This dataset includes metrics of eelgrass size, cover, and biomass from field sites along the Atlantic coast of Nova Scotia, Canada. Field sites were located across a gradient of environmental conditions, and field sampling was conducted in July to August 2022. Eelgrass percent cover, shoot density, and plants were sampled at 10 haphazardly distributed sampling stations within each eelgrass bed at approximately the same depth. Stations were ~10m apart and at least 2m from any eelgrass-bare interface. At each sampling station eelgrass leaves in a 0.5 x 0.5m quadrat were photographed for later computer image analysis to determine percent cover. The number of shoots were then counted in a 0.25 x 0.25m quadrat, and 3 vegetative shoots were collected. Shoots were measured for leaf length, width, and weight in the laboratory. These data were used to determine allometric and cover-biomass relationships for use in non-destructive estimation of bed biomass. Cite this data as: Wong, M.C., & Thomson, J. A. Data of eelgrass (Zostera marina) plant size (length, width), cover, and biomass from the Atlantic Coast of Nova Scotia. Published: February 2025. Coastal Ecosystems Science Division, Maritimes Region, Fisheries and Oceans Canada, Dartmouth NS. For additional information please see: Thomson, J. A., Vercaemer, B., & Wong, M. C. (2025). Non-destructive biomass estimation for eelgrass (Zostera marina): Allometric and percent cover-biomass relationships vary with environmental conditions. Aquatic Botany, 198, 103853. https://doi.org/10.1016/j.aquabot.2024.103853

Cartography of the vegetation cover of Quebec City. The canopy represents the projection on the ground of the tops (crown) of trees (including leaves, branches, and trunks), which is visible from the sky. The data comes from an automated classification of two satellite images covering Quebec City by the pair of World-View-3 and Pléiades satellites acquired in July 2020 (spatial resolution of 31 cm) and from the 2017 Lidar survey of Quebec City.**This third party metadata element was translated using an automated translation tool (Amazon Translate).**

Identification of ecological and biological significant areas (EBSA) in the Estuary and the Gulf of St. Lawrence according to six groups of the food chain : primary production (Lavoie et al, 2007), secondary production (Plourde et McQuinn, 2010), meroplankton (Ouellet, 2007), benthic invertebrates (Chabot et al, 2007), demersal fishes (Castonguay et Valois, 2007) and pelagic fishes (McQuinn et al, 2012). The distribution area of each group has been evaluated using five criteria in order to determine the EBSA (DFO, 2004): 1. Uniqueness: Ranked from areas whose characteristics are unique, rare, distinct, and for which alternatives do not exist to areas whose characteristics are widespread with many areas which are similar. 2. Aggregation: Ranked from areas where most individuals of a species are aggregated to areas where individuals of the species are widespread 3. Fitness consequence: Ranked from areas where the life history activity(ies) undertaken make a major contribution to the fitness of the population or species present to areas where the life history activity(ies) undertaken make only marginal contributions to fitness. 4. Resilience: Ranked from areas where the habitat structures or species are highly sensitive, easily perturbed, and slow to recover to areas where the habitat structures or species are robust, resistant to perturbation, or readily return to the pre-perturbation state. 5. Naturalness: Ranked from areas which are pristine and characterized by native species to areas which are highly perturbed by anthropogenic activities and/or with high abundances of introduced or cultured species. Castonguay, M. and Valois, S. 2007. Zones d’importance écologique et biologique pour les poissons démersaux dans le nord du Golfe du Saint-Laurent. DFO Can. Sci. Advis. Sec. Res. Doc. 2007/014. iii + 34 p. Chabot, D., Rondeau A., Sainte-Marie B., Savard L., Surette T. et Archambault P. 2007. Distribution des invertébrés benthiques dans l’estuaire et le golfe du Saint-Laurent. DFO Can. Sci. Advis. Sec. Res. Doc. 2007/018. iii + 118 p. DFO, 2004. Identification of Ecologically and Biologically Significant Areas. DFO Can. Sci. Advis. Sec. Ecosystem Status Rep. 2004/006. Lavoie, D., Starr, M., Zakardjian, B. and Larouche, P. 2007. Identification of ecologically and biologically significant areas (EBSA) in the Estuary and Gulf of St. Lawrence: Primary production. DFO Can. Sci. Advis. Sec. Res. Doc. 2007/079. iii + 29 p. McQuinn, I.H., Bourassa, M-N., Tournois, C., Grégoire, F., and Baril, D. 2012. Ecologically and biologically significant areas in the Estuary and Gulf of St. Lawrence: small pelagic fishes. DFO Can. Sci. Advis. Sec. Res. Doc. 2012/087. iii + 76 p. Ouellet P. 2007. Contribution à l’identification de zones d’importance écologique et biologique (ZIEB) pour l’estuaire et le golfe du Saint-Laurent : La couche des oeufs et des larves de poissons et de crustacés décapodes. DFO Can. Sci. Advis. Sec. Res. Doc. 2007/011. iii + 76 p. (Mise à jour novembre 2010) Plourde, S. et McQuinn, I.A. 2010. Zones d’importance écologique et biologique dans le golfe du Saint-Laurent : zooplancton et production secondaire. DFO Can. Sci. Advis. Sec. Res. Doc. 2009/104. iv + 27 p.

