Erik E. Osnas

Host Sex and Local Adaptation by Parasites in a Snail-Trematode Interaction

One of the leading theories for the evolutionary stability of sex in eukaryotes relies on parasite‐mediated selection against locally common host genotypes (the Red Queen hypothesis). As such, parasites would be expected to be better at infecting sympatric host populations than allopatric host populations. Here we examined all published and unpublished infection experiments on a snail‐trematode system (Potamopyrgus antipodarum and Microphallus sp., respectively). A meta‐analysis demonstrated significant local adaptation by the parasite, and a variance components analysis showed that the variance due to the host‐parasite interaction far exceeded the variance due to the main effects of host source and parasite source. The meta‐analysis also indicated that asexual host populations were more resistant to allopatric sources of parasites than were (mostly) sexual host populations, but we found no significant differences among parasite populations in the strength of local adaptation. This result suggests that triploid asexual snails are more resistant to remote sources of parasites, but the parasite has, through coevolution, overcome the difference. Finally, we found that the degree of local adaptation did not depend on the genetic distance among host populations. Taken together, the results demonstrate that the parasites are adapted, on average, to infecting their local host populations and suggest that they may be a factor in selecting against common host genotypes in natural populations.

Host culling as an adaptive management tool for chronic wasting disease in white-tailed deer: a modelling study

Summary 1 Emerging wildlife diseases pose a significant threat to natural and human systems. Because of real or perceived risks of delayed actions, disease management strategies such as culling are often implemented before thorough scientific knowledge of disease dynamics is available. Adaptive management is a valuable approach in addressing the uncertainty and complexity associated with wildlife disease problems and can be facilitated by using a formal model.2 We developed a multi‐state computer simulation model using age, sex, infection‐stage, and seasonality as a tool for scientific learning and managing chronic wasting disease (CWD) in white‐tailed deer Odocoileus virginianus. Our matrix model used disease transmission parameters based on data collected through disease management activities. We used this model to evaluate management issues on density‐ (DD) and frequency‐dependent (FD) transmission, time since disease introduction, and deer culling on the demographics, epizootiology, and management of CWD.3 Both DD and FD models fit the Wisconsin data for a harvested white‐tailed deer population, but FD was slightly better. Time since disease introduction was estimated as 36 (95% CI, 24–50) and 188 (41–>200) years for DD and FD transmission, respectively. Deer harvest using intermediate to high non‐selective rates can be used to reduce uncertainty between DD and FD transmission and improve our prediction of long‐term epidemic patterns and host population impacts. A higher harvest rate allows earlier detection of these differences, but substantially reduces deer abundance.4 Results showed that CWD has spread slowly within Wisconsin deer populations, and therefore, epidemics and disease management are expected to last for decades. Non‐hunted deer populations can develop and sustain a high level of infection, generating a substantial risk of disease spread. In contrast, CWD prevalence remains lower in hunted deer populations, but at a higher prevalence the disease competes with recreational hunting to reduce deer abundance.5 Synthesis and applications. Uncertainty about density‐ or frequency‐dependent transmission hinders predictions about the long‐term impacts of chronic wasting disease on cervid populations and the development of appropriate management strategies. An adaptive management strategy using computer modelling coupled with experimental management and monitoring can be used to test model predictions, identify the likely mode of disease transmission, and evaluate the risks of alternative management responses.

Linking process to pattern: estimating spatiotemporal dynamics of a wildlife epidemic from cross-sectional data

