ASU Electronic Theses and Dissertations
This collection includes most of the ASU Theses and Dissertations from 2011 to present. ASU Theses and Dissertations are available in downloadable PDF format; however, a small percentage of items are under embargo. Information about the dissertations/theses includes degree information, committee members, an abstract, supporting data or media.
In addition to the electronic theses found in the ASU Digital Repository, ASU Theses and Dissertations can be found in the ASU Library Catalog.
Dissertations and Theses granted by Arizona State University are archived and made available through a joint effort of the ASU Graduate College and the ASU Libraries. For more information or questions about this collection contact or visit the Digital Repository ETD Library Guide or contact the ASU Graduate College at gradformat@asu.edu.
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- All Subjects: Biology
- Creators: Kang, Yun
- Creators: Angilletta, Michael
Description
Mathematical modeling of infectious diseases can help public health officials to make decisions related to the mitigation of epidemic outbreaks. However, over or under estimations of the morbidity of any infectious disease can be problematic. Therefore, public health officials can always make use of better models to study the potential implication of their decisions and strategies prior to their implementation. Previous work focuses on the mechanisms underlying the different epidemic waves observed in Mexico during the novel swine origin influenza H1N1 pandemic of 2009 and showed extensions of classical models in epidemiology by adding temporal variations in different parameters that are likely to change during the time course of an epidemic, such as, the influence of media, social distancing, school closures, and how vaccination policies may affect different aspects of the dynamics of an epidemic. This current work further examines the influence of different factors considering the randomness of events by adding stochastic processes to meta-population models. I present three different approaches to compare different stochastic methods by considering discrete and continuous time. For the continuous time stochastic modeling approach I consider the continuous-time Markov chain process using forward Kolmogorov equations, for the discrete time stochastic modeling I consider stochastic differential equations using Wiener's increment and Poisson point increments, and also I consider the discrete-time Markov chain process. These first two stochastic modeling approaches will be presented in a one city and two city epidemic models using, as a base, our deterministic model. The last one will be discussed briefly on a one city SIS and SIR-type model.
ContributorsCruz-Aponte, Maytee (Author) / Wirkus, Stephen A. (Thesis advisor) / Castillo-Chavez, Carlos (Thesis advisor) / Camacho, Erika T. (Committee member) / Kang, Yun (Committee member) / Arizona State University (Publisher)
Created2014
Description
There has been important progress in understanding ecological dynamics through the development of the theory of ecological stoichiometry. This fast growing theory provides new constraints and mechanisms that can be formulated into mathematical models. Stoichiometric models incorporate the effects of both food quantity and food quality into a single framework that produce rich dynamics. While the effects of nutrient deficiency on consumer growth are well understood, recent discoveries in ecological stoichiometry suggest that consumer dynamics are not only affected by insufficient food nutrient content (low phosphorus (P): carbon (C) ratio) but also by excess food nutrient content (high P:C). This phenomenon, known as the stoichiometric knife edge, in which animal growth is reduced not only by food with low P content but also by food with high P content, needs to be incorporated into mathematical models. Here we present Lotka-Volterra type models to investigate the growth response of Daphnia to algae of varying P:C ratios. Using a nonsmooth system of two ordinary differential equations (ODEs), we formulate the first model to incorporate the phenomenon of the stoichiometric knife edge. We then extend this stoichiometric model by mechanistically deriving and tracking free P in the environment. This resulting full knife edge model is a nonsmooth system of three ODEs. Bifurcation analysis and numerical simulations of the full model, that explicitly tracks phosphorus, leads to quantitatively different predictions than previous models that neglect to track free nutrients. The full model shows that the grazer population is sensitive to excess nutrient concentrations as a dynamical free nutrient pool induces extreme grazer population density changes. These modeling efforts provide insight on the effects of excess nutrient content on grazer dynamics and deepen our understanding of the effects of stoichiometry on the mechanisms governing population dynamics and the interactions between trophic levels.
