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We have found 215 datasets for the keyword " size". You can continue exploring the search results in the list below.
Datasets: 106,057
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215 Datasets, Page 1 of 22
Seabed grain size analyses, offshore Canada
Grain size is the most fundamental physical property of sediment, and these data are widely used in a variety of applications in science. Marine expeditions of the Geological Survey of Canada have been collecting grain size information on seabed and sub-seabed samples for over 50 years. Results have been recorded at 5th phi midpoints since the early 1990's in contrast to the earlier full, half or quarter phi interval end point values. Users of high resolution data must note that the sum of %Silt and %Clay equals the total %Mud makeup and that %Gravel, %Sand, %Silt and %Clay sum to 100%. Summary statistics include percentages of gravel, sand, silt, clay and mud as well as mean, kurtosis, skewness and standard deviation. The quality of these data varies. Results should be used with some caution as they may not be fully representative of seabed grainsize, particularly in areas of sandy and coarser sediment (e.g., sand and mud can leak out of the sampler during recovery). Canada makes no representation or warranty of any kind with respect to the accuracy, usefulness, novelty, validity, scope, completeness or currency of the data and expressly disclaims any implied warranty of merchantability or fitness for a particular purpose of the data. For the purpose of the web mapping service, grain size data are sorted by the expedition id. Coarse and detailed grain size distribution plots are shown when a point is chosen. If the sample contains more that one sub-sample ( e.g., as with a piston core sequence), the grain size plots are stacked in the display window from the top of the core downwards.
Maritime region grain size data
Fisheries and Oceans Canada (DFO) Maritime Science Branch has collected grain size data from sediment and water column samples using bottle samples, sediment cores, and sediment grabs as part of numerous research projects not only in the Atlantic provinces, but also worldwide. The data collected by DFO focuses on the fine grained (<1mm) particles as these are both a source of food and means of contaminant transport. Grain size data are used to study the fate and distribution of complimentary chemistries like heavy metals, pesticides, hydrocarbons, aquaculture waste as well as a variety of physical processes such as the resuspension and transport of sediment.
Bay of Fundy Sea Scallop Commercial Size Abundance Data
This dataset represents abundance data of commercial size Sea Scallop (Placopecten magellanicus; ≥ 80 mm shell height) from 2011-2023 from the Bay of Fundy Inshore Scallop Survey. Data is binned into 5-mm shell height bins, is prorated to an 800 m tow length and 17.5 feet (5.334 m) drag width (i.e., representing an area swept of 4267 m2), and was collected using unlined dredge gear. Each row represents a tow and contains information such as tow date, cruise name, gear type, geographical coordinates (decimal degrees, WGS 84) and the Scallop Production Area in which the tow took place. Survey protocols are documented in Glass (2017). This dataset contains tow data from a comparative survey conducted in 2012 (Smith et al., 2013). Further, these data correspond to the publication of Hebert et al. (2025).ReferencesGlass, A. 2017. Maritimes Region Inshore Scallop Assessment Survey: Detailed Technical Description. Can. Tech. Rep. Fish. Aquat. Sci. 3231: v + 32 p.Hebert, N, Sameoto, J.A., Keith, D.M., Murphy, O.A., Brown, C.J., Flemming, J. 2025. Interannual variability in the length–weight relationship can disrupt the abundance–biomass correlation of sea scallop (Placopecten magellanicus). ICES. J. Mar. Sci. Smith, S.J., Glass, A., Sameoto. J., Hubley, B., Reeves, A., and Nasmith, L. 2013. Comparative survey between Digby and Miracle drag gear for scallop surveys in the Bay of Fundy. DFO Can. Sci. Advis. Sec. Res. Doc. 2012/161. iv + 20 p.Cite this data as: Sameoto, J.A. Data of: Bay of Fundy Sea Scallop Commercial Size Abundance Data. Published: December 2025. Population Ecology Science Division, Fisheries and Oceans Canada, Dartmouth, N.S. https://open.canada.ca/data/en/dataset/ecc09d98-56ed-4a27-ad62-5c3714a1d9b4
British Columbia Geoduck (Panopea generosa) Age, Size Structure and Growth Parameters, 1993 - 2002
Biological samples of Geoduck Clams have been collected during surveys in British Columbia as part of the broader survey objectives of determining Geoduck density, distribution and population structure. Samples of Geoducks were collected from 41 locations throughout British Columbia between 1993 and 2002. Clams were measured for total weight, shell length, shell weight and were aged. Biological parameters are presented here for individual clams sampled. See Bureau D., W. Hajas, N.W. Surry, C.M. Hand, G. Dovey and A. Campbell. 2002. Age, size structure and growth parameters of Geoducks (Panopea abrupta, Conrad 1849) from 34 locations in British Columbia sampled between 1993 and 2000. Can Tech. Rep. Fish. Aquat. Sci. 2413: 84 p. and Bureau D., W. Hajas, C.M. Hand and G. Dovey. 2003. Age, size structure and growth parameters of Geoducks (Panopea abrupta, Conrad 1849) from seven locations in British Columbia sampled in 2001 and 2002. Can. Tech. Rep. Fish. Aquat. Sci. 2494: 29 p.
