Peatlands include information relating to peatlands defined as a wetland, colonized by vegetation allowing the formation of a soil made of peat that is the result of the fossilization of organic matter.**This third party metadata element was translated using an automated translation tool (Amazon Translate).**

A towfish containing sidescan and video hardware was used to map eelgrass in two shallow northern New Brunswick estuaries. The sidescan and video data were useful in documenting suspected impacts of oyster aquaculture gear and eutrophication on eelgrass. With one boat and a crew of three, the mapping was accomplished at a rate of almost 10 km2 per day. That rate far exceeds what could be accomplished by a SCUBA based survey with the same crew. Moreover, the towfish survey applied with a complementary echosounder survey is potentially a more cost effective mapping method than satellite based remote sensing. Cite this data as: Vandermeulen H. Data of: Bay Scale Assessment of Eelgrass Beds Using Sidescan and Video - Richibucto 2007. Published: October 2017. Coastal Ecosystems Science Division, Fisheries and Oceans Canada, Dartmouth, N.S. https://open.canada.ca/data/en/dataset/ca7af8ba-8810-4de5-aa91-473613b0b38d

The National Ecological Framework for Canada's "Surficial Geology by Ecoprovince” dataset contains tables that provide surficial geology information with the ecoprovince framework polygons. It provides codes that characterize surficial geology (unconsolidated geologic materials) and their English and French-language descriptions as well as information about the area and percentage of the polygon that the material occupies.

Effective conservation planning relies on understanding population connectivity which can be informed by genomic data. This is particularly important for sessile species like the horse mussel (Modiolus modiolus), a key habitat-forming species and conservation priority in Atlantic Canada), yet little genomic information is available to describe horse mussel connectivity patterns. We used more than 8000 restriction-site associated DNA sequencing-derived single nucleotide polymorphisms and a panel of 8 microsatellites to examine genomic connectivity among horse mussel populations in the Bay of Fundy, along the Scotian Shelf, and in the broader northwestern Atlantic extending to Newfoundland. Despite phenotypic differences between sampling locations, we found an overall lack of genetic diversity and population structure in horse mussels in the Northwest Atlantic Ocean. All sampled locations had low heterozygosity, very low FST, elevated inbreeding coefficients, and deviated from Hardy-Weinberg Equilibrium, highlighting generally low genetic diversity across all metrics. Principal components analysis, Admixture analysis, pairwise FST calculations, and analysis of outlier loci (potentially under selection) all showed no independent genomic clusters within the data, and an analysis of molecular variance showed that less than 1% of the variation within the SNP dataset was found between sampling locations. Our results suggest that connectivity is high among horse mussel populations in the Northwest Atlantic, and coupled with large effective population sizes, this has resulted in minimal genomic divergence across the region. These results can inform conservation design considerations in the Bay of Fundy and support further integration into the broader regional conservation network. Cite this data as: Van Wyngaarden, Mallory et al. (2024). Widespread genetic similarity between Northwest Atlantic populations of the horse mussel, Modiolus modiolus. Published: May 2025. Coastal Ecosystem Science Division, Maritimes Region, Fisheries and Oceans Canada, Dartmouth, NS.

