, leading to an overall neutral effects of DCD and DMPP on N2O emissions when accounting for a complete year. In 2018–2019, there was less snowfall and spring thaw N2O emissions totaled just 0.32–0.64 kg N ha−1 and contributed to only 13–40% of annual emissions. All three types of NIs significantly decreased the annual N2O emissions by 37–55%. Yet, this annual reduction was lower than that during the growing season (56–66%) due to the inefficacy of NIs to abate the spring thaw emissions. In particular, nitrapyrin significantly increased the spring thaw N2O emissions by 81% probably owing to higher residual fertilizer-N and carbon availibility. In contrast to N2O, NO fluxes during spring thaw were negligible in all years, and NIs application significantly decreased the annual NO emissions by 68–86% (except for nitrapyrin in 2017–2018). Low NO/N2O ratios and positive relationships of N2O fluxes with soil moisture and nitrate suggested that freeze–thaw induced N2O production mainly from denitrification, which might be stimulated by soil moisture from melting snow. Overall, our results highlight that changes in winter weather conditions, and particularly snow dynamics, could create large uncertainties in assessing the efficacy of soil N-oxide emissions mitigation strategies under climate change.

Characterization of spring thaw and its relationship with carbon uptake for different types of southern boreal forest

The timing of spring thaw is of great biological and hydrological significance in seasonally frozen boreal forests, and may significantly vary for different forest types because of variability in canopy architecture, forest floor characteristics, and soil types. This study explores inter-site variability of spring thaw and its controlling factors between two boreal coniferous (jack pine and black spruce) and one deciduous (aspen) forest sites located in Western Canada. The linkages between spring thaw and carbon uptake were also investigated. Long-term (1998 to 2015) observations of snowfall, snow water equivalent (SWE), snow temperature, soil temperature, soil water content, and CO2 fluxes were analyzed. Average annual peak SWE was 112±27, 98±22, and 93±23 mm for aspen, jack pine and black spruce sites, respectively. Snow accumulation was 15% to 20% higher for the deciduous forest site than for the coniferous forest sites despite similar seasonal snowfall of 117–122 mm. The onset of snowmelt, soil thaw start date and the time to complete snow ablation were quite similar across sites but the differences in soil thaw end date were large. Completion of soil thaw at the aspen site was about 18 and 30 days earlier than the jack pine and black spruce sites, respectively. An earlier soil thaw completion at the aspen site was likely driven by the higher sub-canopy net radiation because of the leafless canopy in spring. Between the two coniferous forest sites, soil thaw completion was delayed by about 2 weeks at the black spruce site where the thicker forest floor (ground cover i.e. moss/lichen and organic soil layer) caused higher ice content and also provided better insulation to the underlying soils. Onset and net annual carbon uptake were strongly correlated with snowmelt start and end dates as well as with soil thaw start and end dates for the coniferous forest sites but the correlations were not statistically significant for the aspen site. This study advances our understanding about the variability of spring thaw, its dynamics and controls, and its relationship to carbon uptake for different forest types in the southern boreal forest.

Comparison of the Bearing Capacity of Pavement Structures with Unbound and Cold Central-Plant Recycled Base Courses Based on FWD Data

