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: Fenichel, Eli
- Creators: Maley, Carlo C
Description
Consideration of both biological and human-use dynamics in coupled social-ecological systems is essential for the success of interventions such as marine reserves. As purely human institutions, marine reserves have no direct effects on ecological systems. Consequently, the success of a marine reserve depends on managers` ability to alter human behavior in the direction and magnitude that supports reserve objectives. Further, a marine reserve is just one component in a larger coupled social-ecological system. The social, economic, political, and biological landscape all determine the social acceptability of a reserve, conflicts that arise, how the reserve interacts with existing fisheries management, accuracy of reserve monitoring, and whether the reserve is ultimately able to meet conservation and fishery enhancement goals. Just as the social-ecological landscape is critical at all stages for marine reserve, from initial establishment to maintenance, the reserve in turn interacts with biological and human use dynamics beyond its borders. Those interactions can lead to the failure of a reserve to meet management goals, or compromise management goals outside the reserve. I use a bio-economic model of a fishery in a spatially patchy environment to demonstrate how the pre-reserve fisheries management strategy determines the pattern of fishing effort displacement once the reserve is established, and discuss the social, political, and biological consequences of different patterns for the reserve and the fishery. Using a stochastic bio-economic model, I demonstrate how biological and human use connectivity can confound the accurate detection of reserve effects by violating assumptions in the quasi-experimental framework. Finally, I examine data on recreational fishing site selection to investigate changes in response to the announcement of enforcement of a marine reserve in the Gulf of California, Mexico. I generate a scale of fines that would fully or partially protect the reserve, providing a data-driven way for managers to balance biological and socio-economic goals. I suggest that natural resource managers consider human use dynamics with the same frequency, rigor, and tools as they do biological stocks.
ContributorsFujitani, Marie (Author) / Abbott, Joshua (Thesis advisor) / Fenichel, Eli (Thesis advisor) / Gerber, Leah (Committee member) / Anderies, John (Committee member) / Arizona State University (Publisher)
Created2014
Description
Many studies over the past two decades examined the link between climate patterns and discharge, but few have attempted to study the effects of the El Niño Southern Oscillation (ENSO) on localized and watershed specific processes such as nutrient loading in the Southwestern United States. The Multivariate ENSO Index (MEI) is used to describe the state of the ENSO, with positive (negative) values referring to an El Niño condition (La Niña condition). This study examined the connection between the MEI and precipitation, discharge, and total nitrogen (TN) and total phosphorus (TP) concentrations in the Upper Salt River Watershed in Arizona. Unrestricted regression models (UMs) and restricted regression models (RMs) were used to investigate the relationship between the discharges in Tonto Creek and the Salt River as functions of the magnitude of the MEI, precipitation, and season (winter/summer). The results suggest that in addition to precipitation, the MEI/season relationship is an important factor for predicting discharge. Additionally, high discharge events were associated with high magnitude ENSO events, both El Niño and La Niña. An UM including discharge and season, and a RM (restricting the seasonal factor to zero), were applied to TN and TP concentrations in the Salt River. Discharge and seasonality were significant factors describing the variability in TN in the Salt River while discharge alone was the significant factor describing TP. TN and TP in Roosevelt Lake were evaluated as functions of both discharge and MEI. Some significant correlations were found but internal nutrient cycling as well as seasonal stratification of the water column of the lake likely masks the true relationships. Based on these results, the MEI is a useful predictor of discharge, as well as nutrient loading in the Salt River Watershed through the Salt River and Tonto Creek. A predictive model investigating the effect of ENSO on nutrient loading through discharge can illustrate the effects of large scale climate patterns on smaller systems.
