PURPOSE:To quantify impacts of nutrient and sediment loading to plant and animal communities and the environmental conditions that support them in estuaries of the Southern Gulf of St. LawrenceDESCRIPTION:The MEQ monitoring program is being implemented in 35-40 estuaries in the southern Gulf of St. Lawrence (sGSL) to support the development of a MEQ measure (threshold) to promote efforts to address nutrient enrichment in estuaries. The two main indicators included in the monitoring program are dissolved oxygen and eelgrass coverage which are used to assess the trophic status of estuaries within the region. The two factors most important for impacting the trophic status of estuaries are nitrogen loading and water residence time, i.e., water circulation. If water residence time is long and/or nitrogen loading is high, nutrient impacts are likely. A peer-reviewed manuscript has demonstrated that these two factors are predictive of the dissolved oxygen regime in the upper estuary and that publication successfully used dissolved oxygen to ascribe trophic status to estuaries. In a companion paper it was also determined that nitrogen loading was negatively correlated with eelgrass coverage. These two papers form the basis of the MEQ monitoring program (see attached). NOTES ON QUALITY CONTROL:Dissolved oxygen loggers require calibration prior to deployment and are checked for drift after retrieval (though drift isn't anticipated given optical sensor technology). In the event that dissolved oxygen loggers weren't cleared at a frequency sufficient to prevent data errors from occurring these data are removed prior to analysis. Additionally, data must be scrubbed of erroneous measurements which are relatively rare and very apparent. An error code of -888.88 is the primary error for dissolved oxygen loggers. Salinity probes rarely provide erroneous data and when they do it is typically the result of fouling.PHYSICAL SAMPLE DETAILS:Water is sampled bi-weekly to monthly using a Niskin water sampler at a depth of 0.5 m from the water surface, from May-November. Samples are processed in the laboratory in duplicate for chlorophyll a and seston within ~8 hours of being collected.SAMPLING METHODS:For each study estuary, dissolved oxygen is monitored continuously with optical dissolved oxygen loggers in the upper and mid-estuary. Tidal amplitude and salinity (NB and NS only) were also monitored at the upper estuary location only. Depth profiles for other water quality variables are taken at the bi-weekly or monthly scale as well as samples for seston (NB and NS only) and chlorophyll a (a proxy for phytoplankton). These parameters are monitored on a 3-year cycle except for two sites in PE and one site in NB and NS which are monitored annually: West and Wheatley, PE, Cocagne, NB and Pugwash, NS, respectively.Data is collected for eelgrass coverage by a collaborator between June-September, ideally during the same year we collect water quality data.Collaborators include the province of PEI’s Department of Environment, Water and Climate Change and the Southern Gulf of St. Lawrence Coalition on Sustainability.USE LIMITATION:To ensure scientific integrity and appropriate use of the data, we would encourage you to contact the data custodian.

A towfish containing sidescan and video hardware was used to map eelgrass in two shallow northern New Brunswick estuaries. The sidescan and video data were useful in documenting suspected impacts of oyster aquaculture gear and eutrophication on eelgrass. With one boat and a crew of three, the mapping was accomplished at a rate of almost 10 km2 per day. That rate far exceeds what could be accomplished by a SCUBA based survey with the same crew. Moreover, the towfish survey applied with a complementary echosounder survey is potentially a more cost effective mapping method than satellite based remote sensing.Cite this data as: Vandermeulen H. Data of: Bay Scale Assessment of Eelgrass Beds Using Sidescan and Video - Shippagan 2007. Published: November 2019. Coastal Ecosystems Science Division, Fisheries and Oceans Canada, Dartmouth, N.S. https://open.canada.ca/data/en/dataset/6454594e-c8f9-41c4-801a-db125b8a8875

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 Beds Using Sidescan and Video -Tabusintac 2008. Published: March 2021. Coastal Ecosystems Science Division, Fisheries and Oceans Canada, Dartmouth, N.S. https://open.canada.ca/data/en/dataset/d1c58bc6-69d4-47b2-bb19-988f88233900

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 Beds Using Sidescan and Video - Bouctouche. Published: November 2017. Coastal Ecosystems Science Division, Fisheries and Oceans Canada, Dartmouth, N.S. https://open.canada.ca/data/en/dataset/b4c83cd2-20f2-47d8-8614-08c1c44c9d8c

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

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.

This inventory, conducted from September 26th to October 3th, 2019, aimed to describe the community structure of macroalgae and benthic macroinvertebrates of five small estuaries of the Upper North Shore of Quebec, namely Barthélemy Bay and the Colombier, Mistassini, Franquelin and Saint-Nicolas rivers. This inventory is part of a doctoral study of Valentine Loiseau on the global changes in the St. Lawrence system, mainly the study of marine benthic communities in response to changes of salinity, to ensure proper management of the environment in the face of future changes. The main objective is to describe the structure and the levels of specific diversities of mediolittoral communities of benthic macroinvertebrates and macroalgae along a salinity gradient. These five small estuaries were selected because of their similar size, hard substrates and easy access. Three levels of hypoosmotic stress (low, medium, high) and one control level (seawater) were used for each of the selected estuaries, with eight quadrats per stress level. Quadrat positions were randomly selected but had to meet two criteria: (1) regular height in the foreshore to control the influence of other stresses (temperature, exposure); and (2) presence of at least one macroalga to maintain homogeneity. A percentage cover by macroalgal and macroinvertebrate species was estimated, and then all organisms were weighed by species and size group. The salinity of the nearest water point was measured at mid-tide with a portable refractometer and a Castaway-type CTD (Conductivity-Temperature-Density) probe. The inventory was done using a stratified random sampling design and the sampling unit was a quadrat measuring 25 x 25 cm. The three files provided (DarwinCore format) are complementary and are linked by the "eventID" key. The "event_information" file includes the generic information of the quadrat, including date and location. The "additional_information_event_and_occurrence" file includes salinity and substrate type of the quadrat, as well as the total weight of all individuals of the same species caught in the quadrat extrapolated to one square metre of surface. For nudibranchs and barnacles, weight was estimated from the size of the individuals so that they were not removed from the environment. The "taxon_occurrence" file includes the taxonomic inventory of macroalgal and benthic macroinvertebrate species observed in the quadrat, identified to the lowest possible species or taxonomic level and biomass by identified species.For quality control, organisms were identified on the field using the following guide: Chabot, Robert et Anne Rossignol. 2003. Algues et faune du littoral du Saint-Laurent maritime : Guide d'identification. Institut des Sciences de la mer de Rimouski, Rimouski ; Pêches et Océans Canada (Institut Maurice-Lamontagne), Mont-Joli. 113 pages. The taxonomy was checked against the World Register of Marine Species (WoRMS) to match recognized standards and using the R obistools and worrms libraries. The WoRMS match was placed in the "scientificNameID" field of the occurrence file. All sample locations were spatially validated. This project was funded by DFO Coastal Environmental Baseline Program under Canada’s Oceans 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.

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

The province of PEI has been monitoring dissolved oxygen in some Island estuaries since 2015.

The province of PEI has been monitoring dissolved oxygen in some Island estuaries since 2015.