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Abstract A major impediment to wildlife conservation and management, from a quantitative perspective, is dealing with high degrees of uncertainty associated with population estimates. Integrated population models (IPMs) can help alleviate that challenge, but they are often limited to narrow spatial or temporal windows owing to the financial and logistical burdens of acquiring requisite datasets. To expand the spatiotemporal scope of practical IPM implementation, we developed a novel method that expresses demographic relatedness among sampled and unsampled locations using geographic principles of spatial autocorrelation. We interpolated demographic parameters at unsampled locations using parameter estimates from data‐informed locations. Errors attributable to the interpolative process were corrected using a joint likelihood and locally recorded count data (‘cheaper’ and broadly distributed). We evaluated the spatially interpolated IPM (SIIPM) for precision and accuracy under variable levels of spatial autocorrelation using simulated data and a Leave‐One‐Out Cross‐Validation (LOOCV) technique. Conventional IPMs and state‐space models (SSM) were fit to the same simulated datasets to provide a comparative assessment of the novel method. In a final, empirical demonstration we fit the SIIPM to data collected from Greater Sage‐Grouse (Centrocercus urophasianus; sage‐grouse) populations located in Nevada, U.S.A. during 2013–2021. SIIPMs outperformed conventional IPMs when fit to data possessing moderate‐to‐high levels of spatial autocorrelation. Under moderate levels of autocorrelation, the average improvement in parameter estimation was 13.6% for survival, 65.3% for recruitment and 23.7% for rate of population change (λ). When spatial autocorrelation was low, the SIIPM still outperformed contemporary approaches in areas that were geographically close (

Many revegetation projects are intended to benefit wildlife species. Yet, there are few a priori evaluations that assess the potential efficiency of restoration actions in recovering wildlife habitats. We developed a spatial vegetation–habitat recovery model to gauge the degree to which field planting strategies could be expected to recover multi-factor habitat conditions for wildlife following wildfires. We simulated a wildfire footprint, multiple sagebrush (Artemisia spp.) planting scenarios, and tracked projected vegetation growth for 15 years post-fire. We used a vegetation transition framework to track and estimate the degree to which revegetation could accelerate habitat restoration for a Greater sage-grouse (Centrocercus) population within the Great Basin, western United States. We assessed the amount of habitat 15 years post-fire to estimate the degree to which revegetation could be expected to accelerate habitat restoration. Our results highlight a potential disconnect between the expansive areas required by wide-ranging wildlife such as sage-grouse and the relatively small areas that planting treatments have created. Habitat restorations and planting strategies that are intended to benefit sage-grouse may only speed up localized habitat restoration. This study provides an example of how linked revegetation–habitat modeling approaches can scope the expected return on restoration investment for habitat improvements and support the strategic use of limited restoration resources.

Abstract Management decisions often focus on the habitat selection of marked individuals without considering the contribution to demographic performance in selected habitats. Because habitat selection is not always adaptive, understanding the spatial relationship between habitat selection and demographic performance is critical to management decisions. Mapping both habitat selection and demographic performance for species of conservation concern can help guide population‐scale conservation efforts. We demonstrate a quantitative approach to differentiate areas supporting selection and survival at large spatial extents. As a case study, we applied this approach to greater sage‐grouse (Centrocercus urophasianus; hereafter, sage‐grouse), an indicator species for sagebrush ecosystems. We evaluated both habitat selection and survival across multiple reproductive life stages (nesting, brood‐rearing) in the Bi‐State Distinct Population Segment, 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 reproductive life stages. These findings suggest resource demands vary across time, with predation risk being a dominant driver of habitat selection during nesting and early brood‐rearing periods when chicks are smaller and flightless, whereas access to forage resources becomes more important during late brood rearing when resources become increasingly limited. Moving beyond identifying and managing habitat solely based on species occupancy or use by incorporating demographic measures allows managers to tailor actions to their specific goals; for example, protections of areas that support high selection and high survival and restoration actions focused on increasing survival in areas of high selection and low survival.

