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We have found 62 datasets for the keyword "estuaires". You can continue exploring the search results in the list below.
Datasets: 105,253
Contributors: 42
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62 Datasets, Page 1 of 7
Bay Scale Assessment of Eelgrass Using Sidescan and Video - Cocagne 2008
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
Bay Scale Assessment of Eelgrass Beds Using Sidescan and Video - Bouctouche
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
Bay Scale Assessment of Eelgrass Beds Using Sidescan and Video - Tabusintac 2008
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
Marine Environmental Quality (MEQ) Dissolved Oxygen, Eelgrass and Nutrient Monitoring in Southern Gulf of St. Lawrence
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.
Bay Scale Assessment of Eelgrass Beds Using Sidescan and Video - Shippagan 2007
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
OD0148 Estuary Dissolved Oxygen Monitoring 2015 to 2021
The province of PEI has been monitoring dissolved oxygen in some Island estuaries since 2015.
Bay Scale Assessment of Eelgrass Beds Using Sidescan and Video - Richibucto 2007
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 - Richibucto 2007. Published: October 2017. Coastal Ecosystems Science Division, Fisheries and Oceans Canada, Dartmouth, N.S. https://open.canada.ca/data/en/dataset/ca7af8ba-8810-4de5-aa91-473613b0b38d
Inventory of macroalgae and benthic macroinvertebrates on the north shore of the Saint-Lawrence Estuary (2019)
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.
OD0149 Estuary Dissolved Oxygen Monitoring 2022
The province of PEI has been monitoring dissolved oxygen in some Island estuaries since 2015.
Community Aquatic Monitoring Program (CAMP) data for the Southern Gulf of St. Lawrence Dataset
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
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