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During 19–21 June 2013 a heavy precipitation event affected southern Alberta and adjoining regions, leading to severe flood damage in numerous communities and resulting in the costliest natural disaster in Canadian history. This flood was caused by a combination of meteorological and hydrological factors, which are investigated from weather and climate perspectives with the fifth generation Canadian Regional Climate Model. Results show that the contribution of orographic ascent to precipitation was important, exceeding 30 % over the foothills of the Rocky Mountains. Another contributing factor was evapotranspiration from the land surface, which is found to have acted as an important moisture source and was likely enhanced by antecedent rainfall that increased soil moisture over the northern Great Plains. Event attribution analysis suggests that human induced greenhouse gas increases may also have contributed by causing evapotranspiration rates to be higher than they would have been under pre-industrial conditions. Frozen and snow-covered soils at high elevations are likely to have played an important role in generating record streamflows. Results point to a doubling of surface runoff due to the frozen conditions, while 25 % of the modelled runoff originated from snowmelt. The estimated return time of the 3-day precipitation event exceeds 50 years over a large region, and an increase in the occurrence of similar extreme precipitation events is projected by the end of the 21st century. Event attribution analysis suggests that greenhouse gas increases may have increased 1-day and 3-day return levels of May–June precipitation with respect to pre-industrial climate conditions. However, no anthropogenic influence can be detected for 1-day and 3-day surface runoff, as increases in extreme precipitation in the present-day climate are offset by decreased snow cover and lower frozen water content in soils during the May–June transition months, compared to pre-industrial climate.

Toxic cyanobacterial blooms (CBs) are becoming more frequent globally, posing a threat to freshwater ecosystems. While making long‐range forecasts is overly challenging, predicting imminent CBs is possible from precise monitoring data of the underlying covariates. It is, however, infeasibly costly to conduct precise monitoring on a large scale, leaving most lakes unmonitored or only partially monitored. The challenge is hence to build a predictive model that can use the incomplete, partially‐monitored data to make near‐future CB predictions. By using 30 years of monitoring data for 78 water bodies in Alberta, Canada, combined with data of watershed characteristics (including natural land cover and anthropogenic land use) and meteorological conditions, we train a Bayesian network that predicts future 2‐week CB with an area under the curve (AUC) of 0.83. The only monitoring data that the model needs to reach this level of accuracy are whether the cell count and Secchi depth are low, medium, or high, which can be estimated by advanced high‐resolution imaging technology or trained local citizens. The model is robust against missing values as in the absence of any single covariate, it performs with an AUC of at least 0.78. While taking a major step toward reduced‐cost, less data‐intensive CB forecasting, our results identify those key covariates that are worth the monitoring investment for highly accurate predictions. Key Points Toxic algae blooms pose threats globally, longing for prompt prediction Our work uses less costly, incomplete data sets to make near‐future bloom predictions We predict blooms with area under the curve 0.83 using partial data of regional and local information

Multiple factors operating across different spatial and temporal scales affect β‐diversity, the variation in community composition among sites. Disentangling the relative influence of co‐occurring ecological drivers over broad biogeographic gradients and time is critical to developing mechanistic understanding of community responses to natural environmental heterogeneity as well as predicting the effects of anthropogenic change. We partitioned taxonomic β‐diversity in phytoplankton communities across 75 north‐temperate lakes and reservoirs in Alberta, Canada, using data‐driven, spatially constrained null models to differentiate between spatially structured, spatially independent, and spuriously correlated associations with a suite of biologically relevant environmental variables. Phytoplankton β‐diversity was largely independent of space, indicating spatial processes (e.g., dispersal limitation) likely play a minor role in structuring communities at the regional scale. Our analysis also identified seasonal differences in the importance of environmental factors, suggesting a general shift toward greater relevance of local, in‐lake (e.g., nutrients and Secchi depth) over regional, atmospheric and catchment‐level (e.g., monthly solar radiation and grassland coverage) drivers as the open‐water growing season progressed. Several local and regional variables explained taxonomic variation jointly, reflecting climatic and land‐use linkages (e.g., air temperature and water column stability or pastureland and nutrient enrichment) that underscore the importance of understanding how phytoplankton communities integrate, and may serve as sentinels of, broader anthropogenic changes. We also discovered similar community composition in natural and constructed water bodies, demonstrating rapid filtering of regional species to match local environmental conditions in reservoirs comparable to those in natural habitats. Finally, certain factors related to human footprint (e.g., cropland development) explained the composition of bloom‐forming and/or toxic cyanobacteria more than the overall phytoplankton community, suggesting their heightened importance to integrated watershed management.

