The Automatic Identification System (AIS) is a global, satellite-based and terrestrial-based ship tracking system that uses shipborne equipment to remotely track vessel identification and positional information and is typically required on vessels of 300 gross tonnage or more on an international voyage, of 500 gross tonnage or more not on an international voyage, and passenger ships of all sizes. AIS tracking technologies are primarily used in support of real-time maritime domain awareness and for maritime security and safety of life at sea. This report describes a geographic information system (GIS) analysis of 2019 AIS data to produce yearly and monthly vessel density maps of all vessel classes combined and yearly density maps of each vessel class. The year 2019 was selected to portray shipping densities in a pre-COVID 19 pandemic depiction of the maritime transport sector in the Northwest Atlantic. Vessel density map applications include use in spatial analysis and decision support for marine spatial planning.In 2023 the process was applied to the years 2013 through to 2022 and were made available using the same processes that were applied to the original 2019 datasets.

The locations of coastal British Columbia marine navigation hazards. The Coastal BC datasets are circa 2004 and legacy in nature. Caution should be exercised when using this data, as it may not be accurate or complete. There are currently no plans to update.

The Planning for an Environmental Response (PIER) initiative falls under the umbrella of the Government of Canada's Oceans Protection Plan (OPP), whose goal is preserving marine ecosystems vulnerable to increased transportation and the development of the marine industry (https://pm.gc.ca/en/news/backgrounders/2016/11/07/canadas-oceans-protection-plan-preserving-and-restoring-canadas). The PIER was established in response to recommendations made in a 2013 report "A review of Canada's ship-source spill preparedness and response regime " by the Tanker Safety Expert Panel (https://tc.canada.ca/en/marine-transportation/marine-safety/tanker-safety-expert-panel). One of the recommendations calls on Fisheries and Oceans (DFO) to work with Environment and Climate Change Canada (ECCC) to collect and compile information on sensitive species and environments for each Canadian Coast Guard (CCG) response area and make it publicly available.The PIERs’ main mandate is to acquire and update biological sensitivity data under its jurisdiction for preparation and response purposes in the event of an oil spill. With DFO-Science, PIER supports ECCC's National Environmental Emergencies Centre (NEEC) and the CCG in their preparations and responses through the sharing of data on biological sensitivities, the development of response tools and expert advice.In this vein, DFO published an analysis in 2018 that aimed to identify the most vulnerable components of the St. Lawrence in order to prioritize them during data collection if gaps were identified (Desjardins et al. 2018). This exercise highlighted the vulnerability of several biological components and important data gaps, particularly in coastal areas. As a result of this finding, the Quebec region PIEI team embarked on a collaborative project with the Université du Québec à Rimouski (UQAR) to map eelgrass beds, tidal marshes and macroalgal beds. In consultation with other DFO-Science data producers, this team has also created datasets adapted for response purposes, notably regarding bivalves and marine mammals. These layers may be used for oil spill preparedness and response by DFO-Quebec Region's Environmental Incident Coordinator, NEEC and CCG. Several of them, deemed relevant in the first 72 hours following a spill, have been transmitted to the NEEC.

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 six pilot sites across Canada (Port of Vancouver, Port of Prince Rupert, Lower St. Lawrence Estuary, Port of Saint John, Placentia Bay, and Iqaluit). The goal of the Program is to gather local information in these areas in effort to build a better understanding of marine ecological conditions. The Maritimes region has developed a habitat classification program to align with the oceanographic interests and data needs of local communities and stakeholders, with the goal of sharing this information via open data. In 2020, a habitat survey in the lower Musquash Marine Protected Area (MPA) was undertaken to further develop this project, using an Autonomous Underwater Vehicle (AUV) equipped with high-frequency (450 kHz) side scan sonar to build a habitat map of the MPA. This dataset includes mosaicked series of sonar images (raw & position-corrected versions), covering roughly 6 km2 of marine and intertidal areas in the Musquash MPA. Doppler Velocity logs and mission-specific files for each survey are also included, along with detailed methodological documentation. These data were generated from 17 separate survey missions that were completed in August, September and October 2020.

CMIST is a peer-reviewed screening-level risk assessment tool for marine invasive species (Drolet et al. 2016). It is a short questionnaire that follows the invasion process from arrival to impact and is designed so an informed assessor can evaluate one species in an assessment area in approximately one day using easily accessible information from internet databases, primary literature, and grey literature. Species can be those with an invasion history in an area or those that are candidates for future invasions.CMIST is score-based and incorporates both likelihood and impact of invasion as well as uncertainty. Questions are general to make CMIST broadly applicable to different taxa, different assessment areas, and different project goals. To date, CMIST has been tested with molluscs, tunicates, crustaceans, and polychaetes introduced or at risk of introduction to three Canadian marine ecoregions (DFO 2009). CMIST has also been successfully applied to non-indigenous freshwater fish in British Columbia with adapted guidelines (T. Therriault, pers. comm.). Upon completion, CMIST produces a risk score adjusted for the assessor’s uncertainty which, combined with information collected during the assessment, can be used to assist in management decisions. For example, in 2015, CMIST assessments were used to identify high risk invaders in three Canadian marine ecoregions (DFO 2016).

