{"help": "https://canwin-datahub.ad.umanitoba.ca/data/fr/api/3/action/help_show?name=package_show", "success": true, "result": {"Creator": "Creator", "Date": "2021-02-04", "IdentifierType": "DOI", "PublicationYear": "2026", "Publisher": "CanWIN", "RelatedIdentifierType": "URL", "RelationType": "IsSupplementTo", "ResourceType": "Phytoplankton bloom", "Rights": "Creative Commons Attribution 4.0 International", "Version": "2", "accessTerms": "CanWIN datasets are licensed individually, details for each licence used can be found using the Licence URL link provided with each dataset. \r\nBy accessing this Web site and Database, you are agreeing to be bound by CanWIN's Terms of Use, all applicable laws and regulations, and agree that you are responsible for compliance with any applicable local laws. If you do not agree with any of these terms, do not use this site. Any claim relating to this web site shall be governed by the laws of the Province of Manitoba without regard to its conflict of law provisions", "activityCollectionType": "", "author": null, "author_email": null, "campaignEndDate": "", "campaignStartDate": "", "contributorName": "Lucas Barbedo", "contributorType": "DataCurator", "creator_user_id": "c3ad971e-75e0-4e57-b825-8ed25f306937", "dataCuratorAffiliation": "Universit\u00e9 du Qu\u00e9bec \u00e0 Rimouski", "dataCuratorEmail": "lucasbarbedo@gmail.com", "datasetCitation": "Barbedo, L. 2020. \"Sea-Ice Edge Phytoplankton Bloom\", Baysys Team 3 - Marine Ecosystems, 10.34992/1e0k-4m16, Canadian Watershed Information Network, V1.", "datasetIdentifier": "10.34992/1e0k-4m16", "datasetLevel": "1.2", "datasetPublisher": "CanWIN", "dateType": "Updated", "descriptionType": "Abstract", "embargoDate": "", "endDate": "2021-11-11", "endDateType": "Other", "frequency": "As needed", "id": "49695e4c-2b6d-4144-8939-fe680eebf4c7", "isopen": false, "kvSchemeURI": "https://www.polardata.ca/pdcinput/public/keywordlibrary", "licenceShemeURI": "https://spdx.org/licenses", "licenceType": "Open", "license_id": null, "license_title": null, "maintainer": null, "maintainer_email": null, "metadata_created": "2021-11-05T01:58:56.756124", "metadata_modified": "2026-02-24T00:04:37.278138", "methodCitation": "", "name": "sea-ice-edge-phytoplankton-bloom", "notes": "Satellite-derived sea-ice retreat timing (tR) and maximum chlorophyll-a concentration in the ice edge zone between 1998 and 2018. Sea ice concentration (SIC) was obtained from the National Snow and Ice Data Center. It is based on daily passive microwave radiometry processed using the Bootstrap algorithm (Comiso, 2000) at 25 km resolution. The Bootstrap technique clusters the multichannel passive microwave sensors: Scanning Multi- channel Microwave Radiometer on the Nimbus-7 satellite, Special Sensor Microwave/Imager and Special Sensor Microwave Imager/Sounder from the Defense Meteorological Satellite Program\u2019s satellites, and the Advanced Microwave Scanning Radiometer (Comiso et al., 1997). SIC was interpolated onto the same Chla grid using the nearest neighborhood scheme implemented in Matlab.\r\n\r\nMulti-sensor merged clorophyll-a concentration (Chla) Level-3 (i.e., binned and mapped) 8-day composites from the Globcolour Project (http://www.globcolour.info/) were used as a proxy for phytoplankton biomass. Globcolour products have a spa- tial resolution of 4.63 km and cover the 1998\u20132018 period. The merged product was selected to improve the spatial-temporal coverage diminishing gaps due to cloud cover and sea-ice coverage (Maritorena et al., 2010). The binning methodology combines the normalized water- leaving radiances from different ocean color sensors whenever they are available, which includes SeaWiFS (1998\u20132010), MODIS-Aqua (2002\u20132018), Medium- Resolution Imaging Spectrometer (MERIS: 2002\u20132011), and Visible Infrared Imaging Radiometer Suite (VIIRS: 2012\u20132018). [Chla] was estimated from normalized water-leaving radiances merged using the Garver-Siegel- Maritorena (GSM) semi-analytical model (Garver and Siegel, 1997; Maritorena et al., 2002).\r\n\r\nTo assess the impacts of sea-ice retreat timing on marginal ice zone phytoplankton blooms (also refers to phytoplankton spring blooms or ice-edge blooms), we analyzed both Chla and SIC variability in parallel. The method is similar to that of Perrette et al. (2011), which was also adopted by Lowry et al. (2014) and Renaut et al. (2018). The sea-ice retreat, tR, is defined as the day at which SIC is below 10% for at least 24 days. This time interval is longer than the 20 days applied by Perrette et al. (2011) and Renaut et al. (2018) and the 14 days by Lowry et al. (2014) because we used 8-day composites instead of daily maps. However, to avoid sub-pixel contamination in ice-infested regions near the ice edge (Be\u00b4langer et al., 2013), we opted to be more conservative by applying a 10% threshold on SIC, as did Perrette et al. (2011) and Renaut et al. (2018) instead of 50% as applied by Lowry et al. (2014). 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You can view the full terms here (https://lwbin.cc.umanitoba.ca/wp-content/uploads/2019/10/CanWIN_DataPolicy_Nov2019.pdf). \r\nCitation: The Data User should properly cite the Data Set in any publications or in the metadata of any derived data products that were produced using the Data Set. \r\nAcknowledgement: The Data User should acknowledge any institutional support or specific funding awards referenced in the metadata accompanying this dataset in any publications where the Data Set contributed significantly to its content. Acknowledgements should identify the supporting party, the party that received the support, and any identifying information such as grant numbers. \r\nNotification: The Data User should notify the Data Set Contact when any derivative work or publication based on or derived from the Data Set is distributed. Notification will include an explanation of how the Data Set was used to produce the derived work. \r\nCollaboration: The Data Set has been released in the spirit of open scientific collaboration. 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Sea ice concentration (SIC) was obtained from the National Snow and Ice Data Center. It is based on daily passive microwave radiometry processed using the Bootstrap algorithm (Comiso, 2000) at 25 km resolution. The Bootstrap technique clusters the multichannel passive microwave sensors: Scanning Multi- channel Microwave Radiometer on the Nimbus-7 satellite, Special Sensor Microwave/Imager and Special Sensor Microwave Imager/Sounder from the Defense Meteorological Satellite Program\u2019s satellites, and the Advanced Microwave Scanning Radiometer (Comiso et al., 1997). SIC was interpolated onto the same Chla grid using the nearest neighborhood scheme implemented in Matlab.\r\n\r\nMulti-sensor merged clorophyll-a concentration (Chla) Level-3 (i.e., binned and mapped) 8-day composites from the Globcolour Project (http://www.globcolour.info/) were used as a proxy for phytoplankton biomass. Globcolour products have a spa- tial resolution of 4.63 km and cover the 1998\u20132018 period. 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