Browsing by Author "Webb, Colleen, advisor"

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Open Access
Avian influenza takes flight: host mobility, viral prevalence, and transmission at large spatial scales
(Colorado State University. Libraries, 2024) Berger, Brooke, author; Webb, Colleen, advisor; Miller, Ryan, committee member; Pepin, Kim, committee member; Gorsich, Erin, committee member; Koons, David, committee member
Many pathogens have large geographic distributions, but we currently have little ability to predict how they may change over time. Understanding what mechanisms drive the large-scale distributions and movements of pathogens is critical to designing effective surveillance programs, disease interventions, and predictive models of disease spread. Additionally, we lack information on what spatial scale these mechanisms are most important. In this dissertation we address one of the fundamental problems in ecology, the "problem of pattern and scale", in the context of disease prevalence and spatial transmission. Are the large-scale patterns we see emergent properties of many small-scale processes, or are they a product of large-scale processes themselves? We focused on the spatial distribution, prevalence and spatial transmission of influenza A virus in its endemic host, wild waterfowl. We used a zero-inflated Bayesian CAR model to determine if local environmental persistence of the virus or regional host migration were better predictors of large-scale patterns of prevalence. We found that an unweighted host migration network better predicted high and low values of prevalence than did local drivers. To understand how these factors impacted where IAV moves in the United States (US) we investigated how local-scale transmission and regional-scale host movements influence large-scale spatial transmission and our ability to detect these transmissions. We developed a Bayesian zero-inflated binomial network model to estimate the probability of spatial transmission between watersheds pairs. We found that regional host movement was the best predictor of spatial transmission and that Mallard ducks likely play a special role in moving the virus throughout the US. Viral movement patterns were closely associated with important waterfowl breeding and wintering habitats rather than flyways, as has been previously shown. In order to extend these analyses to other geographic areas and host species we need to construct continental scale host movement networks from movement data with differing spatial and temporal resolutions. We developed a method to simulate host movements from very few observations allowing us to match mark-recovery data to highly detailed satellite telemetry data. We used the biological information in the detailed movement data to estimate population posterior distributions of travel speed, turning angle, and direction. These quantities and an approximately Bayesian rejection scheme were used to simulate missing locations in the mark-recovery data with estimates of uncertainty. The method was validated with a telemetry dataset tracking the movement of Northern Pintail ducks, an important host of IAV. Movement networks constructed from simulated locations captured known population scale migration patterns of Pintail and exhibited similar higher order community structure. More broadly, this research contributes to our understanding of how host mobility impacts the prevalence and movement patterns of pathogens, and the spatial scale at which this mechanism is important. Our findings suggest that predicting the spread and spillover risk of IAV requires an understanding of where hosts move at the regional scale. In the future, as climate and land-use change alter the migration patterns of wild waterfowl, we can expect the distribution and movement patterns of IAV to shift as well.
Open Access
Big fish start small
(Colorado State University. Libraries, 2020) Leach, Clinton, author; Webb, Colleen, advisor; Poff, LeRoy, committee member; Hooten, Mevin, committee member; Noon, Barry, committee member
Individuals of the same species often participate in substantially different predator-prey interactions. In many species, these differences are driven by individual size and the ontogenetic niche shifts that occur as an individual grows. This intraspecific size-structure can have profound consequences for our understanding of food web structure and community dynamics. These consequences are particularly important in exploited marine ecosystems where fisheries often target the largest individuals and size-structured feedbacks have been implicated in preventing collapsed fisheries from recovering. In this dissertation, we explored the consequences of this size-structure for the Scotian Shelf and Gulf of Alaska ecosystems. To understand how the collapse of the cod stock on the Scotian Shelf may have fed back on the demographic landscape of cod, we developed a model to estimate how the length-dependent growth and survival of cod changed before and after the collapse. We found that forage fish, released from top-down control, likely played an important role in limiting cod access to food, with consequences for cod survival and the potential for long term recovery. To better understand the community context of these changes, we developed a multivariate autoregressive model to capture how shifts in species' size distributions may have driven changes in the interspecific interaction landscape on the Scotian Shelf. This study found further evidence for the role of forage fish in preventing cod recovery, and linked the corresponding changes in interaction structure to an increase in the overall instability of the system. Lastly, we explored the community structure of ontogenetic niche shifts in the Gulf of Alaska by developing a model to identify trophic groups — collections of individuals with similar interaction patterns — in an individual-level food web assembled from stomach contents data. The identified trophic groups revealed substantial overlap in the ontogenetic trajectories of Gulf of Alaska predator species and the low-dimensional structure of the individual-level food web. This work represents a step toward incorporating individual-level processes into modeling frameworks that can be used to both inform existing theory with data and to inform fisheries management. Specifically, this research highlights the different trophic roles that individuals of a species occupy as they grow, and the importance of growth in moving individuals up the food web and maintaining community structure and stability. Our findings suggest that disruptions to this flow and the resulting loss of large individuals can generate a cascade of effects through the system, leading to fundamental reorganization and increased instability.
