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We have found 229 datasets for the keyword "biology". You can continue exploring the search results in the list below.
Datasets: 104,046
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229 Datasets, Page 1 of 23
Monthly Satellite Chlorophyll-a Climatology of the Canadian Pacific Exclusive Economic Zone (2003-2020) - 4 km Resolution
Description:Chlorophyll-a concentration (a proxy for phytoplankton biomass) was retrieved from the MODIS instrument on the Aqua satellite, with data distributed by the NASA Ocean Biology Processing Group, and averaged into monthly climatological composites. The data span the years 2003-2020 and this record includes data at 4 km pixel resolution.Methods:MODIS-Aqua Chlorophyll-a (Chl-a) was acquired from the NASA Ocean Biology Processing Group at processing Level-3 (version 2018), 4-km resolution, where Chl-a concentration was calculated using the OC3/OCI method. The months of January and December were excluded from this dataset, as data in the winter months at higher latitudes are missing due to low sun angle preventing acquisition. The monthly geometric mean value at all pixels was calculated for individual years, then the geometric mean and geometric standard deviation factor of chlorophyll-a were calculated by month from these images. These methods of calculating mean and standard deviation were used due to the log-normal distribution of chlorophyll-a. The geometric standard deviation is a unitless factor, where the lower bound is the ratio of the geometric mean and geometric standard deviation, and the upper bound is the multiplication of the two. In addition to the geometric mean and geometric standard deviation factor the number of occurrences of valid data at each pixel over the period of observation were calculated. Pixels with fewer than two occurrences over the entire period of observation were removed from these maps, and set to a NaN value in the tif files. All resulting rasters were cropped to the Canadian Exclusive Economic Zone and assigned to the NAD83 geographic coordinate reference system (EPSG:4269), and have a final pixel resolution of approximately 0.0417 degrees. The monthly geometric mean, monthly geometric standard deviation factor, and number of occurrences for all pixels are provided.Data Sources:NASA Ocean Biology Processing Group. (2017). MODIS-Aqua Level 2 Ocean Color Data Version R2018.0. NASA Ocean Biology Distributed Active Archive Center. https://doi.org/10.5067/AQUA/MODIS/L2/OC/2018Uncertainties:Satellite values have been evaluated against global datasets, and datasets of samples in the Pacific region (see references). However, uncertainties are introduced when averaging together images over time as each pixel has a differing number of observations. Short-lived or spatially limited events may be missed.
Monthly Satellite Sea Surface Temperature Climatology of the Canadian Pacific Exclusive Economic Zone (2003-2020) – 1 km Resolution
Description:Night-time sea surface temperature (SST) was retrieved from the MODIS instrument on the Aqua satellite, with data distributed by the NASA Ocean Biology Processing Group, and averaged into monthly climatological composites. The data span the years 2003-2020; records were created at 1 km pixel resolution to be consistent with other satellite products.Methods:MODIS-Aqua night long-wave Sea Surface Temperature (SST) images were acquired from the NASA Ocean Biology Processing Group at processing Level-2 (version 2018), 1-km resolution, spanning the period 2003-01-01 to 2020-12-31. Image pixels were aligned and mapped to a regular grid using the SeaDAS program, retaining all pixels with a quality level of ‘1’ or lower, which is recommended for scientific analysis. The monthly mean value at all pixels was calculated for individual years, and used to produce maps of the monthly climatological mean and standard deviation of SST. Additionally, the number of occurrences of valid data at each pixel over the period of observation were calculated. Pixels with fewer than two occurrences over the entire period of observation were removed from these maps, and set to a NaN value in the tif files. A few small gaps between pixels (near the edges of individual images) were filled using the median value of surrounding pixels, provided there were greater than 4 values. Finally, all rasters were cropped to the Canadian Exclusive Economic Zone and assigned to the NAD83 geographic coordinate reference system (EPSG:4269), and have a final pixel resolution of approximately 0.01 degrees. The monthly mean, monthly standard deviation, and number of occurrences for all pixels are provided.Data Sources:NASA Ocean Biology Processing Group. (2017). MODIS-Aqua Level 2 Ocean Color Data Version R2018.0. NASA Ocean Biology Distributed Active Archive Center. https://doi.org/10.5067/AQUA/MODIS/L2/OC/2018Uncertainties:Satellite values have been evaluated against global datasets, and datasets of samples in the Pacific region (see references). However, uncertainties are introduced when averaging together images over time as each pixel has a differing number of observations. Short-lived or spatially limited events may be missed.
