Geology topics

Cameron L. Aldridge

Publications and source records attributed to Cameron L. Aldridge.

At least 73 records · Page 4Linked to original sources

USGS2022

A user guide to selecting invasive annual grass spatial products for the western United States

Invasive annual grasses (IAGs)—including Bromus tectorum (cheatgrass), Taeniatherum caput-medusae (medusahead), and Ventenata dubia (ventenata) species—present significant challenges for rangeland management by altering plant communities, impacting ecosystem function, reducing forage for wildlife and livestock, and increasing fire risk. Numerous spatial data products are used to map IAGs, and understanding the similarities, differences, and potential tradeoffs among these products is key to selecting the right maps for specific applications. This short guide outlines considerations for selecting regional- and national-scale spatial data to support the management of IAGs.

western United States↗

USGS2022

Assessing vegetation recovery from energy development using a dynamic reference approach

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

Wyoming↗

USGS2022

Balancing model generality and specificity in management-focused habitat selection models for Gunnison sage-grouse

Identifying, protecting, and restoring habitats for declining wildlife populations is foundational to conservation and recovery planning for any species at risk of decline. Resource selection analysis is a key tool to assess habitat and prescribe management actions. Yet, it can be challenging to map suitable resource conditions across a wide range of ecological contexts and use the resulting models to identify effective and universal habitat improvement actions. We developed a management-centric modeling approach that sought to balance the need to evaluate the consistency of key habitat conditions and improvement actions across multiple, distinct populations, while allowing context-specific environmental variables and spatial scales to nuance selection responses that form the basis of location-specific management prescriptions. To demonstrate this approach, we developed a set of habitat selection models for Gunnison sage-grouse ( Centrocercus minimus ), a threatened species under the U.S. Endangered Species Act. Conservation, species recovery, and habitat management efforts are needed in six isolated satellite populations (San Miguel, Crawford, Piñon Mesa, Dove Creek, Cerro Summit-Cimarron-Sims, and Poncha Pass) where environmental conditions differ, and the already small number of birds are declining. We used multi-scale and seasonal resource selection analyses to quantify relationships between environmental conditions and sites used by animals. All models included key habitat variables often altered through management actions to assess their differential influences across models. We found important similarities and differences among satellites, indicating that, although some rules of thumb are generally well-grounded, the consideration of population-specific environmental differences could increase the efficiency of local habitat improvement actions. Sage-grouse also had diverse responses to resource conditions at different scales, indicating that regional spatial (e.g., landscape) and local patch scale can differentially influence expected habitat improvements associated with where such management actions are implemented. Although context variables such as topography cannot be manipulated, sage-grouse associations revealed information that could guide the siting of improvement actions. This approach to balancing management objectives associated with habitat assessment may benefit spatially-structured populations with different environmental contexts and species with complex habitat needs and associations.

Colorado↗

USGS2022

Bridging the gap between spatial modeling and management of invasive annual grasses in the imperiled sagebrush biome

Invasions of native plant communities by non-native species present major challenges for ecosystem management and conservation. Invasive annual grasses such as cheatgrass, medusahead, and ventenata are pervasive and continue to expand their distributions across imperiled sagebrush-steppe communities of the western United States. These invasive grasses alter native plant communities, ecosystem function, and fire regimes, threatening sagebrush ecosystem persistence. Spatial data describing the distribution and abundance of invasive species are often used by resource managers to identify, target, and determine needed interventions. However, there are challenges associated with translating these datasets into management actions. We conducted a review of available spatial products to assess advances in, and barriers to, applying contemporary model-based maps to support rangeland management. We found dozens of regional data products describing cheatgrass or annual herbaceous cover and few maps describing ventenata or medusahead. Over the past decade, IAG spatial data increased in spatial and temporal resolution and increasingly used response variables that indicate the severity of infestation such as percent cover. Despite improvements, use of such data is limited by the time required to find, compare, understand, and translate model-based maps into management strategy. There is also a need for products with higher spatial resolution and accuracy. In collaboration with a multipartner stakeholder group, we identified key considerations that guide selection of IAG spatial data products for use by land managers and other users. On the basis of these considerations, we discuss issues that contribute to a research-implementation gap between users and product developers and suggest future directions for improved development of management-ready spatial products.

Rangeland Ecology & Management↗

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↗

USGS2021

Prioritizing restoration areas to conserve multiple sagebrush-associated wildlife species

Strategic restoration of altered habitat is one method for addressing worldwide biodiversity declines. Within the sagebrush steppe of western North America, habitat degradation has been linked to declines in many species, making restoration a priority for managers; however, limited funding, spatiotemporal variation in restoration success, and the need to manage for diverse wildlife species make decision-making regarding restoration actions challenging. To address the challenge of spatial conservation prioritization, we developed the Prioritizing Restoration of Sagebrush Ecosystems Tool (PReSET). This decision support tool utilizes the prioritizr package in program R and an integer linear programming algorithm to select parcels representing both high biodiversity value and high probability of restoration success. We tested PReSET on a sagebrush steppe system within southwestern Wyoming using distributional data for six species with diverse life histories and a spatial layer of predicted sagebrush recovery times to identify restoration targets at both broad and local scales. While the broad-scale portion of our tool outputs can inform policy, the local-scale results can be applied directly to on-the-ground restoration. We identified restoration priority areas with greater precision than existing spatial prioritizations and incorporated range differences among species. We noted tradeoffs, including that restoring for habitat connectivity may require restoration actions in areas with lower probability of success. Future applications of PReSET will draw from emerging datasets, including spatially-varying economic costs of restoration, animal movement data, and additional species, to further improve our ability to target effective sagebrush restoration.

