PURPOSE:To gather localized high-quality data for mapping eelgrass distribution in bays and estuaries in the Gulf Region of Atlantic Canada.DESCRIPTION:Between 2018 and 2023, a total of 48 coastal sites in New Brunswick (NB), Prince Edward Island (PE), and Nova Scotia (NS) have been fully processed for eelgrass presence/absence and depth information.An additional 18 sites from the same region and time period (2018–2023) have data collected but not yet fully processed for depth and eelgrass classification. These sites will be incorporated into the dataset as processing is completed. PARAMETERS COLLECTED:Geographic coordinates, timestamp, submerged aquatic vegetation presence.NOTES ON QUALITY CONTROL:BioSonics Visual Aquatic was used to process raw dt4 files by delineating the bottom and submerged aquatic vegetation (SAV) heights. Initial delineation of the estuary bottom was performed using an automated algorithm within the software, followed by manual adjustments to refine the delineation as needed. An algorithm was then used to delineate vegetation, which was edited visually by referring to written ground-truthing notes and underwater photos taken with a GoPro underwater camera with GPS capacity. Expert advice within DFO was used to advise the analysts on best practices and subtleties in the echograms. All efforts were made to ensure vegetation mapped was eelgrass, but in some cases, such as where the acoustic response was not clear or ground-truthing notes were lacking, it is possible that other types of SAV were included.The processed data were exported from BioSonics Visual Aquatic aggregating sets of 10 pings that were in very close proximity. Grouped pings with a vegetation canopy height >= 0.1 m were assigned an eelgrass presence (i.e., "EG_Presence") value of "Y", while grouped pings with a height < 0.1 m were assigned a presence value of "N".SAMPLING METHODS:Acoustic data were collected during the summer or early fall season (varies depending on the site) by the Southern Gulf of St. Lawrence Coalition on Sustainability (Coalition-SGSL) in partnership with Fisheries and Oceans Canada (DFO) Gulf Region. At some sites, the Province of New Brunswick's Department of Agriculture, Aquaculture and Fisheries (NBDAAF) also collected data using their boat. BioSonics MX Aquatic Habitat Echosounder units with a single beam (8.7°) 204.8kHz transducer (mounting height varied depending on the boat used) was used for data collection by all parties. Positioning was achieved using the BioSonics internal GPS through 2020, then subsequently an external GPS unit (Hemisphere S631 RTK GPS) was used to improve positioning from 1-2m accuracy to ~20cm when differential was obtained. BioSonics Visual Acquisition software was used to collect the data.USE LIMITATION:This product is provided as-is and has not been accuracy-assessed against other data. Since there were no transect-independent ground-truthing points surveyed, the accuracy of any interpolated surfaces created from this data cannot be known.Not for use without inclusion of full metadata. The data products are supplied "as they stand" and DFO does not guarantee the integrity, the completeness, or the accuracy.There were issues with the internal GPS of the BioSonics unit, and their impact on positional accuracy has yet to be determined. Beginning in 2021, an external, higher precision GPS unit was used to increase accuracy.Use of various boats and surveyors, as well as analysts, can introduce some inconsistencies in the data collection and analysis between sites and years. Site-specific characteristics such as mixed submerged aquatic vegetation can complicate mapping efforts. Shallow areas can also be challenging to delineate accurately since the bottom and/or the vegetation can extend higher than the mounted transducer. In these cases, a best estimate was used by the analyst.Weather conditions such as wind can affect the accuracy of the results, as the transponder may pitch and roll with the boat, while increased sediment in the water can interfere with the signal. Single-beam acoustic data has a very small focus footprint, which varies with depth, so it should not be considered a comprehensive bottom mapping tool. However, it does provide valuable point data that can indicate presence of vegetation, canopy height, relative depth, and ground-truthing for other mapping techniques (e.g. aerial or satellite imagery). For example, at 1 m depth, the 8.6 degree single-beam used for this work has a footprint of approximately 0.0177 square metres, and at 2 m depth that footprint becomes 0.0711 square metres.

