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Body size plays a pervasive role in determining physiological and behavioral performance across animals. It is generally thought that smaller animals are limited in performance measures compared to larger animals; yet, the vast majority of animals on earth are small and evolutionary trends like miniaturization occur in every animal clade.

Body size plays a pervasive role in determining physiological and behavioral performance across animals. It is generally thought that smaller animals are limited in performance measures compared to larger animals; yet, the vast majority of animals on earth are small and evolutionary trends like miniaturization occur in every animal clade. Therefore, there must be some evolutionary advantages to being small and/or compensatory mechanisms that allow small animals to compete with larger species. In this dissertation I specifically explore the scaling of flight performance (flight metabolic rate, wing beat frequency, load-carrying capacity) and learning behaviors (visual differentiation visual Y-maze learning) across stingless bee species that vary by three orders of magnitude in body size. I also test whether eye morphology and calculated visual acuity match visual differentiation and learning abilities using honeybees and stingless bees. In order to determine what morphological and physiological factors contribute to scaling of these performance parameters I measure the scaling of head, thorax, and abdomen mass, wing size, brain size, and eye size. I find that small stingless bee species are not limited in visual learning compared to larger species, and even have some energetic advantages in flight. These insights are essential to understanding how small size evolved repeatedly in all animal clades and why it persists. Finally, I test flight performance across stingless bee species while varying temperature in accordance with thermal changes that are predicted with climate change. I find that thermal performance curves varied greatly among species, that smaller species conform closely to air temperature, and that larger bees may be better equipped to cope with rising temperatures due to more frequent exposure to high temperatures. This information may help us predict whether small or large species might fare better in future thermal climate conditions, and which body-size related traits might be expected to evolve.
ContributorsDuell, Meghan (Author) / Harrison, Jon F. (Thesis advisor) / Smith, Brian H. (Thesis advisor) / Rutowski, Ronald (Committee member) / Wcislo, William (Committee member) / Conrad, Cheryl (Committee member) / Arizona State University (Publisher)
Created2018
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Description
Social insect groups, such as bees, termites, and ants, epitomize the emergence of group-level behaviors from the aggregated actions and interactions of individuals. Ants have the unique advantage that whole colonies can be observed in artificial, laboratory nests, and each individual's behavior can be continuously tracked using imaging software. In

Social insect groups, such as bees, termites, and ants, epitomize the emergence of group-level behaviors from the aggregated actions and interactions of individuals. Ants have the unique advantage that whole colonies can be observed in artificial, laboratory nests, and each individual's behavior can be continuously tracked using imaging software. In this dissertation, I study two group behaviors: (1) the spread of alarm signals from three agitated ants to a group of 61 quiescent nestmates, and (2) the reduction in per-capita energy use as colonies scale in size from tens of ants to thousands. For my first experiment, I track the motion of Pogonomyrmex californicus ants using an overhead camera, and I analyze how propagation of an initial alarm stimulus affects their walking speeds. I then build an agent-based model that simulates two-dimensional ant motion and the spread of the alarmed state. I find that implementing a simple set of rules for motion and alarm signal transmission reproduces the empirically observed speed dynamics. For the second experiment, I simulate social insect colony workers that collectively complete a set of tasks. By assuming that task switching is energetically costly, my model recovers a metabolic rate scaling pattern, known as hypometric metabolic scaling. This relationship, which predicts an organism's metabolic rate from its mass, is observed across a diverse set of social insect groups and animal species. The results suggest an explicit link between the degree of workers' task specialization and whole-colony energy use.
ContributorsLin, Michael Robert (Author) / Milner, Fabio A (Thesis advisor, Committee member) / Fewell, Jennifer H (Thesis advisor, Committee member) / Lampert, Adam (Committee member) / Arizona State University (Publisher)
Created2021
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Description
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