PURPOSE:The focus of this research is on changes in the distribution of killer whales in the Canadian Arctic, which is within the field of marine biogeography and marine megafauna. Our research details change in killer whale presence and ties it to changes in sea ice coverage. These are novel results, presenting trends in the arrival and departure dates of killer whales into the eastern Canadian Arctic for the first time. We go on to discuss the impacts of these changes on other aspects of Arctic ecosystems and how increasing in killer whale presence might affect other species and the management of those species in Canada. Killer whales are a widespread species of interest, especially in the Canadian Arctic as their presence is tied to multiple aspects of a region rapidly changing from the effects of climate change. DESCRIPTION:This study examines 20 years of killer whale (Orcinus orca) sightings in the eastern Canadian Arctic, drawing from a comprehensive sighting database spanning 1850-2023. Despite inherent biases favoring data collection near communities and coastal areas, spatiotemporal analyses reveal significant shifts in killer whale distribution linked to changing sea ice conditions. We developed a clustering metric representing the mean distance to the five nearest sightings and results show that killer whales are progressively moving away from historically high-use areas and that sighting locations are becoming more dispersed over time. A significant year × sea ice interaction indicates observations occur earlier during their arrival period at lower sea ice concentrations over time, suggesting that declining sea iceconcentration contributes to earlier arrival. Conversely, for departure periods, killer whales are observed farther south later in the year, likely linked to earlier freeze-up at higher latitudes, and are overall observed later into the year over time. This trend has led to a near doubling of their average presence from 26 days in 2002 to 48 days in 2023 (27 July to 13 September) reflecting an extended open-water season. These findings underscore the prolonged seasonal use of Arctic regions by killer whales, driven by diminishing sea ice and expanding openwater habitat. Such shifts highlight potential implications for Arctic marine ecosystems as killer whales increasingly overlap with endemic species.

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 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.

The Scotian Shelf population of northern bottlenose whales (Hyperoodon ampullatus) is listed as Endangered under Canada’s Species at Risk Act. Partial critical habitat was identified for this population in the Recovery Strategy first published in 2010 (Fisheries and Oceans Canada 2016), and three critical habitat areas were designated along the eastern Scotian Shelf, encompassing the Gully, Shortland Canyon, and Haldimand Canyon (shapefile available online: https://open.canada.ca/data/en/dataset/db177a8c-5d7d-49eb-8290-31e6a45d786c). However, the Recovery Strategy recognized that additional areas may constitute critical habitat for the population and recommended further studies based on acoustic and visual monitoring to assess the importance of inter-canyon areas as foraging habitat and transit corridors for northern bottlenose whales.In a subsequent study of the distribution, movements, and habitat use of northern bottlenose whales on the eastern Scotian Shelf (Stanistreet et al. in press), several sources of data were assessed and additional important habitat was identified in the inter-canyon areas located between the Gully, Shortland Canyon, and Haldimand Canyon (DFO 2020). A summary of the data inputs, analyses, and limitations is provided below.Year-round passive acoustic monitoring conducted with bottom-mounted recorders at two inter-canyon sites from 2012-2014 revealed the presence and foraging activity of northern bottlenose whales in these areas throughout much of the year, with a seasonal peak in acoustic detections during the spring. Detections from acoustic recordings collected during vessel-based surveys provided additional evidence of species occurrence in inter-canyon areas during the summer months. Photo-identification data collected in the Gully, Shortland, and Haldimand canyons between 2001 and 2017 were used to model the residency and movement patterns of northern bottlenose whales within and between the canyons, and demonstrated that individuals regularly moved between the three canyons as well as to and from outside areas. Together, these results indicated a strong degree of connectivity between the Gully, Shortland, and Haldimand canyons, and provided evidence that the inter-canyon areas function as important foraging habitat and movement corridors for Scotian Shelf northern bottlenose whales. The inter-canyon habitat area polygon was delineated using the 500 m depth contour and straight lines connecting the southeast corners of the existing critical habitat areas, but these boundaries are based on limited spatial information on the presence of northern bottlenose whales in deeper waters. More data are needed to determine whether this area fully encompasses important inter-canyon habitat, particularly in regard to the deeper southeastern boundary. Similarly, the full extent of important habitat for Scotian Shelf northern bottlenose whales remains unknown, and potential critical habitat areas outside the canyons and inter-canyon areas on the eastern Scotian Shelf have not been fully assessed. See DFO (2020) for further information.References:DFO. 2020. Assessment of the Distribution, Movements, and Habitat Use of Northern Bottlenose Whales on the Scotian Shelf to Support the Identification of Important Habitat. DFO Can. Sci. Advis. Sec. Sci. Advis. Rep. 2020/008. https://www.dfo-mpo.gc.ca/csas-sccs/Publications/SAR-AS/2020/2020_008-eng.html Fisheries and Oceans Canada. 2016. Recovery Strategy for the Northern Bottlenose Whale, (Hyperoodan ampullatus), Scotian Shelf population, in Atlantic Canadian Waters [Final]. Species at Risk Act Recovery Strategy Series. Fisheries and Oceans Canada, Ottawa. vii + 70 pp. https://www.canada.ca/en/environment-climate-change/services/species-risk-public-registry/recovery-strategies/northern-bottlenose-whale-scotian-shelf.html Stanistreet, J.E., Feyrer, L.J., and Moors-Murphy, H.B. In press. Distribution, movements, and habitat use of northern bottlenose whales (Hyperoodon ampullatus) on the Scotian Shelf. DFO Can. Sci. Advis. Sec. Res. Doc. [https://publications.gc.ca/collections/collection_2022/mpo-dfo/fs70-5/Fs70-5-2021-074-eng.pdf]Cite this data as: Stanistreet, J.E., Feyrer, L.J., and Moors-Murphy, H.B. Data of: Northern bottlenose whale important habitat in inter-canyon areas on the eastern Scotian Shelf. Published: June 2021. Ocean Ecosystems Science Division, Fisheries and Oceans Canada, Dartmouth, N.S. https://open.canada.ca/data/en/dataset/9fd7d004-970c-11eb-a2f3-1860247f53e3

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.

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.

Likelihood of Presence of Bottlenose Whales in the Bay of Fundy and the 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 Northern Bottlenose 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 Bottlenose 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/29dd835b-7c96-4c62-b558-275dfe13cbe9

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.

Modeled data showing the likely distribution of gray whales. CRIMS is a legacy dataset of BC coastal resource data that was acquired in a systematic and synoptic manner from 1979 and was intermittently updated throughout the years. Resource information was collected in nine study areas using a peer-reviewed provincial Resource Information Standards Committee consisting of DFO Fishery Officers, First Nations, and other subject matter experts. There are currently no plans to update this legacy data.

Modeled data showing the likely distribution of humpback whales. CRIMS is a legacy dataset of BC coastal resource data that was acquired in a systematic and synoptic manner from 1979 and was intermittently updated throughout the years. Resource information was collected in nine study areas using a peer-reviewed provincial Resource Information Standards Committee consisting of DFO Fishery Officers, First Nations, and other subject matter experts. There are currently no plans to update this legacy data.