Item talk:Q318913

{

 "DOI": {
   "doi": "10.5066/p1be5qtk",
   "identifiers": [],
   "creators": [
     {
       "name": "Amy K Wray",
       "nameType": "Personal",
       "affiliation": [
         "United States Geological Survey"
       ],
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     {
       "name": "Helen T Davis",
       "nameType": "Personal",
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         "United States Geological Survey"
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     },
     {
       "name": "Bradley J Udell",
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         "United States Geological Survey"
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     },
     {
       "name": "Teresa F Bohner",
       "nameType": "Personal",
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         "United States Geological Survey"
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     {
       "name": "Rich D Inman",
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         "United States Geological Survey"
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     },
     {
       "name": "Bennett T. Lohre",
       "nameType": "Personal",
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         "United States Geological Survey"
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     },
     {
       "name": "Haley B Price",
       "nameType": "Personal",
       "affiliation": [
         "Contractor to the United States Geological Survey"
       ],
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     {
       "name": "Jonathan Reichard",
       "nameType": "Personal",
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         "null"
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           "nameIdentifier": "https://orcid.org/0000-0002-4792-2868",
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       ]
     },
     {
       "name": "Andrea N Schuhmann",
       "nameType": "Personal",
       "affiliation": [
         "United States Geological Survey"
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       ]
     },
     {
       "name": "Bethany R Straw",
       "nameType": "Personal",
       "affiliation": [
         "United States Geological Survey"
       ],
       "nameIdentifiers": [
         {
           "schemeUri": "https://orcid.org",
           "nameIdentifier": "https://orcid.org/0000-0001-9086-4600",
           "nameIdentifierScheme": "ORCID"
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       ]
     },
     {
       "name": "Frank C. Tousley",
       "nameType": "Personal",
       "affiliation": [
         "United States Geological Survey"
       ],
       "nameIdentifiers": [
         {
           "schemeUri": "https://orcid.org",
           "nameIdentifier": null,
           "nameIdentifierScheme": "ORCID"
         }
       ]
     },
     {
       "name": "Jill Utrup",
       "nameType": "Personal",
       "affiliation": [
         "United States Fish and Wildlife Service"
       ],
       "nameIdentifiers": [
         {
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           "nameIdentifier": null,
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       ]
     },
     {
       "name": "Brian E Reichert",
       "nameType": "Personal",
       "affiliation": [
         "United States Geological Survey"
       ],
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           "nameIdentifier": "https://orcid.org/0000-0002-9640-0695",
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   ],
   "titles": [
     {
       "title": "North American Bat Monitoring Program (NABat) Predicted Northern Long-Eared Bat Occupancy Probabilities"
     }
   ],
   "publisher": "U.S. Geological Survey",
   "container": {},
   "publicationYear": 2024,
   "subjects": [
     {
       "subject": "Ecology"
     },
     {
       "subject": "FOS: Biological sciences",
       "schemeUri": "http://www.oecd.org/science/inno/38235147.pdf",
       "subjectScheme": "Fields of Science and Technology (FOS)"
     },
     {
       "subject": "Wildlife Biology"
     }
   ],
   "contributors": [],
   "dates": [],
   "language": null,
   "types": {
     "ris": "DATA",
     "bibtex": "misc",
     "citeproc": "dataset",
     "schemaOrg": "Dataset",
     "resourceType": "Dataset",
     "resourceTypeGeneral": "Dataset"
   },
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   "version": null,
   "rightsList": [],
   "descriptions": [
     {
       "description": "These data contain the results from the North American Bat Monitoring Program's (NABat) species distribution model (SDM) for the northern long-eared bat (Myotis septentrionalis). The provided tabular data includes predictions (with upper and lower confidence intervals) for northern long-eared bat occupancy probabilities (which represent the probability of presence) based on data from the entire summer season (May 1-August 31), averaged from 2017-2022, in each NABat grid cell (5km x 5km scale) across the range of the species. Specifically, predictions represent occupancy probabilities in the pre-volancy season in the summer (May 1\u2013July 15), i.e., the period of time before juveniles can fly and become detectable by capture and/or acoustic surveys. Predictions were produced using an analytical pipeline supported by web-based infrastructure, Bayesian hierarchical modeling, and an SDM framework which integrated stationary acoustic and live-capture data to model the recent summer distribution of the species while accounting for imperfect detection and species misclassification. A tabular file is included detailing the average occupancy probability predictions (from 2017-2022) of each 5 km x 5 km grid cell in the species range, including means, standard deviations, and the 95% Bayesian credible intervals. These data can be cross-referenced to the NABat CONUS 5km master sample for analytical or visualization purposes. We also provide a text file containing the JAGS model used to estimate these occupancy probabilities for reference.",
       "descriptionType": "Abstract"
     }
   ],
   "geoLocations": [],
   "fundingReferences": [],
   "url": "https://www.sciencebase.gov/catalog/item/662c04ced34ea70bd5f122e3",
   "contentUrl": null,
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   "source": "api",
   "isActive": true,
   "state": "findable",
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   "created": "2024-05-14T16:18:43Z",
   "registered": "2024-05-14T16:18:43Z",
   "published": null,
   "updated": "2024-05-14T16:19:01Z"
 }

}