The assessment of the status of eelgrass (Zostera marina) beds at the bay-scale in turbid, shallow estuaries is problematic. The bay-scale assessment (i.e., tens of km) of eelgrass beds usually involves remote sensing methods such as aerial photography or satellite imagery. These methods can fail if the water column is turbid, as is the case for many shallow estuaries on Canada’s eastern seaboard. A novel towfish package was developed for the bay-scale assessment of eelgrass beds irrespective of water column turbidity. The towfish consisted of an underwater video camera with scaling lasers, sidescan sonar and a transponder-based positioning system. The towfish was deployed along predetermined transects in three northern New Brunswick estuaries. Maps were created of eelgrass cover and health (epiphyte load) and ancillary bottom features such as benthic algal growth, bacterial mats (Beggiatoa) and oysters. All three estuaries had accumulations of material reminiscent of the oomycete Leptomitus, although it was not positively identified in our study. Tabusintac held the most extensive eelgrass beds of the best health. Cocagne had the lowest scores for eelgrass health, while Bouctouche was slightly better. The towfish method proved to be cost effective and useful for the bay-scale assessment of eelgrass beds to sub-meter precision in real time. Cite this data as: Vandermeulen H. Data of: Bay Scale Assessment of Eelgrass Using Sidescan and Video - Cocagne 2008. Published: November 2019. Coastal Ecosystems Science Division, Fisheries and Oceans Canada, Dartmouth, N.S. https://open.canada.ca/data/en/dataset/431c815e-65f0-477b-9389-060fa41ec955

To estimate Grey Seal (Halichoerus grypus) pup production, photographic aerial surveys were conducted of the major Grey Seal breeding colonies in Canadian waters. The last survey was completed in January 2021. A total of 72,209 pups were counted on digital imagery from Sable Island, the largest breeding colony. Reconnaissance flights found no new colonies along the Atlantic coast of Nova Scotia and New Brunswick. Pup developmental stage surveys were undertaken on the ground or from helicopter at the seven largest breeding colonies to describe the birth distribution and correct the pup count for the estimate of pups born after the aerial photographic survey. The estimated number of pups born on Sable Island was 76,600 (SE = 2,900) and for Coastal Nova Scotia was 4,700 (SE = 550). For Sable Island, this is the first estimate of pup production since the 1960s that has not been a significant increase. Sable Island accounts for 77.5% of total pup production in Canada, and the change in trend in pup production on Sable Island is reflected in the trend in total pup production. Pup production in the Gulf of St. Lawrence continues to fluctuate with little evidence of trend over the past several decades, while at the more recently-established breeding colonies in southwest Nova Scotia, pup production continues to increase. In February 2026, the time series of grey seal pup production estimates for Maritimes Region was made open source. The open data was set up with no abbreviations or codes and restricted to just Maritimes Region. Notably there are counts in the dataset provided not linked to specific breeding colonies, for the miscellaneous locations the latitude and longitude are for roughly center of the colonies or region. Cite this data as: den Heyer., C. Data of Grey Seal Pup Production in Canadian Water. Published: April 2026. Ocean Ecosystems Science Division, Maritimes Region, Fisheries and Oceans Canada, Dartmouth NS. https://open.canada.ca/data/en/dataset/ea8962b2-0d75-4500-a3de-d631a1e5308f

Moving 6-year analysis of Water body phosphate in the Arctic Ocean, for each season in the period 1965-2017. Every year of the time dimension corresponds to the 6-year centered average for each season. Winter: December-February, Spring: March-May, Summer: June-August, Autumn: September-November. Depth range (IODE standard depths): 0, 5, 10, 20, 30, 40, 50, 75, 100, 125, 150, 200, 250, 300, 400, ..., 1500, 1750, 2000, 2500m. Units: umol/l. Description of DIVA analysis: The computation was done with the DIVAnd (Data-Interpolating Variational Analysis in n dimensions), version 2.6.6, using GEBCO 30sec topography for the spatial connectivity of water masses. The horizontal resolution of the produced DIVAnd maps grids is 0.1 degrees. Signal-to-noise ratio was fixed to 2.0, horizontal correlation length to 100 km, and vertical correlation length varying between 25 and 200 m. Logarithmic transformation is applied to the data prior to the analysis. Background field: the data mean value is subtracted from the data.