Bearing capacity changes over the year, depending on the water content in a pavement structure: the higher the water content, the lower the bearing capacity. As expected, the highest water content in a pavement structure is observed in the early spring as the ice lenses melt. Thus, spring is a critical period for pavement performance, because a decrease in bearing capacity results in faster pavement deterioration. The bearing capacity of pavement structures with an unbound base course and the negative effect of spring thawing on pavement performance have been analyzed by a considerable number of researchers. However, very little is known about the bearing capacity of pavement structures with a cold-recycled base course despite the significantly increasing usage of cold-recycled mixtures. This paper focuses on the bearing capacity of both unbound and cold central-plant recycled base courses at different seasons and their stability. A cold central-plant recycled (CCPR) base course was constructed from a mixture of 38.8% reclaimed asphalt pavement (RAP), 3.1% foamed bitumen and 2.3% cement. A virgin aggregate was added to achieve desirable aggregate gradation. The bearing capacity of the unbound and CCPR base layers, as well as the whole pavement structure, was evaluated by back-calculated E moduli from falling weight deflectometer (FWD) data. In addition to this, the residual pavement life was calculated using mechanistic-empirical pavement design principles. The results showed that the durability of pavement structures with a CCPR base course is more than seven times lower compared to that of pavement structures with an unbound base course, irrespective of season. Nevertheless, the bearing capacity (surface modulus E0) of the pavement structure with a CCPR base course gradually increases due to the curing processes of bituminous and hydraulic binders (in this study, within four years of operation, it increased by 28–47%, depending on the side of the road).

Delay in Arctic Sea Ice Freeze-Up Linked to Early Summer Sea Ice Loss: Evidence from Satellite Observations

The past decades have witnessed a rapid loss of the Arctic sea ice and a significant lengthening of the melt season. The years with the lowest summertime sea ice minimum were found to be accompanied by the latest freeze-up onset on record. Here, a synthetic approach is taken to examine the connections between sea ice melt timing and summer sea ice evolution from the remote sensing perspective. A 40-year (1979–2018) satellite-based time-series analysis shows that the date of autumn sea ice freeze-up is significantly correlated with the sea ice extent in early summer (r = −0.90, p < 0.01), while the spring melt onset is not a promising predictor of summer sea ice evolution. The delay in Arctic sea ice freeze-up (0.61 days year−1) in the Arctic was accompanied by a decline in surface albedo (absolute change of −0.13% year−1), an increase in net short-wave radiation (0.21 W m−2 year−1), and an increase in skin temperature (0.08 °C year−1) in summer. Sea ice loss would be the key reason for the delay in autumn freeze-up, especially in the Laptev, East-Siberian, Chukchi and Beaufort Seas, where sea ice has significantly declined throughout the summer, and strong correlations were found between the freeze-up onset and the solar radiation budget since early summer. This study highlights a connection between the summer sea ice melting and the autumn refreezing process through the ice-albedo feedback based on multisource satellite-based observations.

Identifying hotspots and representative monitoring locations of field scale N2O emissions from agricultural soils: A time stability analysis

Greenhouse gas sampling from agricultural fields is laborious and time-consuming. Soil and topographical heterogeneity cause spatiotemporal variations, making nitrous oxide (N2O) estimation and management a challenge. Identification of representative monitoring locations, hotspots, and coldspots could facilitate the mitigation of agricultural N2O emissions. The objective of this study was to identify and characterize representative monitoring locations, hotspots, and coldspots of N2O emissions in agricultural fields (Baggs farm; BF and Research North farm; RN) in Cambridge, Ontario, Canada, under humid continental climate. Soil in both fields was classified as Orthic Melanic Brunisol, with some areas categorized as Gleyed Brunisolic Gray Brown Luvisol and Orthic Humic Gleysol. In total, 28 sampling points were selected following conditional Latin hypercube design using topographical parameters (digital elevation, slope, topographical wetness index, and Pennock landform classification). Gas samples were collected over a two-year crop rotation with corn (2019) and soybean (2020). Additional sampling was conducted at BF at spring thaw (2020). Time stability analysis using mean relative difference (MRD) and standard deviation of mean relative difference (SDRD) was performed to test the hypothesis that “simultaneous analysis of spatiotemporal variations in N2O emissions could help to identify and characterize representative monitoring locations, hotspots, coldspots and areas with few hot and cold moments. Most of the hotspots were located at shoulder positions, coldspots, and cold moments at backslope, and representative monitoring points were located at leveled positions or localized depressions. Time stability analysis coupled with multivariate groping analysis supported our hypothesis and helped successfully identify hotspots, coldspots, and representative locations based on landform classification with few exceptions. However, inclusion of additional topographical (curvature, contributing area, aspect) and morphological parameters (texture, thickness of soil horizon, depth to bedrock, and water table) are suggested for consideration in future research to manage variable-rate fertilizer application and mitigate N2O hotspots at landscape level.

