Geology topics

David R. Edmunds

Publications and source records attributed to David R. Edmunds.

At least 19 recordsLinked to original sources

USGS2026

Modeling chronic wasting disease transmission risk in mule deer related to habitat characteristics

Chronic wasting disease (CWD) is a prion disease of cervids that spreads to uninfected individuals through direct transmission (contact with infected individuals), vertical transmission (from mother to offspring), or indirect transmission (exposure to contaminated environments). The risk of indirect transmission is unevenly distributed on the landscape, and risk levels are expected to be controlled by patterns of habitat use by infected and uninfected individuals as well as environmental properties that alter the length of time prions remain infectious and available for uptake. Despite evidence from controlled or laboratory studies identifying environmental properties likely to affect patterns of CWD prion locations on the landscape, it remains difficult to connect mechanisms to realized increased or decreased risk of disease transmission, and few studies have attempted to detect patterns of different CWD risk in different environments. Using data from GPS-collared mule deer in Wyoming that were CWD-tested annually, we constructed models predicting annual probability of disease transmission contingent on environmental properties extracted from GPS use points. We compared models that emphasized different pathways of disease transmission by including or excluding sets of covariates that described deer density, habitat selection, and covariates expected to affect prion persistence in the environment. Results indicated that key habitat characteristics often selected by mule deer, such as proximity to secondary roads, were also associated with higher risk of testing positive for CWD, which supports the hypothesis that disease risk was correlated to patterns of habitat use by deer. We also found increased risk associated with spatial properties that were not selected-for by deer, such as areas where topography collects moisture, suggesting that prion retention mechanisms also play a role in risk. Incorporating these spatially-varying risk factors into our understanding of CWD transmission and outbreak progression can support managers in designing data collection and disease management strategies.

Wyoming↗

USGS2025

Range-wide population trend analysis for greater sage-grouse (Centrocercus urophasianus)—Updated 1960–2024

Greater sage-grouse ( Centrocercus urophasianus ; hereafter sage-grouse) are at the center of State and national land-use policies largely because of their unique life-history traits as an ecological indicator for the health of sagebrush ecosystems. This updated population trend analysis provides State and Federal land and wildlife managers with the best available science to help guide management and conservation plans aimed at benefiting sage-grouse populations and the ecosystems they inhabit. This analysis relied on previously published population trend modeling methodology from Coates and others (2021, 2022a) and incorporates population lek count data for 1960–2024. Included in this report are methodological updates to lek count data aggregation, state-space model forecasting, and targeted annual warning system signals, which are detailed under individual Modification sections. State-space models estimated a 2.9-percent average annual decline in sage-grouse populations between 1966 and 2021 (Period 1, six population oscillations) across their geographical range. The average annual decline among climate clusters for the same number of oscillations ranged between 2.2 and 3.4 percent. Cumulative declines were 41.2, 64.1, and 78.8 percent range-wide in Period 5 (19 years), Period 3 (35 years), and Period 1 (55 years), respectively.

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

USGS2025

Different data for different goals: Exploring trade-offs and synergies in the use of spatial data inputs to optimize conservation action in sagebrush ecosystems

Ecosystems worldwide continue to experience rapid rates of habitat and species loss. Management actions to conserve and restore functional habitats are needed to reduce these declines, but funding and resources for such actions are limited. Spatial conservation prioritization (SCP) can facilitate strategic decision-making for targeted conservation planning and delivery, but complexities arise when management objectives include multiple wildlife species and ecological or management constraints, all of which can be further complicated by data uncertainty and existing conservation plans. The Prioritizing Restoration of Sagebrush Ecosystems Tool (PReSET), an R package-based decision-support tool, supports strategic ecosystem management planning across the sagebrush biome by using SCP. We adapted PReSET to better address the needs of multiple wildlife species, evaluate the effects of different ecological or management constraints on conservation outcomes, assess the influence of data uncertainty, and integrate existing conservation plans. Specifically, we developed optimization problems to identify priority sagebrush protection and restoration across the state of Wyoming, USA, and evaluated the efficacy and trade-offs of various approaches to problem design. We evaluated trade-offs in targeting multiple species compared to a single species, including using greater sage-grouse as a potential umbrella species to benefit other sagebrush-dependent wildlife. We then evaluated multi-species protection and restoration problems aimed at minimizing the risks of inadequate connectivity, climate change, and restoration failure, and accounted for data uncertainty to assess relationships between risk aversion of managers and conservation outcomes. We also developed optimization problems within conservation areas identified by an existing sagebrush conservation plan to evaluate the efficacy of guiding local-scale conservation delivery within more broadly defined conservation areas. Our results demonstrate how SCP methods can leverage novel spatial data to develop targeted decision-support resources that can facilitate landscape conservation planning and improve management outcomes across a wide array of systems and species.

