La Financière Agricole's collective corn and grain crop insurance offers protection against losses in yield and quality assessed for the entire area where the insured units are located.**This third party metadata element was translated using an automated translation tool (Amazon Translate).**

This project was completed by the Coastal Environmental Baseline Program (Coastal and Freshwater Ecology Section) in the Newfoundland and Labrador Science Branch of Fisheries and Oceans Canada (DFO). From 2020-2023, there were semi-annual deployments and retrievals of 3 moored CTDs in the bay. From 2020 to November 2021, moored CTDs collected hourly recordings of conductivity, temperature and pressure. From 2021 through 2023, these CTDs collected year-round, hourly, information on temperature, conductivity, pressure, dissolved oxygen, and chlorophyll-a. Acoustic releases also collected hourly ambient noise (mV) data. This record contains the geographic locations of the sites, and information on the timings and types of data collected at each site.

La Financière Agricole's collective crop insurance for cereals and fodder maize covers the loss of quantity and quality. The assessment of losses is carried out collectively for all agricultural businesses in the same geographical area.**This third party metadata element was translated using an automated translation tool (Amazon Translate).**

This project was completed by the Coastal Environmental Baseline Program (Coastal and Freshwater Ecology Section) in the Newfoundland and Labrador Science Branch of Fisheries and Oceans Canada (DFO). From 2018 to 2022 baseline biological and physical data were collected in Placentia Bay using Atlantic Zone Monitoring Program (AZMP) and Cold Ocean Productivity Experiment (COPE) protocols. Complementary data were collected in the bay using moored CTDs. Where possible, sampling was conducted monthly at 4 sites between May and November to capture broad scale spatial and temporal trends. Additionally, data were collected bi-weekly in April and May, and monthly from June to September at one of these sites to capture finer scale temporal trends, such as spring blooms, in collaboration with Dr. C. McKenzie. Phytoplankton were collected using vertical net tows and niskins. Zooplankton were collected using vertical net tows. CTDs were used to collect physical and biogeochemical water column data including temperature, pressure, salinity, depth, chlorophyll-a, turbidity, dissolved oxygen, pH, photosynthetic active radiation (PAR), fluorescent dissolved organic matter (FDOM), and conductivity. Water biogeochemistry data were obtained by collecting water samples with niskins at depths of 5, 10, 20, 30, 40m, and 10m above bottom to measure nutrients, chlorophyll-a, carbonates, and particulate organic carbon and nitrogen (POC/PON). Additionally, eDNA samples were taken at each of the 4 sampling sites. This record contains the geographic locations of the sites, and information on the timing and type of data collected at each site.

Following the merger of the Duplessis and Manicouagan regions under the new name Côte-Nord, Quebec now has 21 tourist regions. The delimitation of regions is based on an unofficial division and is provided by Tourisme Québec. The boundaries were made using municipalities or MRCs.**This third party metadata element was translated using an automated translation tool (Amazon Translate).**

The Database of Declared Agricultural Parcels and Productions (BDPPAD) consists of polygons in vector format representing the outline of agricultural plots that have been associated with the files of clients of La Financière Agricole du Québec (FADQ) since 2003. The plots are kept from year to year to constitute a bank of plots covering as much territory as possible, whether the associated customer is active or not. For each insurance year, agricultural production is associated with the plots that active customers declare to cultivate.**This third party metadata element was translated using an automated translation tool (Amazon Translate).**