Open Access
Ecophysiological and behavioral determinants of niche range in hibernating bats affected by white nose syndrome
(Colorado State University. Libraries, 2022) Golas, Benjamin D., author; Webb, Colleen, advisor; Cryan, Paul, committee member; Hayman, David, committee member; Huyvaert, Kathryn, committee member
The restrictions of a fundamental niche range, physiological conditions under which an organism can persist, becomes increasingly important as populations are subjected to extreme climatic conditions. Hibernating animals are annually subjected to such extremes. For example, insectivorous bats will survive months without caloric intake in winter by lowering body temperature to near freezing to mitigate loss of energy through heat transfer and water through evaporation. However, there is strong overlap between the fundamental niche of hibernating bats and that of the keratinolytic fungus, Pseudogymnoascus destructans (Pd). As a result of Pd growth disrupting wing membranes, hibernating bats are forced to enact frequent energetically costly arousals that can result in starvation and mortality. The resulting disease, white nose syndrome (WNS), has resulted in mass die offs of millions of hibernating bats across North America since Pd introduction. However, there is significant inter- and intraspecific variation in host responses, and the realized niche for bat hibernation may be wider and more variable than previously theorized, making host responses difficult to predict. Ecophysiological models predict torpor arousal and hibernation survival with WNS as a function of microclimates, but they are largely dependent on laboratory-based experiments measuring metabolic parameters like metabolic rate and evaporative water loss that are likely subject to intraspecific local variation. We require a better understanding of the physiological, environmental, and behavioral drivers of successful bat hibernation in natural systems with and without Pd so we can improve risk assessment and guide management strategies for populations affected by WNS. To better understand how torpor arousal is dependent on experienced microclimates, we attached temperature and humidity data loggers to free-ranging Eptesicus fuscus to record microclimates and arousal frequency throughout hibernation. Fitting this data to ecophysiological models describing torpor, we found that while ecophysiological models provide adequate boundaries to biological capabilities for arousal, stochasticity inherent in natural systems can lead to earlier and more frequent arousal than models suggest. To determine how hibernation roosting niche is constrained in spatiotemporally variable hibernacula, we measured microclimates throughout a hibernaculum where Myotis lucifugus populations have thrived despite regional WNS-related mass mortality. Using hierarchical modeling to predict spatiotemporal underground microclimates based on above-ground conditions, we find that hibernation roosts are likely established early in the hibernation season at microsites that are locally stable within a given hibernaculum chamber, but not necessarily the most stable across the hibernaculum. This suggests that M. lucifugus are capable of a more flexible niche space than previously theorized, which may assist in WNS survival. Lastly, we use approximate Bayesian computation to test different hypotheses for how bats survive WNS in this hibernaculum, using ecophysiological models and longitudinal microclimate data to compare local adaptation, microclimate selection, clustering, and grooming strategies. While grooming removal of Pd load appears to be essential to describe observed population survival, we find evidence of all four hypotheses contributing to biologically realistic survival. Ultimately, the indirect fundamental niche range contraction due to Pd disrupting physiological host processes is mitigated by a combination of adaptation and conspecific facilitation expanding realized niche range. Our work represents advancements in novel technological and modeling advancements that allow evaluation of niche range in free-living populations. The results of this study suggest that there are populations with exaptations that facilitate WNS survival, but that alteration of environmental conditions in other hibernacula could lead to a change in niche space outside the range for which residents are locally adapted. Our findings help to inform and guide assessment of at-risk species and inform potential management strategies by considering the significant individual- and population-level variation in local adaptation and microclimate use that can impact WNS survival.
