The Resource Management Area (RMA) dataset is comprised of all the polygons that represent the resource management areas of the 17 Integrated Resource Plans (IRP) - Subregional in Alberta. This dataset does not include the RMAs of Local IPR plans due to the resource restraint. Future enhancement of this data set to include Local IRP plans is feasible when resources are available. A Resource Management Area is an area identified within a Sub-Regional IRP plan for more detailed land and resource management intent on a landscape assessment. Generally, a Resource Management Area is characterized by an intent statement and detailed resource management objectives and guidelines. However, there are IRP plans which have their own specific RMA definitions. Plans include, Lakeland Sub-Regional IRP: A RMA is a geographic area of common resource management intent. There is a management intent statement for each resource management area. The intent statement expresses the resource priorities for the area. Kananaskis Country Sub-Regional IRP: RMA areas identify broad units of land within the planning area which have distinct management intents and specific management objectives.

The Integrated Resource Plan - Subregional dataset is comprised of all the polygons that represent the Sub-Regional Integrated Resource Plans (IRP) in Alberta. All the Sub-Regional IRPs were completed under the Integrated Resource Planning Program, from 1976 to approximately 1995. These plans were endorsed by the Government of Alberta with most being approved by Cabinet. The Sub-Regional Plans describe land-use zonation and objectives within individual defined planning areas, to ensure overall consistency with Regional goals and objectives. An Integrated Resource Plan (IRP) is a plan which identifies the values and associated land and resource management goals for the planning area in consideration of the maintenance of social, economic, and ecological values. An IRP provides direction regarding the type of land and resource management activity that would facilitate meeting the stated objectives in the planning area (for example: recreation, grazing, industrial and commercial activities). The public was often involved in contributing input to the development of an IRP. Majority of IRP plans were endorsed by the Government of Alberta in various periods.

The Integrated Resource Plan - Local dataset is comprised of all the polygons that represent the Local Integrated Resource Plans (IRP) in Alberta. A Local IRP provides land resource management direction for a relatively smaller geographic planning area. A Local Plan is developed to provide more detailed land and resource use parameters than may be available in a Sub-Regional Plan. An IRP is a plan which identifies the values and associated land and resource management goals for the planning area in consideration of the maintenance of social, economic, and ecological values. An IRP provides direction regarding the type of land and resource management activity that would facilitate meeting the stated objectives in the planning area (e.g. recreation, grazing, industrial and commercial activities). The public was often involved in contributing input to the development of an IRP. IRPs were endorsed by the Government of Alberta in various periods.

The Eastern Slopes Land Use Zoning dataset is comprised of all the polygons that represent Eastern Slopes Land Use Zones in Alberta. The dataset was created as a basis to provide analysis for nominating Special Places sites for later designation, under the Special Places 2000 Project. Don Getty Wildland Provincial Park (which comprised mainly of Zone 1 - Prime Protection & Zone 2 - Critical Wildlife) is one of the examples. Except designated natural areas. zoning and any associated policy direction for managing resources and surface access on the general Crown lands within these land use zones do not apply to lands that have been designated as a park or protected area under the Provincial Parks Act, the Willmore Wilderness Park Act or the Wilderness Areas, Ecological Reserves, Natural Areas and Heritage Rangelands Act. This dataset was compiled from many Integrated Resource Plans (IRP) studies as well as the Eastern Slopes Policy which were used in the former Special Places 2000 Project planning process.

Species characterization by environmental DNA (eDNA) is a method that allows the use of DNA released into the environment by organisms from various sources (secretions, faeces, gametes, tissues, etc.). It is a complementary tool to standard sampling methods for the identification of biodiversity. This project provides a list of fish and marine mammal species whose DNA has been detected in water samples collected between 2019 and 2021 using the mitochondrial marker MiFish (12S).The surveys were carried out in the summer of 2019 (July 14-18) and (July 30 - August 5), in the fall of 2020 (October 27-28) and in the summer-fall of 2021 (May 31 - June 3 ) and (August 24-25) between Forestville and Godbout (Haute-Côte-Nord). Sampling was carried out between 1-50 meters depth in 91 stations, with 1 to 3 replicates per station. Two liters of water were filtered through a 1.2 µm fiberglass filter. DNA extractions were performed with the DNeasy Blood and Tissues or PowerWater extraction kit (Qiagen). Negative field, extraction and PCR controls were added at the different stages of the protocol. The libraries were prepared either by Génome Québec (2019, 2020) or by the Genomics Laboratory of the Maurice-Lamontagne Institute (2021), then sequenced on a NovaSeq 4000 PE250 system by Génome Québec. The bioinformatics analysis of the sequences obtained was carried out using an analysis pipeline developed in the genomics laboratory. A first step made it possible to obtain a table of molecular operational taxonomic units (MOTU) using the cutadapt software for the removal of the adapters and the R package DADA2 for the filtration, the fusion, removal of chimeras and compilation of data. The MOTUs table was then corrected using the R package metabaR to eliminate the tag-jumping and take contaminants into consideration. Samples showing a strong presence of contaminating MOTUs were removed from the dataset. The MOTUs were also filtered to remove all remaining adapter sequences and also retain only those of the expected size (around 170 bp). Finally, taxonomic assignments were made on the MOTUs using the BLAST+ program and the NCBI-nt database. Taxonomic levels (species, genus or family) were assigned using a best match method (Top hit), with a threshold of 95%. Only assignments at the level of fish and marine mammals were considered, and the taxa detected were compared to a list of regional species, and corrected if necessary. The species detections of the different replicas have been combined.The file provided includes generic activity information, including site, station name, date, marker type, assignment types used for taxa identification, and a list of taxa or species. The list of taxa has been verified by a biodiversity expert from the Maurice-Lamontagne Institute.This project was funded by Fisheries and Oceans Canada's Coastal Environmental Baseline Data Program under the Oceans Protection Plan. This initiative aims to acquire baseline environmental data that contributes to the characterization of significant coastal areas and supports evidence-based assessments and management decisions to preserve marine ecosystems.Data were also published on SLGO platform : https://doi.org/10.26071/ogsl-2239bca5-c24a

