In 2018, Fisheries and Oceans Canada initiated the Multidisciplinary Arctic Program (MAP) – Last Ice, the first ecosystem study of the poorly characterized region of the Lincoln Sea in the Marine Protected Area of Tuvaijuittuq, where multiyear ice still resides in the Arctic Ocean. MAP-Last Ice takes a coordinated approach to integrate the physical, biochemical, and ecological components of the sea ice-ocean connected ecosystem and its response to climate and ocean forcings. The cross-disciplinary program establishes baseline ecological knowledge for Tuvaijuittuq and, in particular, for its unique multiyear ice ecosystem. The database provides baseline data on the abundance of bacteria and viruses in multi- and first-year ice and in surface waters of the Lincoln Sea in Tuvaijuittuq, and their relation to bio-physical conditions. The data were collected during the 2018 spring field campaign of the MAP-Last Ice Program, at an ice camp offshore of Canadian Forces Station (CFS) Alert.

The Regional Ice Ocean Prediction System (RIOPS) provides ice and ocean forecasts up to 84 hours, four times per day on a 1/12° resolution grid (3-8 km). RIOPS is initialized using analyses from the Global Ice-Ocean Prediction System (GIOPS). Atmospheric fluxes up to 84 hours forecasts are calculated using fields from a component of the Global Deterministic Prediction System (GDPS) at 10km horizontal resolution

The Coastal Environmental Baseline Program is a multi-year Fisheries and Oceans Canada initiative designed to work with Indigenous and local communities and other key parties to collect coastal environmental data at a series of sites across Canada, to build a better understanding of existing marine ecological conditions. The program began data collection in 2019, and with the onset of Phase 2 in 2023, the Maritimes region study area was expanded and renamed ‘Northwest Fundy Shores’. A physical oceanography program was designed to align with the oceanographic interests and data needs of local interest holders. Starting in 2023, oceanographic parameters including water temperature, salinity, depth and turbidity have been monitored at a series of locations in Passamaquoddy Bay, the St. Croix River, and along the Bay of Fundy coast, including the Musquash estuary Marine Protected Area (MPA). This dataset includes seasonal CTD (conductivity, temperature and depth) and turbidity data starting in spring 2023. Instruments are maintained through the winter months at a limited number of sites. Data collection methods are primarily moored instruments on the bottom in water depths of 5-90 meters, and a few buoyant surface floats. Overall, this dataset captures seasonal dynamics in near-shore marine environments in Passamaquoddy Bay, the St Croix River, the Bay of Fundy and the Musquash MPA. Cite this data as: Coastal Environmental Baseline Program (Maritimes Region), Northwest Fundy Shores conductivity, temperature and depth data. Published in May 2025. Coastal Environmental Baseline Program. Coastal Ecosystems Science Division, Fisheries and Oceans Canada, St. Andrews, N.B. 14-02-2025

The Coastal Ice Ocean Prediction System (CIOPS) provides a 48 hour ocean and ice forecast over different domains (East, West, Salish Sea) four times a day at 1/36° resolution. A pseudo-analysis component is forced at the ocean boundaries by the Regional Ice Ocean Prediction System (RIOPS) forecasts and spectrally nudged to the RIOPS solution in the deep ocean. Fields from the pseudo-analysis are used to initialize the 00Z forecast, whilst the 06, 12 and 18Z forecasts use a restart files saved at hour 6 from the previous forecast. The atmospheric fluxes for both the pseudo-analysis and forecast components are provided by the High Resolution Deterministic Prediction System (HRDPS) blended both spatially and temporally with either the Global Deterministic Prediction System (GDPS) (for CIOPS-East) or an uncoupled component of the Global Deterministic Prediction System (GDPS) at 10km horizontal resolution (for CIOPS-West) for areas not covered by the HRDPS.

The Coastal Ice Ocean Prediction System (CIOPS) provides a 48 hour ocean and ice forecast over different domains (East, West, Salish Sea) four times a day at 1/36° resolution. A pseudo-analysis component is forced at the ocean boundaries by the Regional Ice Ocean Prediction System (RIOPS) forecasts and spectrally nudged to the RIOPS solution in the deep ocean. Fields from the pseudo-analysis are used to initialize the 00Z forecast, whilst the 06, 12 and 18Z forecasts use a restart files saved at hour 6 from the previous forecast. The atmospheric fluxes for both the pseudo-analysis and forecast components are provided by the High Resolution Deterministic Prediction System (HRDPS) blended both spatially and temporally with either the Global Deterministic Prediction System (GDPS) (for CIOPS-East) or an uncoupled component of the Global Deterministic Prediction System (GDPS) at 10km horizontal resolution (for CIOPS-West) for areas not covered by the HRDPS.

