Data set covers metrics and metadata related to wild collected copepods Calanus spp. (C. hyperboreus, C. glacialis, C. finmarchicus) and Metridia longa: - body size in prosome length [PL] - dry weight [DW] - lipid content (oil sac area [OSA] and oil sac volume [OSV]) Spatial coverage: North Atlantic sampling sites - Scotian Shelf (SS) - Gulf of Saint Lawrence (GSL) - Gulf of Maine-Georges Bank-Nantucket Shoals (GoM) - Newfoundland shelf (NFL) Cite this data as: Helenius LK, Head EJH, Jekielek P, Orphanides CD, Pepin P, Plourde S, Ringuette M, Walsh HJ, Runge JA, Johnson CL. Calanus spp. size and lipid content metrics in North Atlantic, 1977-2019. Published September 2022. Ocean Ecosystem Science Division, Fisheries and Oceans Canada, Dartmouth, N.S. https://open.canada.ca/data/en/dataset/72e6d3a1-06e7-4f41-acec-e0f1474b555b

8 sets of vertical aerial views (2096 photographs in total), showing the evolution of the territory of the Island of Montreal and its immediate surroundings from 1958 to 1975 (photos taken successively in 1958, 1962, 1964, 1964, 1966, 1966, 1966, 1966, 1966, 1966, 1966, 1966, 1969, 1969, 1971, 1973 and 1975). ATTENTION: For any use of these photographic archives, it is required that the credit mention be: “Archives de la Ville de Montréal”. See also the other sets of aerial views of Montreal Island: [Oblique views from 1925-1939] (https://donnees.montreal.ca/ville-de-montreal/vues-aeriennes-de-l-ile-de-montreal-1925-1935) [Vertical close-up views from 1947-1949] (https://donnees.montreal.ca/ville-de-montreal/vues-aeriennes-archives) [Oblique views from 1960-1992] (https://donnees.montreal.ca/ville-de-montreal/vues-aeriennes-obliques-de-l-ile-de-montreal-1960-1992)**This third party metadata element was translated using an automated translation tool (Amazon Translate).**

Natural areas abutting Lake Simcoe are areas of a continuous vegetation community class that have a minimum size of 1 ha and are wholly or partially within the 30 m buffer zone of the Lake Simcoe shoreline. These areas may be a narrow band of vegetation along the shoreline or larger areas, which extend a greater distance from the shoreline. As described in policy 6.31-SA, the MNR and the MOE will map the location of natural areas abutting Lake Simcoe.

A history of nearshore benthic surveys of Bras d’Or Lake from 2005 – 2011 is presented. Early work utilized drop camera and fixed mount sidescan. The next phase was one of towfish development, where camera and sidescan were placed on one platform with transponder-based positioning. From 2009 to 2011 the new towfish was used to ground truth an echosounder. The surveys were performed primarily in the northern half of the lake; from 10 m depth right into the shallows at less than 1 m. Different shorelines could be distinguished from others based upon the relative proportions of substrate types and macrophyte canopy. The vast majority of macrophytes occurred within the first 3 m of depth. This zone was dominated by a thin but consistent cover of eelgrass (Zostera marina L.) on almost all shores with a current or wave regime conducive to the growth of this plant. However, the eelgrass beds were frequently in poor shape and the negative impacts of commonly occurring water column turbidity, siltation, or possible localized eutrophication, are suspected. All survey data were placed into a Geographic Information System, and this document is a guide to that package. The Geographic Information System could be used to answer management questions such as the placement and character of habitat compensation projects, the selection of nearshore protected areas or as a baseline to determine long term changes. Vandermeulen, H. 2016. Video-sidescan and echosounder surveys of nearshore Bras d’Or Lake. Can. Tech. Rep. Fish. Aquat. Sci. 3183: viii + 39 p. Cite this data as: Vandermeulen H. Bay Scale Assessment of Nearshore Habitat Bras d'Or Lake. Published May 2022. Coastal Ecosystems Science Division, Fisheries and Oceans Canada, Dartmouth, N.S.

