The potential influence of genome-wide adaptive divergence on conservation translocation outcome in an isolated greater sage-grouse population.

Conservation translocations are an important conservation tool commonly employed to augment declining or reestablish extirpated populations. One goal of augmentation is to increase genetic diversity and reduce the risk of inbreeding depression (i.e., genetic rescue). However, introducing individuals from significantly diverged populations risks disrupting coadapted traits and reducing local fitness (i.e., outbreeding depression). Genetic data are increasingly more accessible for wildlife species and can provide unique insight regarding the presence and retention of introduced genetic variation from augmentation as an indicator of effectiveness and adaptive similarity as an indicator of source and recipient population suitability. We used 2 genetic data sets to evaluate augmentation of isolated populations of greater sage-grouse (Centrocercus urophasianus) in the northwestern region of the species range (Washington, USA) and to retrospectively evaluate adaptive divergence among source and recipient populations. We developed 2 statistical models for microsatellite data to evaluate augmentation outcomes. We used one model to predict genetic diversity after augmentation and compared these predictions with observations of genetic change. We used the second model to quantify the amount of observed reproduction attributed to transplants (proof of population integration). We also characterized genome-wide adaptive divergence among source and recipient populations. Observed genetic diversity (HO = 0.65) was higher in the recipient population than predicted had no augmentation occurred (HO = 0.58) but less than what was predicted by our model (HO = 0.75). The amount of shared genetic variation between the 2 geographically isolated resident populations increased, which is evidence of periodic gene flow previously assumed to be rare. Among candidate adaptive genes associated with elevated fixation index (FST) (143 genes) or local environmental variables (97 and 157 genes for each genotype-environment association method, respectively), we found clusters of genes with related functions that may influence the ability of transplants to use local resources and navigate unfamiliar environments and their reproductive potential, all possible reasons for low genetic retention from augmentation.

Influencia potencial de la divergencia adaptativa a nivel genoma sobre el resultado de la reubicación para conservación en una población aislada de urogallo mayor Resumen Las reubicaciones para conservación son una herramienta importante que se usa con frecuencia para aumentar las poblaciones en declinación o reestablecer las poblaciones erradicadas. Una de las metas de este aumento es incrementar la diversidad genética y reducir el riesgo de depresión endogámica (es decir, rescate genético). Sin embargo, la introducción de individuos de una población con divergencia significativa puede perturbar los rasgos coadaptados y reducir la aptitud local (es decir, depresión exogámica). La información genética es cada vez más accesible para las especies silvestres y puede proporcionar conocimiento único con respecto a la presencia y retención de la variación genética introducida a partir del aumento como un indicador de eficiencia y las similitudes adaptativas como un indicador de la idoneidad de la población de origen y la receptora. Usamos dos conjuntos de datos genéticos para evaluar el aumento de las poblaciones aisladas del urogallo mayor (Centrocercus urophasianus) en la región noroeste de la distribución de la especie (Washington, EUA) y para evaluar de forma retrospectiva la divergencia adaptativa entre la población de origen y la receptora. Desarrollamos dos modelos estadísticos para los datos microsatelitales para así evaluar los resultados del aumento. Usamos un modelo para predecir la diversidad genética después del aumento y comparamos estas predicciones con observaciones del cambio genético. Usamos el segundo modelo para cuantificar el aumento de la reproducción observada atribuida a las reubicaciones (evidencia de la integración poblacional). También caracterizamos la divergencia adaptativa a nivel genoma entre la población de origen y la población receptora. La diversidad genética observada (HO = 0.65) fue mayor de lo que se predijo en la población receptora de no haber ocurrido el aumento (HO = 0.58) pero menor de lo que se predijo en nuestro modelo (HO = 0.75). El aumento de la variación genética compartida entre las dos poblaciones residentes geográficamente aisladas incrementó, lo cual es evidencia de un flujo génico periódico que antes se supuso casi no ocurría. Entre los genes adaptativos candidatos asociados a una FST elevada (143 genes) o a variables ambientales locales (97 y 157 genes para cada método de asociación entre el ambiente y el genotipo, respectivamente) encontramos grupos de genes con funciones relacionadas que pueden influir sobre la habilidad de cada reubicación para usar recursos locales y navegar ambientes desconocidos y su potencial reproductivo, todas posibles razones para la baja retención genética en el aumento.

Living on the edge: Predicting songbird response to management and environmental changes across an ecotone.