The excessive input of nitrogen derived from human land-use activities remains a major cause of the eutrophication of coastal ecosystems around the world. However, little data exist on rates of nutrient pollution or its potential impacts to coastal ecosystems in Atlantic Canada. To fill this knowledge gap, a Nitrogen Loading Model (NLM) framework was applied to determine the Total Nitrogen Load (kg TN / yr) from point and non-point source inputs (wastewater, atmospheric deposition, land use, fertilizer applications, and regional industries) in 109 coastal watersheds bordering the Bay of Fundy and Scotian Shelf. To evaluate the potential impact of nitrogen loading, two indicators were calculated for 40 coastal embayments: (1) ∆N, a measure of nitrogen residency that predicts dissolved oxygen problems; and (2) the estuary loading rate, a predictor of the potential for loss of submerged aquatic vegetation. This project was funded by Fisheries and Oceans Canada through a Strategic Program for Ecosystem-based Research and Advice (SPERA) grant. This research has been published in the scientific literature (Kelly et al. 2021). Kelly, N.E., Guijarro-Sabaniel, J. and Zimmerman, R., 2021. Anthropogenic nitrogen loading and risk of eutrophication in the coastal zone of Atlantic Canada. Estuarine, Coastal and Shelf Science, 263, p.107630. doi: https://doi.org/10.1016/j.ecss.2021.107630Cite this data as: Kelly, N.E., Guijarro-Sabaniel, J. and Zimmerman, R. Data of: Estimates of anthropogenic nitrogen loading and eutrophication indicators for the Bay of Fundy and Scotian Shelf. Published: February 2022. Coastal Ecosystems Science Division, Fisheries and Oceans Canada, Dartmouth, N.S. https://open.canada.ca/data/en/dataset/08746031-1970-4bf6-b6d4-3de2715c8634

