데이터셋 상세
캐나다
Pacific Marine Ecological Classification System and its Application to the Northern and Southern Shelf Bioregions
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 analysis 2. Biophysical_Units_L4B - Predicted PMECS Biophysical Units (Level 4B) output from the random forest analysis 3. 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 step 4. Cluster_L4AB - Layer showing the output of species assemblage cluster analysis 5. 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.
데이터 정보
연관 데이터
Coastwide Evaluation and Classification of Pacific Region Estuaries based on Anthropogenic Activities and Significant Fish Habitat
공공데이터포털
Estuaries are highly productive and diverse ecosystems that represent a geographic bottleneck between marine and freshwater systems. Estuaries have been identified as ecologically and biologically significant areas (EBSAs) in Canada’s Pacific Region because of their importance for the aggregation, productivity, and fitness of anadromous fishes, including Pacific salmon. However, estuaries are also the site of many anthropogenic activities, and the degradation of estuarine habitats such as eelgrass beds has had corresponding impacts on many species of ecological, economic, and cultural importance. To support a regional request for information to aid integrated coastal planning, a coastwide classification of estuaries based on anthropogenic activities was completed. Anthropogenic activities and associated stressors relevant to estuary habitats were identified through a literature review and used to guide the compilation of spatial datasets. The spatial datasets were then used in a cluster analysis that identified estuaries that share similar activity types and levels of use. Ecological information was then compiled and mapped to highlight how estuarine fishes and fish habitats considered significant or sensitive relate to the results of the clustering analysis and individual estuaries. This broad-scale analysis represents an initial assessment of BC’s estuaries that can help guide localized efforts and identify opportunities for management efficiencies among estuaries that face similar activities and stressors. Research needs for future evaluations at a finer-scale scale are detailed, as are linkages with projects underway within specific estuaries, to highlight opportunities for collaboration as priority estuaries are identified for management and conservation action. This data record includes select Appendix tables associated with the Canadian Science Advisory Secretariat (CSAS) research document entitled “Coastwide Evaluation and Classification of Pacific Region Estuaries based on Anthropogenic Activities and Significant Fish Habitat”. The Science Advisory Report from the regional peer review meeting held on April 12-13, 2023 is available at: https://www.dfo-mpo.gc.ca/csas-sccs/Publications/SAR-AS/2023/2023_039-eng.html The Appendix tables contain information summarized for individual estuaries along the Pacific Coast of Canada, as follows: Table G1 - Activity data by estuary including cluster assignment, coordinates of estuary centroid, bioregion, estuary and watershed areas, and activity count,. Activities marked with * are restricted datasets and the column is left blank. Area based activities were quantified using a generic raster cell constant value, and the extent of some activities were quantified by buffering and applying a distance decay to the raster values resulting in “generic area units” of overlap with estuaries. Refer to data dictionary (Table G4) for column descriptions and units. Table G3 - Ecological data by estuary including cluster assignment, coordinates of estuary centroid, and bioregion. See section 3.4 for details on how each metric was calculated. Refer to data dictionary (Table G4) for column descriptions and units. Table G4 – Data dictionary in English and French describing column headers and units for fields in Tables G1 and G3. Spatial data for the associated estuaries were mapped by the Pacific Estuary Conservation Program (PECP, Ryder et al. 2007) and the Pacific Birds Habitat Join Venture (PBHJV, PBHJV 2020) and are available for download at: https://pacificbirds.org/2021/02/an-updated-ranking-of-british-columbias-estuaries/
Seamounts of the Northeast Pacific Ocean
공공데이터포털
Seamounts have been identified as Ecologically or Biologically Significant Areas (EBSAs) due to their unique oceanography and ecology; they frequently serve as sites for fisheries and as habitat for a number of species of conservation concern. A mix of isolated seamounts and seamount complexes are distributed throughout Canada’s Pacific offshore waters, although only a subset of these are named. We used several pre-existing spatial databases and predictive models to map all named seamounts within Canada’s Exclusive Economic Zone (EEZ), all named seamounts fished by Canada in international waters, and any predicted (modelled) unnamed seamounts in the EEZ. These data are intended to inform marine planning initiatives in BC by providing collaborative, peer-reviewed scientific data at scales relevant to a BC coast-wide analysis.
