The water level data comes from the groundwater monitoring network of Prince Edward Island (Canadian province). Each well in the observation network is equipped with a hydrostatic pressure transducer and a temperature sensor connected to a data logger. A second pressure transducer located above the water surface allows for adjusting the water level according to atmospheric pressure variations. The time series refers to the level below which the soil is saturated with water at the site and at the time indicated. The water level is expressed in meters above sea level (MASL). The dataset consists of a general description of the observation site including; the identifier, the name, the location, the elevation and a series of numerical values designating the water levels at a defined date and time of measurement.

GIS compilation of data used to perform the stacked cumulative chance of success (resource potential map) in Open file 8556. Natural Resources Canada (NRCan) has been tasked, under the Marine Conservation Targets (MCT) initiative announced in Budget 2016, with evaluating the petroleum resource potential for areas identified for possible protection as part of the Government of Canada's commitment to conserve 10% of its marine areas by 2020. As part of this initiative, NRCan's Geological Survey of Canada (GSC) conducted a broad regional study of the petroleum potential over the majority of the Magdalen Basin, which is the principal geological basin in the southern Gulf of St. Lawrence. The GSC resource assessment is visually represented by a qualitative petroleum potential map. Disclaimer: A simplified colored version of the map is displayed on the Web Mapping Service (WMS). The correct version is available for download through the Federal Geospatial Platform (FGP) and GEOSCAN.

“Prince Edward Island National Park - Total Ecosystem Forest Carbon Density” is the annual carbon density (tonnes carbon per hectare) within Prince Edward Island’s forested ecosystems over a 31-year period from 1990 to 2020. Total Ecosystem Forest Carbon Density includes aboveground and belowground biomass, soil carbon, and dead organic matter. Total Ecosystem Forest Carbon Density was estimated for 31 national parks using the Generic Carbon Budget Model (GCBM), a spatially explicit carbon budget model developed by Canadian Forest Service which uses forest inventory, disturbance, and mean annual temperature data along with yield data to estimate growth and merchantable volume for dominant tree species. Species- and Ecozone-specific equations are then used to convert merchantable volume to aboveground and belowground biomass carbon. Ecozones were classified according to Canada Ecological Land Classification Level 1. The GCBM simulates carbon dynamics to produce spatially explicit estimations of carbon stocks and fluxes. The model simulates and tracks carbon stocks, transfers between Intergovernmental Panel on Climate Change-defined pools, and other metrics including net ecosystem production, net biome production, and emissions of carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O) in annual time steps. The stocks and fluxes are also tracked by disturbance event (e.g., forest fires, insect outbreaks). Total Ecosystem Forest Carbon Density accounts for the effects of natural and anthropogenic disturbances, including wildfires, prescribed burns, and insect outbreaks. These products have a spatial resolution of 30m. This information is part of the Parks Canada Carbon Atlas Series. To obtain a copy of this report, please contact changementclimatique-climatechange@pc.gc.ca. When using this data, please cite as follows: Sharma, T., Kurz, W.A., Fellows, M., MacDonald, A.L., Richards, J., Chisholm, C., Seutin, G., Richardson, K., Keenleyside, K. (2023). Parks Canada Carbon Atlas Series: Carbon Dynamics in the Forests of Canada’s National Parks. Scientific Report. Parks Canada Agency, Gatineau, QC, Canada, 104 p.

