Geology topics

Robin E. Russell

Publications and source records attributed to Robin E. Russell.

At least 37 records · Page 2Linked to original sources

USGS2018

Local factors associated with on‐host flea distributions on prairie dog colonies

Outbreaks of plague, a flea‐vectored bacterial disease, occur periodically in prairie dog populations in the western United States. In order to understand the conditions that are conducive to plague outbreaks and potentially predict spatial and temporal variations in risk, it is important to understand the factors associated with flea abundance and distribution that may lead to plague outbreaks. We collected and identified 20,041 fleas from 6,542 individual prairie dogs of four different species over a 4‐year period along a latitudinal gradient from Texas to Montana. We assessed local climate and other factors associated with flea prevalence and abundance, as well as the incidence of plague outbreaks. Oropsylla hirsuta , a prairie dog specialist flea, and Pulex simulans, a generalist flea species, were the most common fleas found on our pairs. High elevation pairs in Wyoming and Utah had distinct flea communities compared with the rest of the study pairs. The incidence of prairie dogs with Yersinia pestis detections in fleas was low ( n = 64 prairie dogs with positive fleas out of 5,024 samples from 4,218 individual prairie dogs). The results of our regression models indicate that many factors are associated with the presence of fleas. In general, flea abundance (number of fleas on hosts) is higher during plague outbreaks, lower when prairie dogs are more abundant, and reaches peak levels when climate and weather variables are at intermediate levels. Changing climate conditions will likely affect aspects of both flea and host communities, including population densities and species composition, which may lead to changes in plague dynamics. Our results support the hypothesis that local conditions, including host, vector, and environmental factors, influence the likelihood of plague outbreaks, and that predicting changes to plague dynamics under climate change scenarios will have to consider both host and vector responses to local factors.

Ecology and Evolution↗

USGS2018

Identifying management-relevant research priorities for responding to disease-associated amphibian declines

A research priority can be defined as a knowledge gap that, if resolved, identifies the optimal course of conservation action. We (a group of geographically distributed and multidisciplinary research scientists) used tools from nominal group theory and decision analysis to collaboratively identify and prioritize information needs within the context of disease-associated amphibian decline , in order to develop a strategy that would support US management agency needs. We developed iterated influence diagrams to create and assess a unified research strategy. We illustrated a transparent process for identifying specific knowledge gaps in amphibian disease ecology relevant to environmental management, and then constructed a research plan to address these uncertainties. The resulting priorities include a need to: (1) understand the drivers of the community-disease relationship, (2) determine the mechanisms by which exposure to contaminants influence disease outcomes, (3) identify elements of terrestrial and aquatic habitats that stabilize host-pathogen dynamics, (4) discuss how metapopulations may be managed to reduce the speed and intensity of disease outbreaks, and (5) define the relationship between habitat management and the environmental and host microbiomes. Along with identifying research priorities for disease management, we present the details of the process used to develop a consensus plan for addressing disease-related declines in amphibians on federally managed lands of the United States.

Global Ecology and Conservation↗

USGS2017

Factors influencing uptake of sylvatic plague vaccine baits by prairie dogs

Sylvatic plague vaccine (SPV) is a virally vectored bait-delivered vaccine expressing Yersinia pestis antigens that can protect prairie dogs (Cynomys spp.) from plague and has potential utility as a management tool. In a large-scale 3-year field trial, SPV-laden baits containing the biomarker rhodamine B (used to determine bait consumption) were distributed annually at a rate of approximately 100–125 baits/hectare along transects at 58 plots encompassing the geographic ranges of four species of prairie dogs. We assessed site- and individual-level factors related to bait uptake in prairie dogs to determine which were associated with bait uptake rates. Overall bait uptake for 7820 prairie dogs sampled was 70% (95% C.I. 69.9–72.0). Factors influencing bait uptake rates by prairie dogs varied by species, however, in general, heavier animals had greater bait uptake rates. Vegetation quality and day of baiting influenced this relationship for black-tailed, Gunnison’s, and Utah prairie dogs. For these species, baiting later in the season, when normalized difference vegetation indices (a measure of green vegetation density) are lower, improves bait uptake by smaller animals. Consideration of these factors can aid in the development of species-specific SPV baiting strategies that maximize bait uptake and subsequent immunization of prairie dogs against plague.

