This dataset contains the modelled and observed data used in the publication "Fjord circulation permits persistent subsurface water mass in a long, deep mid-latitude inlet" by Laura Bianucci et al., DFO Ocean Sciences Division, Pacific Region (published in the journal Ocean Science in 2024). An application of the Finite Volume Community Ocean Model (FVCOM v4.1) was run from May 24 to June 27, 2019 in the Discovery Islands region of British Columbia, Canada. Observed temperature and salinity profiles available in this area during this time period are included in the dataset, along with the modelled values at the same times and locations.

This dataset contains the outputs for Bute Inlet from two simulations shown in the publication "Fjord circulation permits persistent subsurface water mass in a long, deep mid-latitude inlet" by Laura Bianucci et al., DFO Ocean Sciences Division, Pacific Region (published in the journal Ocean Science in 2024). The Finite Volume Community Ocean Model (FVCOM v4.1) was run with two different sets of initial conditions for the Discovery Islands region of British Columbia, Canada, from May 24 to June 27, 2019. The "Baseline" simulation used observed initial conditions, while the "Sensitivity" simulation removed the observed cold subsurface water mass from the initial profiles. Here in this dataset, we provide 29-day averages of the following variables in a transect along Bute Inlet: potential temperature, density, along-inlet velocity, and Brunt-Väisälä frequency (N^2). The averaging properly removes the tidal effects.

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

This dataset provides projected 30-year, 50-year, and 100-year return levels for harbours in British Columbia by 2050 and 2100 under a high emission scenario SSP585, relative to the mean sea level over 1993-2020. The return levels are a combination of estimated present extreme sea levels and projected mean sea level rise. The present extreme sea levels are derived from hourly coastal sea levels for the period from 1993 to 2020, simulated using a high-resolution Northeast Pacific Ocean Model (NEPOM). The projected mean sea level rise is derived from the regional mean sea level rise data of the IPCC 6th Assessment Report under SSP585, adjusted for the local vertical land motion.

This data set is a generalized characterization of the offshore and inshore environments of Canada’s Pacific Ocean. Compiled from various sources to depict the biogenic habitats, pelagic habitats, and general bottom types such as offshore and inshore by depth strata.

A novel towfish incorporating sidescan and video hardware was used to ground truth echosounder data for the nearshore of Halifax Harbour. The resulting sampling grid extended from the shoreline to a depth of 10 m, including Bedford Basin through the Inner Harbour to the Outer Harbour. Each of these three zones could be distinguished from the others based upon combinations of substrate type, benthic invertebrates, and macrophyte canopy. Bedford Basin had a relative lack of macrophytes and evidence of intense herbivory. The Inner Harbour was characterized by shoreline hardening due to anthropogenic activities. The Outer Harbour was the most “natural” nearshore area with a mix of bottom types and a relatively abundant and diverse macrophyte canopy. All survey data were placed into a GIS, which could be used to answer management questions such as the placement and character of habitat compensation projects in the harbour. Future surveys utilizing similar techniques could be used to determine long term changes in the nearshore of the harbour. Cite this data as: Vandermeulen H. Data of: A Video, Sidescan and Echosounder Survey of Nearshore Halifax Harbour. Published: September 2021. Coastal Ecosystems Science Division, Fisheries and Oceans Canada, Dartmouth, N.S. https://open.canada.ca/data/en/dataset/9122c3e2-3cfc-45d0-ac36-aecb306130f6

This dataset provides 30-year, 50-year, and 100 year return levels for small craft harbours in British Columbia, relative to the mean sea level over 1993-2020. The return levels are derived from coastal sea levels for the period from 1993 to 2020, simulated using a high-resolution Northeast Pacific Ocean Model (NEPOM).

