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K. Ben Gustafson


Email: kgustafson@usgs.gov
Office Phone: 530-669-5069
ORCID: 0000-0003-3530-0372
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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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Managers require quantitative yet tractable tools that can identify areas for restoration yielding effective benefits for targeted wildlife species and the ecosystems they inhabit. A spatially explicit conservation planning tool that guides effective sagebrush restoration for sage-grouse can be made more effective by integrating baseline maps describing existing (pre-restoration) habitat suitability, and the distribution and abundance of breeding sage-grouse. Accordingly, we provide two rasters. The first is a floating point raster file informed by lek data, and derived from: 1) utilization distributions weighted by lek attendance, and 2) a non-linear probability of space-use relative to distance to lek. The second...
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Accurate maps of habitat availability for Greater Sage-grouse (Centrocercus urophasianus) across broad extents are of paramount importance to conservation efforts in sagebrush ecosystems across the Great Basin, particularly for habitat assessments and mitigation efforts. However, the ability to model sage-grouse habitat at fine spatial scales necessary for microhabitat assessment is constrained by the spatial and spectral resolution of most measurements remotely sensed of vegetation composition. Fractional approaches that scale plot-based measures of vegetation composition to satellite imagery that yield estimates of percent cover at relatively coarse resolution (e.g., 30 x 30 meter pixels) are well suited for regional...
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