Livestock grazing, a widespread land use in semi-arid systems, is often placed in opposition to the perpetuation of biological soil crusts (“biocrusts”: lichens, mosses, and algal crusts including cyanobacteria) that live on the soil surface and provide ecosystem functions. The composition of biocrusts and vascular plants varies with climate, soils, and disturbance. In general, ruderal mosses and light algal crusts make up greater proportions of biocrusts in the presence of disturbance, although morphogroups of biocrusts respond differently to various disturbances. It is unknown if there are scenarios under which grazing can occur and ruderal components of biocrust could be maintained. We examine the hypothesis that soil surface texture-moisture interactions influence the ability of biocrusts to withstand trampling, reasoning that finer-textured soils are firmer (therefore serving as a better substrate for biocrusts) when dry and that coarser-textured are firmer when wet. We test these relationships within Birds of Prey, National Conservation Area (Boise, Idaho, USA). Results demonstrate two associations of biocrusts, dependent on season of grazing: one dominated by light algal crusts and lichens that frequently occurs with wet season grazing, and a second dominated by tall mosses and cup lichens that frequently occurs with dry season grazing. High cover of the invasive annual grass, Bromus tectorum (L.) was observed on sites with coarse-textured soils, and high sand content, that are grazed at relatively high intensities, creating unstable surfaces, and likely putting biocrusts at greater susceptibility to trampling. Results suggest that livestock management that accounts for soil texture and moisture could be used to maintain cover of ruderal biocrusts on fine-textured soils, that are grazed in the dry season, at low intensity. We discuss our findings in the context of managing for species of interest. Our findings are timely as varying the season of grazing is increasingly discussed as a means of favoring desirable native perennial grasses. Although ruderal morphogroups of biocrusts are not interpreted as having equivalent ecosystem functions compared to intact biocrusts, their contributions to soil stability, fertility, hydrology, and weed abatement could increase if they were more intentionally targeted by management.

Abstract Wildfire events are becoming more frequent and severe on a global scale. Rising temperatures, prolonged drought, and the presence of pyrophytic invasive grasses are contributing to the degradation of native vegetation communities. Within the Great Basin region of the western U.S., increasing wildfire frequency is transforming the ecosystem toward a higher degree of homogeneity, one dominated by invasive annual grasses and declining landscape productivity. Greater sage-grouse (Centrocercus urophasianus; hereafter sage-grouse) are a species of conservation concern that rely on large tracts of structurally and functionally diverse sagebrush (Artemisia spp.) communities. Using a 12-year (2008–2019) telemetry dataset, we documented immediate impacts of wildfire on demographic rates of a population of sage-grouse that were exposed to two large wildfire events (Virginia Mountains Fire Complex—2016; Long Valley Fire—2017) near the border of California and Nevada. Spatiotemporal heterogeneity in demographic rates were accounted for using a Before-After Control-Impact Paired Series (BACIPS) study design. Results revealed a 40% reduction in adult survival and a 79% reduction in nest survival within areas impacted by wildfires. Our results indicate that wildfire has strong and immediate impacts to two key life stages of a sagebrush indicator species and underscores the importance of fire suppression and immediate restoration following wildfire events.

Abstract Anthropogenic resource subsidization across western ecosystems has contributed to widespread increases in generalist avian predators, including common ravens (Corvus corax; hereafter, raven). Ravens are adept nest predators and can negatively impact species of conservation concern. Predation effects from ravens are especially concerning for greater sage‐grouse (Centrocercus urophasianus; hereafter, sage‐grouse), which have experienced prolonged population decline. Our objectives were to quantify spatiotemporal patterns in raven density, evaluate sage‐grouse nest success concurrent with fluctuating raven densities, and demonstrate a spatially explicit decision support tool to guide management applications to appropriate conflict areas. We combined ~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 and other environmental covariates that influence the risk of nest failure. Raven density commonly exceeded 0.5 ravens km−2 and increased at low elevations with more anthropogenic development and/or agriculture. Reduced sage‐grouse nest survival was strongly associated with elevated raven density (e.g., >0.5 ravens km−2) and varied with topographic ruggedness, shrub cover, and burned areas. For conservation application, we developed a spatially explicit planning tool that predicts nest survival under current and reduced raven numbers within the Great Basin to help direct management actions to localized areas where sage‐grouse nests are at highest risk of failure. Our modeling framework can be generalized to multiple species where spatially registered abundance and demographic data are available.

A fundamental goal of population ecologists is to identify drivers responsible for temporal variation in abundance. Understanding whether variation is associated with environmental stochasticity or anthropogenic disturbances, which are more amenable to management action, is crucial yet difficult to achieve. Here, we present a hierarchical monitoring framework that models rates of change in abundance from spatially structured populations and identifies when local declines fall out of synchrony with trends at larger spatial scales. Importantly, the framework provides signals that alert managers to the categorical significance of observed declines while avoiding signals where declines result from drivers operating at larger spatial scales (e.g., periodic reductions in primary productivity owing to drought). We demonstrate utility through application to a rapidly declining sagebrush (Artemisia spp.) indicator species (greater sage-grouse; Centrocercus urophasianus) using 30 years (1990–2019) of count data collected from greater than 4,400 leks (habitual breeding sites) distributed across the western United States. Results revealed population declines, immediately preceding triggers (2–4-year period), ranging between 58 and 68%. Conversely, population trends unassociated with triggers showed little-to-no sign of decline. Retrospective application of the monitoring framework indicated an average annual rate of 1.7% of leks or 1.3% of neighborhood clusters (lek aggregations) would have required management intervention to reverse range-wide declines and stabilize the U.S. population as a whole.