Description: These commercial whale watching data are comprised of two datasets. First, the ‘whale_watching_trips_jun_sep_british_columbia’ data layer summarizes commercial whale watching trips that took place in 2019, 2020 and 2021 during the summer months (June to September). The second data layer, ‘wildlife_viewing_events_jun_sep_british_columbia’ contains estimated wildlife viewing events carried out by commercial whale watching vessels for the same years (2019, 2020 and 2021) and months (June to September). Commercial whale watching trips and wildlife viewing events are summarized using the same grid, and they can be related using the unique cell identifier field ‘cell_id’. The bulk of this work was carried out at University of Victoria and was funded by the Marine Environmental Observation, Prediction and Response (MEOPAR) Network under the ‘Whale watching AIS Vessel movement Evaluation’ or WAVE project (2018 – 2022). The aim of the WAVE project was to increase the understanding of whale watching activities in Canada’s Pacific region using vessel traffic data derived from AIS (Automatic Identification System). The work was finalized by DFO Science in the Pacific Region. These spatial data products of commercial whale watching operations can be used to inform Marine Spatial Planning, conservation planning activities, and threat assessments involving vessel activities in British Columbia. Methods: A list of commercial whale watching vessels based in British Columbia and Washington State and their corresponding MMSIs (Maritime Mobile Service Identity) was compiled from the whale watching companies and Marine Traffic (www.marinetraffic.com). This list was used to query cleaned CCG AIS data to extract AIS positions corresponding to commercial whale watching vessels. A commercial whale watching trip was defined as a set of consecutive AIS points belonging to the same vessel departing and ending in one of the previously identified whale watching home ports. A classification model (unsupervised Hidden Markov Model) using vessel speed as the main variable was developed to classify AIS vessel positions into wildlife-viewing and non wildlife viewing events. Commercial whale watching trips in the south and north-east of Vancouver Island were limited to a duration of minimum 1 hour and maximum 3.5 hours. For trips in the west coast of Vancouver island the maximum duration was set to 6 hours. Wildlife-viewing events duration was set to minimum of 10 minutes to a maximum of 1 hour duration. For more information on methodology, consult metadata pdf available with the Open Data record. References: Nesdoly, A. 2021. Modelling marine vessels engaged in wildlife-viewing behaviour using Automatic Identification Systems (AIS). Available from: https://dspace.library.uvic.ca/handle/1828/13300. Data Sources: Oceans Network Canada (ONC) provided encoded AIS data for years 2019, 2020 and 2021, within a bounding box including Vancouver Island and Puget Sound used to generate these products. This AIS data was in turn provided by the Canadian Coast Guard (CCG) via a licensing agreement between the CCG and ONC for the non-commercial use of CCG AIS Data. More information here: https://www.oceannetworks.ca/science/community-based-monitoring/marine-domain-awareness-program/ Molly Fraser provided marine mammal sightings data collected on board a whale watching vessels to develop wildlife-viewing events classification models. More information about this dataset here: https://www.sciencedirect.com/science/article/pii/S0308597X20306709?via%3Dihub Uncertainties: The main source of uncertainty is with the conversion of AIS point locations into track segments, specifically when the distance between positions is large (e.g., greater than 1000 meters).

This dataset was compiled as part of a multiyear effort lead by Fisheries and Oceans Canada (DFO) to support sustainable aquaculture regulation in the Coast of Bays, an area of the south coast of Newfoundland. It is the first of a series aiming to provide an oceanographic knowledge baseline of the Coast of Bays. This dataset consists of GIS products and analyses summarized in a spreadsheet. The GIS data include vector shapefiles and raster TIFF images, providing information on the area of interest physical dimensions (e.g. bays area, volume, perimeter, length and width) and other physical characteristics (e.g. tidal volume and freshwater input). A full description of the data and of its use in the context of the motivating project can be found in http://www.dfo-mpo.gc.ca/csas-sccs/Publications/ResDocs-DocRech/2017/2017_076-eng.html. Analyses from this dataset were presented during a Canadian Science Advisory Secretariat (CSAS) meeting which took place in St John’s in March 2015 (http://www.dfo-mpo.gc.ca/csas-sccs/schedule-horraire/2015/03_25-26b-eng.html) and from which a Science Advisory Report (http://www.dfo-mpo.gc.ca/csas-sccs/Publications/SAR-AS/2016/2016_039-eng.html) and Proceedings (http://www.dfo-mpo.gc.ca/csas-sccs/Publications/Pro-Cr/2017/2017_043-eng.html) were published.

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. "