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Effective winter road maintenance relies on precise road friction estimation. Machine learning (ML) models have shown significant promise in this; however, their inherent complexity makes understanding their inner workings challenging. This paper addresses this issue by conducting a comparative analysis of road friction estimation models using four ML methods, including regression tree, random forest, eXtreme Gradient Boosting (XGBoost), and support vector regression (SVR). We then employ the SHapley Additive exPlanations (SHAP) explainable artificial intelligence (AI) to enhance model interpretability. Our analysis on an Alberta dataset reveals that the XGBoost model performs best with an accuracy of 91.39%. The SHAP analysis illustrates the logical relationships between predictor features and friction within all three tree-based models, but it also uncovers inconsistencies within the SVR model, potentially attributed to insufficient feature interactions. Thus, this paper not only showcase the role of explainable AI in improving the ML interpretability of models for road friction estimation, but also provides practical insights that could improve winter road maintenance decisions. [ABSTRACT FROM AUTHOR]

Basal gravel and sand mantling the bedrock floors of buried valleys throughout the Canadian Interior Plains, and conformably overlying proglacial lacustrine sediment, comprise the Empress Group. While previously conceptualized as stratigraphically equivalent deposits of preglacial rivers prior to the first and most extensive continental and montane glaciations, subsequent stratigraphic studies indicated that buried valley basal gravel must have been deposited between, or during, progressively more extensive continental glaciations and could not be stratigraphically equivalent throughout the buried valley network. However, in the general absence of formation-rank stratigraphic description of basal gravel units that might better inform the geologic history of the deposits, most workers simply consider Empress Group sediments time-transgressive. In this paper, we examine basal gravel at provincial and regional scales to understand its genesis and geologic history. At the provincial scale, we map basal gravel in three dimensions using a novel machine learning approach. At the regional scale, we formally define basal gravel formations at either end of the largest buried valley system in Alberta, which informs its glacial history and physiographic development and shows the importance of formation-rank stratigraphic description. Our results indicate that the buried valley network across Alberta is palimpsest in genesis and basal gravel units within it are chronostratigraphically intercalated between tills. We advocate that the Empress Group definition be extended across Alberta with modifications to improve its clarity and utility, and formally define the Old Fort, Unchaga, Ipiatik, and Winefred formations as part of the Empress Group. [ABSTRACT FROM AUTHOR]

Dinosaur skeletal material from the mid-Cretaceous of Canada is rare; however, the Cenomanian-aged Dunvegan Formation of northeastern British Columbia and northwestern Alberta is rich with ichnofossils attributed to nodosaurid ankylosaurs. A long bone (Hudson's Hope Museum specimen HH 2017.010.002) collected in 1993 from the Murray River of northeastern British Columbia is identified here as an ankylosaur femur. Femoral measurements of the bone plotted against femoral measurements of major dinosaur clades, combined with observations on femoral features, indicate that the bone belongs to an ankylosaur. The specimen is too damaged to assign to Nodosauridae or Ankylosauridae. HH 2017.010.002 represents the first limb bone material recovered from the Dunvegan Formation; previous ankylosaur material described from the Dunvegan Formation includes associated vertebrae and ribs from British Columbia and osteoderms from Alberta, as well as the presumed nodosaurid footprints Tetrapodosaurus borealis Sternberg, 1932. The Cenomanian is a time of great ecological change in North America, including the possible extirpation of ankylosaurid ankylosaurs. Fossils from the Dunvegan Formation can thus yield important insight into the responses of fauna to this major transition. [ABSTRACT FROM AUTHOR]

Herbicide resistance in western Canada has increased interest in alternative weed management strategies. Physical impact mills, a form of harvest weed seed control, have been identified as a strategy that may be well suited for Canadian use. The efficacy of the Harrington Seed Destructor, a physical impact mill, was evaluated in 20 producer fields in Alberta on a wide spectrum of weed species over 3 years. Significant differences in weed densities between the physical impact mill treatment and the regular harvest densities were few; however, some population density reductions were observed. Measurable reductions in weed densities may have been limited by the short timeframe of the experiment, the high initial densities of the weeds, or the targeted weed species having dormancy or longer term seedbanks. Additionally, identified knowledge gaps on how best to optimize physical impact mill efficacy may have reduced the efficacy of the physical impact mill in this study. This study showed no conclusive evidence for the efficacy of a physical impact mill on tested weed species under field conditions. However, it did provide a number of important considerations for future studies. [ABSTRACT FROM AUTHOR]

Granular urea fertilizer applied at planting is prone to nitrogen (N) losses in certain environments. Enhanced efficiency fertilizers (EEFs) are developed to mitigate losses and optimize plant uptake. To determine the benefits of EEFs in grain yield and quality enhancement in Canada Western Red Spring (CWRS) wheat, an experiment was conducted from 2019 to 2022 at eight sites in Alberta and Saskatchewan, Canada. The effects of five N sources [urea; urea + urease inhibitor, N-(n-butyl)thiophosphoric triamide (NBPT); urea + nitrification inhibitor, nitrapyrin; urea + dual-inhibitor, NBPT + dicyandiamide; and polymer-coated urea, ESN® (Environmentally Smart Nitrogen®)] and four N rates (60, 120, 180, and 240 kg N ha−1) on CWRS wheat production were examined. Results indicated that N source affected grain yield in Dark Brown Chernozem soils but not in Black Chernozem or Dark Grey Luvisol soils. In Dark Brown Chernozem soils, a dual inhibitor increased grain yield by 3.1% and 3.9% relative to urea and polymer-coated urea, respectively, while all other EEFs attained similar results. The use of a dual inhibitor EEF led to greater net returns compared to urea and polymer-coated urea in the Dark Brown Chernozem soils. Grain protein concentration increased linearly with increasing N rate from 60 to 240 kg N ha−1. Generally, a rate of 120 kg N ha−1 was optimal for CWRS wheat grown in Canadian prairie conditions when coupled with EEFs, particularly a dual inhibitor, and grain yield and protein were often responsive. [ABSTRACT FROM AUTHOR]