Underlying dynamic event processes unfolding in continuous time give rise to spatiotemporal patterns that are sometimes observable at only a few discrete times. Such event processes may be modulated simultaneously over several spatial (e.g., latitude and longitude) and temporal (e.g., age, calendar time, and cohort) dimensions. The ecological challenge is to understand the dynamic latent processes that were integrated over several dimensions (space and time) to produce the observed pattern: a so-called inverse problem. An example of such a problem is characterizing epidemiological rate processes from spatially referenced age-specific prevalence data for a wildlife disease such as chronic wasting disease (CWD). With age-specific prevalence data, the exact infection times are not observed, which complicates the direct estimation of rates. However, the relationship between the observed data and the unobserved rate variables can be described with likelihood equations. Typically, for problems with multiple timescales, the likelihoods are integral equations without closed forms. The complexity of the likelihoods often makes traditional maximum-likelihood approaches untenable. Here, using seven years of hunter-harvest prevalence data from the CWD epidemic in white-tailed deer (Odocoileus virginianus) in Wisconsin, USA, we develop and explore a Bayesian approach that allows for a detailed examination of factors modulating the infection rates over space, age, and time, and their interactions. Our approach relies on the Bayesian ability to borrow strength from neighbors in both space and time. Synthesizing a number of areas of event time analysis (current-status data, age/period/cohort models, Bayesian spatial shared frailty models), our general framework has very broad ecological applicability beyond disease prevalence data to a number of important ecological event time analyses, including general survival studies with multiple time dimensions for which existing methodology is limited. We observed strong associations of infection rates with age, gender, and location. The infection rate appears to be increasing with time. We could not detect growth hotspots, or location by time interactions, which suggests that spatial variation in infection rates is determined primarily by when the disease arrives locally, rather than how fast it grows. We emphasize assumptions and the potential consequences of their violations.

Spatial and temporal patterns of chronic wasting disease: fine- scale mapping of a wildlife epidemic in Wisconsin

Emerging infectious diseases threaten wildlife populations and human health. Understanding the spatial distributions of these new diseases is important for disease management and policy makers; however, the data are complicated by heterogeneities across host classes, sampling variance, sampling biases, and the space-time epidemic process. Ignoring these issues can lead to false conclusions or obscure important patterns in the data, such as spatial variation in disease prevalence. Here, we applied hierarchical Bayesian disease mapping methods to account for risk factors and to estimate spatial and temporal patterns of infection by chronic wasting disease (CWD) in white-tailed deer (Odocoileus virginianus) of Wisconsin, U.S.A. We found significant heterogeneities for infection due to age, sex, and spatial location. Infection probability increased with age for all young deer, increased with age faster for young males, and then declined for some older animals, as expected from disease-associated mortality and age-related changes in infection risk. We found that disease prevalence was clustered in a central location, as expected under a simple spatial epidemic process where disease prevalence should increase with time and expand spatially. However, we could not detect any consistent temporal or spatiotemporal trends in CWD prevalence. Estimates of the temporal trend indicated that prevalence may have decreased or increased with nearly equal posterior probability, and the model without temporal or spatiotemporal effects was nearly equivalent to models with these effects based on deviance information criteria. For maximum interpretability of the role of location as a disease risk factor, we used the technique of direct standardization for prevalence mapping, which we develop and describe. These mapping results allow disease management actions to be employed with reference to the estimated spatial distribution of the disease and to those host classes most at risk. Future wildlife epidemiology studies should employ hierarchical Bayesian methods to smooth estimated quantities across space and time, account for heterogeneities, and then report disease rates based on an appropriate standardization.

Parasite dose, prevalence of infection and local adaptation in a host-parasite system.

Parasites have been found to be more infective to sympatric hosts (local adaptation) in some systems but not in others. The variable nature of results might arise due to differences in host and/or parasite migration rates, parasite virulence, specificity of infection, and to differences in the dose-response functions. We tested this latter possibility by manipulating the dose of trematode (Microphallus sp.) eggs on sympatric and allopatric host populations (Potamopyrgus antipodarum). We found that infection rapidly increased to a high asymptote (0.88 +/- 0.02, 1 S.E.) in the sympatric host population, but infections were low and surprisingly unrelated to dose in the allopatric host. We also found that host survival and growth rate were not negatively affected by increasing parasite dose in either population. These results suggest that defences in the allopatric host were not overwhelmed at high parasite doses, and that any life-history costs of defence are not plastic responses to parasite dose.

Adaptive Capacity of Social-Ecological Systems: Lessons from Immune Systems

How do systems respond to disturbances? The capacity of a system to respond to disturbances varies for different types of disturbance regimes. We distinguish two types of responses: one that enables the system to absorb disturbances from an existing disturbance regime, and one that enables a system to reconstruct itself after a fundamental change in a disturbance regime. We use immune systems as a model for how systems can deal with disturbances, and use this model to derive insights in adaptive capacity of social-ecological systems. We identify a tension between the two types of responses where one benefits from learning and memory while the other requires fast-turnover of experience. We discuss how this may affect building up adaptive capacity of social-ecological systems.

