Fetch is a proxy for wind-wave action and exposure. Estimates of fetch over a total of 39,938 km of the BC coastline were calculated at 50 m intervals, yielding 799,220 near shore fetch points. Fetch was calculated for five regions in Pacific Canada: Haida Gwaii (HG), North and Central Coast (NCC), Queen Charlotte and Johnstone Straits (QCS), Salish Sea (SoG), and West Coast Vancouver Island (WCVI). For all regions, a bearing interval of 5 degrees was used to generate fetch lines for each point along the shoreline, resulting in 72 fetch lines per point. A maximum fetch distance of 200 km was used to ensure the barrier effect of Haida Gwaii was captured.Supplementary information provided includes the fetch geometry calculator script and user guide (Gregr 2014) and a report on the fetch processing objectives, process, and results (Gregr 2015).

Exposure to wind-driven waves forms a key physical gradient in nearshore environments influencing both ecological communities and human activities. We calculated a relative exposure index (REI) for wind-driven waves covering the coastal zone of the Scotian Shelf-Bay of Fundy bioregion. We derived REI and two other fetch-based indices (sum fetch, minimum fetch) from two formulations of wind fetch (unweighted and effective fetch) for input points in an evenly spaced fishnet grid (50-m resolution) covering a buffered area within 5 km from the coastline and shallower than 50 m depth. We calculated unweighted fetch lengths (m) for 32 compass headings per input point (11.25° intervals), and effective fetch lengths for 8 headings per point (45° intervals). Unweighted fetch is the distance along a given heading from a point in coastal waters to land. Effective fetch is a directionally weighted average of multiple fetch measures around a given heading that reduces the influence of irregular coastline shape on exposure estimates. For fetch calculations, we used land features at a 1:50,000 scale for Canadian administrative boundaries (NrCan 2017), and unknown resolution for St. Pierre and Miquelon, and US states bordering the Gulf of Maine (GADM 2012). The summed and minimum unweighted fetch lengths for each point provide coarse summaries of wave exposure and distance to land, respectively. The relative exposure index (REI) gives a more accurate metric of exposure by combining effective fetch with modelled wind speeds (m s-1) and frequency data. We provide the original calculations of unweighted fetch, effective fetch, and other fetch-based indices (i.e., sum, minimum) in csv format along with the REI layer (GeoTIFF format) resampled to 35-m resolution. With broad spatial coverage and high resolution, these indices can support regional-scale distribution modelling of species and biological assemblages in the coastal zone as well as marine spatial planning activities.When using data please cite following:O'Brien JM, Wong MC, Stanley RRE (2022) A relative wave exposure index for the coastal zone of the Scotian Shelf-Bay of Fundy Bioregion. figshare. Collection. https://doi.org/10.6084/m9.figshare.c.5433567ReferencesGADM database of Global Administrative Areas (2012). Global Administrative Areas, version 2.0. (accessed 2 December 2020). www.gadm.orgNatural Resources Canada (2017) Administrative Boundaries in Canada - CanVec Series - Administrative Features - Open Government Portal. (accessed 2 December 2020). https://open.canada.ca/data/en/dataset/306e5004-534b-4110-9feb-58e3a5c3fd97.

This dataset includes five depth-attenuated relative wave exposure index layers in raster format. Relative Exposure Index (REI) values are calculated based on effective fetch (derived from fetch values) combined with modelled wind data. The output REI layers are attenuated by depth, resulting in greater values in shallow, nearshore areas (Bekkby et al. 2008). The cell values represent an estimate of wave exposure at bottom depth normalized between regions from 0 (protected) to 1 (exposed).The objective of this dataset is to provide an estimate of wave exposure at bottom depth, primarily for use in species distribution modelling. Each single-band raster corresponds to a marine region, which generally coincide with the following layers from the Species Distribution Modelling Boundaries (https://www.gis-hub.ca/dataset/sdm-boundaries) dataset: Nearshore_HG, Nearshore_NCC, Nearshore_QCS, Nearshore_QCS, and Shelf_SalishSea. These layers extend to 50 m depth and up to 5 km from shore.Tabular data (csv files) are also included as part of the data package. These data are the calculated Relative Exposure Index (REI) values with fields for position information. The fetch values from gridded nearshore fetch (https://gis-hub.ca/dataset/gridded-nearshore-fetch) are used as a source dataset and the locations in the REI are the same as the gridded fetch.