Open Access
Pathogen persistence in wildlife populations: case studies of plague in prairie dogs and rabies in bats
(Colorado State University. Libraries, 2009) George, Dylan, author; Webb, Colleen, advisor
Disease ecology focuses, in part, on how pathogens persist within host wildlife populations For my dissertation my colleagues and I investigated pathogen persistence mechanisms in two host-pathogen systems: Yersinia pestis (plague) in prairie dogs and rabies virus in bats. Plague, caused by the bacterium Yersinia pestis, recently spread into the range of black-tailed prairie dogs (Cynomys ludovicianus) in North America, and has caused drastic and rapid reduction in local prairie dog populations which have generated a metapopulation dynamic for prairie dogs. We developed a stochastic patch occupancy model to determine if prairie dog populations could persist long-term given the effects of plague. Our model demonstrates that metapopulation dynamics can allow prairie dog persistence. Town extinction in this system is caused by plague. Thus, town extinction and plague colonization are two sides of the same coin, which allows to us to interpret plague dynamics implicit within the prairie dog metapopulation. Long-term metapopulation dynamics indicate plague persists within the system and does not require the involvement of additional reservoir hosts (i.e., other resistant rodent species). Bats are a natural reservoir for rabies, and an increasing number of emerging zoonotic viruses. Little is known about mechanisms that generate unique seasonal patterns and allow enzootic pathogen persistence in bat populations. We propose that life history characteristics unique to many bat species coupled with viral adaptations allow for rabies persistence. First, we developed a statistical model to investigate seasonal patterns of rabies cases in bats. Second, we used data from a five-year study of rabies in big brown bats (Eptesicus fuscus) to parameterize a dynamic disease model that elucidates pathogen persistence mechanisms. We show rabies persists in two distinct ways, (1) through effects on bat population viability, and (2) through effects on viral persistence within a viable bat population. Mortality rates vary across seasons, and low rates during hibernation allow long-term bat population viability. Within a viable bat population, viral persistence occurs because of a lengthy incubation period, enhanced by the metabolic effects of host torpor. The mechanisms we identify may be operating in a similar manner for other bat-borne diseases.
Open Access
Using species functional traits to predict community dynamics
(Colorado State University. Libraries, 2012) Ames, Gregory Michael, author; Webb, Colleen, advisor; Poff, N. LeRoy, committee member; Knapp, Alan, committee member; Noon, Barry, committee member
A major goal for community ecology has been to determine a general set of rules to explain the structure and function of communities. Traits-based methods for describing community dynamics have been touted as providing a set of general methods to describe the structure and function of communities based on measurable properties of individual organisms in the community in a changing environment. Validation of traits-based methods that describe changes in community structure as a function of the interaction between functional traits along changing environmental gradients in real systems is needed. Here we present studies of three different plant communities where we use novel applications of traits-based Bayesian hierarchical models and principal component analysis to explain the changes in community structure/function and demonstrate that the communities are primarily structured by traits and their interactions with a changing environment. In a natural tallgrass prairie we were able to explain more than 84% of the variation in community functional diversity and an average of 64% of the cover variation across the ten species in the study over a 25-year span (Chapter 1). Additionally we show that changes in community structure are primarily explained by relative growth rate and its interaction with precipitation. In an experimentally manipulated grassland, our model explains more than 75% of the variation in total plot biomass over the course of 18 years. Further, we found that this system was primarily driven by the same trait/environment interactions as the tallgrass system. Finally, we show that trait/environment interactions allow us to explain 91% of the variation in plot biomass in a restored riparian wetland. Our ability to explain large portions of the variation in community structure and performance of these three distinct types of plant communities, using similar traits and environmental drivers, provides evidence of general laws underlying the structure of plant communities. This work represents a significant step toward understanding those general laws and helping community ecology develop from a largely descriptive science to a predictive science.