Marine protected areas (MPAs) are one among a number of spatial management tools, and are defined as areas that are established for the long-term, and managed through legal or other effective means, to achieve the long-term conservation of nature with associated ecosystem services and cultural values.Currently, Fisheries and Oceans Canada has a number of MPAs designated under the Oceans Act and Areas of Interest for new MPAs at various stages of progress towards designation. These areas are ecologically significant, with species and/or features that require special management consideration.  An Oceans Act MPA can be established for any of the six conservation purposes outlined in the Act:• The conservation and protection of commercial and non-commercial fishery resources, including marine mammals, and their habitats;  • The conservation and protection of endangered or threatened marine species, and their habitats;  • The conservation and protection of unique habitats;  • The conservation and protection of marine areas of high biodiversity or biological productivity; • The conservation and protection of any other marine resource or habitat as is necessary to fulfill the mandate of the Minister; and• The conservation and protection of marine areas for the purposes of maintaining ecological integrity

To ensure informed decision-making, management, and conservation of marine ecosystems along the British Columbia (BC) coastline, a comprehensive understanding of marine communities and habitats is necessary. Marine planning initiatives, including environmental incident response planning and the development of a marine protected area network, have long been challenged by significant gaps in our knowledge of the distribution of many nearshore marine species. This lack of critical information can impede our ability to effectively manage and protect vulnerable species and ecosystems.   We developed a set of species distribution models (single-SDMs) using data collected from the benthic habitat mapping survey. These models correlate species occurrence data with environmental variables. We used these models to make predictions of the probability of occurrence of each species across the entire BC coast. A cluster analysis of the single-SDM predictions was then used to determine biotopes, which are distinct combinations of physical and chemical water properties and associated biological communities.   We defined and mapped the spatial distribution and probability of nine nearshore macrofauna epibenthic biotopes along with three physiotopes based on environmental conditions. The definition of the biotopes includes correlated species, the type of substrate, and range of environmental conditions (slope, depth, current, temperature, salinity, and tidal current) occurring within each biotope. The biotopes defined here are a first, but important, step in quantitative bioregionalization for the Pacific region as the resolution of nearshore marine community information has been lacking in BC and has hindered marine spatial initiatives.  This dataset contains 71 of the 72 single-SDMs (which excludes Northern abalone, an endangered species), the spatial distribution of 9 biotopes and 3 physiotopes, and the species richness calculated as the sum of occurrence probabilities across all 72 species.

Marine classification schemes based on abiotic surrogates often inform regional marine conservation planning in lieu of detailed biological data. However, theses chemes may poorly represent ecologically relevant biological patterns required for effective design and management strategies. We used a community-level modeling approach to characterize and delineate representative mesoscale (tens to thousands of kilometers) assemblages of demersal fish and benthic invertebrates in the North-west Atlantic. Hierarchical clustering of species occurrence data from four regional annual multispecies trawl surveys revealed three to six groupings (predominant assemblage types) in each survey region, broadly associated with geomorphic and oceanographic features. Indicator analyses identified 3–34 emblematic taxa of each assemblage type. Random forest classifications accurately predicted assemblage dis-tributions from environmental covariates (AUC > 0.95) and identified thermal limits (annual minimum and maximum bottom temperatures) as important pre-dictors of distribution in each region. Using forecasted oceanographic conditions for the year 2075 and a regional classification model, we projected assemblage dis-tributions in the southernmost bioregion (Scotian Shelf-Bay of Fundy) under ahigh emissions climate scenario (RCP 8.5). Range expansions to the north eastare projected for assemblages associated with warmer and shallower waters of the Western Scotian Shelf over the 21st century as thermal habitat on the rela-tively cooler Eastern Scotian Shelf becomes more favorable. Community-level modeling provides a biotic-informed approach for identifying broadscale ecolog-ical structure required for the design and management of ecologically coherent, representative, well-connected networks of Marine Protected Areas. When com-bined with oceanographic forecasts, this modeling approach provides a spatial tool for assessing sensitivity and resilience to climate change, which can improve conservation planning, monitoring, and adaptive management.Cite this data as: O'Brien, J.M., Stanley, R.R.E., Jeffery, N.W., Heaslip, S.W., DiBacco, C., and Wang, Z. Demersal fish and benthic invertebrate assemblages in the Northwest Atlantic.Published: December 2024. Coastal Ecosystems Science Division, Maritimes region, Fisheries and Oceans Canada, Dartmouth NS.https://open.canada.ca/data/en/dataset/14d55ea5-b17d-478c-b9ee-6a7c04439d2b