Effective wildlife management requires robust information regarding population status, habitat requirements, and likely responses to changing resource conditions. Single-species management may inadequately conserve communities and result in undesired effects to non-target species. Thus, management can benefit from understanding habitat relationships for multiple species. Pinyon pine and juniper (Pinus spp. and Juniperus spp.) are expanding into sagebrush-dominated (Artemisia spp.) ecosystems within North America and mechanical removal of these trees is frequently conducted to restore sagebrush ecosystems and recover Greater Sage-grouse (Centrocercus urophasianus). However, pinyon-juniper removal effects on non-target species are poorly understood, and changing pinyon-juniper woodland dynamics, climate, and anthropogenic development may obscure conservation priorities. To better predict responses to changing resource conditions, evaluate non-target effects of pinyon-juniper removal, prioritize species for conservation, and inform species recovery within pinyon-juniper and sagebrush ecosystems, we modeled population trends and density-habitat relationships for four sagebrush-associated, four pinyon-juniper-associated, and three generalist songbird species with respect to these ecosystems. We fit hierarchical population models to point count data collected throughout the western United States from 2008 to 2020. We found regional population changes for 10 of 11 species investigated; 6 of which increased in the highest elevation region of our study. Our models indicate pinyon-juniper removal will benefit Brewer's Sparrow (Spizella breweri), Green-tailed Towhee (Pipilo chlorurus), and Sage Thrasher (Oreoscoptes montanus) densities. Conversely, we predict largest negative effects of pinyon-juniper removal for species occupying early successional pinyon-juniper woodlands: Bewick's Wren (Thryomanes bewickii), Black-throated Gray Warblers (Setophaga nigrescens), Gray Flycatcher (Empidonax wrightii), and Juniper Titmouse (Baeolophus ridgwayi). Our results highlight the importance of considering effects to non-target species before implementing large-scale habitat manipulations. Our modeling framework can help prioritize species and regions for conservation action, infer effects of management interventions and a changing environment on wildlife, and help land managers balance habitat requirements across ecosystems.

A retrospective assessment of fuel break effectiveness for containing rangeland wildfires in the sagebrush biome.

Escalated wildfire activity within the western U.S. has widespread societal impacts and long-term consequences for the imperiled sagebrush (Artemisia spp.) biome. Shifts from historical fire regimes and the interplay between frequent disturbance and invasive annual grasses may initiate permanent state transitions as wildfire frequency outpaces sagebrush communities' innate capacity to recover. Therefore, wildfire management is at the core of conservation plans for sagebrush ecosystems, especially critical habitat for species of conservation concern such as the greater sage-grouse (Centrocercus urophasianus; hereafter sage-grouse). Fuel breaks help facilitate wildfire suppression by modifying behavior through fuels modification and allowing safe access points for containment by firefighters. The Bureau of Land Management has proposed to roughly double the existing fuel break network in the western U.S., centered on the Great Basin. To our knowledge, no broad-scale examination of fuel break effectiveness or the environmental conditions under which fuel breaks are expected to be most effective has been conducted. We performed a retrospective assessment of probability of fuel break contributing to wildfire containment on recorded wildfire and fuel break interactions from 1985 to 2018 within the western U.S. We characterized environmental, fuels, and weather conditions within 500 m of wildfire contact, and within 5 km of the approaching wildfire. We used a binomial mixed model within a Bayesian framework to identify relationships between these variables and fuel break success. Fuel breaks were least successful in areas classified as having low resilience to disturbance and low resistance to invasion, in areas composed of primarily woody fuels, and when operating in high temperature and low precipitation conditions. Fuel breaks were most effective in areas where fine fuels dominated and in areas that were readily accessible. Maintenance history and fuel break type also contributed to the probability of containment. Overall results indicate a complex and sometimes paradoxical relationship between landscape characteristics that promote wildfire spread and those that impact fuel break effectiveness. Finally, we developed predictive maps of fuel break effectiveness by fuel break type to further elucidate these complex relationships and to inform urgently needed fuel break placement and maintenance priorities across the sagebrush biome.

A genetic warning system for a hierarchically structured wildlife monitoring framework.

