Geology topics

Gregory T. Wann

Publications and source records attributed to Gregory T. Wann.

13 recordsLinked to original sources

USGS2025

Greater sage-grouse seasonal habitat associations: A review and considerations for interpretation and management applications

Habitat features needed by wildlife can change in composition throughout the year, particularly in temperate ecosystems, leading to distinct seasonal spatial-use patterns. Studies of species-habitat associations therefore often focus on understanding relationships within discrete seasonal periods with common goals of prediction (e.g., habitat mapping) and inference (e.g., interpreting model coefficients). Across the range of the greater sage-grouse ( Centrocercus urophasianus ) of western North America, the increasing use of high-frequency tracking devices has led to a surge in habitat association studies covering multiple temporal periods and spatial extents. We reviewed the literature for seasonal habitat association studies corresponding to the second and third orders of selection (Johnson 1980). Our objectives were to summarize the methodological approaches used to estimate habitat associations to aid understanding in cross-study comparisons and identify common habitat features reported as selected or avoided within different seasonal periods. We reviewed 71 second- and third-order studies published from 2007–2023 that evaluated covariates collected in a geographic information system (GIS) and modeled probability of selection or intensity of use. The most common study design evaluated a single level of selection (third-order) and was multi-scale (i.e., covariates were measured at varying spatial grains). The most common model approach estimated habitat associations using resource selection functions (RSFs) fit with logistic regression. Studies mostly focused on the breeding periods and winter, but all seasons throughout the annual cycle were covered. There was clear support for selection of sagebrush and avoidance of trees and rugged terrain across seasons, and strong selection of mesic conditions in summer. However, habitat associations for most covariates were mixed, with proportionally equivalent selection and avoidance reported, even within the same seasons. Different factors hampered cross-study comparisons, including variation in study design, but additional contributors likely included important context-dependent habitat associations, such as functional responses to changing habitat availability. We suggest collaborative studies leveraging multiple datasets can help improve seasonal habitat inference by removing the effects of variable study designs.

Journal of Wildlife Management↗

USGS2025

A compilation pipeline for wildlife tracking datasets collected from ground-based and satellite-based telemetry transmission devices

Wildlife conservation planning increasingly requires collaboration and integration of research from discrete studies spanning large geographic areas. Tracking datasets are essential for analyzing animal movements and species distributions in relation to environmental conditions and combining them can enable powerful analyses to further aid planning efforts. However, combining datasets necessitates addressing variation in study designs, tracking methodologies, location uncertainty, and data attributes. We outline a compilation pipeline to integrate ground-based and satellite-based telemetry tracking datasets, motivated from our work with greater sage-grouse ( Centrocercus urophasianus ), a highly imperiled species of western North America. Our objective was to create a database with a standardized set of attributes to facilitate filtering locations for spatial analyses. Our pipeline phases are: (1) dataset pre-processing, (2) formatting individual datasets to a common template, (3) dataset binding, (4) error checking, and (5) filtering. Our pipeline includes additional functionality to identify coordinates from recurrently visited locations (e.g., nest sites), which may be of special interest. The final compiled sage-grouse database included nearly 5 million locations collected from 53 datasets and over 19,000 birds tracked from 1980 to 2022, including over 11,000 nest locations. Our error checks flagged 3.9 % of locations as likely errors, predominantly collected from satellite-based telemetry transmissions. We demonstrate the ability of our pipeline to identify nest locations and flag erroneous locations by applying it to simulated tracking datasets. Overall, our workflow offers a transferable approach for researchers aiming to standardize wildlife telemetry datasets and conduct ecological analyses for both individual studies and large-scale collaborations.

