{
"DOI": {
"doi": "10.5066/p97oso15",
"prefix": "10.5066",
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"creators": [
{
"name": "Jacobi, James D",
"nameType": "Personal",
"givenName": "James D",
"familyName": "Jacobi",
"affiliation": [],
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{
"schemeUri": "https://orcid.org",
"nameIdentifier": "https://orcid.org/0000-0003-2313-7862",
"nameIdentifierScheme": "ORCID"
}
]
},
{
"name": "Brinck, Kevin W",
"nameType": "Personal",
"givenName": "Kevin W",
"familyName": "Brinck",
"affiliation": [],
"nameIdentifiers": [
{
"schemeUri": "https://orcid.org",
"nameIdentifier": "https://orcid.org/0000-0001-7581-2482",
"nameIdentifierScheme": "ORCID"
}
]
}
],
"titles": [
{
"title": "Hawaii Island Regeneration of Metrosideros polymorpha forests since landscape-level canopy dieback in the 1970s"
}
],
"publisher": "U.S. Geological Survey",
"container": {},
"publicationYear": 2019,
"subjects": [
{
"subject": "Botany,Ecology,Forestry"
}
],
"contributors": [],
"dates": [
{
"date": "2019",
"dateType": "Issued"
}
],
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},
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"relatedIdentifier": "https://doi.org/10.1111/jvs.12704",
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}
],
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"descriptions": [
{
"description": "We analyzed very-high-resolution imagery to assess status of Metrosideros polymorpha forests across an 83,603-hectare study area that experienced extensive canopy dieback in the 1970s on the eastern side of the island of Hawaii. Using GIS we generated 1,170 virtual vegetation plots with a 100-m radius; 541 plots in areas mapped in 1977 with trees dead or mostly defoliated (dieback), and 629 plots in adjacent wet forest habitat, previously mapped as non-dieback condition. In each plot we estimated the percent of M. polymorpha trees dead or mostly defoliated, and percent of trees with healthy crowns. These results were combined with habitat data to produce a spatial model depicting probability of canopy dieback within the study area. Seventy-nine percent of plots mapped in 1977 in dieback condition recovered their canopy and were now considered in non-dieback condition. Ninety-one percent of plots in previous non-dieback areas were found to still have a healthy M. polymorpha canopy in 2015. A spatial model allowed us to identify areas within the study area with high, medium, and low probability of experiencing this same type of canopy dieback in the future. This data release package includes two GIS shapefiles and four tabular files that were part of the analysis for this study.",
"descriptionType": "Abstract"
}
],
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