Wyoming↗

USGS2024

Range-wide population trend analysis for greater sage-grouse (Centrocercus urophasianus)—Updated 1960–2023

Greater sage-grouse ( Centrocercus urophasianus ) are at the center of state and national land-use policies largely because of their unique life-history traits as an ecological indicator for health of sagebrush ecosystems. This updated population trend analysis provides state and federal land and wildlife managers with best-available science to help guide management and conservation plans aimed at benefitting sage-grouse populations. This analysis relied on previously published population trend modeling methodology from Coates and others (2021, 2022a) and incorporates population lek count data for 1960–2023. Included in this update are changes in terminology. Specifically, we now use the terms Period 1 (previously Long), Period 2 (previously Medium/Long), Period 3 (previously Medium), Period 4 (previously Short/Medium), Period 5 (previously Short), and Period 6 (previously Recent) to identify specific trends. State-space models estimated 2.8-percent average annual decline in sage-grouse populations between 1966 and 2021 (Period 1, six population oscillations) across their geographical range. Average annual decline among climate clusters for the same number of oscillations ranged between 2.1 and 3.1 percent. Cumulative declines were 41.1, 64.5, and 78.4 percent range-wide during Period 5 (19 years), Period 3 (35 years), and Period 1 (55 years), respectively. Population growth during 2022 and 2023 continue to point to 2021 as the most recent range-wide nadir.

Data Report↗

USGS2024

Estimating traffic volume and road age in Wyoming to inform resource management planning: An application with wildlife-vehicle collisions

Road networks and their associated vehicular traffic disturb many terrestrial systems, but inventories of roads used to assess these effects often focus on the ‘where’ (e.g., local road type and density) and neglect the ‘when’ (e.g., temporal disturbance) or ‘how much’ (e.g., traffic volume disturbance). We developed annual estimates of the ‘when’ (road age) and ‘how much’ (vehicular traffic volume) across 148,172 km of highways, arterials, collectors, local, and gravel/graded roads within the state of Wyoming for the years 1986 to 2020 to provide a comprehensive dataset for future ecological investigations. We leveraged a suite of ancillary data on surface disturbances (e.g., oil & gas drilling operations, wind turbines, and open pit mines) with known establishment dates and combined them using graph theory and centrality metrics to estimate the age of each road. We then predicted traffic volume obtained from the Wyoming Department of Transportation for each year across Wyoming using a machine learning method, XGBoost, and a separate set of spatial covariates hypothesized to explain traffic patterns across large regions. We found that 132,476 km of these roads likely existed before 1986, but that 16,693 km (10.7 %) of roads have been built since 1986. Overall, our estimates of road age were 89 % accurate when assessed on a subset of 1,330 roads with high-resolution aerial imagery. Mean absolute error for predicting traffic volume ranged from 35.2 to 77.9 annual average daily traffic (aadt) for trucks and 269.2 to 516.7 aadt for all-vehicles across the 35 years. We found that mean traffic volume across the state increased by 23 % for both truck-only traffic and all vehicular traffic from 1986 to 2020. However, changes in traffic volume have varied substantially across the state (e.g., 100 % increases in volume in some areas, while other areas experienced declines of up to 1,786 %). We also illustrate a novel application of these data by predicting rates of reported wildlife-vehicle collisions (WVCs) along a subset of roads. We found evidence of a non-linear relationship that supported a threshold hypothesis for WVCs, wherein increases in traffic volume equate to increases in WVCs up to a threshold, above which increases in traffic volume result in declines in WVCs. The data provided here will enable better-informed studies of road ecology to address how roads may affect wildlife populations and key ecosystems across Wyoming.

