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Dam breach is a large-scale, highly unsteady, and complex water-sediment flow. Dam breach events span scenarios involving natural dams (created following valley blocking landslides) to scenarios involving anthropogenic structures such as water-retaining dams and dams designed specifically to store mine waste (e.g. tailings). Management of the risk posed by a potential breach of a dam structure requires a careful analysis of the consequences of failure. These analyses, often called dam breach studies, aim to improve safety and risk management through the prediction of travel time, flow velocity, and spatial extent of the hazard (e.g. map of depth of inundation) in the event of a breach. These factors in turn define the consequence classification of a dam and guide the development of emergency preparedness plans. The key boundary condition required for flood routing numerical simulations often conducted for dam breach studies is the outflow hydrograph which describes the relationship between outflow of the retained volume with time. In this study we explore the effect of failure mechanism on the characteristics of the outflow hydrograph of otherwise identical physical model dams. Physical model dams of 1 m in height were constructed of fine sand near the midspan of the 36 m long, 2.1 m wide, and 1.2 m high large landslide flume facility at Queen’s University Coastal Engineering Laboratory. Three failure mechanisms are explored; a) notch overtopping, initiated by incising a v-notch into the dam crest and allowing the impounded reservoir to intersect this local low point; b) wide-width overtopping, where a retaining wall placed along the crest of the dam allows for an additional reservoir capacity above the height of the crest that when rapidly removed a full width sheet of water cascades over the dam; and c) geotechnical seepage failure, where closing the toe drain allows a seepage face to develop that causes a failure in the downstream face of the dam. The reservoir surface elevation during breach was monitored with a series of five Akamina AWP-24 wave capacitance height gauges distributed centerline in the upstream reservoir. The evolution of breach shape is captured every 3 s using five Canon EOS Rebel T5 Digital Single-lens Reflex (DSLR) that capture a plan view area of the entire 2.1 m width of the dam and a combined upstream and downstream length of 4.3 m. To further capture the evolution of failure a Blickfeld LiDAR sensor was positioned oblique to the downstream slope to capture a point cloud scan ever 1.4 s. These data sets are then used to compare the physical characteristics of each breach process and the resulting implications for the observed outflow hydrographs for each failure mechanism.

Debris flows affect people and infrastructure around the world, and as a result, many numerical models and modelling approaches have been developed to simulate their impacts. Observations from instrumented debris-flow channels show that variability in inflow depth, velocity, and discharge in real debris flows is much higher than what is typically used in numerical simulations. However, the effect of this natural variability on numerical model outputs is not well known. In this study, we examine the effects of using complex inflow time series within a single-phase runout model utilizing a Voellmy flow-resistance model. The interactions between model topography and flow resistance were studied first using a simple triangular hydrograph, which showed that simulated discharges change because of local slopes and Voellmy parameters. Next, more complex inflows were tested using time series based on 24 real debris-flow hydrographs initiated from three locations. We described a simple method to scale inflow hydrographs by defining a target event volume and maximum allowable peak discharge. The results showed a large variation in simulated flow depths and velocities arising from the variable inflow. The effects of variable-inflow conditions were demonstrated in simulations of two case histories of real debris flows, where the variation in inflow leads to significant variations in the simulation outputs. The real debris-flow hydrographs were used to provide an indication of the range of impacts that may result from the natural variability in inflow conditions. These results demonstrate that variation in inflow conditions can lead to reasonable estimates of the potential variation in impacts., Natural Hazards and Earth System Sciences, 22 (5), ISSN:1561-8633, ISSN:1684-9981

Rock avalanches can be a significant hazard to communities located in mountainous areas. Probabilistic predictions of the 3D impact area of these events are crucial for assessing rock avalanche risk. Semi-empirical, calibration-based numerical runout models are one tool that can be used to make these predictions. When doing so, uncertainties resulting from both noisy calibration data and uncertain governing movement mechanism(s) must be accounted for. In this paper, a back-analysis of a database of 31 rock avalanche case histories is used to assess both of these sources of uncertainty. It is found that forecasting results are dominated by uncertainties associated with the bulk basal resistance of the path material. A method to account for both calibration and mechanistic uncertainty is provided, and this method is evaluated using pseudo-forecasts of two case histories. These pseudo-forecasts show that inclusion of expert judgement when assessing the bulk basal resistance along the path can reduce mechanistic uncertainty and result in more precise predictions of rock avalanche runout., Landslides, 19 (12), ISSN:1612-510X