In 2016-17, DFO Maritimes Region undertook a Marine Protected Area (MPA) network analysis for the Scotian Shelf-Bay of Fundy Bioregion. The analysis considered available bioregional-scale ecological and human use data in an effort to identify a draft MPA network design that would protect biodiversity while minimizing any potential impacts on commercial fishing and other industries. The data layers used for the offshore component of the MPA network analysis are provided here. These layers are not presented in their original forms and were modified (e.g. clipped, reclassified, etc.) specifically for use in the MPA network analysis. They should not be used for any other purpose. Please see Serdynska et al. 2021 for details on how each layer was created.Serdynska, A.R., Pardy, G.S., and King, M.C. 2021. Offshore Ecological and Human Use Information considered in Marine Protected Area Network Design in the Scotian Shelf Bioregion. Can. Tech. Rep. Fish. Aquat. Sci. 3382: xi + 100 p. https://publications.gc.ca/collections/collection_2021/mpo-dfo/Fs97-6-3382-eng.pdfCite this data as: Serdynska, A.R., Pardy, G.S., and King, M.C. Data of: Offshore Ecological and Human Use Information considered in Marine Protected Area Network Design in the Scotian Shelf Bioregion. Published: January 2022. Fisheries and Oceans Canada, Dartmouth, N.S. https://open.canada.ca/data/en/dataset/2d9cce9a-d634-4b49-879f-87c40c52acf2

We evaluated an autonomous environmental DNA sampler produced by Dartmouth Ocean Technologies Inc (Dartmouth, Canada) compared to time-at-sample filtration in the laboratory to determine the performance of moored samplers for monitoring in the marine world. We deployed three autonomous samplers from DOT in the Bedford Basin (Canada) over a nine-week period in summer/fall 2023. The samplers filtered seawater in situ at programmed interviews over this time period, and we collected contemporaneous samples with a standard vacuum pump during each sampling period. Both eDNA sample types captured similar fish diversity, including typical diversity for the Northwest Atlantic. The invertebrate community detected using the COI marker was different between each sample type, likely due to differences in filter pore size. We found biofouling on the moored samplers was minimal over the study period, even in a high-traffic area such as the Bedford Basin, likely due to the relatively short experimental period, and copper screening covering in the inlet and outlet valves of the instruments. Overall, our results show promise to deploy autonomous eDNA samplers in marine conservation areas to contribute to monitoring in the temperate ocean, but further testing over longer periods of time is needed to determine if DNA remains well-preserved in the autonomous samplers at ambient ocean temperatures.Cite this data as: Jeffery, N.W., Van Wyngaarden, M., and Stanley, R.R.E. Evaluating an Autonomous eDNA Sampler for Marine Environmental Monitoring: Short- and Long-Term Applications. Published: December 2024. Coastal Ecosystems Science Division, Maritimes Region, Fisheries and Oceans Canada, Dartmouth NS.

PURPOSE:Eastern Beaufort Sea beluga whales form one of the largest summering aggregations of the species in the Mackenzie Estuary. In 2010, the Tarium Niryutait Marine Protected Area (TNMPA) was designated to protect beluga whales and their habitats As a part of ongoing ecological monitoring efforts in the TN MPA, passive acoustic monitoring (PAM) was implemented in 2011 to act as continuous monitoring method, filling the temporal gaps associated with historical aerial surveys. Beginning in 2014, PAM effort increased each year, and oceanographic sensors were added to moorings to (1) better understand oceanographic conditions within the TN MPA and (2) examine the environmental parameters that drive beluga movement and habitat use patterns within the estuary. Several studies using this dataset have been completed, and others are ongoing. However, much more can be done with the acoustic and environmental data. The purpose of this report is to outline deployment methods and instrument settings for moorings to support the full use of the data collected. DESCRIPTION:Each summer, Eastern Beaufort Sea beluga whales form one of the largest aggregations of the species in the Mackenzie Estuary. In 2010, the Tarium Niryutait Marine Protected Area (TNMPA) was designated in the estuary to protect beluga whales and their habitats. As a part of ongoing ecological monitoring efforts in the TN MPA, passive acoustic monitoring (PAM) was implemented in 2011 to act as continuous monitoring method, filling the temporal gaps associated with historical aerial surveys. Beginning in 2014, PAM effort increased each year, and oceanographic sensors were added to each PAM mooring to (1) better understand oceanographic conditions (i.e., temperature, salinity, turbidity, and wave conditions) within the TN MPA and (2) to examine the environmental parameters that drive beluga movement and habitat use patterns within the estuary. Moorings have been deployed with varying configurations of oceanographic sensors in Kugmallit Bay since 2015, but typically record water temperature, salinity, depth, and wave conditions. In 2018, the program was expanded to the Niaqunnaq parcel of the MPA (Shallow Bay), and in 2021 it was expanded again to the Okeevik parcel of the MPA. These observatories have provided new knowledge about drivers of beluga habitat use in the TN MPA, in particular in Kittigaryuit, but more recently in Niaqunnaq and Okeevik.

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

Benthic Marine Ecounits in coastal and offshore British Columbia. Benthic ecounits are intended to describe the sea bed and nearshore. Seven variables were selected to derive benthic ecounits: 1. Depth; 2. Slope; 3. Relief; 4. Temperature; 5. Exposure; 6. Current and 7. Substrate. CRIMS is a legacy dataset of BC coastal resource data that was acquired in a systematic and synoptic manner from 1979 and was intermittently updated throughout the years. Resource information was collected in nine study areas using a peer-reviewed provincial Resource Information Standards Committee consisting of DFO Fishery Officers, First Nations, and other subject matter experts. There are currently no plans to update this legacy data.