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We have found 28 datasets for the keyword "gaspésie". You can continue exploring the search results in the list below.
Datasets: 105,255
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28 Datasets, Page 1 of 3
Marsh inventory in the Chaleur Bay, the Estuary and the Gulf of St. Lawrence
Marsh inventory in the Chaleur Bay, the Estuary and the Gulf of St. Lawrence according to a literature review of documents produced between 1985 and 2002.Additional InformationThe marsh inventory was produced according to a literature review of the following documents:Bolduc, F. et P. Kaltenback. 1995. Caractérisation de l'habitat du poisson du banc de Portneuf et avenues de mise en valeur. Rapport présenté par Pro Faune à la Corporation de développement touristique de Rivière-Portneuf. 13 pages et annexes.Comité ZIP Baie des Chaleurs, 2002. Données numériques acquises suite à la cartographie de milieux humides Baie des Chaleurs pour le comité ZIP (printemps 2002).Comité ZIP Côte-Nord du Golfe. 2001. Inventaire du potentiel côtier et marin de la Basse-Côte-Nord. Version préliminaire de rapport sous forme de CD-ROM, Sept-Îles, mars 2001.Kedney, G. et P. Kaltenback. 1996. Acquisition de connaissances et mise en valeur des habitats du banc de Portneuf. Document réalisé par la firme Pro Faune pour le Comité touristique de Rivière-Portneuf. 50 pages et 5 annexes.Labrecque, J., G. Lavoie et F. Boudreau. 1995. Les plantes susceptibles d'être désignées menacées ou vulnérables du barachois de la rivière Malbaie, Barachois-Ouest, Gaspésie. Gouvernement du Québec, ministère de l'Environnement et de la Faune, Direction de la conservation et du patrimoine écologique, Québec. 20 p.Lemieux, C. 1995. Acquisition de connaissances des habitats côtiers dans la région de Rimouski (1995). Rapport du Groupe-Conseil GENIVAR présenté au Ministère des Pêches et des Océans du Canada, Division de la Gestion de l’Habitat du Poisson, 52 pages + 2 annexes.Lemieux, C. 2001. Projet de projection et de mise en valeur de la baie au Chêne et d'habitats côtiers de la région de Pointe-à-la-Croix (Gaspésie). Rapport du Groupe conseil Génivar inc. Présenté au Comité ZIP Baie des Chaleurs et au ministère de l'Environnement du Québec, direction du patrimoine écologique et du développement durable. 76 p. + 8 annexes.Lemieux, C. et R. Lalumière. 1995. Acquisition de connaissances des habitats côtiers du barachois de Saint-Omer. Rap. du Groupe conseil Genivar inc. pour la DGHP, MPO, 44 pages + 3 ann.Les consultants en environnement Argus inc. 1995a. Caractérisation physico-chimique et biologique de l'habitat du poisson du barachois de Malbaie: automne 1994. Rapport présenté au Club des ornithologues de la Gaspésie dans le cadre du programme Saint-Laurent Vision 2000. 62 p. + ann.Les consultants en environnement Argus inc. 1995b. Barachois de Malbaie: étude d'avant-projet de conservation et de mise en valeur. Rapport présenté au Club des ornithologues de la Gaspésie dans le cadre du programme Saint-Laurent Vision 2000. 71 p. + ann.Les consultants en environnement Argus inc. 1995c. Étude biophysique complémentaire de conservation et mise en valeur de la baie des Capucins. Rapport présenté à la corporation de développement de Les Capucins. 48 p. + ann.Les consultants en environnement Argus inc. 1998. Perspectives d'aménagement et de restauration des marais à spartine du Québec. Rapport final. En collaboration avec le Service canadien de la Faune (Environnement Canada), Pêches et Océans Canada, le Ministère des Transports du Québec et Canards Illimités inc. 123 pages + annexes et index cartographique.Létourneau, G. et M. Jean. 1996. Cartographie des marais, marécages et herbiers aquatiques le long du Saint-Laurent par télédétection aéroportée. Environnement Canada – Région du Québec, Conservation de l’environnement, Centre Saint-Laurent, Montréal. 101 pagesLétourneau, Guy. 1991. Milieux humides, Base de données Létourneau 1991 (de Cornwall à Trois-Pistoles et les Îles-de-la-Madeleine.Logimer. 1985. Développement d'un programme de conservation et de reconstitution des habitats lagunaires gaspésiens. Rapport présenté à Pêches et Océans Canada, section Habitat du poisson. 306 p. et annexes.Procéan inc. 1996. Caractérisation du milieu physique et inventaire biologique du barachois de New Richmond : rapport final. Présenté à la Division de la gestion de l'habitat du poisson, Pêches et Océans Canada par Procéan inc.Vaillancourt, M.-A. et C. Lafontaine. 1999. Caractérisation de la Baie Mitis. Jardins de Métis et Pêches et Océans Canada. Grand-Métis. 185 p.
Maximum Temperature (°C)
Maximum Temperature represents the highest recorded temperature value (°C) at each location for a given time period. Time periods include the previous 24 hours and the previous 7 days from the available date where a climate day starts at 0600UTC.
