Geology topics

Jennifer M. Ramsey

Publications and source records attributed to Jennifer M. Ramsey.

3 recordsLinked to original sources

USGS2015

Identifying priority chronic wasting disease surveillance areas for mule deer in Montana

Chronic wasting disease (CWD) is a fatal prion disease that affects a variety of ungulate species including mule deer ( Odocoileus hemionus ). As of 2014, no CWD cases had been reported in free-ranging ungulates in Montana. However, nearby cases in Canada, Wyoming, and the Dakotas indicated that the disease was encroaching on Montana's borders. Mule deer are native and common throughout Montana, and they represent a significant portion of the total hunter-harvested cervids in the state. The arrival of CWD in Montana may have significant ecosystem and socioeconomic impacts as well as potential consequences for wildlife management. We used 18,879 mule deer locations from 892 individual deer collected during 1975–2011 and modeled habitat selection for 7 herds in 5 of the 7 wildlife management regions in Montana. We estimated resource selection functions (RSF) in a Bayesian framework to predict summer and winter habitat preferences for mule deer. We estimated deer abundance from flyover counts for each region, and used the RSF predictions as weights to distribute the deer across the region. We then calculated the distance to the nearest known infected herds. We predicted areas of high risk of CWD infection in mule deer as areas with densities above the median density estimate and within the lowest quartile of distances to known infected herds. We identified these areas, the southeast corner of Montana and the north-central border near Alberta and Saskatchewan, as priority areas for CWD surveillance and management efforts.

Montana↗

USGS2015

Modeling risk of pneumonia epizootics in bighorn sheep

Pneumonia epizootics are a major challenge for management of bighorn sheep ( Ovis canadensis ) affecting persistence of herds, satisfaction of stakeholders, and allocations of resources by management agencies. Risk factors associated with the disease are poorly understood, making pneumonia epizootics hard to predict; such epizootics are thus managed reactively rather than proactively. We developed a model for herds in Montana that identifies risk factors and addresses biological questions about risk. Using Bayesian logistic regression with repeated measures, we found that private land, weed control using domestic sheep or goats, pneumonia history, and herd density were positively associated with risk of pneumonia epizootics in 43 herds that experienced 22 epizootics out of 637 herd-years from 1979–2013. We defined an area of high risk for pathogen exposure as the area of each herd distribution plus a 14.5-km buffer from that boundary. Within this area, the odds of a pneumonia epizootic increased by >1.5 times per additional unit of private land (unit is the standardized % of private land where global  = 25.58% and SD = 14.53%). Odds were >3.3 times greater if domestic sheep or goats were used for weed control in a herd's area of high risk. If a herd or its neighbors within the area of high risk had a history of a pneumonia epizootic, odds of a subsequent pneumonia epizootic were >10 times greater. Risk greatly increased when herds were at high density, with nearly 15 times greater odds of a pneumonia epizootic compared to when herds were at low density. Odds of a pneumonia epizootic also appeared to decrease following increased spring precipitation (odds = 0.41 per unit increase, global  = 100.18% and SD = 26.97%). Risk was not associated with number of federal sheep and goat allotments, proximity to nearest herds of bighorn sheep, ratio of rams to ewes, percentage of average winter precipitation, or whether herds were of native versus mixed or reintroduced origin. We conclude that factors associated with risk of pneumonia epizootics are complex and may not always be from the most obvious sources. The ability to identify high-risk herds will help biologists and managers determine where to focus management efforts and the risk factors that most affect each herd, facilitating more effective, proactive management.

Journal of Wildlife Management↗

USGS2012

Using structured decision making to manage disease risk for Montana wildlife

We used structured decision-making to develop a 2-part framework to assist managers in the proactive management of disease outbreaks in Montana, USA. The first part of the framework is a model to estimate the probability of disease outbreak given field observations available to managers. The second part of the framework is decision analysis that evaluates likely outcomes of management alternatives based on the estimated probability of disease outbreak, and applies managers' values for different objectives to indicate a preferred management strategy. We used pneumonia in bighorn sheep (Ovis canadensis) as a case study for our approach, applying it to 2 populations in Montana that differed in their likelihood of a pneumonia outbreak. The framework provided credible predictions of both probability of disease outbreaks, as well as biological and monetary consequences of management actions. The structured decision-making approach to this problem was valuable for defining the challenges of disease management in a decentralized agency where decisions are generally made at the local level in cooperation with stakeholders. Our approach provides local managers with the ability to tailor management planning for disease outbreaks to local conditions. Further work is needed to refine our disease risk models and decision analysis, including robust prediction of disease outbreaks and improved assessment of management alternatives.

Montana↗