All island polygons. Islands may overlap as there are islands within islands (e.g., a lake on an island contains an island). GNIS_NAME_1 contains the most atomic name for the island. For example, there are 3797 "Haida Gwaii" islands. If the island has not been named as part of a more specific group or with an individual name, "Haida Gwaii" is the GNIS_NAME_1 value. GNIS_NAME_2 and GNIS_NAME_3 values are null. If the island has a more specific name, "Haida Gwaii" moves to GNIS_NAME_2, and the more atomic name, such as "Moresby Island" is the GNIS_NAME_1. If the island has an individual name, belongs to a group, and is part of Haida Gwaii, the same logic of naming from most to least specific applies. For example, GNIS_NAME_1 = "George Island", GNIS_NAME_2 = "Copper Islands", GNIS_NAME_3 = "Haida Gwaii".

This geospatial data depicts potential development areas (PDAs) recommended by the Committee for the Regional Assessment of Offshore Wind Development in Nova Scotia. The Committee for the Regional Assessment of Offshore Wind Development in Nova Scotia (Committee) provides federal and provincial Ministers with information, knowledge, and analysis regarding future offshore wind (OSW) development in Nova Scotia. Its work is intended to inform and improve future planning, licencing, permitting, and impact assessment processes. Under the Terms of Reference, the Committee submitted an interim report to Ministers on March 23, 2024. This report included the preliminary identification of recommended areas for potential future development areas (PFDAs) for offshore wind. Based on work completed since the interim report, the Committee issued its final report on January 23, 2025, which included refined development areas, the Potential Development Areas (PDAs). These PDAs are based on technical feasibility (using available information) and have the least impact on other offshore users. It should be noted that the PDAs are recommendations only and do not reflect official offshore wind energy areas.

The Agri-Environmental Spatial Data (AESD) product from the Census of Agriculture provides a large selection of farm-level variables from the Census of Agriculture and uses alternative data sources to improve the spatial distribution of the production activities. Therefore, the AESD database offers clients the possibility to better analyze the impact of agriculture activities on the environment and produce key indicators, or for any applications where accurate location of activities matters. Variables are offered using two types of physical boundaries: by Soil Landscape of Canada polygons and by Sub-sub-drainage areas (watersheds). The focus of the redistribution of the data is on the field crops and land use variables, but the database includes all census variables related to crops, livestock and management practices. This frame can also be used to extract Census of Agriculture data by custom geographic areas. Also, users interested in this version of the Census of Agriculture database using administrative types of regions can request it. In both cases, please contact Statistics Canada. This file was produced by Statistics Canada, Agriculture Division, Remote Sensing and Geospatial Analysis section, 2022, Ottawa.

The Standardized Precipitation Evapotranspiration Index (SPEI) is computed similarly to the SPI. The main difference is that SPI assesses precipitation variance, while SPEI also considers demand from evapotranspiration which is subtracted from any precipitation accumulation prior to assessment. Unlike the SPI, the SPEI captures the main impact of increased temperatures on water demand.

List of ZAP points deployed on the territory of Estrie**This third party metadata element was translated using an automated translation tool (Amazon Translate).**

Polygons delimiting the watershed group boundary, which is a collections of drainage areas. In-land groups will contain a single polygon, coastal groups may contain multiple polygons (one for each island)

Community Energy and Emissions Inventory (CEEI) Supporting Indicators Total 2006 Reporting Year by Regional District

List and geolocation of specialized training organizations in the arts supported by the Operational Assistance program of the Ministry of Culture and Communications in 2015-2016 (https://www.mcc.gouv.qc.ca/index.php?id=1645).**This third party metadata element was translated using an automated translation tool (Amazon Translate).**

Identification of significant concentrations of sponges in the Gulf of St. Lawrence biogeographic unit using Kernel density estimation (KDE). This method was applied to create a modelled biomass surface for each taxa and an aerial expansion method was permitted to identify significant concentrations. Only geo-referenced biomass data have been used to identify the “hot spots”. The borders of the areas were refined using knowledge of null catches and species distribution models. Predictive models were produced using a random forest machine-learning technique. For more details, please refer to this report: Kenchington, E., L. Beazley, C. Lirette, F.J. Murillo, J. Guijarro, V. Wareham, K. Gilkinson, M. Koen Alonso, H. Benoît, H. Bourdages, B. Sainte-Marie, M. Treble, and T. Siferd. 2016. Delineation of Coral and Sponge Significant Benthic Areas in Eastern Canada Using Kernel Density Analyses and Species Distribution Models. DFO Can. Sci. Advis. Sec. Res. Doc. 2016/093. vi + 178 p. http://waves-vagues.dfo-mpo.gc.ca/Library/40577806.pdf The present layer only contains the analysis results for sponges. Purpose: As part of the Canada's commitment to the identification and protection of sensitive benthic marine ecosystems, maps of the location of significant concentrations of corals and sponges on the east coast of Canada were produced through quantitative analyses of research vessel trawl survey data, supplemented with other data sources where available. The taxa analyzed are sponges (Porifera), large and small gorgonian corals (Alcyonacea), and sea pens (Pennatulacea). However, only the sponges (Porifera) and sea pens (Pennatulacea) have been considered in the analysis concerning the Gulf of St. Lawrence biogeographic unit.

