Item talk:Q322945

{

 "id": "10.5066/p9bxibf9",
 "attributes": {
   "doi": "10.5066/p9bxibf9",
   "identifiers": [],
   "creators": [
     {
       "name": "Skinner, Kenneth D",
       "nameType": "Personal",
       "givenName": "Kenneth D",
       "familyName": "Skinner",
       "affiliation": [],
       "nameIdentifiers": [
         {
           "schemeUri": "https://orcid.org",
           "nameIdentifier": "https://orcid.org/0000-0003-1774-6565",
           "nameIdentifierScheme": "ORCID"
         }
       ]
     }
   ],
   "titles": [
     {
       "title": "Surrogate regression model data for estimating nitrate concentrations at six springs in Gooding County, south-central Idaho"
     }
   ],
   "publisher": "U.S. Geological Survey",
   "container": {},
   "publicationYear": 2023,
   "subjects": [
     {
       "subject": "Aquatic Biology, Hydrology, Water Quality, Water Resources"
     }
   ],
   "contributors": [],
   "dates": [
     {
       "date": "2023",
       "dateType": "Issued"
     }
   ],
   "language": null,
   "types": {
     "ris": "DATA",
     "bibtex": "misc",
     "citeproc": "dataset",
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     "resourceType": "Dataset",
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   },
   "relatedIdentifiers": [
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       "relatedIdentifier": "10.3133/sir20235095",
       "relatedIdentifierType": "DOI"
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   "descriptions": [
     {
       "description": "Endangered Banbury Springs limpet and threatened Bliss Rapids snail populations in springs along the Snake River in southern Gooding County, south-central Idaho, are declining. To protect these species, the U.S. Fish and Wildlife Service (USFWS) needs to understand what affects the species' habitat such as aquatic vegetation, associated with elevated nitrate concentrations in the springs. In cooperation with the USFWS, the U.S. Geological Survey developed surrogate regression models to estimate nitrate concentration using specific conductance, day of the year, and streamflow as potential explanatory variables. These surrogate models provide a cheaper alternative than measuring nitrate concentrations directly, through discrete sampling, or continuous monitoring via nitrate sensor equipped sonde. The spring surrogate regression models showed that specific conductance can be an effective surrogate for nitrate in springs affected by agriculture and that the model results improved when streamflow data were included. The spring surrogate regression models vary in their ability to estimate nitrate concentration. All the surrogate regression models are included in this data release with the associated USGS Scientific Investigations Report describing the best surrogate regression models to use at each spring.",
       "descriptionType": "Abstract"
     }
   ],
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   "url": "https://www.sciencebase.gov/catalog/item/63dbfa58d34e9fa19a98a102",
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   "state": "findable",
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   "created": "2023-08-29T19:44:33Z",
   "registered": "2023-08-29T19:44:34Z",
   "published": null,
   "updated": "2023-09-01T14:08:58Z"
 },
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}