This layer represents the seasonal distribution of St. Lawrence Estuary beluga whale population (Delphinapterus leucas). Summer distribution is based on many surveys conducted between the end of August and early September. Fall and winter distributions are based on aerial surveys conducted during mid-October, November and from December to March 1989-1990. Spring distribution is based on anecdotal reports and two aerial surveys conducted in late April and early June 1990.Beluga whale seasonal distribution can change according to sea ice cover, predation risk and food availability. This layer represents the general seasonal distribution and does not account for the sexual segregation among males and females in the St. Lawrence Estuary.This layer do not represent the beluga's critical habitat. See the data layer “Beluga whale critical habitat in the Saguenay River and the St. Lawrence Estuary” (https://open.canada.ca/data/en/dataset/fdfef550-b94c-466c-9dcb-24c297c00e3e). Data source : Mosnier, A., Lesage, V., Gosselin, J.-F., Lemieux Lefebvre, S., Hammill, M. O., Doniol-Valcroze, T. 2010. Information relevant to the documentation of habitat use by St. Lawrence beluga (Delphinapterus leucas), and quantification of habitat quality. DFO Can. Sci. Advis. Sec., Res. Doc. 2009/098. iv + 35 p.

The United States population of California Sea Lions (Zalophus californianus) range from southeast Alaska to the Pacific coast of central Mexico. While this population does not breed in Canada, some sub-adult and adult males migrate northwards to British Columbia (BC) during the non-breeding season with an arrival in August–October and a departure in April–May. The population in coastal BC was assessed in 1985 and again in 2023 from dedicated over-winter aerial surveys. The most recent assessment used counts from 2020–2021surveys that were restricted to southern BC as few animals have been documented further north. Additional observations of California Sea Lions were collected while surveying sites for Steller Sea Lions. These opportunistic counts increased from approximately 1,000 animals in the mid-2000s to several thousand individuals in more recent years. Historically occupied sea lion rookeries and haul-out sites were surveyed with nearby areas monitored for potential shifts in distribution. This dataset contains counts that have been collected from sightings of individuals from 1971 through 2021and replaces a previous dataset limited to the 2016/2017 survey season.

Aerial overview surveys are carried out by observers in fixed-wing aircraft flying at appropriate safe heights above ground level over the forest canopy. Surveys cover extensive areas to detect as many new FHDA-caused disturbances as possible. Surveyors record locations, extent, severity, possible causative agent and host tree species involved in the disturbances. Aerial surveys are cost-effective means of obtaining forest health damaging agent (FHDA) caused disturbance data at the landscape level. These surveys help to manage forests by providing early detection of FHDAs and once detected, by monitoring their trends. Aerial surveys are carried out to record locations, extent and severity of new, FHDA-caused disturbances. changes to known FHDA disturbances for historical and evaluation purposes. background information needed for planning management actions. and, forest health data at the forest area, regional and provincial levels for reporting and inventory update. This dataset contains data from 1975 to 2010. Data from 2011 onward is available as a separate dataset.

