The ties that bind the sagebrush biome: integrating genetic connectivity into range-wide conservation of greater sage-grouse.

Conserving genetic connectivity is fundamental to species persistence, yet rarely is made actionable into spatial planning for imperilled species. Climate change and habitat degradation have added urgency to embrace connectivity into networks of protected areas. Our two-step process integrates a network model with a functional connectivity model, to identify population centres important to maintaining genetic connectivity then to delineate those pathways most likely to facilitate connectivity thereamong for the greater sage-grouse (Centrocercus urophasianus), a species of conservation concern ranging across eleven western US states and into two Canadian provinces. This replicable process yielded spatial action maps, able to be prioritized by importance to maintaining range-wide genetic connectivity. We used these maps to investigate the efficacy of 3.2 million ha designated as priority areas for conservation (PACs) to encompass functional connectivity. We discovered that PACs encompassed 41.1% of cumulative functional connectivity-twice the amount of connectivity as random-and disproportionately encompassed the highest-connectivity landscapes. Comparing spatial action maps to impedances to connectivity such as cultivation and woodland expansion allows both planning for future management and tracking outcomes from past efforts.

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.

Multiscale nest-site selection of ducks in the western boreal forest of Alberta.

There is limited data regarding the nesting ecology of boreal ducks and their response to industrial development, despite this region being an important North American breeding area. We investigated how landcover and oil and gas development affect third-order nest-site selection of boreal ducks. We located duck nests in Alberta's western boreal forest between 2016 and 2018. We used multiscale analysis to identify how scale affects the selection of a resource using generalized linear mixed-effects models and determined what scale-optimized combination of landscape features were most important in describing where ducks nest. We located 136 nests of six species of upland nesting ducks between 2016 and 2018. The magnitude, direction, and best spatial scale varied by resource. For landcover, ducks selected nest-sites associated with mineral wetlands (300 m) and open water (300 m). Ducks avoided greater densities of seismic lines (300 m) and pipelines (2500 m) but selected nest-sites associated with borrow pits (300 m) and roads (1000 m). We used our models to predict important duck nesting habitat in the boreal forest, which can support conservation and management decisions. We recommend conservation actions target the conservation of mineral wetlands and associated habitats within this working landscape. Further research is necessary to understand the adaptive consequences of nest-site selection and how industrial development influences important nest predators.

Quantifying functional connectivity: The role of breeding habitat, abundance, and landscape features on range-wide gene flow in sage-grouse.

Functional connectivity, quantified using landscape genetics, can inform conservation through the identification of factors linking genetic structure to landscape mechanisms. We used breeding habitat metrics, landscape attributes, and indices of grouse abundance, to compare fit between structural connectivity and genetic differentiation within five long-established Sage-Grouse Management Zones (MZ) I-V using microsatellite genotypes from 6,844 greater sage-grouse (Centrocercus urophasianus) collected across their 10.7 million-km2 range. We estimated structural connectivity using a circuit theory-based approach where we built resistance surfaces using thresholds dividing the landscape into "habitat" and "nonhabitat" and nodes were clusters of sage-grouse leks (where feather samples were collected using noninvasive techniques). As hypothesized, MZ-specific habitat metrics were the best predictors of differentiation. To our surprise, inclusion of grouse abundance-corrected indices did not greatly improve model fit in most MZs. Functional connectivity of breeding habitat was reduced when probability of lek occurrence dropped below 0.25 (MZs I, IV) and 0.5 (II), thresholds lower than those previously identified as required for the formation of breeding leks, which suggests that individuals are willing to travel through undesirable habitat. The individual MZ landscape results suggested terrain roughness and steepness shaped functional connectivity across all MZs. Across respective MZs, sagebrush availability (<10%-30%; II, IV, V), tree canopy cover (>10%; I, II, IV), and cultivation (>25%; I, II, IV, V) each reduced movement beyond their respective thresholds. Model validations confirmed variation in predictive ability across MZs with top resistance surfaces better predicting gene flow than geographic distance alone, especially in cases of low and high differentiation among lek groups. The resultant resistance maps we produced spatially depict the strength and redundancy of range-wide gene flow and can help direct conservation actions to maintain and restore functional connectivity for sage-grouse.

Assessing the efficacy of fathead minnows (Pimephales promelas) for mosquito control.

