Item talk:Q261046
From geokb
{
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"@context": "https://schema.org",
"@type": "Article",
"additionalType": "Journal Article",
"name": "Using the California Waterfowl Tracker to assess proximity of waterfowl to commercial poultry in the Central Valley of California",
"identifier": [
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"propertyID": "USGS Publications Warehouse IndexID",
"value": "70228198",
"url": "https://pubs.usgs.gov/publication/70228198"
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"value": 70228198
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"propertyID": "DOI",
"value": "10.1637/aviandiseases-D-20-00137",
"url": "https://doi.org/10.1637/aviandiseases-D-20-00137"
}
],
"journal": {
"@type": "Periodical",
"name": "Avian Diseases",
"volumeNumber": "65",
"issueNumber": "3"
},
"inLanguage": "en",
"isPartOf": [
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"@type": "CreativeWorkSeries",
"name": "Avian Diseases"
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],
"datePublished": "2021",
"dateModified": "2022-02-07",
"abstract": "Migratory waterfowl are the primary reservoir of avian influenza viruses (AIV) which can be spread to commercial poultry. Surveillance efforts that track the location and abundance of wild waterfowl and link those data to inform assessments of risk and sampling for AIV currently do not exist. To assist surveillance and minimize poultry exposure to AIV, here we explored the utility of remotely sensed MODerate Resolution Imaging Spectroradiometer (MODIS) satellite imagery in combination with land-based climate measurements (e.g., temperature and precipitation) to predict waterfowl location and abundance in near real-time in the California Central Valley (CCV), where both wild waterfowl and domestic poultry are densely located. Specifically, remotely collected MODIS and climate data were integrated into a previously developed Boosted Regression Tree (BRT) model to predict and visualize waterfowl distributions across the CCV. Daily model-based predictions are publicly available during the winter as part of the dynamic California Waterfowl Tracker (CWT) web-app hosted on the University of California\u2019s Cooperative Extension webpage. In this study, we analyzed 52 days of model predictions and produced daily spatio-temporal maps of waterfowl concentrations near the 605 commercial poultry farms in the CCV during January and February of 2019. Exposure of each poultry farm to waterfowl during each day was classified as \u201chigh\u201d, \u201cmedium\u201d, \u201clow\u201d, or \u201cnone\u201d depending on the density of waterfowl within 4 km of a farm. Results indicated that farms were at substantially greater risk of \u201cexposure\u201d in January, when CCV waterfowl populations peak, than in February. For example, during January, 33% (199/605) of the farms were exposed \u2265 1 day to \u201chigh\u201d waterfowl density versus 19% (115/605) of the farms in February. In addition to demonstrating the overall variability of waterfowl location and density, these data demonstrate how remote sensing can be used to better triage AIV surveillance and biosecurity efforts via the utilization of a functional web-app based tool. The ability to leverage remote sensing is an integral advancement toward improving AIV surveillance in waterfowl in close proximity to commercial poultry. Expansion of these types of remote sensing methods linked to a user-friendly web-tool could be further developed across the continental U.S. The BRT model incorporated into the CWT reflects a first attempt to give an accurate representation of waterfowl distribution and density relative to commercial poultry.",
"description": "10 p.",
"publisher": {
"@type": "Organization",
"name": "American Association of Avian Pathologists"
},
"author": [
{
"@type": "Person",
"name": "Buler, Jeffrey J.",
"givenName": "Jeffrey J.",
"familyName": "Buler"
},
{
"@type": "Person",
"name": "Pitesky, Maurice E.",
"givenName": "Maurice E.",
"familyName": "Pitesky",
"affiliation": [
{
"@type": "Organization",
"name": "University of California, Davis"
}
]
},
{
"@type": "Person",
"name": "Smolinsky, Jaclyn A.",
"givenName": "Jaclyn A.",
"familyName": "Smolinsky",
"affiliation": [
{
"@type": "Organization",
"name": "University of Delaware"
}
]
},
{
"@type": "Person",
"name": "Matchett, Elliott ematchett@usgs.gov",
"givenName": "Elliott",
"familyName": "Matchett",
"email": "ematchett@usgs.gov",
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"propertyID": "ORCID",
"value": "0000-0001-5095-2884",
"url": "https://orcid.org/0000-0001-5095-2884"
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"affiliation": [
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"@type": "Organization",
"name": "Western Ecological Research Center",
"url": "https://www.usgs.gov/centers/werc"
}
]
},
{
"@type": "Person",
"name": "Feirer, Shane",
"givenName": "Shane",
"familyName": "Feirer",
"affiliation": [
{
"@type": "Organization",
"name": "Hopland Research & Extension Center, UC-Agriculture and Natural Resources. Hopland, CA USA"
}
]
},
{
"@type": "Person",
"name": "Kelman, Todd",
"givenName": "Todd",
"familyName": "Kelman",
"affiliation": [
{
"@type": "Organization",
"name": "Department of Population Health and Reproduction, School of Veterinary Medicine, University of California, Davis, CA USA"
}
]
},
{
"@type": "Person",
"name": "Acosta, Sarai",
"givenName": "Sarai",
"familyName": "Acosta",
"affiliation": [
{
"@type": "Organization",
"name": "Department of Population Health and Reproduction, School of Veterinary Medicine, University of California, Davis, CA USA"
}
]
}
],
"funder": [
{
"@type": "Organization",
"name": "Western Ecological Research Center",
"url": "https://www.usgs.gov/centers/werc"
}
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"spatialCoverage": [
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"@type": "Place",
"additionalType": "country",
"name": "United States",
"url": "https://geonames.org/4074035"
},
{
"@type": "Place",
"additionalType": "state",
"name": "California"
},
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"name": "Central Valley of California"
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