COURDO SPÉCIAL program sampling points, watercourse quality, Aquatic environment monitoring network.**This third party metadata element was translated using an automated translation tool (Amazon Translate).**

RUISSO program sampling points, stream water quality, Aquatic environment monitoring network.**This third party metadata element was translated using an automated translation tool (Amazon Translate).**

SAMPLING POINTS FOR THE QUALO program, shoreline water quality of the aquatic environment monitoring network.**This third party metadata element was translated using an automated translation tool (Amazon Translate).**

Flow network arcs (observed, inferred and constructed). Contains no banks, coast or watershed bourdary arcs. Directionalized and connected. Contains heirarchial key and route identifier

Data from the QUALO program, shoreline water quality from the Aquatic Environment Monitoring Network.An [interactive map] (https://experience.arcgis.com/experience/38d7c7bb43da4e2082aa836689d0d318/) is also available.**This third party metadata element was translated using an automated translation tool (Amazon Translate).**

PURPOSE:This study is part of a two-decade series of research aimed to provide a comprehensive synthesis of the effects of harvest and environmental change on fisheries in Great Bear Lake. The main objectives are to assess demographic traits and the current status of harvested species, with a focus on evaluating sustainable harvest levels of lake trout, a cold-adapted species with a relatively narrow thermal niche. As part of this research, trends in water quality and primary productivity are monitored to evaluate potential effects of change on fisheries. DESCRIPTION:Great Bear Lake, one of the largest lakes in North America, contains culturally and recreationally important fish species. Great Bear Lake is located in the sub-Arctic and Arctic Circle. As part of a two-decade series of research aimed to provide a comprehensive synthesis of the effects of harvest and environmental change on fisheries in Great Bear Lake, the main objectives of this study are to assess demographic traits and the current status of harvested species, with a focus on evaluating sustainable harvest levels of lake trout, a cold-adapted species with a relatively narrow thermal niche. As part of this research, trends in water quality and primary productivity are monitored to evaluate potential effects of change on fisheries. From 2021 to 2024, surface water temperature data was collected at depths of 0.1 to 1.0 meters using an RBR Maestro3 through partnered community-led and community/Fisheries and Oceans Canada/university partner collaborative sampling. The project has strong community involvement, including youth through the Guardian Program, to facilitate capacity building and community leadership in the long-term monitoring of Great Bear Lake fisheries and the aquatic ecosystem. This data is an extension of baseline data sets on water quality on the lake. These data will contribute to a better understanding cumulative impacts of climate change on the functioning of large northern lake ecosystems and provide a benchmark for monitoring further change. This data will be important for developing effective strategies for maintaining community-led aquatic monitoring and managing natural resources, particularly fish, which are expected to be increasingly important to communities with declines in other country foods such as caribou.We acknowledge the data were collected in the Sahtú Settlement Area and are made publicly available with the agreement of the Délı̨nę Renewable Resources Council (Délı̨nę Ɂehdzo Got’ı̨nę (Renewable Resources Council)). Collaborators include: the Community of Délı̨nę partners (data collection), Délı̨nę Renewable Resource Council, Sahtú Renewable Resource Board, and University of Manitoba. Community of Délı̨nę partners and field workers that participated in data collection include Chris Yukon, Archie Vital, Ted Mackienzo, Daniel Baton, Lloyd Baton, Simon Neyelle, and Stanley Ferdanan.Funding and logistical support was provided by: Northwest Territories Cumulative Impact Monitoring, Sahtú Renewable Resource Board, the Polar Continental Shelf Program and Fisheries and Oceans Canada.

