The Steller sea lion (Eumetopias jubatus) is the largest of all sea lions and enjoys a lifespan of up to thirty years. In Canada, the Steller can be spotted along the rocky coast of British Columbia. These highly mobile marine mammals typically travel alone or in small groups, but they congregate in large numbers at traditional rookeries and haul-outs during the mating and pupping season. The population was severely depleted in Canada but following its protection in 1970, the size of the adult population has more than doubled.The survey targeted Steller sea lions and sites were chosen based on knowledge of historically occupied rookeries and haul-out sites with nearby areas monitored for potential shifts in distribution. This dataset contains counts that have been collected from sightings of individuals in the 2016/2017 survey season.

The data represent the distribution of species of amphibians, reptiles, reptiles, terrestrial mammals and freshwater and migratory fish in Quebec.The files represent:amphibians: 21 speciesreptiles: 17 speciesterrestrial mammals: 69 speciesfreshwater and migratory fish: 118 speciesThe ranges were established on the basis of various sources of information and validated by the Main Directorate of expertise on terrestrial fauna (DPEFT), the Main Directorate for Threatened or Vulnerable Species (DPEMV) and the Main Directorate of Expertise on Aquatic Wildlife (DPEFA) of the Ministry of the Environment, the Fight against Climate Change, Climate Change, Wildlife and Parks (MELCCFP).The ranges of species of _freshwater and migratory fish_ are also illustrated in the [“Freshwater Fish of Quebec”] poster (https://cdn-contenu.quebec.ca/cdn-contenu/faune/documents/animaux/affiche-poissons-eau-douce.pdf). Some ranges have been slightly modified since they were included in the poster.__There may be differences between the ranges of the species shown in the files and the current spatial distribution of the species. __The distribution areas were produced on a small scale; they provide indicative information on the presence of the species in Quebec.The cards are the property of MELCCFP.__Atten:__ The ranges of marine mammals that frequent the coasts of the province of Quebec are not included in this dataset.**This third party metadata element was translated using an automated translation tool (Amazon Translate).**

Description:These commercial whale watching data are comprised of two datasets. First, the ‘whale_watching_trips_jun_sep_british_columbia’ data layer summarizes commercial whale watching trips that took place in 2019, 2020 and 2021 during the summer months (June to September). The second data layer, ‘wildlife_viewing_events_jun_sep_british_columbia’ contains estimated wildlife viewing events carried out by commercial whale watching vessels for the same years (2019, 2020 and 2021) and months (June to September). Commercial whale watching trips and wildlife viewing events are summarized using the same grid, and they can be related using the unique cell identifier field ‘cell_id’. The bulk of this work was carried out at University of Victoria and was funded by the Marine Environmental Observation, Prediction and Response (MEOPAR) Network under the ‘Whale watching AIS Vessel movement Evaluation’ or WAVE project (2018 – 2022). The aim of the WAVE project was to increase the understanding of whale watching activities in Canada’s Pacific region using vessel traffic data derived from AIS (Automatic Identification System). The work was finalized by DFO Science in the Pacific Region. These spatial data products of commercial whale watching operations can be used to inform Marine Spatial Planning, conservation planning activities, and threat assessments involving vessel activities in British Columbia.Methods:A list of commercial whale watching vessels based in British Columbia and Washington State and their corresponding MMSIs (Maritime Mobile Service Identity) was compiled from the whale watching companies and Marine Traffic (www.marinetraffic.com). This list was used to query cleaned CCG AIS data to extract AIS positions corresponding to commercial whale watching vessels. A commercial whale watching trip was defined as a set of consecutive AIS points belonging to the same vessel departing and ending in one of the previously identified whale watching home ports. A classification model (unsupervised Hidden Markov Model) using vessel speed as the main variable was developed to classify AIS vessel positions into wildlife-viewing and non wildlife viewing events. Commercial whale watching trips in the south and north-east of Vancouver Island were limited to a duration of minimum 1 hour and maximum 3.5 hours. For trips in the west coast of Vancouver island the maximum duration was set to 6 hours. Wildlife-viewing events duration was set to minimum of 10 minutes to a maximum of 1 hour duration. For more information on methodology, consult metadata pdf available with the Open Data record.References:Nesdoly, A. 2021. Modelling marine vessels engaged in wildlife-viewing behaviour using Automatic Identification Systems (AIS). Available from: https://dspace.library.uvic.ca/handle/1828/13300.Data Sources:Oceans Network Canada (ONC) provided encoded AIS data for years 2019, 2020 and 2021, within a bounding box including Vancouver Island and Puget Sound used to generate these products. This AIS data was in turn provided by the Canadian Coast Guard (CCG) via a licensing agreement between the CCG and ONC for the non-commercial use of CCG AIS Data. More information here: https://www.oceannetworks.ca/science/community-based-monitoring/marine-domain-awareness-program/ Molly Fraser provided marine mammal sightings data collected on board a whale watching vessels to develop wildlife-viewing events classification models. More information about this dataset here: https://www.sciencedirect.com/science/article/pii/S0308597X20306709?via%3DihubUncertainties:The main source of uncertainty is with the conversion of AIS point locations into track segments, specifically when the distance between positions is large (e.g., greater than 1000 meters).

