Description: Seasonal climatologies (temperature, salinity, and sigma-t) of the Northeast Pacific Ocean were computed from historical observations including all available conductivity-temperature-depth (CTD), bottle, expendable bathy-thermograph (XBT), and Argo data in NOAA (http://www.argo.ucsd.edu/), Marine Environmental Data Service (MEDS), and Institute of Ocean Sciences archives over 1980 to 2010 period in spatial resolution ranging from approximately 100m to 70km. Methods: Calculations, including smooth and interpolation, were carried out in sixty-five subregions and up to fifty-two vertical levels from surface to 5000m. Seasonal averages were computed as the median of yearly seasonal values. Spring months were defined as April to June, summer months were defined as July to September, fall months were defined as October to December, and winter months were defined as January to March. Uncertainties: Uncertainties are introduced when quality controlled observational data are spatially interpolated to varying distances from the observation point. Climatological averages are calculated from these interpolated values.

Vinsamlega hafið samband við Fiskistofu vegna nánari upplýsinga.

Water_body_chlorophyll-a - Monthly Climatology for the European Seas for the period 1960-2023 on the domain from longitude -45.0 to 70.0 degrees East and latitude 24.0 to 83.0 degrees North. Data Sources: observational data from SeaDataNet/EMODnet Chemistry Data Network. Description of DIVA analysis: The computation was done with the DIVAnd (Data-Interpolating Variational Analysis in n dimensions), version 2.7.12, using GEBCO 30sec topography for the spatial connectivity of water masses. Horizontal correlation length and vertical correlation length vary spatially depending on the topography and domain. Depth range: 0.0, 5.0, 10.0, 15.0, 20.0, 25.0, 30.0, 35.0, 40.0, 45.0, 50.0, 55.0, 60.0, 65.0, 70.0, 75.0, 80.0, 85.0, 90.0, 95.0, 100.0, 125.0, 150.0, 175.0, 200.0, 225.0, 250.0, 275.0, 300.0, 325.0, 350.0, 375.0, 400.0, 425.0, 450.0, 475.0, 500.0, 550.0, 600.0, 650.0, 700.0, 750.0, 800.0, 850.0, 900.0, 950.0, 1000.0, 1050.0, 1100.0, 1150.0, 1200.0, 1250.0, 1300.0, 1350.0, 1400.0, 1450.0, 1500.0, 1550.0, 1600.0, 1650.0, 1700.0, 1750.0, 1800.0, 1850.0, 1900.0, 1950.0, 2000.0, 2100.0, 2200.0, 2300.0, 2400.0, 2500.0, 2600.0, 2700.0, 2800.0, 2900.0, 3000.0, 3100.0, 3200.0, 3300.0, 3400.0, 3500.0, 3600.0, 3700.0, 3800.0, 3900.0, 4000.0, 4100.0, 4200.0, 4300.0, 4400.0, 4500.0, 4600.0, 4700.0, 4800.0, 4900.0, 5000.0, 5100.0, 5200.0, 5300.0, 5400.0, 5500.0 m. Units: mg/m3. The horizontal resolution of the produced DIVAnd analysis is 0.25 degrees.

Bay Scale Assessment of Habitat in Bras d'Or Lake - River Denys 2005 - 2009 data is part of the publication Bay Scale Assessment of Nearshore Habitat Bras d'Or Lakes. A history of nearshore benthic surveys of Bras d’Or Lake from 2005 – 2011 is presented. Early work utilized drop camera and fixed mount sidescan. The next phase was one of towfish development, where camera and sidescan were placed on one platform with transponder-based positioning. From 2009 to 2011 the new towfish was used to ground truth an echosounder. The surveys were performed primarily in the northern half of the lake; from 10 m depth right into the shallows at less than 1 m. Different shorelines could be distinguished from others based upon the relative proportions of substrate types and macrophyte canopy. The vast majority of macrophytes occurred within the first 3 m of depth. This zone was dominated by a thin but consistent cover of eelgrass (Zostera marina L.) on almost all shores with a current or wave regime conducive to the growth of this plant. However, the eelgrass beds were frequently in poor shape and the negative impacts of commonly occurring water column turbidity, siltation, or possible localized eutrophication, are suspected. All survey data were placed into a Geographic Information System, and this document is a guide to that package. The Geographic Information System could be used to answer management questions such as the placement and character of habitat compensation projects, the selection of nearshore protected areas or as a baseline to determine long term changes. Vandermeulen, H. 2016. Video-sidescan and echosounder surveys of nearshore Bras d’Or Lake. Can. Tech. Rep. Fish. Aquat. Sci. 3183: viii + 39 p. Cite this data as: Vandermeulen H. Bay Scale Assessment of Nearshore Habitat Bras d'Or Lake - River Denys 2005 - 2009. Published May 2022. Coastal Ecosystems Science Division, Fisheries and Oceans Canada, Dartmouth, N.S.