ContributorsSversvold, Darren (Author) / Neuer, Susanne (Thesis advisor) / Elser, James (Committee member) / Fenichel, Eli (Committee member) / Arizona State University (Publisher)
Created2012
Description
The southwestern willow flycatcher (Empidonax traillii extimus) is listed as an endangered species throughout its range in the southwestern United States. Little is known about its sub-population spatial structure and how this impacts its population viability. In conjunction with being listed as endangered, a recovery plan was produced by the US Fish and Wildlife Service, with recovery units (sub-populations) roughly based on major river drainages. In the interest of examining this configuration of sub-populations and their impact on the measured population viability, I applied a multivariate auto-regressive state-space model to a spatially extensive time series of abundance data for the southwestern willow flycatcher over the period spanning 1995-2010 estimating critical growth parameters, correlation in environmental stochasticity or "synchronicity" between sub-populations (recovery units) and extinction risk of the sub-populations and the whole. The model estimates two parameters, the mean and variance of annual growth rate. Of the models I tested, I found the strongest support for a population model in which three of the recovery units were grouped (the Lower Colorado, Gila Basin, and Rio Grande recovery units) while keeping all others separate. This configuration has 6.6 times more support for the observed data than a configuration assigning each recovery unit to a separate sub-population, which is how they are circumscribed in the recovery plan. Given the best model, the mean growth rate is -0.0234 (CI95 -0.0939, 0.0412) with a variance of 0.0597 (CI95 0.0115, 0.1134). This growth rate is not significantly different from zero and this is reflected in the low potential for quasi-extinction. The cumulative probability of the population experiencing at least an 80% decline from current levels within 15 years for some sub-populations were much higher (range: 0.129-0.396 for an 80% decline). These results suggest that the rangewide population has a low risk of extinction in the next 15 years and that the formal recovery units specified by the original recovery plan do not correspond to proper sub-population units as defined by population synchrony.
ContributorsDockens, Patrick E. T. (Author) / Sabo, John (Thesis advisor) / Stromberg, Juliet (Committee member) / Fenichel, Eli (Committee member) / Arizona State University (Publisher)
Created2012
Description
The immune system plays a dual role during neoplastic progression. It can suppress tumor growth by eliminating cancer cells, and also promote neoplastic expansion by either selecting for tumor cells that are fitter to survive in an immunocompetent host or by establishing the right conditions within the tumor microenvironment. First, I present a model to study the dynamics of subclonal evolution of cancer. I model selection through time as an epistatic process. That is, the fitness change in a given cell is not simply additive, but depends on previous mutations. Simulation studies indicate that tumors are composed of myriads of small subclones at the time of diagnosis. Because some of these rare subclones harbor pre-existing treatment-resistant mutations, they present a major challenge to precision medicine. Second, I study the question of self and non-self discrimination by the immune system, which is fundamental in the field in cancer immunology. By performing a quantitative analysis of the biochemical properties of thousands of MHC class I peptides, I find that hydrophobicity of T cell receptors contact residues is a hallmark of immunogenic epitopes. Based on these findings, I further develop a computational model to predict immunogenic epitopes which facilitate the development of T cell vaccines against pathogen and tumor antigens. Lastly, I study the effect of early detection in the context of Ebola. I develope a simple mathematical model calibrated to the transmission dynamics of Ebola virus in West Africa. My findings suggest that a strategy that focuses on early diagnosis of high-risk individuals, caregivers, and health-care workers at the pre-symptomatic stage, when combined with public health measures to improve the speed and efficacy of isolation of infectious individuals, can lead to rapid reductions in Ebola transmission.
ContributorsChowell-Puente, Diego (Author) / Castillo-Chavez, Carlos (Thesis advisor) / Anderson, Karen S (Thesis advisor) / Maley, Carlo C (Committee member) / Wilson Sayres, Melissa A (Committee member) / Blattman, Joseph N (Committee member) / Arizona State University (Publisher)
Created2016
Description
The closer integration of the world economy has yielded many positive benefits including the worldwide diffusion of innovative technologies and efficiency gains following the widening of international markets. However, closer integration also has negative consequences. Specifically, I focus on the ecology and economics of the spread of species and pathogens. I approach the problem using theoretical and applied models in ecology and economics. First, I use a multi-species theoretical network model to evaluate the ability of dispersal to maintain system-level biodiversity and productivity. I then extend this analysis to consider the effects of dispersal in a coupled social-ecological system where people derive benefits from species. Finally, I estimate an empirical model of the foot and mouth disease risks of trade. By combining outbreak and trade data I estimate the disease risks associated with the international trade in live animals while controlling for the biosecurity measures in place in importing countries and the presence of wild reservoirs. I find that the risks associated with the spread and dispersal of species may be positive or negative, but that this relationship depends on the ecological and economic components of the system and the interactions between them.
