Modeling External Forcing on Microparasite Dynamics: a tool for understanding observed ecological patterns and forecasting dynamics
Open Access
- Author:
- Luis, Angela D.
- Graduate Program:
- Ecology
- Degree:
- Doctor of Philosophy
- Document Type:
- Dissertation
- Date of Defense:
- March 19, 2010
- Committee Members:
- Ottar N Bjornstad, Dissertation Advisor/Co-Advisor
Ottar N Bjornstad, Committee Chair/Co-Chair
Peter John Hudson, Committee Chair/Co-Chair
Bryan Grenfell, Committee Member
John Fricks, Committee Member
Richard Douglass, Committee Member - Keywords:
- Sin Nombre virus
hantavirus
Peromyscus
deer mice
hibernation
ecological cascade hypothesis - Abstract:
- In this thesis I explore the dynamics of infectious diseases in rodents. Using Sin Nombre hantavirus (SNV) in deer mice as a model system and a combination of mark-recapture analysis and mathematical models, I explore how infectious diseases can affect individuals, populations and communities, and analyze population, community, and ecosystem level patterns in disease dynamics. I also explore the effect of infectious disease on evolutionary histories, specifically, how bacterial infection may have shaped mammalian hibernation patterns. I use a combination of statistical analysis of longterm data and mathematical models to understand observed ecological patterns and improve our ability to forecast dynamics. Microparasites can have a number of effects on individuals, populations, and communities. I explore the effect of SNV on the deer mouse host and what effect this may have on the host population dynamics and persistence of the disease in the population. I find that SNV decreases survival of antibody positive male deer mice by 15.4\%. This can affect both the host population dynamics, by leading to regulation of the host population, as well as the population-level patterns seen in SNV infection, by increasing the critical host density and making the chain of transmission more likely to be broken. Since the host population dynamics can be affected by many intrinsic and extrinsic factors, such as environmental forcing, disturbance, availability of resources, competition, and other food web interactions, these can all have strong influences on the persistence and spread of a pathogen in the host population. I quantitatively evaluate the proposed bottom-up trophic cascade hypothesis to explain the original SNV outbreak, using 15 years of data from Montana. I show that mouse population dynamics in Montana are strongly correlated to precipitation and temperature with a 0 to 5 month lag. These changing environmental conditions alter the carrying capacity of the environment, which can lead to delayed density dependence in prevalence of the virus (with a lag of up to 16 months or more) in the mouse population and intermittent crossing of the critical host density necessary for hantavirus endemicity. My work helps shed some light on the notoriously difficult to understand dynamics of the virus, such as seemingly inverse density dependence in prevalence and sporadic disappearance of the virus from local populations. Since there is no effective treatment or vaccine for HPS, the most effective strategy is to take preventative measures. This quantitative understanding of the lags between environmental conditions and prevalence of the virus may allow us advance warning (up to 20 months or more) of increased risk to humans.