Bovine viral diarrhea virus (BVDV) causes significant economic loss in cattle. Detection of persistently infected (PI) animals is an important control measure, but persistence of maternal antibodies may result in false-negative test results. We assessed the sensitivity and specificity of 2 antigen ELISAs (Idexx BVDV Ag/Serum Plus and BVDV PI X2) and a reverse-transcription real-time PCR (RT-rtPCR; Idexx RealPCR BVDV) assay for detecting PI calves. Ear notch samples were collected from 1,030 calves ~3, 10, 24, and 38 d old (days 3, 10, 24, and 38). All day 38 samples were tested using 2 antigen ELISAs and RT-rtPCR, and any calf that tested positive by any of these tests was blood sampled at ~100 d old (day 100) for antigen and antibody testing by ELISA; samples collected on days 3, 10, and 24 were tested using the antigen ELISAs and PCR. Calves were defined as PI if they were test-positive on day 38 by either ELISA or PCR and were antigen-positive on day 100. Twenty-six calves were PCR BVDV test–positive and one was BVDV PI X2 ELISA–positive at day 38. Five calves were defined as PI, and all tested positive by ELISAs and RT-PCR assay on days 3, 10, and 24. The sensitivity and specificity were 100% for both antigen ELISAs and 96.7% and 100%, respectively, by RT-rtPCR. Test results were not affected by calf age, suggesting that testing for PI calves can be undertaken at any age.

When a life-threatening landslide is recognized, the questions most relevant to community leaders are as follows: is our community safe enough, and if not, how much should we spend on protection? A risk evaluation tool that helps answer these questions, which compares landslide risk faced by a group of people to perceptions of tolerable risk, was first proposed in Hong Kong and is now being used widely in Western Canada within a quantitative risk management framework. After more than a decade of sporadic application in Western Canada, challenges of applying this tool are becoming apparent. For example, its use has resulted in landslide mitigation designs that are unaffordable, and it has failed to persuade funding authorities that proposed risk management solutions are a justifiable allocation of governments’ limited resources. This article suggests that the risk evaluation tool designed in Hong Kong should not be universally applied. We propose modifications believed to be more appropriate for Western Canada, including tolerating landslide risk levels similar to other natural hazard types and emphasizing cost-effectiveness of landslide risk reduction options. Although the proposed tools were developed for the sociopolitical context of Western Canada, we hope the discussions included in this article motivate others to modify these risk evaluation tools for other societies and hazard types and that ultimately this will lead to more rational and consistent decisions that, with time, save lives and resources in landslide-prone regions of the world.

The Johnsons Landing landslide occurred on 12 July 2012 on the shores of Kootenay Lake, British Columbia. The landslide consisted of poorly sorted, low-plasticity debris that initially descended a steep channel, before avulsing onto a glaciofluvial terrace. This event destroyed three homes and killed four people who lived on this terrace. This paper presents a back-analysis of this event using numerical runout modelling. It is shown that undrained flow can explain the observed channel avulsion with fewer model parameters than needed by previous analyses. This mechanism should be considered in similar settings, as ignoring it can lead to underestimation of runup and overtopping of natural and anthropogenic flow obstacles, such as landslide protection structures.

