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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...
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Predictions of raven occurrence in the absence of anthropogenic environmental effects. Raven point counts were related to landscape covariates using Bayesian hierarchical occupancy models and the means of the posterior distributions for relevant effects were used to generate the predictions.
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Predictions of raven occurrence in the absence of natural environmental effects. Raven point counts were related to landscape covariates using Bayesian hierarchical occupancy models and the means of the posterior distributions for relevant effects were used to generate the predictions.
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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.
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These data identify the mean population growth rate and ratio change in abundance of common raven (Corvus corax; ravens) populations from 1966 through 2018, delineated by ecoregions defined by the U.S. Environmental Protection Agency. This enables researchers and land managers to identify regions which may be more heavily affected by growing raven populations. These data support the following publication: Harju, S.M., Coates, P.S., Dettenmaier, S.J., Dinkins, J.B., Jackson, P.J. and Chenaille, M.P., 2022. Estimating trends of common raven populations in North America, 1966–2018. Human–Wildlife Interactions, 15(3), p.5. https://doi.org/10.26077/c27f-e335
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A hierarchical occupancy model adapted from Royle & Dorazio (2008) and Rota et al. (2011) for use in R. References: Royle, J.A. and Dorazio, R.M., 2008. Hierarchical modeling and inference in ecology: the analysis of data from populations, metapopulations and communities. Academic Press. doi:10.1016/B978-0-12-374097-7.50001-5 J. Andrew Royle, Robert M. Dorazio, Rota, C. T., Fletcher Jr, R. J., Dorazio, R. M. and Betts, M. G. (2009), Occupancy estimation and the closure assumption. Journal of Applied Ecology, 46: 1173-1181. doi:10.1111/j.1365-2664.2009.01734.x
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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...
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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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Predictions of an anthropogenic influence on raven occurrence index intersected with sage-grouse concentration areas. The anthropogenic influence index indicates where resource subsidies are contributing the most to raven occurrence.
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Raven point counts were related to landscape covariates using Bayesian hierarchical occupancy models and the mean of the predicted posterior distribution for raven occurrence was used to visualize results.
    map background search result map search result map Raven study site locations in the Great Basin, derived from survey locations 2007 - 2016 Predicted probability of raven occurrence across the Great Basin, USA, 2007 – 2016 (Fig. 3) Predictions of raven occurrence in the absence of natural environmental effects in the Great Basin, 2007-2016 (Fig. 4A) Predictions of raven occurrence in the absence of anthropogenic environmental effects in the Great Basin, 2007-2016 (Fig. 4B) Prediction of raven occurrence intersected with high impact areas for sage-grouse populations in the Great Basin, 2007-2016 (Fig. 5A) Anthropogenic influence on raven occurrence index within sage-grouse concentration areas in the Great Basin, 2007-2016 (Fig. 5B) Hierarchical Occupancy Model Code for R and Accompanying Files Trend Estimates of Common Raven Populations in the United States and Canada, 1966 - 2018 Mean Annual Population Growth Rate and Ratio Change in Abundance of Common Raven within Level I Ecoregions of the United States and Canada, 1966 - 2018 Mean Annual Population Growth Rate and Ratio Change in Abundance of Common Raven within Level II Ecoregions of the United States and Canada, 1966 - 2018 Data to Support Hierarchical Models and Decision Support Maps to Guide Management of Subsidized Avian Predator Densities Estimates of Raven Impacts on Greater Sage-Grouse Nest Survival Delineated by Field Site in California, Nevada, and Idaho (2009 - 2019) Median Estimates of Raven Density in California, Nevada, and Idaho (2012 - 2019) Raven Observations near Greater Sage-Grouse Nests in the Great Basin and Bi-State Regions of the Western United States (2009 - 2019) Data to Support Hierarchical Models and Decision Support Maps to Guide Management of Subsidized Avian Predator Densities Estimates of Raven Impacts on Greater Sage-Grouse Nest Survival Delineated by Field Site in California, Nevada, and Idaho (2009 - 2019) Median Estimates of Raven Density in California, Nevada, and Idaho (2012 - 2019) Raven Observations near Greater Sage-Grouse Nests in the Great Basin and Bi-State Regions of the Western United States (2009 - 2019) Raven study site locations in the Great Basin, derived from survey locations 2007 - 2016 Prediction of raven occurrence intersected with high impact areas for sage-grouse populations in the Great Basin, 2007-2016 (Fig. 5A) Anthropogenic influence on raven occurrence index within sage-grouse concentration areas in the Great Basin, 2007-2016 (Fig. 5B) Hierarchical Occupancy Model Code for R and Accompanying Files Predicted probability of raven occurrence across the Great Basin, USA, 2007 – 2016 (Fig. 3) Predictions of raven occurrence in the absence of natural environmental effects in the Great Basin, 2007-2016 (Fig. 4A) Predictions of raven occurrence in the absence of anthropogenic environmental effects in the Great Basin, 2007-2016 (Fig. 4B) Trend Estimates of Common Raven Populations in the United States and Canada, 1966 - 2018 Mean Annual Population Growth Rate and Ratio Change in Abundance of Common Raven within Level I Ecoregions of the United States and Canada, 1966 - 2018 Mean Annual Population Growth Rate and Ratio Change in Abundance of Common Raven within Level II Ecoregions of the United States and Canada, 1966 - 2018