We evaluated an autonomous environmental DNA sampler produced by Dartmouth Ocean Technologies Inc (Dartmouth, Canada) compared to time-at-sample filtration in the laboratory to determine the performance of moored samplers for monitoring in the marine world. We deployed three autonomous samplers from DOT in the Bedford Basin (Canada) over a nine-week period in summer/fall 2023. The samplers filtered seawater in situ at programmed interviews over this time period, and we collected contemporaneous samples with a standard vacuum pump during each sampling period. Both eDNA sample types captured similar fish diversity, including typical diversity for the Northwest Atlantic. The invertebrate community detected using the COI marker was different between each sample type, likely due to differences in filter pore size. We found biofouling on the moored samplers was minimal over the study period, even in a high-traffic area such as the Bedford Basin, likely due to the relatively short experimental period, and copper screening covering in the inlet and outlet valves of the instruments. Overall, our results show promise to deploy autonomous eDNA samplers in marine conservation areas to contribute to monitoring in the temperate ocean, but further testing over longer periods of time is needed to determine if DNA remains well-preserved in the autonomous samplers at ambient ocean temperatures.Cite this data as: Jeffery, N.W., Van Wyngaarden, M., and Stanley, R.R.E. Evaluating an Autonomous eDNA Sampler for Marine Environmental Monitoring: Short- and Long-Term Applications. Published: December 2024. Coastal Ecosystems Science Division, Maritimes Region, Fisheries and Oceans Canada, Dartmouth NS.

The Automatic Identification System (AIS) is a global, satellite-based and terrestrial-based ship tracking system that uses shipborne equipment to remotely track vessel identification and positional information and is typically required on vessels of 300 gross tonnage or more on an international voyage, of 500 gross tonnage or more not on an international voyage, and passenger ships of all sizes. AIS tracking technologies are primarily used in support of real-time maritime domain awareness and for maritime security and safety of life at sea. This report describes a geographic information system (GIS) analysis of 2019 AIS data to produce yearly and monthly vessel density maps of all vessel classes combined and yearly density maps of each vessel class. The year 2019 was selected to portray shipping densities in a pre-COVID 19 pandemic depiction of the maritime transport sector in the Northwest Atlantic. Vessel density map applications include use in spatial analysis and decision support for marine spatial planning. In 2023 the process was applied to the years 2013 through to 2022 and were made available using the same processes that were applied to the original 2019 datasets.

The Regional Ice Ocean Prediction System (RIOPS) provides ice and ocean forecasts up to 84 hours, four times per day on a 1/12° resolution grid (3-8 km). RIOPS is initialized using analyses from the Global Ice-Ocean Prediction System (GIOPS). Atmospheric fluxes up to 84 hours forecasts are calculated using fields from a component of the Global Deterministic Prediction System (GDPS) at 10km horizontal resolution

The Automatic Identification System (AIS) is a global, satellite-based and terrestrial-based ship tracking system that uses shipborne equipment to remotely track vessel identification and positional information and is typically required on vessels of 300 gross tonnage or more on an international voyage, of 500 gross tonnage or more not on an international voyage, and passenger ships of all sizes. AIS tracking technologies are primarily used in support of real-time maritime domain awareness and for maritime security and safety of life at sea. This report describes a geographic information system (GIS) analysis of 2019 AIS data to produce yearly and monthly vessel density maps of all vessel classes combined and yearly density maps of each vessel class. The year 2019 was selected to portray shipping densities in a pre-COVID 19 pandemic depiction of the maritime transport sector in the Northwest Atlantic. Vessel density map applications include use in spatial analysis and decision support for marine spatial planning.

The Automatic Identification System (AIS) is a global, satellite-based and terrestrial-based ship tracking system that uses shipborne equipment to remotely track vessel identification and positional information and is typically required on vessels of 300 gross tonnage or more on an international voyage, of 500 gross tonnage or more not on an international voyage, and passenger ships of all sizes. AIS tracking technologies are primarily used in support of real-time maritime domain awareness and for maritime security and safety of life at sea. This report describes a geographic information system (GIS) analysis of 2019 AIS data to produce yearly and monthly vessel density maps of all vessel classes combined and yearly density maps of each vessel class. The year 2019 was selected to portray shipping densities in a pre-COVID 19 pandemic depiction of the maritime transport sector in the Northwest Atlantic. Vessel density map applications include use in spatial analysis and decision support for marine spatial planning. In 2023 the process was applied to the years 2013 through to 2022 and were made available using the same processes that were applied to the original 2019 datasets.