Wyoming↗

USGS2023

PopEquus: a predictive modeling tool to support management decisions for free-roaming horse populations

Feral horse ( Equus caballus ) population management is a challenging problem around the world because populations often exhibit density-independent growth, can exert negative ecological effects on ecosystems, and require great cost to be managed. However, strong value-based connections between people and horses cause contention around management decisions. To help make informed decisions, natural resource managers might benefit from more detailed understanding of how horse management alternatives, including combinations of removals and fertility control methods, could achieve objectives of sustainable, multiple-use ecosystems while minimizing overall horse handling and fiscal costs. Here, we describe a modeling tool that simulates horse management alternatives and estimates trade-offs in predicted metrics related to population size, animal handling, and direct costs of management. The model considers six management actions for populations (removals for adoption or long-term holding; fertility control treatment with three vaccines, intrauterine devices, and mare sterilization), used alone or in combination. We simulated 19 alternative management scenarios at 2-, 3-, and 4-year management return intervals and identified efficiency frontiers among alternatives for trade-offs between predicted population size and six management metrics. Our analysis identified multiple alternatives that could maintain populations within target population size ranges, but some alternatives (e.g., removal and mare sterilization, removal and GonaCon treatment) performed better at minimizing overall animal handling requirements and management costs. Cost savings increased under alternatives with more effective, longer lasting fertility control techniques over longer management intervals compared with alternatives with less-effective, shorter lasting fertility control techniques. We built a user-friendly website application, PopEquus , that decision makers and interested individuals can use to simulate management alternatives and evaluate trade-offs among management and cost metrics. Our results and website application provide quantitative trade-off tools for horse population management decisions and can help support value-based management decisions for wild or feral horse populations and ecosystems at local and regional scales around the world.

Ecosphere↗

USGS2023

Range-wide population trend analysis for greater sage-grouse (Centrocercus urophasianus)—Updated 1960–2022

Greater sage-grouse ( Centrocercus urophasianus ) are at the center of state and national land-use policies largely because of their unique life-history traits as an ecological indicator for health of sagebrush ecosystems. This updated population trend analysis provides state and federal land and wildlife managers with best-available science to help guide current management and conservation plans aimed at benefitting sage-grouse populations. This analysis relied on previously published population trend modeling methodology from Coates and others (2021, 2022a) and incorporated population lek count data through 2022. Bayesian state-space models estimated 2.9 percent average annual decline in sage-grouse populations across their geographical range, which varied among subpopulations at the largest scale of analysis, termed climate clusters (2.2–4.7). Cumulative declines were 40.9, 65.0, and 79.6 percent range-wide across short (19 years), medium (35 years), and long (55 years) temporal periods, respectively. These results indicate that the most recent nadir for range-wide populations occurred during 2021. However, growth during 2022 was modest, making 2021 a tentative final nadir at this point.

Data Report↗

USGS2023

Using neutral landscape models to evaluate the umbrella species concept in an ecotone

Context Steep declines in North American rangeland biodiversity have prompted researchers and managers to use umbrella species as a tool to manage diverse suites of co-occurring wildlife, but efficacy of this method has been variable. Evaluation of prairie and shrubland grouse as umbrellas is typically restricted to observed overlap between umbrella and background species, but this approach does not distinguish between overlap due to ubiquity or niche overlap. Objectives We demonstrate a novel application of neutral landscape models (NLMs) to test the effectiveness of greater sage-grouse ( Centrocercus urophasianus ) as an umbrella species for grassland songbirds at a grassland-sagebrush ecotone in northeastern Wyoming, USA. Methods We leveraged existing spatial data representing sage-grouse habitat in two distinct seasons (nesting and late brood-rearing) and density and distribution of eight grassland songbirds. We applied a permutation-based analysis using NLMs to determine whether overlap between background species and greater sage-grouse was greater than expected by chance. Results Three species (western meadowlark Sturnella neglecta , loggerhead shrike Lanius ludovicianus , and lark bunting Calamospiza melanocorys ) had greater overlap than expected with at least one type of greater sage-grouse habitat, while western kingbirds ( Tyrannus verticalis ) indicated avoidance of all sage-grouse habitat assessed. Conclusions NLMs provided a more nuanced evaluation of the umbrella species concept than previously available and allowed us to differentiate between overlap due to ubiquity (e.g., vesper sparrow; Pooecetes gramineus ) rather than overlap in habitat use. All grassland passerine species with greater than expected overlap with sage-grouse habitat either nest in sagebrush (loggerhead shrike) or often select nest locations underneath small shrubs (western meadowlark, lark bunting). These results indicate that nesting substrate is a potential niche axis to consider when evaluating the umbrella species concept, especially within sagebrush-grassland ecotones.