This layer represents areas where primary production is considered to be high. Primary production includes microscopic algal blooms, named phytoplankton, a food resource at the base of the food web of marine ecosystems. The knowledge of these zones can serve as a proxy to identify areas of the St. Lawrence where productivity is higher at different times of the year. Impacting his component may influence the rest of the life cycle in the affected area. Data were generated from the Gulf of St. Lawrence Biogeochemical Model (GSBM) developed by Dr. Diane Lavoie. This model makes it possible to calculate, using 10 variables, the primary production in each cell of the grid of the model. This calculation was done at a monthly resolution and a threshold was then applied to the data to keep only those cells where the estimated concentrations exceeded 20 mg C / m-2. This level of primary production is considered high. Additional Information Monthly mean primary production (mg C m-2) in the first 50 meters of the simulated surface with the three-dimensional CANOPA-GSBM numerical model over a period of 13 years (1998-2010). The Gulf of St. Lawrence Biogeochemical Model (GSBM) simulates biogeochemical cycles of oxygen, carbon and nitrogen, and the biological components that determine the dynamics of the planktonic ecosystem. The model has 10 state variables. The NPZD (nutrients, primary production, zooplankton, detritus) model includes both simplified herbivorous and microbial food chains typical of bloom and post-bloom conditions. The export of biogenic matter at depth is mediated by the herbivorous food web (nitrate, large phytoplankton (diatoms), mesozooplankton, particulate organic matter), while the microbial food web (ammonium, small phytoplankton, microzooplankton, dissolved organic matter) is mainly responsible for nutrient recycling in the euphotic zone. Nitrate is also supplied by rivers. The tight coupling between small phytoplankton growth and microzooplankton grazing, autochtonous nitrogen release and (dissolved organic nitrogen) DON remineralization to ammonium (NH4+) is used to represent the dynamic of the microbial food chain. Biological transfer functions are derived from bulk formulations using mean parameters found in the literature. Biological variables are calculated in nitrogen units and algal biomass and production converted to Chl a and carbon units using fixed stoichiometric ratios. Detrital particulate organic nitrogen (PON) gets fragmented to dissolved organic nitrogen (DON) as it sinks toward the bottom. The phytoplankton growth rate is a function of light and nutrient availability. The available light for phytoplankton growth is a function of sea-ice cover, Chl a and colored dissolved organic matter (CDOM). The GSBM biogeochemical model, coupled with the CANOPA regional circulation model, was used to produce the Chl a layer. The grid of the model is 1/12° horizontally (about 6 x 8 km), 46 layers vertical and covers the Gulf of St. Lawrence, Scotian Shelf and Gulf of Maine regions. The vertical resolution is variable (between 6 m close to the surface to 90 m at depths of about 500 m). This model includes tidal forcing and the freshwater supply of the St. Lawrence River and the many rivers in the region, as well as atmospheric forcing (temperature, wind, etc.) produced by an independent model (National Center for Environmental Prediction (NCEP) Climate Forecast System Version 2). In addition, the circulation model is coupled with a model of sea ice that reproduces the seasonality of the ice cover in the region. The temperature and salinity fields are produced freely by the model and only constrained by monthly climatologies of these conditions at the boundaries of the model domain. The simulation was carried out over a part of the period covering the Zonal Monitoring Program (AZMP) from 1998 to 2010.

The blue shark (Prionace glauca), is a species found in Atlantic Canadian waters which is commonly encountered in commercial and recreational fisheries. Pop-up Satellite Archival Tags (PSAT) and Smart Position and Temperature tag (SPOT) from Wildlife Computers were applied to blue sharks from 2004 to 2008 to collect data on depth (pressure), temperature and ambient light level (for position estimation). Deployments were conducted in Canada on commercial and recreational vessels from mid-August to early October, but mostly in September. A variety of tag models were deployed: PAT 4 (n=16), Mk10 (N=28), and SPOT3 (N=2) and 39 of 46 tags reported. The blue sharks tagged ranged in size from 124 cm to 251 cm Fork Length (curved); 30 were female, 15 were male and 1 was unknown sex. Time at liberty ranged from 4 – 210 days and 16 tags remained on for the programmed duration. Raw data transmitted from the PSAT’s after release was processed through Wildlife Computers software (GPE3) to get summary files, assuming a maximum swimming speed of 2m/s, NOAA OI SST V2 High Resolution data set for SST reference and ETOPO1-Bedrock dataset for bathymetry reference. The maximum likelihood position estimates are available in .csv and .kmz format and depth and temperature profiles are also in .csv format. Other tag outputs as well as metadata from the deployments can be obtained upon request from: warren.joyce@dfo-mpo.gc.ca or heather.bowlby@dfo-mpo.gc.ca.

