Description:These commercial whale watching data are comprised of two datasets. First, the ‘whale_watching_trips_jun_sep_british_columbia’ data layer summarizes commercial whale watching trips that took place in 2019, 2020 and 2021 during the summer months (June to September). The second data layer, ‘wildlife_viewing_events_jun_sep_british_columbia’ contains estimated wildlife viewing events carried out by commercial whale watching vessels for the same years (2019, 2020 and 2021) and months (June to September). Commercial whale watching trips and wildlife viewing events are summarized using the same grid, and they can be related using the unique cell identifier field ‘cell_id’. The bulk of this work was carried out at University of Victoria and was funded by the Marine Environmental Observation, Prediction and Response (MEOPAR) Network under the ‘Whale watching AIS Vessel movement Evaluation’ or WAVE project (2018 – 2022). The aim of the WAVE project was to increase the understanding of whale watching activities in Canada’s Pacific region using vessel traffic data derived from AIS (Automatic Identification System). The work was finalized by DFO Science in the Pacific Region. These spatial data products of commercial whale watching operations can be used to inform Marine Spatial Planning, conservation planning activities, and threat assessments involving vessel activities in British Columbia.Methods:A list of commercial whale watching vessels based in British Columbia and Washington State and their corresponding MMSIs (Maritime Mobile Service Identity) was compiled from the whale watching companies and Marine Traffic (www.marinetraffic.com). This list was used to query cleaned CCG AIS data to extract AIS positions corresponding to commercial whale watching vessels. A commercial whale watching trip was defined as a set of consecutive AIS points belonging to the same vessel departing and ending in one of the previously identified whale watching home ports. A classification model (unsupervised Hidden Markov Model) using vessel speed as the main variable was developed to classify AIS vessel positions into wildlife-viewing and non wildlife viewing events. Commercial whale watching trips in the south and north-east of Vancouver Island were limited to a duration of minimum 1 hour and maximum 3.5 hours. For trips in the west coast of Vancouver island the maximum duration was set to 6 hours. Wildlife-viewing events duration was set to minimum of 10 minutes to a maximum of 1 hour duration. For more information on methodology, consult metadata pdf available with the Open Data record.References:Nesdoly, A. 2021. Modelling marine vessels engaged in wildlife-viewing behaviour using Automatic Identification Systems (AIS). Available from: https://dspace.library.uvic.ca/handle/1828/13300.Data Sources:Oceans Network Canada (ONC) provided encoded AIS data for years 2019, 2020 and 2021, within a bounding box including Vancouver Island and Puget Sound used to generate these products. This AIS data was in turn provided by the Canadian Coast Guard (CCG) via a licensing agreement between the CCG and ONC for the non-commercial use of CCG AIS Data. More information here: https://www.oceannetworks.ca/science/community-based-monitoring/marine-domain-awareness-program/ Molly Fraser provided marine mammal sightings data collected on board a whale watching vessels to develop wildlife-viewing events classification models. More information about this dataset here: https://www.sciencedirect.com/science/article/pii/S0308597X20306709?via%3DihubUncertainties:The main source of uncertainty is with the conversion of AIS point locations into track segments, specifically when the distance between positions is large (e.g., greater than 1000 meters).

This record contains two datasets: 1. Raw unfiltered geographic coordinates and accuracy estimates of ringed seals tagged in the Western Canadian Arctic and 2. The location estimate from state-space models using a 12-hr time step. In total, 17 ringed seals were captured, measured, weighed, and tagged with satellite-linked transmitters (SDR-10, SDR-16, SPLASH) in June and July of 1999, 2000, and 2010. The tags, manufactured by Wildlife Computers Ltd. (Redmond, Washington, USA), sent data to polar orbiting satellites. Data were then retrieved via the Argos system (Harris et al., 1990). Tags collected and relayed information on movement (geographic positions) and diving data of the instrumented animals.

Glaciers and ice masses for the province, derived from aerial imagery flown in the late 1980s and early 1990s. Please refer to the [Glaciers](https://catalogue.data.gov.bc.ca/dataset/glaciers) dataset for recent glacier extents in British Columbia, and [Historical Glaciers](https://catalogue.data.gov.bc.ca/dataset/historical-glaciers) for a comparable historic view.

The Drainage Areas dataset is largely based on the Water Survey of Canada (WSC) drainage area boundaries at the sub-sub-basin level. The data model supports the derivation, from the Fundamental Drainage Areas dataset (sub-sub-basin level), of the WSC and Atlas of Canada drainage area hierarchies and the data is available in all three schemes. Drainage area definitions for both WSC and Atlas of Canada boundaries were reviewed resulting in some modifications. Larger scale reference data sources were used for further manual boundary adjustments. This dataset has been integrated with other National Scale Frameworks hydrology datasets and is considered a component of the Hydrology Theme (see Supplemental Information for more details about the Atlas of Canada National Frameworks data at the 1:1,000,000 scale).The Atlas Frameworks are a set of integrated base map layers which form part of a larger National-Scale Frameworks data collection. These data have been compiled at a scale of 1:1 000 000 with the primary goal being to indicate correct relative positioning with other framework layers rather than absolute positional accuracy.Distributed 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@yukon.ca](mailto:geomatics.help@yukon.ca)

Basic biological data for all fish caught during the 2012 BSMFP expedition. Includes identification, weight, length (total, fork, and, standard), liver weight, gonad weight, sex and maturity level.