The blue whale (Balaenopterus musculus) is a wide-ranging cetacean that can be found in all oceans, inhabiting coastal and oceanic habitats. In the North Atlantic, little is known about blue whale distribution and genetic structure, and if whether animals found in Icelandic waters, the Azores, or Northwest Africa are part of the same population as those from the Northwest Atlantic. In the Northwest Atlantic, seasonal movements of blue whales and habitat use, including the location of breeding and wintering areas, are poorly understood. The behaviour of remotely-monitored animals can be inferred from a time series of location data. This is because animals tend to demonstrate stochasticity in their movement paths as a result of spatial variation in environmental characteristics, such as topography or prey density (Curio 1976; Gardner et al. 1989; Turchin 1991; Wiens et al. 1993). Predators are expected to decrease travel speed and/or increase turning frequency and turning angle when a suitable resource, e.g., food patch, is encountered (Turchin 1991), otherwise known as area-restricted search (ARS). In contrast, animals in transit or travelling tend to move at faster and more regular speeds, with infrequent and smaller turning angles (Kareiva and Odell 1987; Turchin 1998). Based on satellite telemetry to track the seasonal movements of 24 blue whales from eastern Canada in 2002 and from 2010 to 2015, it was possible to estimate trajectories and locations where ARS behaviour of blue whales was inferred at a 4h time interval. To assess blue whale movements and behavior, a Bayesian switching statespace model (SSSM) was applied to Argos-derived telemetry data (Jonsen et al. 2005; Jonsen et al. 2013). An SSSM essentially estimates animal location at fixed time intervals, movement parameters and behavioral patterns. Two important sources of uncertainty can be measured separately: estimation error resulting from inaccurate observations (Argos location error) and process variability linked to the stochasticity of the movement process (behavior mode estimation) (Jonsen et al. 2003; Patterson et al. 2008). The points visible on land are the result of errors in the Argos geographic position calculation. They have been deliberately left unchanged to assess the performance of the model, which was able to clean up some positions, but not all. Lesage, V., Gavrilchuk, K., Andrews, R.D., and Sears, R. 2016. Wintering areas, fall movements and foraging sites of blue whales satellite-tracked in the Western North Atlantic. DFO Can. Sci. Advis. Sec. Res. Doc. 2016/078. v + 38 p.

This dataset reports on lobster abundance and individual biological characteristics (size, sex, shell hardness, egg status), along with seabed substrate information, collected at various coastal sites in the Bay of Fundy, Canada. Surveys were conducted over a 40-year period between 1982 and 2021. Survey areas and SCUBA dive sites were located around Grand Manan Island, Deer Island, Campobello Island, and along the Bay of Fundy’s New Brunswick shore stretching from Passamaquoddy Bay, east to Maces Bay. One survey area was located on the Bay of Fundy’s southern shore (Nova Scotia) in the Annapolis Basin (Lawton et al. 1995). The data represent a compilation of SCUBA diving surveys (1003 belt transects) conducted directly by Fisheries and Oceans Canada (DFO) scientific SCUBA divers (1982-2019), or by contracted commercial divers funded in association with outside collaborating organizations; Department of Fisheries and Agriculture (DFA; 1990 – 1993), the Grand Manan Fishermen’s Association (GMFA; 2013-2015), and the University of New Brunswick (UNB; 2019-2021). Cite this data as: Lawton P, Dinning K, Rochette R, Teed L. American lobster (Homarus americanus) abundance and biological characteristics collected from SCUBA dive surveys in the Bay of Fundy from 1982-2021. Published August 2024. Coastal Ecosystems Science Division, Fisheries and Oceans Canada, St. Andrews, N.B. For additional information please see: Campbell, A. 1990. Aggregations of berried lobsters (Homarus americanus) in shallow waters off Grand Manan, eastern Canada. DFO Can. J. Fish. Aquat. Sci. 47: 520-523. Denton, C.M. 2020. Maritimes Region Inshore Lobster Trawl Survey Technical Description. DFO Can. Tech. Rep. Fish. Aquat. Sci. 3376: v + 52 p. Lawton, P. 1993. Salmon aquaculture and the traditional invertebrate fisheries of the Fundy Isles region: habitat mapping and impact definition: Cooperation Agreement on Fisheries and Aquaculture Development. Submitted by Peter Lawton to the New Brunswick Department of Fisheries and Aquaculture, 84 p. Unpublished monograph. Available from Fisheries and Oceans Canada Library, Dartmouth, NS (Monographs: SH 380.2 .C2 .L39 1992). https://science-catalogue.canada.ca/record=3943769~S6 Lawton, P., Robichaud, D.A., and Moisan, M. 1995. Characteristics of the Annapolis Basin, Nova Scotia, lobster fishery in relation to proposed marine aquaculture development. DFO Can. Tech. Rep. Fish. Aquat. Sci. 2035: iii + 26 p. Lawton, P., Robichaud, D.A., Rangeley, R.W., and Strong, M.B. 2001. American Lobster, Homarus americanus, population characteristics in the lower Bay of Fundy (Lobster Fishing Areas 36 and 38) based on fishery independent sampling. DFO Can. Sci. Advis. Sec. Res. Doc. 2001/093. Wentworth, C.K. 1922. A Scale of Grade and Class Terms for Clastic Sediments. The Journal of Geology 30(5): 377-392. Dinning, K.M., Lawton, P., and Rochette, R. 2025. Increased use of mud bottom by juvenile American lobsters (Homarus americanus) in Maces Bay and Seal Cove, Bay of Fundy, after three decades of population increases and predator declines. Canadian Journal of Fisheries & Aquatic Sciences 82; https://doi.org/10.1139/cjfas-2023-0312