Exposure to wind-driven waves manifests an important physical gradient in the coastal zone that influences a variety of physical and biological processes (i.e., species distribution). Fetch, the unobstructed distance over which wind-driven waves can build, is a popular proxy for wave exposure at a given location commonly used for site-specific evaluations. Here, we provide two measures of fetch (unweighted fetch, effective fetch) and three fetch-derived indices of wave exposure (sum fetch, minimum fetch, and a relative exposure index) covering the coastal zones of two Canadian bioregions (Scotian Shelf-Bay of Fundy, Newfoundland-Labrador Shelves). For each region, we calculated fetch and exposure indices for input points in an evenly spaced fishnet grid (see linked records below for datasets by region). We provide unweighted fetch lengths (m) for 32 compass headings per input point (11.25° intervals), and effective fetch lengths for 8 headings per point (45° intervals). Effective fetch is a weighted average of multiple fetch measures around a given heading that reduces the influence of irregular coastline shape on exposure estimates. We also include calculations of the summed and minimum unweighted fetch lengths for each point that provide coarse proxies of exposure and distance to land, respectively. The relative exposure index (REI), provided as regional spatial layers in raster format, provides a more accurate metric of exposure by combining effective fetch with modelled wind speeds (m s-1) and frequency data. Users may also use fetch calculations to derive their own exposure layers using alternative sources of wind data, indices, or formulations. Detailed methodology on the calculations for fetch, effective fetch and REI are outlined in the Supplementary Information below. Citation information and differences in data pre-processing methods and spatial resolution of the regional analyses are described in their respective data records. The broad spatial coverage and high resolution offered by these indices are suitable to support regional-scale modelling and planning exercises. In particular, these indices will be of value to ongoing Marine Spatial Planning efforts, which includes regional conservation planning, that seek to evaluate the distribution of coastal species and overlap with human activities.

A relative exposure index (REI), unweighted fetch, effective fetch, and other fetch-based indices (i.e., sum, minimum) were calculated for the Newfoundland and Labrador (NL) Shelves bioregion. Due to the extensive coastline of the study region, this analysis was conducted for a 5km buffered region along the coast at a spatial resolution of 250m. Detailed methods on the selection of input points for the NL bioregion are included below.MethodsPreprocessing and input point selection:Land boundary files were obtained for Eastern Canada and the Canadian Arctic (NrCan 2017) at a scale of 1:50,000 as well as for Saint Pierre and Miquelon (Hijmans 2015), and the New England states (GADM 2012) however the scale at which these layers were produced is unknown. Land boundary files were merged into a single land polygon layer and watercourses reaching for in-land and/or above sea level were clipped from this polygon layer (Greyson 2021). A 5km buffer was generated around the NL provincial boundary. This buffer was then clipped by all land polygons to remove areas overlapping land polygons within the study area. All buffer segments intersecting the NAFO divisions within the NL bioregion were selected and the Union tool in ArcGIS Pro (v. 2.7.2) was used to fill-in gaps within the buffered area, creating a more continuous polygon. The buffered layer was then dissolved, and the NL provincial boundary polygon was erased from the buffered layer to create the study area polygon. A 250m fishnet was created and clipped to the study area (5km buffer layer) and the feature to point tool was used (with the “inside parameter checked”) to convert this grid into a point layer (approx. 1,000,000 points). The spatial resolution for all subsequent analyses was matched to the fishnet grid at 250m.ReferencesGADM database of Global Administrative Areas (2012). Global Administrative Areas, version 2.0. (accessed 2 December 2020). www.gadm.orgGreyson, P (2021) Land boundary file for Eastern Canada, the Canadian Arctic, the New England States and Saint Pierre and Miquelon. [shapefile]. Unpublished data.Hijmans, R. and University of California, Berkeley, Museum of Vertebrate Zoology. (2015). First-level Administrative Divisions, Saint Pierre and Miquelon, 2015. UC Berkeley, Museum of Vertebrate Zoology. Available at: http://purl.stanford.edu/bz573nv9230Natural Resources Canada (2017) Administrative Boundaries in Canada - CanVec Series - Administrative Features - Open Government Portal. (accessed 2 December 2020). https://open.canada.ca/data/en/dataset/306e5004-534b-4110-9feb-58e3a5c3fd97.

