Item talk:Q324462

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{

 "id": "10.5066/p9i00wfr",
 "attributes": {
   "doi": "10.5066/p9i00wfr",
   "identifiers": [],
   "creators": [
     {
       "name": "Read, Jordan S",
       "nameType": "Personal",
       "givenName": "Jordan S",
       "familyName": "Read",
       "affiliation": [],
       "nameIdentifiers": [
         {
           "schemeUri": "https://orcid.org",
           "nameIdentifier": "https://orcid.org/0000-0002-3888-6631",
           "nameIdentifierScheme": "ORCID"
         }
       ]
     },
     {
       "name": "Willard, Jared",
       "nameType": "Personal",
       "givenName": "Jared",
       "familyName": "Willard",
       "affiliation": [],
       "nameIdentifiers": []
     },
     {
       "name": "Appling, Alison P",
       "nameType": "Personal",
       "givenName": "Alison P",
       "familyName": "Appling",
       "affiliation": [],
       "nameIdentifiers": [
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           "schemeUri": "https://orcid.org",
           "nameIdentifier": "https://orcid.org/0000-0003-3638-8572",
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       ]
     },
     {
       "name": "Oliver, Samantha K",
       "nameType": "Personal",
       "givenName": "Samantha K",
       "familyName": "Oliver",
       "affiliation": [],
       "nameIdentifiers": []
     }
   ],
   "titles": [
     {
       "title": "Data release: Predicting Water Temperature Dynamics of Unmonitored Lakes with Meta Transfer Learning (Provisional Data Release)"
     }
   ],
   "publisher": "U.S. Geological Survey",
   "container": {},
   "publicationYear": 2021,
   "subjects": [
     {
       "subject": "Aquatic Biology, Climatology, Hydrology, Limnology, Water Quality, Water Resources"
     }
   ],
   "contributors": [],
   "dates": [
     {
       "date": "2021",
       "dateType": "Issued"
     }
   ],
   "language": null,
   "types": {
     "ris": "DATA",
     "bibtex": "misc",
     "citeproc": "dataset",
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       "relatedIdentifier": "10.1029/2021wr029579",
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   "descriptions": [
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       "description": "These data are preliminary or provisional and are subject to revision. They are being provided to meet the need for timely best science. The data have not received final approval by the U.S. Geological Survey (USGS) and are provided on the condition that neither the USGS nor the U.S. Government shall be held liable for any damages resulting from the authorized or unauthorized use of the data. Climate change and land use change have been shown to influence lake temperatures and water clarity in different ways. To better understand the diversity of lake responses to climate change and give managers tools to manage individual lakes, we focused on improving prediction accuracy for daily water temperature profiles in 2,332 lakes during 1980-2019. The data are organized into these items: This research was funded by the Department of the Interior Northeast and North Central Climate Adaptation Science Centers, a Midwest Glacial Lakes Fish Habitat Partnership grant through F&WS Access to computing facilities was provided by USGS Advanced Research Computing, USGS Yeti Supercomputer (https://doi.org/10.5066/F7D798MJ). We thank North Temperate Lakes Long-Term Ecological Research (NSF DEB-1440297) and Global Lake Ecological Observatory Network (NSF #1702991). Lake Information - A lake metadata file and one shapefile of polygons for all 2,332 lakes in this study Observations - Temperature observations for the 2,332 lakes used in this study Model Configurations - Model parameters and metadata used to configure models Model Inputs - Data used to drive predictive models (ice-flags and daily meteorology) Model Predictions - Predictions for water temperature Model Evaluation - Performance of models",
       "descriptionType": "Abstract"
     }
   ],
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   "url": "https://www.sciencebase.gov/catalog/item/5ebe542b82ce476925e44b20",
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   "created": "2020-10-30T18:13:37Z",
   "registered": "2020-10-30T18:13:38Z",
   "published": null,
   "updated": "2023-03-05T04:57:10Z"
 },
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}