FIGURE 3.

(a) 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. (b) 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 m pixel across the landscape. The map shows predicted survival reclassified based on the 25th percentile of all values at failed nests (lowest class), mean value of all nests, and 75th percentile of successful nests. Fate and location data were gathered from ground radio telemetry monitoring of sage‐grouse females in Nevada and California, United States, 2009–2017