A Conservation Unit (CU) is a group of wild Pacific salmon sufficiently isolated from other groups that, if extirpated, is very unlikely to recolonize naturally within an acceptable timeframe, such as a human lifetime or a specified number of salmon generations. Holtby and Ciruna (2007) provided a framework for aggregating the five species of salmon (genus Oncorhynchus) found on Canada’s Pacific coast into species-specific CUs based on three primary characteristics: ecotypology, life history and genetics. The first stage in the description of the Conservation Units is based solely on ecology. The ecotypologies used in this framework include a combined characterization of both freshwater and near-shore marine environments, and is termed “joint adaptive zone”. The second stage of the description involves the use of life history, molecular genetics, and further ecological characterizations to group and partition the first stage units into the final Conservation Units. The result is CUs that are described through the joint application of all three axes. It is important to note that CUs are distinct from other aggregates of Pacific salmon, such as designatable units (DUs) under the Species at Risk Act or management units (MUs). CU Counting Sites: Salmon spawner enumeration data in the Pacific Region is stored and managed in the New Salmon Escapement Database (NuSEDS). The term “escapement” is used to refer to the group of mature salmon that have ‘escaped’ from various sources of exploitation, and returned to freshwater to spawn and reproduce. This data is assigned to a “Counting Site”, which may be a complete watercourse with a marine terminus, a tributary to a larger watercourse, or a defined reach within a watercourse that may or may not encompass the entire population but represents an index of the abundance of that population. CU Status: CUs form the basic unit for assessment under Canada’s Policy for the Conservation of Wild Salmon Policy (WSP) (DFO 2005). The biological status of a CU is evaluated using a number of metrics (Holt et al. 2009; Holt 2009), which indicate a WSP status zone: Red (poor status), Amber (marginal status), or Green (healthy status). A final step then incorporates all metric and status-related information into a final integrated status for each CU, along with expert commentary to support the final status determination (e.g., DFO 2012; DFO 2016). This information is used as inputs to fisheries management processes to help prioritize assessment activities and management actions. Note: CU boundaries were reviewed in 2020-2021 and have been updated from the BC Freshwater Atlas 1:50,000 scale to the BC Freshwater Atlas 1:20,000 scale. The CU boundaries were last updated in March 2023. Please be aware that CUs may be reviewed and are subject to change without notice. Please refer to Conservation Unit Review Requests-Form and Summary for a list of CU review requests that are ongoing or have been finalized.

Fisheries and Oceans Canada (DFO) has been conducting surface water trawl surveys since 1992 in the coastal waters of British Columbia, Washington, Oregon and Alaska and in the high seas of the Gulf of Alaska. These surveys initially focused on determining the migratory patterns (1992-2002) and on the growth and physiology (2003-2016) of juvenile Pacific Salmon. Data collected in shelf and slope waters at depths less than 400 meters off Washington and Oregon State are part of this larger survey series, but are limited to 1999-2001. These surveys focused on determining the migratory patterns of juvenile Pacific Salmon and had funding support from the Bonneville Power Administration as part of the 1995-2011 Canada-USA Salmon Shelf Survival Study. The intent of that study was to monitor and evaluate the effects of ocean conditions on the distribution, migration, growth, and survival of Pacific salmon during their first ocean year, and estimate the subsequent impacts on abundance of Chinook salmon adults returning to the Columbia River system.

This dataset provides 30-year, 50-year, and 100 year return levels for small craft harbours in British Columbia, relative to the mean sea level over 1993-2020. The return levels are derived from coastal sea levels for the period from 1993 to 2020, simulated using a high-resolution Northeast Pacific Ocean Model (NEPOM).

The Innu Audio Index is an extract from the Canadian Geographical Names Data Base (CGNDB) of geographical names with associated audio. The shared audio with the Geographical Names Board of Canada (GNBC) is the intellectual property of the Innu Nation. The points represent official geographical names in Innu-aimun, the language of the Innu Nation. The CGNDB is the authoritative national database of Canada's geographical names. It contains geographical names and their attributes that have been approved by the GNBC, the national coordinating body responsible for standards and policies on place names. The GNBC is working to increase awareness of existing Indigenous place names and help promote the revitalization of Indigenous cultures and languages. The GNBC does not warrant or guarantee that the information is accurate, complete or current at all times. For more information, to report data errors, or to suggest improvements, please contact the GNBC Secretariat at Natural Resources Canada with questions or for more information.

