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biota

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    Náttúrulegt birkilendi á Íslandi er kortlagning yfir alla náttúrulega birkiskóga og birkikjarr á Íslandi. Helstu upplýsingar eru hæð, þekja og aldur. Skilið er á milli núverandi hæðar og aldur fullvaxta birkis. Það er gert samkvæmt alþjóðlegum skilgreiningum um hæð trjágróðurs þar sem miðað er við hæð fullvaxta skógar. Birki var fyrst kortlagt á árunum 1972-1975 og var unnin leiðrétting á gögnunum og gerðar frekari greiningar á árunum 1987-1991. Gögnin voru því komin nokkuð til ára sinna þegar ákveðið var að hefja endurkortlagningu á öllu náttúrulegu birki á Íslandi. Fór sú vinna fram á árunum 2010-2014 og er núverandi þekja því afrakstur þeirrar vinnu. Flatarmál náttúrulegs birkis á Íslandi er 150.600 ha. Frá árinu 1987 hefur flatarmál birkis með sjálfsáningu aukist um 9% og nemur 13.000 ha. Gögnin voru upphaflega hugsuð fyrir mælikvarða 1:15.000, hins vegar var talsvert stór hluti landsins kortlagður í mælikvarða 1:5000 – 1:10.000.

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    Many cetacean species were depleted in Canadian Pacific waters by commercial whaling, which ended in 1967. Although some populations have since shown evidence of recovery, there is limited information about the current abundance and geographic distribution of many species, particularly in difficult-to-survey offshore regions. This lack of baseline data hampers conservation status assessments, including estimating population-level impacts of anthropogenic activities. From July to early September 2018, we conducted ship-based surveys of cetaceans throughout the coastal and offshore waters of British Columbia. Density surface modelling (DSM) was used to produce spatially-explicit abundance estimates and distribution maps for four commonly-encountered cetacean species: the humpback whale (Megaptera novaeangliae), fin whale (Balaenoptera physalus), Dall’s porpoise (Phocoenoides dalli) and harbour porpoise (Phocoena phocoena). We estimated abundances of 7,030 (95% CI = 5,733-8,620) humpback whales, 2,893 (95% CI = 2,171-3,855) fin whales, 23,692 (95% CI = 19,121-29,356) Dall’s porpoises and 5,207 (95% CI = 2,769-9,793) harbour porpoises throughout Canadian Pacific waters. Our results complement design-based abundance estimates calculated from the same survey data, and can be compared with past habitat modelling studies and historical whaling catch data to estimate the extent of recovery of previously harvested populations. The return of these predators to habitats from which they were previously extirpated will have important ecosystem-level implications. The DSM results can contribute to calculations of Potential Biological Removal estimates to inform fisheries bycatch, as well as providing spatial data that can be used to assess the risk of entanglements, ship strikes, acoustic disturbance, and other anthropogenic threats. This dataset contains model-predicted densities of four commonly-encountered cetacean species (humpback whale, fin whale, Dall's porpoise and harbour porpoise) that were estimated using ship-based, visual survey data collected during the Pacific Region International Survey of Marine Megafauna (PRISMM) in July-August of 2018. Abundance of each species (where relevant) is provided for three gridded strata (25 km2 cell size) in the Pacific Region: one for the offshore, extending to Canada’s exclusive economic zone (EEZ), and two for coastal areas (the North Coast and the Salish Sea).

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    Rare species is a point feature class containing rare species sightings.

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    Deep arctic sponge aggregations. This habitat can be described as a type of deep-sea sponge aggregation (sensu OSPAR 2010) occurring only in the deeper, colder water (Arctic modified, and Norwegian Sea Deep Water), where glass sponges (class Hexactinellida) are typical and other strictly deep-sea sponges are common. One of the most common species of glass sponge is the Caulophacus arcticus, which is generally found on hard sea bottoms on the lower part of the continental slope.