ContributorsPeace, Angela (Author) / Kuang, Yang (Thesis advisor) / Elser, James J (Committee member) / Baer, Steven (Committee member) / Tang, Wenbo (Committee member) / Kang, Yun (Committee member) / Arizona State University (Publisher)
Created2014
Description
In 1968, phycologist M.R. Droop published his famous discovery on the functional relationship between growth rate and internal nutrient status of algae in chemostat culture. The simple notion that growth is directly dependent on intracellular nutrient concentration is useful for understanding the dynamics in many ecological systems. The cell quota in particular lends itself to ecological stoichiometry, which is a powerful framework for mathematical ecology. Three models are developed based on the cell quota principal in order to demonstrate its applications beyond chemostat culture.
First, a data-driven model is derived for neutral lipid synthesis in green microalgae with respect to nitrogen limitation. This model synthesizes several established frameworks in phycology and ecological stoichiometry. The model demonstrates how the cell quota is a useful abstraction for understanding the metabolic shift to neutral lipid production that is observed in certain oleaginous species.
Next a producer-grazer model is developed based on the cell quota model and nutrient recycling. The model incorporates a novel feedback loop to account for animal toxicity due to accumulation of nitrogen waste. The model exhibits rich, complex dynamics which leave several open mathematical questions.
Lastly, disease dynamics in vivo are in many ways analogous to those of an ecosystem, giving natural extensions of the cell quota concept to disease modeling. Prostate cancer can be modeled within this framework, with androgen the limiting nutrient and the prostate and cancer cells as competing species. Here the cell quota model provides a useful abstraction for the dependence of cellular proliferation and apoptosis on androgen and the androgen receptor. Androgen ablation therapy is often used for patients in biochemical recurrence or late-stage disease progression and is in general initially effective. However, for many patients the cancer eventually develops resistance months to years after treatment begins. Understanding how and predicting when hormone therapy facilitates evolution of resistant phenotypes has immediate implications for treatment. Cell quota models for prostate cancer can be useful tools for this purpose and motivate applications to other diseases.
First, a data-driven model is derived for neutral lipid synthesis in green microalgae with respect to nitrogen limitation. This model synthesizes several established frameworks in phycology and ecological stoichiometry. The model demonstrates how the cell quota is a useful abstraction for understanding the metabolic shift to neutral lipid production that is observed in certain oleaginous species.
Next a producer-grazer model is developed based on the cell quota model and nutrient recycling. The model incorporates a novel feedback loop to account for animal toxicity due to accumulation of nitrogen waste. The model exhibits rich, complex dynamics which leave several open mathematical questions.
Lastly, disease dynamics in vivo are in many ways analogous to those of an ecosystem, giving natural extensions of the cell quota concept to disease modeling. Prostate cancer can be modeled within this framework, with androgen the limiting nutrient and the prostate and cancer cells as competing species. Here the cell quota model provides a useful abstraction for the dependence of cellular proliferation and apoptosis on androgen and the androgen receptor. Androgen ablation therapy is often used for patients in biochemical recurrence or late-stage disease progression and is in general initially effective. However, for many patients the cancer eventually develops resistance months to years after treatment begins. Understanding how and predicting when hormone therapy facilitates evolution of resistant phenotypes has immediate implications for treatment. Cell quota models for prostate cancer can be useful tools for this purpose and motivate applications to other diseases.
ContributorsPacker, Aaron (Author) / Kuang, Yang (Thesis advisor) / Nagy, John (Committee member) / Smith, Hal (Committee member) / Kostelich, Eric (Committee member) / Kang, Yun (Committee member) / Arizona State University (Publisher)
Created2014
Description
The most advanced social insects, the eusocial insects, form often large societies in which there is reproductive division of labor, queens and workers, have overlapping generations, and cooperative brood care where daughter workers remain in the nest with their queen mother and care for their siblings. The eusocial insects are composed of representative species of bees and wasps, and all species of ants and termites. Much is known about their organizational structure, but remains to be discovered.
