Cyanobacteria (also referred to as blue-green algae) are common photosynthetic bacteria that live in surface waters. Under favorable conditions, such as warm water and high nutrient content, these bacteria can form nuisance “blooms”. The presence of blooms in recreational water causes unpleasant aesthetics and exposure to some toxin-producing blooms may pose potential health risks. Contact with blooms can cause skin rashes and irritation, itchy eyes, and ear infections. Inhaling water may cause allergic-like reactions, runny noses or sore throats. Ingestion of toxins can cause a range of symptoms (e.g., hepatotoxic or neurotoxic effects, and even death). There has been increased public awareness as a result of research over the past 25 years, recent monitoring efforts, and increased public education on the topic. In 2009, Alberta Health and Alberta Health Services began seasonal monitoring for cyanobacterial blooms at high use recreational beaches. In 2019, beach operators took over the sampling role from Alberta Health Services under the Alberta Safe Beach Protocol. Water is collected from shallow water adjacent to beaches and submitted to laboratories for analysis of cyanobacterial bloom indicators. These data, along with visual inspection, are used to characterize potential cyanobacterial blooms and issue recreational water use advisories when cyanobacteria are found in a waterbody at levels that can affect human health. The data presented below is organized into two files that contain supporting data and key cyanobacterial bloom indicators, and counts of individual cyanobacteria species, respectively. Each row represents a water sample collected from an Alberta beach. In the cyanobacteria species data, each water sample will have many associated rows of data. Each column represents a piece of information about that water sample (e.g., key indicators and supporting information) that is used to characterize cyanobacterial blooms. Data from the current year (2025) should be considered preliminary and might change with further quality control/quality assurance steps. This dataset is updated monthly between June and September each year. For more information on these indicators please refer to the column descriptions “Usage Considerations” associated with this dataset.

Zooplankton samples were collected at Ocean Station "P" (50.0000, -145.0000) from 1956 to 1980, and were analyzed to various levels of taxonomic resolution over the years. Although summaries of these data have been previously published ((LeBrasseur 1965) and (Fulton 1978, 1983)) the detailed species data have never been published. This detailed dataset contains total zooplankton wet weights/m3 for the whole period of 1956 to 1980, as well as densities (numbers/m3) for five major taxa (copepods, chaetognaths, euphausiids, amphipods, and Aglantha) from 1964 to 1967, species identifications, counts and lengths for many samples collected between 1968 to 1980. The attached supporting document (Ocean Station "Papa" detailed zooplankton data: 1956 – 1980) contains information on the methods used to collect and process the data along with descriptions of a number of fairly minor points about the data that were not resolved. It also describes, in detail, the format of the original data files, the corrections/changes that were made to these files in creating this version, and how these errors affect what was published in Fulton (1983).The purpose of this record is to make the detailed data available to the scientific community in an electronic format and to provide a convenient reference for citing the detailed data. Waddell, Brenda J., and Skip McKinnell. 1995. Ocean Station "Papa" detailed zooplankton data:1956 - 1980. Can. Tech. Rep. Fish. Aquat. Sci. 2056: 21 p.

Zooplankton and ichthyoplankton data are archived in the Institute of Ocean Sciences (IOS) Zooplankton Database. The data available spans from 1980 to 2018 and is an extraction of vertical net hauls as biomass by major taxa collected during surveys conducted in the oceanic and coastal waters of the Northeast Pacific Ocean. The majority of vertical net hauls in this data set were collected from 10 metres above the sea floor or an approximate maximum depth of 250 metres. For further data requests, please use the contact information provided.

