These datasets show the general spatial distribution of commercial fishing harvest and landed values by fishery on a 1km x 1km planning grid. They aggregate key statistics around fleet specific fishing activity and catch in British Columbia (BC) within the exclusive economic zone (EEZ). These gridded data describe the annual average landed weight (Rounded KGs), and landed catch values (CAD $2016) of the subject fishery over the period. The data represented were created from logbook records and matched to prices from fish slips submitted to DFO by participants of BC’s commercial fishing fleets. The dataset is comprised of an aggregate of all species over 10, 9, or 5 years of fishing seasons, depending on the fishery. To preserve potentially proprietary information, a privacy filtering Rule of Five has been applied to each planning unit (each 1km x 1km planning unit). If any planning units do not meet this minimum of 5 unique vessels/unique identifiers during the time span then they are flagged as being filtered and an average of all filtered planning units is applied. The accompanying GeoDB contains two data layers, “all_fisheries_filtered_gridded “, which includes all of the commercial fisheries data in 1km x 1km grids, and “DFO_marine_bioregions_NSB_subregions”, which includes polygon feature boundaries for the federal marine bioregions and Northern Shelf bioregion sub-regions. This dataset contains data for the following fisheries: - Bottom trawl (2012-2016) - Midwater trawl (2012-2016) - Shrimp by trawl (2007-2016) - Prawn trap (2007-2016) - Rockfish (2012-2016) - Sablefish (2007-2016) - Halibut (2007-2016) - Combo trips - halibut/sablefish (2007-2016) - Lingcod (2007-2016) - Green sea urchin (2006-2015) - Red sea urchin (2007-2015) - Sea cucumber (2008-2016) - Geoduck (2007-2015)

The water level data comes from the groundwater monitoring network of British Columbia (Canadian province). Each well in the observation network is equipped with a hydrostatic pressure transducer and a temperature sensor connected to a data logger. A second pressure transducer located above the water surface allows for adjusting the water level according to atmospheric pressure variations. The time series refers to the level below which the soil is saturated with water at the site and at the time indicated. The water level is expressed in meters above sea level (MASL). The dataset consists of a general description of the observation site including; the identifier, the name, the location, the elevation and a series of numerical values designating the water levels at a defined date and time of measurement.

Cartographic representations of Fisheries Management Areas (FMA)s in the Atlantic and Arctic Regions. Currently Published Fisheries Management Areas: Capelin Crab Herring Mackerel Salmon, Atlantic Scallop Shrimp Snow Crab Squid Each polygon feature class delineates the coordinates of a different series of FMAs. Shapes have been drafted based on a combination of sources including: the Atlantic Fisheries Regulations, Integrated Fisheries Management Plans, indigenous treaties, the bounds of the Territorial Sea, and other information made public on Fisheries and Oceans websites. Information from Variation orders and Conditions of License were also incorporated. The specific sources used to construct each feature class is listed in its metadata and direct links to public sources are included. The original documentation uses a diverse combination datums, or include coordinates with no listed datum. This data series has been projected into NAD83. Vertices in this dataset may differ from the original source documents to fix slivers, make areas congruent with coastlines, or align with other administrative boundaries. Changes made to the original areas in order to make drafting possible have been highlighted in the comments field in the attribute tables. Lines were first drafted as geodesics and vertices were added to approximate loxodromes using the Construct Geodesic Tool in ArcGIS Pro 2.9.8. As documentation is drafted, additional FMAs will be added to the dataset. Currently drafted FMAs my change and expand into currently unmapped areas as new information is incorporated. The feature classes produced as a part of this data series are cartographic representations of legal documents and are meant to be used for general reference in support of marine planning. Whenever there is a difference between the original written source documentation and this digital representation, the originals should be considered authoritative. Every effort has been made to ensure that these files are as accurate as possible but these feature classes are not intended to be used for navigation, legal interpretation or enforcement.