Spatial–temporal variations in riverine carbon strongly influenced by local hydrological events in an alpine catchment

Abstract. Headwater streams drain >70 % of global land areas but are poorly monitored compared with large rivers. The small size and low water buffering capacity of headwater streams may result in a high sensitivity to local hydrological alterations and different carbon transport patterns from large rivers. Furthermore, alpine headwater streams on the “Asian water tower”, i.e., Qinghai–Tibetan Plateau, are heavily affected by thawing of frozen soils in spring as well as monsoonal precipitation in summer, which may present contrasting spatial–temporal variations in carbon transport compared to tropical and temperate streams and strongly influence the export of carbon locked in seasonally frozen soils. To illustrate the unique hydro-biogeochemistry of riverine carbon in Qinghai–Tibetan headwater streams, here we carry out a benchmark investigation on the riverine carbon transport in the Shaliu River (a small alpine river integrating headwater streams) based on annual flux monitoring, sampling at a high spatial resolution in two different seasons and hydrological event monitoring. We show that riverine carbon fluxes in the Shaliu River were dominated by dissolved inorganic carbon, peaking in the summer due to high discharge brought by the monsoon. Combining seasonal sampling along the river and monitoring of soil–river carbon transfer during spring thaw, we also show that both dissolved and particulate forms of riverine carbon increased downstream in the pre-monsoon season due to increasing contribution of organic matter derived from thawed soils along the river. By comparison, riverine carbon fluctuated in the summer, likely associated with sporadic inputs of organic matter supplied by local precipitation events during the monsoon season. Furthermore, using lignin phenol analysis for both riverine organic matter and soils in the basin, we show that the higher acid-to-aldehyde (Ad/Al) ratios of riverine lignin in the monsoon season reflect a larger contribution of topsoil likely via increased surface runoff compared with the pre-monsoon season when soil leachate lignin Ad/Al ratios were closer to those in the subsoil than topsoil solutions. Overall, these findings highlight the unique patterns and strong links of carbon transport in alpine headwater catchments with local hydrological events. Given the projected climate warming on the Qinghai–Tibetan Plateau, thawing of frozen soils and alterations of precipitation regimes may significantly influence the alpine headwater carbon transport, with critical effects on the biogeochemical cycles of the downstream rivers. The alpine headwater catchments may also be utilized as sentinels for climate-induced changes in the hydrological pathways and/or biogeochemistry of the small basin.

A workflow to address pitfalls and challenges in applying machine learning models to hydrology

Data-driven modeling with machine learning (ML) algorithms in hydrologic modeling and forecasting suffers a number of pitfalls and challenges, including variable selection bias, resubstitution validation, inconsistent validation processes for different algorithms and model selection using the test set. They lead to incorrect model development and biased, overly optimistic performance estimates – and thus, unreliable models. This study presents a novel model building and testing workflow that addresses common machine learning (ML) challenges and pitfalls. The presented workflow incorporates optional variable transformation and preprocessing techniques, and applies to various ML model types, variable selection algorithms and resampling techniques. We demonstrate its performance through streamflow forecasting for the Bow River Basin, Alberta, Canada, using four conventional ML algorithms (ANN, SVM, ELM and RBF networks) driven by local hydrometeorological conditions and large-scale climate indices. Using the cross-validation average out-of-sample results and a separate test set, the prediction accuracy estimate bias (the relative difference between the model performance estimated using the validation sets and a separate test set) was empirically estimated to be 5.6%, 4.4%, 2.5% and 3.0% for the Seasonal, May, June and July models, respectively. In addition, the streamflow forecasting models had an average coefficient of determination of 0.85. Preprocessing and dimensionality reduction through principal component analysis (PCA) was detrimental to prediction accuracy. Snow water equivalent from individual snow courses proved the most important predictor for Bow River streamflow, while global climate indices, including the PDO, AMO and PNA, increased the Nash–Sutcliffe efficiency by 6% to 50%. Finally, although forecasting skill decreased with increasing forecast lead time, satisfactory forecasts (NSE>0.5) could be obtained two months in advance of the spring melt, at the end of February. Extensions of this study should address the tendency of different variable selection algorithms to pick irrelevant or redundant predictors after changes in training data.