The Broad Ecosystem Inventory (BEI) Classification provides broad regional information about the distribution of ecosystems throughout the province and the value of these ecosystems to wildlife. This work is done in order to facilitate the use of wildlife information in broad provincial and regional land and resource planning initiatives. Broad Ecosystem Units are mapped based on imagery of the provincial land base generally captured at a scale of 1:250,000. BEI mapping represents forest conditions from approximately 1995 to 2000. The BEI Classification was used to produce wildlife habitat capability and suitability mapping following Provincial Wildlife Habitat Ratings (WHR) Standards (Resource Inventory Committee 1999). Habitat classifications were based on BEI units. BEI units were evaluated and rated to determine the habitat potential (capability) and current habitat conditions (suitability) for selected wild ungulates and furbearers within each seral stage within each Broad Ecosystem Unit (and related site modifier variation) within the framework of Ecosections and Biogeoclimatic Sub-zone/Variants for their ability to supply the species’ necessary life requisites. Regional Wildlife and Habitat biologists, technicians, Forest Ecosystem Specialists, and consulting species experts provided species habitat ratings for each region of the province. Wildlife habitat capability and suitability mapping was completed for the following wild ungulates and furbearers: Northwestern Moose, Alaskan Moose, Shiras' Moose, Bison, Rocky Mountain Elk, Roosevelt Elk, Columbian Black-tailed Deer, Rocky Mountain Mule Deer, Sitka Black-tailed Deer, White-tailed Deer, Dakota White-tailed Deer, Northwestern White-tailed Deer, Boreal Woodland Caribou, Mountain Woodland Caribou, Northern Woodland Caribou, Lynx, Bobcat, and American Badger. Habitat mapping followed Provincial Wildlife Habitat Ratings (WHR) Standards (Resource Inventory Committee 1999).

This layer represents the seasonal distribution of the St. Lawrence Estuary beluga whale population (Delphinapterus leucas). Three groups are represented: females with calf, adult males and mixed sectors. Herd distribution was defined using Fisheries and Oceans Canada (DFO) published data about beluga whales (see references).Herd distribution areas are only valid during the summer, and the uses of these areas by the herds are unknown.Data source :Michaud, R. 1993. Distribution estivale du béluga du St-Laurent; synthèse 1986-1992. Can. Tech. Rep. Fish. Aquat. Sci. 1906: vi + 28 p.

Marine protected areas (MPAs) are one among a number of spatial management tools, and are defined as areas that are established for the long-term, and managed through legal or other effective means, to achieve the long-term conservation of nature with associated ecosystem services and cultural values.Currently, Fisheries and Oceans Canada has a number of MPAs designated under the Oceans Act and Areas of Interest for new MPAs at various stages of progress towards designation. These areas are ecologically significant, with species and/or features that require special management consideration.  An Oceans Act MPA can be established for any of the six conservation purposes outlined in the Act:• The conservation and protection of commercial and non-commercial fishery resources, including marine mammals, and their habitats;  • The conservation and protection of endangered or threatened marine species, and their habitats;  • The conservation and protection of unique habitats;  • The conservation and protection of marine areas of high biodiversity or biological productivity; • The conservation and protection of any other marine resource or habitat as is necessary to fulfill the mandate of the Minister; and• The conservation and protection of marine areas for the purposes of maintaining ecological integrity

Records of marine mammal sightings (N = 5,324) collected by ASOs and submitted to Fisheries and Oceans Canada (DFO) between 1979-2024, across three DFO regions: the Arctic, Newfoundland and Labrador, and the Maritimes. Methods for initial data compilation are provided in the associated technical report "Marine mammal records collected by the at-sea observer (ASO) program in Arctic, Newfoundland and Labrador, and Maritimes regions: a summary of challenges and opportunities for future research." Cite this data as: Feyrer, L.J., Colbourne, N., Lawson, J.W., Moors-Murphy, H.B., Ferguson, S. Dataset update to Marine mammal records collected by the At-Sea Observer program in Arctic, Newfoundland and Labrador and Maritimes regions. Published: February 2025. Ocean Ecosystems Science Division, Fisheries and Oceans Canada, Dartmouth, N.S.

