Item talk:Q324551

{

 "DOI": {
   "doi": "10.5066/p9b4h00q",
   "identifiers": [],
   "creators": [
     {
       "name": "Buchholtz, Erin K",
       "nameType": "Personal",
       "givenName": "Erin K",
       "familyName": "Buchholtz",
       "affiliation": [
         "United States Geological Survey"
       ],
       "nameIdentifiers": [
         {
           "schemeUri": "https://orcid.org",
           "nameIdentifier": "https://orcid.org/0000-0002-1985-9531",
           "nameIdentifierScheme": "ORCID"
         }
       ]
     },
     {
       "name": "Heinrichs, Julie",
       "nameType": "Personal",
       "givenName": "Julie",
       "familyName": "Heinrichs",
       "affiliation": [],
       "nameIdentifiers": [
         {
           "schemeUri": "https://orcid.org",
           "nameIdentifier": "https://orcid.org/0000-0001-7733-5034",
           "nameIdentifierScheme": "ORCID"
         }
       ]
     }
   ],
   "titles": [
     {
       "title": "Landscape and connectivity metrics based on invasive annual grass cover from 2016-2018 summarized at 15 kilometer grid cells in the Great Basin, USA"
     }
   ],
   "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)"
     }
   ],
   "contributors": [],
   "dates": [
     {
       "date": "2023",
       "dateType": "Issued"
     }
   ],
   "language": null,
   "types": {
     "ris": "DATA",
     "bibtex": "misc",
     "citeproc": "dataset",
     "schemaOrg": "Dataset",
     "resourceType": "Dataset",
     "resourceTypeGeneral": "Dataset"
   },
   "relatedIdentifiers": [
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       "relationType": "IsCitedBy",
       "relatedIdentifier": "10.1007/s10530-022-02945-w",
       "relatedIdentifierType": "DOI"
     }
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   "descriptions": [
     {
       "description": "The spatial context of invasions is increasingly recognized as important for the success and efficiency of management actions. This information can be key for managing invasive grasses that threaten native ecosystems. We calculated landscape metrics and circuit-based centrality for invasive grasses using a source input raster of weighted-average annual herbaceous cover from 2016-2018 (Maestas et al. 2020, 30 meter resolution) in the Great Basin, USA. This shapefile data product includes the summarized landscape metrics and connectivity metrics for 15 kilometer grid cells (n = 2408) across the Great Basin, USA. Metrics for each grid cell include: mean patch area (area_mn), class area (ca), number of patches (np), largest patch index (lpi), mean Euclidean nearest neighbor distance (enn_mn), mean patch contiguity (cntg_mn), aggregation index (ai), and centrality (cntrlty). We also calculated dominant abundance class (dm_bnd_) for comparison with these metric values.",
       "descriptionType": "Abstract"
     }
   ],
   "geoLocations": [],
   "fundingReferences": [],
   "url": "https://www.sciencebase.gov/catalog/item/632a0b5fd34e71c6d67b9043",
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   "metadataVersion": 1,
   "schemaVersion": "http://datacite.org/schema/kernel-4",
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   "created": "2023-02-16T20:56:47Z",
   "registered": "2023-02-16T20:56:48Z",
   "published": null,
   "updated": "2023-02-26T04:47:16Z"
 }

}