North American Bat Monitoring Program (NABat) Bayesian Hierarchical Model for Winter Abundance: Predicted Population Estimates (2022 and 2023)
The dataset is comprised of historical observations and predictions of winter colony counts at known sites for three bat species (little brown bat, Myotis lucifugus; tricolored bat, Perimyotis subflavus; and big brown bat, Eptesicus fuscus). The dataset consists of two separate but related data files in tabular format (comma-separated values [.csv]). Each data set consists of predicted winter counts derived using winter status and trends modeling methods developed by the North American Bat Monitoring Program (NABat). These two predicted winter count data sets were used to inform NABat summertime status and trends analysis: 1) modeled abundance predictions for all hibernacula for all three species from 2010-2021, and 2) modeled abundance predictions for P. subflavus from 2010-2023 using updated monitoring data. Abundance predictions were derived with a combined modeling approach that applied an exponential linear interpolation model (when there were less than 4 observations per location) and a Bayesian hierarchical model (where there were 4 or more data points per location).
Complete Metadata
| accessLevel | public |
|---|---|
| bureauCode |
[
"010:12"
]
|
| contactPoint |
{
"fn": "Brian E Reichert",
"@type": "vcard:Contact",
"hasEmail": "mailto:breichert@usgs.gov"
}
|
| description | The dataset is comprised of historical observations and predictions of winter colony counts at known sites for three bat species (little brown bat, Myotis lucifugus; tricolored bat, Perimyotis subflavus; and big brown bat, Eptesicus fuscus). The dataset consists of two separate but related data files in tabular format (comma-separated values [.csv]). Each data set consists of predicted winter counts derived using winter status and trends modeling methods developed by the North American Bat Monitoring Program (NABat). These two predicted winter count data sets were used to inform NABat summertime status and trends analysis: 1) modeled abundance predictions for all hibernacula for all three species from 2010-2021, and 2) modeled abundance predictions for P. subflavus from 2010-2023 using updated monitoring data. Abundance predictions were derived with a combined modeling approach that applied an exponential linear interpolation model (when there were less than 4 observations per location) and a Bayesian hierarchical model (where there were 4 or more data points per location). |
| distribution |
[
{
"@type": "dcat:Distribution",
"title": "Digital Data",
"format": "XML",
"accessURL": "https://doi.org/10.5066/P9L0578M",
"mediaType": "application/http",
"description": "Landing page for access to the data"
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{
"@type": "dcat:Distribution",
"title": "Original Metadata",
"format": "XML",
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"downloadURL": "https://data.usgs.gov/datacatalog/metadata/USGS.64c4387ad34e70357a33d983.xml"
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|
| identifier | http://datainventory.doi.gov/id/dataset/USGS_64c4387ad34e70357a33d983 |
| keyword |
[
"Abundance",
"Hibernacula",
"USGS:64c4387ad34e70357a33d983",
"Winter colony",
"bats",
"biota"
]
|
| modified | 2023-09-01T00:00:00Z |
| publisher |
{
"name": "U.S. Geological Survey",
"@type": "org:Organization"
}
|
| spatial | -168.0469, 24.8466, -51.3281, 62.8351 |
| theme |
[
"Geospatial"
]
|
| title | North American Bat Monitoring Program (NABat) Bayesian Hierarchical Model for Winter Abundance: Predicted Population Estimates (2022 and 2023) |