EcoHealth↗

USGS2017

Sylvatic plague vaccine partially protects prairie dogs (Cynomys spp.) in field trials

Sylvatic plague, caused by Yersinia pestis , frequently afflicts prairie dogs ( Cynomys spp.), causing population declines and local extirpations. We tested the effectiveness of bait-delivered sylvatic plague vaccine (SPV) in prairie dog colonies on 29 paired placebo and treatment plots (1–59 ha in size; average 16.9 ha) in 7 western states from 2013 to 2015. We compared relative abundance (using catch per unit effort (CPUE) as an index) and apparent survival of prairie dogs on 26 of the 29 paired plots, 12 with confirmed or suspected plague ( Y. pestis positive carcasses or fleas). Even though plague mortality occurred in prairie dogs on vaccine plots, SPV treatment had an overall positive effect on CPUE in all three years, regardless of plague status. Odds of capturing a unique animal were 1.10 (95% confidence interval [C.I.] 1.02–1.19) times higher per trap day on vaccine-treated plots than placebo plots in 2013, 1.47 (95% C.I. 1.41–1.52) times higher in 2014 and 1.19 (95% C.I. 1.13–1.25) times higher in 2015. On pairs where plague occurred, odds of apparent survival were 1.76 (95% Bayesian credible interval [B.C.I.] 1.28–2.43) times higher on vaccine plots than placebo plots for adults and 2.41 (95% B.C.I. 1.72–3.38) times higher for juveniles. Our results provide evidence that consumption of vaccine-laden baits can protect prairie dogs against plague; however, further evaluation and refinement are needed to optimize SPV use as a management tool.

EcoHealth↗

USGS2017

Using decision analysis to support proactive management of emerging infectious wildlife diseases

Despite calls for improved responses to emerging infectious diseases in wildlife, management is seldom considered until a disease has been detected in affected populations. Reactive approaches may limit the potential for control and increase total response costs. An alternative, proactive management framework can identify immediate actions that reduce future impacts even before a disease is detected, and plan subsequent actions that are conditional on disease emergence. We identify four main obstacles to developing proactive management strategies for the newly discovered salamander pathogen Batrachochytrium salamandrivorans ( Bsal ). Given that uncertainty is a hallmark of wildlife disease management and that associated decisions are often complicated by multiple competing objectives, we advocate using decision analysis to create and evaluate trade-offs between proactive (pre-emergence) and reactive (post-emergence) management options. Policy makers and natural resource agency personnel can apply principles from decision analysis to improve strategies for countering emerging infectious diseases.

Frontiers in Ecology and the Environment↗

USGS2017

When mechanism matters: Bayesian forecasting using models of ecological diffusion

Ecological diffusion is a theory that can be used to understand and forecast spatio-temporal processes such as dispersal, invasion, and the spread of disease. Hierarchical Bayesian modelling provides a framework to make statistical inference and probabilistic forecasts, using mechanistic ecological models. To illustrate, we show how hierarchical Bayesian models of ecological diffusion can be implemented for large data sets that are distributed densely across space and time. The hierarchical Bayesian approach is used to understand and forecast the growth and geographic spread in the prevalence of chronic wasting disease in white-tailed deer ( Odocoileus virginianus ). We compare statistical inference and forecasts from our hierarchical Bayesian model to phenomenological regression-based methods that are commonly used to analyse spatial occurrence data. The mechanistic statistical model based on ecological diffusion led to important ecological insights, obviated a commonly ignored type of collinearity, and was the most accurate method for forecasting.