California, Colorado, Idaho, Montana, Nevada, Nort↗

USGS2024

Estimates of Southern White-tailed Ptarmigan daily nest survival from multiple sites in the Southern Rocky Mountains of Colorado

Estimating vital rates of avian species is important to understand population dynamics and develop potential conservation strategies that target rates for management. Avian species have reduced potential for high annual fecundity in alpine ecosystems due to a short breeding window and harsh weather conditions. We located nests from Southern White-tailed Ptarmigan ( Lagopus leucura altipetens ) across six study sites in the Southern Rocky Mountains of Colorado to estimate daily nest survival from 2013–2017. We used a known-fate hierarchical nest survival model and fit several covariates, including environmental conditions representing daily weather events and shrub cover, to describe variation in daily survival and derive estimates of nest success. We located and monitored 198 nests from 128 radio-marked ptarmigan hens. The mean nest success estimated as a derived parameter from daily nest survival was 45.6% (95% credible interval [CI]: 31.2–59.6%) and ranged from 40.3% to 50.3% across sites. Variation in daily nest survival was poorly described by the covariates we fit (95% CI of most slope coefficients overlapped 0), although there was some support for a negative effect of relative elevation (nests at lower elevations within a site survived at higher rates) and a positive effect of nest age (older nests survived at higher rates). We examined how variation in nest success was likely to influence the finite rate of population growth using a simple simulation with an age-transition matrix parameterized with previously reported fecundity and survival estimates. We found that the finite growth rate was predicted to increase 18.7% when evaluated from the lower to upper 95% CI estimated values of nest success, conditional on the other vital rates used in our simulation. We discuss the broader implications of these findings in the context of managing for nest survival of Southern White-tailed Ptarmigan.

Colorado↗

USGS2023

A targeted annual warning system developed for the conservation of a sagebrush indicator species

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.

Ecological Indicators↗

USGS2023

A regionally varying habitat model to inform management for greater sage-grouse persistence across their range

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.

Global Ecology and Conservation↗

USGS2021

Range-wide greater sage-grouse hierarchical monitoring framework—Implications for defining population boundaries, trend estimation, and a targeted annual warning system

Incorporating spatial and temporal scales into greater sage-grouse ( Centrocercus urophasianus ) population monitoring strategies is challenging and rarely implemented. Sage-grouse populations experience fluctuations in abundance that lead to temporal oscillations, making trend estimation difficult. Accounting for stochasticity is critical to reliably estimate population trends and investigate variation related to deterministic factors on the landscape, which are amenable to management action. Here, we describe a novel, range-wide hierarchical monitoring framework for sage-grouse centered on four objectives: (1) create a standardized database of lek counts, (2) develop spatial population structures by clustering leks, (3) estimate spatial trends at different temporal extents based on abundance nadirs (troughs), and (4) develop a targeted annual warning system to help inform management decisions. Using automated and repeatable methods (software), we compiled a lek database (as of 2019) that contained 262,744 counts and 8,421 unique lek locations from disparate state data. The hierarchical population units (clusters) included 13 nested levels, identifying biologically relevant units and population structure that minimized inter-cluster sage-grouse movements. With these products, we identified spatiotemporal variation in trends in population abundance using Bayesian state-space models. We estimated 37.0, 65.2, and 80.7-percent declines in abundance range-wide during short (17 years), medium (33 years), and long (53 years) temporal scales, respectively. However, some areas exhibited evidence of increasing trends in abundance in recent decades. Models predicted 12.3, 19.2, and 29.6 percent of populations (defined as clusters of neighboring leks) consisted of over 50-percent probability of extirpation at 19, 38, and 56-year projections from 2019, respectively, based on averaged annual rate of change in apparent abundance across two, four, and six oscillations (average period of oscillation is 9.4 years). At the lek level, models predicted 45.7, 60.1, and 78.0 percent of leks with over 50-percent extirpation probabilities over the same time periods, respectively, mostly located on the periphery of the species’ range. The targeted annual warning system automates annual identification of local populations exhibiting asynchronous decline relative to regional population patterns using simulated management actions and an optimization algorithm for evaluating range-wide stabilization of population abundance. In 2019, approximately 3.2 percent of leks and 2.0 percent of populations were identified by the targeted annual warning system for management intervention range-wide.

California, Colorado, Idaho, Montana, Nevada, Nort↗

USGS2019

The importance of simulation assumptions when evaluating detectability in population models

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 (lambda) 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 lambda, and conclusions regarding effort may be overoptimistic. Here, we used global positioning system (GPS) 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 lambda 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 lambda 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 lambda whereas N-mixture models estimated lambda 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.