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).**

Geometric and conventional representation of the hydrographic network. The 3D hydrographic layer is represented by several natural or physical elements associated with the presence of water. These elements form part of the layers in the digital cartographic compilation.**This third party metadata element was translated using an automated translation tool (Amazon Translate).**

From 1986 to 2000, a major ecological inventory program was carried out in the forests of southern Quebec in order to describe the diversity of forest ecosystems. In total, 28,425 ecological observation points (POE) were established on a territory covering 760,000 km2, located between 45° and 53° N latitude and 57° and 80° W longitude. The POE is a circular sampling unit that covers an area of 400 m². It collects data on the characteristics of forest stand (composition, structure), soil (texture, deposit, drainage), and topography, as well as location information. The coverage of each plant species in the plot is estimated visually. A detailed description of a soil profile is available in approximately 35% of POEs. The ecological classification elements of POEs (groups of indicator species, forest types, potential vegetation, ecological types, etc.) are determined using computerized identification keys using data on vegetation and the physical environment. The criteria used for this ecological classification are those presented in the guides for the recognition of ecological types. The levels of the ecological classification system of the territory are also determined for each POE.**This third party metadata element was translated using an automated translation tool (Amazon Translate).**

Nearshore marine construction activities often involve projects conducted directly in or adjacent to eelgrass beds and can have detrimental effects on eelgrass health, through physical destruction of beds, smothering of plants by sediment, and light reduction from turbidity. A liquefied natural gas (LNG) marine terminal is proposed to be constructed near Goldboro in Isaacs Harbour on the Eastern shore of Nova Scotia in an area where sediments are contaminated with heavy metals from historical goldmining tailings. We conducted a pre-impact assessment of the eelgrass beds in Isaacs Harbour and in adjacent contaminated and non-contaminated harbours. We used underwater video to precisely map the eelgrass bed in the direct construction footprint in Isaacs Harbour. We surveyed 169 stations along ~40 km of coastline from Wine Harbour to New Harbour to identify eelgrass presence or absence in the nearby region and provide data on the distribution and abundance of other sensitive fish habitat such as kelp and other macrophytes. Sediment samples were collected and analyzed for grain size, organic matter content and heavy metal contamination. We also collected eelgrass plants to assess plant condition using morphological and physiological metrics, and heavy metal contamination in plant tissues. The overall condition of eelgrass plants in the surveyed area fell within the range of healthy plant characteristics (morphometrics and carbohydrates reserves) seen elsewhere along the Atlantic coast. However, a few stations displayed high arsenic and mercury contamination in sediments, which translated in some cases to high contamination in eelgrass rhizomes and leaves. There would be significant risk of impact on benthic habitat and contamination of marine biota from resuspension of sediments during a construction and operation of a ship terminal in Isaacs Harbour. This pre-impact assessment will allow DFO to assess the LNG terminal construction proposal and develop appropriate mitigation and monitoring procedures. Collected data will also be used for habitat-forming species distribution modeling to inform marine spatial and conservation planning. Vercaemer, B., O’Brien, J. M., Guijarro-Sabaniel, J. and Wong, M. C. 2022. Distribution and condition of eelgrass (Zostera marina) in the historical goldmining region of Goldboro, Nova Scotia. Can. Tech. Rep. Aquat. Sci. 3513: v + 67 p. Cite this data as: Vercaemer, B., O’Brien, J. M., Guijarro-Sabaniel, J., Wong, M. Data of: Eelgrass (Zostera marina) study in the historical goldmining region of Goldboro, Nova Scotia (2020). Published: February 2023. Coastal Ecosystems Science Division, Fisheries and Oceans Canada, Dartmouth, N.S. https://open.canada.ca/data/en/dataset/ee88aa17-fd30-4d4a-8924-897fd47cf560

The data in this layer represents habitat suitability of soft-shelled clams (Mya arenaria) in the DFO Maritimes region, and was developed using an interdepartmental approach. Substrate classification data as well as bathymetric data for the Region were used to identify potential habitat for soft-shelled clams. Substrates identified as suitable included: sand, mud, sand and mud (Greenlaw, 2022). Contours (0m and 70m) from GEBCO bathymetric data were used to isolate depths between which soft-shelled clams are present. At this stage, a polygon reflecting soft substrates from 0-70m was created as "Suitable". A "Not Suitable" layer was similarly created using the substrates: boulders, continuous bedrock, discontinuous bedrock, gravel, mixed sediment, sand and gravel. To digitally validate the model, the Regional shoreline was divided into subsectors (developed by Environment and Climate Change Canada for the Canadian Shellfish Sanitation Program). Data from DFO (clam harvesting intensity) as well as Conservation and Protection (clam harvesting infraction locations) were used to established species presence within each sub-sector. If there had been any harvesting activity, legal or illegal, in an individual subsector, it was considered "Suitable and Validated". Merged into one final product, the model includes areas that are "Not Suitable", "Suitable", as well as "Suitable and Validated" for soft-shelled clam habitat. Cite this data as: Harvey, C., Vincent, M., Greyson, P., Hamer, A. (2024) Data of: A Soft-Shelled Clam (Mya arenaria) Habitat Suitability Model For The DFO Maritimes Region. Published: January 2024. Coastal Ecosystems Science Division, Fisheries and Oceans Canada, St. Andrews, N.B. https://open.canada.ca/data/en/dataset/c76f7813-d802-4b31-8ebe-476f8a7cacf2

Administrative boundaries of sectors, boroughs and cities.**This third party metadata element was translated using an automated translation tool (Amazon Translate).**

This record contains results from chemical analysis including suspended nitrogen (mg/g), suspended carbon (mg/g), and phosphorus (mg/g) based on dry weight sediment samples collected in the Beaufort Sea.