Data of eelgrass (Zostera marina) plant size (length, width), cover, and biomass from the Atlantic Coast of Nova Scotia
This dataset includes metrics of eelgrass size, cover, and biomass from field sites along the Atlantic coast of Nova Scotia, Canada. Field sites were located across a gradient of environmental conditions, and field sampling was conducted in July to August 2022. Eelgrass percent cover, shoot density, and plants were sampled at 10 haphazardly distributed sampling stations within each eelgrass bed at approximately the same depth. Stations were ~10m apart and at least 2m from any eelgrass-bare interface. At each sampling station eelgrass leaves in a 0.5 x 0.5m quadrat were photographed for later computer image analysis to determine percent cover. The number of shoots were then counted in a 0.25 x 0.25m quadrat, and 3 vegetative shoots were collected. Shoots were measured for leaf length, width, and weight in the laboratory. These data were used to determine allometric and cover-biomass relationships for use in non-destructive estimation of bed biomass. Cite this data as: Wong, M.C., & Thomson, J. A. Data of eelgrass (Zostera marina) plant size (length, width), cover, and biomass from the Atlantic Coast of Nova Scotia. Published: February 2025. Coastal Ecosystems Science Division, Maritimes Region, Fisheries and Oceans Canada, Dartmouth NS.For additional information please see:Thomson, J. A., Vercaemer, B., & Wong, M. C. (2025). Non-destructive biomass estimation for eelgrass (Zostera marina): Allometric and percent cover-biomass relationships vary with environmental conditions. Aquatic Botany, 198, 103853. https://doi.org/10.1016/j.aquabot.2024.103853
Patch Size Assessment Amalgamation Units for the Cariboo Natural Resource Region
This dataset is a combination of landscape unit, biogeoclimatic zone/subzone/variants and Cariboo Chilcotin Land Use Plan leading group type (PineGroup or FirGroup) that patch size assessments are carried out on. Refer to the **Cariboo Regional Biodiversity Conservation Strategy Update Note #4: An Approach for Patch Size Assessments in the Cariboo Forest Region** (see below under "Related Links") for more information on how patch size assessment amalgamation units are derived.
Steller Sea Lion Haulout Counts in British Columbia
The Steller sea lion (Eumetopias jubatus) is the largest species of sea lion with males weighing as much as 1,100 kg and females as much as 350 kg. In Canada, the Steller can be spotted along the rocky coast of British Columbia (BC). These highly mobile marine mammals typically travel alone or in small groups, but they congregate in large numbers at traditional rookeries and haul-outs during the mating and pupping season. Females generally live longer (up to 30 years) than males (usually up to 20 years). The population was severely depleted in Canada but following its protection in 1970, the size of the adult population has more than doubled.Trends in the abundance of Steller sea lions in BC have been assessed based on a series of standardized, province-wide aerial surveys conducted during the breeding season (27-June to 06-July) between 1971 and 2021. Additional ad-hoc surveys during the fall, winter, and spring periods were completed to assess sea lion distribution outside of the breeding season. Surveys targeted historically occupied rookeries and haul-out sites with nearby areas also monitored for potential shifts in distribution.Both datasets contain counts that have been collected from sightings of individuals from 1971 through 2021. The updated standard breeding season survey counts data file consolidates and extends two previous datasets – one covering 1971 through 2013 and the other covering the summer portion of the 2016/2017 surveys. The non-breeding season count data was previously limited to the fall-winter portion of the 2016/2017 surveys and the updated data covers the entire study period to date.