“Prince Edward Island National Park - Total GHG Emissions” datasets consist of estimates of GHG emissions (carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O)) in carbon dioxide equivalents (CO2e) from forested ecosystems in Prince Edward Island National Park from 1990 to 2020 (tonnes carbon dioxide equivalent per hectare). Total GHG emissions for 31 national parks were estimated using the Generic Carbon Budget Model (GCBM), a spatially explicit carbon budget model developed by Canadian Forest Service which uses forest inventory, disturbance, and mean annual temperature data along with yield data to estimate growth and merchantable volume for dominant tree species. Species- and Ecozone-specific equations are then used to convert merchantable volume to aboveground and belowground biomass carbon. The GCBM simulates carbon dynamics to produce spatially explicit estimations of carbon stocks and fluxes. The model simulates and tracks carbon stocks, transfers between Intergovernmental Panel on Climate Change (IPCC)-defined pools, and other metrics including net ecosystem production, net biome production, and emissions of carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O) in annual time steps. The stocks and fluxes are also tracked by disturbance event (e.g., forest fires). Total GHG emissions include those from natural processes like respiration and decomposition and those due to natural and anthropogenic disturbances, including wildfires, prescribed burns, and insect outbreaks. These were calculated as the sum of CO2, CH4, and N2O emission estimates in tonnes carbon (tonnes C) generated by the GCBM. Emissions estimates were then converted to carbon dioxide equivalents (CO2e) using the 100-year Global Warming Potential (IPCC Fourth Assessment Report) factors for CH4 (25) and N2O (298). These products have a spatial resolution of 30m. This information is part of the Parks Canada Carbon Atlas Series. To obtain a copy of this report, please contact changementclimatique-climatechange@pc.gc.ca. When using this data, please cite as follows: Sharma, T., Kurz, W.A., Fellows, M., MacDonald, A.L., Richards, J., Chisholm, C., Seutin, G., Richardson, K., Keenleyside, K. (2023). Parks Canada Carbon Atlas Series: Carbon Dynamics in the Forests of Canada’s National Parks. Scientific Report. Parks Canada Agency, Gatineau, QC, Canada, 104 p.

As part of the development of a nationally-consistent sampling design within the Aquaculture Monitoring Program (AMP), this data reports mesozooplankton assemblages observed at nine coastal shellfish aquaculture sites, located across four DFO regions, with sampling across months, tide phases, and sampling locations. In most sites, strong spatial effects were observed, while tide effects were generally less important for structuring the mesozooplankton communities. Seasonality emerged as an essential factor to design an efficient monitoring program. This dataset represents the first large-scale Canadian coastal study using imaging technology for plankton taxonomic Identification. Cite this data as: Finnis, S., Guyondet, T., McKindsey, C.W., Arseneau, J., Barrell, J., Duhaime, J., Filgueira, R., Gallardi, D., Gaspard, D., Gibb, O., Goodwin, C., Hua, K., Macdonald, T., Milne, R., Lacoursière-Roussel, A. 2023. Guidance on sampling effort to monitor mesozooplankton communities at Canadian bivalve aquaculture sites using an optical imaging system. Can. Tech. Rep. Fish. Aquat. Sci. 3581: vii + 101 p

Most of the data were collected during aerial surveys carried out at low tides during 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 Harbour seal distribution and the mean abundance for all aerial surveys (tables 3 and 5, figures 3 and 5 from Robillard et al. 2005). In the estuary, areas of high abundance have more than 30 individuals, areas of medium abundance have between 10 and 30 individuals and areas of low abundance have fewer than 10 individuals. In the Gulf, areas of high abundance have more than 50 individuals and areas of medium to low abundance have fewer than 50 individuals. Unpublished data obtained from Parks Canada and Sepaq were also used to identify important haulout areas in the Saguenay Fjord sector and in Pointe-aux-Vaches tidal flat sectors, which have been categorized in this dataset as high abundance areas. Data are valid only during summer (except for the Pointe-aux-Vaches flats identified as mainly frequented in autumn by Parc Canada), because spring and fall distributions of the Harbour seal are unknown. Data shown in the Estuary and the Gulf of St. Lawrence are a picture of the situation in 2005 because it is the most recent mapping available for this specie. The distribution of the Harbour seal is non-uniform among the different concentration areas but is similar between June and August. However, Harbour seals tend to decrease their presence along the south shore and the Lower Estuary in August to the benefit of the Saguenay River colonies. Abundance classes are arbitrary but fit with the published results of haulout site utilization from Robillard et al. (2005). Data sources : Parks Canada. 2021. Personal communication. Harbor seal monitoring data on the Pointe-aux-Vaches tidal flat. Parks Canada and SÉPAQ, 2020. Données du suivi du phoque commun dans le fjord du Saguenay. Unpublished data. 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.

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.