Ecology Letters↗

USGS2017

The Bayesian group lasso for confounded spatial data

Generalized linear mixed models for spatial processes are widely used in applied statistics. In many applications of the spatial generalized linear mixed model (SGLMM), the goal is to obtain inference about regression coefficients while achieving optimal predictive ability. When implementing the SGLMM, multicollinearity among covariates and the spatial random effects can make computation challenging and influence inference. We present a Bayesian group lasso prior with a single tuning parameter that can be chosen to optimize predictive ability of the SGLMM and jointly regularize the regression coefficients and spatial random effect. We implement the group lasso SGLMM using efficient Markov chain Monte Carlo (MCMC) algorithms and demonstrate how multicollinearity among covariates and the spatial random effect can be monitored as a derived quantity. To test our method, we compared several parameterizations of the SGLMM using simulated data and two examples from plant ecology and disease ecology. In all examples, problematic levels multicollinearity occurred and influenced sampling efficiency and inference. We found that the group lasso prior resulted in roughly twice the effective sample size for MCMC samples of regression coefficients and can have higher and less variable predictive accuracy based on out-of-sample data when compared to the standard SGLMM.

Journal of Agricultural, Biological, and Environme↗

USGS2017

A framework for modeling emerging diseases to inform management

The rapid emergence and reemergence of zoonotic diseases requires the ability to rapidly evaluate and implement optimal management decisions. Actions to control or mitigate the effects of emerging pathogens are commonly delayed because of uncertainty in the estimates and the predicted outcomes of the control tactics. The development of models that describe the best-known information regarding the disease system at the early stages of disease emergence is an essential step for optimal decision-making. Models can predict the potential effects of the pathogen, provide guidance for assessing the likelihood of success of different proposed management actions, quantify the uncertainty surrounding the choice of the optimal decision, and highlight critical areas for immediate research. We demonstrate how to develop models that can be used as a part of a decision-making framework to determine the likelihood of success of different management actions given current knowledge.

Emerging Infectious Diseases↗

USGS2017

Dispersal hazards of Pseudogymnoascus destructans by bats and human activity at hibernacula in summer

Bats occupying hibernacula during summer are exposed to Pseudogymnoascus destructans ( Pd ), the causative agent of white-nose syndrome (WNS), and may contribute to its dispersal. Furthermore, equipment and clothing exposed to cave environments are a potential source for human-assisted spread of Pd . To explore dispersal hazards for Pd during the nonhibernal season, we tested samples that were collected from bats, the environment, and equipment at hibernacula in the eastern US between 18 July–22 August 2012. Study sites included six hibernacula known to harbor bats with Pd with varying winter-count impacts from WNS and two hibernacula (control sites) without prior history of WNS. Nucleic acid from Pd was detected from wing-skin swabs or guano from 40 of 617 bats (7% prevalence), including males and females of five species at five sites where WNS had previously been confirmed as well as from one control site. Analysis of guano collected during summer demonstrated a higher apparent prevalence of Pd among bats (17%, 37/223) than did analysis of wing-skin swabs (1%, 4/617). Viable Pd cultured from wing skin (2%, 1/56) and low recapture rates at all sites suggested bats harboring Pd during summer could contribute to pathogen dispersal. Additionally, Pd DNA was detected on clothing and trapping equipment used inside and near hibernacula, and Pd was detected in sediment more readily than in swabs of hibernaculum walls. Statistically significant differences in environmental abundance of Pd were not detected among sites, but prevalence of Pd differed between sites and among bat species. Overall, bats using hibernacula in summer can harbor Pd on their skin and in their guano, and demonstration of Pd on clothing, traps, and other equipment used at hibernacula during summertime within the WNS-affected region indicates risk for pathogen dispersal during the nonhibernal season.

Indiana, Kentucky, Ohio, Tennessee, Virginia↗

USGS2016

Effects of wind energy generation and white-nose syndrome on the viability of the Indiana bat