Genetic variation is a well-known indicator of population fitness yet is not typically included in monitoring programs for sensitive species. Additionally, most programs monitor populations at one scale, which can lead to potential mismatches with ecological processes critical to species' conservation. Recently developed methods generating hierarchically nested population units (i.e., clusters of varying scales) for greater sage-grouse (Centrocercus urophasianus) have identified population trend declines across spatiotemporal scales to help managers target areas for conservation. The same clusters used as a proxy for spatial scale can alert managers to local units (i.e., neighborhood-scale) with low genetic diversity, further facilitating identification of management targets. We developed a genetic warning system utilizing previously developed hierarchical population units to identify management-relevant areas with low genetic diversity within the greater sage-grouse range. Within this warning system we characterized conservation concern thresholds based on values of genetic diversity and developed a statistical model for microsatellite data to robustly estimate these values for hierarchically nested populations. We found that 41 of 224 neighborhood-scale clusters had low genetic diversity, 23 of which were coupled with documented local population trend decline. We also found evidence of cross-scale low genetic diversity in the small and isolated Washington population, unlikely to be reversed through typical local management actions alone. The combination of low genetic diversity and a declining population suggests relatively high conservation concern. Our findings could further facilitate conservation action prioritization in combination with population trend assessments and (or) local information, and act as a base-line of genetic diversity for future comparison. Importantly, the approach we used is broadly applicable across taxa.

Defining biologically relevant and hierarchically nested population units to inform wildlife management.

Wildlife populations are increasingly affected by natural and anthropogenic changes that negatively alter biotic and abiotic processes at multiple spatiotemporal scales and therefore require increased wildlife management and conservation efforts. However, wildlife management boundaries frequently lack biological context and mechanisms to assess demographic data across the multiple spatiotemporal scales influencing populations. To address these limitations, we developed a novel approach to define biologically relevant subpopulations of hierarchically nested population levels that could facilitate managing and conserving wildlife populations and habitats. Our approach relied on the Spatial "K"luster Analysis by Tree Edge Removal clustering algorithm, which we applied in an agglomerative manner (bottom-to-top). We modified the clustering algorithm using a workflow and population structure tiers from least-cost paths, which captured biological inferences of habitat conditions (functional connectivity), dispersal capabilities (potential connectivity), genetic information, and functional processes affecting movements. The approach uniquely included context of habitat resources (biotic and abiotic) summarized at multiple spatial scales surrounding locations with breeding site fidelity and constraint-based rules (number of sites grouped and population structure tiers). We applied our approach to greater sage-grouse (Centrocercus urophasianus), a species of conservation concern, across their range within the western United States. This case study produced 13 hierarchically nested population levels (akin to cluster levels, each representing a collection of subpopulations of an increasing number of breeding sites). These closely approximated population closure at finer ecological scales (smaller subpopulation extents with fewer breeding sites; cluster levels ≥2), where >92% of individual sage-grouse's time occurred within their home cluster. With available population monitoring data, our approaches can support the investigation of factors affecting population dynamics at multiple scales and assist managers with making informed, targeted, and cost-effective decisions within an adaptive management framework. Importantly, our approach provides the flexibility of including species-relevant context, thereby supporting other wildlife characterized by site fidelity.

Targeting Sagebrush (Artemisia Spp.) Restoration Following Wildfire with Greater Sage-Grouse (Centrocercus Urophasianus) Nest Selection and Survival Models.

Unprecedented conservation efforts for sagebrush (Artemisia spp.) ecosystems across the western United States have been catalyzed by risks from escalated wildfire activity that reduces habitat for sagebrush-obligate species such as Greater Sage-Grouse (Centrocercus urophasianus). However, post-fire restoration is challenged by spatial variation in ecosystem processes influencing resilience to disturbance and resistance to non-native invasive species, and spatial and temporal lags between slower sagebrush recovery processes and faster demographic responses of sage-grouse to loss of important habitat. Decision-support frameworks that account for these factors can help users strategically apply restoration efforts by predicting short and long-term ecological benefits of actions. Here, we developed a framework that strategically targets burned areas for restoration actions (e.g., seeding or planting sagebrush) that have the greatest potential to positively benefit sage-grouse populations through time. Specifically, we estimated sagebrush recovery following wildfire and risk of non-native annual grass invasion under four scenarios: passive recovery, grazing exclusion, active restoration with seeding, and active restoration with seedling transplants. We then applied spatial predictions of integrated nest site selection and survival models before wildfire, immediately following wildfire, and at 30 and 50 years post-wildfire based on each restoration scenario and measured changes in habitat. Application of this framework coupled with strategic planting designs aimed at developing patches of nesting habitat may help increase operational resilience for fire-impacted sagebrush ecosystems.