This dataset corresponds to daily snow cover percentage at 1km resolution grid over land areas of Canada from 2006-2010. The data are subsampled by 4km to reduce data volumes and considering the geolocation uncertainty of the input satellite imagery. The daily maps are generated by assimilation of daily cloud screened NOAA AVHRR satellite imagery and Canadian Meteorological Centre (CMC) snow depth analysis snow depth and density fields within an off-line version of the CMC daily snow depth model. The snow depth model is modified to include snowpack reflectance model and a surface radiative transfer scheme that relates vegetation and snowpack reflectance to top-of-canopy bi-directional reflectance. A logistic vegetation phenology model is used to parameterize temporal dynamics of canopy leaf area index. A per-pixel particle filter with a 30 day moving window is applied to assimilation observations corresponding to 1km resolution visible band directional reflectance and normalized difference vegetation index and 24km CMC daily snow depth and monthly snow density fields. The assimilation is forced using daily air temperature and precipitation fields. Validation of the datasets has been performed by comparison to MODIS snow cover maps and in-situ snow depth stations across Canada. Validation suggests similar accuracy to MODIS snow cover products over relatively flat terrain. Validation over mountainous regions is ongoing.

Landsat Thematic Mapper (TM) and Enhanced Thematic Mapper (ETM+) sensors were used to generate the circa 2010 Mosaic of Canada at 30 m spatial resolution. All scenes were processed to Standard Terrain Correction Level 1T by the United States Geological Survey (USGS). Further processing performed by the Canada Centre for Remote Sensing included conversion of sensor measurements to top of atmosphere reflectance, cloud and cloud shadow detection, re-projection, selection of best measurements, mosaic generation ,noise removal and quality control. To provide a clear sky measurement for each location in Canada, data from the years 2009, 2010, and 2011 were used, but 2010 was preferentially selected. Bands 3 (0.63-0.69 µm), 4 (0.76-0.90 µm), 5 (1.55-1.75 µm), and 7 (2.08-2.35 µm) are provided in this version as significant atmosphere effects strongly limit the quality of the blue (0.45-0.52 µm) and green (0.52-0.60 µm) bands. Multi-criteria compositing was used for the selection of the most representative pixel. For ETM+ onboard Landsat 7 a scan line malfunction caused missing lines of data in all scenes collected after May 2003. Atmosphere and target variability between scenes cause these lines to have significant radiometric differences in some cases. A Fourier transformation approach was applied to correct this occurrence. This mosaic was developed for land cover and biophysical mapping applications across Canada. Other applications of these data are also possible, but should consider the temporal and spectral limitations of the product. Research to enhance the spatial, spectral and temporal aspects are in development for future versions of moderate resolution products from historical Landsat sensors, Landsat 8, and Sentinel 2 data.

The Moderate Resolution Imaging Spectroradiometer (MODIS ) is one of the most sophisticated sensors that is used in a wide range of applications related to land, ocean and atmosphere. It has 36 spectral channels with spatial resolution varying between 250 m and 1 km at nadir. MODIS channels 1 (B1, visible) and 2 (B2, near infrared) are available at 250 m spatial resolution, an additional five channels for terrestrial applications (bands B3 to B7) are available at 500 m spatial resolution, the other twenty-nine channels not included in this data set capture images with a spatial resolution of 1 km. The MODIS record begins in March 2000 and extends to present with daily measurements over the globe. This level 3 product for Canada was created from the following original Level 1 (1B) MODIS data (collection 5): a) MOD02QKM - Level 1B 250 m swath data, 5 min granules; b ) MOD02HKM - level 1B , 500 m swath data, 5 min granules; c) MOD03 - level 1 geolocation information, 1 km swath data, 5 min granules. All these data are available from the DAAC Earth Observing System Data Gateway (NASA http://ladsweb.nascom.nasa.gov/data/search.html). The terrestrial channels MODIS (B3 to B7) at 500 m spatial resolution were reduced to 250 m with an adaptive regression system and normalization described in Trishchenko et al. (2006, 2009), and the data were mapped using a Lambert Conformal Conic (LCC ) projection (Khlopenkov et al., 2008). These data were combined to form pan-Canadian images using a technique for detection of clear sky, clouds and cloud shadows with a maximum interval of 10 days (Luo et al., 2008). Atmospheric and sun-sensor geometry corrections have not been applied. For each date, data include forward and backward scattering observations as separate files. This allows data to be optimized for a given application. For general use, data from either forward or backward scattering or both should be used. Future release of the MODIS time series will correct the forward and backward scattering geometry to provide a single best observation for each pixel.