Endometritis, diagnosed either by assessing the proportion of nucleated cells that are neutrophils (PMN%) following cytology of the endometrium or by assessing the degree of purulent material within the vagina (purulent vaginal discharge or PVD score), is prevalent among dairy cows. However, limited data exist as to the degree of variation among herds in the prevalence of endometritis diagnosed by these 2 methods. Thus, we undertook a study involving uterine cytological and vaginal sampling at a median of 41 d in milk of 1,807 cows from 100 seasonally breeding dairy herds in New Zealand. The optimal cut-point for PMN% was determined by receiver operator characteristic (ROC) curve analysis using conception to first artificial insemination (AI) as the outcome variable. The prevalence of disease was then calculated at the cow and herd levels, and an estimate of the effect of clustering of cow within a herd was calculated. Reproductive outcomes were collated and associations between endometritis and reproductive outcomes assessed using multivariable models. The optimal PMN% cut-point was ≥2%. The correlation of results for cows within a herd (the intraclass correlation) was 0.03, which was significant; hence, subsequent modeling accounted for this clustering. The cow-level prevalence of PMN% ≥2% was 27.0% [95% confidence interval (CI): 25.0 to 29.1%], whereas the mean within-herd prevalence of PMN% ≥2% was 27.1% (95% CI: 24.7 to 29.6%; range: 5.0 to 63.6%), and the prevalence among herds varied significantly. An elevated PMN% (≥2%) was significantly associated with a reduction in the proportion of cows conceiving to first AI (45.8 vs. 54.5%), a reduced proportion of cows submitted for AI in the first 3 wk of the seasonal breeding program (83.7 vs. 89.3%), and a lower proportion pregnant in the first 3 (44.4 vs. 55.4%) and 6 wk (67.5 vs. 76.4%) of the breeding program relative to cows with a low PMN% (i.e.

Debris flows are among the most destructive types of mass movements throughout the world and are not restricted to certain climate zones or geological environments. In opposite corners of the American continent, Canada and Brazil have experienced several historic debris flows. As part of a one-year international exchange program, the lead author compared morphological evidence related to debris flows and the morphometry of watersheds at sites in Canada and Brazil, with the ultimate goal of improving the understanding of debris flows in Brazil. Field surveys carried out in both areas in 2019 and 2020 permitted observation of the debris-flow signatures, as well as the physical aspects of the surrounding areas and morphometric mapping of watersheds. Both areas exhibit similar typical features of debris flows, and the morphometric results indicate differences that may influence the recurrence of events at the sites in Canada as compared to Brazil due to their higher values for the parameters area > 25° (A25), relief ratio (Rr), and Melton ratio (Mr) at the Canadian sites; however, this dataset is limited. Compared to results in the literature from around the world, values of morphometric parameters at Brazilian sites are within the ranges observed in other tropical climates.

Numerical runout models are important tools for predicting the potential downstream impacts of tailings dam breaches that generate tailings flows, which is a crucial step in emergency preparedness and planning, and risk management. Most existing runout models were originally developed for the analysis of water floods or flow-like landslides (e.g. debris flows). In this study, we back-analyze two well-documented historical tailings dam breaches (1985 Stava, Italy and 1994 Merriespruit, South Africa) using four numerical models (DAN3D, MADflow, FLO-2D and FLOW-3D). The main objective of this multi-case, multi-model benchmarking exercise is to identify collective opportunities to adapt these types of models and associated modelling methods to tailings dam breach runout applications. Comparing best-fit simulation results, we find that all four models are capable of reproducing the bulk behaviour of the real events; however, (i) multiple sets of rheological parameters may produce very similar output results, (ii) the best-fit input parameter combinations are non-transferable between models and inconsistent with independently measured rheological properties of stored tailings, and (iii) choosing an appropriate set requires sufficient understanding of material rheological properties and expert judgment. Using a systematic sensitivity analysis with the First-Order Second-Moment (FOSM) approach, we also find that each model is sensitive to different input parameters, although the total released volume is among the main high-influence parameters in every scenario. We conclude that more case study back-analyses are needed to enhance our understanding of these sensitivities and develop better guidance on the use of these types of numerical models for tailings flow runout prediction.

