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

This data is intended to identify Canadian Alternate Exchange Areas described in https://tc.canada.ca/en/marine-transportation/marine-safety/list-canada-s-designated-alternate-ballast-water-exchange-area-fresh-waters-tp-13617e-2021. The data is not intended for navigation purposes.According to Canada’s Ballast Water Regulations, if your vessel enters waters under Canadian jurisdiction from somewhere other than the U.S. waters within the Great Lakes Basin, and it cannot conduct a ballast water exchange in the areas set out in paragraphs 14(1)(a) and (b) of the regulations, then it will have to conduct a ballast water exchange in one of the areas listed below:-Gulf of St. Lawrence-Atlantic Canada-Western Canada-Canadian Eastern Arctic-Canadian Western Arctic: If you bring your vessel to a Canadian port, offshore terminal or anchorage area in the Western Arctic ballast water must be exchanged in an area as far away from shore as possible, where the water is more than 100 meters deep.Legal Constraints: Users should be aware that the polygons depicting ballast water exchange areas are intended for illustration only and should not be used for navigational or legal purposes.

Location and contact information for Pacific Recreational Fishery Salmon Head Recovery Depots.The sport fishing community has an important role in the recovery of coded-wire tags found in Coho and Chinook. A coded-wire tag is a 1mm piece of wire that is laser etched with a unique number. Tags are injected into the nose cartilage of juvenile salmon prior to ocean migration. Annually, Canada and the United States tag over 50 million juvenile salmon. Fisheries and Oceans Canada applies about 5.5 million tags, using about 5.5 kilometres of wire. Anglers can recognize the presence of a coded-wire tag because of the missing adipose fin (located on the dorsal surface of the salmon). If you have caught an adipose fin clipped Coho and Chinook, it is a simple matter of removing the head from the fish, completing a sport head label and then submitting the head to a Sport Head Recovery Depot in the area. It is just as important to turn in heads from terminal or freshwater sites as it is from marine areas. Even though anglers fishing close to hatcheries can be fairly certain of the origin of their catch, data will not be recorded unless the heads from fin-clipped recoveries are turned in. Without the data, the health of the stock and the value of the resource to anglers could be underestimated.

Description:Biophysical Units: Under the Pacific Marine Ecological Classification System (PMECS; DFO 2016; Rubidge et al. 2016), biophysical units are areas of distinct physiographic and oceanographic conditions and processes that shape species composition at spatial extents of 1000s of km. Geomorphic units:Geomorphic units or geozones are discrete geomorphological structures at the scale of 100s of km that are assumed to have distinctive biological assemblages (e.g., plateaus, ridges, seamounts, canyons). Although the spatial scale of geomorphic units is nested within biophysical units, a single geomorphic unit such as a trough may span more than one biophysical unit. The following 5 layers are included in this geodatabase:1. Biophysical_Units_L4A - Predicted PMECS Biophysical Units (Level 4A) output from the random forest analysis2. Biophysical_Units_L4B - Predicted PMECS Biophysical Units (Level 4B) output from the random forest analysis3. Biophysical_Units_ProbAssign_L4AB - Layer showing the probability that a grid cell was assigned to a given biophysical unit in the final random forest predictive modelling step4. Cluster_L4AB - Layer showing the output of species assemblage cluster analysis5. Geomorphic_Units - Geomorphic units for the BC coast that combines geomorphic units produced by Rubidge et al. 2016) and Proudfoot and Robb (2022).Methods:Biophysical Units:Rubidge et al. (2016) used a two-step process to identify biophysical units in British Columbia. First, a cluster analysis based on the similarity of species composition was used to group sites with similar species into distinct biological assemblages. Second, a random forest analysis was used to identify environmental correlates of the biological assemblages identified by the cluster analysis and to predict and assign the biological assemblage present in areas with too few biological data. Two different similarity thresholds were used to identify two levels (4A, 4B) of biophysical units; see Rubidge et al. (2016) for details. Indicator species for each assemblage (biophysical unit) were also identified.Geomorphic units:Rubidge et al. (2016) used the benthic terrain modeller (BTM) tool with broad and fine-scale benthic positioning index (BPI) parameters to define geomorphic units on the continental shelf in the Northern Shelf Bioregion and the continental slope in both the Northern Shelf Bioregion and Southern Shelf Bioregion. In 2022, geomorphic units were produced for the Strait of Georgia and Southern Shelf Bioregions following the same methods as Rubidge et al. (2016) (Proudfoot and Robb 2022). The geomorphic units produced as part of the PMECS process were merged with the geomorphic units produced for the Strait of Georgia and Southern Shelf bioregions to produce a continuous spatial data product representing geomorphic units for the Canadian Pacific continental shelf and slope. After merging, the geomorphic units produced in 2016 were unchanged (i.e., they are consistent with the original geomorphic units described in Rubidge et al. 2016).Data Sources:From Rubidge et al. (2016): Species data was taken from Fisheries and Oceans Canada (DFO) standardized fisheries-independent research surveys: groundfish trawl and long-line (2003-2013), Tanner Crab trawl and trap (2000–2006), and Dungeness Crab trap (2000–2014). Environmental data came from NASA, the Canadian Hydrographic Service, Fisheries and Oceans Canada, Bio-ORACLE, and elsewhere (details in Rubidge et al. 2016). From Proudfoot and Robb (2022): bathymetry data came from Natural Resources Canada (details in Proudfoot and Robb 2022).Uncertainties:The data is intended for use at the bioregional scale, and caution should be used for finer-scale analyses.

