The Department of Fisheries and Oceans (DFO) Science Branch has designed a multispecies dive survey protocol to provide unbiased, coast wide monitoring of benthic invertebrate stocks (as may be required under the updated Fisheries Act) and associated habitat information for a suite of benthic marine invertebrate species (Green (Strongylocentrotus droebachiensis), Purple (S. purpuratus) and Red Sea Urchin (Mesocentrotus franciscanus), Geoduck (Panopea generosa), Giant Red Sea Cucumber (Apostichopus californicus), Northern Abalone (Haliotis kamtschatkana), and Sunflower Sea Star (Pycnopodia helianthoides)). Based on information available at this time, the proposed survey design can provide estimates of coast wide stock status for Red Sea Urchin and Giant Red Sea Cucumber, and relative abundance indices for Geoduck, Green Sea Urchin, Purple Sea Urchin, Northern Abalone and Sunflower Sea Star.The new protocol was tested through a series of pilot surveys conducted on a subset of areas of the BC coast each September from 2016-2021. Design of the pilot surveys was based on previous dive survey data and experience and demonstrated the practical feasibility of the protocol, while also gathering preliminary information to guide recommendations about the statistical design of the survey.The dataset consists of a relational database containing tables representing each component of the survey methodology. The primary component of the survey is a transect location. Along each transect, systematically spaced quadrats are sampled, and on each quadrat, substrate observations are recorded, multiple species of algae are recorded, and multiple individual invertebrates are measured or counted. The tables are linked by transect number and quadrat number.

SummaryThe Quebec region of the Department of Fisheries and Oceans (DFO) is responsible for the assessment of several fish and invertebrate stocks exploited in the Estuary and the northern Gulf of St. Lawrence. The commercial catches sampling program is one of the sources of information used to complete these assessments. The data collected by this program, at wharf or at sea, offers among other things the advantage of a relatively large spatio-temporal coverage and provides some of the necessary knowledge to assess the demography and the structure of the exploited populations. This program is implemented by specialized DFO staff whose main mandate is to collect biological data on groundfish, pelagic fish and marine invertebrate species that are commercially exploited in the various marine communities.DataThis dataset on the green urchin (Strongylocentrotus droebachiensis) includes the metadata, sample weight, the test width and the number of specimens measured. This dataset covers the periods of 1995, 1997-1999 and 2003 to present. In order to protect the confidentiality of the sources, some informations (such as those concerning the vessel) have been excluded and others (such as the date of capture) have been simplified. Entries where there was only one vessel in a fishing area for a given year were also excluded. Further information including the fishing areas coordinates can be found by clicking on the «Atlantic and Arctic commercial fisheries» and «Fishing areas» links below.

The Quebec region of the Department of Fisheries and Oceans (DFO) is responsible for the assessment of several fish and invertebrate stocks exploited in the Estuary and the northern Gulf of St. Lawrence. The commercial catches sampling program is one of the sources of information used to complete these assessments. The data collected by this program, at wharf or at sea, offers among other things the advantage of a relatively large spatio-temporal coverage and provides some of the necessary knowledge to assess the demography and the structure of the exploited populations. This program is implemented by specialized DFO staff whose main mandate is to collect biological data on groundfish, pelagic fish and marine invertebrate species that are commercially exploited in the various marine communities.The following species have been sampled by this program from 1976 to present:1. American lobster (Homarus americanus)2. American plaice (Hippoglossoides platessoides)3. Atlantic cod (Gadus morhua)4. Atlantic halibut (Hippoglossus hippoglossus)5. Atlantic herring (Clupea harengus)6. Atlantic lyre crab (Hyas araneus)7. Atlantic mackerel (Scomber scombrus)8. Atlantic surfclam (Spisula solidissima)9. Arctic Lyre Crab (Hyas coarctatus)10. Capelin (Mallotus villosus)11. Common softshell clam (Mya arenaria)12. Giant scallop (Placopecten magellanicus)13. Greenland halibut (Reinhardtius hippoglossoides)14. Green urchin (Strongylocentrotus droebachiensis)15. Iceland scallop (Chlamys islandica)16. Redfish (Sebastes sp.)17. Rock crab (Cancer irroratus)18. Sea cucumber (Cucumaria frondosa)19. Snow crab (Chionoecetes opilio)20. Stimpson surfclam (Mactromeris polynyma)21. Waved whelk (Buccinum undatum)22. White hake (Urophycis tenuis)23. Winter flounder (Pseudopleuronectes americanus)24. Yellowtail flounder (Limanda ferruginea)For more information concerning these species, see the «Related Products» section below.