Wind energy generation holds the potential to adversely affect wildlife populations. Species-wide effects are difficult to study and few, if any, studies examine effects of wind energy generation on any species across its entire range. One species that may be affected by wind energy generation is the endangered Indiana bat ( Myotis sodalis ), which is found in the eastern and midwestern United States. In addition to mortality from wind energy generation, the species also faces range-wide threats from the emerging infectious fungal disease, white-nose syndrome (WNS). White-nose syndrome, caused by Pseudogymnoascus destructans , disturbs hibernating bats leading to high levels of mortality. We used a spatially explicit full-annual-cycle model to investigate how wind turbine mortality and WNS may singly and then together affect population dynamics of this species. In the simulation, wind turbine mortality impacted the metapopulation dynamics of the species by causing extirpation of some of the smaller winter colonies. In general, effects of wind turbines were localized and focused on specific spatial subpopulations. Conversely, WNS had a depressive effect on the species across its range. Wind turbine mortality interacted with WNS and together these stressors had a larger impact than would be expected from either alone, principally because these stressors together act to reduce species abundance across the spectrum of population sizes. Our findings illustrate the importance of not only prioritizing the protection of large winter colonies as is currently done, but also of protecting metapopulation dynamics and migratory connectivity.

PeerJ↗

USGS2016

When can the cause of a population decline be determined?

Inferring the factors responsible for declines in abundance is a prerequisite to preventing the extinction of wild populations. Many of the policies and programmes intended to prevent extinctions operate on the assumption that the factors driving the decline of a population can be determined. Exogenous factors that cause declines in abundance can be statistically confounded with endogenous factors such as density dependence. To demonstrate the potential for confounding, we used an experiment where replicated populations were driven to extinction by gradually manipulating habitat quality. In many of the replicated populations, habitat quality and density dependence were confounded, which obscured causal inference. Our results show that confounding is likely to occur when the exogenous factors that are driving the decline change gradually over time. Our study has direct implications for wild populations, because many factors that could drive a population to extinction change gradually through time.

Ecology Letters↗

USGS2016

U.S. Geological Survey science strategy for highly pathogenic avian influenza in wildlife and the environment (2016–2020)

Introduction Through the Science Strategy for Highly Pathogenic Avian Influenza (HPAI) in Wildlife and the Environment, the USGS will assess avian influenza (AI) dynamics in an ecological context to inform decisions made by resource managers and policymakers from the local to national level. Through collection of unbiased scientific information on the ecology of AI viruses and wildlife hosts in a changing world, the U.S. Geological Survey (USGS) will enhance the development of AI forecasting tools and ensure this information is integrated with a quality decision process for managing HPAI. The overall goal of this USGS Science Strategy for HPAI in Wildlife and the Environment goes beyond documenting the occurrence and distribution of AI viruses in wild birds. The USGS aims to understand the epidemiological processes and environmental factors that influence HPAI distribution and describe the mechanisms of transmission between wild birds and poultry. USGS scientists developed a conceptual model describing the process linking HPAI dispersal in wild waterfowl to the outbreaks in poultry. This strategy focuses on five long-term science goals, which include: Science Goal 1—Augment the National HPAI Surveillance Plan; Science Goal 2—Determine mechanisms of HPAI disease spread in wildlife and the environment; Science Goal 3—Characterize HPAI viruses circulating in wildlife; Science Goal 4—Understand implications of avian ecology on HPAI spread; and Science Goal 5—Develop HPAI forecasting and decision-making tools. These goals will help define and describe the processes outlined in the conceptual model with the ultimate goal of facilitating biosecurity and minimizing transfer of diseases across the wildlife-poultry interface. The first four science goals are focused on scientific discovery and the fifth goal is application-based. Decision analyses in the fifth goal will guide prioritization of proposed actions in the first four goals.

Open-File Report↗

USGS2016

Evaluation of Yersinia pestis transmission pathways for sylvatic plague in prairie dog populations in the western U.S.

Sylvatic plague, caused by the bacterium Yersinia pestis , is periodically responsible for large die-offs in rodent populations that can spillover and cause human mortalities. In the western US, prairie dog populations experience nearly 100% mortality during plague outbreaks, suggesting that multiple transmission pathways combine to amplify plague dynamics. Several alternate pathways in addition to flea vectors have been proposed, such as transmission via direct contact with bodily fluids or inhalation of infectious droplets, consumption of carcasses, and environmental sources of plague bacteria, such as contaminated soil. However, evidence supporting the ability of these proposed alternate pathways to trigger large-scale epizootics remains elusive. Here we present a short review of potential plague transmission pathways and use an ordinary differential equation model to assess the contribution of each pathway to resulting plague dynamics in black-tailed prairie dogs ( Cynomys ludovicianus ) and their fleas ( Oropsylla hirsuta ). Using our model, we found little evidence to suggest that soil contamination was capable of producing plague epizootics in prairie dogs. However, in the absence of flea transmission, direct transmission, i.e., contact with bodily fluids or inhalation of infectious droplets, could produce enzootic dynamics, and transmission via contact with or consumption of carcasses could produce epizootics. This suggests that these pathways warrant further investigation.