The shallow substrate bottom type model was created to support near shore habitat modelling. Data sources include both available observations of bottom type and environmental predictor layers including oceanographic layers, fetch, and bathymetry and its derivatives. Using weighted random forest classification from the ranger R package, the relationship between observed bottom type and predictor layers can be determined, allowing bottom type to be classified across the study areas. The predicted raster files are classified as follows: 1) Rock, 2) Mixed, 3) Sand, 4) MudThe categorical substrate model domains are restricted to the extent of the input bathymetry layers (see data sources) which is 5 km from the 50 m depth contour.

The lobster recruitment project is run by the Fishermen and Scientist Research Society (FSRS) through DFO funding. Fishermen participating in the lobster recruitment project collect information about lobster in their fishing area by fishing 2-5 scientific project traps (SPTs) (fished in fixed locations) within the regular commercial season. The SPTs used in all fishing areas are smaller than commercial traps and designed to primarily catch juvenile lobsters below the legal-size limit.These traps are additional to the vessel's legal number of commercial traps. The lobster recruitment project has more than 120 fishers participating from all LFAs along the Atlantic coast of Nova Scotia from LFA 27 in Cape Breton to LFA 35 in the Bay of Fundy (excluding LFA 28, who have not participated to-date).The number of fishermen per LFA and number of SPTs per fisherman are decided on by the LFA Advisory Committees. This decision considers how much additional effort they were comfortable having in the LFA (i.e. number of SPTs) and from how many traps each fisher could be reasonably expected to collect data. It is also important to have fishers dispersed enough to maximize study footprint. DFO Science consults on project design. SAMPLING METHODS: The fishers record the number, sex and length of lobsters captured in each SPT, as well as presence of eggs, tags or v-notch. Bottom temperatures are monitored by placing a temperature recorder in one of their SPTs for the entire lobster season.Cite this data as: Tibbets-Scott, S., Zisserson, B. Data of: Fishermen and Scientist Research Society (FSRS) Lobster Recruitment Trap Project. Published: November 2020. Population Ecology Division, Fisheries and Oceans Canada, Dartmouth, N.S. https://open.canada.ca/data/en/dataset/a88f9b4d-b59a-44f6-ae7e-d36550266940

Spatial distribution of lumpfish catch rates (number per tow) during the August DFO research survey conducted annually since 1990, to assess the state of groundfish and shrimp stocks in the northern Gulf of St. Lawrence.The area sampled by a tow is the product of the distance trawled (fishing time multiplied by vessel speed) and the wing spread (13.41 m for the Alfred Needler and 16.94 m for the Teleost). Given that this area may vary among tows, the sampling unit is standardized and defined as being a station sampled by a tow over a distance of 0.75 nautical miles (1,389 m) with a horizontal wing spread of 16.94 m. Catch variables were calculated based on the standard area, 0.02353 km².After each tow, the catch was sorted by taxa, and the number of individuals and total biomass of these taxa were noted. For taxa identified to the species level, individual biometric parameters (e.g., length, weight) and biological parameters (e.g., sex, maturity of gonads) were recorded based on a subsample. Full methods are described in Bourdages et al. (2010).Note that the increase in catch rate for the 2005-2009 period coincides with a change in gear for this survey.Bourdages, H., and Ouellet, J.-F. 2011. Geographic distribution and abundance indices of marine fish in the northern Gulf of St. Lawrence (1990–2009). Can. Tech. Rep. Fish. Aquat. Sci. 2963: vi + 171 p.Source:Gauthier, J., Grégoire, F., and Nozères, C. 2017. Assessment of Lumpfish (Cyclopterus lumpus) in the Gulf of St. Lawrence (3Pn, 4RS) in 2015. DFO Can. Sci. Advis. Sec. Res. Doc. 2017/051. v + 47 p.PurposeThe multidisciplinary survey of groundfish and shrimp in the northern Gulf of St. Lawrence has been conducted every August by Fisheries and Oceans Canada for more than two decades. Initially, its objective was to determine the abundance and geographic distribution of commercially important taxa. However, for couple of years, the objective was expanded to include all taxa caught with the shift toward the ecosystem approach.