Bay Scale Assessment of Nearshore Habitat Bras d'Or Lake - Chapel Island 2008 data is part of the publication Bay Scale Assessment of Nearshore Habitat Bras d'Or Lakes. A history of nearshore benthic surveys of Bras d’Or Lake from 2005 – 2011 is presented. Early work utilized drop camera and fixed mount sidescan. The next phase was one of towfish development, where camera and sidescan were placed on one platform with transponder-based positioning. From 2009 to 2011 the new towfish was used to ground truth an echosounder. The surveys were performed primarily in the northern half of the lake; from 10 m depth right into the shallows at less than 1 m. Different shorelines could be distinguished from others based upon the relative proportions of substrate types and macrophyte canopy. The vast majority of macrophytes occurred within the first 3 m of depth. This zone was dominated by a thin but consistent cover of eelgrass (Zostera marina L.) on almost all shores with a current or wave regime conducive to the growth of this plant. However, the eelgrass beds were frequently in poor shape and the negative impacts of commonly occurring water column turbidity, siltation, or possible localized eutrophication, are suspected. All survey data were placed into a Geographic Information System, and this document is a guide to that package. The Geographic Information System could be used to answer management questions such as the placement and character of habitat compensation projects, the selection of nearshore protected areas or as a baseline to determine long term changes. Vandermeulen, H. 2016. Video-sidescan and echosounder surveys of nearshore Bras d’Or Lake. Can. Tech. Rep. Fish. Aquat. Sci. 3183: viii + 39 p. Cite this data as: Vandermeulen H. Bay Scale Assessment of Nearshore Habitat Bras d'Or Lake - Chapel Island 2008. Published May 2022. Coastal Ecosystems Science Division, Fisheries and Oceans Canada, Dartmouth, N.S.

The data presented on this page concern the 2013-2014 mapping of temperature differences, the classification maps of these temperature differences (i.e. urban heat and freshness islands) and the map of the urban heat island intensity index. These different maps are detailed below: - The mapping of __Temperature differences in °C__ represents the temperature difference in the city compared to a nearby forest. It was produced at the scale of the Quebec ecumene (2016 census, 167,764 km2). This mapping, provided on a grid with a spatial resolution of 15 m, was carried out with a predictive machine learning model built on Landsat-8 satellite data provided by the *United States Geological Survey (USGS) * as well as from other geospatial variables such as hydrography and topography. - Mapping of classes of surface temperature differences, i.e. __Islands of urban heat and freshness (ICFU) * as well as from other geospatial variables such as hydrography and topography. - Mapping of classes of surface temperature differences, i.e. __Islands of urban heat and freshness (ICFU) __ was conducted for * [population centers from the 2021 census] ( https://www150.statcan.gc.ca/n1/pub/92-195-x/2021001/geo/pop/pop-fra.htm) * (CTRPOP) with at least 1,000 inhabitants and a density of at least 400 inhabitants per km2 to which is added a 2 km buffer zone. It thus covers all major urban centers, i.e. 14,072 km2. The method for categorizing ICFUs is the ranking of predicted temperature differences for each population center into 9 levels. Classes 8 and 9 are considered __Urban Heat Islands__ and classes 1, 2, and 3 as __Urban Freshness Islands__. The interval values for each class and population center are shown in the production metadata file. Since surface temperatures were analyzed at the Quebec ecumene scale, but the classification intervals were calculated for each population center individually, the differences in temperature grouped into the different classes vary from region to region. Thus, there are differences observed in the predicted temperature differences between North and South Quebec and according to urban realities. For example, a temperature difference of 2°C may be present in class 1 (cooler) in a population center located in southern Quebec, but may be present in class 9 (very hot) in a population center in northern Quebec. It is therefore important to interpret the identification of heat islands in relation to the relative temperature difference data produced at the Quebec ecumene scale. - The __Urban Heat Island Intensity Index (SUHII) __ map __ represents the Surface Urban Heat Island Intensity Index (SUHII) __ represents the Surface Urban Heat Island Intensity Index (SUHII) map __ represents the Surface Urban Heat Island Intensity Index (SUHII) __ map. This index is calculated for each * [dissemination island] (https://www150.statcan.gc.ca/n1/pub/92-195-x/2021001/geo/db-id/db-id-fra.htm) * (ID) of Statistics Canada included in the * [2021 census population centers] (https://www150.statcan.gc.ca/n1/pub/92-195-x/2021001/geo/pop/pop-fra.htm) * (CTRPOP) * () * (CTRPOP). It highlights areas with higher heat island intensity, by calculating a weighted average from temperature difference classes, giving more weight to the hottest classes. This weight is proportional to the class number (e.g. a class 9 surface is 9 times more important in the index than the same area with a class 1). These maps as well as those of * [2020-2022] (https://www.donneesquebec.ca/recherche/dataset/ilots-de-chaleur-fraicheur-urbains-et-ecarts-de-temperature-relatifs-2020-2022) * are used for the * [Analysis of change between the mapping of heat/freshness islands 2013-2014 and 2020-2022] (https://www.donneesquebec.ca/recherche/dataset/analyse-de-changement-ilots-chaleur-fraicheur-et-indice-intensite-ilots-chaleur-urbains) *. For more details on the creation of the various maps as well as their advantages, limitations and potential uses, consult the * [Technote] (https://www.donneesquebec.ca/recherche/dataset/ilots-de-chaleur-fraicheur-urbains-et-ecarts-de-temperature-relatifs-2013-2014/resource/0696b7d8-b02f-4fcf-9876-1a3cec0587cd) * (simplified version) and/or the * [methodological report] (https://www.donneesquebec.ca/recherche/dataset/ilots-de-chaleur-fraicheur-urbains-et-ecarts-de-temperature-relatifs-2013-2014/resource/a33969ba-143a-4524-88c3-8ec7485676b1) * (version complete). The production of this data was coordinated by the National Institute of Public Health of Quebec (INSPQ) and carried out by the forest remote sensing laboratory of the Center for Forestry Education and Research (CERFO), funded under the * [2013-2020 Climate Change Action Plan] (https://www.environnement.gouv.qc.ca/changementsclimatiques/plan-action.asp) * of the Quebec government entitled Le Québec en action vert 2020.**This third party metadata element was translated using an automated translation tool (Amazon Translate).**