The data were collected during two research projects: Development of community-based monitoring for aquatic invasive species in the Canadian Arctic - preparing for increased shipping related to resource development and climate change; Diversity of pelagic primary producers in coastal habitats and the potential for harmful blooms in Eastern Canadian Arctic, with a focus near Iqaluit, Nunavut. Funding was provided by Polar Knowledge Canada, Fisheries and Oceans Canada (Strategic Program for Ecosystem-based Research and Advice, Aquatic Invasive Species Program and Oceans Ocean Protection Plan) and the Nunavik Marine Region Wildlife Board. These data are the abundance, richness and diversity of dinoflagellate communities in Canadian Arctic seaports to provide baseline data and to verify the presence of potential non-indigenous species and harmful taxa. These data can be used as a reference source for monitoring the introduction of potentially non-native species introduced into Arctic ports where shipping activities are high. SAMPLING Dinoflagellate samples were collected using a 20 μm (30 cm diameter) Nitex® plankton net during August in Churchill (MB) (2007 and 2015), in Deception Bay (QC ) (2016), in Iqaluit (NU) (2015 and 2019) and in Milne Inlet (2017). Samples were collected from 1 m of the surface to 1 m above the bottom. PREPARATION : Samples were stored in 4% formaldehyde. Sample preparation and counting were performed using the Utermöhl method. OBSERVATION : Samples were observed using an inverted microscope (NIKON Eclipse TE-2000-U) under a magnification of 200x. ABUNDANCE : The calculation of the abundance of dinoflagellates (cell / liter) was carried out as follows: Number of cells X Volume of the bottle / Volume of the Utermöhl chamber / (pi X Radius^2 X Depth) X 1000 ENVIRONMENTAL VARIABLES Environmental data were measured using a CTD and a Secchi disk. The time between sea ice melt and sampling was calculated by subtracting the sampling day from the breakup dates (ice concentration <1/10) which were extracted from the Canadian Ice Service records. For further information, please consult the following paper: Dhifallah F, Rochon A, Simard N, McKindsey CW, Gosselin M, Howland KL. 2022. Dinoflagellate communities in high-risk Canadian Arctic ports. Estuarine, Coastal and Shelf Science 266:107731

Bay Scale Assessment of Nearshore Habitat Bras dOr Lake - Malagawash 2007 2008 data is part of the publication Bay Scale Assessment of Nearshore Habitat Bras d'Or Lakes. A history of nearshore benthic surveys of Bras d’Or Lake from 2005 – 2011 is presented. Early work utilized drop camera and fixed mount sidescan. The next phase was one of towfish development, where camera and sidescan were placed on one platform with transponder-based positioning. From 2009 to 2011 the new towfish was used to ground truth an echosounder. The surveys were performed primarily in the northern half of the lake; from 10 m depth right into the shallows at less than 1 m. Different shorelines could be distinguished from others based upon the relative proportions of substrate types and macrophyte canopy. The vast majority of macrophytes occurred within the first 3 m of depth. This zone was dominated by a thin but consistent cover of eelgrass (Zostera marina L.) on almost all shores with a current or wave regime conducive to the growth of this plant. However, the eelgrass beds were frequently in poor shape and the negative impacts of commonly occurring water column turbidity, siltation, or possible localized eutrophication, are suspected. All survey data were placed into a Geographic Information System, and this document is a guide to that package. The Geographic Information System could be used to answer management questions such as the placement and character of habitat compensation projects, the selection of nearshore protected areas or as a baseline to determine long term changes. Vandermeulen, H. 2016. Video-sidescan and echosounder surveys of nearshore Bras d’Or Lake. Can. Tech. Rep. Fish. Aquat. Sci. 3183: viii + 39 p. Cite this data as: Vandermeulen H. Bay Scale Assessment of Nearshore Habitat Bras d'Or Lake - Malagawash 2007 - 2008. Published May 2022. Coastal Ecosystems Science Division, Fisheries and Oceans Canada, Dartmouth, N.S.