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 European Green Crab (EGC) is a high-risk global invader that can devastate coastal marine ecosystems by displacing native species, degrading and disturbing native habitats (including eelgrass), and altering food webs. EGC has recently been detected in the Canadian portion of the Salish Sea. As EGC continue to establish in the region, identifying locations on which to focus limited monitoring resources is an ongoing problem given the vast amount of coastal habitat that could be occupied by the species. A variety of methods can be used to identify highly suitable habitats for EGC at a range of spatial scales. However, none have been evaluated in the context of informing EGC management, nor for the Canadian portion of the Salish Sea. Here we evaluate five individual methods developed to assess habitat suitability for EGC (i.e., MaxEnt, stochastic gradient boosted linear and logistic regression models, a rapid site selection tool, and a qualitative site assessment and ranking tool) and five derived models generated by multiplying the outputs of these individual models. Each model relied on slightly different environmental and habitat input variables affecting EGC invasion success. Thus, rather than identifying a single preferred model, we used a multi-model ensemble approach to identify sites that are expected to be most suitable for the species. The ensemble approach likely increases predictive power by including both environmental and habitat characteristics when identifying priority sites for early detection/monitoring for EGC in the Canadian waters of the Salish Sea. Finally, we describe how the models evaluated here, alone or in combination, could be used to identify additional sites either within the Salish Sea or into new areas.This dataset contains predicted habitat suitability from five models for European Green Crab at beaches in the Salish Sea (British Columbia, Pacific Region).

This data report provides information on temperature and salinity in the Godbout region of the St. Lawrence Estuary. Sampling was carried out from 2019 to 2021 over an area of <5 km2. The databases provide information on temperature and salinity at an hourly rate for 2 years. The aim of this project is to analyze telemetry data from sea urchins (Strongylocentrotus droebachiensis), snow crabs (Chionoecetes opilio), rock crabs (Cancer irroratus), spider crabs (Hyas spp.) and whelks (Buccinum undatum). This report focuses on the presentation of benthic environmental data collected throughout the study with high spatial and temporal resolution. All reported variables were collected at the seafloor, as the aim of the project was to study the movement of epibenthic species. Temperature data were collected from three devices: telemetry receivers with integrated temperature sensors (InnovaseaTM), HoboTM and Star-OddiTM probes. Temperature data processing involved cleaning up extreme values (below 2°C and above 20°C) and homogenizing the data to fit the bathymetry matrix (1m x 1m cells) of the study site. Temperature data are provided in a NetCDF file with a matrix of the entire study site, where there is a stratum for each hour between August 2019 and October 2021 and in each file, a temperature value for each pixel of the raster. Salinity data were collected from Star-OddiTM probes only. Salinity values were averaged hourly for the entire study area. Salinity data is provided as a CSV file with one salinity value per hour for the entire study area.