Scale-dependent influence of the sagebrush community on genetic connectivity of the sagebrush obligate Gunnison sage-grouse.

Habitat fragmentation and degradation impacts an organism's ability to navigate the landscape, ultimately resulting in decreased gene flow and increased extinction risk. Understanding how landscape composition impacts gene flow (i.e., connectivity) and interacts with scale is essential to conservation decision-making. We used a landscape genetics approach implementing a recently developed statistical model based on the generalized Wishart probability distribution to identify the primary landscape features affecting gene flow and estimate the degree to which each component influences connectivity for Gunnison sage-grouse (Centrocercus minimus). We were interested in two spatial scales: among distinct populations rangewide and among leks (i.e., breeding grounds) within the largest population, Gunnison Basin. Populations and leks are nested within a landscape fragmented by rough terrain and anthropogenic features, although requisite sagebrush habitat is more contiguous within populations. Our best fit models for each scale confirm the importance of sagebrush habitat in connectivity, although the important sagebrush characteristics differ. For Gunnison Basin, taller shrubs and higher quality nesting habitat were the primary drivers of connectivity, while more sagebrush cover and less conifer cover facilitated connectivity rangewide. Our findings support previous assumptions that Gunnison sage-grouse range contraction is largely the result of habitat loss and degradation. Importantly, we report direct estimates of resistance for landscape components that can be used to create resistance surfaces for prioritization of specific locations for conservation or management (i.e., habitat preservation, restoration, or development) or as we demonstrated, can be combined with simulation techniques to predict impacts to connectivity from potential management actions.

Assessing vegetation recovery from energy development using a dynamic reference approach.

Ecologically relevant references are useful for evaluating ecosystem recovery, but references that are temporally static may be less useful when environmental conditions and disturbances are spatially and temporally heterogeneous. This challenge is particularly acute for ecosystems dominated by sagebrush (Artemisia spp.), where communities may require decades to recover from disturbance. We demonstrated application of a dynamic reference approach to studying sagebrush recovery using three decades of sagebrush cover estimates from remote sensing (1985-2018). We modelled recovery on former oil and gas well pads (n = 1200) across southwestern Wyoming, USA, relative to paired references identified by the Disturbance Automated Reference Toolset. We also used quantile regression to account for unmodelled heterogeneity in recovery, and projected recovery from similar disturbance across the landscape. Responses to weather and site-level factors often differed among quantiles, and sagebrush recovery on former well pads increased more when paired reference sites had greater sagebrush cover. Little (<5%) of the landscape was projected to recover within 100 years for low to mid quantiles, and recovery often occurred at higher elevations with cool and moist annual conditions. Conversely, 48%-78% of the landscape recovered quickly (within 25 years) for high quantiles of sagebrush cover. Our study demonstrates advantages of using dynamic reference sites when studying vegetation recovery, as well as how additional inferences obtained from quantile regression can inform management.

Environmental gradients of selection for an alpine-obligate bird, the white-tailed ptarmigan (Lagopus leucura).

The warming climate will expose alpine species adapted to a highly seasonal, harsh environment to novel environmental conditions. A species can shift their distribution, acclimate, or adapt in response to a new climate. Alpine species have little suitable habitat to shift their distribution, and the limits of acclimation will likely be tested by climate change in the long-term. Adaptive genetic variation may provide the raw material for species to adapt to this changing environment. Here, we use a genomic approach to describe adaptive divergence in an alpine-obligate species, the white-tailed ptarmigan (Lagopus leucura), a species distributed from Alaska to New Mexico, across an environmentally variable geographic range. Previous work has identified genetic structure and morphological, behavioral, and physiological differences across the species' range; however, those studies were unable to determine the degree to which adaptive divergence is correlated with local variation in environmental conditions. We used a genome-wide dataset generated from 95 white-tailed ptarmigan distributed throughout the species' range and genotype-environment association analyses to identify the genetic signature and environmental drivers of local adaptation. We detected associations between multiple environmental gradients and candidate adaptive loci, suggesting ptarmigan populations may be locally adapted to the plant community composition, elevation, local climate, and to the seasonality of the environment. Overall, our results suggest there may be groups within the species' range with genetic variation that could be essential for adapting to a changing climate and helpful in guiding conservation action.

An empirical comparison of population genetic analyses using microsatellite and SNP data for a species of conservation concern.