Wyoming↗

USGS2023

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.

Ecological Applications↗

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↗

USGS2022

Range-wide population trend analysis for greater sage-grouse (Centrocercus urophasianus)—Updated 1960–2021

Greater sage-grouse ( Centrocercus urophasianus ) are at the center of state and national land use policies largely because of their unique life-history traits as an ecological indicator for health of sagebrush ecosystems. This updated population trend analysis provides state and federal land and wildlife managers with best-available science to help guide current management and conservation plans aimed at benefitting sage-grouse populations. This analysis relied on previously published population trend modeling methodology from Coates and others (2021) and includes the addition of three analytical updates: (1) identification of population nadirs (lowest points within cycles) at the lek (breeding ground) and neighborhood cluster (group of leks) spatial scales, (2) truncation of prior distributions on rate of change in apparent abundance values to more realistic boundaries for leks with missing data, and (3) addition of 2 years of population lek count data (2020 and 2021) to the current dataset (1953–2021). Bayesian state-space models estimated 2.9 percent average annual decline in sage-grouse populations across their geographical range, which varied among subpopulations at the largest scale of analysis, termed climate clusters (2.2–4.6). Cumulative declines were 42.5, 65.6, and 80.1 percent range-wide across short (19 years), medium (35 years), and long (55 years) temporal periods, respectively. These results indicate that range-wide populations continued to decline during 2020 and 2021, although two climate clusters (eastern area and Bi-State area) have shown growth in population abundance in recent years, indicating they have surpassed a recent population abundance nadir.

Data Report↗

USGS2022

Spatial scale selection for informing species conservation in a changing landscape

Identifying the relevant spatial scale at which species respond to features in a landscape (scale of effect) is a pressing research need as managers work to reduce biodiversity loss amid a variety of environmental challenges. Until recently, researchers often evaluated a subset of potential scales of effect inferred from previous studies in other locations, often based on different biological responses and environmental variables. These approaches, however, can create uncertainty as to whether relevant spatial scales were identified, and whether the effects of environmental variables at scale were accurately estimated. Identifying scales of effect is particularly relevant for the greater sage-grouse ( Centrocercus urophasianus ), a sagebrush-obligate species of conservation concern requiring large areas of intact sagebrush cover ( Artemisia spp.) for habitat. We demonstrate the application of a scale selection approach that jointly estimates the scale of effect and the effect of sagebrush cover on trends in population size using counts from 584 sage-grouse leks in southwestern Wyoming (2003–2019) and annual estimates of sagebrush cover from a remote sensing product. From this approach, we estimated a positive effect of mean sagebrush cover with a 95% probability that the scale of effect occurred within 5.02 km of leks. In an average year, we found that lower levels of sagebrush cover within these estimated scales could support increasing trends in sage-grouse population size when populations were small, but higher levels of sagebrush cover were needed to sustain growing populations when populations were larger. With standardized monitoring and annual estimates of vegetation from remote sensing, this scale selection approach can be applied to identify relevant scales for other populations, species, and biological responses such as demography and movement.

Wyoming↗

USGS2022

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.

