A national map of Canadian Fire Behaviour Prediction (FBP) Fuel Types (FT) developed from public data sources. The resolution of the raster grid is 30m, classified from the Spatialized Canadian National Forest Inventory (SCANFI) dataset, ecozones of Canada, and the National Burned Area Composite (NBAC). The purpose of the dataset is to characterize Canadian forests into fuel types for use in Fire Behaviour Prediction calculations as well as for situational awareness of national fire potential.

11 tagged Blue whales (Balaenoptera musculus) were tracked during the daytime movements as well as the feeding behaviour in the St. Lawrence River estuary. Kernel density was applied to derminate the high density feeding areas of all individuals combined (30, 40, 50, 60, 75, 95 %).Doniol-Valcroze T, Lesage V, Giard J, Michaud R, 2012. Challenges in marine mammal habitat modelling: evidence of multiple foraging habitats from the identification of feeding events in blue whales. Endang Species Res, Vol. 17 : 255–268, doi : 10.3354/esr00427(English version only)

The blue whale (Balaenopterus musculus) is a wide-ranging cetacean that can be found in all oceans, inhabiting coastal and oceanic habitats. In the North Atlantic, little is known about blue whale distribution and genetic structure, and if whether animals found in Icelandic waters, the Azores, or Northwest Africa are part of the same population as those from the Northwest Atlantic. In the Northwest Atlantic, seasonal movements of blue whales and habitat use, including the location of breeding and wintering areas, are poorly understood.The behaviour of remotely-monitored animals can be inferred from a time series of location data. This is because animals tend to demonstrate stochasticity in their movement paths as a result of spatial variation in environmental characteristics, such as topography or prey density (Curio 1976; Gardner et al. 1989; Turchin 1991; Wiens et al. 1993). Predators are expected to decrease travel speed and/or increase turning frequency and turning angle when a suitable resource, e.g., food patch, is encountered (Turchin 1991), otherwise known as area-restricted search (ARS). In contrast, animals in transit or travelling tend to move at faster and more regular speeds, with infrequent and smaller turning angles (Kareiva and Odell 1987; Turchin 1998).Based on satellite telemetry to track the seasonal movements of 24 blue whales from eastern Canada in 2002 and from 2010 to 2015, it was possible to estimate trajectories and locations where ARS behaviour of blue whales was inferred at a 4h time interval.To assess blue whale movements and behavior, a Bayesian switching statespace model (SSSM) was applied to Argos-derived telemetry data (Jonsen et al. 2005; Jonsen et al. 2013). An SSSM essentially estimates animal location at fixed time intervals, movement parameters and behavioral patterns.Two important sources of uncertainty can be measured separately: estimation error resulting from inaccurate observations (Argos location error) and process variability linked to the stochasticity of the movement process (behavior mode estimation) (Jonsen et al. 2003; Patterson et al. 2008).The points visible on land are the result of errors in the Argos geographic position calculation. They have been deliberately left unchanged to assess the performance of the model, which was able to clean up some positions, but not all.Lesage, V., Gavrilchuk, K., Andrews, R.D., and Sears, R. 2016. Wintering areas, fall movements and foraging sites of blue whales satellite-tracked in the Western North Atlantic. DFO Can. Sci. Advis. Sec. Res. Doc. 2016/078. v + 38 p.

Acoustic telemetry allows detailed observations of the movement behaviour of many species and as tags get smaller, smaller organisms may be tagged. The number of studies using acoustic telemetry to evaluate marine invertebrate movement is growing, but novel attachment methods include unknowns about the effects of tagging procedures on individual survival and behaviour. This study compared methods of tag attachment on green sea urchins (Strongylocentrotus droebachiensis) to determine the feasibility of using acoustic transmitters to track echinoid movement. Four tagging methods were compared in the lab and tag retention, urchin condition, and survival analysed. Two tagging methods (Dyneema® fishing line and T-bar tags) were evaluated in the field using an existing acoustic telemetry array. Urchins were tagged and the study area revisited one week and 2 months post-release by scuba divers to estimate movement and tag retention. The best methods in the lab, with high tag retention, survival, and minimal effects on urchin condition, were fishing line methods. T-bar tags, although showing high tag retention, caused significant mortality and had deleterious long-term effects on urchin condition and behaviour. After 2 months in the field, as in the lab, fishing line was a more effective tagging method. Urchins tagged with fishing line showed increased estimates of space occupancy compared to T-bar-tagged urchins and a single fishing-line tagged individual was found by divers in good health after 80 days. Combined, these laboratory and field results demonstrate the feasibility of using acoustic telemetry to observe urchin movement. Results strongly suggest that surgical attachment methods that minimize injuries at the attachment site should be prioritized for echinoid tagging studies. Together, lab and field tests indicate that acoustic telemetry is a promising method to examine marine echinoid movement over ecologically relevant spatial and temporal scales.The data available includes the laboratory data (tag retention, survival, diameter, wet weight, gonad weight and condition/righting time) and the field data (metadata and acoustic telemetry detections for tagged individuals, results of diver searches and 2-day estimates of movement measured in the field). Data from the laboratory experiment and diver observations in the field have been verified and undergone a control for quality. Acoustic telemetry detections are raw detection files (unfiltered); see the published article for a description of how the data were treated for analyses (https://doi.org/10.1186/s40317-022-00309-8).