Cold-water corals are conspicuous in the waters off Eastern Canada. Despite that, there are few DNA sequence records from specimens collected in the region available in GenBank, and not all species recorded in the region have sequence data regardless of geographic origin. This can limit the use of eDNA techniques to detect and identify corals. Our objective was to sequence and publish sequences for two octocoral DNA barcoding markers: CO1 and MutS. We sequenced and deposited 36 sequences to GenBank from 19 specimens representing three sea pen taxa (Octocorallia: Pennatuloidea): Distichoptilum gracile, Pennatula aculeata, and Protoptilum carpenteri. Identification of all specimens was confirmed by B. M. Neves before submission. Specimens and DNA tissues were donated to the Canadian Museum of Nature, where they are currently stored. This publication is part 1 of a series of GenBank submissions by our lab.Specimens were collected from across the Northwest Atlantic and originate from depths ranging between 200-1924 meters. Specimens were collected as part of research vessel multispecies trawl surveys or remotely operated vehicle (ROV ROPOS) surveys. DNA was isolated and purified using the QIAgen DNeasy Blood and Tissue kit, with an initial overnight incubation with Proteinase K. Two commonly used octocoral barcoding regions were amplified using previously described primers: 1) COII8068F (McFadden et al., 2004) and COIOCTR (France and Hoover, 2002) for the CO1 gene, and 2) ND42599F (France and Hoover, 2002) and mut3458R (Sánchez et al., 2003) for the MutS gene. Amplifications were conducted using 12.5 µl of Green DreamTaq Master Mix (Thermo Fisher Scientific), 1 µl of template DNA, 0.5 µl of each 10 µM forward and reverse primers, 0.5 µl of 10 µM reverse primer, and 10.5 µl of water. Thermocycling was run as follows: 3 min of initial denaturation at 95 °C, followed by 40 cycles at 95 °C for 30 s, 30 s at annealing temperature of 48 °C, then 65 s at an extension temperature of 72 °C, and a final elongation at 72 °C for 4 min. PCR products were cleaned using Agencourt AMPure XP Beads (Beckman Coulter) and sent to The Center for Advanced Genomics, Toronto, Canada for Sanger sequencing. Sequences were visualized and aligned using Geneious Prime 2022.0.2. Obtained sequences have been deposited in GenBank under accession numbers OQ569768- OQ569784 and OQ420359- OQ420377. This work was funded by Fisheries and Oceans Canada under an Enhanced Regional Capacity grant (2020-2021) and the Marine Conservation Targets (MCT) program (2021-2024), Newfoundland and Labrador Region.

In 2018, Fisheries and Oceans Canada initiated the Multidisciplinary Arctic Program (MAP) – Last Ice, the first ecosystem study of the poorly characterized region of the Lincoln Sea in the Marine Protected Area of Tuvaijuittuq, where multiyear ice still resides in the Arctic Ocean. MAP-Last Ice takes a coordinated approach to integrate the physical, biochemical, and ecological components of the sea ice-ocean connected ecosystem and its response to climate and ocean forcings. The cross-disciplinary program establishes baseline ecological knowledge for Tuvaijuittuq and, in particular, for its unique multiyear ice ecosystem. The database provides baseline data on the abundance of bacteria and viruses in multi- and first-year ice and in surface waters of the Lincoln Sea in Tuvaijuittuq, and their relation to bio-physical conditions. The data were collected during the 2018 spring field campaign of the MAP-Last Ice Program, at an ice camp offshore of Canadian Forces Station (CFS) Alert.

The Canadian Aquatic Biomonitoring Network (CABIN) is an aquatic biomonitoring program for assessing the health of fresh water ecosystems in Canada. Benthic macroinvertebrates are collected at a site location and their counts are used as an indicator of the health of that water body. CABIN is based on the network of networks approach that promotes inter-agency collaboration and data-sharing to achieve consistent and comparable reporting on fresh water quality and aquatic ecosystem conditions in Canada. The program is maintained by Environment and Climate Change Canada (ECCC) to support the collection, assessment, reporting and distribution of biological monitoring information. A set of nationally standardized CABIN protocols are used for field collection, laboratory work, and analysis of biological monitoring data. A training program is available to certify participants in the standard protocols. There are two types of sites in the CABIN database (reference and test). Reference sites represent habitats that are closest to “natural” before any human impact. The data from reference sites are used to create reference models that CABIN partners use to evaluate their test sites in an approach known as the Reference Condition Approach (RCA). Using the RCA models, CABIN partners match their test sites to groups of reference sites on similar habitats and compare the observed macroinvertebrate communities. The extent of the differences between the test site communities and the reference site communities allows CABIN partners to estimate the severity of the impacts at those locations. CABIN samples have been collected since 1987 and are organized in the database by study (partner project). The data is delineated by the 11 major drainage areas (MDA) found in Canada and each one has a corresponding study, habitat and benthic invertebrate data file. Links to auxiliary water quality data are provided when available. Visits may be conducted at the same location over time with repeat site visits being identified by identical study name / site code with different dates. All data collected by the federal government is available on Open Data and more partners are adding their data continually. The csv files are updated monthly. Contact the CABIN study authority to request permission to access non open data.