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    The shallow, coastal regions of the world’s oceans are highly productive ecosystems providing important habitat for commercial, forage, endangered, and iconic species. Given the diversity of ecosystem services produced or supported by this ecosystem, a better understanding of its structure and function is central to developing an ecosystem-based approach to management. However this region termed the ‘white strip’ by marine geologists because of the general lack of high-resolution bathymetric data - is dynamic, highly variable, and difficult to access making data collection challenging and expensive. Since substrate is a key indicator of habitat in this important ecosystem, we created a continuous substrate map of Bottom Patches (BoPs) from the best available bottom type data using an approach that is simple, quantitative, and transparent making it amenable to iterative improvement as data quality and availability improve. To provide subsequent analyses (such as habitat models) with some confidence in the defined bottom type values, we developed a corresponding confidence surface based on the agreement of, and distance between observations. Such data are critical to assessments of species distributions and anthropogenic risk. Bottom patches (BoPs) have been created to represent bottom type for the entire Pacific Canadian coast from the high high water line to a depth of 50 metres (m). As a polygon representation, the BoPs describe patches of similar substrate prescribed by depth classes and the available field observations. In the areas where no observations are available, predicted bottom type values are used. The approach is described in Gregr et al. (2013), as a spatial framework for representing nearshore ecosystems. Accuracy of the bottom type depends on a multitude of factors but primarily the reliability and density of the bottom type observations. The horizontal accuracy of these data likely ranges from metres to 10s of metres because of the source data or data processing required. Areas with a higher data density, where the data show strong coherence, are understood to have higher accuracy. The BoPs use depth ribbons (polygons describing bathymetric ecozones) as an input. Depth ribbons for Pacific Canada were created from a high resolution (20 x 20 m2) bathymetry. Given the resolution of these data, processing was facilitated by dividing the Pacific Coast into 5 regions. The West Coast of Vancouver Island, extending from Cape Sutil in the North past Port San Juan to the South, includes a total of 110,313 BoP polygons. Bottom Patches for Queen Charlotte Strait and Strait of Georgia regions were combined for a total of 235,754 BoP polygons. The North Central Coast region, extending from the Alaskan border in the North to Cape Caution in the South, includes a total of 431,639 BoP polygons. The Haida Gwaii region includes a total of 86,825 BoP polygons. These data are intended for scientific research only. The developers (Fisheries and Oceans Canada, SciTech Environmental Consulting) are not responsible for damages resulting from any omissions or errors that may be contained in this dataset and expressly disclaims any warranty of fitness for any particular purpose. Developers shall not be liable for any losses, financial or otherwise, due to the use of these data. The user assumes the entire risk as to the suitability, results and performance of the dataset for their proposed use. Please credit SciTech and Fisheries and Oceans Canada as the source of the data in any maps, reports, or articles that are printed or published on paper or the Internet.

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    Polygons denoting concentrations of sea pens, small and large gorgonian corals and sponges on the east coast of Canada have been identified through spatial analysis of research vessel survey by-catch data following an approach used by the Northwest Atlantic Fisheries Organization (NAFO) in the Regulatory Area (NRA) on Flemish Cap and southeast Grand Banks. Kernel density analysis was used to identify high concentrations and the area occupied by successive catch weight thresholds was used to identify aggregations. These analyses were performed for each of the five biogeographic zones of eastern Canada. The largest sea pen fields were found in the Laurentian Channel as it cuts through the Gulf of St. Lawrence, while large gorgonian coral forests were found in the Eastern Arctic and on the northern Labrador continental slope. Large ball-shaped Geodia spp. sponges were located along the continental slopes north of the Grand Banks, while on the Scotian Shelf a unique population of the large barrel-shaped sponge Vazella pourtalesi was identified. The latitude and longitude marking the positions of all tows which form these and other dense aggregations are provided along with the positions of all tows which captured black coral, a non-aggregating taxon which is long-lived and vulnerable to fishing pressures. These polygons identify sponge grounds from the broader distribution of sponges in the region as sampled by Campelen trawl gear in the Newfoundland - Labrador Shelves biogeographic zone. A 200 kg minimum threshold for the sponge catch was identified as the weight that separated the sponge ground habitat from the broader distribution of sponges with these research vessel tow data and gear type.

