The Georgia Basin Boundary dataset displays the extent of the Georgia Basin Ecosystem Initiative undertaken by the federal, provincial, and municipal governments. The objectives of the project are to support initiatives for clean air, clean water, habitat and species protection, and improved environmental decision-making in the Georgia Basin. The dataset consists of both a polygon layer and line layer

The Georgia Basin Boundary dataset displays the extent of the Georgia Basin Ecosystem Initiative undertaken by the federal, provincial, and municipal governments. The objectives of the project are to support initiatives for clean air, clean water, habitat and species protection, and improved environmental decision-making in the Georgia Basin. The dataset consists of both a polygon layer and line layer

Snow survey administrative basin areas, which are components of the BC snow survey network. Basin codes are used as basis of snow survey station names, and for some reporting purposes.

This layer details Important Areas (IAs) relevant to sponge reefs (Hexactinosida) 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, fish, geographic features, invertebrates, 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.

Phytoplankton pigments, determined by high-performance liquid chromatography (HPLC) are measured seasonally along a 20-station transect in the Juan de Fuca / Strait of Georgia Basin. Sampling was initiated in 2004, discontinued in 2012 and restarted in 2015. In addition, occasional sampling is carried out at several locations and times in inland waters.For data inquiries please contact: Angelica Pena for data from 2004 to 2015 and Nina Nemcek for data from 2015 to present.

Zooplankton data collected during surveys conducted in the central and northern Strait of Georgia, 1996-2018.

In 1997, a magnitude 4.6 earthquake occurred 3 to 4 km beneath the Strait of Georgia, near Vancouver. This scenario visualizes the effects of that event if it occurred today with a magnitude of 5.0. A magnitude 7.0 Georgia Strait scenario is also provided, and represents a less likely but more consequential case for comparison.

In 1997, a magnitude 4.6 earthquake occurred 3 to 4 km beneath the Strait of Georgia, near Vancouver. This scenario visualizes the effects of that event if it occurred today with a magnitude of 4.9. A magnitude 7.0 Georgia Strait scenario is also provided, and represents a less likely but more consequential case for comparison.

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)

The Geological Atlas of the Western Canada Sedimentary Basin was designed primarily as a reference volume documenting the subsurface geology of the Western Canada Sedimentary Basin. This GIS dataset is one of a collection of shapefiles representing part of Chapter 9 of the Atlas, Middle Ordovician to Lower Devonian Strata of the Western Canada Sedimentary Basin, Figure 22, Ordovician-Silurian Subcrop/Outcrop Williston Basin. Shapefiles were produced from archived digital files created by the Alberta Geological Survey in the mid-1990s, and edited in 2005-06 to correct, attribute and consolidate the data into single files by feature type and by figure.