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We have found 43 datasets for the keyword " gris". You can continue exploring the search results in the list below.
Datasets: 106,031
Contributors: 42
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43 Datasets, Page 1 of 5
Likelihood of Presence of Grey Seal in Area Response Planning Pilot Areas
Likelihood of Presence of Grey Seal in the Bay of Fundy and Port Hawkesbury Area Response Plan. The Coastal Oceanography and Ecosystem Research section (DFO Science) reviewed reported opportunistic sightings and local knowledge sources to estimate areas where Grey Seals are present and delineated these areas.A version of this dataset was created for the National Environmental Emergency Center (NEEC) following their data model and is available for download in the Resources section.Cite this data as: Lazin, G., Hamer, A.,Corrigan, S., Bower, B., and Harvey, C. Data of: Likelihood of presence of Grey Seal in Area Response Planning pilot areas. Published: June 2018. Coastal Ecosystems Science Division, Fisheries and Oceans Canada, St. Andrews, N.B. https://open.canada.ca/data/en/dataset/e73c90ff-0ab6-4257-8d6d-3dfc46fc0dc5
Counts of harbour seals (Phoca vitulina) and grey seals (Halichoerus grypus) from an aerial survey of the coast of the Newfoundland Shelf and Sandwich Bay, Labrador during the summer of 2021
Harbour seals reside throughout the year around Newfoundland and Labrador (NL). The first systematic survey for harbour seals occurred along the NL Shelf during July and August 2021 to obtain counts of hauled out individuals and assess distribution. Grey seals are seasonal residents in NL, mainly present in the summer and autumn months. Grey seals were also recorded during the survey as these two species can share haul-out locations. Surveys were flown along the coastline with a Bell 429 helicopter with photographs taken of hauled out seals. This data includes the counts of hauled out harbour, grey and unknown seals seen during the survey. Adjusted counts are also provided, which assign the unknown seals to species based on the number of positively identified harbour and grey seals from each survey day. The realized survey coverage (survey tracks) is also included. Cite this data as: Hamilton, C.D., Goulet, P.J., Stenson, G.B., and Lang, S.L.C. 2024. Data of: Counts of harbour seals (Phoca vitulina) and grey seals (Halichoerus grypus) from an aerial survey of the coast of the Newfoundland Shelf and Sandwich Bay, Labrador during the summer of 2021This data can be found in: Hamilton, C.D., Goulet, P.J., Stenson, G. B., and Lang, S.L.C. 2023. Counts and spatial distribution of harbour seals (Phoca vitulina) and grey seals (Halichoerus grypus) from an aerial survey of the coast of the Newfoundland Shelf and Sandwich Bay, Labrador during the summer of 2021. Can. Tech. Rep. Fish. Aquat. Sci. 3566: v + 39 p. https://publications.gc.ca/site/eng/9.927831/publication.html DFO. 20XX. Stock assessment of Atlantic harbour seals (Phoca vitulina vitulina) in Canada for 2019-2021. DFO Can. Sci. Advis Sec. Sci. Advis. Rep. 2023/XXX. Lang, S.L.C., St-Pierre, A.P., Hamilton, C.D., Mosnier, A., Lidgard, D.C., Goulet, P., den Heyer, C.E., Bordeleau, X., Irani, A.I., and Hammill, M.O. 20XX. Population status assessment and Potential Biological Removal (PBR) for the Atlantic harbour seal (Phoca vitulina vitulina) in Canadian waters. DFO Can. Sci. Advis. Sec. Res. Doc. 2024
Grey seal distribution and abundance in the Estuary and the Gulf of St. Lawrence, including Saguenay River
Data were collected during aerial surveys carried out at low tides in June and August 1994-1997, 2000 and 2001. June and August are respectively pupping and moulting seasons, when the haulout sites are intensively used by seals. Features in this layer show the Grey seal distribution and mean abundance for all aerial surveys (tables 4 and 6, figures 4 and 6 from Robillard et al. 2005). In the estuary, areas of high abundance have more than 25 individuals, areas of medium abundance have between 5 and 25 individuals and areas of low abundance have fewer than 5 individuals. In the Gulf, areas of high abundance have more than 70 individuals and areas of medium to low abundance have fewer than 70 individuals.Data are valid only during summer because Grey seals in the Estuary and northern Gulf migrate to the southern Gulf of St. Lawrence