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    Fishing event (e.g., day, time, location, catch effort), and associated biological data from the Standardized Inlet Survey component of the annual Sablefish Research and Assessment Survey on the British Columbia coast. Introduction DFO and the Canadian Sablefish Association undertake a collaborative fishery-independent annual research survey under a joint agreement. The survey employs longline trap gear to obtain catch rate data, gather biological samples, capture oceanographic measurements, and collect tag release and recapture data. Data summaries are provided here for standardized sets conducted at fixed stations within mainland inlets. The design of the sablefish survey has developed over time by incorporating and discontinuing components, including individual experimental studies (not available on OpenData). This Standardized Inlet Survey component differs in methodology from the other two survey components: (1) Offshore stratified random survey (2003 – present; available on OpenData using link below), and (2) Standardized trap survey – offshore indexing and offshore tagging (1990 – 2010; not yet available on OpenData). For the Standardized Inlet Survey, sets are allocated to five specific polygons in each of the following four inlet areas: Portland Inlet, Gil Island, Finlayson Channel, and Dean/Burke Channel. All four inlets were surveyed consistently between 2003 and 2019. No inlets were surveyed in 2020, and a single inlet was surveyed each year since 2021. Survey procedures are standardized and documented in Canadian Technical Reports of Fisheries and Aquatic sciences. Data tables provided for the Standardized Inlet Survey include (i) Effort, (ii) Catch, and (iii) Biological Information. Inlet Effort This table contains information about annual survey trips and fishing events (sets). Trip-level information includes the year the survey took place, a unique trip identifier, the vessel that conducted the survey and the trip start and end dates (the dates the vessel was away from the dock conducting the survey). Set-level information includes the inlet name, date, time, location and depth that fishing took place, soak time, and number of traps deployed. All successful fishing events are included, where successful sets are those that met survey design specifications. Inlet Catch This table contains the catch information from successful fishing events. Catch is identified to species or to the lowest taxonomic level possible. Catch is recorded as fish counts and / or weight. The unique trip identifier and set number are included so that catches can be related to the fishing event information (including capture location) for each set. Inlet Biological Information This table contains the biological data for sampled catches. Data may include any or all of length, weight, sex, maturity and age. Most of the sampled catch is Sablefish; however, some biological information has been collected for other species. Age structures are collected and are archived until required for analyses; therefore, all existing structures have not been aged. Tissue samples (usually a fin clip) may be collected for genetic (DNA) analysis for specific species. Tissue samples may be archived until required for analysis; for more information please see the data contacts. The unique trip identifier and set number are included so that samples can be related to the fishing event and catch information.

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    Tow, catch, and length frequency for fish caught during the August sentinel surveys in the southern Gulf of St. Lawrence (NAFO Division 4T). Abundance indices and spatial distribution patterns of commercial groundfish. Note: Due to delays caused by logistic complexities and Covid the project did not take place in 2020

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    Mobile Core Bathurst Caribou Management Zone

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    Bluefin tuna landings are reported to the Department of Fisheries and Oceans and stored in the Maritime Fishery Information System Database. This database was queried in January 2016 for all reported landings of Bluefin tuna in coastal Nova Scotia. Longline data was excluded due to location uncertainties associated with the gear. Bluefin tuna sightings are also reported opportunistically to the DFO Whale Sightings Database. The Coastal Oceanography and Ecosystem Research section considered these landings and sightings to estimate the presence of Bluefin tuna within the Area Response Plan areas. Bluefin tuna presence varies seasonally and this spatial information should be used in conjunction with temporal information. A version of this dataset was created for the National Environmental Emergency Center (NEEC) following their data model and is available for download in the Resources section. Cite this data as: Lazin, G., Hamer, A.,Corrigan, S., Bower, B., and Harvey, C. Data of: Likelihood of presence of Bluefin Tuna in Area Response Planning pilot areas. Published: June 2018. Coastal Ecosystems Science Division, Fisheries and Oceans Canada, St. Andrews, N.B. https://open.canada.ca/data/en/dataset/0c3b25df-f831-43e8-a8ac-336e1467c4fe