The purpose of this study was to characterize the kelp bed at Batture-aux-Alouettes, a preferred food source for the green sea urchin (Strongylocentrotus droebachiensis). The green urchin is fished commercially in Quebec and the fishing effort is concentrated on the Batture-aux-Alouettes near Tadoussac, at the mouth of the Saguenay Fjord. The study was conducted in two separate phases in 2018 and 2019. The main objective of this study was to determine the abundance and biomass of the kelp bed at Batture-aux-Alouettes. The first phase, using a stratified random sampling design, was conducted from August 21th to August 24th, 2018. Sampling of two 50 x 50 cm quadrats, separated by a distance of approximately 30 m, was conducted at eleven sites during twelve dives in the eastern section of the Batture-aux-Alouettes to collect kelp for biomass estimation and macroalgal species richness assessment. In the second phase, a total of 429 stations were first sampled between July 15 and 18, 2019 with a camera system dropped in two 50 x 50 cm quadrats. The presence or absence of kelp, percent macroalgal cover, and substrate type were assessed for each photo. As a result of this underwater photographic analysis, 129 of these stations were identified as having a presence of kelp and 88 of these stations had a presence of other algal species. To ensure equal representation of the different depth strata, the stations with kelp were divided into three depth categories: shallow (-1.7 m to 0 m), medium (0 m to 2 m) and deep (2 m to 5 m). Dives were conducted from August 13 to 15, 2019, at ten of these stations using a stratified random sampling design, taking care to ensure a balanced spatial distribution as well as an equal distribution of the different depth strata (four in the shallow, three in the medium, and two in the deep). Sampling of the 50 x 50 cm dive quadrat took place at three different distances spaced 5 m apart from a transect, i.e. at the 3 m (_3m), 8 m (_8m) and 13 m (_13m) mark. If there was little or no kelp in the quadrat, the quadrat sampling could be repeated for up to four quadrats per distance for a total area of 1 m². Two additional quadrats were conducted (_x) at two stations. Biomass assessment was also done via "cookie cutter" sampling (_CC). Divers took the same 50 x 50 cm quadrat and placed it on a selected (i.e., non-random) plot with 100% kelp cover.The three files provided (DarwinCore format) are complementary and are linked by the "eventID" key. The "event_information" file includes generic information about the event, such as date and location. The "additional_information_event_and_occurrence" file includes sample size, protocol and sampling effort. The "taxon_occurrence" file includes the taxonomy of the species observed, identified to the species or lowest possible taxonomic level. To obtain the abundance and biomass assessment of the kelp bed at Batture-aux-Alouettes, contact Rénald Belley (renald.belley@dfo-mpo.gc.ca).For quality control, the organisms were identified in the field fallowing the guide: Chabot, Robert et Anne Rossignol. 2003. Algues et faune du littoral du Saint-Laurent maritime : Guide d'identification. Institut des Sciences de la mer de Rimouski, Rimouski; Pêches et Océans Canada (Institut Maurice-Lamontagne), Mont-Joli. 113 pages. The taxonomy was checked against the World Register of Marine Species (WoRMS) to match recognized standards and using the R obistools and worrms libraries. The WoRMS match was placed in the "scientificNameID" field of the occurrence file. All sample locations were spatially validated. This project was funded by DFO Coastal Environmental Baseline Program under Canada’s Oceans Protection Plan. This initiative aims to acquire environmental baseline data contributing to the characterization of important coastal areas and to support evidence-based assessments and management decisions for preserving marine ecosystems.

Off Road Vehicle (ORV) Trail Plan show the trails (whether individually or by zone) within the off-road vehicle management area or the part of the off-road vehicle management area for which a trail plan is developed, on which an off-road vehicle may be used. A red, yellow, green scheme is used to symbolize the level of restriction on the trail plan. Red: off road vehicles are prohibited; Yellow: off road vehicles are prohibited except where designated by an approved Off Road Management Area Trail Plan; Green: off road vehicles are not prohibitedDistributed from [GeoYukon](https://yukon.ca/geoyukon) by the [Government of Yukon](https://yukon.ca/maps) . Discover more digital map data and interactive maps from Yukon's digital map data collection.For more information: [geomatics.help@gov.yk. ca](mailto:geomatics.help@yukon.ca)

These products are derived from RGB (red/green/blue) images, a satellite processing technique that uses a combination of satellite sensor bands (also called channels) and applies a red/green/blue (RGB) filter to each of them. The result is a false-color image, i.e. an image that does not correspond to what the human eye would see, but offers high contrast between different cloud types and surface features. The on-board sensor of a weather satellite obtains two basic types of information: visible light data (reflected light) reflecting off clouds and different surface types, also known as "reflectance", and infrared data (emitted radiation) which are short-wave and long-wave radiation emitted by clouds and surface features. RGBs are specially designed to combine this type of satellite data, resulting in an information-rich final product.Other products are based on the enhancement of channel data for a single wavelength, also aimed at highlighting meteorological features of the observed surface or clouds, but in a simpler way since only a single wavelength is involved. This older approach is still useful today, as its simplicity makes image interpretation easier in some cases.

These products are derived from RGB (red/green/blue) images, a satellite processing technique that uses a combination of satellite sensor bands (also called channels) and applies a red/green/blue (RGB) filter to each of them. The result is a false-color image, i.e. an image that does not correspond to what the human eye would see, but offers high contrast between different cloud types and surface features. The on-board sensor of a weather satellite obtains two basic types of information: visible light data (reflected light) reflecting off clouds and different surface types, also known as "reflectance", and infrared data (emitted radiation) which are long-wave radiations emitted by clouds and surface features. RGBs are specially designed to combine this type of satellite data, resulting in an information-rich final product. Four types of products are currently generated from the GOES-West and GOES-East satellites: "NightIR" and "NightMicrophysics", at 2km resolution, are generated 24 hours a day with infrared channels, so are visible both night and day, and "NaturalColour" and "DayCloudConvection", at 1km resolution, which combine visible light channels with infrared channels; their higher resolution makes the latter two products more popular, but they are not available during most of the night (between 02UTC and 07UTC for GOES-Est, and between 06UTC and 11UTC for GOES-Ouest) given the absence of reflected sunlight. Other RGB products should be added gradually in the future to meet different needs.