This study tested the hypothesis that increasing the duration and/or frequency of antimicrobial treatment of subclinical mastitis would result in a higher bacteriological cure rate. Glands with a positive California mastitis test (CMT) from cows with an elevated somatic cell count (>500,000 cells/mL) that had an intramammary infection were randomly assigned at cow level to no treatment (Control; n = 80 glands), intramammary infusion of 200 mg cloxacillin sodium on three occasions at 48 h intervals (3 × 48 h; n = 273 glands), five occasions at 24 h intervals (5 × 24 h; n = 279 glands), or on five occasions at 48 h intervals (5 × 48 h; n = 72 glands). Glands were resampled at 21 (±3) and 28 (±3) days after initiation of treatment. The gland-level cure rate for any pathogen was 5/80 (6.2%), 139/173 (49.8%), 172/297 (61.6%) and 58/72 (80.6%) for Control, 3 × 48 h, 5 × 24 h and 5 × 48 h, respectively. The cure rate for major pathogens (defined as Staphylococcus aureus or Streptococcus spp.) was 4/52 (7.7%), 84/197 (42.6%), 96/183 (52.5%) and 36/48 (75%) for Control, 3 × 48 h, 5 × 24 h and 5 × 48 h, respectively. We conclude that treatment was superior to no treatment, and bacteriological cure rate was higher with the 5 × 24 h protocol than for the 3 × 48 h protocol and was higher with the 5 × 48 h than the 5 × 24 h protocol.

Staphylococcus aureus is one of the leading causes of bovine mastitis worldwide and is a common indication for use of antimicrobials on dairy farms. This study aims to investigate the association between on-farm antimicrobial usage and the antimicrobial resistance (AMR) profiles of mastitis-causing S. aureus. Whole-genome sequencing was performed on 57 S. aureus isolates derived from cows with either clinical or subclinical mastitis from 17 dairy herds in New Zealand. The genetic relatedness between isolates was examined using the core single nucleotide polymorphism alignment whilst AMR and virulence genes were identified in-silico. The association between gene presence-absence and sequence type (ST), antimicrobial susceptibility and dry cow therapy treatment was investigated using Scoary. Altogether, eight STs were identified with 61.4% (35/57) belonging to ST-1. Furthermore, 14 AMR-associated genes and 76 virulence-associated genes were identified, with little genetic diversity between isolates belonging to the same ST. Several genes including merR1 which is thought to play a role in ciprofloxacin-resistance were found to be significantly overrepresented in isolates sampled from herds using ampicillin/cloxacillin dry cow therapy. Overall, the presence of resistance genes remains low and current antimicrobial usage patterns do not appear to be driving AMR in S. aureus associated with bovine mastitis.

Rock avalanches involve extremely rapid, flow-like movement of fragmented rock with extreme destructive potential. With increasing development pressures in mountainous regions, there is a need for simple, stochastic estimates of runout distances to aid in hazard assessments and prioritize sites for more detailed investigation. To support the development of an empirical predictive tool, a systematic method was used to describe 49 rock avalanches in the Canadian Cordillera, which had been documented in the literature but not previously compiled into a regional inventory. These cases were described using measured or estimated numerical values for volume, fall height, runout length, total impacted area and the ratio of total impacted area over runout length (referred to as mean path width), and qualitative descriptions of the topographic confinement, substrate material and source geology. Linear regressions were fit to the data, with qualitative attributes treated as indicator variables. A strong relationship was found for runout distance predicted from volume, fall height and lateral confinement. A second relationship was found for mean path width over runout length predicted from volume. These relationships were converted to survival functions to estimate the runout exceedance probability and the mean path width exceedance probability. These survival functions were implemented in a computer tool, called the Probabilistic Runout Estimator—Rock Avalanche (PRE-RA), which can be used to estimate spatial impact probability ranges for rock avalanche runout. An application of this tool was demonstrated using two recent Canadian rock avalanches, which were not used in the dataset to estimate the statistical relationships.

Extremely rapid, flow-like landslides pose a significant hazard worldwide; however, the analysis of the impact area and velocity of these flows is not routine. Semi-empirical numerical models are one tool that is available for performing this sort of analysis. These models are physically based; however, certain input parameters are determined through model calibration, using back-analysis of real landslide cases. Objective, repeatable calibration methods are needed for this approach to be useful for landslide runout prediction. The present analysis describes the application of optimization theory and Bayesian statistics to calibrate these types of models. Two complementary methods are presented. The first uses the Gauss-Marquardt-Levenberg optimization algorithm to efficiently determine a set of best-fit calibrated model parameters. The second uses a posterior analysis to quantify errors associated with parameter calibration, which can then be used for probabilistic forward analysis. Three case histories are presented to demonstrate how the new methods are able to rapidly calibrate a runout model, reduce subjectivity inherent in the calibration process, and provide information on parameter uncertainty.