The Adaptive Management Framework for Yukon placer mining is complemented by traditional knowledge and monitoring of water quality objectives, aquatic health, and economic health. The aquatic health monitoring program is governed by the Aquatic Health Monitoring Protocol. The Protocol describes the locations, timing, frequency and methods employed during sampling, as well as the methods used to analyze sampling data. The Reference Condition Approach (RCA) is the method chosen for assessing the health of freshwater ecosystems in the Yukon. One RCA model was developed for bioassessment based upon benthic macroinvertebrates, and a second model was developed to assess the diversity of fish species. The RCA model for invertebrates relies upon 224 reference sites collected over the period 2004 to 2010 by the University of Western Ontario, Fisheries and Oceans Canada, and Yukon G overnment, using the same standard protocol. The invertebrate data set was analyzed at the family level. There are two fundamental steps in the process of developing the predictive model. The first is to classify the reference sites based on their biological characteristics. This requires defining a number of community types based on the taxonomic composition. The second step is to determine a subset of habitat attributes that are associated with those community types. Following this step the number and type of organisms expected to occur at any given site can be determined from habitat attributes. For more information, contact the Yukon Placer Secretariat.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 Canadian Aquatic Biomonitoring Network (CABIN) is an aquatic biomonitoring program for assessing the health of fresh water ecosystems in Canada. Benthic macroinvertebrates are collected at a site location and their counts are used as an indicator of the health of that water body. CABIN is based on the network of networks approach that promotes inter-agency collaboration and data-sharing to achieve consistent and comparable reporting on fresh water quality and aquatic ecosystem conditions in Canada. The program is maintained by Environment and Climate Change Canada (ECCC) to support the collection, assessment, reporting and distribution of biological monitoring information. A set of nationally standardized CABIN protocols are used for field collection, laboratory work, and analysis of biological monitoring data. A training program is available to certify participants in the standard protocols. There are two types of sites in the CABIN database (reference and test). Reference sites represent habitats that are closest to “natural” before any human impact. The data from reference sites are used to create reference models that CABIN partners use to evaluate their test sites in an approach known as the Reference Condition Approach (RCA). Using the RCA models, CABIN partners match their test sites to groups of reference sites on similar habitats and compare the observed macroinvertebrate communities. The extent of the differences between the test site communities and the reference site communities allows CABIN partners to estimate the severity of the impacts at those locations. CABIN samples have been collected since 1987 and are organized in the database by study (partner project). The data is delineated by the 11 major drainage areas (MDA) found in Canada and each one has a corresponding study, habitat and benthic invertebrate data file. Links to auxiliary water quality data are provided when available. Visits may be conducted at the same location over time with repeat site visits being identified by identical study name / site code with different dates. All data collected by the federal government is available on Open Data and more partners are adding their data continually. The csv files are updated monthly. Contact the CABIN study authority to request permission to access non open data.