Increased demand for domestic production of renewable energy has led to expansion of energy infrastructure across western North America. Much of the western U.S. comprises remote landscapes that are home to a variety of vegetation communities and wildlife species, including the imperiled sagebrush ecosystem and indicator species such as greater sage-grouse (Centrocercus urophasianus). Geothermal sources in particular have potential for continued development across the western U.S. but impacts to greater sage-grouse and other species are unknown. To address this information gap, we describe a novel two-pronged methodology that analyzes impacts of geothermal energy production on pattern and process of greater sage-grouse populations using (a) before-after control-impact (BACI) measures of population growth and lek absence rates and (b) concurrent-to-operation evaluations of demographic rates. Growth and absence rate analyses utilized 14 years of lek survey data collected prior (2005–2011) and concurrent (2012–2018) to geothermal operations at two sites in Nevada, USA. Demographic analyses utilized relocation data, restricted inference to concurrent years, and incorporated 17 additional control sites. Demographic results were applied to >100 potential geothermal sites distributed across the study region to generate spatially explicit predictions of unrealized population-level impacts. • State-space and generalized linear models yield estimates of population growth and lek absence rates, respectively, before and after the onset of geothermal energy production; distances ranging from 2–30 km are evaluated as alternative control-impact footprint hypotheses; this provides inference about the spatial extent as well as the magnitude of impacts associated with geothermal development. • Estimation of important population demographic rates are implemented to investigate the processes by which geothermal energy development might reduce population growth; independent estimates of confounding, environmental effects from 17 control sites are made spatially explicit within ‘impact’ models to establish baseline conditions otherwise masked by collinearity. • Population matrix models are built using estimates from demographic analyses to provide landscape mapping of impacts associated with potential geothermal sites.

Identifying habitat needs for species with large distributions is challenging because species-habitat associations may vary across scales and regions (spatial nonstationarity). Furthermore, management efforts often cross jurisdictional boundaries, complicating the development of cohesive conservation strategies among management entities. The greater sage-grouse (Centrocercus urophasianus) is a rapidly declining species that spans 11 U.S. states and responds to habitat conditions across a wide range of spatial scales and regions. Allowing for regional variance in species-habitat associations and suitability predictions could systematically identify important habitats at levels relevant to management. We collaboratively developed a model with Bureau of Land Management (BLM) biologists that: (1) evaluated the scale of effect for different environmental covariates; (2) accounted for regional differences in population-level responses; and (3) predicted probabilities of persistence across the U.S. occupied range. We modeled range-wide lek persistence data (6615 communal breeding sites classified as active or inactive) as a function of environmental covariates. Environmental covariates included sagebrush cover, pinyon-juniper cover, topography, precipitation, point and line disturbance densities, and landscape configuration metrics. Our model treated habitat assessment areas – regionally delineated by BLM biologists – as random intercepts and slopes that allowed for geographic variation in species-habitat associations and predicted probabilities of lek persistence. Our final model indicated support for 12 environmental covariates predicting lek persistence at scales extending between 1- to 15-km radii from lek centers, and a covariate measuring distance to the occupied range boundary. Five of these covariates showed significant regionally varying responses: sagebrush clumpiness (a measure of habitat aggregation), pinyon-juniper cover, point disturbance of anthropogenic features such as energy infrastructure and communication towers, elevation, and a topographic index associated with mesic habitats. This spatial nonstationarity indicates unitary range-wide recommendations, or rules-of-thumb with respect to their effects on lek persistence, may be problematic for these environmental conditions. For covariates that did not include random slopes, and which were potentially amenable to management actions, we found that leks were predicted to become extirpated when sagebrush cover fell below 9.6 % (summarized at the 3.2-km radius extent), and the proportion of classified sagebrush habitat fell below 0.7 (1-km). We produced a continuous predictive probability surface of lek persistence which we binned based on model sensitivity thresholds to produce habitat quality categories. The highest quality habitat (capturing 50 % of active leks) covered 25.5 % of the occupied range, while the combined lowest through highest quality habitats (capturing 95 % of active leks) covered 65.0 %. Accommodating regional environmental differences in models that are relevant to habitat management planning will help ensure their applicability to targeted goals. Continuous collaboration between modelers and land managers early in the modeling process increases the likelihood of this outcome.

