A towfish containing sidescan and video hardware was used to map eelgrass in two shallow northern New Brunswick estuaries. The sidescan and video data were useful in documenting suspected impacts of oyster aquaculture gear and eutrophication on eelgrass. With one boat and a crew of three, the mapping was accomplished at a rate of almost 10 km2 per day. That rate far exceeds what could be accomplished by a SCUBA based survey with the same crew. Moreover, the towfish survey applied with a complementary echosounder survey is potentially a more cost effective mapping method than satellite based remote sensing. Cite this data as: Vandermeulen H. Data of: Bay Scale Assessment of Eelgrass Beds Using Sidescan and Video - Richibucto 2007. Published: October 2017. Coastal Ecosystems Science Division, Fisheries and Oceans Canada, Dartmouth, N.S. https://open.canada.ca/data/en/dataset/ca7af8ba-8810-4de5-aa91-473613b0b38d

The National Ecological Framework for Canada's "Surficial Geology by Ecoprovince” dataset contains tables that provide surficial geology information with the ecoprovince framework polygons. It provides codes that characterize surficial geology (unconsolidated geologic materials) and their English and French-language descriptions as well as information about the area and percentage of the polygon that the material occupies.

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.

Funded under DFO's Marine Conservation Targets Program in partnership with the Huntsman Marine Science Centre (HMSC), this diver-based imagery and sample collection benthic survey documents the occurrence of sponges at 42 dive sites in the Eastern Shore Islands (ESI) Area of Interest (AOI, ~2089 km2) off the Atlantic coast of Nova Scotia, Canada from dive surveys conducted in summer 2021 and 2022. Water quality, species occurrences and counts, habitat, slope, and substrate characteristics were catalogued through diver log sheets, camera imagery, specimen vouchers, and high-resolution bathymetric data. A total of 54 dives to depths from 11 to 33 m (below sea level), collecting up to 147 still images, one-hour of video, and 17 specimen samples per site, resulted in 220 observations for 27 different sponge taxa. This included three new records for Canada (Hymedesmia stellifera, Plocamionida arndti, Hymedesmia jecusculum) and a range extension for a species new to science (Crellomima mehqisinpekonuta) which was recently described from the Bay of Fundy. There were also four species which may seem to be new to science (Halichondria sp., Hymedesmia sp., Protosuberires sp., and Sphaerotylus sp.). Sponges were found to occupy a diversity of micro-habitats, often several different ones in proximity. A total of eight distinct habitat classes were defined, based on varying abundances and diversity of sponges and associated benthic species. These are likely widely distributed among the many complex submerged seabed features within this AOI. Collected specimens were preserved and are stored at the Atlantic Reference Centre (ARC) in St. Andrew's, New Brunswick. Cite this data as: Goodwin, C., Cooper, J.A., Lawton, P., Teed, L.L. 2025. Sponge occurrence and associated species and habitat descriptions derived from the 2021 and 2022 SCUBA diving surveys in the Eastern Shore Islands Area of Interest, Nova Scotia. Version 1.4. Fisheries and Oceans Canada. Occurrence dataset. https://ipt.iobis.org/obiscanada/resource?r=eastern_shore_islands_sponge_survey_2021_2022&v=1.4

The National Ecological Framework for Canada's "Soil Development by Ecodistrict” dataset contains tables that provide soil development information for components within the ecodistrict framework polygon. It provides soil development codes and their English and French-language descriptions as well as the percentage of the polygon that the component occupies. The soil development descriptions are based on the second edition of the Canadian System of Soil Classification (Agriculture Canada Expert Committee on Soil Survey, 1987).