Marine Protected Areas require comprehensive monitoring to ensure objectives are achieved; however, monitoring natural ecosystems at scale is challenged by the biodiversity it aims to measure. Environmental DNA (eDNA) metabarcoding holds promise to address this monitoring challenge. We conducted paired sampling at 54 sites for fish and invertebrate assemblages in the Northwest Atlantic using groundfish trawls and eDNA metabarcoding of benthic seawater using four genetic markers (12S rRNA, 16S rRNA, 18S rRNA, and CO1). Compared to trawling, eDNA detected similar patterns of species turnover, larger estimates of gamma diversity, and smaller estimates of alpha diversity. A total of 63.6% (42/66) of fish species captured by trawling were detected by eDNA, along with an additional 26 species. Of the 24 missed detections by eDNA, 12 were inevitable as they lacked reference sequences. Excluding taxa assigned to higher than species level and those without a species name, 23.6% (17/72) of invertebrate species captured by trawling were detected by CO1, which detected an additional 98 species. We demonstrate that eDNA is capable of detecting patterns of community assemblage and species turnover in an offshore environment, emphasizing its strong potential for a non-invasive, comprehensive, and scalable tool for biodiversity monitoring supporting marine conservation programmes.Cite this data as: Jeffery, N., Rubidge, E., Abbott, C., Westfall, K., Stanley, R. (2024): Data of: eDNA metabarcoding enriches traditional trawl survey data for monitoring biodiversity in the marine environment.Published: August 2024. Coastal Ecosystems Science Division, Fisheries and Oceans Canada, Dartmouth, N.S. https://open.canada.ca/data/en/dataset/43a91ba7-8025-4330-88db-db14022d729d

Pelagic Marine Ecounits are intended to describe the sea surface and water column. Two variables were selected to derive pelagic ecounits:1. Salinity and 2. Stratification. The British Columbia Marine Ecological Classification (BCMEC) is a hierarchical classification that delineates Provincial marine areas into Ecozones, Ecoprovinces, Ecoregions and Ecosections. The classification was developed from previous Federal and Provincial marine ecological classifications which were based on 1:2,000,000 scale information. The BCMEC has been developed for marine and coastal planning, resource management and a Provincial marine protected areas strategy. A new, smaller level of classification termed ecounits developed using 1:250,000 scale depth, current, exposure, subsurface relief and substrate was created to verify the larger ecosections, and to delineate their boundaries. CRIMS is a legacy dataset of BC coastal resource data that was acquired in a systematic and synoptic manner from 1979 and was intermittently updated throughout the years. Resource information was collected in nine study areas using a peer-reviewed provincial Resource Information Standards Committee consisting of DFO Fishery Officers, First Nations, and other subject matter experts. There are currently no plans to update this legacy data.

Includes: * National Parks * National Marine Conservation Areas * heritage canals * National Wildlife Areas * Other Federal Protected areas This dataset is provided by the federal government, and may not include all Federal protected lands.

This line layer describes hiking trails for which Parks Canada has a responsibility. This includes trails found in national parks, national historic sites, and national marine conservation areas.Data is not necessarily complete - updates will occur weekly.

Seagrasses support multiple key ecosystem functions (e.g., sediment stabilization, carbon storage, nursery habitat) in nearshore environments across all three Canadian coastlines. Eelgrass (Zostera marina) is a seagrass species that has been designated as an Ecologically Significant Species (ESS) and is the most widely distributed and abundant seagrass in Canada. Given the considerable conservation and management interest in eelgrass habitats, large-scale data aggregation efforts have been initiated to generate comprehensive distribution maps of eelgrass coverage in Canadian coastal waters. However, extensive portions of the Newfoundland coastline have not yet been surveyed for the presence of eelgrass. We combine spatial data layers describing shoreline characteristics, relative exposure index (REI), depth, and freshwater inputs to delineate areas potentially suitable for eelgrass growth in Newfoundland. We determined that many nearshore environments could potentially support eelgrass habitats but confirming eelgrass presence will require further validation and ground-truthing. Incorporating distribution models that use environmental covariates to estimate probabilities of occurrence in nearshore areas could help to strengthen these predictions. Mapping eelgrass distributions provides baseline data essential to eelgrass monitoring and implementation of coastal marine conservation, informing emergency response, and is particularly important considering the consequences associated with the potential loss of ecosystem functions in the event of eelgrass decline. King, B.G.C., Gullage, L., Butt, K., Warren, M., Allard, K., Gregory, R.S., and Byrne, M.A. 2026. Using shoreline characteristics, relative exposure, depth, and freshwater inputs as surrogate measures to identify areas potentially suitable for eelgrass (Zostera marina) in Newfoundland. Can. Tech. Rep. Fish. Aquat. Sci. 3737: vii + 22 p.https://doi.org/10.60825/7thp-4425

