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.

Ranked index of model-projected nest site selection integrated with nesting productivity (i.e., nest survival), demonstrating the spatial distribution of adaptive vs. maladaptive habitat selection at each 30 m pixel. Hierarchical models of nest selection and survival were fit to landscape covariates within a Bayesian modeling framework in Nevada and California from 2009 through 2017 to develop spatially explicit information about nest site selection and survival consequences across the landscape. Habitat was separated into 16 classes ranking from high (1) to low (16). Habitat ranked highest where the top nest selection and survival classes intersected (adaptive selection), whereas the lowest rank occurred where the top nest selection class intersected with the lowest survival class (maladaptive selection, or potential ecological trap).

Ranked index of model-projected nest site selection integrated with nesting productivity (i.e., nest survival), demonstrating the spatial distribution of adaptive vs. maladaptive habitat selection at each 30 m pixel. Hierarchical models of nest selection and survival were fit to landscape covariates within a Bayesian modeling framework in Nevada and California from 2009 through 2017 to develop spatially explicit information about nest site selection and survival consequences across the landscape. Habitat was separated into 16 classes ranking from high (1) to low (16). Habitat ranked highest where the top nest selection and survival classes intersected (adaptive selection), whereas the lowest rank occurred where the top nest selection class intersected with the lowest survival class (maladaptive selection, or potential ecological trap).

We applied spatially-explicit models to a spatiotemporally robust dataset of greater sage-grouse (Centrocercus urophasianus) nest locations and fates across wildfire-altered sagebrush ecosystems of the Great Basin ecoregion, western USA. Using sage-grouse as a focal species, we quantified scale-dependent factors driving nest site selection and nest survival across broad spatial scales in order to identify wildfire impacts and other environmental influences on variation in nesting productivity across a broad ecoregion spanning mesic and xeric shrub communities. To investigate the consequences of habitat selection and explore the potential for a source-sink reproductive landscape, we sought to classify nesting habitat on a scale ranging from adaptive (high selection, high survival) to maladaptive (high selection, low survival).

We applied spatially-explicit models to a spatiotemporally robust dataset of greater sage-grouse (Centrocercus urophasianus) nest locations and fates across wildfire-altered sagebrush ecosystems of the Great Basin ecoregion, western USA. Using sage-grouse as a focal species, we quantified scale-dependent factors driving nest site selection and nest survival across broad spatial scales in order to identify wildfire impacts and other environmental influences on variation in nesting productivity across a broad ecoregion spanning mesic and xeric shrub communities. To investigate the consequences of habitat selection and explore the potential for a source-sink reproductive landscape, we sought to classify nesting habitat on a scale ranging from adaptive (high selection, high survival) to maladaptive (high selection, low survival).

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 meter pixel across the landscape.

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 meter pixel across the landscape.

Resource selection functions (RSF) and associated maps are often used by managers to guide conservation actions (Crawford et al., 2020; Pratt and Beck, 2021; Saher et al., 2022). However it is important to move beyond designating important habitat solely based on species occupancy or use. Incorporating demographic measures such as reproductive success will provide increased power and detail for ranking habitat for management priority, particularly across multiple life stages and large spatial extents (Gibson et al., 2016; Pratt and Beck, 2021; Stephens et al., 2015). We provide a quantitative approach to differentiate productive habitats supporting high selection and survival from areas of maladaptive selection where selection and survival are misaligned at large spatial scales. References cited Crawford, B. A., Maerz, J. C., and Moore, C. T. (2020). Expert-informed habitat suitability analysis for at-risk species assessment and conservation planning. Journal of Fish and Wildlife Management, 11(1), 130-150. https://doi.org/10.3996/092019-JFWM-075 Gibson, D., Blomberg, E. J., Atamian, M. T., and Sedinger, J. S. (2016). Nesting habitat selection influences nest and early offspring survival in Greater Sage-Grouse. The Condor: Ornithological Applications, 118(4), 689-702. https://doi.org/10.1650/CONDOR-16-62.1 Pratt, A. C., and Beck, J. L. (2021). Do greater sage-grouse exhibit maladaptive habitat selection? Ecosphere, 12(3), e03354. https://doi.org/10.1002/ecs2.3354 Saher, D. J., O’Donnell, M. S., Aldridge, C. L., and Heinrichs, J. A. (2022). Balancing model generality and specificity in management-focused habitat selection models for Gunnison sage-grouse. Global Ecology and Conservation, 35, e01935. https://doi.org/10.1016/j.gecco.2021.e01935 Stephens, P. A., Pettorelli, N., Barlow, J., Whittingham, M. J., and Cadotte, M. W. (2015). Management by proxy? The use of indices in applied ecology. Journal of Applied Ecology, 52(1), 1-6.