Intra- and Inter-Annual Variability in the Dissolved Inorganic Nitrogen in an Urbanized River before and after Wastewater Treatment Plant Upgrades: Case Study in the Grand River (Southwestern Ontario)

External nitrogen (N) inputs originating from human activities act as essential nutrients accumulation in aquatic ecosystems or it is exported elsewhere, where the assimilation capacity is surpassed. This research presents a multi-annual case study of the dissolved inorganic nitrogen (DIN) in an urban river in Ontario (Canada), assessed changes in N downstream of the largest wastewater treatment plant (WTP) in the watershed. Changes in the DIN effluent discharge, in-river concentrations and loads were observed comparing the intra- and inter-annual variability (2010–2013) before, during and after WTP upgrades. These upgrades reduced the ammonium concentration in the river from 0.44 to 0.11 mg N-NH4+/L (year average), but the N load in the effluent increased. In the river, nitrate and ammonium concentrations responded to seasonal variability, being higher during the low temperature (>10 °C) and high flow seasons (spring and spring melt). Among years, changes in the DIN concentration are likely controlled by the effluent to river dilution ratio, which variability resides on the differences in river discharge between years. This suggest that the increasing trend in the DIN concentration and loads are the result of agricultural and urban additions, together with reduced N assimilation, in addition to N loads responding to variable river discharge. Finally, we propose monitoring both concentrations and loads, as they provide answers to different questions for regulatory agencies and water managers, allowing tailored strategies for different purposes, objectives and users.

Temperature and discharge variations in natural mineral water springs due to climate variability: a case study in the Piedmont Alps (NW Italy).

In the context of global climate change, understanding the relationships between climate and groundwater is increasingly important. This study in the NW Alps represents the first regional-scale investigation of the groundwater feature variation in mountain aquifers due to climate variability. The analysis of groundwater temperature and discharge in 28 natural mineral water springs and meteorological parameters (rainfall and air temperature) permitted us to evaluate the annual behaviour and possible trends of these parameters during the period from 2001 to 2018. The air temperature showed a positive trend almost everywhere, with a rise of up to 0.03 °C/year. In contrast, only ten springs showed a positive trend for groundwater temperature, but with the smallest rates of increase. Moreover, despite the substantial stability of the rainfall amount, 50% of the analysed springs showed a trend (29 and 21% for positive and negative trends, respectively) with low discharge variations. Finally, cross-correlation analyses proved the close relationship between air and groundwater temperatures, with a time lag between 0 and 3 months, and between spring discharge and air temperature, with a time lag between 1 and 3 months. In particular, spring discharge is closely connected to snow melting in spring and subordinate to rainfall. These results highlight the existing correlations between spring discharge and various meteorological and topographic parameters in the studied mountain area and provide a preliminary framework of the impacts of climatic variability on the availability and temperature of the exploited water resources.Supplementary InformationThe online version contains supplementary material available at 10.1007/s10653-021-00864-8.

Study on the Mechanical Damage Characteristics of Asphalt Concrete in the Spring Thawing Environment

Abstract Moisture damage under freeze-thaw cycles is one of several serious pavement distresses faced by the majority of transportation agencies. This phenomenon triggers several pavement distresses, thus necessitating pavement maintenance and rehabilitation, which costs the country billions of dollars. In this article, a freeze-soak-scour cycle test was designed to simulate the special environment of the spring thawing season, and the evolution of mechanical properties of the asphalt concrete (AC-16) was studied. Moreover, the influence of freezing, soaking, and scouring (i.e., three separate factors on the mechanical properties of AC-16) were discussed based on the gray relational degree theory. The results illustrated that the freeze factor had a more significant impact on the damage process of AC-16 compared with the soak and scour factor. Finally, the freeze-soak-scour damage model of AC-16 was established and the damage speed and damage degree of AC was quantified based on the logistic judgment model. The model parameter Amax has been used to evaluate the damage degree of the mechanical performance of the AC-16, and model parameter x0.5 has been used to evaluate the damage speed of the mechanical performance of the AC-16.