Ecology and Evolution↗

USGS2022

Defining fine-scaled population structure among continuously distributed populations

Understanding wildlife population structure and connectivity can help managers identify conservation strategies, as structure can facilitate the study of population changes and habitat connectivity can provide information on dispersal and biodiversity. To facilitate the use of wildlife monitoring data for improved adaptive management, we developed a novel approach to define hierarchical tiers (multiple scales) of population structure. We defined population structure by combining graph theory with biological inference about dispersal capability (based on movement, gene flow, and habitat condition) and functional processes affecting movement (e.g. habitat selection across scales of landscape preferences). First, we developed least-cost paths between high fidelity sites (habitat patches) using a cost surface, informed from functional processes of habitat characteristics to account for resistance of inter-patch movements. Second, we combined the paths into a multi-path graph construct. Third, we used information on potential connectivity (dispersal distances) and functional connectivity (permeability of fragmented landscapes based on selection preferences) to decompose the graph into hierarchical tiers of connected subpopulations, denoting the degree that dispersal affected population structure. As a case study, we applied our approach across the greater sage-grouse ( Centrocercus urophasianus ) range, a species of conservation concern in western United States. We described the relative importance of local populations and where to potentially avoid landscape disturbances that may negatively affect population connectivity using centrality measures supported by graph theory, and we demonstrated close alignment of the resulting population structure with population densities. This method can be adapted for other species with site fidelity and used as a management tool to evaluate population trends and responses to landscape changes across different temporal and spatial scales.

Methods in Ecology and Evolution↗

USGS2021

U.S. Geological Survey science for the Wyoming Landscape Conservation Initiative—2018 annual report

The Wyoming Landscape Conservation Initiative (WLCI) was established in 2007 as a collaborative interagency partnership to develop and implement science-based conservation actions. During the past 11 years, partners from U.S. Geological Survey (USGS), State and Federal land management agencies, universities, and the public have collaborated to implement a long-term (more than 10 years) science-based program that assesses and enhances the quality and quantity of wildlife habitats in the southwest Wyoming region while facilitating responsible development. The USGS WLCI Science Team completes scientific research and develops tools that inform and support WLCI partner planning, decision making, and on-the-ground management actions. In fiscal year 2018, the USGS initiated 3 new projects and continued efforts on 21 ongoing science and web-development projects. The first new project was initiated to support Secretarial Order 3362 which calls on the USGS to assist Western States in mapping big-game migration corridors and developing new mapping tools. During 2018, the USGS hosted a workshop in Laramie, Wyoming, which included more than 70 State and Federal wildlife experts from Colorado, New Mexico, Texas, and Wyoming. Most of the mapping and migration tool curricula used in the workshop were derived from prior WLCI studies and mapping efforts of big-game migration movement in habitats undergoing large-scale energy development. The second new project was in response for WLCI partners to better understand sedimentation and hydrogeomorphic processes in a cold-desert headwater and the third new project was designed to improve our approach for people to access, manage, and analyze WLCI data and WLCI resource information. The USGS published 18 products (including peer-reviewed journal articles, USGS series publications, and data releases) and provided more than a dozen professional oral and poster presentations at scientific meetings and numerous informal presentations to WLCI partners at meetings and workshops. This report summarizes the objectives and status of each project and highlights the USGS 2018 accomplishments and products.

Wyoming↗

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↗

USGS2021

Prioritizing landscapes for grassland bird conservation with hierarchical community models

Context Given widespread population declines of birds breeding in North American grasslands, management that sustains wildlife while supporting rancher livelihoods is needed. However, management effects vary across landscapes, and identifying areas with the greatest potential bird response to conservation is a pressing research need. Objectives We developed a hierarchical modeling approach to study grassland bird response to habitat factors at multiple scales and levels. We then identified areas to prioritize for implementing a bird-friendly ranching program. Methods Using bird survey data from grassland passerine species and 175 sites (2009–2018) across northeast Wyoming, USA, we fit hierarchical community distance sampling models and evaluated drivers of site-level density and regional-level distribution. We then created spatially-explicit predictions of bird density and distribution for the study area and predicted outcomes from pasture-scale management scenarios. Results Cumulative overlap of species distributions revealed areas with greater potential community response to management. Within each species’ potential regional-level distribution, the grassland bird community generally responded negatively to cropland cover and vegetation productivity at local scales (up to 10 km of survey sites). Multiple species declined with increasing bare ground and litter cover, shrub cover, and grass height measured within sites. Conclusions We demonstrated a novel approach to multi-scale and multi-level prioritization for grassland bird conservation based on hierarchical community models and extensive population monitoring. Pasture-scale management scenarios also suggested the examined community may benefit from less bare ground cover and shorter grass height. Our approach could be extended to other bird guilds in this region and beyond.

Wyoming↗