Ocean physical conditions in the Maritimes Region in 2019 were characterized by cooler surface temperatures, continued warmer bottom temperatures and weaker stratification compared to recent years. Deep nutrient inventories were lower than normal over most of the region, with the exception of the Cabot Strait section where deep nutrients were near or higher than normal during the spring sampling and associated with record-warm water. Anomalies of surface nutrients were negative across the region, with the exception of positive anomalies observed at the deep shelf and offshore stations of the Louisbourg section. The spring phytoplankton bloom was near or slightly earlier than normal across the Scotian Shelf (SS) with near-normal duration. Peak chlorophyll a concentrations during the spring bloom occurred within a narrow time window across the SS. At Halifax-2 (HL2), the spring bloom was characterized by a high amplitude, and a rapid progression and decline. Plankton community changes persisted in 2019 with lower abundance of large phytoplankton (diatoms), mainly lower-than-normal biomass of zooplankton and abundance of Calanus finmarchicus, and higher-than-normal abundance of non-copepods. Arctic Calanus and warm-shelf copepods showed mixed abundance anomalies in 2019, reversing the pattern of 2018. Above-normal abundances of Oithona atlantica, especially at HL2, suggest a greater influence of offshore waters in recent years. Surface temperature in the Bedford Basin was near normal in 2019 with mainly cooler-than-normal temperatures from January to June and near- or slightly-above-normal temperatures from July to December. Bottom temperature and salinity were below normal in 2019 with near- or slightly-above-normal conditions at the start of the year and progressing toward cooler and fresher water from February to December. Surface and deep nitrate, phosphate and silicate were near or below normal, with surface phosphate reaching a record low in 2019. The 2018 Continuous Plankton Recorder data indicated an annual abundance of diatoms close to normal for the Eastern (ESS) and Western Scotian Shelf (WSS), while the abundance of dinoflagellates and the Phytoplankton Colour Index values were near (WSS) or above (ESS) normal. The annual abundance of Calanus CI-IV was near normal (ESS) or slightly below normal (WSS), while C. finmarchicus CV-VI levels were slightly below (ESS) or below (WSS) normal. The abundance of Calanus glacialis (ESS, WSS) and Para/Pseudocalanus and Limacina spp. (WSS) were lower than normal, while that of coccolithphore (ESS, WSS), and copepod nauplii and foraminifera (ESS) was higher than normal. "

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

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

Circumpolar depiction of species richness based on the distributions of the 11 ice-associated Focal Ecosystem Components (according to the distributions reported in IUCN Red List species accounts). A maximum of nine species occur in any one geographic location. The Arctic gateways in both the Atlantic and Pacific regions have the highest species diversity. STATE OF THE ARCTIC MARINE BIODIVERSITY REPORT - <a href="https://arcticbiodiversity.is/findings/marine-mammals" target="_blank">Chapter 3</a> - Page 152 - Figure 3.6.1

Data layers show commercial fishery footprints for directed fisheries using bottom and pelagic longlines for groundfish and large pelagics respectively, and traps for hagfish, LFA 41 and Grey Zone lobster, snow crab, and other crab on the Scotian Shelf, the Bay of Fundy, and Georges Bank in NAFO Divisions 4VWX and Canadian portions of 5Y and 5Z. Bottom longline and trap fishery maps aggregate commercial logbook effort (bottom longline soak time and logbook entries) per 2-minute grid cell using 2002–2017 data. Pelagic longline maps aggregate speed-filtered vessel monitoring system (VMS) track lines as vessel minutes per km2 on a base-10 log scale using 2003–2018 data. The following data layers are included in the mapping service for use in marine spatial planning and ecological risk assessment: 1) multi-year and quarterly composite data layers for bottom longline and trap gear, and 2) multi-year and monthly composite data layers for pelagic longline gear. Additional details are available online: S. Butler, D. Ibarra and S. Coffen-Smout, 2019. Maritimes Region Longline and Trap Fisheries Footprint Mapping for Marine Spatial Planning and Risk Assessment. Can. Tech. Rep. Fish. Aquat. Sci. 3293: v + 30 p. http://publications.gc.ca/collections/collection_2019/mpo-dfo/Fs97-6-3293-eng.pdf

The analysis was performed per season using DIVA software tool (Data-Interpolating Variational Analysis). The analyses products are stored as NetCDF CF files and made available as WMS layers for easy browsing and adding. Every step of the time dimension corresponds to a 6-year moving average from 1983 to 2016. The depth dimension spans from surface to 1000 m, with 21 vertical levels. The boundaries and overlapping zones between these regions were filtered to avoid any unrealistic spatial discontinuities. This combined water body dissolved oxygen concentration product is masked using the relative error threshold 0.5. Units: µmol/l Created by 'University of Liège, GeoHydrodynamics and Environment Research (ULiège-GHER)'. The data used as input for DIVA have been extracted from the EMODnet Chemistry Download Service: https://emodnet-chemistry.maris.nl/search Intermediate regional data products: Mediterranean Sea - DIVA 4D 6-year analysis of Water body chlorophyll-a 1990/2017 v2018, Arctic Ocean - DIVA 4D 6-year analysis of Water body chlorophyll-a 1980/2017 v2018, Black Sea - DIVA 4D 6-year analysis of Water body chlorophyll-a 1990/2016 v2018, North East Atlantic Ocean - DIVA 4D 6-year analysis of Water body chlorophyll-a 1960/2017 v2018, North Sea - DIVA 4D 6-year analysis of Water body chlorophyll-a 1980/2017 v2018, Baltic Sea - DIVA 4D 6-year analysis of Water body chlorophyll-a 1980/2016 v2018