The Atlantic Colonial Waterbird Monitoring database captures geo-referenced data collected under the Atlantic Region’s Canadian Wildlife Service (CWS) Colonial Seabird Monitoring program, and data collected under CWS’ waterfowl and protected areas programs. These programs collectively monitor 22 species of colonial waterbirds breeding in the Atlantic Region of the following groups: fulmars, shearwaters, storm-petrels, gannets, gulls, terns, alcids, eiders, herons and cormorants, with the primary outcome to update information on the distribution, status, and trends of waterbirds breeding in all four Atlantic provinces. Surveys are conducted using one of three platforms: aerial, boat, or ground. Aerial surveys provide the most cost-effective way of conducting a comprehensive population census of diurnal species visible from air, namely gulls (Herring, Great Black-backed, Ring-billed, Glaucous), Black-legged Kittiwakes, Northern Gannets, terns (Arctic, Common, Roseate, Caspian), cormorants (Greater, Double-crested), Black Guillemots, and Common Eiders.Aerial surveys are also effective in identifying new colonies and provide additional information on how to most effectively conduct boat and ground surveys. Boat and ground surveys are conducted at smaller geographic scales and are necessary to obtain complementary information on the species composition of colonies and correction factors to finalize gull, tern and eider estimates obtained from the aerial surveys. Ground and/or boat surveys are also necessary to conduct colony counts of cliff-nesting birds (murres and fulmars), crevice nesting birds (razorbills and guillemots) and burrow-nesting birds (puffins, storm-petrels, shearwaters). Raw data are captured using various survey methods, including:1) visual estimates, 2) direct counts of number of individuals or apparently occupied sites and/or photo counts, 3) sub-sampling the colony through plot counts and extrapolating the estimated occupied densities over the occupied area which in turn is estimated using a variety of geographic information system approaches (e.g., Wilhelm et al. 2015). Important outcomes for how data are used include informing marine spatial planning, emergency preparedness, impact assessment of various anthropogenic threats, and COSEWIC status assessment (e.g., COSEWIC 2020). Further, these data are regularly used internally or in collaboration with partners to form the basis of peer-reviewed publications on regional, national, and/or global population trends for target species (e.g., Langlois Lopez et al. 2022, Iles et al. 2025).This dataset represents a subset of data collected from surveys led by CWS spanning from 1910 to 2024 and summarized to present, at a given colony, the year and count of birds from the most recent survey, the year and maximum count of birds within the last 20 years (if available), and the year and maximum count of birds ever recorded. In addition, CWS works closely with a variety of partners (e.g., provincial, other federal departments, academic, not-for profit organizations) to supplement colonial waterbird data collected in the Atlantic Region. To request additional census or survey data, please contact CWS.COSEWIC. 2020. COSEWIC assessment and status report on the Leach’s Storm-Petrel (Atlantic population) Oceanodroma leucorhoa in Canada. Committee on the Status of Endangered Wildlife in Canada. Ottawa. xii + 70 pp. (https://www.canada.ca/en/environment-climate-change/services/species-risk-public-registry.html). Iles, D.T., S.E. Gutowsky, A.M. Calvert, S.I. Wilhelm, J.-F. Rail, A. Hedd, H.L. Major, A.C. Smith, and G.J. Robertson. 2025. Estimating regional trajectories and trends of seabirds from sparse and inconsistent colony counts: case studies from eastern Canada with Leach’s Storm-Petrel and Atlantic Puffin. Avian Conservation and Ecology 20(2):16. https://doi.org/10.5751/ACE-02931-200216Langlois Lopez, S., Bond, A.L., O’Hanlon, N.J., Wilson, J.M., Vitz, A., Mostello, C.S., Hamilton, F., Rail, J.-F., Welch, L., Boettcher, R., Wilhelm, S.I., Anker-Nilssen, T., Daunt, F., and Masden, E. 2022. Global population and conservation status of the Great Black-backed Gull Larus marinus. Bird Conservation International, 1–11. https://doi.org/10.1017/S0959270922000181Wilhelm, S.I., Mailhiot, J., Arany, J., Chardine, J.W., Robertson, G.J., and Ryan, P.C. 2015. Update and trends of three important seabird populations in the western North Atlantic using a geographic information system approach. Marine Ornithology 43: 211-222.

The Great Lakes Migrant Waterfowl Surveys provide periodic data on waterfowl abundance, spatial and temporal distributions, and use along the shorelines of major water bodies and river systems in Ontario during mostly during spring and fall, and to a lesser extent during summer and winter, seasons. The primary survey area covers the shoreline and nearshore (~1km) waters of the Lower Great Lakes region of Ontario, specifically including the St. Lawrence River, Lake Ontario, Niagara River, Lake Erie, Detroit River and Lake St. Clair and associated major marshes and embayments. Aerial surveys, typically flown several times within spring (March –May: 1969, 1971, 1972, 1975 –1979, 1981, 1982, 1984 –1988, 1991 –1996, 1998 –2003 & 2009 –2011) and fall (September –December: 1968, 1970, 1971, 1974 –2003 & 2009 –2011) survey periods, have been conducted periodically on a relatively regular basis (approx. 5-10 years) along the Lower Great Lakes shorelines between 1968 and 2011. Smaller-scale surveys also have been conducted periodically during summer (June –August: 1968 –1970, 1972, 1974, 1975, 1977, 1982, 1984, 1986, 1989, 1999 & 2002) in this region. This survey often has been conducted in conjunction with the Midwinter Survey, so its data (up to 2004) also are included in the CWS Migrant Waterfowl Surveys database (Year ≥2004 & Month = January & February).Data from several aerial surveys conducted periodically during the non-breeding period outside the Lower Great Lakes region also are included in this database. Spring and fall surveys have been conducted along the shorelines and nearshore waters of the Upper Great Lakes region of Ontario, specifically at St. Clair River (Fall 2012 & 2013), Lake Huron (Fall 1973, 1996; Spring 1974) / Georgian Bay (Fall 1973, 1996, 2012 & 2013) & Lake Superior (Fall 2000). Aerial surveys also have been conducted inland in southeastern Ontario along the Rideau River (Fall 1998 & Spring 1999).

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.