Arizona, California, Colorado, Dakota, Dakota, Ida↗

USGS2016

Salamander chytrid fungus ( Batrachochytrium salamandrivorans ) in the United States—Developing research, monitoring, and management strategies

The recently (2013) identified pathogenic chytrid fungus, Batrachochytrium salamandrivoran s ( Bsal ), poses a severe threat to the distribution and abundance of salamanders within the United States and Europe. Development of a response strategy for the potential, and likely, invasion of Bsal into the United States is crucial to protect global salamander biodiversity. A formal working group, led by Amphibian Research and Monitoring Initiative (ARMI) scientists from the U.S. Geological Survey (USGS) Patuxent Wildlife Research Center, Fort Collins Science Center, and Forest and Rangeland Ecosystem Science Center, was held at the USGS Powell Center for Analysis and Synthesis in Fort Collins, Colorado, United States from June 23 to June 25, 2015, to identify crucial Bsal research and monitoring needs that could inform conservation and management strategies for salamanders in the United States. Key findings of the workshop included the following: (1) the introduction of Bsal into the United States is highly probable, if not inevitable, thus requiring development of immediate short-term and long-term intervention strategies to prevent Bsal establishment and biodiversity decline; (2) management actions targeted towards pathogen containment may be ineffective in reducing the long-term spread of Bsal throughout the United States; and (3) early detection of Bsal through surveillance at key amphibian import locations, among high-risk wild populations, and through analysis of archived samples is necessary for developing management responses. Top research priorities during the preinvasion stage included the following: (1) deployment of qualified diagnostic methods for Bsal and establishment of standardized laboratory practices, (2) assessment of susceptibility for amphibian hosts (including anurans), and (3) development and evaluation of short- and long-term pathogen intervention and management strategies. Several outcomes were achieved during the workshop, including development of an organizational structure with working groups for a Bsal Task Force, creation of an initial influence diagram to aid in identifying effective management actions in the face of uncertainty, and production of a list of potential management actions and key research uncertainties. Additional products under development include a Bsal Strategic Action plan, an emergency response plan, a monitoring and surveillance program, a standardized diagnostic approach, decision models for natural resource agencies, and a reporting database for salamander mortalities. This workshop was the first international meeting to address the threat of Bsal to salamander populations in the United States, with more than 30 participants from U.S. conservation and resource management agencies (U.S. Fish and Wildlife Service, U.S. Forest Service, U.S. Department of Defense, U.S. National Park Service, and Association of Fish and Wildlife Agencies) and academic research institutions in Australia, the Netherlands, Switzerland, the United Kingdom, and the United States.

Open-File Report↗

USGS2016

Spatial variation in risk and consequence of Batrachochytrium salamandrivorans introduction in the USA

A newly identified fungal pathogen, Batrachochytrium salamandrivorans ( Bsal ), is responsible for mass mortality events and severe population declines in European salamanders. The eastern USA has the highest diversity of salamanders in the world and the introduction of this pathogen is likely to be devastating. Although data are inevitably limited for new pathogens, disease-risk assessments use best available data to inform management decisions. Using characteristics of Bsal ecology, spatial data on imports and pet trade establishments, and salamander species diversity, we identify high-risk areas with both a high likelihood of introduction and severe consequences for local salamanders. We predict that the Pacific coast, southern Appalachian Mountains and mid-Atlantic regions will have the highest relative risk from Bsal . Management of invasive pathogens becomes difficult once they are established in wildlife populations; therefore, import restrictions to limit pathogen introduction and early detection through surveillance of high-risk areas are priorities for preventing the next crisis for North American salamanders.