Figure 3.2.2a: Relative abundance of major eukaryote taxonomic groups found by high throughput sequencing of the small-subunit (18S) rRNA gene across Arctic Marine Areas. Figure 3.2.2b: Relative abundance of major eukaryote functional groups found by microscopy in the Arctic Marine Areas. STATE OF THE ARCTIC MARINE BIODIVERSITY REPORT - <a href="https://arcticbiodiversity.is/findings/plankton" target="_blank">Chapter 3</a> - Page 70 - Figures 3.2.2a and 3.2.2b

Sea ice meiofauna composition (pie charts) and total abundance (red circles) across the Arctic, compiled by the CBMP Sea Ice Biota Expert Network from 27 studies between 1979 and 2015. Scaled circles show total abundance per individual ice core while pie charts show average relative contribution by taxon per Arctic Marine Area (AMA). Number of ice cores for each AMA is given in parenthesis after region name. Note that studies were conducted at different times of the year, with the majority between March and August (see 3.1 Appendix). The category ‘other’ includes young stages of bristle worms (Polychaeta), mussel shrimps (Ostracoda), forams (Foraminifera), hydroid polyps (Cnidaria), comb jellies (Ctenophora), sea butterflies (Pteropoda), marine mites (Acari) and unidentified organisms. STATE OF THE ARCTIC MARINE BIODIVERSITY REPORT - <a href="https://arcticbiodiversity.is/findings/sea-ice-biota" target="_blank">Chapter 3</a> - Page 40 - Figure 3.1.4 From the report draft: "Here, we synthesized 19 studies across the Arctic conducted between 1979 and 2015, including unpublished sources (B. Bluhm, R. Gradinger, UiT – The Arctic University of Norway; H. Hop, Norwegian Polar Institute; K. Iken, University of Alaska Fairbanks). These studies sampled landfast sea ice and offshore pack ice, both first- and multiyear ice (Appendix 3.1). Meiofauna abundances reported in individual data sources were converted to individuals m-2 of sea ice assuming that ice density was 95% of that in melted ice. Due to the low taxonomic resolution in the reviewed studies, ice meiofauna were grouped into: Copepoda, nauplii (for copepods as well as other taxa with naupliar stages), Nematoda, Polychaeta (mostly juveniles, but also trochophores), flatworms (Acoelomorpha and Platyhelminthes; these phyla have mostly been reported as one category), Rotifera, and others (which include meroplanktonic larvae other than Polychaeta, Ostracoda, Foraminifera, Cnidaria, Ctenophora, Pteropoda, Acari, and unidentified organisms). Percentage of total abundance for each group was calculated for each ice core, and these percentages were used for regional averages. Maximum available ice core length was used in data analysis, but 50% of these ice cores included only the bottom 10 cm of the ice, 12% the bottom 5 cm, 10% the bottom 2 cm, and 11% the entire ice-thickness. Data from 617 cores were used."

This visualization product displays the marine litter material categories percentage per trawl. EMODnet Chemistry included the collection of marine litter in its 3rd phase. Since the beginning of 2018, data of seafloor litter collected by international fish-trawl surveys have been gathered and processed in the EMODnet Chemistry Marine Litter Database (MLDB). The harmonization of all the data has been the most challenging task considering the heterogeneity of the data sources, sampling protocols (OSPAR and MEDITS protocols) and reference lists used on a European scale. Moreover, within the same protocol, different gear types are deployed during bottom trawl surveys. Unlike other EMODnet seafloor litter products, all trawls surveyed since 2007 are included in this map even if the wingspread and/or the distance are/is unknown. Only surveys with an unknown number of items were excluded from this product. Harmonization of the material categories between ICES and MEDITS lists was performed and the following calculation was applied: Material % = (∑Number of items of each material category*100)/(∑Number of items of all material categories) More information on data processing and calculation are detailed in the attached document. Warning: the absence of data on the map does not necessarily mean that they do not exist, but that no information has been entered in the Marine Litter Database for this area.

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