Monitoring programs are an important component of Marine Protected Area (MPA) management, providing requisite information on the state of, and changes in, protected ecosystems. Monitoring is required to gauge the efficacy of MPAs towards their conservation objectives and provides information needed to evaluate the benefits provided to biodiversity from restricted access. However, in Nova Scotia’s coastal zone, there is a lack of baseline data, including fish diversity and community structure in macrophyte beds, which makes monitoring intractable. In 2017, the Eastern Shore Islands was identified as a coastal Area of Interest (AOI) for the potential establishment of an MPA. In 2018 an overview was conducted, detailing the spatial and temporal ecological attributes of the AOI. This information revealed a unique coastal ecosystem associated with a dense archipelago and relatively natural seascape. The abundance of plant and algal biogenic habitats within the area was assumed to host a diversity of juvenile fish species. The primary objective of this project is to begin development of a long-term biodiversity monitoring program in the Eastern Shore Islands and other coastal Areas of Interest for conservation planning. We propose implementing this program with the use of direct (beach seines, scuba diving, and stable isotope sampling) and indirect (environmental DNA - eDNA) sampling. Environmental DNA (eDNA) is a useful tool to examine marine biodiversity in a non-invasive way, on a small spatial scale. eDNA can be easily collected and filtered and is becoming increasingly cost efficient to sequence and may be a useful marine protected area monitoring tool. While eDNA generally yields comparable results to traditional sampling techniques in terms of biodiversity captured, little is known on how eDNA signals fluctuate across years (or even days to weeks). We will compare species detections using eDNA metabarcoding to visual surveys (scuba and seine nets) to census eelgrass beds across the coastal zone, providing a baseline and time series of species diversity on which to base long-term monitoring. This project will generate inventories of eelgrass bed locations, and fish and invertebrate diversity within eelgrass beds. We additionally collect fish length distribution data to examine seasonal and inter-annual trends in size structure over time. The data generated from direct and indirect sampling will provide a comprehensive and ongoing catalog of species diversity and community structure in coastal eelgrass beds, as well as best-practices for sampling eDNA in the coastal environment.Cite this data as: Jeffery, N.W., Pettitt-Wade, H., Van Wyngaarden, M., and Stanley, R.R.E. Maritimes Coastal Biodiversity Monitoring Program – Beach Seining.Published: December 2023. Coastal Ecosystems Science Division, Maritimes region, Fisheries and Oceans Canada, Dartmouth NS. https://open.canada.ca/data/en/dataset/dbbcb23a-d018-4b70-b8ec-89997aded770

Significant climate change impacts are highly likely in all Canadian marine and freshwater basins, with effects increasing over time (DFO 2012). Climate models project that ecosystems and fisheries across Canada will be disrupted into the foreseeable future (Lotze et al. 2019; Bryndum-Buchholz et al. 2020; Tittensor et al. 2021; Boyce et al. 2024). Despite its imminence, climate change is infrequently factored into Canada’s primary marine conservation strategies, such as spatial planning (O’Regan et al. 2021) or fisheries management (Boyce et al. 2021; Pepin et al. 2022). The Climate Risk Index for Biodiversity (CRIB) was developed to assess climate risk for marine species in a quantitative, spatially explicit, and scalable manner, supporting climate-informed decision-making. It has been used to evaluate climate risks for marine life globally (Boyce et al. 2022), regionally (Lewis et al. 2023; Boyce et al. 2024; Keen et al. 2023), for fisheries (Boyce et al. 2024), and in support of spatial conservation planning (Keen et al. 2023). This dataset contains climate vulnerability and risk estimates from the CRIB framework adapted to consider warming at both the sea surface and its bottom for 145 marine species of conservation or fisheries interest across Canada’s marine territory. Climate risk is available at a 0.25-degree resolution under two contrasting emission scenarios to 2100. For each species, location, and scenario, 12 climate indexes, three vulnerability dimensions, and an overall vulnerability and risk score are provided. The accompanying report describes the data, methods, and workflow used to calculate risk. This report also guides the interpretation of these data to inform and support climate-informed decision-making in Canada.