McElhanney Consulting Services Ltd (MCSL) has performed a LiDAR and Imagery survey in southern Saskatchewan. The purpose was to generate DEMs for hydraulic modeling of floodplain, digital terrain maps, and other products for portions of the Swift Current Creek valley and other miscellaneous tributaries and related water course valleys in and around the City of Swift Current. The acquisition was completed between the 16th and 25th of October, 2009. The survey consisted of approximately 790 square kilometers of coverage. While collecting the LiDAR data, we also acquired aerial photo in RGB and NIR modes consisting of 1649 frames each. In addition to the main area of interest, McElhanney has acquired some LiDAR and photo of low lying areas adjacent to the project area. This additional area was acquired on speculation that the data may be required in the future. The 3Dimensional laser returns (point cloud) were classified using Microstation (v8), Terrascan and TerraModeler. A series of algorithms based on topography were created to separate laser returns that hit the ground from the ones that hit objects above the ground. Steps taken are: Classified LiDAR surface as Bare earth, Classified other features as non-bare earth or default, Formatted to ASPRS .LAS V1.1 (Class 1 - Default (non-bare earth), Class 2 – Ground points (bare earth)), 239 tiles each 2km x2km generated for LiDAR data, File prefix FF – Classified (Non-Bare Earth and Bare Earth), File Prefix BE – Bare Earth only, Bare Earth Model Key Point (MKPts) surface files are thinned Bare earth LiDAR points. MKPts files generate a virtually identical surface without the large file size, MKPts file format is ASCII (Easting Northing Z-elevation) xyz and LAS format.

This data set represents the interventions determined by the City of Montreal's Intervention Plan for the period 2016-2021. This planning includes both the infrastructure deficit and the maintenance needs during the period in question. The Intervention Plan is the result of a macroscopic analysis of physical and state data. Moreover, the capacity of the City and its boroughs to carry out is not unlimited; it is often determined by a combination of factors, including the availability of budgets, coordination needs, planning capacity as well as the capacity of the market to carry out this work. Consideration should also be given to the social and economic impacts of infrastructure work. These are all factors that may justify the delay of several interventions to later years. The data are available in the following documents: - The summary table shows the classes of integrated interventions of A, B, C or D for the unified sections. For each section, a recommendation on the work is indicated if necessary. These tables help managers identify priority segments and sections. If the dates of work of the assets in the same street section are different, the section is repeated as many times as there are different dates for the section. - The digital file presents the results of the Intervention Plan per unified section. This unit is the linear geometric element that supports the management data for all the infrastructure segments of the intervention plan. The division of the unified section is usually done at roadway intersections and easement limits. If the dates of work of the assets in the same street section are different, the section is repeated as many times as there are different dates for the section. - The integrated interventions map shows the opportunities for coordinating interventions between the three drinking water, sewage and road networks. For more information on water management in Montreal, consult [the City of Montreal's website] (https://montreal.ca/unites/service-de-leau). The 2023-2027 results are available on the page [Results of the Action Plan for the assets of drinking water, sewage and roads networks (2023-2027)] page (https://donnees.montreal.ca/dataset/resultats-plan-intervention-actifs-eau-voirie-2023).**This third party metadata element was translated using an automated translation tool (Amazon Translate).**