Ecosphere↗

USGS2019

Assessing lek attendance of male greater sage‐grouse using fine‐resolution GPS data: Implications for population monitoring of lek mating grouse

Counts of males displaying on breeding grounds are the primary management tool used to assess population trends in lekking grouse species. Despite the importance of male lek attendance (i.e., proportion of males on leks available for detection) influencing lek counts, patterns of within season and between season variability in attendance rates are not well understood. We used high‐frequency global positioning system (GPS) telemetry data from male greater sage‐grouse ( Centrocercus urophasianus; n = 67) over five lekking seasons (2013–2017) at eight study sites in Nevada to estimate lek attendance rates. Specifically, we recorded daily locations of sage‐grouse in relation to mapped lek boundaries and used generalized additive models to assess temporal variation in attendance rates by age class (subadult vs. adult). Average timing of peak attendance occurred on 16 April but varied from March 16, 2014 to April 21 , 2016. Overall, adult males attended leks at higher rates (0.683 at peak) and earlier in the season (19 March) than subadults (0.421 at peak on April 19). Peak attendance probability was positively related to cumulative winter precipitation. Daily probabilities of lek switching differed between adults (0.019 at peak on March 3) and subadults (0.046 at peak on March 22), and lek switching was negatively related to distance to nearest lek. Our results indicate variable patterns in lek attendance through time, and that lek switching may occur at higher rates than previously thought. We demonstrate the use of generalizable daily attendance curves to date‐correct lek counts and derive estimates of male abundance, although such an approach will likely require the incorporation of information on age structure to produce robust results that are useful for population monitoring.

Nevada↗

USGS2019

Estimating sightability of greater sage-grouse at leks using an aerial infrared system and N-mixture models

Counts of grouse present at leks (breeding grounds) during spring are widely used to monitor population numbers and assess trends. However, only a proportion of birds available to count are detected resulting in a biased population index. We designed a study using an aerial integrated infrared imaging system (AIRIS) and experimental pseudo-leks to quantify sightability (proportion of birds detected) of conventional ground-based visual (GBV) surveys for greater sage-grouse Centrocercus urophasianus . Specifically, we calibrated AIRIS at pseudo-leks composed of known numbers of captively-raised birds, primarily ring-necked pheasant Phasianus colchicus . We then carried out AIRIS and GBV surveys, simultaneously, on nearby sage-grouse leks, allowing us to model AIRIS and GBV sightability. AIRIS detected ∼93% of birds on pseudo-leks while GBV detected ∼86% of sage-grouse on leks. Thus, the ground count observation error was –14% from the ‘true' number of male sage-grouse attending the leks. We also found sagebrush cover decreased sightability for GBV counts but did not influence sightability by AIRIS. Because standard GBV protocols typically make repeated counts of sage-grouse in a single morning, we also modeled repeated GBV counts using N -mixture models and found an 88% sightability, which was nearly the same as GBV sightability from the AIRIS analysis. This suggests that the use of repeated morning counts can potentially account for imperfect detection in the standard GBV surveys currently implemented. We also provide generalized correction values that could be employed by resource managers using either GBV or AIRIS to better estimate ‘true’ numbers of sage-grouse attending leks within similar environments to this study. The findings and interpretation presented can help guide effective monitoring protocols that account for observation error and improve accuracy of data used for population trend and abundance estimation.

California, Idaho, Nevada↗

USGS2017

Hierarchical population monitoring of greater sage-grouse ( Centrocercus urophasianus ) in Nevada and California—Identifying populations for management at the appropriate spatial scale

