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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...
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.
To develop effective adaptive management plans, conservation and natural resource managers need to know how climate change will affect the species and ecosystems they manage. This project provides managers with information about potential climate change effects on species and managed areas in the Pacific Northwest. We evaluated projected changes in climate, vegetation, and species distributions through the year 2099 and assessed the potential impacts of these changes on key species and managed lands. We worked with conservation and natural resource managers to incorporate the results of this study into state, federal, and non-governmental organization (NGO) management plans. The projected changes in climate, vegetation,...
Categories: Project;
Types: Map Service,
OGC WFS Layer,
OGC WMS Layer,
OGC WMS Service;
Tags: 2009,
CASC,
Climate change,
Climate modelling,
Completed,
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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