Geology topics

Adrian P. Monroe

Publications and source records attributed to Adrian P. Monroe.

At least 37 records · Page 2Linked to original sources

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

Colorado River Basin Actionable and Strategic Integrated Science and Technology Project—Science strategy

The U.S. Geological Survey (USGS) conducts a wide variety of science that improves understanding of droughts and their effects on ecosystems and society. This work includes data collection and monitoring of aquatic and terrestrial systems; assessment and analysis of patterns, trends, drivers, and impacts of drought; development and application of predictive models; and delivery of information and decision-making tools to stakeholders. Stakeholders, which include Federal, Tribal, State, and local agencies, nongovernmental organizations, and others, use this information to anticipate, assess, react to, and mitigate drought conditions and impacts. There is no obvious near-term solution to reduce the frequency and severity of droughts or to mitigate drought impacts. Multidecadal drought is a “grand challenge” that benefits from integration of existing technologies, data, knowledge, and models across related and disparate disciplines, facilitated by new science and technology. In response, the USGS initiated a new integrated-science approach in the Colorado River Basin in 2020. The Colorado River Basin was specifically selected because of concerns about future drought and its consequences for the region. This document explains how the Colorado River Basin Actionable and Strategic Integrated Science and Technology (ASIST) project extends and enhances the science supported by USGS Mission Areas and Programs and articulates scientific gaps and stakeholder needs to identify and reduce drought risks. The approach seeks to answer complex Earth science questions developed in partnership with stakeholders about severe long-term drought. An integrated approach is required to tackle these complex questions, which any single science discipline cannot answer on its own. In addition to increased understanding of drought and drought effects in complex systems, the Colorado River Basin ASIST project was designed to improve efficiencies through rapid location of a broad array of data sources, assembly of model-ready multidisciplinary data, and delivery of actionable science to stakeholders at the speeds and scales needed for decision making. The project team identified the following actions needed for USGS to implement and advance an integrated science approach in the Colorado River Basin: (1) engage with stakeholders to document their needs and iteratively co-produce science and science delivery tools to address these needs, (2) integrate monitoring and observation systems developed by USGS and other agencies that track droughts and their effects, (3) collect and provide analysis-ready data to support integrated applications, (4) integrate data and model connections to predict multiple drought impacts, (5) conduct multidisciplinary coordination to improve interpretations, (6) leverage the knowledge base across USGS to enhance decision making, and (7) support the development of new integrated science approaches and technologies that provide analysis and management tools that can be used to adapt to the effects of drought in the Colorado River Basin. Proposals for initial short-term use-case projects were solicited, a subset of which was selected for funding to test implementation of these actions. Additionally, the project organized and convened a series of science and technology collaboration workshops in the USGS focused on challenges that were identified and prioritized by the short-term use-case projects and during the initial stakeholder analysis. These workshops were designed to bring together diverse perspectives to discuss science and technology challenges, stakeholder needs, capabilities, and knowledge gaps, with the goal of determining how the USGS can address challenges, identify future opportunities for continued engagement between participants, and inform the next steps for the Colorado River Basin ASIST project. Continuing to collaboratively engage with a wide range of stakeholders using an integrated approach will provide a suitable foundation of data and tools to formulate actionable intelligence for predicting droughts and informing adaptation to the effects of long-term drought in a holistic, timely, and effective manner.

Arizona, California, Colorado, Nevada, New Mexico,↗

USGS2023

A hidden cost of single species management: Habitat-relationships reveal potential negative effects of conifer removal on a non-target species