The success of social insects is dependent upon cooperative behavior and adaptive strategies shaped by natural selection that respond to internal or external conditions. The objective of my research was to investigate specific mechanisms that have helped shaped the structure of division of labor observed in social insect colonies, including age polyethism and nutrition, and phenomena known to increase colony survival such as egg cannibalism. I developed various Ordinary Differential Equation (ODE) models in which I applied dynamical, bifurcation, and sensitivity analysis to carefully study and visualize biological outcomes in social organisms to answer questions regarding the conditions under which a colony can survive. First, I investigated how the population and evolutionary dynamics of egg cannibalism and division of labor can promote colony survival. I then introduced a model of social conflict behavior to study the inclusion of different response functions that explore the benefits of cannibalistic behavior and how it contributes to age polyethism, the change in behavior of workers as they age, and its biological relevance. Finally, I introduced a model to investigate the importance of pollen nutritional status in a honeybee colony, how it affects population growth and influences division of labor within the worker caste. My results first reveal that both cannibalism and division of labor are adaptive strategies that increase the size of the worker population, and therefore, the persistence of the colony. I show the importance of food collection, consumption, and processing rates to promote good colony nutrition leading to the coexistence of brood and adult workers. Lastly, I show how taking into account seasonality for pollen collection improves the prediction of long term consequences.
The success of social insects is dependent upon cooperative behavior and adaptive strategies shaped by natural selection that respond to internal or external conditions. The objective of my research was to investigate specific mechanisms that have helped shaped the structure of division of labor observed in social insect colonies, including age polyethism and nutrition, and phenomena known to increase colony survival such as egg cannibalism. I developed various Ordinary Differential Equation (ODE) models in which I applied dynamical, bifurcation, and sensitivity analysis to carefully study and visualize biological outcomes in social organisms to answer questions regarding the conditions under which a colony can survive. First, I investigated how the population and evolutionary dynamics of egg cannibalism and division of labor can promote colony survival. I then introduced a model of social conflict behavior to study the inclusion of different response functions that explore the benefits of cannibalistic behavior and how it contributes to age polyethism, the change in behavior of workers as they age, and its biological relevance. Finally, I introduced a model to investigate the importance of pollen nutritional status in a honeybee colony, how it affects population growth and influences division of labor within the worker caste. My results first reveal that both cannibalism and division of labor are adaptive strategies that increase the size of the worker population, and therefore, the persistence of the colony. I show the importance of food collection, consumption, and processing rates to promote good colony nutrition leading to the coexistence of brood and adult workers. Lastly, I show how taking into account seasonality for pollen collection improves the prediction of long term consequences.
ContributorsRodríguez Messan, Marisabel (Author) / Kang, Yun (Thesis advisor) / Castillo-Chavez, Carlos (Thesis advisor) / Kuang, Yang (Committee member) / Page Jr., Robert E (Committee member) / Gardner, Carl (Committee member) / Arizona State University (Publisher)
Created2018
Description
There is considerable recent interest in the dynamic nature of immune function in the context of an animal’s internal and external environment. An important focus within this field of ecoimmunology is on how availability of resources such as energy can alter immune function. Water is an additional resource that drives animal development, physiology, and behavior, yet the influence hydration has on immunity has received limited attention. In particular, hydration state may have the greatest potential to drive fluctuations in immunity and other physiological functions in species that live in water-limited environments where they may experience periods of dehydration. To shed light on the sensitivity of immune function to hydration state, I first tested the effect of hydration states (hydrated, dehydrated, and rehydrated) and digestive states on innate immunity in the Gila monster, a desert-dwelling lizard. Though dehydration is often thought to be stressful and, if experienced chronically, likely to decrease immune function, dehydration elicited an increase in immune response in this species, while digestive state had no effect. Next, I tested whether dehydration was indeed stressful, and tested a broader range of immune measures. My findings validated the enhanced innate immunity across additional measures and revealed that Gila monsters lacked a significant stress hormone response during dehydration (though results were suggestive). I next sought to test if life history (in terms of environmental stability) drives these differences in dehydration responses using a comparative approach. I compared four confamilial pairs of squamate species that varied in habitat type within each pair—four species that are adapted to xeric environments and four that are adapted to more mesic environments. No effect of life history was detected between groups, but hydration was a driver of some measures of innate immunity and of stress hormone concentrations in multiple species. Additionally, species that exhibited a stress response to dehydration did not have decreased innate immunity, suggesting these physiological responses may often be decoupled. My dissertation work provides new insight into the relationship between hydration, stress, and immunity, and it may inform future work exploring disease transmission or organismal responses to climate change.