ContextIndustrial development in Canada’s boreal forest creates cumulative environmental effects on biodiversity. Some effects may be scale-dependent, creating uncertainty in understanding and hindering effective management.ObjectivesWe estimated cumulative effects of energy sector development on distributions of sixteen migratory songbird species at multiple spatial scales within the boreal region of Alberta, Canada, and evaluated evidence for scale domains in species responses.MethodsWe used a hierarchical, multi-scale sampling and modelling framework to compare effects of oil and gas footprint on songbirds at five spatial scales. We used Bayesian Lasso to facilitate direct comparison of parameter estimates across scales, and tested for differences in grouped parameter estimates among species.ResultsWe found consistent scale-dependent patterns across species, showing variable responses to development occurring at the smallest scale, little effect at intermediate scales, and stronger, mainly positive effects at the largest scales. Differences in grouped parameter estimates across scales showed strong evidence for scale domains in the response of songbirds to energy sector development.ConclusionsWe concluded that variable effects at the smallest scale represented individual habitat selection, while larger scale positive effects reflected expanding distributions of open habitat- and disturbance-associated species in areas of high oil and gas footprint. Our results show that single-scale analyses do not reflect population processes occurring at other scales. Future research on linking patterns at different scales is required to fully understand cumulative effects of land use change on wildlife populations.

Temporarily plugged or “suspended” wells pose environmental and economic risks due to the large volume of methane gas leaked. In the Canadian Province of Alberta, which, by far, has the largest number of petroleum wells in Canada, there are no regulations stipulating the maximum length of time a well can be left suspended. In recent years, an increasing number of wells have been put into the suspended state by owners. We show using a large data set obtained from the Alberta Energy Regulator that leak spells have increased between 1971 and 2019. For the same time period, the probability of an unresolved leak has also increased, and the amount of methane emitted per leak has substantially gone up. Lastly, we provide simple social-cost-of methane computations indicating that responsible policies can incentivize well owners towards remediation and reclamation and support efforts to fight climate change and improve upon economic expedience.

Little is known about the specific role of exotic species on measures of grassland plant diversity, including how this may vary with climatic conditions or large mammal herbivory. This study examined vegetation responses to long-term livestock grazing, including plant richness and diversity, as well as the contribution of exotic species to these metrics, across a network of 107 northern temperate grasslands in Alberta, Canada, spanning a broad aridity gradient. Exposure to grazing modestly increased plant richness, but did not alter Shannon’s diversity, Simpson’s diversity, or evenness, suggesting stability in floral diversity relative to grazing. However, grazing did increase grass cover while reducing shrub cover, the latter of which was only apparent in mesic grasslands. Unlike total plant diversity, exotic species richness and cover, together with exotic plant contributions to diversity, varied jointly with grazing and aridity. While long-term grazing increased exotic species, this response was most apparent in wetter areas, and nongrazed grasslands remained more resistant to the presence of exotics. Several exotic species were positive indicators of grazing in wetter grasslands, and coincided with lower native species cover, indicating grazing may be facilitating a shift from native to exotic vegetation under these conditions. Overall, our results indicate that while long-term grazing has altered the composition and cover of certain functional groups, including favoring exotics and minimizing woody vegetation in mesic areas, overall changes to plant diversity were limited. Additionally, these findings suggest that semi-arid northern temperate grasslands remain relatively resistant to grazing effects, including their susceptibility to exotic plant encroachment. These results improve our understanding of how ongoing grazing exposure may impact grassland diversity, including efforts to conserve native vegetation, as well as the important role of climate in altering fundamental grassland responses to grazing.

