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.

Catch, effort, location (latitude, longitude), relative abundance indices, and associated biological data from groundfish multi-species bottom trawl surveys in West Coast Haida Gwaii.Introduction The West Coast Haida Gwaii (WCHG) synoptic bottom trawl survey was first conducted annually from 2006 to 2008 and has since been repeated every second year on even numbered years. The survey was not impacted by the COVID-19 pandemic. This survey is one of a set of long-term and coordinated surveys that together cover the continental shelf and upper slope of most of the British Columbia coast. The other surveys are the Queen Charlotte Sound (QCS) survey, the Hecate Strait (HS) survey, the West Coast Vancouver Island (WCVI) survey, and the Strait of Georgia (SOG) survey. The objectives of these surveys are to provide fishery independent abundance indices of all demersal fish species available to bottom trawling and to collect biological samples of selected species. The survey follows a random depth-stratified design and the sampling units are 2 km by 2 km blocks. The synoptic bottom trawl surveys are conducted by Fisheries and Oceans Canada (DFO) in collaboration with the Canadian Groundfish Research and Conservation Society (CGRCS), a non-profit society composed of participants in the British Columbia commercial groundfish trawl fishery. The Queen Charlotte Sound and West Coast Haida Gwaii surveys are conducted under collaborative agreements, with the CGRCS providing chartered commercial fishing vessels and field technicians, while DFO provides in-kind contributions for running the surveys including personnel and equipment. The Hecate Strait, West Coast Vancouver Island, and Strait of Georgia surveys are conducted by DFO and have typically taken place on a Canadian Coast Guard research vessel. Until 2016 this vessel was the CCGS W.E. Ricker. From 2021 onwards, this vessel was the CCGS Sir John Franklin. In years when a coast guard vessel has not been available, the Hecate Strait, West Coast Vancouver Island, and Strait of Georgia surveys have taken place on chartered industry vessels. Data from these surveys are also presented in the groundfish data synopsis report (Anderson et al. 2019).EffortThis table contains information about the survey trips and fishing events (trawl tows/sets) that are part of this survey series. Trip-level information includes the year the survey took place, a unique trip identifier, the vessel that conducted the survey, and the trip start and end dates (the dates the vessel was away from the dock conducting the survey). Set-level information includes the date, time, location, and depth that fishing took place, as well as information that can be used to calculate fishing effort (duration) and swept area. All successful fishing events are included, regardless of what was caught.CatchThis table contains the catch information from successful fishing events. Catches are identified to species or to the lowest taxonomic level possible. Most catches are weighed, but some are too small (“trace” amounts) or too large (e.g. very large Big Skate). The unique trip identifier and set number are included so that catches can be related to the fishing event information (including capture location).BiologyThis table contains the available biological data for catches which were sampled. Data may include any or all of length, sex, weight, age. Different length types are measured depending on the species. Age structures are collected when possible for species where validated aging methods exist and are archived until required for an assessment; therefore, all existing structures have not been aged at this time. The unique trip identifier and set number are included so that samples can be related to the fishing event and catch information.BiomassThis table contains relative biomass indices of species that have been captured in every survey of the time series. The coefficient of variation and bootstrapped 95% confidence intervals are provided for each index. The groundfish data synopsis report (Anderson et al. 2019) provides an explanation of how the relative biomass indices are derived. Note that we do not calculate a biomass index for the 2014 West Coast Haida Gwaii survey, as this survey was incomplete due to operational problems.

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.

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.

Considered the "king" of sea lions, the Steller sea lion (Eumetopias jubatus) is the biggest 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. This hefty mammal usually travels alone or in a small group, but wisely, it joins others for protection during the mating and birthing season. Little is known about its oceanic lifestyle; however, the good news for this sea-loving mammal is that since the Steller sea lion first became protected in 1970, the size of the adult population has more than doubled. Recent trends in the abundance of Steller sea lions (Eumetopias jubatus) in British Columbia were assessed based on a series of thirteen province-wide aerial surveys conducted during the breeding season (27-June to 06-July) between 1971 and 2013.

The Olympia oyster (Ostrea lurida Carpenter, 1864) is one of four species of oysters established in British Columbia (BC), Canada, and the only naturally occurring oyster in BC (Bourne 1997; Gillespie 1999, 2009). O. lurida reaches the northern limit of its range in the Central Coast of British Columbia at Gale Passage, Campbell Island, approximately 52°12’N, 128°24’W (Gillespie 2009).First Nations historically utilized Olympia oysters for food and their shells for ornamentation (Ellis and Swan 1981; Harbo 1997). European settlers harvested Olympia oysters commercially from the early 1800s until the early 1930s when stocks became depleted and the industry moved towards other larger, introduced oyster species (Bourne 1997; Quayle 1988). Since that time, Olympia oysters have likely maintained stable populations in BC, but have not recovered to abundance levels observed prior to the late 1800s (Gillespie 1999, 2009).Olympia oysters were designated a species of Special Concern by the Committee on the Status of Endangered Wildlife in Canada (COSEWIC) in 2000 and 2010 and listed under the Species at Risk Act (SARA) in 2003 (DFO 2009; COSEWIC 2011). A management plan was developed and posted to the SARA Public Registry in 2009 (DFO 2009). One of the objectives of this plan was to ensure maintenance of the relative abundance (density) of Olympia oyster at index sites. The plan also recommended development of a survey protocol for determining relative abundance (density) estimates. In response, a Canadian Science Advisory Secretariat (CSAS) Research Document was completed recommending a survey method for Olympia oysters (Norgard et al. 2010); a CSAS Science Advisory Report (DFO 2010) for selection of index sites was also completed.Thirteen index sites were chosen from a mixture of previously surveyed sites, and by random site selection. In 2014, a fourteenth site was added at Joes Bay in the Broken Group area in partnership with Parks Canada. The selected sites provided a representative sample of Olympia oyster populations in different geographic zones in the Pacific region and span the much of the range of Olympia oysters in BC. The number of sites was reduced to six in 2018 so that annual surveys could be completed to better understand population dynamics and identify long-term trends.

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 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).

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

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.