Abstract Increased wildfire frequency and associated replacement of sagebrush (Artemisia spp.) with invasive annual grasses contribute to declines of greater sage‐grouse (Centrocercus urophasianus; hereafter, sage‐grouse) populations across the Great Basin. However, little is known about wildfire effects on sage‐grouse nest‐site selection and nest survival, which can influence population persistence. The primary objective of this study was to evaluate the effects of the Rush Fire on sage‐grouse nest survival using before (2007–2009) and after (2015–2018) data collected from a population of sage‐grouse occupying the border of northeastern California and northwestern Nevada. We employed a before–after–control–impact (BACI) experimental design to account for spatiotemporal heterogeneity in the system and to derive estimates of relative change in survival parameters. Sage‐grouse nest survival decreased after the Rush Fire but decreased more in the burned area relative to the unburned area. Although female sage‐grouse continued to occupy burned areas, nest survival was reduced from 52% to 19%. Using a BACI ratio approach we found that nest survival decreased approximately 51% in the burned area, relative to the unburned area, following wildfire. Habitat analyses were restricted to the postfire period and found that female sage‐grouse that nested within unburned areas selected for wider nesting substrate, taller perennial grass height, and greater low sagebrush canopy cover. Conversely, female sage‐grouse that nested in burned areas used shorter sagebrush canopy cover than what was available across the entire study area but showed stronger selection for perennial grass height than their unburned counterparts. Strong nest‐site fidelity in sage‐grouse may explain the continued use of suboptimal habitat in wildfire‐altered landscapes, resulting in a reproductive cost, and overall reproduction well below replacement rate. Results suggest that fire suppression or rapid postfire habitat restoration, especially within nesting habitat, may be essential to conserving robust sage‐grouse populations into the future.

Abstract Water is a critical and limited resource, particularly in the arid West, but water availability is projected to decline even while demand increases due to growing human populations and increases in duration and severity of drought. Mesic areas provide important water resources for numerous wildlife species, including the greater sage‐grouse (Centrocercus urophasianus; hereafter, sage‐grouse), an indicator for the health of sagebrush ecosystems. Understanding how wildlife use these crucial areas is necessary to inform management and conservation of sensitive species. Specifically, the influence of anthropogenic water subsidies such as irrigated pastures is not well‐studied. We evaluated brood‐rearing habitat selection and brood survival of sage‐grouse in Long Valley, California, an area where the water rights are primarily owned by the city of Los Angeles and water is used locally to irrigate for livestock. This area thus represents a unique balance between the needs of wildlife and people that could increasingly define future water management. In this study, sage‐grouse broods moved closer to the edge of mesic areas and used more interior areas during the late brood‐rearing period, selecting for greener areas after 1 July. Mesic areas were particularly important during dry years, with broods using areas farther interior than in wet years. Brood survival was also positively influenced by the availability and condition of mesic resources, as indicated by variation in values of normalized difference vegetation index (NDVI), with survival peaking at moderate values of NDVI and just outside the edge but decreasing inside the mesic areas. Our results highlight the importance of quality edge habitat of large mesic areas for sage‐grouse to balance habitat selection and survival, particularly during drier years and during the late brood‐rearing period, which is a critical period because chick survival has been shown to influence population growth. This study highlights the implications of large‐scale anthropogenic water manipulation, and the balance between local irrigation and water distribution to benefit other regions, from the context of a species of high conservation concern in North American sagebrush ecosystems.