The Genomic Capabilities of Microbial Communities Track Seasonal Variation in Environmental Conditions of Arctic Lagoons.

In contrast to temperate systems, Arctic lagoons that span the Alaska Beaufort Sea coast face extreme seasonality. Nine months of ice cover up to ∼1.7 m thick is followed by a spring thaw that introduces an enormous pulse of freshwater, nutrients, and organic matter into these lagoons over a relatively brief 2–3 week period. Prokaryotic communities link these subsidies to lagoon food webs through nutrient uptake, heterotrophic production, and other biogeochemical processes, but little is known about how the genomic capabilities of these communities respond to seasonal variability. Replicate water samples from two lagoons and one coastal site near Kaktovik, AK were collected in April (full ice cover), June (ice break up), and August (open water) to represent winter, spring, and summer, respectively. Samples were size fractionated to distinguish free-living and particle-attached microbial communities. Multivariate analysis of metagenomes indicated that seasonal variability in gene abundances was greater than variability between size fractions and sites, and that June differed significantly from the other months. Spring (June) gene abundances reflected the high input of watershed-sourced nutrients and organic matter via spring thaw, featuring indicator genes for denitrification possibly linked to greater organic carbon availability, and genes for processing phytoplankton-derived organic matter associated with spring blooms. Summer featured fewer indicator genes, but had increased abundances of anoxygenic photosynthesis genes, possibly associated with elevated light availability. Winter (April) gene abundances suggested low energy inputs and autotrophic bacterial metabolism, featuring indicator genes for chemoautotrophic carbon fixation, methane metabolism, and nitrification. Winter indicator genes for nitrification belonged to Thaumarchaeota and Nitrosomonadales, suggesting these organisms play an important role in oxidizing ammonium during the under-ice period. This study shows that high latitude estuarine microbial assemblages shift metabolic capabilities as they change phylogenetic composition between these extreme seasons, providing evidence that these communities may be resilient to large hydrological events in a rapidly changing Arctic.

The Role of Basin Geometry in Mountain Snowpack Responses to Climate Change

Snowmelt contributions to streamflow in mid-latitude mountain basins typically dominate other runoff sources on annual and seasonal timescales. Future increases in temperature and changes in precipitation will affect both snow accumulation and seasonal runoff timing and magnitude, but the underlying and fundamental roles of mountain basin geometry and hypsometry on snowmelt sensitivity have received little attention. To investigate the role of basin geometry in snowmelt sensitivity, a linear snow accumulation model and the Cold Regions Hydrological Modeling (CRHM) platform driven are used to estimate how hypsometry affects basin-wide snow volumes and snowmelt runoff. Area-elevation distributions for fifty basins in western Canada were extracted, normalized according to their elevation statistics, and classified into three clusters that represent top-heavy, middle, and bottom-heavy basins. Prescribed changes in air temperature alter both the snow accumulation gradient and the total snowmelt energy, leading to snowpack volume reductions (10–40%), earlier melt onsets (1–4 weeks) and end of melt season (3 weeks), increases in early spring melt rates and reductions in seasonal areal melt rates (up to 50%). Basin hypsometry controls the magnitude of the basin response. The most sensitive basins are bottom-heavy, and have a greater proportion of their area at low elevations. The least sensitive basins are top-heavy, and have a greater proportion of their area at high elevations. Basins with similar proportional areas at high and low elevations fall in between the others in terms of sensitivity and other metrics. This work provides context for anticipating the impacts of ongoing hydrological change due to climate change, and provides guidance for both monitoring networks and distributed modeling efforts.