This shapefile dataset was designed using polygons extracted from the Cartography of Coastal Ecosystems of Maritime Quebec geodatabase (2022, Laboratory for Dynamics and Integrated Management of Coastal Zones, Fisheries and Oceans Canada), described in the paragraph below. It consists of polygons with eelgrass and incorporates attributes describing the vegetation cover, the composition of the seagrass beds, the associated ecosystem name, the imagery data that allowed photo-interpretation and the presence or absence of field data. A unique sequence number associated with each polygon makes it possible to trace the paired polygon of the geodatabase of coastal ecosystems to attribute values not detailed in this shapefile. The study area includes all of the estuarine and maritime coasts of Quebec, with the exception of certain sectors, including most of the Lower North Shore and Anticosti Island, with the exception of villages of Kegaska, la Romaine, Chevery, Blanc-Sablon and Port-Menier. Some islands off the estuary and gulf coasts are part of the region covered, such as Île d'Orléans, Isle-aux-Coudres, Île Verte and Île Bonaventure.The Mapping of Coastal Ecosystems of Maritime Quebec was carried out jointly by the Laboratory for Dynamics and Integrated Coastal Zone Management (LDGIZC) of the University of Quebec at Rimouski as part of the Coastal Resilience Project; and by the Fisheries and Oceans Canada team, as part of the Integrated Marine Response Planning Program (IMRP). A classification of coastal ecosystems was carried out on more than 4,200 km of coastal corridor, focusing on estuarine and maritime coasts of Quebec located between the limit of the upper foreshore and the shallow infralittoral (about 10m deep). The mapping method developed is based on semi-automated segmentation and a photo-interpretation of coastal ecosystems, using very high resolution multispectral photographs (RBVI) acquired between 2015 and 2020 by DFO. The classification of polygons is based on the assignment of predefined value classes for the biological and physical attributes under study (e.g., substrates, plant type, vegetation cover, geosystem, etc. ). Helicopter-born oblique photographs and field data helped to reduce the uncertainty associated with photo-interpretation. UQAR and DFO conducted field sampling campaigns targeting the mediolittoral (4,390 stations) and the lower mediolittoral and infralittoral zones (2,959 stations), respectively , which validated some of the attributes identified by photo-interpretation and provided detailed information on community structure . The geodatabase of the Mapping of coastal ecosystems is hosted and managed by UQAR on their SIGEC-Web cartographic platform: https://ldgizc.uqar.ca/Web/sigecwebCredits © DFO (2023, Fisheries and Oceans Canada)Provencher-Nolet, L., Paquette, L., Pitre, L.D., Grégoire, B. and Desjardins, C. 2024. Cartographie des macrophytes estuariens et marins du Québec. Rapp. Tech. Can. Sci. halieut. Aquat. 3617 : v + 99 p.Grégoire, B., Pitre, L.D., Provencher-Nolet, L., Paquette, L. and Desjardins, C. 2024. Distribution d’organismes marins de la zone côtière peu profonde du Québec recensés par imagerie sous-marine de 2017 à 2021. Rapp. tech. can. sci. halieut. aquat. 3616 : v + 78 p.Grégoire, B. 2022. Biodiversité du relevé côtier Planification pour une intervention environnementale intégrée dans l’estuaire et le golfe du Saint-Laurent (2017–2021). Observatoire global du Saint-Laurent. [Jeu de données]Jobin, A., Marquis, G., Provencher-Nolet, L., Gabaj Castrillo. M. J., Trubiano C., Drouet, M., Eustache-Létourneau, D., Drejza, S. Fraser, C. Marie, G. et P. Bernatchez (2021) Cartographie des écosystèmes côtiers du Québec maritime — Rapport méthodologique. Chaire de recherche en géoscience côtière, Laboratoire de dynamique et de gestion intégrée des zones côtières, Université du Québec à Rimouski. Rapport remis au ministère de l’Environnement et de la Lutte contre les changements climatiques, septembre 2021, 98 p.

The Department of Fisheries and Oceans (DFO) Science Branch has designed a multispecies dive survey protocol to provide unbiased, coast wide monitoring of benthic invertebrate stocks (as may be required under the updated Fisheries Act) and associated habitat information for a suite of benthic marine invertebrate species (Green (Strongylocentrotus droebachiensis), Purple (S. purpuratus) and Red Sea Urchin (Mesocentrotus franciscanus), Geoduck (Panopea generosa), Giant Red Sea Cucumber (Apostichopus californicus), Northern Abalone (Haliotis kamtschatkana), and Sunflower Sea Star (Pycnopodia helianthoides)). Based on information available at this time, the proposed survey design can provide estimates of coast wide stock status for Red Sea Urchin and Giant Red Sea Cucumber, and relative abundance indices for Geoduck, Green Sea Urchin, Purple Sea Urchin, Northern Abalone and Sunflower Sea Star.The new protocol was tested through a series of pilot surveys conducted on a subset of areas of the BC coast each September from 2016-2021. Design of the pilot surveys was based on previous dive survey data and experience and demonstrated the practical feasibility of the protocol, while also gathering preliminary information to guide recommendations about the statistical design of the survey.The dataset consists of a relational database containing tables representing each component of the survey methodology. The primary component of the survey is a transect location. Along each transect, systematically spaced quadrats are sampled, and on each quadrat, substrate observations are recorded, multiple species of algae are recorded, and multiple individual invertebrates are measured or counted. The tables are linked by transect number and quadrat number.