Location of bike paths in the City of Rimouski**This third party metadata element was translated using an automated translation tool (Amazon Translate).**

To slow the spread of the Brown spruce longhorn beetle to new areas, the Canadian Food Inspection Agency (CFIA) uses measures to control the movement of potentially infested materials. Slowing the spread of the Brown spruce longhorn beetle will protect Canada's environment and forest resources. It also helps keep international markets open to the forest industry and nurseries in non-regulated parts of Ontario and Quebec and in the rest of Canada.

Description: Seasonal temperature climatology of the Northeast Pacific Ocean was computed from historical observations including all available conductivity-temperature-depth (CTD), bottle, expendable bathy-thermograph (XBT), and Argo data in NOAA (http://www.argo.ucsd.edu/), Marine Environmental Data Service (MEDS), and Institute of Ocean Sciences archives over 1980 to 2010 period. Methods: Calculations, including smooth and interpolation, were carried out in sixty-five subregions and up to fifty-two vertical levels from surface to 5000m. Seasonal averages were computed as the median of yearly seasonal values. Spring months were defined as April to June, summer months were defined as July to September, fall months were defined as October to December, and winter months were defined as January to March. The data available here contain raster layers of seasonal temperature climatology for the Canadian Pacific Exclusive Economic Zone (EEZ), a subset of seasonal climatology of the Northeast Pacific Ocean, in high spatial resolution of 1/300 degree. References: Foreman, M. G. G., W. R. Crawford, J. Y. Cherniawsky, and J. Galbraith (2008). Dynamic ocean topography for the northeast Pacific and its continental margins, Geophys. Res. Lett., 35, L22606, doi: 10.1029/2008GL035152. Data Sources: NOAA, MEDS and IOS observational data Uncertainties: Uncertainties are introduced when quality controlled observational data are spatially interpolated to varying distances from the observation point. Climatological averages are calculated from these interpolated values.

Exo makes its data on schedules and planned routes available in the standardized *General Transit Feed Specification* (GTFS) format.**This third party metadata element was translated using an automated translation tool (Amazon Translate).**

As the COVID-19 pandemic spreads, researchers and health professionals have noted large differences in the impact that the infection has on individuals. Whereas some remain asymptomatic and unaware of their infection or experience only mild symptoms, others require hospitalization, ventilation, and may even die. As research evidence accumulates, both nationally and internationally, it appears that certain health characteristics, such as obesity or the presence of chronic conditions, increase the risk of severe outcomes among those who are infected with the novel coronavirus. To better understand which segments of the Canadian population may be vulnerable to severe health outcomes related to COVID-19, Statistics Canada and the Public Health Agency of Canada have worked collaboratively to build an index of underlying health conditions in the adult household population. Using information from the 2017/2018 Canadian Community Health Survey, new data tables released today estimate the proportion of the adult household population who may be at greater risk of severe health outcomes related to COVID-19 due to the presence of underlying health conditions.

The names of these rivers in the Bay of Fundy and Port Hawkesbury Area Response Plan (ARP) regions were obtained from Recovery Potential Assessments (see references), and cross referenced with the Atlas of Canada hosted online by Natural Resources Canada. These rivers were then identified and marked in ArcGIS using the Nova Scotia and New Brunswick Hydrographic Networks. Point features were used to represent the river mouths. For rivers large enough to be represented by polygon features, the point was placed where the polygon closed the inlet. For smaller rivers represented by a polyline, the point was placed where the line intersected the coastline. When multiple tributaries of a river were identified as salmon rivers, only the most seaward was marked. Cite this data as: Corrigan, S. Data of: Salmon Rivers Presence, Maritimes Region. Published: June 2019. Coastal Ecosystems Science Division, Fisheries and Oceans Canada, St. Andrews, N.B. https://open.canada.ca/data/en/dataset/ded53eaa-bb98-4476-beea-3138372c740b