Sagebrush (Artemisia spp.) scale of effect for Greater Sage-grouse (Centrocercus urophasianus) population trends in southwest Wyoming, USA 2003-2019
The distance within which populations respond to features in a landscape (scale of effect) can indicate how disturbance and management may affect wildlife. Using annual counts of male Greater Sage-grouse (Centrocercus urophasianus) attending 584 leks in southwest Wyoming (2003-2019) and estimates of sagebrush cover from the Rangeland Condition Monitoring Assessment and Projection (RCMAP), we used a scale selection approach to jointly estimate the scale of effect and the effect of sagebrush cover in the surrounding landscape for sage-grouse population trends. We estimated these parameters using a state-space model fit with a Bayesian approach. Data formatting necessary for this analysis produced data stored in two lists, one for model constants (nimbleconstants_sg_wlci.txt, including number of years, number of sites [leks], number of scales, number of visits, indicators for site and year, and number of detection parameters) and one for model data (nimbledata_sg_wlci.txt, including lek counts/surveys in both long- and array-format, a matrix for detection covariates, an array for sagebrush cover [scaled], and unscaled arrays for sagebrush, ordinal date, and time since sunrise).
Complete Metadata
| accessLevel | public |
|---|---|
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[
"010:12"
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|
| contactPoint |
{
"fn": "Adrian P Monroe",
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"hasEmail": "mailto:amonroe@usgs.gov"
}
|
| description | The distance within which populations respond to features in a landscape (scale of effect) can indicate how disturbance and management may affect wildlife. Using annual counts of male Greater Sage-grouse (Centrocercus urophasianus) attending 584 leks in southwest Wyoming (2003-2019) and estimates of sagebrush cover from the Rangeland Condition Monitoring Assessment and Projection (RCMAP), we used a scale selection approach to jointly estimate the scale of effect and the effect of sagebrush cover in the surrounding landscape for sage-grouse population trends. We estimated these parameters using a state-space model fit with a Bayesian approach. Data formatting necessary for this analysis produced data stored in two lists, one for model constants (nimbleconstants_sg_wlci.txt, including number of years, number of sites [leks], number of scales, number of visits, indicators for site and year, and number of detection parameters) and one for model data (nimbledata_sg_wlci.txt, including lek counts/surveys in both long- and array-format, a matrix for detection covariates, an array for sagebrush cover [scaled], and unscaled arrays for sagebrush, ordinal date, and time since sunrise). |
| distribution |
[
{
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"title": "Digital Data",
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"accessURL": "https://doi.org/10.5066/P9KDOBM2",
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|
| identifier | http://datainventory.doi.gov/id/dataset/USGS_62fd4103d34e3a444286a0d4 |
| keyword |
[
"Southwest Wyoming",
"USGS:62fd4103d34e3a444286a0d4",
"United States of America",
"Wyoming",
"Wyoming Landscape Conservation Initiative",
"biota",
"density dependence",
"landscape",
"population dynamics",
"scale"
]
|
| modified | 2022-10-05T00:00:00Z |
| publisher |
{
"name": "U.S. Geological Survey",
"@type": "org:Organization"
}
|
| spatial | -111.0487, 40.8917, -105.9123, 43.4700 |
| theme |
[
"Geospatial"
]
|
| title | Sagebrush (Artemisia spp.) scale of effect for Greater Sage-grouse (Centrocercus urophasianus) population trends in southwest Wyoming, USA 2003-2019 |
