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Monthly mean salinity from Bedford Institute of Oceanography North Atlantic Model (BNAM) results were averaged over 1990 to 2015 period to create monthly mean climatology for the Northwest Atlantic Ocean, which can be considered as a representation of the climatological state of the Northwest Atlantic Ocean. The BNAM model is eddy-resolving, NEMO-based ice-ocean coupled North Atlantic Ocean model developed at the Bedford Institute of Oceanography (BIO) to support DFO monitoring programs. The data available here is monthly climatology for eight selected depths (surface, 110 m, 156 m, 222 m, 318 m, 541 m, 1062 m, bottom) in 1/12 degree spatial resolution. The data for each month from 1990 until present for the entire model domain ( 8°–75°N latitude and 100°W–30°E longitude) and various depths is available upon request. The 1990-2017 model hindcast result is compared with observational data from surface drifter and satellite altimetry. The model demonstrates good skill in simulating surface currents, winter convection events in the Labrador Sea, and the Atlantic Meridional Overturning Circulation as observed at 26.5°N and 41°N. Model results have been used to interpret changes in the Labrador Current and observed warming events on the Scotian Shelf, and are reported through the annual AZMP Canadian Science Advisory Secretariat Process. When using data please cite following: Wang, Z., Lu, Y., Greenan, B., Brickman, D., and DeTracey, B., 2018. BNAM: An eddy resolving North Atlantic Ocean model to support ocean monitoring. Can. Tech. Rep. Hydrogr. Ocean. Sci. 327: vii + 18p
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Vinsamlega hafið samband við Umhverfisstofnun vegna nánari upplýsinga.
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The Agri-Environmental Indicator (AEI) dataset series provides information that was created using indicators that assess the environmental impact of agricultural activities. These agri-environmental indicators integrate information on soils, climate and land surface features with statistics on land use and crop and livestock management practices. The datasets provide valuable, location-specific information on the overall environmental risks and conditions in agriculture across Canada and how these change over time. This dataset series collects AEI data that is related to geographic features and can be represented on a map. Other types of AEI data are not included. The datasets can be organized into the following major groups: • Farm land management • Soil health • Water quality • Air quality • Food and beverage industry (not included) Farm land management datasets: • Soil cover • Wildlife habitat • Farm land management (not included) Soil health datasets: • Soil erosion • Soil organic matter • Trace elements • Soil salinity Water quality datasets: • Nitrogen • Phosphorus • Coliforms • Pesticides Air quality datasets: • Greenhouse Gases • Ammonia • Particulate Matter
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To show the locations of campsites on Parks Canada sites, campsites administered by Parks Canada, or other campsites of interest to Parks Canada. Data is not necessarily complete - updates will occur weekly.
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Data from the analysis of sea surface temperature, sea surface salinity, bottom temperature, and bottom salinity, over the Gulf of Maine and Scotian Shelf, for 23 CMIP6 models. The analysis includes an evaluation of CMIP6 model performance for the CMIP6 historical (1950-2014) experiment. Future projections are summarized for CMIP6 scenarios SSP245 and SSP370 with the calculation of relative annual and seasonal changes between the historical period (1950-2014) and three future periods (2030-2039, 2040-2049, 2030-2049). Wang, Z., DeTracey, B., Maniar, A., Greenan, B., Gilbert, D. and Brickman, D., Future hydrographic state of the Scotian Shelf and Gulf of Maine from 23 CMIP6 models. Can. Tech. Rep. Hydrogr. Ocean. Sci. XXX: vii + XXXp. Cite this data as: Wang, Z., DeTracey, B., Maniar, A., Greenan, B., Gilbert, D. and Brickman, D. Future hydrographic state of the Scotian Shelf and Gulf of Maine from 23 CMIP6 Models. Published July 2022. Ocean Ecosystem Science Division, Fisheries and Oceans Canada, Dartmouth, N.S. https://open.canada.ca/data/en/dataset/6247bb5a-14b3-461d-9ed3-b42553107bbc
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To outline the locations of buildings on Parks Canada sites, buildings that Parks Canada manages, and other buildings of interest to Parks Canada. Polygon file to map building footprints of buildings on Parks Canada sites. Footprints may be derived by tracing the roof outline (for example from an airphoto) or using more detailed measurements of the ground floor. Data is not necessarily complete - updates will occur weekly.
