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The flexibility and robustness of social insect colonies, when they cope with challenges as integrated units, raise many questions, such as how hundreds and thousands of individual local responses are coordinated without a central controlling process. Answering such questions requires: 1. Quantifiable collective responses of colonies under specific scenarios; 2.

The flexibility and robustness of social insect colonies, when they cope with challenges as integrated units, raise many questions, such as how hundreds and thousands of individual local responses are coordinated without a central controlling process. Answering such questions requires: 1. Quantifiable collective responses of colonies under specific scenarios; 2. Decomposability of the collective colony-level response into individual responses; and 3. Mechanisms to integrate the colony- and individual-level responses. In the first part of my dissertation, I explore coordinated collective responses of colonies in during the alarm response to an alarmed nestmate (chapter 2&3). I develop a machine-learning approach to quantitatively estimate the collective and individual alarm response (chapter 2). Using this methodology, I demonstrate that colony alarm responses to the introduction of alarmed nestmates can be decomposed into immediately cascading, followed by variable dampening processes. Each of those processes are found to be modulated by variation in individual alarm responsiveness, as measured by alarm response threshold and persistence of alarm behavior. This variation is modulated in turn by environmental context, in particular with task-related social context (chapter 3). In the second part of my dissertation, I examine the mechanisms responsible for colonial changes in metabolic rate during ontogeny. Prior studies have found that larger ant colonies (as for larger organisms) have lower mass-specific metabolic rates, but the mechanisms remain unclear. In a 3.5-year study on 25 colonies, metabolic rates of colonies and colony components were measured during ontogeny (chapter 4). The scaling of metabolic rate during ontogeny was fit better by segmented regression or quadratic regression models than simple linear regression models, showing that colonies do not follow a universal power-law of metabolism during the ontogenetic development. Furthermore, I showed that the scaling of colonial metabolic rates can be primarily explained by changes in the ratio of brood to adult workers, which nonlinearly affects colonial metabolic rates. At high ratios of brood to workers, colony metabolic rates are low because the metabolic rate of larvae and pupae are much lower than adult workers. However, the high colony metabolic rates were observed in colonies with moderate brood: adult ratios, because higher ratios cause adult workers to be more active and have higher metabolic rates, presumably due to the extra work required to feed more brood.
ContributorsGuo, Xiaohui (Author) / Fewell, Jennifer H (Thesis advisor) / Kang, Yun (Thesis advisor) / Harrison, Jon F (Committee member) / Liebig, Juergen (Committee member) / Pratt, Stephen C (Committee member) / Pavlic, Theodore P (Committee member) / Arizona State University (Publisher)
Created2021
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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

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.
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