Mosquitoes function as important vectors for many diseases globally and can have substantial negative economic, environmental, and health impacts. Specifically, West Nile virus (WNv) is a significant and increasing threat to wildlife populations and human health throughout North America. Mosquito control is an important means of controlling the spread of WNv, as the virus is primarily spread between avian and mosquito vectors. This is of particular concern for avian host species such as the Greater sage-grouse (Centrocercus urophasianus), in which WNv negatively impacts fitness parameters. Most mosquito control methods focus on the larval stages. In North America, control efforts are largely limited to larvicides, which require repeated application and have potentially negative ecological impacts. There are multiple potential advantages to using indigenous fish species as an alternative for larval control including lowered environmental impact, decreased costs in terms of time and financial inputs, and the potential for the establishment of self-sustaining fish populations. We tested the efficacy of using fathead minnows (Pimephales promelas) as biological control for mosquito populations in livestock reservoirs of semiarid rangelands. We introduced minnows into 10 treatment reservoirs and monitored an additional 6 non-treated reservoirs as controls over 3 years. Adult mosquitoes of species known to transmit WNv (e.g., Culex tarsalis) were captured at each site and mosquito larvae were also present at all sites. Stable isotope analysis confirmed that introduced fathead minnows were feeding at the mosquito larvae trophic level in all but one treatment pond. Treatment ponds demonstrated suppressed levels of mosquito larva over each season compared to controls with a model-predicted 114% decrease in larva density within treatment ponds. Minnows established self-sustaining populations throughout the study in all reservoirs that maintained sufficient water levels. Minnow survival was not influenced by water quality. Though minnows did not completely eradicate mosquito larvae, minnows are a promising alternative to controlling mosquito larvae density within reservoirs. We caution that careful site selection is critical to avoid potential negative impacts, but suggest the introduction of fathead minnows in reservoirs can dramatically reduce mosquito larva abundance and potentially help mitigate vector-borne disease transmission.

Spatial and temporal variation in the range-wide cyclic dynamics of greater sage-grouse.

Periodic changes in abundance, or population cycles, are common in a variety of species and is one of the most widely studied ecological phenomena. The strength of, and synchrony between population cycles can vary across time and space and understanding these patterns can provide insight into the mechanisms generating population cycles and their variability within and among species. Here, we used wavelet and spectral analysis on a range-wide dataset of abundance for the greater sage-grouse (Centrocercus urophasianus) to test for regional differences in temporal cyclicity. Overall, we found that most populations (11 of 15) were cyclic at some point in a 50-year time series (1965-2015), but the patterns varied over both time and space. Several peripheral populations demonstrated amplitude dampening or loss of cyclicity following population lows in the mid-1990s. Populations through the core of the range in the Great and Wyoming Basins had more consistent cyclic dynamics, but period length appeared to shorten from 10-12 to 6-8 years. In one time period, where cyclicity was greatest overall, increased pairwise population synchrony was correlated with cycle intensity. Our work represents a comprehensive range-wide assessment of cyclic dynamics and revealed substantial variation in temporal and spatial trends of cyclic dynamics across populations.

Developing approaches for linear mixed modeling in landscape genetics through landscape-directed dispersal simulations.

Dispersal can impact population dynamics and geographic variation, and thus, genetic approaches that can establish which landscape factors influence population connectivity have ecological and evolutionary importance. Mixed models that account for the error structure of pairwise datasets are increasingly used to compare models relating genetic differentiation to pairwise measures of landscape resistance. A model selection framework based on information criteria metrics or explained variance may help disentangle the ecological and landscape factors influencing genetic structure, yet there are currently no consensus for the best protocols. Here, we develop landscape-directed simulations and test a series of replicates that emulate independent empirical datasets of two species with different life history characteristics (greater sage-grouse; eastern foxsnake). We determined that in our simulated scenarios, AIC and BIC were the best model selection indices and that marginal R2 values were biased toward more complex models. The model coefficients for landscape variables generally reflected the underlying dispersal model with confidence intervals that did not overlap with zero across the entire model set. When we controlled for geographic distance, variables not in the underlying dispersal models (i.e., nontrue) typically overlapped zero. Our study helps establish methods for using linear mixed models to identify the features underlying patterns of dispersal across a variety of landscapes.

Differential influences of local subpopulations on regional diversity and differentiation for greater sage-grouse (Centrocercus urophasianus).

The distribution of spatial genetic variation across a region can shape evolutionary dynamics and impact population persistence. Local population dynamics and among-population dispersal rates are strong drivers of this spatial genetic variation, yet for many species we lack a clear understanding of how these population processes interact in space to shape within-species genetic variation. Here, we used extensive genetic and demographic data from 10 subpopulations of greater sage-grouse to parameterize a simulated approximate Bayesian computation (ABC) model and (i) test for regional differences in population density and dispersal rates for greater sage-grouse subpopulations in Wyoming, and (ii) quantify how these differences impact subpopulation regional influence on genetic variation. We found a close match between observed and simulated data under our parameterized model and strong variation in density and dispersal rates across Wyoming. Sensitivity analyses suggested that changes in dispersal (via landscape resistance) had a greater influence on regional differentiation, whereas changes in density had a greater influence on mean diversity across all subpopulations. Local subpopulations, however, varied in their regional influence on genetic variation. Decreases in the size and dispersal rates of central populations with low overall and net immigration (i.e. population sources) had the greatest negative impact on genetic variation. Overall, our results provide insight into the interactions among demography, dispersal and genetic variation and highlight the potential of ABC to disentangle the complexity of regional population dynamics and project the genetic impact of changing conditions.