Modeled data showing the likely distribution of Killer Whales. CRIMS is a legacy dataset of BC coastal resource data that was acquired in a systematic and synoptic manner from 1979 and was intermittently updated throughout the years. Resource information was collected in nine study areas using a peer-reviewed provincial Resource Information Standards Committee consisting of DFO Fishery Officers, First Nations, and other subject matter experts. There are currently no plans to update this legacy data.

This layer details Important Areas (IAs) relevant to key invertebrate species (which are not corals or sponges) in the Strait of Georgia (SOG) ecoregion. This data was mapped to inform the selection of marine Ecologically and Biologically Significant Areas (EBSA). Experts have indicated that these areas are relevant based upon their high ranking in one or more of three criteria (Uniqueness, Aggregation, and Fitness Consequences). The distribution of IAs within ecoregions is used in the designation of EBSAs.Canada’s Oceans Act provides the legislative framework for an integrated ecosystem approach to management in Canadian oceans, particularly in areas considered ecologically or biologically significant. DFO has developed general guidance for the identification of ecologically or biologically significant areas. The criteria for defining such areas include uniqueness, aggregation, fitness consequences, resilience, and naturalness. This science advisory process identifies proposed EBSAs in Canadian Pacific marine waters, specifically in the Strait of Georgia (SOG), along the west coast of Vancouver Island (WCVI, southern shelf ecoregion), and in the Pacific North Coast Integrated Management Area (PNCIMA, northern shelf ecoregion).Initial assessment of IA's in PNCIMA was carried out in September 2004 to March 2005 with spatial data collection coordinated by Cathryn Clarke. Subsequent efforts in WCVI and SOG were conducted in 2009, and may have used different scientific advisors, temporal extents, data, and assessment methods. WCVI and SOG IA assessment in some cases revisits data collected for PNCIMA, but should be treated as a separate effort.Other datasets in this series detail IAs for birds, cetaceans, coral and sponges, fish, geographic features, and other vertebrates.Though data collection is considered complete, the emergence of significant new data may merit revisiting of IA's on a case by case basis.

The hydrographic features of the CanVec series include watercourses, water linear flow segments, hydrographic obstacles (falls, rapids, etc.), waterbodies (lakes, watercourses, etc.), permanent snow and ice features, water wells and springs.The Hydrographic features theme provides quality vector geospatial data (current, accurate, and consistent) of Canadian hydrographic phenomena. It aims to offer a geometric description and a set of basic attributes on hydrographic features that comply with international geomatics standards, seamlessly across Canada.The CanVec multiscale series is available as prepackaged downloadable files and by user-defined extent via a Geospatial data extraction tool.Related Products (Open Maps Links):[Topographic Data of Canada - CanVec Series](https://open.canada.ca/data/en/dataset/8ba2aa2a-7bb9-4448-b4d7-f164409fe056)

A hydrogeological unit is defined as any soil or rock unit or zone that by virtue of its hydraulic properties has a distinct influence on the storage or movement of groundwater. It is considered the main dataset from the GGP point of view. Hydrogeological units are ranked into five levels (from largest to smallest): 1) hydrogeological region, 2) hydrogeological context, 3) aquifer system, 4) hydrostratigraphic unit, and 5) aquifer. Here are formal definitions for these different types of hydrogeologic units. - Hydrogeological region Hydrogeological regions are areas in which the properties of sub-surface water, or groundwater, are broadly similar in geology, climate and topography. There are 9 such regions identified in Canada (ref?). - Hydrogeological context Hydrogeological contexts are units of reporting, conceptually narrower than regions, and are additionally delineated by physiographic and hydrogeological aspects. - Aquifer system ""A heterogeneous body of intercalated permeable and poorly permeable material that functions regionally as a water-yielding hydraulic unit; it comprises two or more permeable beds [aquifers] separated at least locally by aquitards [confining units] that impede groundwater movement but do not greatly affect the regional hydraulic continuity of the system"" (Poland et al., 1972). - Hydrostratigraphic unit (HSU) ""Body of sediment and/or rock characterized by ground water flow that can be demonstrated to be distinct under both unstressed (natural) and stressed (pumping) conditions, and is distinguishable from flow in other HSUs"" (Noyes et al.) - Aquifer ""A formation, group of formations, or part of a formation that contains sufficient saturated permeable material to yield significant quantities of water to wells and springs"" (Lohman et al, 1972, p. 21). The rank attribute is used to specify the scope of the described unit. The general principle behind this specification is to allow the same data structure to apply to various types of hydrogeological units, from the local aquifer to the almost continental hydrogeological region. The dataset includes properties such as identification, physiography, geology, aquifer description and properties, water balance, groundwater use and risk. It features numerical values or a general description when no values are available. The description can also be used to add context to the numerical values. For each property, metadata identifying the source of the original data, links to similar data in GIN, and description of the processes, algorithms or methodology used to obtain these datasets will be available to complement the data. This dataset is designed to capture and represent a set of synthesized information pertaining to hydrogeological units through maps and succinct table reports. Some attributes (or properties) of the dataset are irrelevant depending of the rank of the unit. In general, this dataset is organised to include multiple properties associated with aquifers and larger hydrogeologic units. These properties are grouped into categories, which include identification, physiography, geology, aquifer description, water balance, groundwater use and risk. The numerical values associated with each of the properties can be used to create thematic maps; hence, the importance of using standardized units of measurement and definitions for these properties. When numerical values are not available, a general description may be supplied instead. The description can also be used to add context to the numerical values. Because this dataset is the cornerstone of the national view on groundwater, supplemental contextual information (metadata) must be part of the data. Thus, for each property, metadata identifying the source of the original data, links to similar data in GIN, and a description of the processes, algorithms or methodology used to obtain these datasets will be available to complement the data.

Historical finds of Coleophora serratella