Royal Society Open Science↗

USGS2015

Avian influenza ecology in North Atlantic sea ducks: Not all ducks are created equal

Wild waterfowl are primary reservoirs of avian influenza viruses (AIV). However the role of sea ducks in the ecology of avian influenza, and how that role differs from freshwater ducks, has not been examined. We obtained and analyzed sera from North Atlantic sea ducks and determined the seroprevalence in those populations. We also tested swab samples from North Atlantic sea ducks for the presence of AIV. We found relatively high serological prevalence (61%) in these sea duck populations but low virus prevalence (0.3%). Using these data we estimated that an antibody half-life of 141 weeks (3.2 years) would be required to attain these prevalences. These findings are much different than what is known in freshwater waterfowl and have implications for surveillance efforts, AIV in marine environments, and the roles of sea ducks and other long-lived waterfowl in avian influenza ecology.

PLoS ONE↗

USGS2015

Integrating resource selection into spatial capture-recapture models for large carnivores

Wildlife managers need reliable methods to estimate large carnivore densities and population trends; yet large carnivores are elusive, difficult to detect, and occur at low densities making traditional approaches intractable. Recent advances in spatial capture-recapture (SCR) models have provided new approaches for monitoring trends in wildlife abundance and these methods are particularly applicable to large carnivores. We applied SCR models in a Bayesian framework to estimate mountain lion densities in the Bitterroot Mountains of west central Montana. We incorporate an existing resource selection function (RSF) as a density covariate to account for heterogeneity in habitat use across the study area and include data collected from harvested lions. We identify individuals through DNA samples collected by (1) biopsy darting mountain lions detected in systematic surveys of the study area, (2) opportunistically collecting hair and scat samples, and (3) sampling all harvested mountain lions. We included 80 DNA samples collected from 62 individuals in the analysis. Including information on predicted habitat use as a covariate on the distribution of activity centers reduced the median estimated density by 44%, the standard deviation by 7%, and the width of 95% credible intervals by 10% as compared to standard SCR models. Within the two management units of interest, we estimated a median mountain lion density of 4.5 mountain lions/100 km 2 (95% CI = 2.9, 7.7) and 5.2 mountain lions/100 km 2 (95% CI = 3.4, 9.1). Including harvested individuals (dead recovery) did not create a significant bias in the detection process by introducing individuals that could not be detected after removal. However, the dead recovery component of the model did have a substantial effect on results by increasing sample size. The ability to account for heterogeneity in habitat use provides a useful extension to SCR models, and will enhance the ability of wildlife managers to reliably and economically estimate density of wildlife populations, particularly large carnivores.

Montana↗

USGS2015

Avian community responses to post-fire forest structure: Implications for fire management in mixed conifer forests

Fire is a natural process and the dominant disturbance shaping plant and animal communities in many coniferous forests of the western US. Given that fire size and severity are predicted to increase in the future, it has become increasingly important to understand how wildlife responds to fire and post-fire management. The Angora Fire burned 1243 hectares of mixed conifer forest in South Lake Tahoe, California. We conducted avian point counts for the first 3 years following the fire in burned and unburned areas to investigate which habitat characteristics are most important for re-establishing or maintaining the native avian community in post-fire landscapes. We used a multi-species occurrence model to estimate how avian species are influenced by the density of live and dead trees and shrub cover. While accounting for variations in the detectability of species, our approach estimated the occurrence probabilities of all species detected including those that were rare or observed infrequently. Although all species encountered in this study were detected in burned areas, species-specific modeling results predicted that some species were strongly associated with specific post-fire conditions, such as a high density of dead trees, open-canopy conditions or high levels of shrub cover that occur at particular burn severities or at a particular time following fire. These results indicate that prescribed fire or managed wildfire which burns at low to moderate severity without at least some high-severity effects is both unlikely to result in the species assemblages that are unique to post-fire areas or to provide habitat for burn specialists. Additionally, the probability of occurrence for many species was associated with high levels of standing dead trees indicating that intensive post-fire harvest of these structures could negatively impact habitat of a considerable proportion of the avian community.

California↗