The Brier Island/Digby Neck area has been identified as an Ecologically and Biologically Significant Area (EBSA) by Fisheries and Oceans Canada and is one of four marine areas within the Bay of Fundy recognised by Parks Canada as of national significance for marine conservation planning. The area is representative of important outer Bay of Fundy features with significant marine mammal, bird, and benthic diversity including potentially important aggregations of sensitive benthic species such as horse mussel and sponge. Much of the information used for this recognition is now over 40 years old and should be re-validated using standardised georeferenced survey methods. As a first phase, a diver-based survey of the sublittoral habitats and associated species was conducted in August and September of 2017 for the Brier Island area. This report summarises the major sublittoral habitat types, species assemblages, and oceanographic conditions observed at 20 locations including Northwest and Southwest Ledges, Gull Rock, Peter’s Island, and Grand Passage. A total of 962 records were made of 178 taxa, consisting of 43 algae and 135 animals. Comparison with historical records largely confirmed the continued presence of unique habitats and species assemblages for which this area was initially recognised as an EBSA. Differences in species richness observed for cryptic and less known taxonomic groups such as sponges and bryozoans were attributable to changes in survey methods and knowledge. Based on these findings, additional surveys of inshore and offshore Brier Island using more quantitative methods developed for other Bay of Fundy EBSAs would further support regional MPA network planning and provide relative scales of species diversity and habitat coverage for this area.

The Atlantic dataset is part of Environment and Climate Change Canada’s Shoreline Classification and Pre-Spill database. Shoreline classification data has been developed for use by the Environmental Emergencies Program of Environment and Climate Change Canada for environmental protection purposes. Marine and estuarine shorelines are classified according to the character (substrate and form) of the upper intertidal (foreshore) or upper swash zone (Sergy, 2008). This is the area where oil from a spill usually becomes stranded and where treatment or cleanup activities take place. The basic parameter that defines the shoreline type is the material that is present in the intertidal zone. The presence or absence of sediments is a key factor in determining whether oil is stranded on the surface of a substrate or can penetrate and/or be buried. This dataset contains thousands of linear shoreline segments ranging in length from 200 m and 2 km long. The entities represent the location of the segments and their geomorphological description. There exist further fields in the attribute table for this dataset. We are currently working on standardizing our shoreline segmentation datasets and the updated data will soon be uploaded to the catalog. Sergy, G. (2008). The Shoreline Classification Scheme for SCAT and Oil Spill Response in Canada. Proceedings of the 31stArctic and Marine Oil Spill Program Technical Seminar.Environment Canada, Ottawa, ON, Pp. 811-819.

This layer details Important Areas (IAs) relevant to key cetacean species in the Pacific North Coast Integrated Management Area (PNCIMA). This data was mapped to inform the selection of marine Ecologically and Biologically Significant Areas (EBSA). Experts have indicated that these areas are relevant based upon their high ranking in one or more of three criteria (Uniqueness, Aggregation and Fitness Consequences). The distribution of IAs within ecoregions is used in the designation of EBSAs. Canada’s Oceans Act provides the legislative framework for an integrated ecosystem approach to management in Canadian oceans, particularly in areas considered ecologically or biologically significant. DFO has developed general guidance for the identification of ecologically or biologically significant areas. The criteria for defining such areas include uniqueness, aggregation, fitness consequences, resilience, and naturalness. This science advisory process identifies proposed EBSAs in Canadian Pacific marine waters, specifically in the Strait of Georgia (SOG), along the west coast of Vancouver Island (WCVI, southern shelf ecoregion), and in the Pacific North Coast Integrated Management Area (PNCIMA, northern shelf ecoregion). Initial assessment of IAs in PNCIMA was carried out in September 2004 to March 2005 with spatial data collection coordinated by Cathryn Clarke. Subsequent efforts in WCVI and SOG were conducted in 2009, and may have used different scientific advisors, temporal extents, data, and assessment methods. WCVI and SOG IA assessment in some cases revisits data collected for PNCIMA, but should be treated as a separate effort. Other datasets in this series detail IAs for birds, coral and sponges, fish, geographic features, invertebrates, and other vertebrates. Though data collection is considered complete, the emergence of significant new data may merit revisiting of IAs on a case by case basis.

The Global Deterministic Wave Prediction System (GDWPS) produces wave forecasts out to 120 hours in the future using the third generation spectral wave forecast model WaveWatch III® (WW3). The model is forced by the 10 meters winds and the ice concentration from the Global Deterministic Prediction System (GDPS). The ice concentration is used by the model to attenuate wave growth in areas covered by 25% to 75% ice and to suppress it for concentration above 75%. Forecast elements include significant wave height, peak period and primary swell height, direction and period.