The Global Ensemble Prediction System (GEPS) carries out physics calculations to arrive at probabilistic predictions of atmospheric elements from the current day out to 16 days into the future (up to 39 days twice a week on Mondays and Thursdays at 00UTC for calculating forecast anomalies). The GEPS produces different outlooks (scenarios) to estimate the forecast uncertainties due to the nonlinear (chaotic) behavior of the atmosphere. The probabilistic predictions are based on an ensemble of 20 scenarios that differ in their initial conditions, their physics parameters which are randomly perturbed by a Stochastic Parameter Perturbation (SPP) method, and the stochastic perturbations (kinetic energy). A control member that is not perturbed is also available. Weather elements include temperature, precipitation, cloud cover, wind speed and direction, humidity and others. This product contains raw numerical results of these calculations. Geographical coverage is global. Data is available on some fifteen vertical levels on a global latitude-longitude uniform grid with 0.5 degree horizontal resolution (about 39km). Predictions are performed twice a day.

PURPOSE:Ringed seals (Pusa hispida) rely on sea ice as habitat throughout their life history and inhabit a broad latitudinal range with diverse sea-ice conditions. Anthropogenic climate warming is triggering poleward species redistributions, highlighting the importance of understanding how species distributions and abundance vary along latitudinal gradients. Using ringed seals as a model species, the purpose was to estimate density via aerial surveys along a latitudinal gradient in the eastern Canadian Arctic to investigate latitudinal trends in the ringed seals response to regional variation in sea-ice conditions. DESCRIPTION:Ringed seals (Pusa hispida) rely on sea ice as habitat throughout their life history and inhabit a broad latitudinal range with diverse sea-ice conditions, making them a model species to study patterns in density along a spatial-environmental gradient. We estimated the density of ringed seals from systematic aerial surveys along a latitudinal gradient in the eastern Canadian Arctic to investigate latitudinal trends in the ringed seals response to regional variation in sea-ice conditions. Ringed seals exhibited similar densities at lower and intermediate latitudes, while higher latitudes displayed an order of magnitude lower ringed seal density. This shift is concurrent with the transition in ice conditions from predominantly first-year ice at lower latitudes to primarily multiyear ice at higher latitudes. These findings indicate that the variation in icescapes across the ringed seal’s vast range influences their density. The shift in sea-ice conditions may also have consequences for biological productivity that supports their diet. Our results highlight a likely non-uniform response of ringed seals to ongoing sea-ice recession across the Arctic.

The initial objective of this dataset was to study the seasonal movement patterns of harbour seals (Phoca vitulina) in the St. Lawrence Estuary and Sable Island. This study was part of a larger program that studied the foraging behavior of the species.Ten harbour seals were captured using gillnets from 1994 to 1998 at three sites in the St. Lawrence Estuary (Bic, n=1 individual; île Blanche, n=1; Métis-sur-Mer, n=5) and one site on Sable Island (n=3 individuals). The individuals were equipped with a satellite-linked time-depth recorder (Type3.10, Wildlife Computers) equipped with an Argos tag and placed on the back of the neck. For most individuals, satellite tracking began in September and continued until the following spring.The dataset consists of series of geographic locations of ten harbor seals with associated dates and times and movement speeds calculated from successive locations.The location data were only filtered based on the validity class provided by Argos. Class Z locations were excluded.

Inventory of building footprints in the City of Rouyn-Noranda.**This third party metadata element was translated using an automated translation tool (Amazon Translate).**

All stops in the public transport network managed by the City of Rouyn-Noranda**This third party metadata element was translated using an automated translation tool (Amazon Translate).**

Itinerary of the various bus routes managed by the City of Rouyn-Noranda**This third party metadata element was translated using an automated translation tool (Amazon Translate).**