Eelgrass (Zostera marina) is important to waterfowl such as Atlantic Brant (Branta bernicla hrota), Canada Goose (Branta canadensis), American Black Duck (Anas rubripes), Common Goldeneye (Bucephala clangula) and Barrow's Goldeneye (Bucephala islandica). In New Brunswick eelgrass can be found along the Gulf of St. Lawrence, in protected harbours. Within this dataset are the results of eelgrass land-cover classifications using either satellite or aerial photography for seven harbours: Bouctouche (46 30’N, 64 39’W); Miscou (47.90 N, -64.55 W); Neguac (47.25 N, -65.03 W); Richibucto (46.70 N, -64.80 W); Saint-Simon (47.77 N, -64.76 W); Tracadie (47.55 N, -64.88 W); and Cocagne (46.370 N, -64.600 W). Information on each dataset is provided: 1. Bouctouche This dataset contains results from an eelgrass classification for Bouctouche Bay, New Brunswick. True colour aerial photography at 57 centimetre resolution was collected on September 2, 2009 by Nortek Resources of Thorburn, Nova Scotia (http://www.nortekresources.com/). Image classification was conducted using eCognition Developer v. 8 Software, which first segments the image into spectrally similar units, which were then classified manually. Additionally, the Department of Fisheries and Oceans (Gulf Region, Moncton, NB) conducted a visual field survey in the same field season at 688 sites. Two-thirds of these sites were used to assist in image classification, while the remainder were used to assess accuracy. Three classes were identified: i. Good Quality Eelgrass: relatively dense, clean, green blades with minimal epiphytes or algal growth. ii. Medium Quality Eelgrass: predominately green blades that may have some epiphyte or algal growth. These stands can be less or equally dense as Good Quality Eelgrass, but the best grasses are certainly not as abundant. iii. Eelgrass Absent/Poor Quality: eelgrass is absent, or if it is present it is typically covered with epiphytes or other algae or dying or dead. Eelgrass was classified correctly 83.7% of the time in a fuzzy accuracy assessment technique, whereby those classes that were ‘off’ by one class, e.g. Good Quality eelgrass classed as Medium Quality, were given half credit towards the overall accuracy. Of 187 sites that were within the classification area, 131 were correct, 51 were "one-off", and 5 were incorrect [(131 + (51/2))/ 187 = 0.837]. 2. Miscou True colour aerial photography at 57 centimetre resolution was collected on August 20th and 24th, 2009 by Nortek Resources of Thorburn, Nova Scotia (http://www.nortekresources.com/). Image classification was conducted using eCognition Developer v. 8 Software, which first segments the image into spectrally similar units, which were then classified manually. Additionally, the Department of Fisheries and Oceans (Gulf Region, Moncton, NB) conducted a visual field survey in the same field season at 103 sites. From these sites 70% were used to assist in image classification, while the remainder were used to assess accuracy. Three classes were identified: i. Good Quality Eelgrass: relatively dense, clean, green blades with minimal epiphytes or algal growth. ii. Medium Quality Eelgrass: predominately green blades that may have some epiphyte or algal growth. These stands can be less or equally dense as Good Quality Eelgrass, but the best grasses are certainly not as abundant. iii. Eelgrass Absent/Poor Quality: eelgrass is absent, or if it is present it is typically covered with epiphytes or other algae or dying or dead. Eelgrass was classified correctly 96.7% of the time (30/31 = 0.967). 3. Neguac This dataset contains results from an eelgrass classification for Neguac Bay, New Brunswick. True colour aerial photography at 57 centimetre resolution was collected on September 2, 2009 by Nortek Resources of Thorburn, Nova Scotia (http://www.nortekresources.com/). Image classification was conducted using eCognition Developer v. 8 Software, which first segments the image into spectrally similar units, which were then classified manually. Additionally, the Department of Fisheries and Oceans (Gulf Region, Moncton, NB) conducted a visual field survey in the same field season at 126 sites. Two-thirds of these sites were used to assist in image classification, while the remainder were used to assess accuracy. Three classes were identified: i. Good Quality Eelgrass: relatively dense, clean, green blades with minimal epiphytes or algal growth. ii. Medium Quality Eelgrass: predominately green blades that may have some epiphyte or algal growth. These stands can be less or equally dense as Good Quality Eelgrass, but the best grasses are certainly not as abundant. iii. Eelgrass Absent/Poor Quality: eelgrass is absent, or if it is present it is typically covered with epiphytes or other algae or dying or dead. Eelgrass was classified correctly 81% of the time in a fuzzy accuracy assessment technique, whereby those classes that were ‘off’ by one class, e.g. Good Quality eelgrass classed as Medium Quality, were given half credit towards the overall accuracy. Of 39 sites that were within the classification area, 27 were correct, 9 were "one-off", and 3 were incorrect [(27 + (9/2))/ 39 = 0.81]. 4. Richibucto Eelgrass classification in Richibucto Harbour, New Brunswick. Derived from a Quickbird satellite image collected on August 28, 2007 at as close to low-tide as possible. Quickbird's ground resolution is 2.4 m. Classification was objected-oriented using Definiens software. Accuracy was 81.5%. Data used for accuracy and training was collected along transects using a differential GPS positioned towfish holding sidescan sonar, and a video camera that was later transcribed as XY points to describe eel-grass presence. 5. Saint-Simon An eelgrass distribution map was classified from remotely sensed imagery in Shippagan Harbour, New Brunswick. Derived from a Quickbird satellite image collected on July 27, 2007 at as close to low-tide as possible. Classification was objected-oriented using Definiens software. Data used for accuracy and training was collected along transects using a differential GPS positioned towfish holding sidescan sonar, and a video camera that was later transcribed as XY points to describe eel-grass presence. 6. Tracadie This dataset contains results from an eelgrass classification for Tracadie Bay, New Brunswick. True colour aerial photography at 57 centimetre resolution was collected on September 2, 2009 by Nortek Resources of Thorburn, Nova Scotia (http://www.nortekresources.com/). Image classification was conducted using eCognition Developer v. 8 Software, which first segments the image into spectrally similar units, which were then classified manually. Additionally, the Department of Fisheries and Oceans (Gulf Region, Moncton, NB) conducted a visual field survey in the same field season at 101 sites. Approximately two-thirds of these sites were used to assist in image classification, while the remainder was used to assess accuracy. Three classes were identified: i. Good Quality Eelgrass: relatively dense, clean, green blades with minimal epiphytes or algal growth. ii. Medium Quality Eelgrass: predominately green blades that may have some epiphyte or algal growth. These stands can be less or equally dense as Good Quality Eelgrass, but the best grasses are certainly not as abundant. iii. Eelgrass Absent/Poor Quality: eelgrass is absent, or if it is present it is typically covered with epiphytes or other algae or dying or dead. Eelgrass was classified correctly 79.3% of the time in a fuzzy accuracy assessment technique, whereby those classes that were ‘off’ by one class, e.g. Good Quality eelgrass classed as Medium Quality, were given half credit towards the overall accuracy. Of 29 sites that were within the classification area, 18 were correct, 10 were "one-off", and 1 was incorrect [(18 + (10/2))/ 29 = 0.793]. 7. Cocagne Visible orthorectified aerial photography was used to classify polygons containing eelgrass in Cocagne Harbour. Field data for image training and validation were collected along transects in summer 2008 using a dGPS positioned towfish holding sidescan sonar and a video camera that was later transcribed as XY geographic points to describe eelgrass presence and a qualitative description of density. The area was flown for photography on September 24, 2008. eCognition Developer 8 software was used to segment the imagery, essentially polygons. Polygons were then classified manually for the presence of eelgrass. Using field data revealed eelgrass presence to be mapped correctly 87.2% of the time.