BACKGROUND: Use of genomic tools to characterize wildlife populations has increased in recent years. In the past, genetic characterization has been accomplished with more traditional genetic tools (e.g., microsatellites). The explosion of genomic methods and the subsequent creation of large SNP datasets has led to the promise of increased precision in population genetic parameter estimates and identification of demographically and evolutionarily independent groups, as well as questions about the future usefulness of the more traditional genetic tools. At present, few empirical comparisons of population genetic parameters and clustering analyses performed with microsatellites and SNPs have been conducted. RESULTS: Here we used microsatellite and SNP data generated from Gunnison sage-grouse (Centrocercus minimus) samples to evaluate concordance of the results obtained from each dataset for common metrics of genetic diversity (HO, HE, FIS, AR) and differentiation (FST, GST, DJost). Additionally, we evaluated clustering of individuals using putatively neutral (SNPs and microsatellites), putatively adaptive, and a combined dataset of putatively neutral and adaptive loci. We took particular interest in the conservation implications of any differences. Generally, we found high concordance between microsatellites and SNPs for HE, FIS, AR, and all differentiation estimates. Although there was strong correlation between metrics from SNPs and microsatellites, the magnitude of the diversity and differentiation metrics were quite different in some cases. Clustering analyses also showed similar patterns, though SNP data was able to cluster individuals into more distinct groups. Importantly, clustering analyses with SNP data suggest strong demographic independence among the six distinct populations of Gunnison sage-grouse with some indication of evolutionary independence in two or three populations; a finding that was not revealed by microsatellite data. CONCLUSION: We demonstrate that SNPs have three main advantages over microsatellites: more precise estimates of population-level diversity, higher power to identify groups in clustering methods, and the ability to consider local adaptation. This study adds to a growing body of work comparing the use of SNPs and microsatellites to evaluate genetic diversity and differentiation for a species of conservation concern with relatively high population structure and using the most common method of obtaining SNP genotypes for non-model organisms.

Adaptive rangeland management benefits grassland birds utilizing opposing vegetation structure in the shortgrass steppe.

Rangelands are temporally and spatially complex socioecological systems on which the predominant land use is livestock production. In North America, rangelands also contain approximately 80% of remaining habitat for grassland birds, a guild of species that has experienced precipitous declines since the 1970s. While livestock grazing management may benefit certain grassland bird species by generating the vegetation structure and density they prefer, these outcomes are poorly understood for avian species breeding in the shortgrass steppe. We evaluated how two grazing management systems, continuous, season-long grazing and adaptive, rest-rotational grazing, affected grassland bird abundance from 2013 to 2017 in Colorado's shortgrass steppe. We examined grazing impacts in conjunction with ecological sites, which constitute unique soil and plant communities. When grazing management was evaluated in conjunction with spatial variation in ecological sites, we found three of our five focal bird species responded to grazing management. McCown's Longspur abundance decreased in pastures rested from grazing the previous year. The effect of grazing on Horned Lark and Grasshopper Sparrow depended on ecological site: Horned Lark density was highest in pastures that were intensively grazed and Grasshopper Sparrow density was highest in pastures that were rested the previous year in the least productive ecological site. In addition, densities of all species varied across ecological sites. Our results suggest consideration of soil and vegetation characteristics can inform how adaptive management is applied on a landscape to benefit the full suite of breeding grassland birds, including species that have seemingly contrasting habitat needs. For example, a manager could target adaptive drought mitigation practices, such as resting pastures for 1 yr to generate grassbanks, in less productive soils to benefit grassland birds that prefer taller/denser vegetation structure, or could apply intensive, short-duration grazing on less productive soils to benefit species preferring shorter/sparser vegetation. A single year of intensive, short-duration grazing (i.e., one component of our rotational treatment) across the landscape, however, might not create sufficient habitat for species that prefer short/sparse vegetation in our system (e.g., McCown's Longspur). Ultimately, our study indicates how cattle production on rangelands can congruently support grassland bird populations in the shortgrass steppe.

Signatures of adaptive divergence among populations of an avian species of conservation concern.