Numerous wildlife species within semi-arid shrubland ecosystems across western North America are experiencing substantial habitat loss and fragmentation. These changes in habitat are often attributed to a diverse suite of factors including prolonged and increasingly severe droughts, conifer expansion, anthropogenic development, domestic and feral livestock grazing, and invasion of exotic annual grasses, which promotes increased wildfire frequency and severity. Greater sage-grouse (Centrocercus urophasianus; hereafter, sage-grouse) are considered an indicator of sagebrush ecosystem health and have experienced widespread population decline associated with habitat loss and degradation, as well as changes in predator communities. Our objectives were to model and map sage-grouse habitat selection and survival during the important brood-rearing life stage in relation to landscape-scale environmental predictors. Furthermore, we sought to understand impacts of wildfire and annual grass invasion on brood habitat, as these accelerated disturbance regimes are a primary cause of habitat loss within the Great Basin region of the USA. We used a hierarchical Bayesian modeling framework to estimate resource selection functions and survival for early and late brood-rearing stages of sage-grouse in relation to a broad suite of habitat characteristics evaluated at multiple spatial scales within the Great Basin from 2009 to 2019. Sage-grouse selected for greater perennial grass cover, higher relative elevations, and areas closer to springs and wet meadows during both early and late brood-rearing. Terrain characteristics, including heat load and aspect, were important in survival models, as was variation in shrub height. We also found strong evidence for higher survival for both early and late broods within previously burned areas, but survival within burned areas decreased as annual grass cover (i.e. cheatgrass, Bromus tectorum) increased. This interaction effect demonstrates how invasion of annual grasses into burned areas, which has become prevalent in Great Basin sagebrush ecosystems, can lead to maladaptive habitat selection by brood-rearing greater sage-grouse. Understanding these complex relationships aids wildlife conservation and habitat management as wildfire and annual grass cycles continue to accelerate across western ecosystems.

Abstract Human enterprise has led to large‐scale changes in landscapes and altered wildlife population distribution and abundance, necessitating efficient and effective conservation strategies for impacted species. Greater sage‐grouse (Centrocercus urophasianus; hereafter sage‐grouse) are a widespread sagebrush (Artemisia spp.) obligate species that has experienced population declines since the mid‐1900s resulting from habitat loss and expansion of anthropogenic features into sagebrush ecosystems. Habitat loss is especially evident in North Dakota, USA, on the northeastern fringe of sage‐grouse’ distribution, where a remnant population remains despite recent development of energy‐related infrastructure. Resource managers in this region have determined a need to augment sage‐grouse populations using translocation techniques that can be important management tools for countering species decline from range contraction. Although translocations are a common tool for wildlife management, very little research has evaluated habitat following translocation, to track individual behaviors such as habitat selection and fidelity to the release site, which can help inform habitat requirements to guide selection of future release sites. We provide an example where locations from previously released radio‐marked sage‐grouse are used in a resource selection function framework to evaluate habitat selection following translocation and identify areas of seasonal habitat to inform habitat management and potential restoration needs. We also evaluated possible changes in seasonal habitat since the late 1980s using spatial data provided by the Rangeland Analysis Platform coupled with resource selection modeling results. Our results serve as critical baseline information for habitat used by translocated individuals across life stages in this study area, and will inform future evaluations of population performance and potential for long‐term recovery.

Abstract Defining boundaries of species' habitat across broad spatial scales is often necessary for management decisions, and yet challenging for species that demonstrate differential variation in seasonal habitat use. Spatially explicit indices that incorporate temporal shifts in selection can help overcome such challenges, especially for species of high conservation concern. Greater sage‐grouse Centrocercus urophasianus (hereafter, sage‐grouse), a sagebrush obligate species inhabiting the American West, represents an important case study because sage‐grouse exhibit seasonal habitat patterns, populations are declining in most portions of their range and are central to contemporary national land use policies. Here, we modeled spatiotemporal selection patterns for telemetered sage‐grouse across multiple study sites (1,084 sage‐grouse; 30,690 locations) in the Great Basin. We developed broad‐scale spatially explicit habitat indices that elucidated space use patterns (spring, summer/fall, and winter) and accounted for regional climatic variation using previously published hydrographic boundaries. We then evaluated differences in selection/avoidance of each habitat characteristic between seasons and hydrographic regions. Most notably, sage‐grouse consistently selected areas dominated by sagebrush with few or no conifers but varied in type of sagebrush selected by season and region. Spatiotemporal variation was most apparent based on availability of water resources and herbaceous cover, where sage‐grouse strongly selected upland natural springs in xeric regions but selected larger wet meadows in mesic regions. Additionally, during the breeding period in spring, herbaceous cover was selected strongly in the mesic regions. Lastly, we expanded upon an existing joint–index framework by combining seasonal habitat indices with a probabilistic index of sage‐grouse abundance and space use to produce habitat maps useful for sage‐grouse management. These products can serve as conservation planning tools that help predict expected benefits of restoration activities, while highlighting areas most critical to sustaining sage‐grouse populations. Our joint–index framework can be applied to other species that exhibit seasonal shifts in habitat requirements to help better guide conservation actions.

