Proxied dataset of inshore lobster commercial fishing for 2012 - 2021 in the Newfoundland and Labrador region. Only lobster harvested from the Newfoundland and Labrador region are included, based on species sought. Commercial data for the inshore lobster fishery does not require a set of coordinates be provided for catch records. With zero georeferenced inshore lobster records, the inshore lobster fishery leaves a major data gap in one of Newfoundland and Labradors largest fisheries. The Gulf region created a lobster proxy mapping tool, which associated each commercial lobster record with the most likely 10km2 hexagon grid cell based on a number of weighted variables. The tool was adopted by the Newfoundland and Labrador region and altered to work with its own variables which include human use, habitat, accessibility, area/location, home port distance, traditional ecological knowledge and depth. Each hexagon represents the summed total weight of all records associated with a particular hexagon. The best available commercial data used in this model is derived from landings data and may not include catches that have resulted in cash/wharf sales. As a result, there are some areas of Newfoundland and Labrador that may be under represented in this dataset where wharf sales may be high. Therefore, this dataset should be viewed as a general estimation on lobster harvesting patterns within Newfoundland and Labrador.

This point layer shows the locations of places of interest to Parks Canada, visitors, employees, or local residents. These are points that are not already mapped as Parks Canada facilities or components of facilties. Data is not necessarily complete - updates will occur weekly.

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.

The water level data comes from the groundwater monitoring network of Yukon (Canadian territory). 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.

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 (https://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].

This dataset is part of Environment and Climate Change Canada’s Shoreline Classification and Pre-Spill database. Shoreline classification data has been developed for use by the Environmental Emergencies Program of Environment and Climate Change Canada for environmental protection purposes. Marine and freshwater shorelines are classified according to the character (substrate and form) of the upper intertidal (foreshore) or upper swash zone (Sergy, 2008). This is the area where oil from a spill usually becomes stranded and where treatment or cleanup activities take place. The basic parameter that defines the shoreline type is the material that is present in the intertidal zone. The presence or absence of sediments is a key factor in determining whether oil is stranded on the surface of a substrate or can penetrate and/or be buried. This dataset contains thousands of linear shoreline segments ranging in length from 200 m and 2 km long. The entities represent the location of the segments and their geomorphological description. There exist further fields in the attribute table for this dataset. We are currently working on standardizing our shoreline segmentation datasets and the updated data will soon be uploaded to the catalog. Sergy, G. (2008). The Shoreline Classification Scheme for SCAT and Oil Spill Response in Canada. Proceedings of the 31stArctic and Marine Oil Spill Program Technical Seminar.Environment Canada, Ottawa, ON, Pp. 811-819.

This dataset was developed to provide a complete record of salmon rivers within the province of Newfoundland and Labrador. It is organized by DFO detachment area and can be used for resource planning and management purposes. It is suitable for general mapping, visualization and query. It is derived from the National Hydro Network (NHN) data. The geodatabase contains feature datasets for each of the 8 DFO detachments in Newfoundland and Labrador (Bay Roberts, Clarenville, Goose Bay, Marystown, Rocky Harbour, Springdale, Stephenville, Twillingate). Each of the feature datasets contain 4 feature classes that describe aspects of the salmon rivers within each detachment area. The RiverBasins feature class contains polygons outlining the extent of each of the salmon river watersheds that fall within that DFO detachment area. Polygons were delineated using provincial DEMs, National Hydro Network (NHN) river features, the DFO detachment area boundary, and tools contained in the ArcHydro toolset for ArcPro GIS software. The SalmonNetwork feature class contains lines which show the flow (undirected) of the river network through each of the salmon river watersheds that fall within that DFO detachment area. The flow is depicted by lines that run through rivers and streams and through waterbodies. The lines were imported from the National Hydro Network (Primary Directed Flow feature class) and then organized by salmon river watershed, to create a dataset with one line feature for each watershed. The SalmonRivers feature class contains lines which show salmon rivers within each of the salmon river watersheds that fall within that DFO detachment area. The lines were imported from the National Hydro Network (SLWater feature class) and then organized by salmon river watershed, to create a dataset with one line feature for each watershed. Only "single-line" rivers are included. Larger, "two-sided" rivers are depicted as polygons in the "Salmon Waterbodies" dataset. This SalmonWaterbodies feature class contains polygons which show salmon waterbodies within each of the salmon river watersheds that fall within that DFO detachment area. The polygons were imported from the National Hydro Network (Waterbody feature class) and then organized by salmon river watershed, to create a dataset with one polygon feature for each watershed. Larger, "two-sided" rivers are also depicted as polygons in the "Salmon Waterbodies" dataset. The geodatabase contains attribute information on the name, zone and class of each salmon river as reflected in the following documents: (i) Anglers' Guide - Scheduled Salmon Rivers of Newfoundland and Labrador and (ii) Conservation and Protection - Scheduled Salmon Rivers & DFO Detachment Regions Newfoundland and Labrador. It also provides links to online information on current in-season status

It has long been understood that 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 such as at Neguac Bay, in the province's northeast (47015’N, 65002’W).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 (https://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:Good Quality Eelgrass: relatively dense, clean, green blades with minimal epiphytes or algal growth. 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. 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].

The atlas provides printable maps, Web Services and downloadable data files representing seabirds at-sea densities in eastern Canada. The information provided on the open data web site can be used to identify areas where seabirds at sea are found in eastern Canada. However, low survey effort or high variation in some areas introduces uncertainty in the density estimates provided. The data and maps found on the open data web site should therefore be interpreted with an understanding of this uncertainty. Data were collected using ships of opportunity surveys and therefore spatial and seasonal coverage varies considerably. Densities are computed using distance sampling to adjust for variation in detection rates among observers and survey conditions. Depending on conditions, seabirds can be difficult to identify to species level. Therefore, densities at higher taxonomic levels are provided. more details in the document: Atlas_SeabirdsAtSea-OiseauxMarinsEnMer.pdf. By clicking on "View on Map" you will visualize a example of the density measured for all species combined from April to July - 2006-2020. ESRI REST or WMS map services can be added to your web maps or opened directly in your desktop mapping applications. These are alternatives to downloading and provide densities for all taxonomical groups and species as well as survey effort.