ContributorsMoeller, Karla T (Author) / DeNardo, Dale (Thesis advisor) / Angilletta, Michael (Committee member) / French, Susannah (Committee member) / Rutowski, Ronald (Committee member) / Sabo, John (Committee member) / Arizona State University (Publisher)
Created2016
Description
Desert environments provide considerable challenges to organisms because of high temperatures and limited food and water resources. Accordingly, desert species have behavioral and physiological traits that enable them to cope with these constraints. However, continuing human activity as well as anticipated further changes to the climate and the vegetative community pose a great challenge to such balance between an organism and its environment. This is especially true in the Arabian Desert, where climate conditions are extreme and environmental disturbances substantial. This study combined laboratory and field components to enhance our understanding of dhub (Uromastyx aegyptius) ecophysiology and determine whether habitat protection influences dhub behavior and physiology.
Results of this study showed that while body mass and body condition consistently diminished as the active season progressed, they were both greater in protected habitats compared to non-protected habitats, regardless of season. Dhubs surface activity and total body water decreased while evaporative water loss and body temperature increased as the active season progressed and ambient temperature got hotter. Total body water was also significantly affected by habitat protection.
Overall, this study revealed that, while habitat protection provided more vegetation, it had little effect on seasonal changes in surface activity. While resource availability in protected areas might allow for larger dhub populations, unprotected areas showed similar body morphometrics, activity, and body temperatures. By developing an understanding of how different coping strategies are linked to particular ecological, morphological, and phylogenetic traits, we will be able to make more accurate predictions regarding the vulnerability of species. By combining previous studies pertaining to conservation of protected species with the results of my study, a number of steps in ecosystem management are recommended to help in the preservation of dhubs in the Kuwaiti desert.
Results of this study showed that while body mass and body condition consistently diminished as the active season progressed, they were both greater in protected habitats compared to non-protected habitats, regardless of season. Dhubs surface activity and total body water decreased while evaporative water loss and body temperature increased as the active season progressed and ambient temperature got hotter. Total body water was also significantly affected by habitat protection.
Overall, this study revealed that, while habitat protection provided more vegetation, it had little effect on seasonal changes in surface activity. While resource availability in protected areas might allow for larger dhub populations, unprotected areas showed similar body morphometrics, activity, and body temperatures. By developing an understanding of how different coping strategies are linked to particular ecological, morphological, and phylogenetic traits, we will be able to make more accurate predictions regarding the vulnerability of species. By combining previous studies pertaining to conservation of protected species with the results of my study, a number of steps in ecosystem management are recommended to help in the preservation of dhubs in the Kuwaiti desert.
ContributorsAl-Sayegh, Mohammed (Author) / DeNardo, Dale (Thesis advisor) / Angilletta, Michael (Committee member) / Smith, Andrew (Committee member) / Sabo, John (Committee member) / Majeed, Qais (Committee member) / Arizona State University (Publisher)
Created2017
Description
A key factor in the success of social animals is their organization of work. Mathematical models have been instrumental in unraveling how simple, individual-based rules can generate collective patterns via self-organization. However, existing models offer limited insights into how these patterns are shaped by behavioral differences within groups, in part because they focus on analyzing specific rules rather than general mechanisms that can explain behavior at the individual-level. My work argues for a more principled approach that focuses on the question of how individuals make decisions in costly environments.
In Chapters 2 and 3, I demonstrate how this approach provides novel insights into factors that shape the flexibility and robustness of task organization in harvester ant colonies (Pogonomyrmex barbatus). My results show that the degree to which colonies can respond to work in fluctuating environments depends on how individuals weigh the costs of activity and update their behavior in response to social information. In Chapter 4, I introduce a mathematical framework to study the emergence of collective organization in heterogenous groups. My approach, which is based on the theory of multi-agent systems, focuses on myopic agents whose behavior emerges out of an independent valuation of alternative choices in a given work environment. The product of this dynamic is an equilibrium organization in which agents perform different tasks (or abstain from work) with an analytically defined set of threshold probabilities. The framework is minimally developed, but can be extended to include other factors known to affect task decisions including individual experience and social facilitation. This research contributes a novel approach to developing (and analyzing) models of task organization that can be applied in a broader range of contexts where animals cooperate.