In 2021, the Canada Coast Guard (CCG) and Fisheries and Oceans Canada (DFO) updated its administrative boundaries following the creation a new Arctic region.There are now 7 administrative regions in DFO (Pacific, Arctic, Ontario and Prairie, Quebec, Gulf, Maritimes, Newfoundland and Labrador). DFO and Coast Guard Arctic Regions developed these regions in partnership with the people they serve; this important decision will lead to stronger programs and services to better meet the unique needs of our Arctic communities.DFO and CCG operations and research cover Canada's land and waters to the international boundaries (EEZ) and are in no way limited to the boundaries drawn in the map.

This dataset provides marine bacteriological water quality data for bivalve shellfish harvest areas in Prince Edward Island, Canada. Shellfish harvest area water temperature and salinity data are also provided as adjuncts to the interpretation of fecal coliform density data. The latter is the indicator of fecal matter contamination monitored annually by Environment and Climate Change Canada (ECCC) within the framework of the Canadian Shellfish Sanitation Program (CSSP). The geospatial positions of the sampling sites are also provided. These data are collected by ECCC for the purpose of making recommendations on the classification of shellfish harvest area waters. ECCC recommendations are reviewed and adopted by Regional Interdepartmental Shellfish Committees prior to regulatory implementation by Fisheries and Oceans Canada (DFO). This dataset is 'Deprecated'. Please use updated source here. https://open.canada.ca/data/en/dataset/6417332a-7f37-49bd-8be9-ce0402deed2a

The Water Survey of Canada (WSC) is the national authority responsible for the collection, interpretation and dissemination of standardized water resource data and information in Canada. In partnership with the provinces, territories and other agencies, WSC operates over 2800 active hydrometric gauges across the country. WSC maintains and provides real-time and historic hydrometric data for some 8000 active and discontinued stations. This dataset consists of a set of polygons that represent the drainage areas of both active and discontinued discharge stations. Users are encouraged to report any errors using the “Contact Us” webpage at: https://weather.gc.ca/mainmenu/contact_us_e.html?site=water

Points, polylines and polygons where species and features have been found, harvested or detailed. Community Based Coastal Resource Inventory (CCRI) – Fisheries and Oceans Canada in conjunction with several Federal and Provincial agencies created, implemented, and managed a program which set out to develop a coastal resource inventory based on the traditional knowledge of local residents. Through partnerships with the province of Newfoundland and Labrador’s Regional Economic Development (RED) Boards and other community based groups the project assembled a database containing several decade’s worth of local knowledge. The value of the information collected came through individual interviews with people who had extensive knowledge of the immediate geography and resource, having lived, worked and harvested the regions over a lifetime. This project ran from 1996 to 2007.

The water level data comes from the groundwater monitoring network of Nova Scotia (Canadian province). Each well in the observation network is equipped with a hydrostatic pressure transducer and a temperature sensor connected to a data logger. A second pressure transducer located above the water surface allows for adjusting the water level according to atmospheric pressure variations. The time series refers to the level below which the soil is saturated with water at the site and at the time indicated. The water level is expressed in meters above sea level (MASL). The dataset consists of a general description of the observation site including; the identifier, the name, the location, the elevation and a series of numerical values designating the water levels at a defined date and time of measurement.