Description:Data on recreational boating are needed for marine spatial planning initiatives in British Columbia (BC). Vessel traffic data are typically obtained by analyzing automatic identification system (AIS) vessel tracking data, but recreational vessels are often omitted or underrepresented in AIS data because they are not required to carry AIS tracking devices. Transport Canada’s National Aerial Surveillance Program (NASP) conducted aerial surveys to collect information on recreational vessels along several sections of the BC coast between 2018 and 2022. Recreational vessel sightings were modeled against predictor variables (e.g., distance to shore, water depth, distance to, and density of marinas) to predict the number of recreational vessels along coastal waters of BC.The files included here are:--A Geodatabase (‘Recreational_Boating_Data_Model’), which includes: (1) recreational vessel sightings data collected by NASP in BC and used in the recreational vessel traffic model (‘Recreational_Vessels_PointData_BC’); (2) aerial survey effort (or number of aerial surveys) raster dataset (‘surveyeffort’); and (3) a vector grid dataset (2.5 km resolution) containing the predicted number of recreational vessels per cell and predictor variables (‘Recreational_Boating_Model_Results_BC).--Scripts folder which includes R Markdown file with R code to run the modelling analysis (‘Recreational_Boating_Model_R_Script’) and data used to run the code.Methods:Data on recreational vessels were collected by NASP during planned aerial surveys along pre-determined routes along the BC coast from 2018 to 2022. Data on non-AIS recreational vessels were collected using video cameras onboard the aircraft, and data on AIS recreational vessels using an AIS receiver also onboard the aircraft. Recreational boating predictors explored were: water depth, distance to shore, distance to marinas, density of marinas, latitude, and longitude. Recreational vessel traffic models were fitted using Generalized Linear Models (GLM) R packages and libraries used here include: AED (Roman Lustrik, 2021) and MASS (Venables, W. N., Ripley, 2002), pscl package (Zeileis, Kleiber, and Jackman, 2008) for zeroinfl() and hurdle() function. Final model was selected based on the Akaike’s information criterion (AIC) and the Bayes’ information criterion (BIC). An R Markdown file with code use to run this analysis is included in the data package in a folder called Script. Spatial Predictive Model: The selected model, ZINB, consist of two parts: one with a binomial process that predicts the probability of encountering a recreational vessel, and a second part that predicts the number of recreational vessels via a count model. The closer to shore and to marinas, and the higher the density of marinas, the higher the predicted number of recreational vessels. The probability of encountering recreational vessels is driven by water depth and distance to shore. For more information on methodology, consult metadata pdf available with the Open Data record.References:Serra-Sogas, N. et al. 2021. Using aerial surveys to fill gaps in AIS vessel traffic data to inform threat assessments, vessel management and planning. Marine Policy 133: 104765. https://doi.org/10.1016/j.marpol.2021.104765Data Sources:Recreational vessel sightings and survey effort: Data collected by NASP and analyzed by Norma Serra to extract vessel information and survey effort (more information on how this data was analyzed see SerraSogas et al, 2021). Bathymetry data for the whole BC coast and only waters within the Canadian EEZ was provided by DFO – Science (Selina Agbayani). The data layer was presented as a raster file of 100 meters resolution. Coastline dataset used to estimate distance to shore and to clip grid was provided by DFO – Science (Selina Agbayani), created by David Williams and Yuriko Hashimoto (DFO – Oceans). Marinas dataset was provided by DFO – Science (Selina Agbayani), created by Josie Iacarella (DFO – Science). This dataset includes large and medium size marinas and fishing lodges. The data can be downloaded from here: Floating Structures in the Pacific Northwest - Open Government Portal (https://open.canada.ca/data/en/dataset/049770ef-6cb3-44ee-afc8-5d77d6200a12)Uncertainties:Model results are based on recreational vessels sighted by NASP and their related predictor variables and not always might reflect real-world vessel distributions. Any biases caused by the opportunistic nature of the NASP surveys were minimized by using survey effort as an offset variable.

This dataset provides the point locations of horse bands as they were observed during annual aerial surveys. Equine Management Zones are surveyed using a helicopter and horses observed on the landscape during minimum count surveys are reported. Data is stored in file geodatabase, feature class format with associated attributes, meaning each point has a number of horses observed and age class. This dataset simply reports the horses counted on the landscape at one snapshot in time. This data also depicts the flight track flown during the annual aerial minimum counts. Surveys are flown by helicopter once per year when suitable conditions permit. Areas are typically flown by grid pattern within high density areas and over known horse locations. In low density areas, preferred habitats are flown. For additional methodology information and results from prior years please visit https://www.alberta.ca/feral-horse-management.aspx

Survey data depicting the presence of the endangered Rocky Mountain Ridged Mussel (Gonidea angulata) from 2008-2011. Surveys were conducted by different researchers at different locations.

Aerial overview surveys are carried out by observers in fixed-wing aircraft flying at appropriate safe heights above ground level over the forest canopy. Surveys cover extensive areas to detect as many new FHDA-caused disturbances as possible. Surveyors record locations, extent, severity, possible causative agent and host tree species involved in the disturbances. Aerial surveys are cost-effective means of obtaining forest health damaging agent (FHDA) caused disturbance data at the landscape level. These surveys help to manage forests by providing early detection of FHDAs and once detected, by monitoring their trends. Aerial surveys are carried out to record locations, extent and severity of new, FHDA-caused disturbances. changes to known FHDA disturbances for historical and evaluation purposes. background information needed for planning management actions. and, forest health data at the forest area, regional and provincial levels for reporting and inventory update. This dataset contains data from 2011 to the most current data received. Data from 2010 and earlier is available as a separate dataset.