Evolution of pathogen virulence across space during an epidemic

We explore pathogen virulence evolution during the spatial expansion of an infectious disease epidemic in the presence of a novel host movement trade-off, using a simple, spatially explicit mathematical model. This work is motivated by empirical observations of the Mycoplasma gallisepticum invasion into North American house finch (Haemorhous mexicanus) populations; however, our results likely have important applications to other emerging infectious diseases in mobile hosts. We assume that infection reduces host movement and survival and that across pathogen strains the severity of these reductions increases with pathogen infectiousness. Assuming these trade-offs between pathogen virulence (host mortality), pathogen transmission, and host movement, we find that pathogen virulence levels near the epidemic front (that maximize wave speed) are lower than those that have a short-term growth rate advantage or that ultimately prevail (i.e., are evolutionarily stable) near the epicenter and where infection becomes endemic (i.e., that maximize the pathogen basic reproductive ratio). We predict that, under these trade-offs, less virulent pathogen strains will dominate the periphery of an epidemic and that more virulent strains will increase in frequency after invasion where disease is endemic. These results have important implications for observing and interpreting spatiotemporal epidemic data and may help explain transient virulence dynamics of emerging infectious diseases.

The Role of Competition and Local Habitat Conditions for Determining Occupancy Patterns in Grebes

Abstract Wetland use was studied in the Pied-billed Grebe (Podilymbus podiceps) and Horned Grebe (Podiceps auritus) in southwestern Manitoba during April to August of 1997. Of the 180 wetlands surveyed, 74 had no grebe use, six were sporadically used by either grebe species, 19 were consistently used by Horned Grebe, nine switched from Horned Grebe to Pied-billed Grebe use, none switched from Pied-billed Grebe to Horned Grebe use, 68 were consistently used by Pied-billed Grebe, one was regularly used by both species but at different times, and three were concurrently used by both species throughout the breeding season. Wetlands used by grebes were larger, deeper, and had more vegetated area than wetlands not used by grebes, wetlands where occupancy changed were larger, deeper, and had more vegetated area than wetlands consistently used by one species, and wetlands that were concurrently used by both species were larger, deeper, and had more vegetated area than wetlands used by only one species at a time. Five logistic regression models were used to model the probability of observing a grebe brood as a function of the habitat characteristics of the wetland, grebe species, and their interaction. The three best models all contained a parameter describing the habitat characteristics of the wetlands. In two of the three best models, the probability of observing a grebe brood increased with increased wetland size, depth, and vegetated area. These results indicate that habitat characteristics influence breeding quality of a wetland and that grebes may be competing for high quality wetlands in this study area.

Immune response to sympatric and allopatric parasites in a snail-trematode interaction.

BackgroundThe outcome of parasite exposure depends on the (1) genetic specificity of the interaction, (2) induction of host defenses, and (3) parasite counter defenses. We studied both the genetic specificity for infection and the specificity for the host-defense response in a snail-trematode interaction (Potamopyrgus antipodarum-Microphallus sp.) by conducting a reciprocal cross-infection experiment between two populations of host and parasite.ResultsWe found that infection was greater in sympatric host-parasite combinations. We also found that the host-defense response (hemocyte concentration) was induced by parasite exposure, but the response did not increase with increased parasite dose nor did it depend on parasite source, host source, or host-parasite combination.ConclusionThe results are consistent with a genetically specific host-parasite interaction, but inconsistent with a general arms-race type interaction where allocation to defense is the main determinant of host resistance.

Rejoinder: sifting through model space

DENNIS M. HEISEY, ERIK E. OSNAS, PAUL C. CROSS, DAMIEN O. JOLY, JULIA A. LANGENBERG, AND MICHAEL W. MILLER USGS, National Wildlife Health Center, Madison, Wisconsin 53711 USA Department of Forest and Wildlife Ecology, University of Wisconsin, 1630 Linden Drive, Madison, Wisconsin 52706 USA USGS, Northern Rocky Mountain Science Center, Bozeman, Montana 59717 USA Global Health Programs, Wildlife Conservation Society, 1008 Beverly Drive, Nanaimo, British Columbia V9S 2S4 Canada Wisconsin Department of Natural Resources, 101 South Webster Street, Madison, Wisconsin 53703 USA Colorado Division of Wildlife, Wildlife Research Center, 317 West Prospect Road, Fort Collins, Colorado 80526-2097 USA