Item talk:Q274251
From geokb
{
"USGS Publications Warehouse": { "@context": "https://schema.org", "@type": "CreativeWork", "additionalType": "Other Government Series", "name": "Habitat suitability and ecological associations of two non-native ungulate species on the Hawaiian island of Lanai", "identifier": [ { "@type": "PropertyValue", "propertyID": "USGS Publications Warehouse IndexID", "value": "70214031", "url": "https://pubs.usgs.gov/publication/70214031" }, { "@type": "PropertyValue", "propertyID": "USGS Publications Warehouse Internal ID", "value": 70214031 } ], "inLanguage": "en", "isPartOf": [ { "@type": "CreativeWorkSeries", "name": "Hawaii Cooperative Studies Unit Technical Report Series" } ], "datePublished": "2020", "dateModified": "2021-02-17", "abstract": "The ability to effectively manage game species for specific conservation objectives is often limited by the scientific understanding of their distribution and abundance. This is especially true in Hawai\u2018i where introduced game mammals are poorly studied and have low value relative to native species in other states. We modeled the habitat suitability and ecological associations of European mouflon sheep (\u201cmouflon\u201d; Ovis musimon) and axis deer (Axis axis) on the island of L\u0101na\u2018i using intensive aerial survey and environmental data that included climate, vegetation, and topographic variables. We conducted diagnostic tests on a suite of primarily categorical predictors and determined most were highly correlated. We therefore developed a suite of other spatial predictor layers with continuous variables. We tested several modeling approaches but settled on generalized linear models (GLM) and random GLMs because they could account for group size of animals and were based on curvilinear responses of each species to environmental variability. Both mammal species were habitat generalists showing little affinity to particular plant species or communities. Continuous predictors associated with plant productivity such as mean annual precipitation, normalized difference vegetation index (NDVI), and cloud cover were important explanatory factors in a GLM of axis deer and a random GLM of mouflon habitat suitability. The presence of axis deer was also an important explanatory predictor for mouflon distribution, but deer were not influenced by mouflon distribution, indicating asymmetrical competition. Consequently, mouflon were restricted to lower elevation arid and very dry slopes, whereas axis deer were more broadly distributed throughout other upland environments of the island, but avoided steep terrain. Findings indicate that removal of a substantial portion of the more abundant axis deer population may lead to an increase in abundance and distribution of mouflon without containment. Resulting spatial models of game mammal habitat suitability will be employed to inform land use prioritization analyses and to help resolve long-standing conflicts between native species conservation and sustained-yield hunting.", "description": "iv, 30 p.", "publisher": { "@type": "Organization", "name": "Hawai\u2018i Cooperative Studies Unit, University of Hawai\u2018i" }, "author": [ { "@type": "Person", "name": "Leopold, Christina", "givenName": "Christina", "familyName": "Leopold", "identifier": { "@type": "PropertyValue", "propertyID": "ORCID", "value": "0000-0003-0499-3196", "url": "https://orcid.org/0000-0003-0499-3196" } }, { "@type": "Person", "name": "Muise, Jacob", "givenName": "Jacob", "familyName": "Muise", "affiliation": [ { "@type": "Organization", "name": "KIA Hawaii" } ] }, { "@type": "Person", "name": "Sprague, Jonathan", "givenName": "Jonathan", "familyName": "Sprague", "affiliation": [ { "@type": "Organization", "name": "Pulama Lana\u2018i" } ] }, { "@type": "Person", "name": "Hess, Steve C. shess@usgs.gov", "givenName": "Steve C.", "familyName": "Hess", "email": "shess@usgs.gov", "identifier": { "@type": "PropertyValue", "propertyID": "ORCID", "value": "0000-0001-6403-9922", "url": "https://orcid.org/0000-0001-6403-9922" }, "affiliation": [ { "@type": "Organization", "name": "Pacific Island Ecosystems Research Center", "url": "https://www.usgs.gov/pacific-island-ecosystems-research-center" }, { "@type": "Organization", "name": "Pacific Islands Ecosys Research Center", "url": "https://www.usgs.gov/centers/pacific-islands-water-science-center" } ] }, { "@type": "Person", "name": "Fortini, Lucas", "givenName": "Lucas", "familyName": "Fortini", "identifier": { "@type": "PropertyValue", "propertyID": "ORCID", "value": "0000-0002-5781-7295", "url": "https://orcid.org/0000-0002-5781-7295" }, "affiliation": [ { "@type": "Organization", "name": "Pacific Island Ecosystems Research Center", "url": "https://www.usgs.gov/pacific-island-ecosystems-research-center" } ] } ], "funder": [ { "@type": "Organization", "name": "Pacific Island Ecosystems Research Center", "url": "https://www.usgs.gov/pacific-island-ecosystems-research-center" } ], "spatialCoverage": [ { "@type": "Place", "additionalType": "country", "name": "United States", "url": "https://geonames.org/4074035" }, { "@type": "Place", "additionalType": "state", "name": "Hawai'i" }, { "@type": "Place", "additionalType": "unknown", "name": "L\u0101na\u2018i", "url": "https://geonames.org/5850056" }, { "@type": "Place", "geo": [ { "@type": "GeoShape", "additionalProperty": { "@type": "PropertyValue", "name": "GeoJSON", "value": { "type": "FeatureCollection", "features": [ { "type": "Feature", "properties": {}, "geometry": { "type": "Polygon", "coordinates": [ [ [ -156.79962158203125, 20.824159066298787 ], [ -156.8909454345703, 20.917189979347988 ], [ -156.9891357421875, 20.931941310423674 ], [ -157.060546875, 20.913982976117605 ], [ -157.06329345703125, 20.88383379386135 ], [ -157.0323944091797, 20.85624519604873 ], [ -157.0001220703125, 20.834427371957577 ], [ -156.9891357421875, 20.812606385754087 ], [ -156.99462890624997, 20.78564668820214 ], [ -156.9843292236328, 20.756113874762082 ], [ -156.9609832763672, 20.72400644605942 ], [ -156.88201904296875, 20.73877670943921 ], [ -156.8305206298828, 20.75868217465891 ], [ -156.80374145507812, 20.804904106750566 ], [ -156.79962158203125, 20.821591880501483 ], [ -156.79962158203125, 20.824159066298787 ] ] ] } } ] } } }, { "@type": "GeoCoordinates", "latitude": 20.833914350860404, "longitude": -156.92743894707846 } ] } ] }
}