Range of distribution of the local woodland caribou population, mountain ecotype, Gaspesie population
## #Mise in custody and data use limits:* ** The report by Lesmerises and St-Laurent (2018) must be cited when using this file (see Literature section) . *** The distribution area of the mountain caribou population in Gaspésie in this file represents the state of knowledge on the use of land by mountain caribou between 1988 and 2016. * Information on the distribution of the local population does not make it possible to establish with certainty that caribou are absent in territories outside this range. * The range is subject to change, depending on new telemetry data that will be acquired, as our local knowledge is refined, and as caribou land use patterns change. ## #Description of the distribution area of the local woodland caribou population, mountain ecotype, Gaspésie populationThe data represent the distribution area of woodland caribou, mountain ecotype, population of Gaspésie (hereinafter mountain caribou of Gaspésie).The file contains the polygon and the name assigned to the population, the period covered by the telemetry data used during the delimitation exercise, and the date of the last update. The information contained in the file of occurrences of species in a precarious situation of the Quebec Natural Heritage Data Center (CDPNQ) is also present in the file (CDPNQ occurrence number, French, English and scientific name of the species, the type of occurrence, the rank of precariousness (rank S) and the status under the Act Respecting Threatened or Vulnerable Species, see MELCCFP 2023 for a description of these fields.).## #Contexte of the publicationThe Ministry of the Environment, the Fight against Climate Change, Wildlife and Parks (hereinafter MELCCFP) is responsible for the monitoring and management of mountain caribou in Gaspésie (Government of Quebec, 2021 a, b). The local population has been identified as the appropriate monitoring and management scale for this species since each population may face different threats depending on the habitat and socio-economic context in which it is found (Environment Canada, 2008). The local population is defined as a group of caribou occupying a defined territory that is spatially distinct from the territories occupied by other caribou groups. The dynamics of the local population are determined primarily by local factors influencing birth and mortality rates, rather than by the contributions or losses resulting from immigration or emigration between groups. As a result, the distribution area of the local population of mountain caribou in Gaspésie is defined as the geographic area where a group of individuals exposed to similar factors influencing their demographics live and which meets the needs of their life cycle during a given period of time (e.g. calving, rutting, wintering).In 2018, Lesmerises and St-Laurent produced the report *Influence of the rate of habitat disturbance, regional coyote abundance, and predator control on the demographic parameters of the Gaspesia-Atlantic caribou population* report presented to the Canadian Wildlife Service (Environment Canada). One of the objectives of the report was to delineate the range of this population. The MELCCFP uses the distribution area delimited by Lesmerises and St-Laurent (2018) as part of the monitoring and management of mountain caribou in Gaspésie. For any questions related to the Lesmerises and St-Laurent report (2018), please contact Mr. St-Laurent ([Martin-hugues_St-laurent@uqar.ca] (mailto: Martin-hugues_St-laurent@uqar.ca)).## #Méthodologie in a nutshellThe methodology presented here is a summary of that described in Lesmerises and St-Laurent (2018).Telemetry data from three follow-ups carried out during different periods of time were used (1988-1991, 1998-2008 and 2013-2016). The caribou were equipped with VHF collars during the first two follow-ups. Aerial flights were carried out at various times in order to locate the caribou. During the follow-up from 2013 to 2016, the caribou were equipped with GPS/Argos collars programmed to acquire locations every 2 or 3 hours depending on the collar model used. The range of the mountain caribou population in Gaspésie was defined by estimating a minimum convex polygon comprising 99% of telemetry locations plus a 10 km buffer zone. Finally, the parts superimposed on the St. Lawrence River were removed.## #LittératureEnvironment Canada. 2008. Scientific review for the identification of critical habitat for the boreal population of woodland caribou (*Rangifer tarandus caribou*) in Canada. August 2008. Ottawa: Environment Canada. 80 pp. + 192 pp. appendices.Government of Quebec. 2021 a. Monitoring system for forest caribou populations in Quebec and mountain caribou in Gaspésie 2020-2031: summary document, Ministry of Forests, Wildlife and Parks, Directorate of Expertise on Terrestrial Wildlife, Herpetofauna and Avifauna, 16 pp.Government of Quebec. 2021 b. Literature review on the factors involved in the decline of forest caribou populations in Quebec and mountain caribou in Gaspésie, Ministère des Forêts, de la Faune et des Parcs, Direction of expertise on terrestrial fauna, herpetofauna and avifauna, 244 pp. + 15p. appendicesLesmerises, F. and M.-H. St-Laurent. 2018. Influence of the rate of habitat disturbance, regional coyote abundance, and predator control on the demographic parameters of the caribou population in Gaspesia-Atlantique. Scientific report submitted to Environment Canada — Canadian Wildlife Service, Rimouski (Quebec). 22 pp. + 8 appendices.Ministry of the Environment, the Fight against Climate Change, Wildlife and Parks (MELCCFP). 2023. The Quebec Natural Heritage Data Center — Information document, Government of Quebec, Quebec, 32 pp.**This third party metadata element was translated using an automated translation tool (Amazon Translate).**
Heat Wave
Heat Wave represents the consecutive number of days (April 1 – October 31) where the maximum daily temperature is greater than 25 or 30 degrees respectively. Heat wave products are only generated during the Growing Season, April 1 through October 31.