AIMS To develop an intrauterine infection model for Trueperella pyogenes in postpartum dairy cows and to assess the effect of this infection on the degree of intrauterine inflammation and concentrations of progesterone in serum. METHODS The oestrous cycles of 36 healthy, non-pregnant, postpartum dairy cows were synchronised. They were then treated by intrauterine infusion of 0.5 g cephapirin before being blocked by age and randomly assigned to treatment with intrauterine infusion of saline (n = 18), 107 (n = 9) or 109 (n = 9) cfu of T. pyogenes, approximately 4 days after the expected time of ovulation (Day 0). Prior to intrauterine infusion on Day 0 and again on Days 3, 7, 10, and 15, cytobrush samples were collected from the uterus of each cow for microbiology and assessment of the percentage of polymorphonuclear neutrophils (PMN%). Blood samples were collected on the same days for measurement of concentrations of progesterone in serum, and uterine lumen diameter was assessed daily using transrectal ultrasonography. RESULTS Trueperella pyogenes was isolated from 5/18 (28%), 7/9 (78%) and 8/9 (89%) cows infused with saline, 107 or 109 cfu of T. pyogenes, respectively (p 0.05), whereas it was higher on Days 7 and 10 than Day 0 in the 107 cfu group, and higher on Days 3 and 10 than Day 0 in the 109 cfu group (p 2 mm was higher in cows infused with 107 (29.3 (95% CI = 14.5-44.2)%) or 109 cfu (19.2 (95% CI = 7.0-31.5)%) than in control cows (3.1 (95% CI = 0.1-6.0)%) (p

Risk-taking is an essential part of life. As individuals, we evaluate risks intuitively and often subconsciously by comparing the perceived risks with expected benefits. We do this so commonly that it passes unnoticed, like when we decide to speed home from work or go for a swim. The comparison changes, however, when one entity (such as a government) imposes a risk evaluation on another person. For example, in a quantitative risk management framework, the estimated risk is compared with a tolerable risk threshold to decide if the person is ‘safe enough’. Landslide risk management methods are well established and there is consensus on tolerable life-loss risk thresholds. However, beneath this consensus lie several key details that are explored by this article, along with suggestions for refinement. Specifically, we suggest using the risk unit, micromort (one micromort equals a life loss risk of 1 in 1 million), in describing risk estimates and thresholds, to improve risk communication. For risk estimation, we provide guidance for defining and combining landslide scenarios and for recognizing where unquantified risk from low-probability/high-consequence scenarios ought to inform risk management decisions. For risk tolerance thresholds, we highlight the pitfalls of selecting unachievably low thresholds and suggest that there is no single universal threshold. Additionally, we argue that gross disproportion between costs and benefits of further risk reduction, which is integral to the As Low As Reasonably Practicable (ALARP) principle, is a commonly unachievable and counter-productive condition for risk tolerance, and other conditions centered on proportionality often apply. Finally, we provide several figures that can be used as risk communication tools, to provide context for risk estimates and risk tolerance thresholds when these values are reported to decision makers and the public.

Researchers are increasingly incorporating force histories derived from long-period seismic waves into multidisciplinary studies of large, rapid landslides. The force history can provide important information about what happened during failure — information that complements data available from field investigations and remote sensing analyses. It can also provide additional constraints on the dynamics of landslide motion than can be used to validate and/or calibrate numerical landslide models. However, the inversions need to be of high quality and must be interpreted properly. Because this technique is relatively new, we are still discovering how to best conduct inversions to obtain robust results and how to appropriately interpret these results. In this study, we run numerical models of landslides with idealized source and path geometries using two different modeling packages, DAN3D and D-Claw, and we use the model outputs to generate synthetic long-period seismic data. Both models use depth-averaged flow equations over 3D topography, with DAN3D using semi-empirical material rheologies and D-Claw using a two-phase granular and fluid flow approach. To examine the influence of station azimuthal coverage and distance, we synthesize seismic data for a wide range of possible station configurations. We then use these synthetic seismic data to conduct seismic inversions using the recently released open-source Python-based software package, lsforce (https://code.usgs.gov/ghsc/lhp/lsforce). In doing these inversions, we add differing levels and types of noise, vary the inversion options (e.g., frequency range, regularization techniques) and then compare the results to the “known” dynamics of the modeled idealized landslides. We aim to understand common artefacts, limitations, and other potential pitfalls in interpretation, to guide the inversion process in future studies. We repeat this process for idealized landslides of increasing complexity, including multi-part failures, sinuous paths, and gradual versus sudden initiations, to simulate how these characteristics are reflected in the force history and to better understand what level of detail can be constrained from the seismic inversion. This work will help guide researchers to obtain more reliable information about landslide dynamics from seismic inversions in future landslide studies.