Boundaries identifying similar behavioural ecotypes and sub-populations of Grizzly bears. This dataset contains versions from multiple years. From 2018 on, NatureServe conservation concern ranking categories (e.g., Very Low, Low, Moderate, High, Extreme Concern) supersede the pre-2018 population status categories (e.g., Viable, Threatened, Extirpated) contained in the field STATUS. NatureServe conservation concern ranking categories reflect population size and trend, genetic and demographic isolation, as well as threats to bears and their habitats. The NatureServe conservation concern ranking fields are named CONSERVATION_CONCERN_RANK and CONSERVATION_CONCERN_DESC. Please view the attached PDF file for a summary of changes to this dataset from 2012 onward. To download only the 2018 units, in the link below, select the "Export" tab, then select the "Provincial Layer Download" button: https://maps.gov.bc.ca/ess/hm/imap4m/?catalogLayers=7744,7745 Grizzly Bear Conservation Ranking results table is available here: https://catalogue.data.gov.bc.ca/dataset/e08876a1-3f9c-46bf-b69a-3d88de1da725 Grizzly Bear population estimates from various years are available here: https://catalogue.data.gov.bc.ca/dataset/2bf91935-9158-4f77-9c2c-4310480e6c29 Grizzly Bear reports are available here: https://www2.gov.bc.ca/gov/content/environment/plants-animals-ecosystems/wildlife/wildlife-conservation/grizzly-bear

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.

PURPOSE:In this study, we examined the structure and function of the Southampton Island marine food web across 149 species of benthic and pelagic invertebrates, fishes, marine mammals and seabirds collected from 2016 to 2019, to provide a baseline for future studies that aim to quantify temporal changes in food web structuring. More specifically,we used a multi-biomarker approach combining stable isotopes and HBIs to: (i) determine the vertical trophic structure of the marine food web, (ii) investigate the contribution of benthic and pelagic-derived prey to the higher trophic level species of the Arctic food web, and (iii) determine the role of ice algae and phytoplankton carbon source use across different trophic levels and compartments (pelagic and benthic). By shedding new light on the functioning of the Southampton Island food web and specifically how the contribution of ice algae and benthic habitat shapes its structure, these results will be relevant to adaptive management and conservation initiatives implemented in response to anthropogenic stressors and climate change. DESCRIPTION:Climate-driven alterations of the marine environment are most rapid in Arctic and subarctic regions, including Hudson Bay in northern Canada, where declining sea ice, warming surface waters and ocean acidification are occurring at alarming rates. These changes are altering primary production patterns that will ultimately cascade up through the food web. Here, we investigated (i) the vertical trophic structure of the Southampton Island marine ecosystem in northern Hudson Bay, (ii) the contribution of benthic and pelagic-derived prey to the higher trophic level species, and (iii) the relative contribution of ice algae and phytoplankton derived carbon in sustaining this ecosystem. For this purpose, we measured bulk stable carbon, nitrogen and sulfur isotope ratios as well as highly branched isoprenoids in samples belonging to 149 taxa, including invertebrates, fishes, seabirds and marine mammals. We found that the benthic invertebrates occupied 4 trophic levels and that the overall trophic system went up to an average trophic position of 4.8. The average δ34S signature of pelagic organisms indicated that they exploit both benthic and pelagic food sources, suggesting there are many interconnections between these compartments in this coastal area. The relatively high sympagic carbon dependence of Arctic marine mammals (53.3 ± 22.2 %) through their consumption of benthic invertebrate prey, confirms the important role of the benthic subweb for sustaining higher trophic level consumers in the coastal pelagic environment. Therefore, a potential decrease in the productivity of ice algae could lead to a profound alteration of the benthic food web and a cascading effect on this Arctic ecosystem.Collaborators:Centre for Earth Observation Science, University of Manitoba, Winnipeg, Manitoba, Canada - R´emi Amiraux, C.J. Mundy, Jens K. Ehn, Z.A. Kuzyk.Quebec-Ocean, Sentinel North and Takuvik, Biology Department, Laval University, Quebec, Quebec, Canada - Marie Pierrejean.Scottish Association for Marine Science, Oban, UK - Thomas A. Brown.Department of Natural Resource Sciences, McGill University, Ste. Anne de Bellevue, Quebec, Canada - Kyle H. Elliott.Department of Biological Sciences, University of Manitoba, Winnipeg, Manitoba, Canada - Steven H. Ferguson, Cory J.D. Matthews, Cortney A. Watt, David J. Yurkowski.School of the Environment, University of Windsor, Windsor, Ontario, Canada - Aaron T. Fisk.Science and Technology Branch, Environment and Climate Change Canada, Ottawa, Ontario, Canada - Grant Gilchrist.College of Fisheries and Ocean Sciences, University of Alaska Fairbanks, Fairbanks, AK, USA - Katrin Iken.Department of Earth Sciences, University of New Brunswick, Fredericton, NB, Canada - Audrey Limoges.Department of Integrative Biology, University of Windsor, Windsor, Ontario, Canada - Oliver P. Love, Wesley R. Ogloff.Department of Arctic Biology, The University Centre in Svalbard, Longyearbyen, Norway - Janne E. Søreide.