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{

 "DOI": {
   "doi": "10.5066/p9jpvpgv",
   "identifiers": [],
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     {
       "name": "D'Acunto, Laura E",
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     {
       "name": "Pearlstine, Leonard",
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       "givenName": "Leonard",
       "familyName": "Pearlstine",
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         "National Parks Service"
       ],
       "nameIdentifiers": []
     },
     {
       "name": "Haider, Saira M",
       "nameType": "Personal",
       "givenName": "Saira M",
       "familyName": "Haider",
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       "name": "Hackett, Caitlin E",
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       "name": "Romanach, Stephanie S",
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       "givenName": "Stephanie S",
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     {
       "name": "Shinde, Dilip",
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       "givenName": "Dilip",
       "familyName": "Shinde",
       "affiliation": [
         "National Park Service"
       ],
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   ],
   "titles": [
     {
       "title": "Everglades Vulnerability Analysis (EVA) modeling scripts and output"
     }
   ],
   "publisher": "U.S. Geological Survey",
   "container": {},
   "publicationYear": 2023,
   "subjects": [
     {
       "subject": "Ecology"
     },
     {
       "subject": "FOS: Biological sciences",
       "schemeUri": "http://www.oecd.org/science/inno/38235147.pdf",
       "subjectScheme": "Fields of Science and Technology (FOS)"
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       "date": "2023",
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   "descriptions": [
     {
       "description": "The Everglades Vulnerability Analysis (EVA) is a series of connected Bayesian networks that models the landscape-scale response of indicators of Everglades ecosystem health to changes in hydrology and salinity on the landscape. Using the uncertainty built into each network, it also produces surfaces of vulnerability in relation to user-defined \u2018ideal\u2019 outcomes. This dataset includes the code used to build the modules and generate outputs of module outcome probabilities and landscape vulnerability.",
       "descriptionType": "Abstract"
     }
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   "created": "2023-03-06T14:48:32Z",
   "registered": "2023-03-06T14:48:33Z",
   "published": null,
   "updated": "2023-03-31T17:55:33Z"
 }

}

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