Number of large fires (>200 hectares) - Medium-term (2041-2070) under RCP 8.5
The fire regime describes the patterns of fire seasonality, frequency, size, spatial continuity, intensity, type (e.g., crown or surface fire) and severity in a particular area or ecosystem.The number of large fires refers to the annual number of fires greater than 200 hectares (ha) that occur per units of 100,000 ha. It was calculated per Homogeneous Fire Regime (HFR) zones. These HFR zones represent areas where the fire regime is similar over a broad spatial scale (Boulanger et al. 2014). Such zonation is useful in identifying areas with unusual fire regimes that would have been overlooked if fires had been aggregated according to administrative and/or ecological classifications.Fire data comes from the Canadian National Fire Database covering 1959–1999 (for HFR zones building) and 1959-1995 (for model building). Multivariate Adaptive Regression Splines (MARS) modeling was used to relate monthly fire regime attributes with monthly climatic/fire-weather in each HFR zone. Future climatic data were simulated using the Canadian Earth System Model version 2 (CanESM2) and downscaled at a 10 Km resolution using ANUSPLIN for two different Representative Concentration Pathways (RCP). RCPs are different greenhouse gas concentration trajectories adopted by the Intergovernmental Panel on Climate Change (IPCC) for its fifth Assessment Report. RCP 2.6 (referred to as rapid emissions reductions) assumes that greenhouse gas concentrations peak between 2010-2020, with emissions declining thereafter. In the RCP 8.5 scenario (referred to as continued emissions increases) greenhouse gas concentrations continue to rise throughout the 21st century.Provided layer: projected number of large fires (>200 ha) across Canada for the medium-term (2041-2070) under the RCP 8.5 (continued emissions increases).Reference: Boulanger, Y., Gauthier, S., et al. 2014. A refinement of models projecting future Canadian fire regimes using homogeneous fire regime zones. Canadian Journal of Forest Research 44, 365–376.
Number of large fires (>200 hectares) - Long-term (2071-2100) under RCP 2.6
The fire regime describes the patterns of fire seasonality, frequency, size, spatial continuity, intensity, type (e.g., crown or surface fire) and severity in a particular area or ecosystem.The number of large fires refers to the annual number of fires greater than 200 hectares (ha) that occur per units of 100,000 ha. It was calculated per Homogeneous Fire Regime (HFR) zones. These HFR zones represent areas where the fire regime is similar over a broad spatial scale (Boulanger et al. 2014). Such zonation is useful in identifying areas with unusual fire regimes that would have been overlooked if fires had been aggregated according to administrative and/or ecological classifications.Fire data comes from the Canadian National Fire Database covering 1959–1999 (for HFR zones building) and 1959-1995 (for model building). Multivariate Adaptive Regression Splines (MARS) modeling was used to relate monthly fire regime attributes with monthly climatic/fire-weather in each HFR zone. Future climatic data were simulated using the Canadian Earth System Model version 2 (CanESM2) and downscaled at a 10 Km resolution using ANUSPLIN for two different Representative Concentration Pathways (RCP). RCPs are different greenhouse gas concentration trajectories adopted by the Intergovernmental Panel on Climate Change (IPCC) for its fifth Assessment Report. RCP 2.6 (referred to as rapid emissions reductions) assumes that greenhouse gas concentrations peak between 2010-2020, with emissions declining thereafter. In the RCP 8.5 scenario (referred to as continued emissions increases) greenhouse gas concentrations continue to rise throughout the 21st century.Provided layer: projected number of large fires (>200 ha) across Canada for the long-term (2071-2100) under the RCP 2.6 (rapid emissions reductions).Reference: Boulanger, Y., Gauthier, S., et al. 2014. A refinement of models projecting future Canadian fire regimes using homogeneous fire regime zones. Canadian Journal of Forest Research 44, 365–376.
Number of large fires (>200 hectares) - Short-term (2011-2040) under RCP 8.5
The fire regime describes the patterns of fire seasonality, frequency, size, spatial continuity, intensity, type (e.g., crown or surface fire) and severity in a particular area or ecosystem.The number of large fires refers to the annual number of fires greater than 200 hectares (ha) that occur per units of 100,000 ha. It was calculated per Homogeneous Fire Regime (HFR) zones. These HFR zones represent areas where the fire regime is similar over a broad spatial scale (Boulanger et al. 2014). Such zonation is useful in identifying areas with unusual fire regimes that would have been overlooked if fires had been aggregated according to administrative and/or ecological classifications.Fire data comes from the Canadian National Fire Database covering 1959–1999 (for HFR zones building) and 1959-1995 (for model building). Multivariate Adaptive Regression Splines (MARS) modeling was used to relate monthly fire regime attributes with monthly climatic/fire-weather in each HFR zone. Future climatic data were simulated using the Canadian Earth System Model version 2 (CanESM2) and downscaled at a 10 Km resolution using ANUSPLIN for two different Representative Concentration Pathways (RCP). RCPs are different greenhouse gas concentration trajectories adopted by the Intergovernmental Panel on Climate Change (IPCC) for its fifth Assessment Report. RCP 2.6 (referred to as rapid emissions reductions) assumes that greenhouse gas concentrations peak between 2010-2020, with emissions declining thereafter. In the RCP 8.5 scenario (referred to as continued emissions increases) greenhouse gas concentrations continue to rise throughout the 21st century.Provided layer: projected number of large fires (>200 ha) across Canada for the short-term (2011-2040) under the RCP 8.5 (continued emissions increases).Reference: Boulanger, Y., Gauthier, S., et al. 2014. A refinement of models projecting future Canadian fire regimes using homogeneous fire regime zones. Canadian Journal of Forest Research 44, 365–376.
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