The assessment of the status of eelgrass (Zostera marina) beds at the bay-scale in turbid, shallow estuaries is problematic. The bay-scale assessment (i.e., tens of km) of eelgrass beds usually involves remote sensing methods such as aerial photography or satellite imagery. These methods can fail if the water column is turbid, as is the case for many shallow estuaries on Canada’s eastern seaboard. A novel towfish package was developed for the bay-scale assessment of eelgrass beds irrespective of water column turbidity. The towfish consisted of an underwater video camera with scaling lasers, sidescan sonar and a transponder-based positioning system. The towfish was deployed along predetermined transects in three northern New Brunswick estuaries. Maps were created of eelgrass cover and health (epiphyte load) and ancillary bottom features such as benthic algal growth, bacterial mats (Beggiatoa) and oysters. All three estuaries had accumulations of material reminiscent of the oomycete Leptomitus, although it was not positively identified in our study. Tabusintac held the most extensive eelgrass beds of the best health. Cocagne had the lowest scores for eelgrass health, while Bouctouche was slightly better. The towfish method proved to be cost effective and useful for the bay-scale assessment of eelgrass beds to sub-meter precision in real time. Cite this data as: Vandermeulen H. Data of: Bay Scale Assessment of Eelgrass Beds Using Sidescan and Video -Tabusintac 2008. Published: March 2021. Coastal Ecosystems Science Division, Fisheries and Oceans Canada, Dartmouth, N.S. https://open.canada.ca/data/en/dataset/d1c58bc6-69d4-47b2-bb19-988f88233900

Ocean physical conditions in the Maritimes Region in 2019 were characterized by cooler surface temperatures, continued warmer bottom temperatures and weaker stratification compared to recent years. Deep nutrient inventories were lower than normal over most of the region, with the exception of the Cabot Strait section where deep nutrients were near or higher than normal during the spring sampling and associated with record-warm water. Anomalies of surface nutrients were negative across the region, with the exception of positive anomalies observed at the deep shelf and offshore stations of the Louisbourg section. The spring phytoplankton bloom was near or slightly earlier than normal across the Scotian Shelf (SS) with near-normal duration. Peak chlorophyll a concentrations during the spring bloom occurred within a narrow time window across the SS. At Halifax-2 (HL2), the spring bloom was characterized by a high amplitude, and a rapid progression and decline. Plankton community changes persisted in 2019 with lower abundance of large phytoplankton (diatoms), mainly lower-than-normal biomass of zooplankton and abundance of Calanus finmarchicus, and higher-than-normal abundance of non-copepods. Arctic Calanus and warm-shelf copepods showed mixed abundance anomalies in 2019, reversing the pattern of 2018. Above-normal abundances of Oithona atlantica, especially at HL2, suggest a greater influence of offshore waters in recent years. Surface temperature in the Bedford Basin was near normal in 2019 with mainly cooler-than-normal temperatures from January to June and near- or slightly-above-normal temperatures from July to December. Bottom temperature and salinity were below normal in 2019 with near- or slightly-above-normal conditions at the start of the year and progressing toward cooler and fresher water from February to December. Surface and deep nitrate, phosphate and silicate were near or below normal, with surface phosphate reaching a record low in 2019. The 2018 Continuous Plankton Recorder data indicated an annual abundance of diatoms close to normal for the Eastern (ESS) and Western Scotian Shelf (WSS), while the abundance of dinoflagellates and the Phytoplankton Colour Index values were near (WSS) or above (ESS) normal. The annual abundance of Calanus CI-IV was near normal (ESS) or slightly below normal (WSS), while C. finmarchicus CV-VI levels were slightly below (ESS) or below (WSS) normal. The abundance of Calanus glacialis (ESS, WSS) and Para/Pseudocalanus and Limacina spp. (WSS) were lower than normal, while that of coccolithphore (ESS, WSS), and copepod nauplii and foraminifera (ESS) was higher than normal. "

The assessment of the status of eelgrass (Zostera marina) beds at the bay-scale in turbid, shallow estuaries is problematic. The bay-scale assessment (i.e., tens of km) of eelgrass beds usually involves remote sensing methods such as aerial photography or satellite imagery. These methods can fail if the water column is turbid, as is the case for many shallow estuaries on Canada’s eastern seaboard. A novel towfish package was developed for the bay-scale assessment of eelgrass beds irrespective of water column turbidity. The towfish consisted of an underwater video camera with scaling lasers, sidescan sonar and a transponder-based positioning system. The towfish was deployed along predetermined transects in three northern New Brunswick estuaries. Maps were created of eelgrass cover and health (epiphyte load) and ancillary bottom features such as benthic algal growth, bacterial mats (Beggiatoa) and oysters. All three estuaries had accumulations of material reminiscent of the oomycete Leptomitus, although it was not positively identified in our study. Tabusintac held the most extensive eelgrass beds of the best health. Cocagne had the lowest scores for eelgrass health, while Bouctouche was slightly better. The towfish method proved to be cost effective and useful for the bay-scale assessment of eelgrass beds to sub-meter precision in real time. Cite this data as: Vandermeulen H. Data of: Bay Scale Assessment of Eelgrass Beds Using Sidescan and Video - Bouctouche. Published: November 2017. Coastal Ecosystems Science Division, Fisheries and Oceans Canada, Dartmouth, N.S. https://open.canada.ca/data/en/dataset/b4c83cd2-20f2-47d8-8614-08c1c44c9d8c