ContributorsShanafelt, David William (Author) / Perrings, Charles (Thesis advisor) / Fenichel, Eli (Committee member) / Richards, Timorthy (Committee member) / Janssen, Marco (Committee member) / Collins, James (Committee member) / Arizona State University (Publisher)
Created2016
Description
Resistance to existing anti-cancer drugs poses a key challenge in the field of medical oncology, in that it results in the tumor not responding to treatment using the same medications to which it responded previously, leading to treatment failure. Adaptive therapy utilizes evolutionary principles of competitive suppression, leveraging competition between drug resistant and drug sensitive cells, to keep the population of drug resistant cells under control, thereby extending time to progression (TTP), relative to standard treatment using maximum tolerated dose (MTD). Development of adaptive therapy protocols is challenging, as it involves many parameters, and the number of parameters increase exponentially for each additional drug. Furthermore, the drugs could have a cytotoxic (killing cells directly), or a cytostatic (inhibiting cell division) mechanism of action, which could affect treatment outcome in important ways. I have implemented hybrid agent-based computational models to investigate adaptive therapy, using either a single drug (cytotoxic or cytostatic), or two drugs (cytotoxic or cytostatic), simulating three different adaptive therapy protocols for treatment using a single drug (dose modulation, intermittent, dose-skipping), and seven different treatment protocols for treatment using two drugs: three dose modulation (DM) protocols (DM Cocktail Tandem, DM Ping-Pong Alternate Every Cycle, DM Ping-Pong on Progression), and four fixed-dose (FD) protocols (FD Cocktail Intermittent, FD Ping-Pong Intermittent, FD Cocktail Dose-Skipping, FD Ping-Pong Dose-Skipping). The results indicate a Goldilocks level of drug exposure to be optimum, with both too little and too much drug having adverse effects. Adaptive therapy works best under conditions of strong cellular competition, such as high fitness costs, high replacement rates, or high turnover. Clonal competition is an important determinant of treatment outcome, and as such treatment using two drugs leads to more favorable outcome than treatment using a single drug. Switching drugs every treatment cycle (ping-pong) protocols work particularly well, as well as cocktail dose modulation, particularly when it is feasible to have a highly sensitive measurement of tumor burden. In general, overtreating seems to have adverse survival outcome, and triggering a treatment vacation, or stopping treatment sooner when the tumor is shrinking seems to work well.
ContributorsSaha, Kaushik (Author) / Maley, Carlo C (Thesis advisor) / Forrest, Stephanie (Committee member) / Anderson, Karen S (Committee member) / Cisneros, Luis H (Committee member) / Arizona State University (Publisher)
Created2023
Modeling Spatial Competition and Adaptive Therapy Protocols in Three-Dimensional Vascularized Tumors
Description
In contrast to traditional chemotherapy for cancer which fails to address tumor heterogeneity, raises patients’ levels of toxicity, and selects for drug-resistant cells, adaptive therapy applies ideas from cancer ecology in employing low-dose drugs to encourage competition between cancerous cells, reducing toxicity and potentially prolonging disease progression. Despite promising results in some clinical trials, optimizing adaptive therapy routines involves navigating a vast space of combina- torial possibilities, including the number of drugs, drug holiday duration, and drug dosages. Computational models can serve as precursors to efficiently explore this space, narrowing the scope of possibilities for in-vivo and in-vitro experiments which are time-consuming, expensive, and specific to tumor types. Among the existing modeling techniques, agent-based models are particularly suited for studying the spatial inter- actions critical to successful adaptive therapy. In this thesis, I introduce CancerSim, a three-dimensional agent-based model fully implemented in C++ that is designed to simulate tumorigenesis, angiogenesis, drug resistance, and resource competition within a tissue. Additionally, the model is equipped to assess the effectiveness of various adaptive therapy regimens. The thesis provides detailed insights into the biological motivation and calibration of different model parameters. Lastly, I propose a series of research questions and experiments for adaptive therapy that CancerSim can address in the pursuit of advancing cancer treatment strategies.
ContributorsShah, Sanjana Saurin (Author) / Daymude, Joshua J (Thesis advisor) / Forrest, Stephanie (Committee member) / Maley, Carlo C (Committee member) / Arizona State University (Publisher)
Created2023