Many cetacean species were depleted in Canadian Pacific waters by commercial whaling, which ended in 1967. Although some populations have since shown evidence of recovery, there is limited information about the current abundance and geographic distribution of many species, particularly in difficult-to-survey offshore regions. This lack of baseline data hampers conservation status assessments, including estimating population-level impacts of anthropogenic activities. From July to early September 2018, we conducted ship-based surveys of cetaceans throughout the coastal and offshore waters of British Columbia. Density surface modelling (DSM) was used to produce spatially-explicit abundance estimates and distribution maps for four commonly-encountered cetacean species: the humpback whale (Megaptera novaeangliae), fin whale (Balaenoptera physalus), Dall’s porpoise (Phocoenoides dalli) and harbour porpoise (Phocoena phocoena). We estimated abundances of 7,030 (95% CI = 5,733-8,620) humpback whales, 2,893 (95% CI = 2,171-3,855) fin whales, 23,692 (95% CI = 19,121-29,356) Dall’s porpoises and 5,207 (95% CI = 2,769-9,793) harbour porpoises throughout Canadian Pacific waters. Our results complement design-based abundance estimates calculated from the same survey data, and can be compared with past habitat modelling studies and historical whaling catch data to estimate the extent of recovery of previously harvested populations. The return of these predators to habitats from which they were previously extirpated will have important ecosystem-level implications. The DSM results can contribute to calculations of Potential Biological Removal estimates to inform fisheries bycatch, as well as providing spatial data that can be used to assess the risk of entanglements, ship strikes, acoustic disturbance, and other anthropogenic threats. This dataset contains model-predicted densities of four commonly-encountered cetacean species (humpback whale, fin whale, Dall's porpoise and harbour porpoise) that were estimated using ship-based, visual survey data collected during the Pacific Region International Survey of Marine Megafauna (PRISMM) in July-August of 2018. Abundance of each species (where relevant) is provided for three gridded strata (25 km2 cell size) in the Pacific Region: one for the offshore, extending to Canada’s exclusive economic zone (EEZ), and two for coastal areas (the North Coast and the Salish Sea).

La Financière Agricole du Québec service centers and counters.**This third party metadata element was translated using an automated translation tool (Amazon Translate).**

This dataset is a contribution to the development of a kelp distribution vector dataset. Bull kelp (Nereocystis leutkeana) and giant kelp (Macrocystis pyrifera) are important canopy-forming kelp species found in marine nearshore habitats on the West coast of Canada. Often referred to as a foundation species, beds of kelp form structural underwater forests that offer habitat for fishes and invertebrates. Despite its far-ranging importance, kelp has experienced a decline in the west coast of North America. The losses have been in response to direct harvest, increase in herbivores through the removal of predators by fisheries or diseases, increase in water turbidity from shoreline development as well as sea temperature change, ocean acidification, and increased storm activates. Understanding these impacts and the level of resilience of different kelp populations requires spatiotemporal baselines of kelp distribution. The area covered by this dataset includes the BC coast and extends to portions of the Washington and Alaska coasts. This dataset was created using 137 British Admiralty (BA) charts, including insets, with scales ranging from 1:6,080 to 1:500,000, created between 1858 and 1956. All surveys were based on triangulation, in which a sextant or theodolite was used to determine latitude and angles, while a chronometer was used to help determine longitude. First, each BA chart was scanned by the Canadian Hydrographic Service (CHS) using the CHS Colortrac large format scanner, and saved as a Tagged Image Format at 200 DPI, which was deemed sufficient resolution to properly visualize all the features of interest. Subsequently, the scanned charts were imported into ESRI ArcMap and georeferenced directly to WGS84 using CHS georeferencing standards and principles (charts.gc.ca). In order to minimize error, a hierarchy of control points was used, ranging from high survey order control points to comparing conspicuous stable rock features apparent in satellite imagery. The georeferencing result was further validated against satellite imagery, CHS charts and fieldsheets, the CHS-Pacific High Water Line (charts.gc.ca), and adjacent and overlapping BA charts. Finally, the kelp features were digitized, and corresponding chart information (scale, chart number, title, survey start year, survey end year, and comments) was added as attributes to each feature. Given the observed differences in kelp feature representation at different scales, when digitizing kelp features, polygons were used to represent the discrete observations, and as such, they represent presence of kelp and not kelp area. Polygons were created by tracing around the kelp feature, aiming to keep the outline close to the stipe and blades. The accuracy of the location of the digitized kelp features was defined using a reliability criterion, which considers the location of the digitized kelp feature (polygon) in relation to the local depth in which the feature occurs. For this, we defined a depth threshold of 40 m to represent a low likelihood of kelp habitat in areas deeper than the threshold. An accuracy assessment of the digitized kelp features concluded that 99% of the kelp features occurred in expected areas within a depth of less than 40 m, and only about 1% of the features occurred completely outside of this depth.