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Audibility dataset in this file were analyzed in the publication “Optimizing Detection of the Bobwhite Reproduction Call Using Passive Acoustic Monitoring” https://doi.org/10.7944/P9U67LQX
These data were collected in 2017 on the 48,000-ha Buenos Aires National Wildlife Refuge (hereafter, Refuge). We used audibility trials (i.e., sound detection tests) to estimate and model probability of detection of male masked bobwhite reproduction calls by distance and weather. We selected 17 random locations using the Create Random Points Tool in ArcMap (ArcGIS 10.0, Redlands, CA, USA) within a 9,300-ha area representative of masked bobwhite habitat conditions. At these locations, we established plots where we conducted audibility trials. Each plot consisted of transects radiating from the centroid in the four cardinal directions. Along each transect, we simulated the reproduction call of male masked bobwhites using an electronic game caller (FoxPro Crossfire, Digital Game Caller, Lewistown, PA, USA) to broadcast recordings calibrated to the appropriate sound intensity of 112 dB at 10 cm. We held the game caller 1.5 meters from the ground to simulate a perched calling male. A technician walked each transect and played the recording at standardized distances. At each distance, we played a recording of three calls in each cardinal direction. This resulted in 12 calls per distance.
At the center of each plot, we placed an ARU (Wildlife Acoustics SM4, Autonomous Recording Unit, Maynard, MA, USA) to detect recording playback and a weather station with a console (Davis Instruments Corporation, 6152 Vantage Pro 2, Hayward, CA, USA).
We used Kaleidoscope Pro 4.5.5 (Wildlife Acoustics, Maynard, MA, USA) to manually identify calls and for automated detection with an advanced classifier. We named the advanced classifier MxModel. For manual sound analysis, we navigated to the playback time recorded during field data collection. For each playback time, we listened to the audio and studied the spectrogram (i.e., search for the distinct bob-white call geometry or signature) to determine if the call was logged by the ARU.
Resources
2 resources available
-
MBQ_Audibility_Models_Added.txt
TXT -
Masked_Bobwhite_Audibility_Metadata.docx
DOCX
Complete Metadata
| accessLevel | public |
|---|---|
| bureauCode |
[
"010:18"
]
|
| contactPoint |
{
"fn": "Todd Sutherland",
"@type": "vcard:Contact",
"hasEmail": "mailto:todd_sutherland@fws.gov"
}
|
| description | These data were collected in 2017 on the 48,000-ha Buenos Aires National Wildlife Refuge (hereafter, Refuge). We used audibility trials (i.e., sound detection tests) to estimate and model probability of detection of male masked bobwhite reproduction calls by distance and weather. We selected 17 random locations using the Create Random Points Tool in ArcMap (ArcGIS 10.0, Redlands, CA, USA) within a 9,300-ha area representative of masked bobwhite habitat conditions. At these locations, we established plots where we conducted audibility trials. Each plot consisted of transects radiating from the centroid in the four cardinal directions. Along each transect, we simulated the reproduction call of male masked bobwhites using an electronic game caller (FoxPro Crossfire, Digital Game Caller, Lewistown, PA, USA) to broadcast recordings calibrated to the appropriate sound intensity of 112 dB at 10 cm. We held the game caller 1.5 meters from the ground to simulate a perched calling male. A technician walked each transect and played the recording at standardized distances. At each distance, we played a recording of three calls in each cardinal direction. This resulted in 12 calls per distance. At the center of each plot, we placed an ARU (Wildlife Acoustics SM4, Autonomous Recording Unit, Maynard, MA, USA) to detect recording playback and a weather station with a console (Davis Instruments Corporation, 6152 Vantage Pro 2, Hayward, CA, USA). We used Kaleidoscope Pro 4.5.5 (Wildlife Acoustics, Maynard, MA, USA) to manually identify calls and for automated detection with an advanced classifier. We named the advanced classifier MxModel. For manual sound analysis, we navigated to the playback time recorded during field data collection. For each playback time, we listened to the audio and studied the spectrogram (i.e., search for the distinct bob-white call geometry or signature) to determine if the call was logged by the ARU. |
| distribution |
[
{
"@type": "dcat:Distribution",
"title": "MBQ_Audibility_Models_Added.txt",
"format": "txt",
"mediaType": "text/plain",
"downloadURL": "https://iris.fws.gov/APPS/ServCat/DownloadFile/235586?Reference=155632"
},
{
"@type": "dcat:Distribution",
"title": "Masked_Bobwhite_Audibility_Metadata.docx",
"format": "docx",
"mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document",
"downloadURL": "https://iris.fws.gov/APPS/ServCat/DownloadFile/235587?Reference=155632"
}
]
|
| identifier | http://datainventory.doi.gov/id/dataset/FWS_ServCat_155632 |
| issued | 2023-01-01T00:00:00Z |
| keyword |
[
"Arizona",
"Buenos Aires National Wildlife Refuge",
"Colinus virginianus ridgwayi",
"Masked Quail",
"Mexico",
"audibility",
"detection",
"kHz",
"masked bobwhite",
"quail"
]
|
| landingPage | https://iris.fws.gov/APPS/ServCat/Reference/Profile/155632 |
| modified | 2023-01-01T00:00:00Z |
| programCode |
[
"010:028",
"010:094"
]
|
| publisher |
{
"name": "U.S. Fish and Wildlife Service",
"@type": "org:Organization"
}
|
| spatial | -111.577538,31.4545612,-111.262009,31.8270149 |
| temporal | 2017-01-01/2017-01-01 |
| theme |
[
"Tabular Dataset"
]
|
| title | Audibility dataset in this file were analyzed in the publication “Optimizing Detection of the Bobwhite Reproduction Call Using Passive Acoustic Monitoring” https://doi.org/10.7944/P9U67LQX |