The Coastal Ice Ocean Prediction System (CIOPS) provides a 48 hour ocean and ice forecast over different domains (East, West, Salish Sea) four times a day at 1/36° resolution. A pseudo-analysis component is forced at the ocean boundaries by the Regional Ice Ocean Prediction System (RIOPS) forecasts and spectrally nudged to the RIOPS solution in the deep ocean. Fields from the pseudo-analysis are used to initialize the 00Z forecast, whilst the 06, 12 and 18Z forecasts use a restart files saved at hour 6 from the previous forecast. The atmospheric fluxes for both the pseudo-analysis and forecast components are provided by the High Resolution Deterministic Prediction System (HRDPS) blended both spatially and temporally with either the Global Deterministic Prediction System (GDPS) (for CIOPS-East) or an uncoupled component of the Global Deterministic Prediction System (GDPS) at 10km horizontal resolution (for CIOPS-West) for areas not covered by the HRDPS.

Description:Seasonal climatologies (temperature, salinity, and sigma-t) of the Northeast Pacific Ocean were computed from historical observations including all available conductivity-temperature-depth (CTD), bottle, expendable bathy-thermograph (XBT), and Argo data in NOAA (http://www.argo.ucsd.edu/), Marine Environmental Data Service (MEDS), and Institute of Ocean Sciences archives over 1980 to 2010 period in spatial resolution ranging from approximately 100m to 70km.Methods:Calculations, including smooth and interpolation, were carried out in sixty-five subregions and up to fifty-two vertical levels from surface to 5000m. Seasonal averages were computed as the median of yearly seasonal values. Spring months were defined as April to June, summer months were defined as July to September, fall months were defined as October to December, and winter months were defined as January to March.Uncertainties:Uncertainties are introduced when quality controlled observational data are spatially interpolated to varying distances from the observation point. Climatological averages are calculated from these interpolated values.

Marine Protected Areas require comprehensive monitoring to ensure objectives are achieved; however, monitoring natural ecosystems at scale is challenged by the biodiversity it aims to measure. Environmental DNA (eDNA) metabarcoding holds promise to address this monitoring challenge. We conducted paired sampling at 54 sites for fish and invertebrate assemblages in the Northwest Atlantic using groundfish trawls and eDNA metabarcoding of benthic seawater using four genetic markers (12S rRNA, 16S rRNA, 18S rRNA, and CO1). Compared to trawling, eDNA detected similar patterns of species turnover, larger estimates of gamma diversity, and smaller estimates of alpha diversity. A total of 63.6% (42/66) of fish species captured by trawling were detected by eDNA, along with an additional 26 species. Of the 24 missed detections by eDNA, 12 were inevitable as they lacked reference sequences. Excluding taxa assigned to higher than species level and those without a species name, 23.6% (17/72) of invertebrate species captured by trawling were detected by CO1, which detected an additional 98 species. We demonstrate that eDNA is capable of detecting patterns of community assemblage and species turnover in an offshore environment, emphasizing its strong potential for a non-invasive, comprehensive, and scalable tool for biodiversity monitoring supporting marine conservation programmes.Cite this data as: Jeffery, N., Rubidge, E., Abbott, C., Westfall, K., Stanley, R. (2024): Data of: eDNA metabarcoding enriches traditional trawl survey data for monitoring biodiversity in the marine environment.Published: August 2024. Coastal Ecosystems Science Division, Fisheries and Oceans Canada, Dartmouth, N.S. https://open.canada.ca/data/en/dataset/43a91ba7-8025-4330-88db-db14022d729d

This dataset comprises a map of inland water bodies in Canada and neighboring regions, as described by Ghayourmanesh et al. (2024). The data are mapped using the Lambert Conformal Conic (LCC) geographic projection with a spatial resolution of 250 meters. The LCC projection is frequently used as a standard projection at the Canada Centre for Remote Sensing (CCRS) (Trishchenko et al., 2016, Trishchenko, 2019). Each pixel value represents a code describing either the probability of inland water presence or land/ocean(sea) mask

This dataset provides 1/36-degree monthly-mean ocean current climatology (April - September) in the Northeast Pacific. The climatological fields are derived from hourly ocean currents for the period from 1993 to 2020, simulated using a high-resolution Northeast Pacific Ocean Model (NEPOM).