This dataset was collected in support of a Competitive Science and Research Fund project (21-CC-05-06 Impacts of coastal acidification and climate change stressors on the Atlantic sea scallop: larval supply, recruitment and adaptive capacity to multiple global change drivers) lead by Fisheries and Oceans Canada (DFO). The objective of this research is to characterize coastal environmental conditions associated with scallop spawning and larval drift in Passamaquoddy Bay, New Brunswick. This dataset includes temperature, conductivity, salinity, sigma-theta, sea pressure, and depth information taken at weekly intervals at the sampling stations. In total, this dataset represents a total of 62 CTD profiles collected across 3 sampling stations over 22 sampling days from June to October 2022. Sampling stations were selected to compare scallop recruitment signals from Chamcook Harbour, a decommissioned scallop aquaculture site in Big Bay (MS-1077) and in the middle of Passamaquoddy Bay. Data were processed in accordance with instrumentation manufacturer guidelines and DFO Ocean Data and Information Section QAQC procedures. Cite this data as: Miller, E., Quinn, B., Azetsu-Scott, K., Childs, D., Gabriel, C-E., Newhook, M. 2025. Impacts of coastal acidification and climate change stressors on the Atlantic sea scallop. Published October 2025. Coastal Ecosystems Science Division, Fisheries and Oceans Canada, St. Andrews, N.B

The Beaufort Regional Environmental Assessment-Marine Fishes Project (2012-2014) and Canadian Beaufort Sea-Marine Ecosystem Assessment (CBS-MEA, 2017-present) conducted by Fisheries and Oceans Canada provide offshore surveys of marine fishes and ecosystems on the Canadian Beaufort Shelf and slope in August and early September. The projects focus on integrating oceanography, food web linkages, physical-biological couplings and spatial and inter-annual variability, within the context of ongoing climate-driven change including enhanced Ocean Acidification. Sampling was conducted from the F/V Frosti at stations along transects spanning 20-1000 m. Zooplankton was collected using a bongo or multi-net system in conjunction with oceanographic and biogeochemical sampling.

This data is used for referencing spatial and tabular Forest Resource Processing Facility information. Each facility has one or more processing sites, each dedicated to processing resources for a specific purpose. For example, a pulp, paper and paperboard facility has one processing site to produce pulp, and another one dedicated to producing paper. All facilities that use 1,000 cubic metres or more of forest resources in one year must have a facility licence. This data class has been remodeled in 2014 to make it more flexible as a stand-alone product.

**NOTE** This dataset is going to be replaced by the Data Catalogue layer: [Forest Inventory Ground Plots - Public Access](https://catalogue.data.gov.bc.ca/dataset/6d6d115f-4cc2-4141-909e-3344b3a72bcf) This new layer links to the updated database for all Forest Analysis and Inventory Branch ground sample plots. Growth and Yield dataset is a provincial data set that comprised of Permanent Sample Plots (PSP). Researchers such as GY modellers and those wanting to know the position of all samples will use the all status view to better understand the spatial distribution of historic measurement data including samples that are currently destroyed or inactive

Identification of significant concentrations of sponges in the Gulf of St. Lawrence biogeographic unit using Kernel density estimation (KDE).This method was applied to create a modelled biomass surface for each taxa and an aerial expansion method was permitted to identify significant concentrations. Only geo-referenced biomass data have been used to identify the “hot spots”. The borders of the areas were refined using knowledge of null catches and species distribution models. Predictive models were produced using a random forest machine-learning technique. For more details, please refer to this report: Kenchington, E., L. Beazley, C. Lirette, F.J. Murillo, J. Guijarro, V. Wareham, K. Gilkinson, M. Koen Alonso, H. Benoît, H. Bourdages, B. Sainte-Marie, M. Treble, and T. Siferd. 2016. Delineation of Coral and Sponge Significant Benthic Areas in Eastern Canada Using Kernel Density Analyses and Species Distribution Models. DFO Can. Sci. Advis. Sec. Res. Doc. 2016/093. vi + 178 p.http://waves-vagues.dfo-mpo.gc.ca/Library/40577806.pdfThe present layer only contains the analysis results for sponges. Purpose:As part of the Canada's commitment to the identification and protection of sensitive benthic marine ecosystems, maps of the location of significant concentrations of corals and sponges on the east coast of Canada were produced through quantitative analyses of research vessel trawl survey data, supplemented with other data sources where available. The taxa analyzed are sponges (Porifera), large and small gorgonian corals (Alcyonacea), and sea pens (Pennatulacea). However, only the sponges (Porifera) and sea pens (Pennatulacea) have been considered in the analysis concerning the Gulf of St. Lawrence biogeographic unit.

Climate

RESULTS opening's forest cover poylgons with silviculture component provided. Current forest cover subimssion into RESULTS must contain attribute and map information. However, there are historical forest cover polygon infomration where maps are not available. Forest Cover is provided at three critical milestones of at harvesting, at regeneration, and at free growing. This is a part o fthe Silviculture and Land Status Tracking dataset, which includes tracking achievement of silviculture obligations on Crown Land

Forest Total Aboveground Biomass 2015Total aboveground biomass. Individual tree total aboveground biomass is calculated using species-specific equations. In the measured ground plots, aboveground biomass per hectare is calculated by summing the values of all trees within a plot and dividing by the area of the plot. Aboveground biomass may be separated into various biomass components (e.g. stem, bark, branches, foliage) (units = t/ha). Products relating the structure of Canada's forested ecosystems have been generated and made openly accessible. The shared products are based upon peer-reviewed science and relate aspects of forest structure including: (i) metrics calculated directly from the lidar point cloud with heights normalized to heights above the ground surface (e.g., canopy cover, height), and (ii) modelled inventory attributes, derived using an area-based approach generated by using co-located ground plot and ALS data (e.g., volume, biomass). Forest structure estimates were generated by combining information from lidar plots (Wulder et al. 2012) with Landsat pixel-based composites (White et al. 2014; Hermosilla et al. 2016) using a nearest neighbour imputation approach with a Random Forests-based distance metric. These products were generated for strategic-level forest monitoring information needs and are not intended to support operational-level forest management. All products have a spatial resolution of 30 m. For a detailed description of the data, methods applied, and accuracy assessment results see Matasci et al. (2018). When using this data, please cite as follows: Matasci, G., Hermosilla, T., Wulder, M.A., White, J.C., Coops, N.C., Hobart, G.W., Bolton, D.K., Tompalski, P., Bater, C.W., 2018b. Three decades of forest structural dynamics over Canada's forested ecosystems using Landsat time-series and lidar plots. Remote Sensing of Environment 216, 697-714. Matasci et al. 2018)Geographic extent: Canada's forested ecosystems (~ 650 Mha)Time period: 1985–2011

All wetland polygons for the province

All double line river polygons for the province