Moving 6-year analysis of Silicate at Atlantic Sea for each season. - winter: January-March, - spring: April-June, - summer: July-September, - autumn: October-December Every year of the time dimension corresponds to the 6-year centred average of each season. 6-year periods span - from 1972-1977 until 2015-2020 (winter), - from 1984-1989 until 2015-2020 (spring), - from 1972-1977 until 2015-2020 (summer), - from 1971-1976 until 2015-2020 (autumn). Observational data span from 1971 to 2020. Depth range (IODE standard depths): -2000.0, -1750, -1500.0, -1400.0, -1300.0, -1200.0, -1100.0, -1000.0, -900.0, -800.0, -700.0, -600.0, -500.0, -400.0, -300.0, -250.0, -200.0, -150.0, -125.0, -100.0, -75.0, -50.0,-40.0, -30.0, -20.0, -10.0, -5.0, -0.0 Data Sources: observational data from SeaDataNet/EMODNet Chemistry Data Network. Description of DIVA analysis: Geostatistical data analysis by DIVA (Data-Interpolating Variational Analysis) tool. GEBCO 1min topography is used for the contouring preparation. Analyzed filed masked using relative error threshold 0.3 and 0.5 DIVA settings. Correlation length was optimized and filtered vertically and a seasonally-averaged profile was used. Signal to noise ratio was fixed to 1. Logarithmic transformation applied to the data prior to the analysis. Background field: the data mean value is subtracted from the data. Detrending of data: no, Advection constraint applied: no. Units: umol/l

The assessment of the status of eelgrass (Zostera marina) beds at the bay-scale in turbid, shallow estuaries is problematic. The bay-scale assessment (i.e., tens of km) of eelgrass beds usually involves remote sensing methods such as aerial photography or satellite imagery. These methods can fail if the water column is turbid, as is the case for many shallow estuaries on Canada’s eastern seaboard. A novel towfish package was developed for the bay-scale assessment of eelgrass beds irrespective of water column turbidity. The towfish consisted of an underwater video camera with scaling lasers, sidescan sonar and a transponder-based positioning system. The towfish was deployed along predetermined transects in three northern New Brunswick estuaries. Maps were created of eelgrass cover and health (epiphyte load) and ancillary bottom features such as benthic algal growth, bacterial mats (Beggiatoa) and oysters. All three estuaries had accumulations of material reminiscent of the oomycete Leptomitus, although it was not positively identified in our study. Tabusintac held the most extensive eelgrass beds of the best health. Cocagne had the lowest scores for eelgrass health, while Bouctouche was slightly better. The towfish method proved to be cost effective and useful for the bay-scale assessment of eelgrass beds to sub-meter precision in real time. Cite this data as: Vandermeulen H. Data of: Bay Scale Assessment of Eelgrass Using Sidescan and Video - Cocagne 2008. Published: November 2019. Coastal Ecosystems Science Division, Fisheries and Oceans Canada, Dartmouth, N.S. https://open.canada.ca/data/en/dataset/431c815e-65f0-477b-9389-060fa41ec955

The locations of coastal British Columbia marine navigation hazards. The Coastal BC datasets are circa 2004 and legacy in nature. Caution should be exercised when using this data, as it may not be accurate or complete. There are currently no plans to update.

EMODnet Chemistry aims to provide access to marine chemistry data sets and derived data products concerning eutrophication, acidity and contaminants. The chemicals chosen reflect importance to the Marine Strategy Framework Directive (MSFD). ITS-90 water temperature and Water body salinity variables have been also included (as-is) to complete the Eutrophication and Acidity data. If you use these variables for calculations, please refer to SeaDataNet for having the quality flags: https://www.seadatanet.org/Products/Aggregated-datasets . This aggregated dataset contains all unrestricted EMODnet Chemistry data on Eutrophication and Acidity (14 parameters with quality flag indicators), and covers the North Sea with 587584 CDI records. Data were aggregated and quality controlled by 'Aarhus University, Department of Bioscience, Marine Ecology Roskilde' from Denmark. Regional datasets concerning eutrophication and acidity are automatically harvested and resulting collections are aggregated and quality controlled using ODV Software and following a common methodology for all Sea Regions ( https://doi.org/10.6092/9f75ad8a-ca32-4a72-bf69-167119b2cc12). When not present in original data, Water body nitrate plus nitrite was calculated by summing up the Nitrates and Nitrites. Same procedure was applied for Water body dissolved inorganic nitrogen (DIN) which was calculated by summing up the Nitrates, Nitrites and Ammonium. Quality flags for Water body dissolved inorganic nitrogen (DIN) should be disregarded since that currently they are not based on the original quality flags of nitrite, nitrate and ammonium. Parameter names are based on P35, EMODnet Chemistry aggregated parameter names vocabulary, which is available at: https://www.bodc.ac.uk/resources/vocabularies/vocabulary_search/P35/. Detailed documentation is available at: https://dx.doi.org/10.6092/4e85717a-a2c9-454d-ba0d-30b89f742713 Explore and extract data at: https://emodnet-chemistry.webodv.awi.de/eutrophication>NorthSea The aggregated dataset can be downloaded as ODV collection and spreadsheet, which is composed of metadata header followed by tab separated values. This spreadsheet can be imported to ODV Software for visualisation (More information can be found at: http://www.seadatanet.org/Standards-Software/Software/ODV). The original datasets can be searched and downloaded from EMODnet Chemistry Chemistry CDI Data and Discovery Access Service: https://emodnet-chemistry.maris.nl/search