Understanding the genetic underpinning of adaptive divergence among populations is a key goal of evolutionary biology and conservation. Gunnison sage-grouse (Centrocercus minimus) is a sagebrush obligate species with a constricted range consisting of seven discrete populations, each with distinctly different habitat and climatic conditions. Though geographically close, populations have low levels of natural gene flow resulting in relatively high levels of differentiation. Here, we use 15,033 SNP loci in genomic outlier analyses, genotype-environment association analyses, and gene ontology enrichment tests to examine patterns of putatively adaptive genetic differentiation in an avian species of conservation concern. We found 411 loci within 5 kbp of 289 putative genes associated with biological functions or pathways that were overrepresented in the assemblage of outlier SNPs. The identified gene set was enriched for cytochrome P450 gene family members (CYP4V2, CYP2R1, CYP2C23B, CYP4B1) and could impact metabolism of plant secondary metabolites, a critical challenge for sagebrush obligates. Additionally, the gene set was also enriched with members potentially involved in antiviral response (DEAD box helicase gene family and SETX). Our results provide a first look at local adaption for isolated populations of a single species and suggest adaptive divergence in multiple metabolic and biochemical pathways may be occurring. This information can be useful in managing this species of conservation concern, for example, to identify unique populations to conserve, avoid translocation or release of individuals that may swamp locally adapted genetic diversity, or guide habitat restoration efforts.

Mismatches between breeding phenology and resource abundance of resident alpine ptarmigan negatively affect chick survival.

Phenological mismatches-defined here as the difference in reproductive timing of an individual relative to the availability of its food resources-occur in many avian species. Mistiming breeding activities in environments with constrained breeding windows may have severe fitness costs due to reduced opportunities for repeated breeding attempts. Therefore, species occurring in alpine environments may be particularly vulnerable.We studied fitness consequences of timing of breeding in an alpine-endemic species, the white-tailed ptarmigan (Lagopus leucura), to investigate its influence on chick survival. We estimated phenological mismatch by measuring plant and arthropods used by ptarmigan in relation to their timing of breeding.We monitored 120 nests and 67 broods over a three-year period (2013-2015) at three alpine study sites in the Rocky Mountains of Colorado. During this same period, we actively monitored food resource abundance in brood-use areas to develop year and site-specific resource phenology curves. We developed several mismatch indices from these curves that were then fit as covariates in mark-recapture chick survival models.A correlation analysis between seasonal changes in arthropod and food plant abundance indicated that a normalized difference vegetation index (NDVI) was likely the best predictor for food available to hens and chicks. A survival model that included an interaction between NDVI mismatch and chick age received strong support and indicated young chicks were more susceptible to mismatch than older chicks.We provide evidence that individual females of a resident alpine species can be negatively affected by phenological mismatch. Our study focused on individual females and did not examine if phenological mismatch was present at the population level. Future work in animal populations occurring in mountain systems focusing on a combination of both individual- and population-level metrics of mismatch will be beneficial.

Influences of potential oil and gas development and future climate on Sage-grouse declines and redistribution.

Multiple environmental stressors impact wildlife populations, but we often know little about their cumulative and combined influences on population outcomes. We generally know more about past effects than potential future impacts, and direct influences such as changes of habitat footprints than indirect, long-term responses in behavior, distribution, or abundance. Yet, an understanding of all these components is needed to plan for future landscapes that include human activities and wildlife. We developed a case study to assess how spatially explicit individual-based modeling could be used to evaluate future population outcomes of gradual landscape change from multiple stressors. For Greater Sage-grouse in southwest Wyoming, USA, we projected oil and gas development footprints and climate-induced vegetation changes 50 years into the future. Using a time-series of planned oil and gas development and predicted climate-induced changes in vegetation, we recalculated habitat selection maps to dynamically modify future habitat quantity, quality, and configuration. We simulated long-term Sage-grouse responses to habitat change by allowing individuals to adjust to shifts in habitat availability and quality. The use of spatially explicit individual-based modeling offered a useful means of evaluating delayed indirect impacts of landscape change on wildlife population outcomes. The inclusion of movement and demographic responses to oil and gas infrastructure resulted in substantive changes in distribution and abundance when cumulated over several decades and throughout the regional population. When combined, additive development and climate-induced vegetation changes reduced abundance by up to half of the original size. In our example, the consideration of only a single population stressor the final possible population size by as much as 50%. Multiple stressors and their cumulative impacts need to be broadly considered through space and time to avoid underestimating the impacts of multiple gradual changes and overestimating the ability of populations to withstand change.

Conservation Genomics in the Sagebrush Sea: Population Divergence, Demographic History, and Local Adaptation in Sage-Grouse (Centrocercus spp.).