Estimating the potential runout distance of a landslide and it associated impacted area is an important component of landslide hazard and risk analysis. This can be done using empirical; or physics-based runout analysis methods. The current study uses the empirical method by compiling previously published international examples of landslide runout and unpublished New Zealand landslides triggered by recent earthquakes and rainstorm events. The results are presented in a series of ΔH/L versus volume plots for different landslide types, substrate (glacier versus unglaciated), and triggers (earthquake versus rainfall). The plots contain superimposed probability of runout exceedance lines. The results from this study provide landslide researchers and practitioners simple tools to conduct a forward-looking empirical-probabilistic runout analysis for debris avalanches, debris flows, and rock avalanches. The methodology presented is appropriate for a regional-level assessment or scoping-level site-specific assessment to identify areas warranting more detailed work. Applications and limitations of empirical-probabilistic runout methods are also discussed.

Tailings flows result from the breach of tailings dams. Large-scale tailings flows can travel over substantial distances with high velocities and cause significant loss of life, environmental damage, and economic costs. Runout modelling and inundation mapping are critical components of risk assessment for tailings dams. In an attempt to develop consistency in reporting tailings data, we established a new tailings-flow runout classification system. Our data analysis applies to the zone corresponding to the extent of the main solid tailings deposit, which is characterized by visible or field-confirmed sedimentation, above typical surface water levels if extending into downstream water bodies. We introduced a new database of 33 tailings dam breaches by independently estimating the planimetric inundation area for each event using remote sensing data. This paper examines the applicability of a semi-physical area–volume relationship using the new database. Our results indicate that the equation A= cV2∕3, which has been used previously to characterize the mobility of other types of mass movements, is a statistically justifiable choice for the relationship between total released volume and planimetric inundation area. Our analysis suggests that, for a given volume, tailings flows are, on average, less mobile than lahars but more mobile than non-volcanic debris flows, rock avalanches, and waste dump failures.

A number of veterinary clinical pathology laboratories in New Zealand have been reporting emergence of increased minimum in inhibitory concentrations for β-lactams in the common clinical bovine mastitis pathogen Streptococcus uberis. The objective of this study was to determine the genetic basis of this increase in MIC for β-lactams amongst S. uberis. Illumina sequencing and determination of oxacillin MIC was performed on 265 clinical isolates. Published sequences of the five penicillin binding proteins pbp1a, pbp1b, pbp2a, pbp2b, and pbp2x were used to identify, extract and align these sequences from the study isolates. Amino acid substitutions resulting from single nucleotide polymorphisms (SNP) within these genes were analysed for associations with elevated (≥ 0.5 mg/L) oxacillin MIC together with a genome wide association study. The population structure of the study isolates was approximated using a phylogenetic tree generated from an alignment of the core genome. A total of 53 % of isolates had MIC ≥ 0.5 mg/L for oxacillin. A total of 101 substitutions within the five pbp were identified, of which 11 were statistically associated with an MIC ≥ 0.5 mg/L. All 140 isolates which exhibited an increased β-lactam MIC had SNPs leading to pbp2x E381K and Q554E substitutions. The phylogenetic tree indicated that the genotype and phenotype associated with the increased MIC for oxacillin were present in several different lineages suggesting that acquisition of this increased β-lactam MIC had occurred in multiple geographically distinct regions. Reanalysis of the data from the intervention studies from which the isolates were originally drawn found a tendency for the pbp2x E381K substitution to be associated with lower cure rates. It is concluded that there is geographically and genetically widespread presence of pbp substitutions associated with reduced susceptibility to β-lactam antimicrobials. Additionally, presence of pbp substitutions tended to be associated with poorer cure rate outcomes following antimicrobial therapy for clinical mastitis.

