Sightings data were collected by the Mingan Island Cetacean Study (MICS) from 1980 to 2008 with annual surveys realised in the Gulf of St. Lawrence between the end of may and early november. Surveys were conducted using inflatable boats enabling the close approaches necessary to photograph and biopsy blue whales.The aim of this project was to provide additional information for designating blue whale critical habitat as required under the Canadian Species at Risk Act.For more details consult the following report:Ramp, C. and Sears, R. 2013. Distribution, densities, and annual occurrence of individual blue whales (Balaenoptera musculus) in the Gulf of St. Lawrence, Canada from 1980-2008. DFO Can. Sci. Advis. Sec. Res. Doc. 2012/157. vii + 37 p.http://www.dfo-mpo.gc.ca/csas-sccs/Publications/ResDocs-DocRech/2012/2012_157-eng.htmlData of blue whale sightings, collected by the MICS, have been analysed per km of effort in 3 x 3 km grid cells in the Gulf of St. Lawrence for the 2000-2008 period.

A modelling analysis conducted by Fisheries and Oceans Canada (DFO) identified these areas as the most suitable habitat for Blue whales: Gulf of St. Lawrence, waters off the southern coast of Newfoundland, the region of Mecatina Trough, the Esquiman Channel and the continental shelf margin off Nova Scotia. They represent important areas for foraging, feeding and socializing for Blue whales. The sources of data used to determine these important areas (by the enclosing boxes method) and the annual and seasonal cycles of Blue whale travel patterns include, but are not limited to, radio and satellite telemetry, passive acoustic monitoring, line-transect aerial surveys, anecdotal reports of observations and modelling.This layer does not represent the general distribution of the Blue whale. Important areas have been identified by reviewing several sources of information and to the best of researchers' knowledge. Several information about Blue whales, their behaviour and habitat use are still unknown. Data is scarce in some areas during winter periods. Observation efforts mostly occur during the summer period, however, data sources can validate their presence during seasons when the observation effort is lower. The Mecatina trough region represents an important area based on historical and non-current data. The presence data per month refers strictly to the information available in the cited research document, and does not express the absence of the species outside the months when a presence was validated. The presented information is valid until the following research survey.Reference:Lesage, V., J.-F. Gosselin, J. W. Lawson, I. McQuinn, H. Moors-Murphy, S. Plourde, R. Sears. and Y. Simard. 2018. Habitats important to blue whales (Balaenoptera musculus) in the Western North Atlantic. DFO Can. Sci. Advis. Sec. Res. Doc. 2016/080: iv + 50 p.

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.

The St. Lawrence Estuary is known as a summer foraging area for several species of marine mammals, including several species of rorquals. Among these is the blue whale, which feeds almost exclusively on euphausiids. Therefore, the abundance, distribution and local density of krill should logically be a strong explanatory variable for the distribution of blue whales. However little is known about the spatial association of blue whales with the aggregation dynamics of krill in eastern Canada. Six years of acoustic surveys, conducted in August from 2009 to 2014, were undertaken to study the medium- and small-scale distribution of krill within the northwestern Gulf of St. Lawrence and estuary. The data shows a mosaic of the maximum annual density of arctic krill (T. raschii) made from these surveys.McQuinn, I.H., Gosselin, J.-F., Bourassa, M.-N., Mosnier, A., St-Pierre, J.-F., Plourde, S., Lesage, V., Raymond, A. 2016. The spatial association of blue whales (Balaenoptera musculus) with krill patches (Thysanoessa spp. and Meganyctiphanes norvegica) in the estuary and northwestern Gulf of St. Lawrence. DFO Can. Sci. Advis. Sec. Res. Doc. 2016/104. iv + 19 p.

General distribution of Humpback Whales in the Estuary and Gulf of St. Lawrence based on all identified whales from the entire MICS database (Mingan Island Cetacean Study).Additional informationThe MICS (Mingan Island Cetacean Study) has been collecting and compiling in a photo-identification catalogue, blue whale (and other type of whales) sightings for the western North Atlantic since 1979. Since 1987, the material and sampling protocol has been being relatively stable, neither random nor systematic. Field work is conducted abord inflatable boats. Because the whole Gulf ot St. Lawrence cannot be thoroughly studied, MCIS conducts surveys in known whale aggregation areas. The spatial effort is also weather dependent and is mainly constrained by wind direction and strength. Therefore, the study area is not homogeneously covered.Each whale observation is associated with a picture that allows individual identification based on the animal's pigmentation pattern. For more details consult the mentionned report:Gagné, J.A., Ouellet, P., Savenkoff, C., Galbraith, P.S., Bui, A.O.V. et Bourassa, M.-N. Éd. 2013. Rapport intégré de l’initiative de recherche écosystémique (IRÉ) de la région du Québec pour le projet : les espèces fourragères responsables de la présence des rorquals dans l’estuaire maritime du Saint-Laurent. Secr. can. de consult. sci. du MPO. Doc. de rech. 2013/086. vi + 181 p.