Sage-grouse are two closely related iconic species of the North American West, with historically broad distributions across sagebrush-steppe habitat. Both species are dietary specialists on sagebrush during winter, with presumed adaptations to tolerate the high concentrations of toxic secondary metabolites that function as plant chemical defenses. Marked range contraction and declining population sizes since European settlement have motivated efforts to identify distinct population genetic variation, particularly that which might be associated with local genetic adaptation and dietary specialization of sage-grouse. We assembled a reference genome and performed whole-genome sequencing across sage-grouse from six populations, encompassing both species and including several populations on the periphery of the species ranges. Population genomic analyses reaffirmed genome-wide differentiation between greater and Gunnison sage-grouse, revealed pronounced intraspecific population structure, and highlighted important differentiation of a small isolated population of greater sage-grouse in the northwest of the range. Patterns of genome-wide differentiation were largely consistent with a hypothesized role of genetic drift due to limited gene flow among populations. Inferred ancient population demography suggested persistent declines in effective population sizes that have likely contributed to differentiation within and among species. Several genomic regions with single-nucleotide polymorphisms exhibiting extreme population differentiation were associated with candidate genes linked to metabolism of xenobiotic compounds. In vitro activity of enzymes isolated from sage-grouse livers supported a role for these genes in detoxification of sagebrush, suggesting that the observed interpopulation variation may underlie important local dietary adaptations, warranting close consideration for conservation strategies that link sage-grouse to the chemistry of local sagebrush.

Multi-model comparison highlights consistency in predicted effect of warming on a semi-arid shrub.

A number of modeling approaches have been developed to predict the impacts of climate change on species distributions, performance, and abundance. The stronger the agreement from models that represent different processes and are based on distinct and independent sources of information, the greater the confidence we can have in their predictions. Evaluating the level of confidence is particularly important when predictions are used to guide conservation or restoration decisions. We used a multi-model approach to predict climate change impacts on big sagebrush (Artemisia tridentata), the dominant plant species on roughly 43 million hectares in the western United States and a key resource for many endemic wildlife species. To evaluate the climate sensitivity of A. tridentata, we developed four predictive models, two based on empirically derived spatial and temporal relationships, and two that applied mechanistic approaches to simulate sagebrush recruitment and growth. This approach enabled us to produce an aggregate index of climate change vulnerability and uncertainty based on the level of agreement between models. Despite large differences in model structure, predictions of sagebrush response to climate change were largely consistent. Performance, as measured by change in cover, growth, or recruitment, was predicted to decrease at the warmest sites, but increase throughout the cooler portions of sagebrush's range. A sensitivity analysis indicated that sagebrush performance responds more strongly to changes in temperature than precipitation. Most of the uncertainty in model predictions reflected variation among the ecological models, raising questions about the reliability of forecasts based on a single modeling approach. Our results highlight the value of a multi-model approach in forecasting climate change impacts and uncertainties and should help land managers to maximize the value of conservation investments.

A multispecies test of source-sink indicators to prioritize habitat for declining populations.

For species at risk of decline or extinction in source-sink systems, sources are an obvious target for habitat protection actions. However, the way in which source habitats are identified and prioritized can reduce the effectiveness of conservation actions. Although sources and sinks are conceptually defined using both demographic and movement criteria, simplifications are often required in systems with limited data. To assess the conservation outcomes of alternative source metrics and resulting prioritizations, we simulated population dynamics and extinction risk for 3 endangered species. Using empirically based habitat population models, we linked habitat maps with measured site- or habitat-specific demographic conditions, movement abilities, and behaviors. We calculated source-sink metrics over a range of periods of data collection and prioritized consistently high-output sources for conservation. We then tested whether prioritized patches identified the habitats that most affected persistence by removing them and measuring the population response. Conservation decisions based on different source-sink metrics and durations of data collection affected species persistence. Shorter time series obscured the ability of metrics to identify influential habitats, particularly in temporally variable and slowly declining populations. Data-rich source-sink metrics that included both demography and movement information did not always identify the habitats with the greatest influence on extinction risk. In some declining populations, patch abundance better predicted influential habitats for short-term regional persistence. Because source-sink metrics (i.e., births minus deaths; births and immigrations minus deaths and emigration) describe net population conditions and cancel out gross population counts, they may not adequately identify influential habitats in declining populations. For many nonequilibrium populations, new metrics that maintain the counts of individual births, deaths, and movement may provide additional insight into habitats that most influence persistence.

Patterns in Greater Sage-grouse population dynamics correspond with public grazing records at broad scales.