Population ecologists have long recognized the importance of ecological scale in understanding processes that guide observed demographic patterns for wildlife species. However, directly incorporating spatial and temporal scale into monitoring strategies that detect whether trajectories are driven by local or regional factors is challenging and rarely implemented. Identifying the appropriate scale is critical to the development of management actions that can attenuate or reverse population declines. We describe a novel example of a monitoring framework for estimating annual rates of population change for greater sage-grouse ( Centrocercus urophasianus ) within a hierarchical and spatially nested structure. Specifically, we conducted Bayesian analyses on a 17-year dataset (2000–2016) of lek counts in Nevada and northeastern California to estimate annual rates of population change, and compared trends across nested spatial scales. We identified leks and larger scale populations in immediate need of management, based on the occurrence of two criteria: (1) crossing of a destabilizing threshold designed to identify significant rates of population decline at a particular nested scale; and (2) crossing of decoupling thresholds designed to identify rates of population decline at smaller scales that decouple from rates of population change at a larger spatial scale. This approach establishes how declines affected by local disturbances can be separated from those operating at larger scales (for example, broad-scale wildfire and region-wide drought). Given the threshold output from our analysis, this adaptive management framework can be implemented readily and annually to facilitate responsive and effective actions for sage-grouse populations in the Great Basin. The rules of the framework can also be modified to identify populations responding positively to management action or demonstrating strong resilience to disturbance. Similar hierarchical approaches might be beneficial for other species occupying landscapes with heterogeneous disturbance and climatic regimes.

California, Nevada↗

USGS2016

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.

Colorado↗

USGS2014

Estimates of annual survival, growth, and recruitment of a white-tailed ptarmigan population in Colorado over 43 years

Long-term datasets for high-elevation species are rare, and considerable uncertainty exists in understanding how high-elevation populations have responded to recent climate warming. We present estimates of demographic vital rates from a 43-year population study of white-tailed ptarmigan ( Lagopus leucura ), a species endemic to alpine habitats in western North America. We used capture-recapture models to estimate annual rates of apparent survival, population growth, and recruitment for breeding-age ptarmigan, and we fit winter weather covariates to models in an attempt to explain annual variation. There were no trends in survival over the study period but there was strong support for age and sex effects. The average rate of annual growth suggests a relatively stable breeding-age population ( λ ¯ "> λ ¯ = 1.036), but there was considerable variation between years for both population growth and recruitment rates. Winter weather covariates only explained a small amount of variation in female survival and were not an important predictor of male survival. Cumulative winter precipitation was found to have a quadratic effect on female survival, with survival being highest during years of average precipitation. Cumulative winter precipitation was positively correlated with population growth and recruitment rates, although this covariate only explained a small amount of annual variation in these rates and there was considerable uncertainty among the models tested. Our results provide evidence for an alpine-endemic population that has not experienced extirpation or drastic declines. However, more information is needed to understand risks and vulnerabilities of warming effects on juveniles as our analysis was confined to determination of vital rates for breeding-age birds.

Colorado↗

USGS2011

Effects of climate change on nutrition and genetics of White-tailed Ptarmigan

White-tailed Ptarmigan ( Lagopus leucura ) are well suited as a focal species for the study of climate change because they are adapted to cool, alpine environments that are expected to undergo unusually rapid climate change. We compared samples collected in the late 1930s, the late 1960s, and the late 2000s using molecular genetic and stable isotope methods in an effort to determine whether White-tailed Ptarmigan on Mt. Evans, Colorado, have experiences recent environmental changes resulting in shifts in genetic diversity, gene frequency, and nutritional ecology. We genotyped 115 individuals spanning the three time periods, using nine polymorphic microsatellite loci in our genetic analysis. These samples were also analyzed for stable carbon and nitrogen isotopic composition. We found a slight trend of lower heterozygosity through time, and allelic richness values were significantly lower in more recent times, but not significantly using an alpha of 0.05 ( P < 0.1). We found no changes in allele frequencies across time periods, suggesting that population sizes have not changed dramatically. Feather δ 13 C and δ 15 N values decreased significantly across time periods, whereas the range in isotope values increased consistently from the late 1930s to the late time periods. Inferred changes in the nutritional ecology of White-tailed Ptarmigan on Mt. Evans relate primarily to increased atmospheric deposition of nutrients that likely influenced foraging habits and tundra plant composition and nutritional quality. Future work seeks to integrate genetic and isotopic data with long-term demographics to develop a detailed understanding of the interaction among environmental stressors on the long-term viability of ptarmigan populations.

Studies in Avian Biology↗