This dataset is derived from analyses of photo samples obtained by deploying drop camera photo (DCP) systems conducted during various research surveys in coastal areas of the north shore of the St. Lawrence Estuary and the Gulf between Portneuf-sur-Mer and Sept-Îles between June and October of 2019 to 2022. It contains 4866 species occurrence data of 109 different taxa for epibenthic invertebrates and submerged aquatic vegetation (including algae) at depths ranging from 0 to more than 50 meters. Additional information about this dataset is available in the “Method step description” section.The research surveys were undertaken by the Department of Fisheries and Oceans Canada as part of the baseline program of the Ocean Protection Plan. This initiative aims to acquire environmental baseline data contributing to the characterization of important coastal areas and to support evidence-based assessments and management decisions for preserving marine ecosystems. Data acquired during the research surveys additionally include: 1) fish and invertebrate species occurrence data derived from analyses of video samples collected using a stereoscopic baited remote underwater camera video systems (stereo-BRUVs) 2) fish and invertebrates catch data from beam trawl sampling (occurrence and catch weights by species), 3) substrate classification based on drop camera samples, 4) oceanographic measurements of the water column from Seabird 19plus V2 profiling CTD (conductivity, temperature, depth, photosynthetic active radiation, pH, dissolved oxygen), 5) nutrients (NO2, NO3, NH4, PO4, SiO3) and dissolve organic carbon (DOC) concentrations, and 6) current speed and direction from tilt meters. The datasets of the first two elements will also be available as independent datasets on the OBIS/GBIF portal. To obtain data from items 3-6 and/or biological data collected on fish and invertebrate taxa, please contact David Lévesque or Marie-Julie Roux.The elaboration of conservation objectives based on an ecosystem assessment approach for fishery stock assessment requires the development of sampling methods to maximize the data collection on the ecosystem, while minimizing the impact on organisms and the marine environment. This project aims at characterising the coastal ecosystem of the St. Lawrence Estuary and Gulf between Portneuf-sur-Mer and Sept-Îles (QC), including the physico-chemistry of water, phytoplankton, zooplankton, submerged vegetation, benthic habitats as well as assemblages of fish and invertebrates. Sampling was performed by combining conventional methods such as CTD profiling, zooplankton nets, and beam trawl, with non-extractive methods such as drop camera photo (DCP) and stereoscopic baited remote underwater camera video systems (stereo-BRUVs). The data collected will help define baseline ecosystem conditions in the study area; explore the links between environmental conditions, habitat structure and biological assemblages; identify important habitats for marine species; as well as the evaluation of the performance of visual sampling methods compared to conventional methods. The results will make it possible to optimize the seasonal or annual monitoring in order to better understand the direct and indirect effects of human activities in coastal environments.Method Step Description: 1. Acquisition of photo samples in sequence: The drop camera photo (DCP) system used to sample underwater pictures is a stainless steel frame in the shape of a triangular prism of 50 cm wide, 100 cm long and 76 cm high at the level of the central eyelet. The sampling area is a quadrat of 0.25 m2 (interior dimensions of 50 cm by 50 cm). The system consists of two GoPro Hero 5 cameras (4000 × 3000 pixels) and two 8000 lumens dive lights (Big Blue VL8000). The first camera captures the elements located in the quadrat when viewed from above. The second camera offers an oblique view facilitating the evaluation of the elements present in the quadrat. At all sampling stations, five to nine system deployments (replicas) capturing photos every 10 seconds for 60 to 120 seconds were performed. Surveys took place between : June 28th to July 5th 2019July 13th to July 20th 2019September 30th to October 9th 2019August 10th to August 20th 2020October 1st to October 10th 2020April 22nd to May 5th 2021July 27th to August 10th 2021October 15th to October 24th 2021June 24th to Jully 5th 2022August 15th to August 26th 20222. Image analysis: A photo image analysis method with sequence (moving images) was used for the occurrence data extraction and organism counts; measurements were taken to obtain vegetation cover percentages and substrate analyzes were also carried out. Analyzes were performed with the open-source Fiji software from ImageJ. A quality/visibility rating was assigned to the analyzed image sequences. 3. Taxonomic approach: Epibenthic organisms were identified at the lowest possible taxonomic rank. A morphotype approach has been systematically used (during annotations) for the identification of sponges, hydrozoans and bryozoans, and occasionally for other organisms such as algae. Species codes were also used to distinguish certain species that could not be identified at the time of the annotations (see verbatim Identification). To eliminate observer bias, the same person analyzed all images used in this database. The organisms were identified from underwater images using a combination of identification guides and scientific papers.4. Open nomenclature: The concept of open nomenclature has been integrated into occurrence data to support taxonomic identifications with their level of certainty, as recommended by Horton et al., 2021. The abbreviation stet. (stetit) was used when the decision not to go lower was made but an identification might be possible, whereas indet (Indeterminabilis) was used when a lower level identification was considered uncertain or impossible (see identificationqualifier). In addition, the abbreviation Confer (cf.) was used and integrated into the data tables (see occurrenceRemarks) in order to link identifications that could potentially and/or possibly be associated.5. Remarks: Several remarks have also been incorporated (see organismRemarks, identificationRemarks and taxonRemarks), and are intended to provide additional information that may be useful to some data users; Please note that these sections could be modified or improved.6. Quality control: The taxonomic identifications were verified through a validation process, in collaboration with various expert taxonomists. All scientific names have been checked against the World Register of Marine Species (WoRMS) to match currently recognized standards. The WoRMS match was placed in the taxonID field of the instance file. Data quality control was performed using Robistools and worms packages. All sample locations were plotted on a map for visual verification that the latitude and longitude coordinates were within the described sample area.7. Data sharing: Only metadata and biodiversity occurrence data are shared in this dataset. The two files provided (DarwinCore format) are complementary and are linked by the "eventID" key. The "event" file includes generic event information, including date and location. The "occurrence" file includes the original identifiers of the observed organisms, identification comments and their taxonomy. A data dictionary is also provided to explain the fields used. For access to other data or images, contact David Lévesque.For more details about the project and the methodology, a technical report (Scallon-Chouinard et al., 2022) including sampling methods with drop camera photo systems (DCP) and stereoscopic baited remote underwater camera video systems (stereo-BRUVs) is currently available online (https://waves-vagues.dfo-mpo.gc.ca/library-bibliotheque/41081225.pdf); another technical report detailing photo and video image analysis methods will also be available.This project was funded by the Department of Fisheries and Oceans Canada as part of the baseline program of the Ocean Protection Plan.

