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.

This product displays for DDT, DDE, and DDD, positions with values counts that have been measured per matrix for each year and are present in EMODnet regional contaminants aggregated datasets, v2024. The product displays positions for every available year.

The Regional Deterministic Wave Prediction System (RDWPS) produces wave forecasts out to 48 hours in the future using the third generation spectral wave forecast model WaveWatch III® (WW3). The model is forced by the 10 meters winds from the High Resolution Deterministic Prediction System (HRDPS). Over the Great Lakes, an ice forecast from the Water Cycle Prediction System of the Great Lakes (WCPS) is used by the model to attenuate or suppress wave growth in areas covered by 25% to 75% and more than 75% ice, respectively. Over the ocean, an ice forecast from the Regional Ice Ocean Prediction System (RIOPS) is used: in the Northeast Pacific, waves propagate freely for ice concentrations below 50%, above this threshold there is no propagation; in the Northwest Atlantic the same logic is used as in the Great Lakes. Forecast elements include significant wave height, peak period, partitioned parameters and others. This system includes several domains: Lake Superior, Lake Huron-Michigan, Lake Erie, Lake Ontario, Atlantic North-West and Pacific North-East.

Envision Mapping was sub-contracted by Heriot Watt University for Scottish Natural Heritage (SNH) to undertake broad scale subtidal biotope mapping of Sullom Voe cSAC. Sullom Voe in the Shetland Isles is the most northerly site in the UK to be selected as a representative of large shallow inlets and bays, and within the site series it is the only Scottish example of a ria (known locally as a ?voe?). The boreal-arctic (northern) species-rich communities of Sullom Voe are restricted to Shetland voes and are not represented elsewhere in the SAC series. The purpose was to map the main features and biota using acoustic remote sensing techniques combined with grab and video sampling.

Benthic macro-infauna biomass in the northern Bering and Chukchi Seas from 1970 to 2012, displayed as decadal pattern Adapted from Grebmeier et al. (2015a) with permission from Elsevier. STATE OF THE ARCTIC MARINE BIODIVERSITY REPORT - <a href="https://arcticbiodiversity.is/findings/benthos" target="_blank">Chapter 3</a> - Page 98 - Figure 3.3.6 Cumulative scores of benthos drivers for each of the 8 CAFF-AMAs. The cumulative scores are taken from the last column of Table 3.3.1. The flower chart/plot helps to visualize the data.

The Eastern Shore Islands was announced as an "Area of Interest" (AOI) in 2018 by the DFO Maritimes region to potentially be considered for a Marine Protected Area under the federal Oceans Act. As part of its mandate for monitoring established and potential conservation areas, DFO Science regularly deploys instruments including conductivity/temperature/depth (CTD) loggers, and other instruments for measuring dissolved oxygen, nutrients, and other chemical ocean properties. This data collection includes temperature and other oceanographic records for the ESI AOI from June 2024 onward. The data are derived from temperature loggers (Hobo Tidbit loggers or similar) and Sea-Bird MicroCATs, but may in future years include current profiles or additional oceanographic data. These data will be used to monitor temperatures in this coastal region to detect any biological shifts associated with temperature and climate fluctuations, and be used to groundtruth oceanographic models. Cite this data as: Jeffery, N., Stanley, R., Pettitt- Wade, H. (2025): Data of: Baseline oceanographic records for the Eastern Shore Islands Area of Interest. Published: September 2025. Coastal Ecosystems Science Division, Fisheries and Oceans Canada, Dartmouth, N.S. https://open.canada.ca/data/en/dataset/f0020cec-5671-4908-8fdd-11fc097de99d

Trends in abundance or diversity of sea ice biota Focal Ecosystem Components across each Arctic Marine Area. STATE OF THE ARCTIC MARINE BIODIVERSITY REPORT - Chapter 4 - Page 177 - Figure 4.1

Status of marine mammal Focal Ecosystem Component stocks by Arctic Marine Area. STATE OF THE ARCTIC MARINE BIODIVERSITY REPORT - <a href="https://arcticbiodiversity.is/findings/marine-mammals" target="_blank">Chapter 3</a> - Page 157 - Figure 3.6.3

This product displays for Benzo(a)pyrene, positions with values counts that have been measured per matrix and are present in EMODnet regional contaminants aggregated datasets, v2022. The product displays positions for all available years.

For the background of data production and data interpretation we refer to the PAME report “Modelling Arctic oceanographic connectivity to further develop PAME’s MPA toolbox”. The uploaded data consist of two main types: 1. Connectivity matrices describing the seascape connectivity in the model domain consisting of 40893 model grid cells. The connectivity matrices describe the probability of dispersal between any two selected model grid cells. 2. GIS shape files of dispersal distance (km) from each model grid cell within the model domain.