A Fahrboschung angle versus volume methodology for estimating the runout distance of large open pit slope failures was proposed to the open pit geotechnics community in 2015 (Whittall et al. 2015). Since that 2015 publication, three commonly received questions on the methodology include: This paper provides a summary of refinements to runout estimate techniques for pit slope failures. In particular, empirical tools for estimating small-volume bench scale failures and a probabilistic framework for spatially distributed runout estimates are provided. A risk assessment methodology is proposed that can be mapped across the pit floor by dividing it into square grid cells and calculating individual risk for each cell. The goal of this paper is to supply practitioners with quick, repeatable tools to better understand the landslide risk to which workers and equipment are exposed, and support decision-making when working in an open pit with a developing or imminent pit slope failure.

The objective of this study was to assess the effect of increasing dietary starch for approximately 30 d postpartum on reproduction outcomes in pasture-grazed, seasonal-calving dairy cows. Cows (n = 948) from 3 commercial herds were blocked by age (2, 3, and >3 yr), breed, and expected calving date and randomly assigned to 1 of 2 postpartum treatment groups: high starch (34.7 ± 1.9% nonstructural carbohydrate; mean ± SD) or low starch (22.5 ± 0.4% nonstructural carbohydrate). The high-starch group in all 3 farms received 4.0 to 4.5 kg/d of a 75:25 cracked corn:barley grain mixture in the dairy parlor, split evenly between the morning and afternoon milkings. The low-starch cows received 5.0 to 5.5 kg/d of a 50:50 mixture of palm kernel meal:soy hulls (herds 1 and 3) fed in the parlor; low-starch cows in the remaining herd (herd 2) did not receive a concentrate feed. Cows were cograzed on ryegrass–white clover dominant pastures and were offered corn silage (herds 1 and 3) and canola, corn distillers grain, and palm kernel meal (herd 1) throughout the study. At 1 mo before the start of the seasonal breeding period, the high-starch supplement was removed, and within each herd treatment groups were managed similarly through breeding. Presence of purulent vaginal discharge was assessed at 28 DIM, and tail paint was assessed weekly from 2 to 6 wk postpartum for signs of estrus. The interval to first observed estrus was unaffected by treatment (32.7 vs. 33.5 ± 2 d for high and low starch, respectively), but there were tendencies for a herd × treatment interaction for proportion of cows pregnant to first service and for pregnancy within 6 wk. This interaction was significant for the proportion of cows finally pregnant; a lower proportion of high-starch cows were pregnant to first service, pregnant by 6 wk, and pregnant by the end of the seasonal breeding period in herd 1, but diet did not affect these outcomes in the other herds. Our results do not support a positive effect on reproduction from increasing dietary starch in seasonally bred grazing dairy cows. However, the interactions indicate variability in the herd response to dietary starch early postpartum and imply that pregnancy rate could potentially be compromised through the provision of starch to grazing dairy cows in early lactation (i.e., prebreeding). The experiment was not designed to define the reasons for these interactions, but differences should be considered in future research on the subject.