Survival of translocated prairie-grouse (Tympanuchus spp.) is often low in the first few weeks or months following release into a novel environment. Understanding the processes and mechanisms that influence short-term, post-release survival, such as Allee effects (i.e., inverse density dependence), or individual characteristics of translocated individuals (e.g., age, sex) is imperative for designing successful translocation programs. Additionally, identifying timeframes during which translocated individuals are particularly vulnerable to mortality is especially useful for population management. We translocated 215 Columbian Sharp-tailed Grouse (T. phasianellus columbianus; CSTG) as a species reintroduction project to historical habitat in northeastern Nevada from 2013 to 2017 and quantified annual post-release survival probabilities during the 150-d breeding season. In a Bayesian framework, we first identified a prospective 40-d threshold in which the daily probability of survival substantially increased from before to after the threshold. Next, while accounting for the threshold effect at 40 d, we identified an age by population size interaction in which survival of yearling and adult CSTG changed across time. Yearlings exhibited substantially higher survival probabilities when the population at the release site was small (≤ 10 males on lek) during early translocation years, and adults exhibited substantially higher survival probabilities when the population at the release site was moderate or large (≥ 8 males on lek) during latter years of the translocation. This might represent inverse density dependent effects on survival wherein adult survival improved concomitantly with increases in population sizes. Short-term, post-release survival is less intuitive for yearlings, but yearlings greatly outperformed adults during the critical first three years of the reintroduction (i.e., the establishment phase) when the population at the release site was very small. In future reintroduction projects, establishing a population with translocated yearling CSTG followed by adults might hasten conservation goals.

Translocated animals undergo a phase of behavioral adjustment after being released in a novel environment, initially prioritizing exploration and gradually shifting toward resource exploitation. This transition has been termed post-release behavioral modification. Post-release behavioral modification may also manifest as changes in habitat selection through time, and these temporal dynamics may differ between individuals. We aimed to evaluate how post-release behavioral modification is reflected in temporal dynamics of habitat selection and its variability across individuals using a population of translocated female greater sage-grouse as a case study. Sage-grouse were translocated from Wyoming to North Dakota (USA) during the summers of 2018–2020. We analyzed individual habitat selection as a function of sagebrush cover, herbaceous cover, slope, and distance to roads. Herbaceous cover is a key foraging resource for sage-grouse during summer; thus, we expected a shift from exploration to exploitation to manifest as temporally-varying selection for herbaceous cover. For each individual sage-grouse (N = 26), we tested two competing models: a null model with no time-dependence and a model with time-dependent selection for herbaceous cover. We performed model selection at the individual level using an information-theoretic approach. Time-dependence was supported for five individuals, unsupported for seven, and the two models were indistinguishable based on AICc for the remaining fourteen. We found no association between the top-ranked model and individual reproductive status (brood-rearing or not). We showed that temporal dynamics of post-release habitat selection may emerge in some individuals but not in others, and that failing to account for time-dependence may hinder the detection of steady-state habitat selection patterns. These findings demonstrate the need to consider both temporal dynamics and individual variability in habitat selection when conducting post-release monitoring to inform translocation protocols.

Pinyon and juniper expansion into sagebrush ecosystems is one of the major challenges facing land managers in the Great Basin. Effective pinyon and juniper treatment requires maps that accurately and precisely depict tree location and degree of woodland development so managers can target restoration efforts for early stages of pinyon and juniper expansion. However, available remotely sensed layers that cover a regional spatial extent lack the spatial resolution or accuracy to meet this need. Accuracy can be improved using object-based image analysis methods such as automated feature extraction, which has proven successful in accurately classifying land cover at the site-level but to date has yet to be applied to regional extents due to time and computational limitations. Using Feature Analyst™, we implement our framework with 1-m2 reference imagery provided by National Agricultural Imagery Program to classify conifers across Nevada and northeastern California. Our resulting binary conifer map has an overall accuracy of 86%. We discuss the advantages to accuracy and precision our framework provides compared to other classification methods.● This framework allows automated feature extraction for large quantities of data and very high spatial resolution imagery● It leverages supervised learning● It results in high accuracy maps for regional spatial extents