Monthly Satellite Chlorophyll-a Climatology of the Canadian Pacific Exclusive Economic Zone (2003-2020) - 1 km Resolution
Description:Chlorophyll-a concentration (a proxy for phytoplankton biomass) was retrieved from the MODIS instrument on the Aqua satellite, with data distributed by the NASA Ocean Biology Processing Group, and averaged into monthly climatological composites. The data span the years 2003-2020 and this record includes data at 1 km pixel resolution.Methods:MODIS-Aqua Chlorophyll-a (Chl-a) was acquired from the NASA Ocean Biology Processing Group at processing Level-2 (version 2018), 1-km resolution, where Chl-a concentration was calculated using the OC3/OCI method. The months of January and December were excluded from this dataset, as data in the winter months at higher latitudes are missing due to low sun angle preventing acquisition. The pixels were aligned on a regular grid using the SeaDAS program, after which the monthly geometric mean value at all pixels was calculated for individual years. Finally, the geometric mean and geometric standard deviation factor of chlorophyll-a were calculated by month from these images. These methods of calculating mean and standard deviation were used due to the log-normal distribution of chlorophyll-a. The geometric standard deviation is a unitless factor, where the lower bound is the ratio of the geometric mean and geometric standard deviation, and the upper bound is the multiplication of the two. In addition to these variables, the number of occurrences of valid data at each pixel over the period of observation were calculated. Pixels with fewer than two occurrences over the entire period of observation were removed from these maps, and set to a NaN value in the tif files. A few small gaps between pixels (near the edges of individual images) were filled using the median value of surrounding pixels, provided there were greater than 4 values. Finally, all rasters were cropped to the Canadian Exclusive Economic Zone and assigned to the NAD83 geographic coordinate reference system (EPSG:4269), and have a final pixel resolution of approximately 0.01 degrees. The monthly geometric mean, monthly geometric standard deviation factor, and number of occurrences for all pixels are provided.Data Sources:NASA Ocean Biology Processing Group. (2017). MODIS-Aqua Level 2 Ocean Color Data Version R2018.0. NASA Ocean Biology Distributed Active Archive Center. https://doi.org/10.5067/AQUA/MODIS/L2/OC/2018Uncertainties:Satellite values have been evaluated against global datasets, and datasets of samples in the Pacific region (see references). However, uncertainties are introduced when averaging together images over time as each pixel has a differing number of observations. Short-lived or spatially limited events may be missed.
Year-round utilization of sea ice-associated carbon in Arctic ecosystems
This record contains a comprehensive synthesis of previously published highly branched isoprenoid (HBI) results, providing a quantitative spatial and temporal assessment of carbon partitioning within the Arctic marine ecosystem and validating estimates of sea-ice particulate organic carbon (iPOC) values as quantitative predictors of ice algal carbon in Arctic food webs.This publication was a collaborative effort with the following contributors: David Yurkowski (Fisheries and Oceans Canada), Lisa Loseto (Fisheries and Oceans Canada), Steve Ferguson (Fisheries and Oceans Canada), Bruno Rosenberg (Fisheries and Oceans Canada), C.W. Koch (Natural History Museum, London, UK; University of Maryland Center for Environmental Science, Maryland, US); T.A. Brown (Scottish Association for Marine Science, Oban, Scotland); R. Amiraux (Centre for Earth Observation Science, University of Manitoba, Canada); C. Ruiz-Gonzalez (Scottish Association for Marine Science, Oban, Scotland); M. Maccorquodale (Scottish Association for Marine Science, Oban, Scotland); G. Yunda-Guarin (Québec-Océan and Takuvik, Biology Department, Laval University, Canada); D. Kohlbach (Norwegian Polar Institute, Fram Centre, Tromsø, Norway); N.E. Hussey (Integrative Biology, University of Windsor, Ontario, Canada).
Northern marine coastal and ecosystem studies in the Canadian Beaufort Sea—sampling information
The objective of this project was to gather data to develop a model of the food web of the lower trophic levels of the nearshore area of the Beaufort Sea. Sampling took place from 2005 to 2008 using the CCGS Nahidik. The multidisciplinary character of the Nahidik program produced measurements of biology/ecology (primary production, phytoplankton, zooplankton, benthos, fish), chemical and physical oceanography, contaminants, geology and hydro acoustics. The data were collected in July and August of each year. The Nahidik program provided data to provide a baseline for future studies as well as an information source for environmental assessment.