PURPOSE:Chlorophyll a is a photosynthetic pigment common to aquatic algae, and its measurement can provide an estimate of free-floating algae abundance in an aquatic system. For more than 40 years, the Fisheries and Oceans Canada - Great Lakes Laboratory for Fisheries and Aquatic Sciences (DFO-GLLFAS) office in Sault Ste. Marie Ontario has collected water samples for chlorophyll a spectrophotometric analysis, producing data in the form of mg/m3. The collection of chlorophyll a data was generally conducted to assist in characterizing the aquatic systems level of primary productivity, since that can influence fish abundance. This was a supplementary measure of the quality of fish habitat in these systems for a variety of fish-related projects of relevance to DFO’s mandate. Consistency of data collection was dependent on the duration of each project and funding available. DESCRIPTION:The initial study collected chlorophyll a data from the five lakes in the Turkey Lakes Watershed (TLW – Upper and Lower Batchawana Lakes, Wishart Lake, Little Turkey Lake and Turkey Lake) as well as Quinn Lake which is located outside of the TLW (see Smokorowski et al. 2006) in partnership with Environment and Climate Change Canada (ECCC) and Natural Resources Canada (NRCAN), as part of Canada’s Acid Rain Initiative. The TLW study was established in 1979 to evaluate the impacts of acid rain on terrestrial and aquatic ecosystems. This dataset encompasses chlorophyll a data collected from five lakes in the TLW and Quinn Lake (data also collected by the Canadian Wildlife Service and Environment and Climate Change Canada) from 1983 - 2010 with some gaps of varying duration (Webster et al., 2021). Note that an experimental habitat removal took place in some TLW lakes and Quinn Lake in 1999 and 2000. Specifically, in autumn of 1999, 50% of the coarse woody material was removed from the shorelines of Little Turkey Lake and Quinn Lake, and in autumn of 2000, 50% of the course woody material was removed from Wishart Lake shoreline (details available in Smokorowski et al., 2006). Methods Summary: Sampling was only conducted during the open water season and the frequency and extent of sampling frequency in each waterbody varied and was project- and funding-dependent. There are no chlorophyll a data for the years 1986, 1989 – 1990, 1996 – 1997, 2006-2007 and 2009.Sampling was accomplished by rinsing on site an appropriately-cleaned 1 L, brown-opaque polyethylene bottles at least three times. For hand draw samples, the bottle was immersed sub-surface (less than 0.5 meters) to collect the sample. Composite tube samples were collected using an integrated water sampling tube that collected epilimnion water from the entire water column to a depth of 5 meters. Up to five - 1 L (1000 mL) samples were collected per station and returned to the lab on ice. Each 1 L sample was filtered using glass fiber filters (Whatman GF/C, 42.5 mm) within one day of sampling, and then frozen prior to standard chlorophyll a analysis (American Public Health Association [APHA] 1985). From 1983-1998, Chlorophyll a concentrations (mg/L) was calculated based on APHA 1985; from 1998 to present the calculation was based on APHA (1998). The sample dataset information includes the georeferenced sampling locations, the raw data for chlorophyll a calculations, and the calculated chlorophyll a concentrations using both the APHA (1985) and APHA (1998) methods. This dataset was published in partnership with the Canadian Institute of Ecology and Evolution - Living Data Project, which was funded by a CREATE grant from the Natural Science and Engineering Research Council of Canada. We would like to recognize Caroline Dallstream for her effort in publishing this dataset. SAMPLING METHODS:Methods Summary: Sampling was only conducted during the open water season and the frequency and extent of sampling frequency in each waterbody varied and was project- and funding-dependent. There are no chlorophyll a data for the years 1986, 1989 – 1990, 1996 – 1997, 2006-2007 and 2009. See Sampling was accomplished by rinsing on site an appropriately-cleaned 1 L, brown-opaque polyethylene bottles at least three times. For hand draw samples, the bottle was immersed sub-surface (less than 0.5 meters) to collect the sample. Composite tube samples were collected using an integrated water sampling tube that collected epilimnion water from the entire water column to a depth of 5 meters. Up to five - 1 L (1000 mL) samples were collected per station and returned to the lab on ice. Each 1 L sample was filtered using glass fiber filters (Whatman GF/C, 42.5 mm) within one day of sampling, and then frozen prior to standard chlorophyll a analysis (American Public Health Association [APHA] 1985). From 1983-1998, Chlorophyll a concentrations (mg/L) was calculated based on APHA 1985; from 1998 to present the calculation was based on APHA (1998). The sample dataset information includes the georeferenced sampling locations, the raw data for chlorophyll a calculations, and the calculated chlorophyll a concentrations using both the APHA (1985) and APHA (1998) methods.USE LIMITATION:To ensure scientific integrity and appropriate use of the data, we would encourage you to contact the data custodian.