in the fall. These seals will spend the winter on Sable Island, on the ice shelf in the Northumberland Strait or on neighboring islands. During the summer, in the Estuary and the Gulf of St. Lawrence, its distribution is not uniform between the different concentration areas identified, but it is similar between June and August. However, there are some areas where Grey seals are more abundant in August than in June. Abundance classes are arbitrary but fit with the published results of haul-out sites utilization from Robillard et al. (2005). Data shown are a picture of the situation in 2005 because it is the most recent mapping available for this species.Data sources and references:Lavigueur, L., Hammill, M.O., and Asselin, S. 1993. Distribution et biologie des phoques et autres mammifères marins dans la région du parc marin du Saguenay. Rapp. manus. can. sci. halieut. aquat. 2220: vi + 40.Lesage, V., and Hammill, M.O. 2001. The status of the grey seal, Halichoerus grypus, in the Northwest Atlantic. Can. Field-Nat. 115(4): 653-662.Robillard, A., V. Lesage, and M.O. Hammill. 2005. Distribution and abundance of harbour seals (Phoca vitulina concolor) and grey seals (Halichoerus grypus) in the Estuary and Gulf of St. Lawrence, 1994–2001. Can. Tech. Rep. Fish. Aquat. Sci. 2613: 152 pp.
Monthly Climate Observation Summaries
A cross-country summary of the averages and extremes for the month, including precipitation totals, max-min temperatures, and degree days. This data is available from stations that produce daily data.
Range Units
A Range Unit is an administrative area established to assist in the management of the range program. Typically made up of one or more pastures. Generally, one or more Range Units make up a Stock Range
Atlas of Canada National Scale Data – Annual Minimum Snow and Ice (MSI) Extent Time Series
The Annual Minimum Snow and Ice (MSI) Extent of the Atlas of Canada National Scale Data, are data sets compiled containing annual data from 2000 to present. The data sets were derived from research published by the Canada Centre for Remote Sensing which classified satellite imagery over Canada and neighbouring regions for the continued presence or absence of snow and ice from April 1 to September 20 each year. The Atlas of Canada MSI products consist of a vector dataset and a raster time-series animation application.VECTOR DATASETThe vector dataset has been generalized to display at the scale of 1:1,000,000.TIME-SERIES ANIMATION APPLICATIONThe time-series animation application has not been generalized from its original scale (250 m pixels).The application is disseminated through the Data Cube Platform, implemented by the Canada Centre for Mapping and Earth Observation, Natural Resources Canada using geospatial big data management techniques. These technologies enable the rapid and efficient visualization of high-resolution geospatial data and allow for the rapid generation of dynamically derived products. The time-series is also available as a Web Map Service (WMS) and Web Coverage Service (WCS).CREDITSource data provided by Alexander P. Trishchenko, Canada Centre for Remote Sensing, Natural Resources Canada Metadata record: https://open.canada.ca/data/en/dataset/808b84a1-6356-4103-a8e9-db46d5c20fcf
Hydrogeological Information System (HIS)
The Hydrogeological Information System (HIS) contains the physical characteristics of wells and boreholes (location, depth, stratigraphy encountered, etc.) mainly from drilling reports transmitted by well drillers for groundwater sampling installations serving private drinking water residences. The geographic coverage corresponds to all of Quebec although most of the data are found in the south of the province. A monthly update is made.SIH data can be useful for hydrogeology professionals, the academic community and a wider audience in order to make interpretations on portions of territory, for example on the depth of the rock in a sector, or to consult more precise points of information such as the description of a specific identified well.**This third party metadata element was translated using an automated translation tool (Amazon Translate).**
CA Forest Wildfire (1985-2022)