Northern Marine Coastal and Ecosystem Studies in the Canadian Beaufort Sea—sample locations
The objective of this project was to gather data to develop a model of the food web of the lower trophic levels of the nearshore area of the Beaufort Sea. Sampling took place from 2005 to 2008 using the CCGS Nahidik. The multidisciplinary character of the Nahidik program produced measurements of biology/ecology (primary production, phytoplankton, zooplankton, benthos, fish), chemical and physical oceanography, contaminants, geology and hydro acoustics. The data were collected in July and August of each year. The Nahidik program provided data to provide a baseline for future studies as well as an information source for environmental assessment. This record contains the geographic coordinates and station names from 2005 to 2008.
Biodiversity of the Benthic Epifauna Trawl Survey from KEBABB program (2021)
This resource documents a dataset of epifauna occurrences collected in 2021 during The Knowledge and Ecosystem-Based Approach in Baffin Bay (KEBABB) program developed by the Department of Fisheries and Oceans Canada (DFO) in collaboration with university partners. The overall objective of KEBABB is to characterize the variability and trends in physical, chemical, and biological oceanographic conditions and food webs supporting fisheries in the connected ecosystems of western Baffin Bay and Lancaster Sound. In 2021, DFO expanded the KEBABB program to Barrow Strait (KEBABS-Knowledge and Ecosystem-Based Approach in Barrow Strait), a key productive area of the Tallurutiup Imanga National Marine Conservation Area. The study took place in the Eastern Canadian Arctic (mainly in Baffin Bay, Davis Strait and Barrow Strait). Sampling is done along transects at fixed stations in the study area. Catches are collected with a 1.5 m Agassiz trawl (5 mm mesh net) for 3 minutes bottom-contact time at a target speed of 1.5 knots and with a 3 m benthic beam trawl (6.4 mm mesh net) for 15 minutes bottom-contact time at a target speed of 3 knots. A total of 16 stations were sampled for epifauna in 2021 between 85-850 m depth. Epibenthic invertebrates are identified to the lowest possible taxonomic level and photographed. All unknown specimens are frozen. In the lab, the identifications are validated or refined with the photos and the frozen specimens.The data are presented in Darwin Core and are separated in two files:The “Activité_épifaune_KEBABB_epifauna_event_en” file which contains information about missions, stations and deployments, which are presented under a hierarchical activity structure.The “Occurrence_épifaune_KEBABB_epifauna_en” file that contains the taxonomic occurrences.Further details on sampling can be found in the following report: Pućko, M., Charette, J., Tremblay P., Brulotte S., St-Denis B., Ciastek S., Hedges, K., Kuzyk, Z., Roy V., and Michel, C. 2022. An ecosystem-based approach in the eastern Arctic: KEBABB/S (Knowledge and Ecosystem-Based Approach in Baffin Bay/Barrow Strait) 2021 expedition report. Can. Manuscr. Rep. Fish. Aquat. Sci. 3250: viii + 58 p. https://publications.gc.ca/collections/collection_2022/mpo-dfo/Fs97-4-3250-eng.pdfUSE LIMITATION:To ensure scientific integrity and appropriate use of the data, we would encourage you to contact the data custodian.
