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These tables serve as input data for hierarchical models investigating interactions between raven density and Greater Sage-grouse nest success. Observations were recorded over an 11 year time period, spanning from 2009 through 2019. The model is run in JAGS via R, the code is publicly available via the U.S. Geological Survey's GitLab (O'Neil et al. 2023). We recommend not making any changes or edits to the tables unless the user is experienced with hierarchical modeling. References: O'Neil, S.T., Coates, P.S., Webster, S.C., Brussee, B.E., Dettenmaier, S.J., Tull, J.C., Jackson, P.J., Casazza, M.L., and Espinosa, S.P., 2023, Code for a hierarchical model of raven densities linked with sage-grouse nest survival...
A raster representing Greater Sage-grouse (hereafter sage-grouse) space-use and lek abundance. A higher pixel value corresponds to a greater amount of likelihood that the area is utilized by sage-grouse. Values are the result of combining a kernel density estimation on lek abundances with a raster representing distance to lek. The kernel density was calculated using maximum lek abundances observed between the most recent population nadir for the Great Basin region (2013) and the most recent lek counts available (2021). Polygons representing high-space use areas of Greater Sage-grouse (hereafter sage-grouse) space-use and lek abundance. Areas represent the 85 percent isopleth of the abundance and space-use index...
Rasters representing Greater Sage-grouse (hereafter sage-grouse) habitat selection indices (HSI), habitat selection categories, HSI combined with space-use, and example management categories. Researchers with the U.S. Geological Survey, in close cooperation with multiple state and federal resource agency partners, sought to map sage-grouse distribution and produce example habitat designations in these states. Herein, we report results of our primary study objective, which was to map sage-grouse distribution and create example habitat management and priority designations, based on more than a decade of location and survival data collected from marked sage-grouse across the study region.
The data were collected at Morley Nelson, Birds of Prey National Conservation Area (NCA) where known grazing regimes, including the season of grazing, have been in practice for the last 30 years. Surveyed plots were placed to account for intensity of grazing and to avoid confounding disturbances. Data were collected on the morphogroups of biological soil crusts (biocrusts) found within the NCA, and include measurements on soils related to texture, carbon, nitrogen and the abundance of soil aggregating cyanobacteria in the soil. These data support the following publication: Condon, L.A., Rosentreter, R., Veblen, K.E. and Coates, P.S., 2024. Season of grazing interacts with soil texture, selecting for associations...
Categories: Data;
Tags: BLM AIM data,
Birds of Prey National Conservation Area,
Ecology,
Great Basin,
Idaho,
A raster identifying areas that met the criteria to be priority habitat before a fire disturbance occurred. This file is binary, a value of 1 indicates the pixel represents pre-fire priority habitat, a value of 0 indicates the pixel did not meet the criteria of selection, survival, and space-use to be considered pre-fire priority habitat.
Rasters representing median raven density estimates, calculated from approximately 28,000 raven point count surveys conducted between 2009 and 2019. Estimates were the result of a Bayesian hierarchical distance sampling model, using environmental covariates on detection and abundance.
These data are the results of a spatially interpolated integrated population model (SIIPM) fit to count and demographic data collected from populations of Greater Sage-grouse (Centrocercus urophasianus; hereafter, sage-grouse) located in Nevada, U.S.A. during 2013-2021. We used a novel framework, using integrated population models (IPMs), to express demographic relatedness among sampled and unsampled populations using geographic principles of spatial autocorrelation (Shepard, 1968; Tobler, 1970). Specifically, the framework pairs relatively inexpensive population count data with spatially interpolated demographic estimates. When conducted within a Bayesian framework, spatially interpolated demographic parameters...
Rasters representing Greater Sage-grouse (hereafter sage-grouse) survival indices and categories during the nesting, early brood, and late brood life stages. A higher pixel value corresponds to a better chance of survival. The four categories of survival are very low, low, moderate, and high. We have also included rasters representing source and sink habitats for sage-grouse. Habitat sinks occur in areas of maladaptive habitat selection, where there are relatively high levels of selection, but low chance of survival. Source habitats were defined as any pixel that supported both high selection and high survival for a given life stage. Importantly, a given pixel was only considered source habitat if it was not sink...
We expanded developed methodology to incorporate habitat selection and survival during reproductive life stages and specific seasons with updated greater sage-grouse location and known fate datasets. We included brood-rearing areas that are understood to be threatened and important for population persistence. We combined predictive habitat map surfaces for each life stage and season with updated information on current occupancy patterns to classify habitat based on its suitability and probability of occupancy. We performed additional steps to delineate example habitat management areas, specifically: (1) incorporated corridors connecting key nesting and brood-rearing habitat; (2) corrected outputs for pre-wildfire...
We combined approximately 28,000 raven point count surveys with data from more than 900 sage-grouse nests between 2009 and 2019 within the Great Basin, USA. We modeled variation in raven density using a Bayesian hierarchical distance sampling approach with environmental covariates on detection and abundance. Concurrently, we modeled sage-grouse nest survival using a hierarchical frailty model as a function of raven density as well as other environmental covariates that influence risk of failure. Raven density commonly exceeded more than 0.5 ravens per square kilometer and increased at low relative elevations with prevalent anthropogenic development and/or agriculture. Reduced sage-grouse nest survival was strongly...
These rasters are the result of calculating the difference in Greater Sage-grouse nest survival after a simulated reduction of raven density to 0.1 ravens per square kilometer. The difference in nest survival represents spatial variation in potential to improve nest survival by reducing raven impacts. The extent of each individual raster is the extent of the field site at which sage-grouse nest observations were recorded.
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