These products are derived from RGB (red/green/blue) images, a satellite processing technique that uses a combination of satellite sensor bands (also called channels) and applies a red/green/blue (RGB) filter to each of them. The result is a false-color image, i.e. an image that does not correspond to what the human eye would see, but offers high contrast between different cloud types and surface features. The on-board sensor of a weather satellite obtains two basic types of information: visible light data (reflected light) reflecting off clouds and different surface types, also known as "reflectance", and infrared data (emitted radiation) which are long-wave radiations emitted by clouds and surface features. RGBs are specially designed to combine this type of satellite data, resulting in an information-rich final product. Four types of products are currently generated from the GOES-West and GOES-East satellites: "NightIR" and "NightMicrophysics", at 2km resolution, are generated 24 hours a day with infrared channels, so are visible both night and day, and "NaturalColour" and "DayCloudConvection", at 1km resolution, which combine visible light channels with infrared channels; their higher resolution makes the latter two products more popular, but they are not available during most of the night (between 02UTC and 07UTC for GOES-Est, and between 06UTC and 11UTC for GOES-Ouest) given the absence of reflected sunlight. Other RGB products should be added gradually in the future to meet different needs.

Likelihood of Presence of Finback Whales in the Bay of Fundy and Port Hawkesbury Area Response Plan. The Coastal Oceanography and Ecosystem Research section (DFO Science) reviewed reported opportunistic whale sightings and local knowledge sources to estimate areas where Finback whales are seasonally present and delineate these areas.A version of this dataset was created for the National Environmental Emergency Center (NEEC) following their data model and is available for download in the Resources section.Cite this data as: Lazin, G., Hamer, A.,Corrigan, S., Bower, B., and Harvey, C. Data of: Likelihood of presence of Finback Whale in Area Response Planning pilot areas. Published: June 2018. Coastal Ecosystems Science Division, Fisheries and Oceans Canada, St. Andrews, N.B. https://open.canada.ca/data/en/dataset/7e2f85b3-19eb-4ecf-8557-69c8df1bc084

These products are derived from RGB (red/green/blue) images, a satellite processing technique that uses a combination of satellite sensor bands (also called channels) and applies a red/green/blue (RGB) filter to each of them. The result is a false-color image, i.e. an image that does not correspond to what the human eye would see, but offers high contrast between different cloud types and surface features. The on-board sensor of a weather satellite obtains two basic types of information: visible light data (reflected light) reflecting off clouds and different surface types, also known as "reflectance", and infrared data (emitted radiation) which are short-wave and long-wave radiation emitted by clouds and surface features. RGBs are specially designed to combine this type of satellite data, resulting in an information-rich final product.Other products are based on the enhancement of channel data for a single wavelength, also aimed at highlighting meteorological features of the observed surface or clouds, but in a simpler way since only a single wavelength is involved. This older approach is still useful today, as its simplicity makes image interpretation easier in some cases.

Layers that present various important parameters such as inventories, presence, sightings, distribution, relative occurrence or catch rates, critical habitat, breeding and feeding areas, potential spawning and haul-out sites for the different species with status under the Species at Risk Act (SARA).The act classifies those species as being either extirpated, endangered, threatened, or of special concern. Under SARA, Fisheries and Oceans Canada must produce recovery strategies and action plans for aquatic species listed as endangered or threatened. The act is part of Canada’s strategy to protect hundreds of wild plants and animal species from becoming extinct, and to help in their recovery.The different species represented by the layers are the following:1. American shad (Alosa sapidissima)2. Atlantic sturgeon (Acipenser oxyrinchus)3. Atlantic wolffish (Anarhichas lupus)4. Beluga whale (Delphinapterus leucas)5. Blue whale (Balaenoptera musculus)6. Copper redhorse (Moxostoma hubbsi)7. Eelgrass (Zostera marina)8. Grey seal (Halichoerus grypus)9. Harbor seal (Phoca vitulina)10. Humpback whale (Megaptera novaeangliae)11. Lake sturgeon (Acipenser fulvescens)12. Lumpfish (Cyclopterus lumpus)13. Northern wolffish (Anarhichas denticulatus)14. Rainbow smelt (Osmerus mordax)15. Sea pens (Pennatulacea)16. Seaweed17. Smooth skate (Malacoraja senta)18. Sponges19. Spotted wolffish (Anarhichas minor)20. Striped bass (Morone saxatilis)21. Thorny skate (Amblyraja radiata)22. Winter skate (Leucoraja ocellata)