Fire Burn Severity - Same Year
This layer is the current fire year burn severity classification for large fires (greater than 100 ha). Burn severity mapping is conducted using best available pre- and post-fire satellite multispectral imagery acquired by the MultiSpectral Instrument (MSI) aboard the Sentinel-2 satellite or the Operational Land Imager (OLI) sensor aboard the Landsat-8 and 9 satellites. Every attempt is made to use cloud, smoke, shadow and snow-free imagery that was acquired prior to September 30th. However, in late fire seasons imagery acquired after September 30th may be used. This layer is considered an interim product for the 1-year-later burn severity dataset (WHSE_FOREST_VEGETATION.VEG_BURN_SEVERITY_SP). Mapping conducted during the following growing season benefits from greater post-fire image availability and is expected to be more representative of tree mortality. #### Methodology: • Select suitable pre- and post-fire imagery or create a cloud/snow/smoke-free composite from multiple images scenes • Calculate normalized burn severity ratio (NBR) for pre- and post-fire images • Calculate difference NBR (dNBR) where dNBR = pre NBR – post NBR • Apply a scaling equation (dNBR_scaled = dNBR*1000 + 275)/5) • Apply BARC thresholds (76, 110, 187) to create a 4-class image (unburned, low severity, medium severity, and high severity) • Mask out water bodies using a satellite-derived water layer • Apply region-based filters to reduce noise • Confirm burn severity analysis results through visual quality control • Produce a vector dataset and apply Euclidian distance smoothing
Statistically downscaled scenarios of projected maximum temperature change
Statistically downscaled multi-model ensembles of projected change (also known as anomalies) in maximum temperature (°C) are available at a 10km spatial resolution for 1951-2100. Statistically downscaled ensembles are based on output from twenty-four Coupled Model Intercomparison Project Phase 5 (CMIP5) global climate models (GCM). Daily maximum temperature from GCM outputs were downscaled using the Bias Correction/Constructed Analogues with Quantile mapping version 2 (BCCAQv2). A historical gridded maximum temperature dataset of Canada (ANUSPLIN) was used as the downscaling target. Projected change in maximum temperature (°C) is with respect to the reference period of 1986-2005. Seasonal and annual averages of projected maximum temperature change to 1986-2005 are provided. Specifically, the 5th, 25th, 50th, 75th and 95th percentiles of the downscaled ensembles of maximum temperature change are available for the historical time period, 1901-2005, and for emission scenarios, RCP2.6, RCP4.5 and RCP8.5, for 2006-2100. Twenty-year average changes in statistically downscaled maximum temperature (°C) for four time periods (2021-2040; 2041-2060; 2061-2080; 2081-2100), with respect to the reference period of 1986-2005, for RCP2.6, RCP4.5 and RCP8.5 are also available in a range of formats. The median projected change across the ensemble of downscaled CMIP5 climate models is provided. Note: Projections among climate models can vary because of differences in their underlying representation of earth system processes. Thus, the use of a multi-model ensemble approach has been demonstrated in recent scientific literature to likely provide better projected climate change information.
Coal Agreements
Coal Agreement feature class contains provincial extent polygon features representing Coal applications, agreements, leases, and licences, with varying term dates and conditions. These applications and subsequent agreements give the holder the right to explore Coal.
Freshwater Atlas Glaciers
Glaciers and ice masses for the province, derived from aerial imagery flown in the late 1980s and early 1990s. Please refer to the [Glaciers](https://catalogue.data.gov.bc.ca/dataset/glaciers) dataset for recent glacier extents in British Columbia, and [Historical Glaciers](https://catalogue.data.gov.bc.ca/dataset/historical-glaciers) for a comparable historic view.
Manitoba LiDAR Tracker
The purpose of this dataset is to show end users where LiDAR data has been acquired by the Government of Manitoba.LiDAR (Light Detection and Ranging) is a remote sensing technology that uses lasers to collect accurate, continuous elevation data over relatively large areas. These data are essential for activities such as forestry, flood risk management, land use planning, and natural resources management. The Manitoba Government is increasingly acquiring LiDAR data across the province.This layer was created on August 5, 2009 by Manitoba Sustainable Development and was updated on August 9, 2021.To download LiDAR data from the Manitoba Land Initiative (MLI) site, follow this link: https://mli2.gov.mb.ca/dems/index_external_lidar.html Fields included ( Alias (Field Name): Field description.) ObjectID (OBJECTID) - Automatically generated feature numberAcquired (ACQUIRED) - LiDAR data capture dateContractor (CONTRACTOR) - Contractor nameContributor (CONTRIB) - Manitoba Government departmentName (NAME) - Dataset nameCellsize (CELLSIZE) - Raster DEM cell sizeMLI (MLI) - Data available for download on the Manitoba Land Initiative site
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.
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