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Interaction among societal and biological drivers of policy at the wildlife-agricultural interface

dc.contributor.authorMiller, Ryan S., author
dc.contributor.authorWebb, Colleen T., advisor
dc.contributor.authorHobbs, N. Thompson, committee member
dc.contributor.authorAntolin, Michael F., committee member
dc.contributor.authorOpp, Susan M., committee member
dc.date.accessioned2017-09-14T16:04:49Z
dc.date.available2018-09-12T16:04:38Z
dc.date.issued2017
dc.description.abstractThis dissertation research on wildlife policy and biology focuses on understanding the mechanisms that drive development of wildlife-agricultural policy and also on understanding the underlying ecological drivers of pathogen transmission and population growth for an invasive species. This research uses a combination of meta-analyses, mathematical models, and Bayesian statistics to examine the drivers of emerging wildlife policy, transient population dynamics, and ecological determinants of pathogen prevalence, using wild pigs (Sus scrofa) as a study system. Chapter One investigates cross-species disease transmission between wildlife, domestic animals and humans, which is an increasing threat to public and veterinary health. The risk to agricultural and human health was investigated by evaluating the status of 84 pathogens; the host species most at risk for transmission; and the co-occurrence of wild pigs, agriculture and humans. This was accomplished with a combination of meta-analysis and network analysis approaches. Thirty-four economically important swine pathogens (bacterial, viral, and parasitic) that cause clinical disease in livestock, poultry, wildlife, and humans were identified with the potential for transmission. Chapter Two investigates the conflicts between wildlife and agriculture and characterizes the processes that drive emergence of policy at the wildlife-agricultural interface. Using data describing congressional policy activity related to wild pigs, generalized linear models were used to relate the frequency of policy activity to the frequency of negative newspaper articles and amount of the U.S. agricultural industry potentially impacted by wild swine over a 30-year period. A strong linkage between wild pig policy activity and predictors representing news media, specifically negativity of media, geographic distribution of media, and amount of agriculture potentially impacted were identified as important. Results suggest that agriculture and media coverage may act as determinants for wildlife-agricultural policy development. Chapter Three investigates the ecological drivers of pathogen prevalence, specifically the role of species diversity. To accomplish this, a hierarchical Bayesian model that accounted for imperfect detection probability was used to investigate the influence of species diversity on the infection probability in wild pigs for pathogens with broad and narrow host ranges. Consistent with the species-diversity dilution hypothesis, prevalence of a single-host pathogen, pseudorabies virus, was negatively influenced by increasing richness of non-competent hosts. Contrary to the species-diversity amplification hypothesis, a multi-host pathogen, swine brucellosis, did not increase in prevalence as competent hosts increased in richness. Accounting for imperfect detection was important and indicated that processes other than diagnostic test error alone may be important for determining pathogen prevalence. Environmental gradients associated with changes in pathogen prevalence were linked to host species survival, specifically the severity of temperature and precipitation during the coldest period of the year. This together with species diversity may limit the ability of single-host pathogens to invade populations experiencing stressful conditions. Chapter Four investigates environmental drivers of short-term population dynamics for invasive and native populations. Short-term transient population dynamics are common in vertebrates, particularly invasive vertebrates, and by their nature are directly influenced by the interaction of population structure and vital rates. Using a novel methodological framework, we found consistent differences in the way vital rates and age structure in invasive and native wild pig populations contribute to transient dynamics suggesting that invasive and native populations are influenced by differing mechanisms. These dynamics appear to be linked with environmental conditions that regulate demography. Vital rates with the largest influence on population growth had the greatest variability across populations, contrary to the demographic buffering hypothesis. In native populations, vital rates contributed most to population growth. Invasive populations demonstrated a trade-off in the contribution of vital rates and age structure that may have unexpected consequences for invasive species management.
dc.format.mediumborn digital
dc.format.mediumdoctoral dissertations
dc.identifierMiller_colostate_0053A_14297.pdf
dc.identifier.urihttps://hdl.handle.net/10217/183930
dc.languageEnglish
dc.language.isoeng
dc.publisherColorado State University. Libraries
dc.relation.ispartof2000-2019
dc.rightsCopyright and other restrictions may apply. User is responsible for compliance with all applicable laws. For information about copyright law, please see https://libguides.colostate.edu/copyright.
dc.subjectmodel
dc.subjectpopulation
dc.subjectwild pig
dc.subjectpolicy
dc.subjectdisease
dc.subject.lcshSus scrofa
dc.titleInteraction among societal and biological drivers of policy at the wildlife-agricultural interface
dc.typeText
dcterms.embargo.expires2018-09-12
dcterms.embargo.terms2018-09-12
dcterms.rights.dplaThis Item is protected by copyright and/or related rights (https://rightsstatements.org/vocab/InC/1.0/). You are free to use this Item in any way that is permitted by the copyright and related rights legislation that applies to your use. For other uses you need to obtain permission from the rights-holder(s).
thesis.degree.disciplineBiology
thesis.degree.grantorColorado State University
thesis.degree.levelDoctoral
thesis.degree.nameDoctor of Philosophy (Ph.D.)

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