Mapping of the odor constrained areas of wastewater treatment plants in the urban planning code (CDU) on the territory of Laval.**This third party metadata element was translated using an automated translation tool (Amazon Translate).**

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.

Fish Habitat Assessment Output: 5 of 16 High Water Level (75.4m ASL) - Juvenile/Adult Habitat - High Vegetation Association Species (All Thermal Guilds) Habitat suitability was assessed for the Bay of Quinte Area of Concern, at a 3 m grid resolution, using the Habitat Ecosystem Assessment Tool (HEAT), temperature algorithms, vegetation models, and water level input. Habitat classifications were based on three variables: depth (elevation), vegetation, and substrate; and modified by temperature suitabilities. The final suitability maps were based on documented habitat and temperature associations for the fish in the area. Different life stages (spawning requirements, nursery habitat, adult habitat) were modeled for the years of 1972-2011. Suitability values were scaled from 0 (not suitable) to 1 (highly suitable) and converted to suitability classes of very low, low, medium, and high. The final maps for each guild – life stage combination are maximum suitability values from the 39-year period modelled.

Community Energy and Emissions Inventory (CEEI) Supporting Indicators Total 2009 Reporting Year by Regional District

A shapefile of the Nova Scotia Automated Surface Water Quality Monitoring Network monitoring stations. The network was established in 2002 to assess near real-time water quality in surface waters across the province at five river stations and one lake station. The results are used to help manage water resources, determine baseline water quality in lakes and watercourses throughout the province, evaluate the impact of human activities on surface water, and assess long term trends in water quality. The following weblink connects to a Nova Scotia Department of Environment and Climate Change web map that includes the six monitoring station locations and an alternative method for downloading the same dataset: http://nse.maps.arcgis.com/apps/webappviewer/index.html?id=7ded7a30bef44f848e8a4fc8672c89bd

Sponge reefs are constructed by hexactinellid (glass) sponges of the Order Hexactinosida. The sponges trap fine sediments, and over centuries of sponge growth and sediment trapping, form large bioherms or reef mounds. Glass sponge reefs are unique habitats found along the Pacific coast of Canada and the United States and they have significant historic, ecological, and economic value. They link benthic and pelagic environments by playing important roles in filtration and carbon and nitrogen processing, and acting as silica sinks. They also form habitat for diverse communities of invertebrates and fish, including those of economic importance. Thus, accurate and up-to-date information on the location and spatial extent of sponge reefs is important to the management and conservation of many of Canada’s Pacific marine species. We generated a map of known sponge reefs, derived from two source shape files: 1) Sponge_Reef_West_Coast, mapped by Natural Resources Canada (NRCan), 2) Howesound_Nine_reef_polygons and 3) HoweSound_Five_reef_polygons, which were mapped by DFO and NRCan. The resultant polygon shapefile is published on the GIS hub as a file geodatabase feature class.

The project (Quoddy Region Pelagics Telemetry) will support the assessment of the effects of aquaculture on the distribution and abundance of pelagic fishes (salmon, mackerel, herring) and large predators (shark, marine mammals) in Passamaquoddy Bay and the Bay of Fundy, an area of intense finfish culture. An acoustic receivers network is placed yearly (from April to December) across various passageways, locations of project-specific interest, and at aquaculture sites in the region. Tagged pelagic species will be tracked through the network to provide information on migration routes, movement speed, survival rates and suspected predators, and determine interaction and residence at aquaculture sites. The network was utilized for monitoring the passage of: hatchery-reared wild salmon (n=340) released in the Magaguadavic River in 2018, 2019 and 2021, wild alewives (n=30) from the St. Croix River in 2021, and farmed Atlantic salmon released in the wild (n=99) in 2021. The receiver network has more recently supported adjacent projects on the use of the region by white shark and porbeagle as well as the residence of mackerel, herring, and sculpin at farm sites. The receivers additionally support other researchers with detection of striped bass, Inner Bay of Fundy Atlantic salmon, sturgeon, and many other species. Placement of the network will continue into 2025 inclusive with the longer-term goal to eventually deploy an array covering the entrance to the Bay of Fundy. Cite this data as: Trudel, M., Wilson, B., Black, M. 2023. Assessing bay-scale impacts of aquaculture operations on the distribution and abundance of pelagic fishes and large predators. Accessed via the Ocean Tracking Network OBIS IPT in January 2025 (version 3.1). https://doi.org/10.14286/xfa6sr

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".

Links the edge type codes used in the stream network layer with an English description used to categorize stream network features

High resolution forest change for Canada (Binary Change/No-change) The forest change data included in this product is national in scope (entire forested ecosystem) and represents the first wall-to-wall characterization of wildfire and harvest in Canada at a spatial resolution commensurate with human impacts. It is developed within the framework of Canada’s National Terrestrial Ecosystem Monitoring System (NTEMS). The information outcomes represent 25 years of stand replacing change in Canada’s forests, derived from a single, consistent spatially-explicit data source, derived in a fully automated manner. This demonstrated capacity to characterize forests at a resolution that captures human impacts is key to establishing a baseline for detailed monitoring of forested ecosystems from management and science perspectives. Time series of Landsat data were used to characterize national trends in stand replacing forest disturbances caused by wildfire and harvest for the period 1985–2010 for Canada's 650 million hectare forested ecosystems (https://authors.elsevier.com/sd/article/S0034425717301360 ). Landsat data has a 30m spatial resolution, so the change information is highly detailed and is commensurate with that of human impacts. These data represent annual stand replacing forest changes. The stand replacing disturbances types labeled are wildfire and harvest, with lower confidence wildfire and harvest, also shared. The distinction and sharing of lower class membership likelihoods is to indicate to users that some change events were more difficult to allocate to a change type, but are generally found to be in the correct category. For an overview on the data, image processing, and time series change detection methods applied, as well as information on independent accuracy assessment of the data, see Hermosilla et al. (2016; http://www.tandfonline.com/doi/full/10.1080/17538947.2016.1187673). The data available is, 1. a binary change/no-change; 2. Change year; and, 3. Change type. When using this data, please cite as: White, J.C., M.A. Wulder, T. Hermosilla, N.C. Coops, and G. Hobart. (2017). A nationwide annual characterization of 25 years of forest disturbance and recovery for Canada using Landsat time series. Remote Sensing of Environment. 192: 303-321. DOI: 10.1016/j.rse.2017.03.035. https://authors.elsevier.com/sd/article/S0034425717301360 Geographic extent: Canada's forested ecosystems (~ 650 Mha) Time period: 1985–2010