Funded under DFO's Marine Conservation Targets Program in partnership with the Huntsman Marine Science Centre (HMSC), this diver-based imagery and sample collection benthic survey documents the occurrence of sponges at 42 dive sites in the Eastern Shore Islands (ESI) Area of Interest (AOI, ~2089 km2) off the Atlantic coast of Nova Scotia, Canada from dive surveys conducted in summer 2021 and 2022. Water quality, species occurrences and counts, habitat, slope, and substrate characteristics were catalogued through diver log sheets, camera imagery, specimen vouchers, and high-resolution bathymetric data. A total of 54 dives to depths from 11 to 33 m (below sea level), collecting up to 147 still images, one-hour of video, and 17 specimen samples per site, resulted in 220 observations for 27 different sponge taxa. This included three new records for Canada (Hymedesmia stellifera, Plocamionida arndti, Hymedesmia jecusculum) and a range extension for a species new to science (Crellomima mehqisinpekonuta) which was recently described from the Bay of Fundy. There were also four species which may seem to be new to science (Halichondria sp., Hymedesmia sp., Protosuberires sp., and Sphaerotylus sp.). Sponges were found to occupy a diversity of micro-habitats, often several different ones in proximity. A total of eight distinct habitat classes were defined, based on varying abundances and diversity of sponges and associated benthic species. These are likely widely distributed among the many complex submerged seabed features within this AOI. Collected specimens were preserved and are stored at the Atlantic Reference Centre (ARC) in St. Andrew's, New Brunswick. Cite this data as: Goodwin, C., Cooper, J.A., Lawton, P., Teed, L.L. 2025. Sponge occurrence and associated species and habitat descriptions derived from the 2021 and 2022 SCUBA diving surveys in the Eastern Shore Islands Area of Interest, Nova Scotia. Version 1.4. Fisheries and Oceans Canada. Occurrence dataset. https://ipt.iobis.org/obiscanada/resource?r=eastern_shore_islands_sponge_survey_2021_2022&v=1.4

The National Ecological Framework for Canada's "Soil Development by Ecodistrict” dataset contains tables that provide soil development information for components within the ecodistrict framework polygon. It provides soil development codes and their English and French-language descriptions as well as the percentage of the polygon that the component occupies. The soil development descriptions are based on the second edition of the Canadian System of Soil Classification (Agriculture Canada Expert Committee on Soil Survey, 1987).