In Chapters 2 and 3, I demonstrate how this approach provides novel insights into factors that shape the flexibility and robustness of task organization in harvester ant colonies (Pogonomyrmex barbatus). My results show that the degree to which colonies can respond to work in fluctuating environments depends on how individuals weigh the costs of activity and update their behavior in response to social information. In Chapter 4, I introduce a mathematical framework to study the emergence of collective organization in heterogenous groups. My approach, which is based on the theory of multi-agent systems, focuses on myopic agents whose behavior emerges out of an independent valuation of alternative choices in a given work environment. The product of this dynamic is an equilibrium organization in which agents perform different tasks (or abstain from work) with an analytically defined set of threshold probabilities. The framework is minimally developed, but can be extended to include other factors known to affect task decisions including individual experience and social facilitation. This research contributes a novel approach to developing (and analyzing) models of task organization that can be applied in a broader range of contexts where animals cooperate.
ContributorsUdiani, Oyita (Author) / Kang, Yun (Thesis advisor) / Fewell, Jennifer H (Thesis advisor) / Janssen, Marcus A (Committee member) / Castillo-Chavez, Carlos (Committee member) / Arizona State University (Publisher)
Created2016
Description
Variation in living systems and how it cascades across organizational levels is central to biology. To understand the constraints and amplifications of variation in collective systems, I mathematically study how group-level differences emerge from individual variation in eusocial-insect colonies, which are inherently diverse and easily observable individually and collectively. Considering collective processes in three species where increasing degrees of heterogeneity are relevant, I address how individual variation scales to colony-level variation and to what degree it is adaptive. In Chapter 2, I introduce a Markov-chain decision model for stochastic individual quorum-based recruitment decisions of rock-ant workers during house hunting, and how they determine collective speed--accuracy balance. Differences in the average threshold-dependent response characteristics of workers between colonies cause collective differences in decision-making. Moreover, noisy behavior may prevent drastic collective cascading into poor nests. In Chapter 3, I develop an ordinary differential equation (ODE) model to study how cognitive diversity among honey-bee foragers influences collective attention allocation between novel and familiar resources. Results provide a mechanistic basis for changes in foraging activity and preference with group composition. Moreover, sensitivity analysis reveals that the main individual driver for foraging allocation shifts from recruitment (communication) to persistence (independent effort) as colony composition changes. This might favor specific degrees of heterogeneity that best amplify communication in wild colonies. Lastly, in Chapter 4, I consider diversity in size, age, and task for nest defense in stingless bees. To better understand how these dimensions of diversity interact to balance defensive demands with other colony needs, I study their effect on colony size and task allocation through a demographic Filippov ODE model. Along each dimension, variation is beneficial in a certain range, outside of which colony adaptation and survival are compromised. This work elucidates how variation in collective properties emerges from nonlinear interactions between varying components in eusocial insects, but it can be generalized to other biological systems with similar fundamental characteristics but less empirical tractability. Moreover, it has the potential of inspiring algorithms that capitalize on heterogeneity in engineered systems where simple components with limited information and no central control must solve complex tasks.