Fishing event data (e.g. year, date, time, location, catch and effort) and associated biological data from the Offshore Stratified Random Survey component of the annual Sablefish Research and Assessment Survey on the British Columbia coast. Introduction DFO and the Canadian Sablefish Association (CSA) collaborate to undertake an annual fishery-independent research survey under a joint agreement. The survey employs longline trap gear to obtain catch rate data, gather biological samples, capture oceanographic measurements, and collect tag release and recapture data. Data summaries provided here are for the offshore stratified random sampling design (StRS) component of the survey, which has been conducted annually since 2003. The design of the sablefish survey has developed over time by incorporating and discontinuing components, including individual experimental studies (not available on OpenData). This StRS Survey component differs in methodology from the other two survey components: (1) Standardized trap survey – mainland inlets (1994-present; available on OpenData using link below), and (2) Standardized trap survey – offshore indexing and offshore tagging (1990 – 2010; not yet available on OpenData). The Sablefish offshore stratified random trap survey (StRS) follows a depth and area stratified random sampling design. The survey area is partitioned into five spatial strata (S1 to S5) and three depth strata (RD1 to RD3) for a total of 15 strata. The five spatial strata are S1 (South West Coast Vancouver Island or SWCVI), S2 (North West Coast Vancouver Island or NWCVI), S3 (Queen Charlotte Sound or QCS), S4 (South West Coast of Haida Gwaii or SWCHG), and S5 (North West Coast of Haida Gwaii or NWCHG). The three depth strata are 100-250 fathoms (RD1), 250-450 fathoms (RD2), and 450-750 fathoms (RD3). The area within each of the 15 strata are sectioned into 2 km x 2 km grid cells or ‘fishing blocks’ from which set locations are randomly chosen each year. Survey procedures are standardized and documented in Canadian Technical Reports of Fisheries and Aquatic sciences. Data tables provided for the offshore stratified random survey include (i) effort, (ii) catch, (iii) biological information, (iv) the sampling frame from which blocks are selected for sampling each year, and (v) the calculated coastwide Sablefish biomass index. StRS Effort This table contains information about the annual survey trips and fishing events (sets). Trip-level information includes the year the survey took place, a unique trip identifier, the vessel that conducted the survey and the trip start and end dates (the dates the vessel was away from the dock conducting the survey). Set-level information includes the date, time, location and depth that fishing took place, the survey spatial and depth strata for the set, reason for the set, soak time, number of traps deployed and number of traps fished. All successful fishing events are included, i.e., those sets that conformed to specified survey standards. StRS Catch This table contains the catch information from successful fishing events. Catches are identified to species or to the lowest taxonomic level possible. Catches are recorded as fish counts and / or weight. The unique trip identifier and set number are included so that catches can be related to the fishing event information (including capture location). StRS Biological Information This table contains the biological data for sampled catches. Data may include any or all of length, weight, sex, maturity, and age. Most of the sampled catch is Sablefish; however, some biological information has been collected on Rockfish, Flatfish and other Roundfish species in some years. Age structures are collected and are archived until required for analyses; therefore, all existing structures have not been aged at this time. Tissue samples (usually a fin clip) may be collected for genetic (DNA) analysis for specific species. Genetic samples may be archived until required for analyses; for more information, please see the data contacts. The unique trip identifier and set number are included so that samples can be related to the fishing event and catch information. Sample Frame This table contains a list of all of the 2km x 2km grid cells or ‘fishing blocks’ that are part of the stratified random sampling frame. A subset of blocks are randomly selected for sampling each year from this list. For each grid cell, the corresponding depth and spatial strata ID is included. This sample frame can be used to calculate design-based abundance indices for the survey. StRS Biomass Index This table contains a coastwide relative biomass index for Sablefish based on the annual StRS survey. Stratified random sampling mean index values and 95% confidence intervals are calculated by year using the classical survey stratified random sampling estimator (Cochran 1977) and the number of possible sampling units per stratum provided by Wyeth et al. (2007). The relative biomass index has been input to the operating model and management procedure used to provide management advice for BC Sablefish since 2011 (Cox et al. 2011).