Land management priorities and decisions may result in population declines for non-target wildlife species. In the western United States, large-scale removal of conifer from sagebrush ecosystems ( Artemisia spp.) is occurring to recover greater sage-grouse ( Centrocercus urophasianus ) populations and may result in pinyon jay ( Gymnorhinus cyanocephalus ) habitat loss. Jay populations have experienced long-term declines, due to unknown causes, resulting in a recent petition for listing under the Endangered Species Act of 1973. We developed a Bayesian hierarchical model of jay abundance, using 13 years of point count data (2008–2020) collected across the western United States, to estimate regional population trends, model habitat requirements, assess conifer removal effects on jays, and generate hypotheses regarding jay population declines. Our model included climate and landcover covariates and regional trends in pinyon jay density. We applied our modeled habitat relationships to map predicted pinyon jay density, given 2008 and 2020 resource conditions, and map density changes from 2008 to 2020. Our results indicate pinyon jay populations are declining within Bird Conservation Region 16. Jay density was positively associated with sagebrush cover, Palmer Drought Severity Index, and pinyon-juniper cover. Conversely, jay populations were negatively associated with Normalized Difference Vegetation Index (NDVI). We found higher pinyon jay densities within locations possessing both sagebrush and pinyon-juniper cover; conditions characteristic of phase I and II conifer encroachment which are preferentially targeted for conifer removal to restore sagebrush communities. Conifer removal, if conducted at locations with high pinyon jay densities, is therefore likely to negatively affect jay abundance.

Arizona, California, Colorado, Idaho, Kansas, Mont↗

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

U.S. Geological Survey Colorado River Basin Actionable and Strategic Integrated Science and Technology (ASIST)—Information Management Technology Plan

Introduction More than 840 publications, 575 data releases, and 330 project web pages from the U.S. Geological Survey (USGS) pertain to the Colorado River Basin. Limited interconnections between Colorado River Basin publications, data, and web pages restrict the ability to synthesize and interpret scientific resources. Currently, these pieces are spread across multiple isolated locations, internal systems, data repositories, and local offices. The increasing size, complexity, and diversity of Colorado River Basin data creates additional need for integration. These different data types—including discrete, continuous, aerial, remote sensing, geophysical, geospatial, and other types in varied formats—are collected over numerous time and space scales and require data-intensive science and technology to integrate. Information management technology (IMT) resources are enterprise capabilities that the USGS workforce can leverage at multiple scales with consistent interoperable solutions to better facilitate integrated science. The USGS 21st Century Science Strategy directs the USGS to establish enterprise IMT capabilities that support integrated work through interoperable software and database solutions at multiple scales. This Information Management Technology Plan identifies nine steps to leverage new and existing technologies, data, models, and scientific knowledge to support integrated science projects conducted across the Colorado River Basin. These steps are transferable to integrated-science studies in other locations.

Arizona, Colorado, Nevada, New Mexico, Utah, Wyomi↗

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

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

Galliform exclusion from the Migratory Bird Treaty Act has produced an alternate conservation path, but no evidence for differences in population status

The Migratory Bird Treaty Act (MBTA) is critical to avian conservation in the United States, both through its protection of migratory birds and as a catalyst for a century of coordinated avian conservation. While more than 1,000 species are protected by MBTA, of extant bird species native to the continental U.S., only 20 species belonging to the order Galliformes are explicitly excluded. Management of galliforms has occurred largely without direct federal oversight, placing this group on a fundamentally different conservation path during the century following MBTA passage. In this paper, we review the historical context and biological justification for exclusion of galliforms from MBTA and synthesize how their present-day conservation differs from that of migratory birds. We find the most prominent difference between the two groups involves the scope of coordination among stakeholders. The U.S. government, primarily via the Department of Interior, acts as de facto coordinating body for migratory bird conservation and plays the central role in oversight, funding, and administration of management in the United States. In contrast, galliform management falls primarily to individual state wildlife agencies, and coordinated conservation efforts have been more ad hoc and unevenly spread across species. Migratory birds benefit from an almost universally greater scope of research and monitoring, scale of habitat conservation, and sophistication of harvest management compared with galliforms. Galliform harvest management plans, in particular, are less likely to use measurable objectives, reporting of uncertainty in population parameters, and explanation of harvest management techniques. Based on a review of species status lists (e.g., the U.S. Endangered Species Act), we found no evidence that galliforms were more frequently listed than migratory species. Regional trend estimates from the North American Breeding Bird Survey (BBS) were more likely to be negative for galliforms over the period 1966–2015, but this was primarily driven by Northern Bobwhite ( Colinus virginianus ). Data to assess galliform population status are generally poor, which complicates assessment for roughly half of galliform species. Increased support for coordination among state agencies and other stakeholders, similar to that applied to migratory birds, could help to ensure that galliform conservation is poised to tackle forthcoming challenges associated with global change.

North America↗

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 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↗

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↗