This feature delineates forest and vegetation stands in the Yukon at a scale of 1:5,000. It is an operational level forest inventory (as opposed to a management level). This inventory has been completed in various stages, between 2013 and 2014, and delineation via softcopy from stereo images acquired in the years 2007 and 2012. The aerial images used for the Haines Junction region (Champagne and Aishihik Traditional Territory) had a ground sample distance (GSD) of 40 cm and were collected in both color and infrared. The aerial imagery in the southcentral Yukon were 1:40,000 black and white hard copy images, scanned at 60 microns or approximately 1m GSD.Distributed from [GeoYukon](https://yukon.ca/geoyukon) by the [Government of Yukon](https://yukon.ca/maps) . Discover more digital map data and interactive maps from Yukon's digital map data collection.For more information: [geomatics.help@yukon.ca](mailto:geomatics.help@yukon.ca)

This feature delineates forest and vegetation stands in the Yukon at a scale of 1:5,000. It is an operational level forest inventory (as opposed to a management level). This inventory has been completed in various stages, between 2013 and 2014, and delineation via softcopy from stereo images acquired in the years 2007 and 2012. The aerial images used for the Haines Junction region (Champagne and Aishihik Traditional Territory) had a ground sample distance (GSD) of 40 cm and were collected in both color and infrared. The aerial imagery in the southcentral Yukon were 1:40,000 black and white hard copy images, scanned at 60 microns or approximately 1m GSD.Distributed from [GeoYukon](https://yukon.ca/geoyukon) by the [Government of Yukon](https://yukon.ca/maps) . Discover more digital map data and interactive maps from Yukon's digital map data collection.For more information: [geomatics.help@yukon.ca](mailto:geomatics.help@yukon.ca)

Each summer, environmental community groups collect important data to determine if groupings of fish, shrimp and crab – what is called a community- can be used as an indicator of the health status of bays and estuaries. Sampling was conducted from May through September for the first years then from June through August. In 2018 and 2019, the sampling was conducted just once in each estuary. Community group members and staff sample six stations once a month in their designated estuary.Fish, shrimps and crabs are collected with a beach seine net and later released live back to the water once identified and counted. From this, the community groups provide important information to Fisheries and Oceans Canada, including:- identification and numbers of fish, shrimp and crab species;- water conditions and samples;- information on aquatic plants;- sediment samples.With this information, Fisheries and Oceans Canada scientists working with government agencies and universities can conduct analyses to determine the suitability of indicators to assess the health of bays and estuaries.PARAMETERS COLLECTED:Parameters: abundance, species richness, species developmental stage (young-of-the-year or adult), water temperature, water salinity, water dissolved oxygen, dissolved inorganic nutrient (nitrate, nitrite, phosphate), sediment % organic content, sediment % humidity content and sediment mean grain size, % submerged aquatic vegetation coverNOTES ON QUALITY CONTROL:Data entry into Excel and first quality control verification is done by CAMP summer students. A second quality control verification is done by DFO staff. See publ # 2823 attached to this record.In 2018, the historical data was migrated into a relationship database. From this year on, annual data will be entered into the database using a custom application. The application front end has numerous QC elements built-in.SAMPLING METHODS:Please see the following URL for sampling details: http://www.dfo-mpo.gc.ca/Library/319437.pdf