Greenland Sharks (Somniosus microcephalus) are estimated to have the highest longevity of any invertebrate (392 ± 120 years), making bycatch a significant concern (Nielsen et al. 2016). However, in the Newfoundland and Labrador (NL) region, accurate estimates of bycatch are not often available for the species (Simpson et al. 2021). To address this, species distribution models (SDMs) were generated to delineate habitat suitability for the species throughout the NL region in order to identify areas where a higher rate of bycatch is expected to occur.Observations of Greenland shark bycatch recorded by At-Sea Observers (ASOs) in NL (1983 – 2019), Spain (1999 – 2017), and by the Northwest Atlantic Fisheries Organization (NAFO) Secretariat (2014 – 2019) were compiled to generate a presence-only dataset. Multiple environmental variables were assessed for collinearity, and non-collinear variables (Bathymetry and mean monthly bottom temperature for March and November (1990 – 2015)) were retained for use in the SDM. MaxEnt (maximum entropy) software was used to model habitat suitability because it is a presence-only modelling program that is able to account for a lack of absence data by comparing the environmental conditions at occurrence locations to those at randomly selected background points. Overall, the results indicated that habitat suitability for Greenland Shark was highest in deeper waters along the shelf edge in NAFO Divisions 3OP, and the Laurentian Channel, but also extended along the edge of the Labrador shelf, the Grand Banks, and deeper areas along the continental shelf such as the Hawke Channel, Funk Island Deep, and the slopes of Saglek, Nain, and Hamilton Banks. Beyond the Economic Exclusive Zone (EEZ) and within the NAFO regulatory area (NRA), suitable habitat was also present within the Flemish Pass, and along the slope of the Flemish Cap and shelf edge in NAFO Divisions 3NO (Simpson et al. 2021). More detailed information can be found in Simpson et al. 2021.References:Nielsen, J., R. B. Hedeholm, J. Heinemeier, P. G. Bushnell, J. S. Christiansen, J. Olsen, C. B. Ramsey, R. W. Brill, M. Simon, K. F. Steffensen, J. F. Steffensen. 2016. Eye lens radiocarbon reveals centuries of longevity in the Greenland shark (Somniosus microcephalus). Science 353 (6300):702-704Simpson, M. R., Gullage, L., Konecny, C., Ollerhead, N., Treble, M.A., Nogueira, A., González-Costas, F. 2021. Spatial-temporal variation in Greenland shark (Somniosus microcephalus) bycatch in the NAFO Regulatory Area. NAFO SCR Doc. 21/028

Description:This dataset consists of monthly mean simulation results from Canada's three Oceans: the Atlantic, Pacific and Arctic from 2015 to 2017.Abstract from the report:A numerical ocean model with biogeochemistry has been developed for a domain that spans Canada's three oceans: the Atlantic, Pacific and Arctic. The domain extends to 26°N in the Atlantic and 44°N in the Pacific, and spans the full width of each basin as well as the whole of the Arctic Ocean. The resolution is moderate to high (≈0.25°, 75 levels). A series of simulations was conducted to assess the best choices for biogeochemical model parameters across the diverse regions, using a variety of validation data sets including satellite ocean colour (surface chlorophyll and particulate organic carbon, integrated primary production), surface underway pCO2, and depth profiles of oxygen and nitrate concentration from ships and Argo floats. In addition to parameter values, processes examined include interactive sediments, fluvial nutrients, light attenuation by fluvial coloured dissolved organic matter (CDOM), and iron limitation. The results indicate that the optimal parameter set is one that limits phytoplankton losses to grazing and other processes so as to ensure strong biological drawdown of dissolved inorganic carbon and nutrients in spring and summer; among the parameter sets tested both insufficient and excessive drawdown were observed. Sensitivity to other processes such as interactive sediments, fluvial nutrients or CDOM attenuation was weak in most regions. In some regions, attenuation by CDOM or sequestration of nutrients in the sediment can substantially reduce primary production and zooplankton biomass, and fluvial nutrients can cause localized reduction of pCO2 by as much as 60 μatm. Iron limitation has an effect on the model solution in regions generally considered iron-replete; building a model that successfully spans iron-limited and non-iron-limited domains will require complete and accurate specification of iron sources and sinks.

This dataset contains the abundance (per m²) and the biomass (mg dry per m²) of macrofauna (≥ 500µm) in eelgrass and adjacent bare soft sediments, collected at sites in the Atlantic of Nova Scotia from 2009 to 2013.Cite this data as: Wong M.C. Data of Benthic invertebrates in seagrass and bare soft sediments in Atlantic Nova Scotia Published May 2020. Coastal Ecosystems Science Division, Fisheries and Oceans Canada, Dartmouth, N.S. https://open.canada.ca/data/en/dataset/05d5f46a-7f19-11ea-8a4e-1860247f53e3Publications: Wong, M. C., & Dowd, M. (2021). Functional trait complementarity and dominance both determine benthic secondary production in temperate seagrass beds. Ecosphere. 12(11), e03794. https://doi.org/10.1002/ecs2.3794Wong, M. C. (2018). Secondary Production of Macrobenthic Communities in Seagrass (Zostera marina, Eelgrass) Beds and Bare Soft Sediments Across Differing Environmental Conditions in Atlantic Canada. Estuaries and Coasts, 41, 536–548. https://doi.org/10.1007/s12237-017-0286-2