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Scott C Gardner

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Integrating Spatially Explicit Indices of Abundance and Habitat Quality: An Applied Example for Greater Sage-grouse Management
This USGS data release represents geospatial data for the sage-grouse habitat mapping project. This study provides timely and highly useful information about greater sage-grouse over a large area of the Great Basin. USGS researchers and their colleagues created a template for combining landscape-scale occurrence or abundance data with habitat selection data in order to identify areas most critical to sustaining populations of species of conservation concern. The template also identifies those areas where land use changes have minimal impact. To inform greater sage-grouse conservation planning, the researchers developed greater sage-grouse habitat management categories based on habitat selection indices (HSI) and...
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We examined nest survival of Greater Sage-grouse (Centrocercus urophasianus; hereafter, sage-grouse) in relation to fine-scale habitat patterns that influenced nest site selection, using data from nests of telemetered females at 17 sites across 6 years in Nevada and northeastern California, USA. Importantly, sites spanned mesic and xeric average precipitation conditions and concomitant vegetation community structure across cold desert ecosystems of the North American Great Basin. Vegetative cover immediately surrounding sage-grouse nests was important for both nest site selection and nest survival, but responses varied between mesic and xeric sites. For example, while taller perennial grass was selected at xeric...
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Map of cumulative 38-day nest survival predicted from a Bayesian hierarchical shared frailty model of sage-grouse nest fates. The midpoint of coefficient conditional posterior distributions of 38-day nest survival were used for prediction at each 30 meter pixel across the landscape.
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Ranked index of model-projected nest site selection integrated with nesting productivity (i.e., nest survival), demonstrating the spatial distribution of adaptive vs. maladaptive habitat selection at each 30 m pixel. Hierarchical models of nest selection and survival were fit to landscape covariates within a Bayesian modeling framework in Nevada and California from 2009 through 2017 to develop spatially explicit information about nest site selection and survival consequences across the landscape. Habitat was separated into 16 classes ranking from high (1) to low (16). Habitat ranked highest where the top nest selection and survival classes intersected (adaptive selection), whereas the lowest rank occurred where...
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Map of nesting habitat selection scores predicted from a resource selection function (RSF) developed from sage-grouse nest locations. Nest site selection was modeled using a generalized linear mixed model of used and random locations in a Bayesian modeling environment, and the midpoint of coefficient conditional posterior distributions were used for prediction. Continuous values were reclassified and ranked using a percent isopleth approach with respect to observed nest locations.
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