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This point layer shows the locations of named places that fall within Parks Canada areas of interest. Data is not necessarily complete - updates will occur weekly.
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Line layer that shows the locations of lockstation gates. (See Gates_Barriers_Portails_Barrieres for other gates and fences). Data is not necessarily complete - updates will occur weekly.
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Funded through DFO's Strategic Program for Ecosystem-based Research and Advice (SPERA), this benthic survey covers several seabed areas adjacent to Deer Island and Campobello Island, the Wolves Islands, and Grand Manan (NB) over a two-year study period (2016-2017). One hundred and fifty drift camera transects were completed within the ~91 sq-km study region collecting continuous high-definition video with periodic 4K resolution video (provided by a downward facing Blackmagic Production Camera 4K equipped with video lights). A Nikon D800 36.1 megapixel digital still imagery camera (equipped with a studio strobe light) captured seafloor images at ~30s intervals over a maximum 25-minute drift survey period. The camera was triggered by lowering the camera frame within 1 m of the seabed, releasing tension on a trigger weight suspended below the frame. Camera location was tracked using an ultra-short baseline acoustic positioning system (Tracklink 1500HA transceiver with 1505B transponder on the camera frame). Species presence/absence, abundance, and bottom type was recorded manually using PhotoQuad v1.4 software. An average field of view of 0.7 x 0.5 m was determined from a subset of digital still images within which the 10 cm diameter trigger weight was fully in view. Thirty-eight key and common species were described using explicit taxonomic identifiers, while other species were recorded within broader general categories (e.g. unidentified Cnidaria). Identification was made to the lowest possible taxonomic level. Primary bottom-type was defined as the grain size with the most percent coverage for each image/video interval. Grain size limits were determined using the Wentworth scale. Cite this data as: Lawton P. Benthic Species Presence/Absence in the Lower Bay of Fundy Derived From High Resolution Video and Still Imagery. Published May 2022. Coastal Ecosystems Science Division, Fisheries and Oceans Canada, Dartmouth, N.S.
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Monthly mean currents from Bedford Institute of Oceanography North Atlantic Model (BNAM) results were averaged over 1990 to 2015 period to create monthly mean climatology for the Northwest Atlantic Ocean, which can be considered as a representation of the climatological state of the Northwest Atlantic Ocean. The BNAM model is eddy-resolving, NEMO-based ice-ocean coupled North Atlantic Ocean model developed at the Bedford Institute of Oceanography (BIO) to support DFO monitoring programs. The data available here is monthly climatology for eight selected depths (surface, 110 m, 156 m, 222 m, 318 m, 541 m, 1062 m, bottom) in 1/12 degree spatial resolution. The data for each month from 1990 until present for the entire model domain ( 8°–75°N latitude and 100°W–30°E longitude) and various depths is available upon request. The 1990-2017 model hindcast result is compared with observational data from surface drifter and satellite altimetry. The model demonstrates good skill in simulating surface currents, winter convection events in the Labrador Sea, and the Atlantic Meridional Overturning Circulation as observed at 26.5°N and 41°N. Model results have been used to interpret changes in the Labrador Current and observed warming events on the Scotian Shelf, and are reported through the annual AZMP Canadian Science Advisory Secretariat Process. When using data please cite following: Wang, Z., Lu, Y., Greenan, B., Brickman, D., and DeTracey, B., 2018. BNAM: An eddy resolving North Atlantic Ocean model to support ocean monitoring. Can. Tech. Rep. Hydrogr. Ocean. Sci. 327: vii + 18p