PURPOSE: Establishing efficient, non-destructive sampling methods for clam population assessments. DESCRIPTION: In the Gulf of St. Lawrence (GSL) Management Region, clam assessments are uncommon due to limited resources and the labour-intensive nature of sampling clam beds. Furthermore, clam assessments typically rely on destructive sampling that disturbs sediment and removes animals from their habitat. Establishing efficient, non-destructive sampling methods for clam population assessments can reduce the impact of scientific sampling on these habitats and provide for more efficient monitoring. In this study, we tested the idea that visually observing siphon holes on the sediment surface could predict the presence, number, and size of soft-shell clams across different sites in the southern GSL. Siphon holes reasonably predicted the presence, number, and size/biomass of soft-shell clams in most, but not all, sites. Thus, in many habitats in the GSL, siphon holes can be used for population assessments, providing a powerful tool to enhance Science advice to fisheries managers. Data was collected at the following sites: * Maisonnette, Parc Maisonnette, Maisonnette, New Brunswick, Canada * Kouchibouguac, Loggiecroft wharf, Kouchibouguac National Park, New Brunswick, Canada * Shemogue, Amos Point Road, Little Shemogue, New Brunswick, Canada * Powell's Cove, Powell's Point Provincial Park, Little Harbour, Nova Scotia, Canada PARAMETERS COLLECTED: - Clam abundance - Clam biomass (total sample) - Clam size (length, weight) - Siphon hole abundance - Siphon hole size - Siphon hole characterization (i.e., identification of actual clam based on shape) - Seawater temperature - Sediment grain size - Sediment organic content (%) - Sediment relative moisture content (%) NOTES ON QUALITY CONTROL: Original data entry by Jillian Hunt and/or Isabelle Brennan. Data checked and validated prior to analysis by Jeff Clements. Data further checked and validated prior to publication by Amélie Robichaud. PHYSICAL SAMPLE DETAILS: No physical samples retained. - Clam samples returned back to original habitat after measuring and weighing in the field. - Sediment core samples stored in walk-in freezer and discarded after processing and analysis. SAMPLING METHODS: i. Identifying, counting, weighing, and measuring (with calipers) clams ii. Identifying, counting, and measuring (with calipers) clam siphon holes iii. Seawater temperature monitoring via data loggers iv. Sediment grain size, organic content, and moisture content analysis USE LIMITATION: To ensure scientific integrity and appropriate use of the data, we would encourage you to contact the data custodian.

The National Ecological Framework for Canada's "Land Cover by Ecodistrict” dataset provides land cover information within the ecodistrict framework polygon. It provides landcover codes and their English and French language description as well as information about the percentage of the polygon that the component occupies.

The National Ecological Framework for Canada's "Surficial Geology by Ecoregion” dataset contains tables that provide surficial geology information with the ecoregion framework polygons. It provides codes that characterize surficial geology (unconsolidated geologic materials) and their English and French-language descriptions as well as information about the area and percentage of the polygon that the material occupies.

The greenland shark (Somniosus microcephalus), is a species found in Atlantic Canadian waters which is occasionally encountered in commercial fisheries. Pop-up Satellite Archival Tags (PSAT) from Wildlife Computers were applied to greenland sharks from 2006 to 2009 to collect data on depth (pressure), temperature and ambient light level (for position estimation). Deployments were conducted in Canada on commercial vessels throughout the year and in Cumberland Sound (Pangirtung) on a scientific expedition in April 2008. A variety of tag models were deployed: PAT 4 (n=1) and Mk10 (N=15) and 14 of 16 tags reported. Greenland sharks tagged ranged in size from 250 cm to 549 cm Total Length (curved); 3 were female, 9 were male, and 4 were of unknown sex. Time at liberty ranged from 48 – 350 days and 9 tags remained on the sharks for the programmed duration. Raw data transmitted from the PSAT’s after release was processed through Wildlife Computers software (GPE3) to get summary files, assuming a maximum swimming speed of 2m/s, NOAA OI SST V2 High Resolution data set for SST reference and ETOPO1-Bedrock dataset for bathymetry reference. The maximum likelihood position estimates are available in .csv and .kmz format and depth and temperature profiles are also in .csv format. Other tag outputs as well as metadata from the deployments can be obtained upon request from: warren.joyce@dfo-mpo.gc.ca or heather.bowlby@dfo-mpo.gc.ca.

Buffer zone of 300 meters around the railways present on the territory of the city. Used in public safety analyses. **Collection context** Derived from the layer of railways in the territory of the city of Saint-Hyacinthe. **Collection method** Buffer zone of 300 meters. Spatial analysis. **Attributes** * `Id` (`long`): Identifier For more information, consult the metadata on the Isogeo catalog (OpenCatalog link).**This third party metadata element was translated using an automated translation tool (Amazon Translate).**