Livestock production is increasingly at risk from rising temperatures under global warming. Despite this, how temperature increases impact the behavior of cattle on pasture is not fully understood. This research reports on patterns of beef cattle activity, including step counts and lying time, during the summer and fall grazing seasons of 2021, coincident with an unusual period of elevated temperatures and heat load within a northern temperate rangeland of Alberta, Canada. Beef heifers and first calf cows with calves at side were monitored using IceRobotics leg-mounted pedometers deployed from June 24 to August 26 in summer pasture, and August 27 to November 10 in fall pasture. Heat load conditions were quantified through the temperature-humidity index (THI), which has previously been reported to alter cattle behavior. Cattle exhibited marked diurnal shifts in activity patterns during elevated heat loading periods, increasing their activity (movement) at night and midday, with reduced activity in the morning and afternoon. While heifers had greater step counts in summer than cows, the reverse was true during fall, with cows being more active than heifers and having reduced lying times. A regression tree analysis indicated the specific thresholds for heat load (THI) that alter cattle activity were 54 (lower value) and 70 (upper value), below and above which, movement rates increased with greater heat loading. These results are useful for assessing cattle behavioral responses to weather conditions, including heat load. Further work is needed to understand how cattle activity under open-range grazing in temperate environments alter cattle behavior, stress and beef production outcomes, particularly in the face of escalating climate change.

Bitumen extraction from oil sands ore in Alberta, Canada, has generated > 1.3 billion m3 of tailings comprised of slurry of fine silt, clay, residual bitumen, and diluent hydrocarbons, deposited in ponds. Key environmental issues associated with oil sands tailings include biogenic greenhouse gas emissions (methane and carbon dioxide), water toxicity and its potential seepage, water reuse, and solids consolidation. Methane produced during anaerobic microbial metabolism of hydrocarbons is emitted from tailings ponds and end-pit lakes where tailings are reclaimed. This study tests one of the strategies to minimize methane emissions using iron minerals and other terminal electron acceptors for the biodegradation of residual hydrocarbons under alternative, non-methanogenic redox conditions. Preliminary data exhibited biodegradation of a higher number of hydrocarbons (heptane, octane and decane, and toluene) under sulfate-reducing conditions compared to toluene biodegradation only under nitrate- and iron-reducing conditions. Amorphous iron mineral suppressed methanogenesis, whereas iron crystalline mineral enhanced methane production. Our overall results reveal the potential of indigenous microbes to biodegrade hydrocarbons in the tailings under different redox conditions, and thereby channel carbon flow from hydrocarbons to carbon dioxide.

Delay in the hibernation emergence date of female Columbian ground squirrels in Canada over 20 years is related to climatic conditions other than increasing temperature, and as years of later emergence are associated with decreased individual fitness, plastic responses to climate change may be associated with declines in population viability. Hibernation disrupted by climate change The effects of climate change on the seasonal biological rhythms of bird and plant populations are well documented. How mammals are affected is less well known. Using a 20-year data set of hibernation-emergence dates for Columbian ground squirrels in Alberta, Canada, an international team of researchers reports a rare example of a delay resulting from climate change. The authors attribute this delay — which amounts to almost half a day per year — to an increasing prevalence of late-season snowstorms. Females experienced lower fitness during years of later emergence and, as a result, the growth rate of the population is lower than it was previously. Consensus projections from current climate models are for increased winter precipitation, so such events could become more common in future. These findings imply that behavioural responses to climate can be associated with declines in individual fitness, as well as being triggered directly by temperature increases. The most commonly reported ecological effects of climate change are shifts in phenologies, in particular of warmer spring temperatures leading to earlier timing of key events 1 , 2 . Among animals, however, these reports have been heavily biased towards avian phenologies, whereas we still know comparatively little about other seasonal adaptations, such as mammalian hibernation. Here we show a significant delay (0.47 days per year, over a 20-year period) in the hibernation emergence date of adult females in a wild population of Columbian ground squirrels in Alberta, Canada. This finding was related to the climatic conditions at our study location: owing to within-individual phenotypic plasticity, females emerged later during years of lower spring temperature and delayed snowmelt. Although there has not been a significant annual trend in spring temperature, the date of snowmelt has become progressively later owing to an increasing prevalence of late-season snowstorms. Importantly, years of later emergence were also associated with decreased individual fitness. There has consequently been a decline in mean fitness (that is, population growth rate) across the past two decades. Our results show that plastic responses to climate change may be driven by climatic trends other than increasing temperature, and may be associated with declines in individual fitness and, hence, population viability.