Records of marine mammal sightings (N = 5,324) collected by ASOs and submitted to Fisheries and Oceans Canada (DFO) between 1979-2024, across three DFO regions: the Arctic, Newfoundland and Labrador, and the Maritimes. Methods for initial data compilation are provided in the associated technical report "Marine mammal records collected by the at-sea observer (ASO) program in Arctic, Newfoundland and Labrador, and Maritimes regions: a summary of challenges and opportunities for future research." Cite this data as: Feyrer, L.J., Colbourne, N., Lawson, J.W., Moors-Murphy, H.B., Ferguson, S. Dataset update to Marine mammal records collected by the At-Sea Observer program in Arctic, Newfoundland and Labrador and Maritimes regions. Published: February 2025. Ocean Ecosystems Science Division, Fisheries and Oceans Canada, Dartmouth, N.S.

These datasets show commercial fisheries catch weight landings of directed fisheries and bycatch from the Scotian Shelf, the Bay of Fundy, and Georges Bank from NAFO Divisions 4VWX and the Canadian portions of 5Y and 5Z. Atlantic Canadian inter-regional maps of four species (Atlantic Halibut, Bluefin Tuna, Redfish and Scallop) are also included from NAFO Divisions 4RST, 3KLMNOP, and 2GHJ. Five-year composite maps (2014–2018) that aggregate catches for each map series are publicly available. The maps aggregate catch weight (kg) per 10 km2 hexagon grid cell for selected species, species groupings and gear types to identify important fishing areas. These maps may be used for decision making in coastal and oceans management, including marine spatial planning, environmental emergency response operations and protocols, Marine Stewardship Council certification processes, marine protected area networks, and ecological risk assessment.These datasets have been filtered to comply with the Government of Canada's privacy policy. Privacy assessments were conducted to identify NAFO unit areas containing data with less than five vessel IDs, licence IDs or fisher IDs. If this threshold was not met, catch weight locations were withheld from these unit areas to protect the identity or activity of individual vessels or companies.Maps were created for the following species, species groupings and gear types:1. Groundfish (all species)2. Groundfish Bottom Trawl3. Groundfish Gillnet4. Groundfish Bottom Longline5. Groundfish (quarterly composites Q1, Q2, Q3, Q4)6. Atlantic Cod7. Atlantic Cod, Haddock and Pollock8. Flatfish9. Atlantic Halibut10. Greenland Halibut (Turbot)11. Hagfish12. Cusk13. Dogfish14. Redfish15. Red Hake16. Silver Hake17. White Hake18. Monkfish19. Sculpin20. Skate21. Wolffish22. Squid23. Herring24. Mackerel25. Large Pelagics26. Bluefin Tuna27. Other Tuna28. Swordfish29. Porbeagle, Mako and Blue Shark30. Snow Crab31. Other Crab32. Scallop33. Scallop (quarterly composites Q1, Q2, Q3, Q4)34. Offshore Clam35. Shrimp36. Offshore Lobster37. Disputed Zone Area 38B Lobster38. Whelk