ContributorsNavas Zuloaga, Maria Gabriela (Author) / Kang, Yun (Thesis advisor) / Smith, Brian H (Thesis advisor) / Pavlic, Theodore P (Committee member) / Arizona State University (Publisher)
Created2022
Description
The migratory grasshopper (Melanoplus sanguinipes) is one of the most economically important grasshoppers in the western rangelands of the United States (US), capable of causing incredible amounts of damage to crops and rangelands. While M. sanguinipes has been the focus of many research studies, areas like field nutritional physiology and ecology, and interactions between nutritional physiology and biopesticide resistance have very little research. This dissertation presents a multifaceted approach through three research-driven chapters that examine the nutritional physiology of M. sanguinipes and how it interacts with an entomopathogenic fungus for grasshopper management, as well as the challenges of using biopesticides for grasshopper management. Using the Geometric Framework for Nutrition (GFN), I established baseline macronutrient intake for M. sanguinipes, both in laboratory and field populations. Through this work, I found that field and lab populations can exhibit different protein (p) to carbohydrate (c) ratios, or Intake Targets (ITs), but that the field populations had ITs that matched the nutrients available in their environment. I also used the GFN to show that infections with the fungal entomopathogen Metarhizium robertsii DWR2009 did not alter ITs in M. sanguinipes. Although, when confined to carbohydrate- or protein-biased diets, infected grasshoppers had a slightly extended lifespan relative to grasshoppers fed balanced protein:carbohydrate diets. Interestingly, in a postmortem for the grasshopper, the fungus was only able to effectively sporulate on grasshoppers fed the 1p:1c diets, suggesting that grasshopper diet can have substantial impacts on the spread of fungal biopesticides throughout a population, in the absence of any inhibitory abiotic factors. Lastly, I examined the major barriers to fungal and microsporidian biopesticide usage in the United States, including low efficacy, thermal and environmental sensitivity, non-target effects, unregistered or restricted use, and economic or accessibility barriers. I also explored potential solutions to these challenges. This dissertation's focus on Melanoplus sanguinipes and Metarhizium roberstii Strain DWR2009, generates new information about how nutritional physiology and immunology intersect to impact M. sanguinipes performance. The methodology in each of the experimental chapters provides a framework for examining other problematic grasshopper species, by determining baseline nutritional physiology, and coupling nutrition with immunology to maximize the effectiveness of biological pesticides.
ContributorsZembrzuski, Deanna (Author) / Cease, Arianne (Thesis advisor) / Harrison, Jon (Committee member) / Angilletta, Michael (Committee member) / Jaronski, Stefan (Committee member) / Arizona State University (Publisher)
Created2023
Description
Dominance behavior can regulate a division of labor in a group, such as that between reproductive and non-reproductive individuals. Manipulations of insect societies in a controlled environment can reveal how dominance behavior is regulated. Here, I examined how morphological caste, fecundity, group size, and age influence the expression of dominance behavior using the ponerine ant Harpegnathos saltator. All H. saltator females have the ability to reproduce. Only those with a queen morphology that enables dispersal, however, show putative sex pheromones. In contrast, those with a worker morphology normally express dominance behavior. To evaluate how worker-like dominance behavior and associated traits could be expressed in queens, I removed the wings from alate gynes, those with a queen morphology who had not yet mated or left the nest, making them dealate. Compared to gynes with attached wings, dealates frequently performed dominance behavior. In addition, only the dealates demonstrated worker-like ovarian activity in the presence of reproductive individuals, whereas gynes with wings produced sex pheromones exclusively. Therefore, the attachment of wings determines a gyne’s expression of worker-like dominance behavior and physiology. When the queen dies, workers establish a reproductive hierarchy among themselves by performing a combination of dominance behaviors. To understand how reproductive status depends on these interactions as well as a worker’s age, I measured the frequency of dominance behaviors in groups of different size composed of young and old workers. The number of workers who expressed dominance scaled with the size of the group, but younger ones were more likely to express dominance behavior and eventually become reproductive. Therefore, the predisposition of age integrates with a self-organized process to form this reproductive hierarchy. A social insect’s fecundity and fertility signal depends on social context because fecundity increases with colony size. To evaluate how a socially dependent signal regulates dominance behavior, I manipulated a reproductive worker’s social context. Reproductive workers with reduced fecundity and a less prominent fertility signal expressed more dominance behavior than those with a stronger fertility signal and higher fecundity. Therefore, dominance behavior reinforces rank to compensate for a weak signal, indicating how social context can feed back to influence the maintenance of dominance. Mechanisms that regulate H. saltator’s reproductive hierarchy can inform how the reproductive division of labor is regulated in other groups of animals.
ContributorsPyenson, Benjamin (Author) / Liebig, Jürgen (Thesis advisor) / Hölldobler, Bert (Committee member) / Fewell, Jennifer (Committee member) / Pratt, Stephen (Committee member) / Kang, Yun (Committee member) / Arizona State University (Publisher)
Created2022