Imperiled sagebrush (Artemisia spp.) ecosystems of western North America are experiencing unprecedented conservation planning efforts. Advances in decision-support tools operationalize concepts of ecosystem resilience by quantitatively linking spatially explicit variation in soil and plant processes to outcomes of biotic and abiotic disturbances. However, failure to consider higher trophic-level fauna of conservation concern in these tools can hinder efforts to operationalize resilience owing to spatiotemporal lags between slower reorganization of plant and soil processes following disturbance, and faster behavioral and demographic responses of fauna to disturbance. Here, we provide multi-scale examples of decision-support tools for management and restoration actions that evaluate general resilience mapped to variation in soil moisture and temperature regimes through new lenses of habitat selection and population performance responses for an at-risk obligate species to sagebrush ecosystems, the greater sage-grouse (Centrocercus urophasianus). We then briefly describe general pathways going forward for more explicit integration of sage-grouse fitness with factors influencing variation in sagebrush resilience to disturbance and resistance to invasive species (e.g., annual grasses). The intended product of these efforts is a more targeted operational definition of resilience for managers by using quantifiable metrics that help limit chances of spatiotemporal mismatches among restoration responses owing to differences in engineering resilience between sagebrush ecosystem processes and sage-grouse population dynamics. Moreover, spatial resilience can be promoted though explicit consideration of sage-grouse and sagebrush predicted responses to active and passive management treatments across space and time. We describe tools that include multi-scale geospatial overlays and simulation analyses of post-disturbance land cover recovery aimed at prioritizing primary threats to sagebrush ecosystems in the Great Basin in the western portion of sage-grouse range (i.e., grass-fire cycles and conifer expansion), but underlying concepts have broader application to a range of ecosystems.

Abstract Population monitoring is integral to the conservation and management of wildlife; yet, analyses of population demographic data rarely consider processes occurring across spatial scales, potentially limiting the effectiveness of adaptive management. Therefore, we developed a method to identify hierarchical levels of organization (i.e., populations) to define multiple spatial scales, specifically intended to help guide appropriate conservation and management actions. This approach can support mobile species with high site fidelity where surveys occur on birthing/breeding grounds or migratory stopovers. Our approach used a graph‐based clustering algorithm (Spatial K'luster Analysis by Tree Edge Removal) that explicitly included habitat selection information at multiple scales and further refined with constraint‐based rules. We applied these concepts to greater sage‐grouse leks (breeding grounds), a species of conservation concern, in two different ecological contexts (Nevada and Wyoming, USA). The constraint‐based rules accounted for inter‐lek movement distances based on literature and field studies in Nevada from 2012 to 2016, included methods to support a spatially balanced monitoring design, and identified barriers to movements among leks based on resistance surfaces. We evaluated the performance of our hierarchical clusters in Nevada using independent data from radio‐marked sage‐grouse, and we found the finest‐scaled cluster level captured ~90% of sage‐grouse movements and mid‐level scales captured ~97–99% of movements. We expected comparable performance for Wyoming, where we lacked radio‐marked sage‐grouse for an evaluation, because genetic studies estimate similar dispersal distances to our ~15 km inter‐lek movement distance in Nevada. For sage‐grouse and other mobile species with high site fidelity, our approach to defining these frameworks could prove valuable for conservation and management applications, such as improving estimation of scale‐dependent population trends and guiding the prescription of management actions at spatial scales that align with identified threats. Specific to sage‐grouse, our analysis sets the stage for designing a monitoring framework that relies on comparison of short‐ and long‐term population trends across our defined spatial scales and identifies and disentangles factors driving local (e.g., habitat quality) and regional (e.g., climate) population changes, thereby supporting scale‐dependent management and research needs for adaptive management practices.

Abstract Population monitoring is important for investigating a variety of ecological questions, and N‐mixture models are increasingly used to model population size (N) and trends (λ) while estimating detectability (p) from repeated counts within primary periods (when populations are closed to changes). Extending these models to dynamic processes with serial dependence across primary periods may relax the closure assumption, but simulations to evaluate models and inform effort (e.g., number of repeated counts) typically assume p is constant or random across sites and years. Thus, it is unknown how these models perform under scenarios where trends in p confound inferences on N and λ, and conclusions regarding effort may be overoptimistic. Here, we used global positioning system data from greater sage‐grouse (Centrocercus urophasianus) to inform simulations of the detection process for lek counts of this species, and we created scenarios with and without linear annual trends in p. We then compared estimates of N and λ from hierarchical population models either fit with single maximum counts or with detectability estimated from repeated counts (dynamic N‐mixture models). We also explored using auxiliary data to correct counts for variation in detectability. Uncorrected count models consistently underestimated N by >50%, whereas N‐mixture models without auxiliary data underestimated N to a lesser degree due to unmodeled heterogeneity in p such as age. Nevertheless, estimates of λ from both types of models were unbiased and similar for scenarios without trends in p. When p declined systematically across years, uncorrected count models underestimated λ, whereas N‐mixture models estimated λ with little bias when all sites were counted repeatedly. Auxiliary data also reduced bias in parameter estimates. Evaluating population models using scenarios with systematic variation in p may better reveal potential biases and inform effort than simulations that assume p is constant or random. Dynamic N‐mixture models can distinguish between trends in p and N, but also require repeated counts within primary periods for accurate estimates. Auxiliary data may be useful when researchers lack repeated counts, wish to monitor more sites less intensively, or require unbiased estimates of N.