Human land use, such as livestock grazing, can have profound yet varied effects on wildlife interacting within common ecosystems, yet our understanding of land-use effects is often generalized from short-term, local studies that may not correspond with trends at broader scales. Here we used public land records to characterize livestock grazing across Wyoming, USA, and we used Greater Sage-grouse (Centrocercus urophasianus) as a model organism to evaluate responses to livestock management. With annual counts of male Sage-grouse from 743 leks (breeding display sites) during 2004-2014, we modeled population trends in response to grazing level (represented by a relative grazing index) and timing across a gradient in vegetation productivity as measured by the Normalized Vegetation Difference Index (NDVI). We found grazing can have both positive and negative effects on Sage-grouse populations depending on the timing and level of grazing. Sage-grouse populations responded positively to higher grazing levels after peak vegetation productivity, but populations declined when similar grazing levels occurred earlier, likely reflecting the sensitivity of cool-season grasses to grazing during peak growth periods. We also found support for the hypothesis that effects of grazing management vary with local vegetation productivity. These results illustrate the importance of broad-scale analyses by revealing patterns in Sage-grouse population trends that may not be inferred from studies at finer scales, and could inform sustainable grazing management in these ecosystems.

Effects of Seasonal Weather on Breeding Phenology and Reproductive Success of Alpine Ptarmigan in Colorado.

Animal populations occurring at high elevations are often assumed to be in peril of extinctions or local extirpations due to elevational-dispersal limitations and thermoregulatory constraints as habitats change and warm. However, long-term monitoring of high-elevation populations is uncommon relative to those occurring at lower elevations, and evidence supporting this assumption is limited. We analyzed 45 years of reproductive data for two Colorado populations of white-tailed ptarmigan (Lagopus leucura), an alpine-endemic species with restricted distribution in western North America. Seasonal temperatures measured by the number of growing degree days warmed significantly at our study sites for pre-nesting, nesting, and brood-rearing seasonal periods (mean advance of 8 growing degree days per decade), and both populations advanced their reproductive phenology over the study period based on median hatch dates (median advance of 3.7 and 1.9 days per decade for the northern and southern sites, respectively). Reproductive performance measured by the number of chicks per hen declined significantly at one study site but not the other, and differences between sites may have been due to habitat degradation at one study area. Annual variability in chicks per hen was large at both sites but only weakly related to seasonal weather. An index of precipitation and temperature during the brood-rearing period was the best predictor for reproductive success with warm and dry conditions relating positively to number of chicks per hen. Our results provide evidence for two alpine ptarmigan populations that are remarkably invariant to fluctuations in seasonal weather with respect to reproductive success as measured by number of chicks per hen in the breeding population. These results are surprising given the general perception of alpine animal populations as being highly sensitive to warming temperatures.

Landscape characteristics influencing the genetic structure of greater sage-grouse within the stronghold of their range: a holistic modeling approach.

Given the significance of animal dispersal to population dynamics and geographic variability, understanding how dispersal is impacted by landscape patterns has major ecological and conservation importance. Speaking to the importance of dispersal, the use of linear mixed models to compare genetic differentiation with pairwise resistance derived from landscape resistance surfaces has presented new opportunities to disentangle the menagerie of factors behind effective dispersal across a given landscape. Here, we combine these approaches with novel resistance surface parameterization to determine how the distribution of high- and low-quality seasonal habitat and individual landscape components shape patterns of gene flow for the greater sage-grouse (Centrocercus urophasianus) across Wyoming. We found that pairwise resistance derived from the distribution of low-quality nesting and winter, but not summer, seasonal habitat had the strongest correlation with genetic differentiation. Although the patterns were not as strong as with habitat distribution, multivariate models with sagebrush cover and landscape ruggedness or forest cover and ruggedness similarly had a much stronger fit with genetic differentiation than an undifferentiated landscape. In most cases, landscape resistance surfaces transformed with 17.33-km-diameter moving windows were preferred, suggesting small-scale differences in habitat were unimportant at this large spatial extent. Despite the emergence of these overall patterns, there were differences in the selection of top models depending on the model selection criteria, suggesting research into the most appropriate criteria for landscape genetics is required. Overall, our results highlight the importance of differences in seasonal habitat preferences to patterns of gene flow and suggest the combination of habitat suitability modeling and linear mixed models with our resistance parameterization is a powerful approach to discerning the effects of landscape on gene flow.