Wyoming↗

USGS2021

Synthesizing and analyzing long-term monitoring data: A greater sage-grouse case study

Long-term monitoring of natural resources is imperative for increasing the understanding of ecosystem processes, services, and how to manage those ecosystems to maintain or improve function. Challenges with using these data may occur because methods of monitoring changed over time, multiple organizations collect and manage data differently, and monetary resources fluctuate, affecting many aspects of data. Because many species respond to changes in habitat conditions and predator-prey relationships across different spatial scales that span management boundaries, greater efforts for collaborating are essential. We demonstrate the challenges and methods for standardizing greater sage-grouse ( Centrocercus urophasianus ) long-term monitoring data across the species range in the western United States to inform population modeling needs identified by the Western Association of Fish and Wildlife Agencies. We used automated and repeatable methods of standardizing data via custom open-source software ( grsg_lekdb ) to improve the scientific integrity of future sage-grouse population assessments within and among states. Data standardization included reconciling uses of different terminology and expunging unusable data, resulting in the removal of 26% of data records due to database insertion errors and modifications to >1 million values to correct formatting and typing errors. Our approaches maximized the inclusion of usable data and identified data that could inform detection probabilities, population trends, and monitoring guidelines. Using sage-grouse databases as an example, we identified the importance of data management and how quality assurance and quality control measures can improve the usefulness of these data for future research needs. Our methods of using informatics and concluding recommendations can support similar endeavors of flora and fauna monitoring programs, whether those efforts are to use existing data or support new monitoring programs.

Ecological Informatics↗

USGS2021

Integrating wildlife habitat models with state-and-transitions models to enhance the management of rangelands for multiple objectives

State-and-transition models (STMs) are tools used in rangeland management to describe linear and nonlinear vegetation dynamics as conceptual models. STMs can be improved by including additional ecosystem services, such as wildlife habitat, so that managers can predict how local populations might respond to state changes and to illustrate the tradeoffs in managing for different ecosystem services. Our objective was to incorporate songbird density into an STM developed for sagebrush rangelands in northwest Colorado to guide local management of sagebrush birds. The STM included two shrub-dominated community phases, a native grassland state, and a shrubland and grassland phase within an exotic-dominated state. We surveyed plots for songbirds, collected a suite of vegetation indicators at each plot, and quantified songbird habitat relationships with count-based regression models. We then used the estimated models to predict songbird density based on average vegetation conditions per state or community phase. Moderate or increasing shrub cover were important predictors for shrubland-associated species, and responses to understory components varied by species. In the STM, we predicted higher densities of shrubland-associated bird species in the shrub-dominated phases and higher densities of grassland-associated bird species in the state and phase lacking shrub cover. No single state or phase captured the highest density for all songbirds, illustrating the value of alternative states. Our results also demonstrate the utility of displaying traditional wildlife count models against the range of vegetation conditions associated with each state or phase to understand how wildlife density can vary within states and phases. Our approach can assist land managers to gauge the potential impacts of land-use decisions and natural vegetation variability on wildlife, especially for species of conservation concern.

Rangeland Ecology and Management↗

USGS2020

Postfire growth of seeded and planted big sagebrush - Strategic designs for restoring Greater Sage-grouse nesting habitat

Wildfires change plant community structure and impact wildlife habitat and population dynamics. Recent wildfire‐induced losses of big sagebrush ( Artemisia tridentata ) in North American shrublands are outpacing natural recovery and leading to substantial losses in habitat for sagebrush‐obligate species such as Greater Sage‐grouse. Managers are considering restoration strategies that include planting container‐grown sagebrush to improve establishment within areas using more conventional seeding methods. Although it is thought that planting sagebrush provides initial structural advantages over seeding, empirical comparisons of sagebrush growth are lacking between individuals established post‐fire using both methods. Using a Bayesian hierarchical approach, we evaluated sagebrush height and canopy area growth rates for plants established in 26 seeded and 20 planted locations within the Great Basin. We then related recovery rates to previously published nesting habitat requirements for sage‐grouse. Under average weather conditions, planted or seeded sagebrush will require 3 or 4 years, respectively, and a relatively high density (≥ 2 plants/m 2 ) to achieve the minimum recommended canopy cover for sage‐grouse (15 %). Sagebrush grown in warmer and drier conditions met this cover goal months earlier. Although planted sagebrush reached heights to meet sage‐grouse nesting requirements (30 cm) one year earlier than seeded plants, seeded individuals were ~19 cm taller with 410 cm 2 more canopy area than planted sagebrush after 8 years. However, big sagebrush establishment from seed is unreliable. Strategically planting small, high density patches of container‐grown sagebrush in historic sage‐grouse nesting habitat combined with lower density seedings in larger surrounding areas may accelerate sage‐grouse habitat restoration.