Wildfire change year 1985-2022.Wildfire changes occurred from 1985 to 2022 displaying the year of greatest wildfire disturbance. It is developed within the framework of Canada’s National Terrestrial Ecosystem Monitoring System (NTEMS). The information outcomes represent 38 years of wildfires in Canada's forests, derived from a single, consistent, spatially explicit data source in a fully automated manner. Time series of Landsat data with 30 m spatial resolution were used to characterize national trends in stand replacing forest disturbances caused by wildfire for the period 1985-2022 for Canada's 650-million-hectare forested ecosystems.When using this data, please cite as: Hermosilla, T., M.A. Wulder, J.C. White, N.C. Coops, G.W. Hobart, L.B. Campbell, 2016. Mass data processing of time series Landsat imagery: pixels to data products for forest monitoring. International Journal of Digital Earth 9(11), 1035-1054. https://doi.org/10.1080/17538947.2016.1187673 (Hermosilla et al. 2016).See references below for an overview on the data processing, metric calculation, change attribution, and time series change detection methods applied, as well as information on independent accuracy assessment of the data..Hermosilla, T., Wulder, M. A., White, J. C., Coops, N.C., Hobart, G.W., (2015). An integrated Landsat time series protocol for change detection and generation of annual gap-free surface reflectance composites. Remote Sensing of Environment 158, 220-234. https://doi.org/10.1016/j.rse.2014.11.005 (Hermosilla et al. 2015a).Hermosilla, T., Wulder, M.A., White, J.C., Coops, N.C., Hobart, G.W., (2015). Regional detection, characterization, and attribution of annual forest change from 1984 to 2012 using Landsat-derived time-series metrics. Remote Sensing of Environment 170, 121-132. https://doi.org/10.1016/j.rse.2015.09.004 (Hermosilla et al. 2015b).Hermosilla, T., M.A. Wulder, J.C. White, N.C. Coops, G. W. Hobart, (2017). Updating Landsat time series of surface-reflectance composites and forest change products with new observations. International Journal of Applied Earth Observation and Geoinformation. 63,104-111. https://doi.org/10.1016/j.jag.2017.07.013 (Hermosilla et al. 2017).
Grizzly Bear Population Units
Boundaries identifying similar behavioural ecotypes and sub-populations of Grizzly bears. This dataset contains versions from multiple years. From 2018 on, NatureServe conservation concern ranking categories (e.g., Very Low, Low, Moderate, High, Extreme Concern) supersede the pre-2018 population status categories (e.g., Viable, Threatened, Extirpated) contained in the field STATUS. NatureServe conservation concern ranking categories reflect population size and trend, genetic and demographic isolation, as well as threats to bears and their habitats. The NatureServe conservation concern ranking fields are named CONSERVATION_CONCERN_RANK and CONSERVATION_CONCERN_DESC. Please view the attached PDF file for a summary of changes to this dataset from 2012 onward. To download only the 2018 units, in the link below, select the "Export" tab, then select the "Provincial Layer Download" button: https://maps.gov.bc.ca/ess/hm/imap4m/?catalogLayers=7744,7745 Grizzly Bear Conservation Ranking results table is available here: https://catalogue.data.gov.bc.ca/dataset/e08876a1-3f9c-46bf-b69a-3d88de1da725 Grizzly Bear population estimates from various years are available here: https://catalogue.data.gov.bc.ca/dataset/2bf91935-9158-4f77-9c2c-4310480e6c29 Grizzly Bear reports are available here: https://www2.gov.bc.ca/gov/content/environment/plants-animals-ecosystems/wildlife/wildlife-conservation/grizzly-bear
Adult Salmon Logbook Data Collected by Volunteer Anglers from Nova Scotian Rivers (SFA 18A, 18B)
PURPOSE: Adult salmon logbook data are collected annually from volunteer anglers on the Margaree River. These data are used as an input to the current model for predicting abundance of large and small salmon returns each season in the Margaree River (Breau and Chaput 2012). Logbook data used in the model come from in-season fishing. However, the dataset provided also includes early out-of-season fishing that was conducted by volunteer anglers under a scientific license issued by DFO. This early out-of-season early fishing began in 2015 as a pilot project and ran until 2023. DESCRIPTION: Tabularized data from logbooks of anglers in SFA 18A and 18B PHYSICAL SAMPLE DETAILS: LogbooksUSE LIMITATION: To ensure scientific integrity and appropriate use of the data, we would encourage you to contact the data custodian.
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