Ecologically or Biologically Significant Marine Areas (EBSAs), Newfoundland and Labrador Shelves
The Oceans Act (1997) commits Canada to maintaining biological diversity and productivity in the marine environment. A key component of this is to identify areas that are considered ecologically or biologically significant. Fisheries and Oceans Canada (DFO) Science has developed guidance on the identification of Ecologically or Biologically Significant Areas (EBSAs) (DFO 2004) and has endorsed the scientific criteria of the Convention on Biological Diversity (CBD) for identifying ecologically or biologically significant marine areas as defined in Annex I of Decision IX/20 of its 9th Conference of Parties. These criteria were applied to the Newfoundland and Labrador (NL) Shelves Bioregion in two separate data-driven processes. The first process focused on the area north of the Placentia Bay-Grand Banks (PBGB) Large Ocean Management Area (LOMA) (DFO 2013). The second process focused on the PBGB area (DFO 2019), where EBSAs had previously been identified using a more Delphic approach (Templeman 2007). In both cases, an EBSA Steering Committee, comprised of experts in oceanography, ecosystem structure and function, taxa-specific life histories and Geographic Information Systems (GIS) guided the process by advising or aiding in the identification, collection, processing and analysis of data layers, as well as participating in the final selection of candidate EBSAs (Wells et al. 2017, Ollerhead et al. 2017, Wells et al. 2019). All information was compiled in a GIS and a hierarchical approach was used to review individual data layers and groupings of data layers. Peer review meetings were held for both processes, during which candidate EBSAs were reviewed and the final EBSAs were agreed upon and delineated. In the northern study area, a total of fifteen EBSAs were identified and described; three of these areas are primarily coastal areas; seven are in offshore areas; four EBSAs straddle coastal and offshore areas; and one is a transitory EBSA that follows the southern extent of pack ice. In the PBGB study area, fourteen EBSAs were identified in two different categories: seven based on coastal data and seven based on offshore data. In comparing the new PBGB EBSAs to those identified in 2007, nine of them overlap spatially and are based on similar features; however, there were some variations in the boundaries. Two of the EBSAs that were identified in 2007 were no longer considered EBSAs in 2017, but portions of both of these areas were captured in part by other EBSAs. Five new EBSAs were identified in areas not previously considered.References:DFO, 2004. Identification of Ecologically and Biologically Significant Areas. DFO Can. Sci. Advis. Sec. Ecosystem Status Rep. 2004/006.DFO. 2013. Identification of additional Ecologically and Biologically Significant Areas (EBSAs) within the Newfoundland and Labrador Shelves Bioregion. DFO Can. Sci. Advis. Sec. Sci. Advis. Rep. 2013/048.DFO. 2019. Re-evaluation of the Placentia Bay-Grand Banks Area to Identify Ecologically and Biologically Significant Areas . DFO Can. Sci. Advis. Sec. Sci. Advis. Rep. 2019/040.Ollerhead, L.M.N., Gullage, M., Trip, N., and Wells, N. 2017. Development of Spatially Referenced Data Layers for Use in the Identification and Delineation of Candidate Ecologically and Biologically Significant Areas in the Newfoundland and Labrador Shelves Bioregion. DFO Can. Sci. Advis. Sec. Res. Doc. 2017/036. v + 38 pTempleman, N.D. 2007. Placentia Bay-Grand Banks Large Ocean Management Area Ecologically and Biologically Significant Areas. Can. Sci. Advis. Sec. Res. Doc. 2007/052: iii + 15 p.Wells, N.J., Stenson, G.B., Pepin, P., and Koen-Alonso, M. 2017. Identification and Descriptions of Ecologically and Biologically Significant Areas in the Newfoundland and Labrador Shelves Bioregion. DFO Can. Sci. Advis. Sec. Res. Doc. 2017/013. v + 87 p.Wells, N., K. Tucker, K. Allard, M. Warren, S. Olson, L. Gullage, C. Pretty, V. Sutton-Pande and K. Clarke. 2019. Re-evaluation of the Placentia Bay-Grand Banks Area of the Newfoundland and Labrador Shelves Bioregion to Identify and Describe Ecologically and Biologically Significant Areas. DFO Can. Sci. Advis. Sec. Res. Doc. 2019/049. viii + 138 p.
Northern marine coastal and ecosystem studies in the Canadian Beaufort Sea—water quality data
The objective of this project was to gather data to develop a model of the food web of the lower trophic levels of the nearshore area of the Beaufort Sea. Sampling took place from 2005 to 2008 using the CCGS Nahidik. The multidisciplinary character of the Nahidik program produced measurements of biology/ecology (primary production, phytoplankton, zooplankton, benthos, fish), chemical and physical oceanography, contaminants, geology and hydro acoustics. The data were collected in July and August of each year. The Nahidik program provided data to provide a baseline for future studies as well as an information source for environmental assessment.This record contains water chemistry data collected as part of this project including suspended nitrogen, dissolved nitrogen, suspended phosphorus, dissolved phosphorus, dissolved organic carbon, suspended carbon, chlorophyll a, and suspended silicon.
Biologic and Ecologic
BiologicEcologic ISO Feature Dataset symbolization and publication. September 5, 2017.
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