This dataset documents the epifauna occurrences collected from 2021 to 2024 during the Canadian Beaufort Sea Marine Ecosystem Assessment (CBS-MEA) conducted by the Department of Fisheries and Oceans (DFO). This scientific program focuses on the integration of oceanography, food web linkages, physical-biological couplings, and spatial and interannual variabilities. The program also aims to expand the baseline coverage of species diversity, abundances, and habitat associations in previously unstudied areas of the Beaufort Sea and Western Canadian Archipelago. The study took place mainly in the Canadian Beaufort Sea and the Amundsen Gulf. Sampling is done along transects at fixed stations in the study area. Catches are collected with a 3 m benthic beam trawl for 10 minutes bottom-contact time at a target speed of 2 knots and with a modified Atlantic Western IIA otter trawl for 20 minutes bottom-contact time at a target speed of 2.9 knots. A total of 32 stations were sampled for epifauna in 2021, 22 in 2022, 23 in 2023 and 22 in 2024, between 22-655 m depth. Epibenthic invertebrates were identified to the lowest taxonomic level possible and photographed. All unknown specimens are frozen. In the lab, the identifications are validated or refined with the photos and the frozen specimens.The data are presented in Darwin Core and are separated in two files:The "Activité_épifaune_CBSMEA_epifauna_event_en" file which contains information about missions, stations and deployments, which are presented under a hierarchical activity structure.The "Occurrence_épifaune_CBSMEA_epifauna_en" file that contains the taxonomic occurrences.

This dataset documents the infauna occurrences collected from 2021 to 2024 during the Canadian Beaufort Sea Marine Ecosystem Assessment (CBS-MEA) conducted by the Department of Fisheries and Oceans (DFO). This scientific program focuses on the integration of oceanography, food web linkages, physical-biological couplings, and spatial and interannual variabilities. The program also aims to expand the baseline coverage of species diversity, abundances, and habitat associations in previously unstudied areas of the Beaufort Sea and Western Canadian Archipelago. The study took place mainly in the Canadian Beaufort Sea and the Amundsen Gulf. Sampling is done along transects at fixed stations in the study area. Catches are collected using a 50 x 50 cm box-corer. Two or three box core are collected per station to obtain replicates. A total of 29 stations were sampled for infauna in 2021, 14 in 2022, 21 in 2023 and 24 in 2024 between 21-653 m depth. Half of the box corer (0.125 m2) is sampled for infauna taxonomy. The first 20 cm of sediment are collected and sieved through a 0.5 mm mesh sieve. The samples are preserved in seawater-formaldehyde solution (10 % v/v). In the lab, infauna is identified to the lowest taxon level possible.The data are presented in two files:The "endofaune_evenement_infauna_event_en" file which contains information about missions, stations and deployments, which are presented under a hierarchical activity structure.The "endofaune_occurrence_infauna_en" file that contains the taxonomic occurrences.

The Adaptive Management Framework for Yukon placer mining is complemented by traditional knowledge and monitoring of water quality objectives, aquatic health, and economic health. The aquatic health monitoring program is governed by the Aquatic Health Monitoring Protocol. The Protocol describes the locations, timing, frequency and methods employed during sampling, as well as the methods used to analyze sampling data. The Reference Condition Approach (RCA) is the method chosen for assessing the health of freshwater ecosystems in the Yukon. One RCA model was developed for bioassessment based upon benthic macroinvertebrates, and a second model was developed to assess the diversity of fish species. The RCA model for invertebrates relies upon 224 reference sites collected over the period 2004 to 2010 by the University of Western Ontario, Fisheries and Oceans Canada, and Yukon G overnment, using the same standard protocol. The invertebrate data set was analyzed at the family level. There are two fundamental steps in the process of developing the predictive model. The first is to classify the reference sites based on their biological characteristics. This requires defining a number of community types based on the taxonomic composition. The second step is to determine a subset of habitat attributes that are associated with those community types. Following this step the number and type of organisms expected to occur at any given site can be determined from habitat attributes. For more information, contact the Yukon Placer Secretariat.Distributed from [GeoYukon](https://yukon.ca/geoyukon) by the [Government of Yukon](https://yukon.ca/maps) . Discover more digital map data and interactive maps from Yukon's digital map data collection.For more information: [geomatics.help@yukon.ca](mailto:geomatics.help@yukon.ca)

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