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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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
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Likelihood of Presence of Harbour Porpoise in the Bay of Fundy and Port Hawkesbury Area Response Plan. The Coastal Oceanography and Ecosystem Research section (DFO Science) reviewed reported opportunistic whale sightings and local knowledge sources to estimate areas where Harbour Porpoises are seasonally present and delineate these areas. 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 Harbour Porpoise 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/58ea48ab-f052-48ab-9c18-4353e51b8bea
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The Coastal Oceanography and Ecosystem Research section (DFO Science) reviewed the presence of Cod in the Population Ecology Division (DFO Science) Ecosystem Survey trawls to describe the likelihood of presence. The survey consists of a stratified random design using a bottom trawl. This layer was created for consideration in oil spill response planning. 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 Atlantic Cod 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/af2bf6c0-481d-4445-bbc6-7a785d2a9aa9
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Description Conservation of marine biodiversity requires understanding the joint influence of ongoing environmental change and fishing pressure. Addressing this challenge requires robust biodiversity monitoring and analyses that jointly account for potential drivers of change. Here, we ask how demersal fish biodiversity in Canadian Pacific waters has changed since 2003 and assess the degree to which these changes can be explained by environmental change and commercial fishing. Using a spatiotemporal multispecies model based on fisheries independent data, we find that species density (number of species per area) and community biomass have increased during this period. Environmental changes during this period were associated with temporal fluctuations in the biomass of species and the community as a whole. However, environmental changes were less associated with changes in species’ occurrence. Thus, the estimated increases in species density are not likely to be due to environmental change. Instead, our results are consistent with an ongoing recovery of the demersal fish community from a reduction in commercial fishing intensity from historical levels. These findings provide key insight into the drivers of biodiversity change that can inform ecosystem-based management. The layers provided represent three community metrics: 1) species density (i.e., species richness), 2) Hill-Shannon diversity, and 3) community biomass. All layers are provided at a 3 km resolution across the study domain for the period of 2003 to 2019. For each metric, we provide layers for three summary statistics: 1) the mean value in each grid cell over the temporal range, 2) the probability that the grid cell is a hotspot for that metric, and 3) the temporal coefficient of variation (i.e., standard deviation/mean) across all years. Methods: The analysis that produced these layers is presented in Thompson et al. (2022). The analysis uses data from the Groundfish Synoptic Bottom Trawl Research surveys in Queen Charlotte Sound (QCS), Hecate Strait (HS), West Coast Vancouver Island (WCVI), and West Coast Haida Gwaii (WCHG) from 2003 to 2019. Cartilaginous and bony fish species caught in DFO groundfish surveys that were present in at least 15% of all trawls over the depth range in which they were caught were included. This depth range was defined as that which included 95% of all trawls in which that species was present. The final dataset used in our analysis consisted of 57 species (Table S1 in Thompson et al. 2022). The spatiotemporal dynamics of the demersal fish community were modeled using the Hierarchical Modeling of Species Communities (HMSC) framework and package (Tikhonov et al. 2021) in R. This framework uses Bayesian inference to fit a multivariate hierarchical generalized mixed model. We modeled community dynamics using a hurdle model, which consists of two sub models: a presence-absence model and a biomass model that is conditional on presence. Our list of environmental covariates included bottom depth, bathymetric position index (BPI), mean summer tidal speed, substrate muddiness, substrate rockiness, whether the trawl was inside or outside of the ecosystem-based trawling footprint, and survey region (QCS & HS vs. WCVI & WCHG)), mean summer near-bottom temperature deviation, mean summer near-bottom dissolved oxygen deviation, mean summer cross-shore and along-shore current velocities near the seafloor, mean summer depth-integrated primary production, and local-scale commercial fishing effort. Layers are provided for three community metrics. All metrics should be interpreted as the value that would be expected in the catch from an average tow in the Groundfish Synoptic Bottom Trawl Research Surveys taken in a given 3 km grid cell. Species density (sometimes called species richness) should be interpreted as the number of the 57 species that would be caught in a trawl. Hill-Shannon diversity is a measure of diversity that gives greater weight to communities where biomass is spread equally across species. Community biomass is the total biomass across all 57 species that would be expected to be caught per square km in an average tow. Data Sources: Research data was provided by Pacific Science's Groundfish Data Unit for research surveys from the GFBio database between 2003 and 2019 that occurred in four regions: Queen Charlotte Sound, Hecate Strait, West Coast Haida Gwaii, and West Coast Vancouver Island. Our analysis excludes species that are rarely caught in the research trawls and so our estimates would not include the occurrence or biomass of these rare species. Commercial fishing data was accessed through a DFO R script detailed here: https://github.com/pbsassess/gfdata. Local scale commercial fishing effort was calculated from this data. The substrate layers were obtained from a substrate model (Gregr et al. 2021). The oceanographic layers (bottom temperature, dissolved oxygen, tidal and circulation speeds, primary production) were obtained from a hindcast simulation of the British Columbia continental margin (BCCM) model (Peña et al. 2019). Uncertainties: Species that are not well sampled by the trawl surveys may not be accurately estimated by our model. The model did not include spatiotemporal random effects, which likely underestimates spatiotemporal variability in the region. It is also important to underline covariate uncertainty and model uncertainty. The hotspot estimates provide one measure of model uncertainty/certainty.
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Distribution of fulmar, shearwater and petrel bird species habitat in coastal British Columbia showing relative abundance (RA) by season and overall relative importance (RI). RI is based on project region and not on the province as a whole. CRIMS is a legacy dataset of BC coastal resource data that was acquired in a systematic and synoptic manner from 1979 and was intermittently updated throughout the years. Resource information was collected in nine study areas using a peer-reviewed provincial Resource Information Standards Committee consisting of DFO Fishery Officers, First Nations, and other subject matter experts. There are currently no plans to update this legacy data.
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Survey areas is a polygon feature class containing mudflats and staging areas observed for shorebirds.
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This spatial file includes the polygon boundaries of the four Pacific Great Blue Heron Conservation Regions in British Columbia, as described in the management plan. These Conservation Regions are recognized based on degree of isolation, population sizes, and differences in trends and threats. The management objective for Pacific Great Blue Heron is to ensure that all four Conservation Regions have stable or locally increasing numbers of herons. Refer to the "Management Plan for the Great Blue Heron fannini subspecies (Ardea herodias fannini) in Canada" on the SARA Regristry for more information.
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Modeled data showing the likely distribution of pacific white sided dolphins. Coastal Resource Information Management System (CRIMS) is a legacy dataset of BC coastal resource data that was acquired in a systematic and synoptic manner from 1979 and was intermittently updated throughout the years. Resource information was collected in nine study areas using a peer-reviewed provincial Resource Information Standards Committee consisting of DFO Fishery Officers, First Nations, and other subject matter experts. There are currently no plans to update this legacy data.
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The National Ecological Framework for Canada's "Surface Form by Ecodistrict" dataset contains tables that provide surface form information for components within the ecodistrict framework polygon. It provides surface form codes and their English and French-language descriptions as well as information about the percentage of the polygon that the component occupies. Surface form descriptions describe assemblages of slopes or recurring patterns of forms that occur at the earth's surface. When applied to consolidated materials (material that has been transformed to hard rock), it refers to the form produced after modification by geological processes. The mineral soil surface forms are: dissected; hummocky (irregular); inclined; level, rolling; ridged; steep; terraced; undulating. The wetland surface forms are: bog; fen; marsh; swamp.
Arctic SDI catalogue