Landscapes for Energy and Wildlife: Conservation Prioritization for Golden Eagles across Large Spatial Scales.

Proactive conservation planning for species requires the identification of important spatial attributes across ecologically relevant scales in a model-based framework. However, it is often difficult to develop predictive models, as the explanatory data required for model development across regional management scales is rarely available. Golden eagles are a large-ranging predator of conservation concern in the United States that may be negatively affected by wind energy development. Thus, identifying landscapes least likely to pose conflict between eagles and wind development via shared space prior to development will be critical for conserving populations in the face of imposing development. We used publically available data on golden eagle nests to generate predictive models of golden eagle nesting sites in Wyoming, USA, using a suite of environmental and anthropogenic variables. By overlaying predictive models of golden eagle nesting habitat with wind energy resource maps, we highlight areas of potential conflict among eagle nesting habitat and wind development. However, our results suggest that wind potential and the relative probability of golden eagle nesting are not necessarily spatially correlated. Indeed, the majority of our sample frame includes areas with disparate predictions between suitable nesting habitat and potential for developing wind energy resources. Map predictions cannot replace on-the-ground monitoring for potential risk of wind turbines on wildlife populations, though they provide industry and managers a useful framework to first assess potential development.

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.

The influence of mitigation on sage-grouse habitat selection within an energy development field.

Growing global energy demands ensure the continued growth of energy development. Energy development in wildlife areas can significantly impact wildlife populations. Efforts to mitigate development impacts to wildlife are on-going, but the effectiveness of such efforts is seldom monitored or assessed. Greater sage-grouse (Centrocercus urophasianus) are sensitive to energy development and likely serve as an effective umbrella species for other sagebrush-steppe obligate wildlife. We assessed the response of birds within an energy development area before and after the implementation of mitigation action. Additionally, we quantified changes in habitat distribution and abundance in pre- and post-mitigation landscapes. Sage-grouse avoidance of energy development at large spatial scales is well documented. We limited our research to directly within an energy development field in order to assess the influence of mitigation in close proximity to energy infrastructure. We used nest-location data (n = 488) within an energy development field to develop habitat selection models using logistic regression on data from 4 years of research prior to mitigation and for 4 years following the implementation of extensive mitigation efforts (e.g., decreased activity, buried powerlines). The post-mitigation habitat selection models indicated less avoidance of wells (well density ß = 0.18 ± 0.08) than the pre-mitigation models (well density ß = -0.09 ± 0.11). However, birds still avoided areas of high well density and nests were not found in areas with greater than 4 wells per km2 and the majority of nests (63%) were located in areas with ≤ 1 well per km2. Several other model coefficients differed between the two time periods and indicated stronger selection for sagebrush (pre-mitigation ß = 0.30 ± 0.09; post-mitigation ß = 0.82 ± 0.08) and less avoidance of rugged terrain (pre-mitigation ß = -0.35 ± 0.12; post-mitigation ß = -0.05 ± 0.09). Mitigation efforts implemented may be responsible for the measurable improvement in sage-grouse nesting habitats within the development area. However, we cannot reject alternative hypotheses concerning the influence of population density and intraspecific competition. Additionally, we were unable to assess the actual fitness consequences of mitigation or the source-sink dynamics of the habitats. We compared the pre-mitigation and post-mitigation models predicted as maps with habitats ranked from low to high relative probability of use (equal-area bins: 1 - 5). We found more improvement in habitat rank between the two time periods around mitigated wells compared to non-mitigated wells. Informed mitigation within energy development fields could help improve habitats within the field. We recommend that any mitigation effort include well-informed plans to monitor the effectiveness of the implemented mitigation actions that assess both habitat use and relevant fitness parameters.

Population cycles are highly correlated over long time series and large spatial scales in two unrelated species: greater sage-grouse and cottontail rabbits.

Animal species across multiple taxa demonstrate multi-annual population cycles, which have long been of interest to ecologists. Correlated population cycles between species that do not share a predator-prey relationship are particularly intriguing and challenging to explain. We investigated annual population trends of greater sage-grouse (Centrocercus urophasianus) and cottontail rabbits (Sylvilagus sp.) across Wyoming to explore the possibility of correlations between unrelated species, over multiple cycles, very large spatial areas, and relatively southern latitudes in terms of cycling species. We analyzed sage-grouse lek counts and annual hunter harvest indices from 1982 to 2007. We show that greater sage-grouse, currently listed as warranted but precluded under the US Endangered Species Act, and cottontails have highly correlated cycles (r = 0.77). We explore possible mechanistic hypotheses to explain the synchronous population cycles. Our research highlights the importance of control populations in both adaptive management and impact studies. Furthermore, we demonstrate the functional value of these indices (lek counts and hunter harvest) for tracking broad-scale fluctuations in the species. This level of highly correlated long-term cycling has not previously been documented between two non-related species, over a long time-series, very large spatial scale, and within more southern latitudes.