Effect of Biochar on Soil and Water Loss on Sloping Farmland in the Black Soil Region of Northeast China during the Spring Thawing Period

Biochar, as a kind of soil amendment, has attracted wide attention from scholars in various countries, and the effects of biochar on soil and water loss have been well reported. However, soil erosion is significantly affected by geographical conditions, climate, and other factors, and research on the characteristics of soil erosion and the effects of biochar application in seasonally frozen soil areas is currently unclear. The purpose of this study was to explore the effect of corn straw biochar application on soil and water conservation during the spring thawing period. Specifically, through field experiments, the addition of 0, 6, and 12 kg m−2 biochar on slopes of 1.8, 3.6, 5.4, and 7.2° and the effects on runoff and the soil erosion rate of farmland were analyzed. The results showed that in the 6 and 12 kg m−2 biochar addition treatments, the saturated water content of the soil increased by 24.17 and 42.91%, and the field capacity increased by 32.44 and 51.30%, respectively. Compared with the untreated slope, with an increase in biochar application rate, runoff decreased slightly, and soil erosion decreased significantly. This study reveals that biochar can be used as a potential measure to prevent soil and water loss on sloping farmland in cold regions.

The Influence of Meltwater on Phytoplankton Blooms Near the Sea‐Ice Edge

AbstractPhytoplankton blooms occur annually at the sea‐ice edge throughout the Arctic during the spring melt period. Our study considers how these spring blooms may depend on sea‐ice meltwater, focusing on the role of horizontal mixing and advection. We extend the classic Fisher reaction‐diffusion equation to consider a time‐ and space‐varying death rate that represents the role of meltwater in the system. Our results indicate that blooms peak at a characteristic distance from the ice edge where (i) meltwater is concentrated enough to stratify the upper ocean such that the phytoplankton are confined near the surface and (ii) phytoplankton have been exposed to sufficient sunlight to allow for optimized growth. The results reproduce key characteristics of a large bloom observed in Fram Strait in May 2019. Our findings support the idea that sea‐ice meltwater is of central importance in setting the spatial patterns of Arctic phytoplankton blooms.

Stormwater quality assessment and management for the town of Jasper in Alberta, Canada

Abstract Stormwater pollutants can have deleterious impacts on the aquatic life of receiving water bodies. This paper presents the findings of a stormwater quality monitoring program performed in the town of Jasper in Alberta, Canada. This is one of the very few studies done on a small urban settlement to identify key pollutants of concern, characterize stormwater and identify unique pollutant sources in the town. A total of 14 stormwater quality parameters were found to be of high concern to aquatic life. The most prominent pollutants were total suspended solids (TSS), metals and phosphorus which compared well with studies conducted in large urban settlements. Tourist influx contributed to high metal and petroleum hydrocarbon loads during the peak season due to high vehicular activity. Elk were found to reside in the town during summer and their fecal droppings resulted in elevated fecal coliform concentrations. It was found that winter road salting was responsible for excessive chloride concentrations observed during the spring melt. TSS concentrations were statistically correlated with various metals as well as phosphorus using Spearman's rank correlation. It was found that the current street sweeping schedule in the town coincided with lower TSS and metal loads in stormwater.

COVID Monsters and Fairies.

The fairies moved in the month of the virus; I invite them during the spring thaw. The fairy doors come in the mail, their brown package stamped by customs, the smell of burn and bits of sawdust still lingering around their edges. Quarantine will be crafty, I decide. I glue, paint and gild by night. I leave the newly crafted doors to dry. Perhaps the fairies will protect us.

