Robin E Russell
Robin is a Research Statistician at the National Wildlife Health Center. Her work focuses on the development of models to evaluate population and community level effects of emerging diseases on wildlife, predict the spread of disease and estimate spatial patterns of disease risk.
- Ph.D. Forestry and Natural Resources, Purdue University, 2003
- M.S. Zoology, Colorado State University, 1999
- B.A. Biology, Reed College, 1995
- Research Statistician, US Geological Survey, 2010-Present
- Biometrician, Montana Fish Wildlife and Parks 2008-2010
- Ecologist, US Forest Service, Rocky Mountain Research Station 2006-2008
- Postdoctoral Ecologist, Montana State University and US Forest Service, 2004-2006
- 2005-Present Wildlife Society
- 2006-Present Biometrics Working Group, Wildlife Society
Science and Products
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...Campbell Grant, Evan H.; Adams, Michael J.; Fisher, Robert N.; Grear, Daniel A.; Halstead, Brian J.; Hossack, Blake R.; Muths, Erin L.; Richgels, Katherine L. D.; Russell, Robin E.; Smalling, Kelly; Waddle, J. Hardin; Walls, Susan C.; White, C. LeAnn
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...Russell, Robin E.; Abbott, Rachel C.; Tripp, Daniel W.; Rocke, Tonie E.
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...Abbott, Rachel C.; Russell, Robin E.; Richgels, Katherine; Tripp, Daniel W.; Matchett, Marc R.; Biggins, Dean E.; Rocke, Tonie E.
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...Ballmann, Anne; Torkelson, Miranda R.; Bohuski, Elizabeth A.; Russell, Robin E.; Blehert, David S.
Field efficacy trials with sylvatic plague vaccine
These data were collected as part of a field trial to test the efficacy of a sylvatic plague vaccine. Treatment and control sites were selected randomly from the available sites at each location. Site pairs were a minimum of 20 acres, (with a few exceptions). Prairie dog trapping took place a minimum of two weeks post-baiting and trapping...Richgels, Katherine; Russell, Robin E.; Rocke, Tonie E.
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...Rocke, Tonie E.; Tripp, Daniel W.; Russell, Robin E.; Abbott, Rachel C.; Richgels, Katherine; Matchett, Marc R.; Biggins, Dean E.; Griebel, Randall; Schroeder, Greg; Grassel, Shaun M.; Pipkin, David R.; Cordova, Jennifer; Kavalunas, Adam; Maxfield, Brian; Boulerice, Jesse T.; Miller, Michael W.
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...Grant, Evan H. Campbell; Muths, Erin L.; Katz, Rachel A.; Canessa, Stefano; Adams, Michael J.; Ballard, Jennifer R.; Berger, Lee; Briggs, Cheryl J.; Coleman, Jeremy; Gray, Matthew J.; Harris, M. Camille; Harris, Reid N.; Hossack, Blake R.; Huyvaert, Kathryn P.; Kolby, Jonathan E.; Lips, Karen R.; Lovich, Robert E.; McCallum, Hamish I.; Mendelson, Joseph R.; Nanjappa, Priya; Olson, Deanna H.; Powers, Jenny G.; Richgels, Katherine L. D.; Russell, Robin E.; Schmidt, Benedikt R.; Spitzen-van der Sluijs, Annemarieke; Watry, Mary Kay; Woodhams, Douglas C.; White, C. LeAnn
A dynamic spatio-temporal model for spatial data
Analyzing spatial data often requires modeling dependencies created by a dynamic spatio-temporal data generating process. In many applications, a generalized linear mixed model (GLMM) is used with a random effect to account for spatial dependence and to provide optimal spatial predictions. Location-specific covariates are often included as fixed...Hefley, Trevor J.; Hooten, Mevin B.; Hanks, Ephraim M.; Russell, Robin; Walsh, Daniel P.
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...Hefley, Trevor J.; Hooten, Mevin B.; Russell, Robin E.; Walsh, Daniel P.; Powell, James A.
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...Hefley, Trevor J.; Hooten, Mevin B.; Hanks, Ephraim M.; Russell, Robin E.; Walsh, Daniel P.
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...Russell, Robin E.; Katz, Rachel A.; Richgels, Katherine L. D.; Walsh, Daniel P.; Grant, Evan H. Campbell
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...Erickson, Richard A.; Thogmartin, Wayne E.; Diffendorfer, James E.; Russell, Robin E.; Szymanski, Jennifer A.