Radar systems designed to detect avian activity at airfields are useful in understanding factors that influence the risk of bird and aircraft collisions (bird strikes). We used an avian radar system to measure avian activity at Beale Air Force Base, California, USA, during 2008 and 2009. We conducted a 2-part analysis to examine relationships among avian activity, bird strikes, and meteorological and time-dependent factors. We found that avian activity around the airfield was greater at times when bird strikes occurred than on average using a permutation resampling technique. Second, we developed generalized linear mixed models of an avian activity index (AAI). Variation in AAI was first explained by seasons that were based on average migration dates of birds at the study area. We then modeled AAI by those seasons to further explain variation by meteorological factors and daily light levels within a 24- hour period. In general, avian activity increased with decreased temperature, wind, visibility, precipitation, and increased humidity and cloud cover. These effects differed by season. For example, during the spring bird migration period, most avian activity occurred before sunrise at twilight hours on clear days with low winds, whereas during fall migration, substantial activity occurred after sunrise, and birds generally were more active at lower temperatures. We report parameter estimates (i.e., constants and coefficients) averaged across models and a relatively simple calculation for safety officers and wildlife managers to predict AAI and the relative risk of bird strike based on time, date, and meteorological values. We validated model predictability and assessed model fi t. These analyses will be useful for general inference of avian activity and risk assessment efforts. Further investigation and ongoing data collection will refine these inference models and improve our understanding of factors that influence avian activity, which is necessary to inform management decisions aimed at reducing risk of bird strikes.

Human-altered landscapes have provided resource subsidies for common ravens (Corvus corax) resulting in a substantial increase in raven abundance and distribution throughout the United States and Canada in the past 25 years. Ravens are effective predators of eggs and young of ground-nesting birds. During 2002–2005, we tested whether chicken egg baits treated with CPTH (3-chloro-p-toluidine hydrochloride) could be used to manage raven numbers in an area where raven depredation was impacting sharp-tailed grouse (Tympanuchus phasianellus columbianus) and greater sage-grouse (Centrocercus urophasianus) populations in Nevada. We performed multiple raven surveys at a treatment site and 3 control sites and used videography to identify predators and estimate egg bait consumption. We detected reductions in raven abundances over time at the treatment site during all years of this study and did not detect reductions in raven abundances at control sites. Videographic observations of egg consumption indicated that the standard 1:2 ratio (1 raven removed/2 eggs consumed) substantially overestimated raven take because nontarget species (rodents) consumed some egg baits. The technique described here likely will be effective at reducing raven densities where this is the intended management action.

Abundance and distribution of Common Ravens (Corvus corax) have increased across western North America in recent decades, leading to conservation concern for sensitive prey species. Multiple management options have been proposed to reduce raven numbers or reduce the impacts of predation by ravens on sensitive species. We carried out a longitudinal study to evaluate the effects of experimentally manipulating the reproductive success of territorial ravens on the reproductive performance of their prey on Alcatraz Island across 6 years. Specifically, we employed remote video-monitoring on nests of predator and prey to document the effects of oiling raven eggs, a technique to prevent eggs from hatching, on raven reproduction, and to estimate impacts of raven hatching success on their predation of Black-crowned Night-Heron (Nycticorax nycticorax) nests. We used Bayesian multinomial logistic exposure models to estimate night-heron nest and chick survival and account for variation in nest failure across different life stages (i.e., egg versus nestling). We found daily predation rates on night-heron nests (median: 1.71%, 85% CI: 1.15-2.44%) and chicks (median: 0.57%, 85% CI: 0.27-1.03%) were the highest during years when ravens nested successfully. During years that raven eggs were oiled, daily predation rates on night-heron nests (0.98%, 85% CI: 0.55-1.57%) and chicks (0.00%, 85% CI: 0.0-0.00%) decreased, and we observed the lowest daily predation rates for nests (0.40%, 85% CI: 0.17-0.76%) during years when raven nesting was naturally absent on the island. The greatest probability of survival of night-heron eggs and chicks occurred during years when ravens were present but not nesting on Alcatraz. Our results suggest that manipulation of raven breeding success can influence predation and reproductive performance of their prey. These results also indicate that egg-oiling can be a viable localized method to reduce raven recruitment and possibly aid in the conservation of sensitive avian species.