California, Idaho, Nevada, Oregon, Utah↗

USGS2020

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

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

Alaska, Washington, Montana, Colorado, New Mexico,↗

USGS2020

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

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

Arizona, Colorado, New Mexico, Utah↗

USGS2020

Bridging the research-management gap: Landscape ecology in practice on public lands in the western United States

The field of landscape ecology has grown and matured in recent decades, but incorporating landscape science into land management decisions remains challenging. Many lands in the western United States are federally owned and managed for multiple uses, including recreation, conservation, and energy development. We argue for stronger integration of landscape science into the management of these public lands. We open by outlining the relevance of landscape science for public land planning, management, and environmental effects analysis, including pertinent laws and policies. We identify challenges to integrating landscape science into public land management, including the multijurisdictional nature and complicated spatial pattern of public lands, the capacity of agencies to identify and fill landscape science needs, and public perceptions about the meaning of landscape approaches to management. We provide several recent examples related to landscape monitoring, restoration, reclamation, and conservation in which landscape science products were developed specifically to support decision-making. We close by highlighting three actions - elevating the importance of science-management partnerships dedicated to coproducing actionable landscape science products, identifying where landscape science could foster efficiencies in the land-use planning process, and developing scenario-based landscape models for shrublands - that could improve landscape science support for public land planners and managers.

Arizona, California, Colorado, Idaho, Montana, New↗

USGS2020

The transformative impact of genomics on sage-grouse conservation and management

For over two decades, genetic studies have been used to assist in the conservation and management of both Greater Sage-grouse ( Centrocercus urophasianus ) and Gunnison Sage-grouse ( C. minimus ), addressing a wide variety of topics including taxonomy, parentage, population connectivity, and demography. The field of conservation genetics has been transformed by dramatic improvements in sequencing technology, facilitating genomic studies in many wildlife species. The quality and amount of data generated by genomic methods vastly exceed that of traditional genetic studies, allowing for increased precision in estimating genetic parameters of interest. Perhaps more importantly, genomic methods can provide insight into non-neutral evolution such as adaptive divergence. Here we recount the shift from genetic to genomic methods using two wildlife species of substantial conservation interest, focusing on the improved capabilities and advantages of genomic methods. For instance, reassessment of divergence in sage-grouse using genomic methods confirmed strong differentiation between the two species and revealed that a small population in the state of Washington was more genetically distinct than previously recognized. Further, new genomic resources and approaches have been used to identify a family of genes linked to local dietary adaptation suggesting that sage-grouse may possess digestive and metabolic adaptations that mitigate the effects of consuming plant secondary metabolites like those found in sagebrush. Genetic variation among populations in these gene regions is thought to be involved with local dietary adaptations, and therefore maintaining the tie between sage-grouse and the chemistry of local sagebrush may be an important management consideration. We posit that the integration of newly developed genomic resources combined with the vast wealth of ecological and behavioral data for sage-grouse has the potential to shed light on mechanistic relationships that ultimately are vital to the conservation and management of these species.

Book chapter↗

USGS2020

Using remote sensing products to predict recovery of vegetation across space and time following energy development

Using localized studies to understand how ecosystems recover can create uncertainty in recovery predictions across landscapes. Large archives of remote sensing data offer opportunities for quantifying the spatial and temporal factors influencing recovery at broad scales and predicting recovery. For example, energy production is a widespread and expanding land use among many semi-arid ecosystems of the Western United States dominated by sagebrush ( Artemisia spp.), a keystone species providing a variety of ecological services. With remotely-sensed (Landsat) estimates of vegetation cover collected every 2–5 years from southwestern Wyoming, USA, over nearly three decades (1985–2015), we modeled changes in sagebrush cover on 375 former oil and gas well pads in response to weather and site-level conditions. We then used modeled relationships to predict recovery time across the landscape as an indicator of resilience for vegetation after well pad disturbances, where faster recovery indicates a greater capacity to recover when similarly disturbed. We found the rate of change in sagebrush cover generally increased with moisture and temperature, particularly at higher elevations. Rate of change in sagebrush cover also increased and decreased with greater percent sand and larger well pads, respectively. We predicted 21% of the landscape would recover to pre-disturbance conditions within 60 years, whereas other areas may require >100 years for recovery. These predictions and maps could inform future restoration efforts as they reflect resilience. This approach also is applicable to other disturbance types (e.g., fires and vegetation removal treatments) across landscapes, which can further improve conservation efforts by characterizing past conditions and monitoring trends in subsequent years.

Wyoming↗

USGS2019

Designing multi-scale hierarchical monitoring frameworks for wildlife to support management: A sage-grouse case study

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

Nevada, Wyoming↗