Tailings dam failures have received significant attention in recent years due to the catastrophic downstream consequences, as evidenced by the 2019 Feijao disaster in Brazil and numerous precedents. This paper presents a timely review of tailings flows with the support of a comprehensive global database of 63 cases that have been remotely analyzed through a compilation of satellite imagery, digital elevation models and literature. The synthesis provides insight into the influence of impoundment conditions, preconditioning and trigger variables, failure mechanisms and the downstream environment on tailings flow behaviour. The database also sheds light on the limitations of data quality and availability in the public domain. Magnitude-frequency statistics indicate that tailings dam breaches that have produced catastrophic mass flows with total outflow volumes of ≥1 M m3 have occurred at a mean recurrence interval of 2–3 years over the period 1965–2020. Weather hazards and impoundment drainage issues are identified as major causative variables. The occurrence of liquefaction and/or the incorporation of free water are sufficient conditions to trigger extremely rapid, highly mobile behaviour. Travel path confinement and steeper bed slopes enhance flow velocities (peak of 25–30 m/s) and kinetic energy, whereas flow mobility appears to be exacerbated along major rivers. Although general trends may be observed in empirical observations, such efforts are prone to substantial uncertainty due to the complexity and variability of site conditions (that are typically unaccounted for in broad statistical approaches) as well as poor data availability and/or quality for many of the selected cases. This highlights the importance of performing site-specific investigations through numerical models, laboratory tests and field observations to better predict post-breach behaviour (ideally within a probabilistic framework) when undertaking site assessments.

The high consequences of recent large open pit slope failures have increased industry and regulatory interest in establishing exclusion zones beneath an impending pit wall failure. This paper proposes a methodology to delineate an exclusion zone for an impending pit slope failure. The focus of this paper is a framework for the management of life loss risk to the most exposed individual. The probability of the landslide occurring and the probability of the resulting landslide being very or extremely rapid are described in this paper. Set in a probabilistic framework , empirical runout analysis tools are useful for estimating the spatial probability of impact throughout the open pit and establishing exclusion zones. Runout exceedance probability charts calibrated to a large dataset of pit slope failures are provided. The temporal probability that the most exposed individual is present and cannot be evacuated is also described. The resulting risk is mapped across the pit floor by dividing it into square grid cells and calculating the probability of death to the most exposed individual for each cell. The cells can be colour coded to indicate specific risk exposure ranges relative to the exclusion zone set. A conceptual case study is used to illustrate the proposed methods.

A contributing factor to declining fertility in dairy cows is an activated inflammatory system associated with uterine infection. Detecting uterine disease using biomarkers may allow earlier diagnosis and intervention with resultant improvements in fertility. Exosomes are known to participate in intercellular communication, paracrine, and endocrine signaling. Exosomes carry a cargo of proteins, lipids, and nucleic acids that represent specific cellular sources. Prostaglandins are lipids that are critical determinants of bovine fertility. In this study exosomes were isolated from the plasma of cows before (d 0) and during (d 10) the study in healthy animals or those with an induced uterine infection in a 2 × 2 factorial design. Exosomes were characterized for size and number (nanoparticle tracking analysis), exosomal marker expression (Western blot), and morphology (transmission electron microscopy). No significant differences were observed in exosome size or number. The abundance of exosome-enriched markers was confirmed in noninfected and infected animals. Transmission electron microscopy confirmed the morphology of the exosomes. These exosomes were co-incubated with bovine endometrial epithelial and stromal cells. Exosomes from d-10-infected animal plasma decreased PGF2α production in endometrial epithelial but not stromal cells. For future research, the identification of effectors in the cargo may provide a useful basis for early diagnosis of uterine infection using an exosomal characterization approach.

This paper proposes and demonstrates a two-layer depth-averaged model with non-hydrostatic pressure correction to simulate landslide-generated waves. Landslide (lower layer) and water (upper layer) motions are governed by the general shallow water equations derived from mass and momentum conservation laws. The landslide motion and wave generation/propagation are separately formulated, but they form a coupled system. Our model combines some features of the landslide analysis model DAN3D and the tsunami analysis model COMCOT and adds a non-hydrostatic pressure correction. We use the new model to simulate a 2007 rock avalanche-generated wave event at Chehalis Lake, British Columbia, Canada. The model results match both the observed distribution of the rock avalanche deposit in the lake and the wave run-up trimline along the shoreline. Sensitivity analyses demonstrate the importance of accounting for the non-hydrostatic dynamic pressure at the landslide-water interface, as well as the influence of the internal strength of the landslide on the size of the generated waves. Finally, we compare the numerical results of landslide-generated waves simulated with frictional and Voellmy rheologies. Similar maximum wave run-ups can be obtained using the two different rheologies, but the frictional model better reproduces the known limit of the rock avalanche deposit and is thus considered to yield the best overall results in this particular case.