PURPOSE: Establishing efficient, non-destructive sampling methods for clam population assessments. DESCRIPTION: In the Gulf of St. Lawrence (GSL) Management Region, clam assessments are uncommon due to limited resources and the labour-intensive nature of sampling clam beds. Furthermore, clam assessments typically rely on destructive sampling that disturbs sediment and removes animals from their habitat. Establishing efficient, non-destructive sampling methods for clam population assessments can reduce the impact of scientific sampling on these habitats and provide for more efficient monitoring. In this study, we tested the idea that visually observing siphon holes on the sediment surface could predict the presence, number, and size of soft-shell clams across different sites in the southern GSL. Siphon holes reasonably predicted the presence, number, and size/biomass of soft-shell clams in most, but not all, sites. Thus, in many habitats in the GSL, siphon holes can be used for population assessments, providing a powerful tool to enhance Science advice to fisheries managers. Data was collected at the following sites: * Maisonnette, Parc Maisonnette, Maisonnette, New Brunswick, Canada * Kouchibouguac, Loggiecroft wharf, Kouchibouguac National Park, New Brunswick, Canada * Shemogue, Amos Point Road, Little Shemogue, New Brunswick, Canada * Powell's Cove, Powell's Point Provincial Park, Little Harbour, Nova Scotia, Canada PARAMETERS COLLECTED: - Clam abundance - Clam biomass (total sample) - Clam size (length, weight) - Siphon hole abundance - Siphon hole size - Siphon hole characterization (i.e., identification of actual clam based on shape) - Seawater temperature - Sediment grain size - Sediment organic content (%) - Sediment relative moisture content (%) NOTES ON QUALITY CONTROL: Original data entry by Jillian Hunt and/or Isabelle Brennan. Data checked and validated prior to analysis by Jeff Clements. Data further checked and validated prior to publication by Amélie Robichaud. PHYSICAL SAMPLE DETAILS: No physical samples retained. - Clam samples returned back to original habitat after measuring and weighing in the field. - Sediment core samples stored in walk-in freezer and discarded after processing and analysis. SAMPLING METHODS: i. Identifying, counting, weighing, and measuring (with calipers) clams ii. Identifying, counting, and measuring (with calipers) clam siphon holes iii. Seawater temperature monitoring via data loggers iv. Sediment grain size, organic content, and moisture content analysis USE LIMITATION: To ensure scientific integrity and appropriate use of the data, we would encourage you to contact the data custodian.

This dataset includes the extent of the boreal forest as well as the extent of managed boreal forest worldwide. The extent of boreal forest was produced from Brandt et al. (2013) and a modified version of Goudilin (1987). Managed forest was defined as suggested by IPCC (2003) using data from FAFS (2009), Gauthier et al. (2014), See et al. (2015) and AICC maps. The extent of managed forest mostly includes areas managed for wood production, areas protected from large-scale disturbances as well as formal protected areas. Both boreal forest extent and managed boreal forest extent are available in raster and vector data. Please cite this data product as: Boucher, D., D.G. Schepaschenko, S. Gauthier, P. Bernier, T. Kuuluvainen, A. Z. Shvidenko. 2024. World boreal forest and managed boreal forest extent. DOI: 10.23687/88d70716-2600-4995-8d5f-86f96e383abf These data were presented in the following article: Gauthier, S., P. Bernier, T. Kuuluvainen, A. Z. Shvidenko, D. G. Schepaschenko. 2015. Boreal forest health and global change. Science 349:819-822. DOI: 10.1126/science.aaa9092 References: J. P. Brandt, M. D. Flannigan, D. G. Maynard, I. D. Thompson, W. J. A. Volney, Environ. Rev. 21, 207–226 (2013) I. S. Goudilin, Landscape map of the USSR. Legend to the landscape map of the USSR. Scale 1:2 500 000. Moscow, Ministry of Geology of the USSR (1987) [in Russian]. Inter-governmental panel on climate change (IPCC). J. Penman, M. Gytarsky, T. Hiraishi, T. Krug, D. Kruger, et al., Eds., Good practice guidance for land use, land-use change and forestry (IPCC/NGGIP/IGES, Kanawaga, 2003) Federal Agency of Forest Service (FAFS), Forest Fund of the Russian Federation (state by 1 January 2009) (Federal Agency of Forest Service, Moscow, 2009) [in Russian] S. Gauthier et al., Environ. Rev. 22, 256–285 (2014). See et al., Harnessing the power of volunteers, the internet and Google Earth to collect and validate global spatial information using Geo-Wiki. Technological Forecasting and Social Change. (2015). doi:10.1016/j.techfore.2015.03.002 Alaska Interagency Coordination Center (AICC). Fire Information. https://fire.ak.blm.gov/content/maps/aicc/Large%20Maps/Alaska_Fire_Management_Options.pdf (the version of 2014 was used)