The influence of tillage and fertilizer on the flux and source of nitrous oxide with reference to atmospheric variation using laser spectroscopy

Nitrous oxide (N2O) is the third most important long-lived greenhouse gas and agriculture is the largest source of N2O emissions. Curbing N2O emissions requires understanding influences on the flux and sources of N2O. We measured flux and evaluated microbial sources of N2O using site preference (SP; the intramolecular distribution of 15N in N2O) in flux chambers from a grassland tilling and agricultural fertilization experiments and atmosphere. We identified values greater than that of the average atmosphere to reflect nitrification and/or fungal denitrification and those lower than atmosphere as increased denitrification. Our spectroscopic approach was based on an extensive calibration with 18 standards that yielded SP accuracy and reproducibility of 0.7 ‰ and 1.0 ‰, respectively, without preconcentration. Chamber samples from the tilling experiment taken ~ monthly over a year showed a wide range in N2O flux (0–1.9 g N2O-N ha−1 d−1) and SP (− 1.8 to 25.1 ‰). Flux and SP were not influenced by tilling but responded to sampling date. Large fluxes occurred in October and May in no-till when soils were warm and moist and during a spring thaw, an event likely representing release of N2O accumulated under snow cover. These high fluxes could not be ascribed to a single microbial process as SP differed among chambers. However, the year-long SP and flux data for no-till showed a slight direct relationship suggesting that nitrification increased with flux. The comparative data in till showed an inverse relationship indicating that high flux events are driven by denitrification. Corn (Zea mays) showed high fluxes and SP values indicative of nitrification ~ 4 wk after fertilization with subsequent declines in SP indicating denitrification. Although there was no effect of fertilizer treatment on flux or SP in switchgrass (Panicum virgatum), high fluxes occurred ~ 1 month after fertilization. In both treatments, SP was indicative of denitrification in many instances, but evidence of nitrification/fungal denitrification also prevailed. At 2 m atmospheric N2O SP had a range of 31.1 ‰ and 14.6 ‰ in the grassland tilling and agricultural fertilization experiments, respectively. These data suggest the influence of soil microbial processes on atmospheric N2O and argue against the use of the global average atmospheric SP in isotopic modeling approaches.

Perennial Grain Crops Reduce N <sub>2</sub>O Emissions Under Specific Site Conditions

Perennial grain crops represent a novel hybrid between annually harvested grain crops and perennial forage crops, which are seeded once and grow for multiple subsequent seasons. Previous research has shown comparatively reduced nitrous oxide (N2O) emissions from perennial forage crops relative to annual grain crops, however, the effect of perennial grain cropping on N2O emissions is unclear. We quantified field N2O emissions along an experimental continuum of perenniality (perennial forage, perennial grain, fall grain, spring grain and fallow) established at two sites within Alberta, Canada with contrasting soils: Luvisolic at the Breton site and Chernozemic at the Edmonton site. We used static chambers and a micrometeorological technique based on an open-path Fourier-transform infrared gas sensor (OP-FTIR). Perennial grain crops reduced cumulative N2O emissions at the Breton site by 60% and 94% in years two and three of the study, respectively (Ps < 0.0001). Conversely, no reduction in N2O emissions by the perennial grain crop relative to the annual crop was evident at the Edmonton site. Correlation analyses encompassing both sites revealed that the average root density from 0-60 cm was negatively correlated with soil available nitrogen (N) (0-15 cm depth) in years one (Ps < 0.01) and two (Ps < 0.05). Moreover, in year two, root density was negatively correlated with cumulative N2O emissions, specifically at the Breton site (P < 0.01). Results suggest that the enhanced root density of perennial crops reduced soil N availability at the Breton site, which translated into reduced cumulative N2O emissions in year two. Notably, increased root density did not correlate with reduced N2O emissions at the Edmonton site, suggesting that factors such as increased soil clay and carbon content in the Chernozemic soil overrode crop controls on N2O emission. Further, OP-FTIR measurements at the Breton site were in general agreement with static chamber measurements, which collectively informed that the bulk reduction in cumulative N2O emissions occurred during spring thaw. Overall, the ability for perennial cereal grain crops to reduce N2O emissions relative to annual crops was site-specific.