Southern Ocean Benthic Classification (SOBC) - ecoregions, bathomes and environmental types
공공데이터포털
This dataset is intended for general use in spatial planning and management to identify areas where benthic marine assemblages are likely to differ from each other in the Southern Ocean. We achieve this by using a hierarchical spatial classification of ecoregions, bathomes and environmental types. Ecoregions are defined according to available data on biogeographic patterns and environmental drivers on dispersal. Bathomes are identified according to depth strata defined by species distributions. Environmental types are uniquely classified according to the geomorphic features found within the bathomes in each ecoregion. This circum-Antarctic map of environmental types can be used to support spatial management aimed at conserving benthic biodiversity across the entire Southern Ocean. The study area spans the region managed by the Commission for the Conservation of Antarctic Marine Living Resources (CCAMLR). The northern boundary of this region is a line approximating the location of the Polar Front. The southern boundary was defined as the northern edge of the permanent ice shelf of the Antarctic continent. The shapefile can be used to identify three levels of the hierarchical classification (see Fig. 1 of Douglass et al., 2014): 1) Level 1: Ecoregions 2) Level 2b: Geomorphic features nested in each ecoregion 3) Level 3: Environmental Types The dataset cannot be used to analyse a level 2a nesting since for some geomorphic features (e.g. seamounts and canyons) the nested bathomes were combined when generating environmental types. If a level 2a nesting is required please contact douglass.lucinda@gmail.com The shapefile contains ten fields: EcoID- Abbreviated Level 1 benthic ecoregion names Ecoregion- Level 1 benthic ecoregion names Geomorph2- Geomorphic features BathID- Bathome identification number which can be used to sort the depth classes Bathome2 - Bathome EcoGeo- Level 2b nesting of geomorphic features in each ecoregion EnvTyp- Level 3 environmental types GeoClsID- Geomorphic class identification number GeoCls- Geomorphic classes Sqkm- Area in square kilometers
Important Areas for Invertebrates in Pacific North Coast Integrated Management Area
공공데이터포털
This layer details Important Areas (IAs) relevant to key invertebrate species (which are not corals or sponges) in the Pacific North Coast Integrated Management Area (PNCIMA). This data was mapped to inform the selection of marine Ecologically and Biologically Significant Areas (EBSA). Experts have indicated that these areas are relevant based upon their high ranking in one or more of three criteria (Uniqueness, Aggregation and Fitness Consequences). The distribution of IAs within ecoregions is used in the designation of EBSAs. Canada’s Oceans Act provides the legislative framework for an integrated ecosystem approach to management in Canadian oceans, particularly in areas considered ecologically or biologically significant. DFO has developed general guidance for the identification of ecologically or biologically significant areas. The criteria for defining such areas include uniqueness, aggregation, fitness consequences, resilience, and naturalness. This science advisory process identifies proposed EBSAs in Canadian Pacific marine waters, specifically in the Strait of Georgia (SOG), along the west coast of Vancouver Island (WCVI, southern shelf ecoregion), and in the Pacific North Coast Integrated Management Area (PNCIMA, northern shelf ecoregion). Initial assessment of IAs in PNCIMA was carried out in September 2004 to March 2005 with spatial data collection coordinated by Cathryn Clarke. Subsequent efforts in WCVI and SOG were conducted in 2009, and may have used different scientific advisors, temporal extents, data, and assessment methods. WCVI and SOG IA assessment in some cases revisits data collected for PNCIMA, but should be treated as a separate effort. Other datasets in this series detail IAs for birds, cetaceans, coral and sponges, fish, geographic features, and other vertebrates. Though data collection is considered complete, the emergence of significant new data may merit revisiting of IAs on a case by case basis.
Pacific Marine Habitat Classes
공공데이터포털
This data set is a generalized characterization of the offshore and inshore environments of Canada’s Pacific Ocean. Compiled from various sources to depict the biogenic habitats, pelagic habitats, and general bottom types such as offshore and inshore by depth strata.
Seagrass - Gulf Islands National Seashore - 2011/10/04
공공데이터포털
Seagrass or submerged aquatic vegetation (SAV) is a valuable and abundant resource found within Gulf Islands National Seashore. It provides habitat for many fish and invertebrates. Seagrass grows in shallow waters and, therefore, is prone to damage and erosion from boats, propellers, fishing equipment, and wakes. We have employed an object-based image analysis technique using Trimble eCognition software to quantify the seagrass and provide a baseline for future studies.
Seagrass - Gulf Islands National Seashore - 2011/10/04
공공데이터포털
Seagrass or submerged aquatic vegetation (SAV) is a valuable and abundant resource found within Gulf Islands National Seashore. It provides habitat for many fish and invertebrates. Seagrass grows in shallow waters and, therefore, is prone to damage and erosion from boats, propellers, fishing equipment, and wakes. We have employed an object-based image analysis technique using Trimble eCognition software to quantify the seagrass and provide a baseline for future studies.
High Seas Marine Protected Areas: Benthic environmental conservation priorities from a GIS analysis of global ocean biophysical data
공공데이터포털
In order to design a representative network of high seas marine protected areas (MPAs), an acceptable scheme is required to classify the benthic bioregions of the oceans. Given the lack of sufficient biological information to accomplish this task, we used a multivariate statistical method with 6 biophysical variables (depth, seabed slope, sediment thickness, primary production, bottom water dissolved oxygen and bottom temperature) to objectively classify the ocean floor into 11 different categories, comprised of 53,713 separate polygons, that we have termed "seascapes". Validation of the seascape classification was carried out by comparing the seascapes with an existing map of seafloor geomorphology, and by GIS analysis of the number of separate polygons and perimeter/area ratio. We conclude that seascapes, derived using a multivariate statistical approach, are biophysically meaningful subdivisions of the ocean floor and can be expected to contain different biological associations, in as much as different geomorphological units do the same. Our study illustrates how the identification of potential sites for high seas marine protected areas can be accomplished by GIS analysis of seafloor geomorphic and seascape classification maps. Using this approach, maps of seascape and geomorphic heterogeneity were generated in which heterogeneity hot-spots identify themselves as MPA candidates. The use of computer-aided mapping tools removes subjectivity in the MPA design process and provides greater confidence to stakeholders that an unbiased result has been achieved.
목록