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| griddap | Subset | tabledap | Make A Graph | wms | files | Accessible | Title | Summary | FGDC | ISO 19115 | Info | Background Info | RSS | Institution | Dataset ID | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| log in | [Global Seabird Breeding Success] - Annual seabird productivity at breeding colonies around the world from 1964 to 2023 (Stratification Impacts on Seabirds Project) (Global analysis of stratification impacts on seabirds through food resources ) | This global dataset on breeding productivity represents a compilation of individual time series from species and sites (seabird breeding colonies) across the world. Each time series was contributed by a Global Seabird Working Group (GSWG) collaborator. It contains the number of offspring produced per nesting female per year, which is a variable measured similarly by researchers. Seabird breeding productivity is typically measured by monitoring individual nest sites through time within each breeding season. Data from multiple females are then averaged to produce estimates of annual productivity for each species at each site, resulting in “species-site” time series. Typically, measurements are made for multiple species at each site, so data are often available for a portion of the full seabird community, including species feeding at different trophic levels and in different parts of the water column. Variance for species-site breeding productivity is estimated as the standard error across years for each time series. Here, there are 202 time series encompassing 87 sites and 73 seabird species.\n\ncdm_data_type = Other\nVARIABLES:\nyear (unitless)\nsite (unitless)\nlatitude (degrees_north)\nlongitude (degrees_east)\nspeciesnum (unitless)\nspecies (unitless)\nScientificName_accepted (unitless)\nAphiaID (unitless)\nLSID (unitless)\nbreeding_success (reproduction_rate)\nn (individuals)\n | BCO-DMO | bcodmo_dataset_985565_v1 | ||||||||||||
| log in | [Ocean Conditions at Seabird Colony Sites] - Seasonally and spatially averaged stratification mixed layer temperature and chlorophyll-a around Northern Hemisphere seabird colonies from 1993 to 2019 (Stratification impacts on seabirds project) (Global analysis of stratification impacts on seabirds through food resources ) | This dataset provides seasonal averages of mixed layer temperature, water column stratification, and mixed layer chlorophyll-a content for coastal marine regions around the world using the Marine Ecoregions of the World (MEOW) framework. The MEOW framework spatially partitions coastal marine areas into a hierarchical, nested structure based on biogeographic and environmental characteristics. Seven ecosystems are represented in the dataset: the Arctic, Cold Temperate Northeast Pacific, Cold Temperate Northwest Pacific, Warm Temperate Northeast Pacific, Hawaii, Northern European Seas, and Cold Temperate Northwest Atlantic, which are roughly equivalent to Large Marine Ecosystems. Environmental data was extracted for the domain of these seven ecosystems using the GLORYS12V1 global ocean reanalysis, which resolves monthly ocean conditions at 1/12-degree, daily resolution across 50 vertical depth levels. This state-of-the-art reanalysis assimilates historical data from multiple sources, including satellite observations and buoy data, and covers the period from 1993 to 2019. We extracted temperature, mixed layer depth, and salinity for the upper 200 m of the water column, which were used to calculate coastal stratification. Stratification was quantified using the Potential Energy Anomaly (PEA), a robust metric that measures the energy required to thoroughly mix the water column and reflects seasonal stratification patterns. All environmental variables were spatially averaged over corresponding ecoregions and temporally averaged over the pre-breeding and breeding seasons of seabird colonies within the ecoregion. By offering detailed classifications and environmental characterizations, this dataset serves as a valuable resource for analyzing regional oceanographic patterns and understanding how physical processes shape seabird populations and marine ecosystems.\n\ncdm_data_type = Other\nVARIABLES:\nidnum (exp_id)\nyear (years)\nspp (unitless)\nScientificName_accepted (unitless)\nAphiaID (unitless)\nLSID (unitless)\nsite (unitless)\nsppsite (unitless)\n... (27 more variables)\n | BCO-DMO | bcodmo_dataset_985768_v1 | ||||||||||||
| https://erddap.bco-dmo.org/erddap/tabledap/bcodmo_dataset_3095 | https://erddap.bco-dmo.org/erddap/tabledap/bcodmo_dataset_3095.graph | https://erddap.bco-dmo.org/erddap/files/bcodmo_dataset_3095/ | public | [phytoplankton taxonomy] - Time-Series of Phytoplankton Taxonomy and Density collected by the CARIACO Ocean Time-Series Project from November 1995 to January 2017 (CARIACO Ocean Time-Series Program) | The CARIACO Ocean Time-Series Program (formerly known as CArbon Retention In A Colored Ocean) started on November 1995 (CAR-001) and ended on January 2017 (CAR-232). Monthly cruises were conducted to the CARIACO station (10.50\\u00b0 N, 64.67\\u00b0 W) onboard the R/V Hermano Gin\\u00e9s of the Fundaci\\u00f3n La Salle de Ciencias Naturales de Venezuela. The program studied the relationship between surface primary production, physical forcing variables like the wind, and the settling flux of particulate carbon in the Cariaco Basin. This depression, located on the continental shelf of Venezuela, shows marked seasonal and interannual variation in hydrographic properties and primary production (carbon fixation rates by photosynthesis of planktonic algae).\\r\\n\\r\\nOne of the monthly measurements taken by the program was water sampling at different depths for phytoplankton taxonomy (occurrence and density). Those water samples were collected with Niskin bottles during the first CTD Cast of the morning at 1, 7, 25, 35, 75, and 100 m depth. Phytoplankton taxonomy and density was determined at each depth at the level of species or genera. Values of zero are real and denote that a specific species was not found at that cruise/depth.\n\ncdm_data_type = Other\nVARIABLES:\nCruise (unitless)\nCruise_ID_2 (unitless)\nLeg (unitless)\nCast (unitless)\nDay_local (unitless)\nMonth_local (unitless)\nYear_local (unitless)\nlatitude (degrees_north)\nlongitude (degrees_east)\nTime_start_local (unitless)\nTime_end_local (unitless)\nDatetime_local (unitless)\ntime (Datetime UTC, seconds since 1970-01-01T00:00:00Z)\nSpeciesNameOriginal (Species Name Original, unitless)\nSpeciesNameCleaned (Species Name Cleaned, unitless)\n... (11 more variables)\n | https://erddap.bco-dmo.org/erddap/metadata/fgdc/xml/bcodmo_dataset_3095_fgdc.xml | https://erddap.bco-dmo.org/erddap/info/bcodmo_dataset_3095/index.htmlTable | https://www.bco-dmo.org/dataset/3095
| https://erddap.bco-dmo.org/erddap/rss/bcodmo_dataset_3095.rss | https://erddap.bco-dmo.org/erddap/subscriptions/add.html?datasetID=bcodmo_dataset_3095&showErrors=false&email= | BCO-DMO | bcodmo_dataset_3095 |