Resource selection functions (RSF) and associated maps are often used by managers to guide conservation actions (Crawford et al., 2020; Pratt and Beck, 2021; Saher et al., 2022). However it is important to move beyond designating important habitat solely based on species occupancy or use. Incorporating demographic measures such as reproductive success will provide increased power and detail for ranking habitat for management priority, particularly across multiple life stages and large spatial extents (Gibson et al., 2016; Pratt and Beck, 2021; Stephens et al., 2015). We provide a quantitative approach to differentiate productive habitats supporting high selection and survival from areas of maladaptive selection where selection and survival are misaligned at large spatial scales. References cited Crawford, B. A., Maerz, J. C., and Moore, C. T. (2020). Expert-informed habitat suitability analysis for at-risk species assessment and conservation planning. Journal of Fish and Wildlife Management, 11(1), 130-150. https://doi.org/10.3996/092019-JFWM-075 Gibson, D., Blomberg, E. J., Atamian, M. T., and Sedinger, J. S. (2016). Nesting habitat selection influences nest and early offspring survival in Greater Sage-Grouse. The Condor: Ornithological Applications, 118(4), 689-702. https://doi.org/10.1650/CONDOR-16-62.1 Pratt, A. C., and Beck, J. L. (2021). Do greater sage-grouse exhibit maladaptive habitat selection? Ecosphere, 12(3), e03354. https://doi.org/10.1002/ecs2.3354 Saher, D. J., O’Donnell, M. S., Aldridge, C. L., and Heinrichs, J. A. (2022). Balancing model generality and specificity in management-focused habitat selection models for Gunnison sage-grouse. Global Ecology and Conservation, 35, e01935. https://doi.org/10.1016/j.gecco.2021.e01935 Stephens, P. A., Pettorelli, N., Barlow, J., Whittingham, M. J., and Cadotte, M. W. (2015). Management by proxy? The use of indices in applied ecology. Journal of Applied Ecology, 52(1), 1-6.

We demonstrate a quantitative approach to differentiate source and sink habitats at large spatial scales using the greater sage-grouse (Centrocercus urophasianus; hereafter, sage-grouse), an indicator species for sagebrush ecosystems, as a case-study. We evaluated both selection and survival across multiple reproductive life stages (nesting, brood-rearing) in the Bi-State Distinct Population Segment (DPS), a genetically distinct and geographically isolated population of sage-grouse on the southwestern edge of the species’ range. Our approach allowed us to identify both mismatches between selection and survival and trade-offs between life stages. These findings suggest competing resource demands across time, with predation risk being a dominant factor for nests and during early brood-rearing when chicks are smaller and flightless, whereas access to forage resources becomes more important during late brood-rearing when resources become increasingly limited. These data consist of both continuous indices and categorical rasters representing selection and survival for the nesting and brooding seasons. The selection and survival categories were then intersected again to create source-sink classes. Seasonal results were also combined to produce composite rasters which represent selection, survival, and source-sinks across the entire reproductive life cycle of sage-grouse.