This is a spatial layer showing Ministry of Forests Radio Communication Sites. Communication Sites are physical land locations containing structures and equipment which provide two or one-way voice and or data wireless communications to field staff or for operational activities

This is a spatial layer showing Ministry of Forests Recreation Lines. These are the linear spatial representation for features such as recreation trails

Central lines for the layout of street sections.**Collection context** Maintenance by the geomatics division in collaboration with the engineering department.**Collection method** Computer-aided mapping.**Attributes*** `ASSET_ID` (`integer`): Identifier* `Odonym` (`varchar`): Odonym* `Jurisdiction` (`varchar`): Jurisdiction* `Status` (`varchar`): Status* `NIV_HIERARC` (`varchar`): Hierarchical level* `Circulation` (`varchar`): Traffic* `Coating` (`varchar`): Coating* `NB_VOIE` (`integer`): Number of channels* `LENGTH` (`numeric`): Length* `display_class` (`varchar`): Display class* `ODONYME_INT_A` (`varchar`): Odonym intersection A* `ODONYME_INT_B` (`varchar`): Odonym intersection B* `ADR_DEBUT_G` (`integer`): Address start left* `ADR_FIN_G` (`integer`): End left address* `ADR_DEBUT_D` (`integer`): Right start address* `ADR_FIN_D` (`integer`): Right end address* `NOTES` (`varchar`): Notes* `SOURCE` (`varchar`): Source* `DATE_CREATION` (`smalldatetime`): Created on* `DATE_MODIFICATION` (`smalldatetime`): Modified on* `USER_MODIFICATION` (`varchar`): Modified by* `ODO_LONG_COMPLETE` (`varchar`): Full long odonym* `ODO_INDEX_COURT` (`varchar`): Short index odonym* `ODO_INDEX_LONG` (`varchar`): Long index odonymFor more information, consult the metadata on the Isogeo catalog (OpenCatalog link).**This third party metadata element was translated using an automated translation tool (Amazon Translate).**

An administrative unit of forest land designated by the Minister, as authorized under Section 14(1) of the Forests Act.

High-resolution map of leading tree species distribution for Canada’s forested ecosystems (2019). Leading tree species map produced from a 2019 Landsat image composite, geographic and climate data, elevation derivatives, and remote sensing derived phenology following the framework described in Hermosilla et al. (2022). Regional classification models were generated based on Canada’s National Forest Inventory using a 150x150 km tiling system. The leading tree species are defined by representing the most voted tree species from the Random Forests classification models (i.e. the class with the highest class membership probability).The data represents leading tree species of Canada's forested ecosystems in 2019. An image compositing window of August 1 ± 30 days was used to generate the best-available-pixel (BAP) image composites utilized as source data for the classification.The science and methods developed to generate the information outcomes shown here, that track and characterize the history of Canada’s forests, were led by Canadian Forest Service of Natural Resources Canada, developed within the framework of Canada’s National Terrestrial Ecosystem Monitoring System (NTEMS), partnered with the University of British Columbia, augmented by processing capacity from Digital Research Alliance of Canada.For an overview on the data, image processing, and methods applied, as well as information on independent accuracy assessment of the data, see Hermosilla et al. (2022) https://doi.org/10.1016/j.rse.2022.113276When using this data, please cite as: Hermosilla, T., Bastyr, A., Coops, N.C., White, J.C., Wulder, M.A., 2022. Mapping the presence and distribution of tree species in Canada’s forested ecosystems. Remote Sensing of Environment 282, 113276.

Geotechnical reports are indexed within a database maintained by HPW-TEB Geotechnical Unit. Meta data associated to each geotechnical report are captured within this indexing table, including report reference number, title, author, highway and km start and end. The table has been modified to include columns that aid in georeferencing geotechnical reports. Added columns include route ID, Latitude, and Longitude. Transportation Engineering Branch is continually improving its geographical information systems with a major focus on creating linear referencing routes within ArcGIS. Georeferencing geotechnical reports will utilize the linear referencing routes in creating points and line shape files by referencing the highway number and km points or ranges as defined within the indexing table. Distributed from [GeoYukon](https://yukon.ca/geoyukon) by the [Government of Yukon](https://yukon.ca/maps). Discover more digital map data and interactive maps from Yukon’s digital map data collection.For more information: [geomatics.help@yukon.ca](mailto:geomatics.help@yukon.ca)