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Title:Multiscale dynamics in honeybee societies
Author(s):Deviprasad Rao, Vikyath
Director of Research:Goldenfeld, Nigel
Doctoral Committee Chair(s):Maslov, Sergei
Doctoral Committee Member(s):DeVille, Robert E; Kuehn, Seppe
Department / Program:Physics
Degree Granting Institution:University of Illinois at Urbana-Champaign
Subject(s):complex systems
biological physics
honey bee
social networks
Abstract:In this dissertation, I examine the social organization of a model organism, the honeybee, at multiple scales. I begin in Part I at the microbial scale, by studying the relationship between the social caste of individuals and the microbes they harbour in their gastrointestinal tracts. Using 16S rRNA sequence data, I reconstruct the gut microbiomes of honeybees of different castes. I find that the microbiomes of two previously-uncharacterized social castes -- drones and queens -- contain the same bacteria as those in the guts of worker bees. However, despite this similarity, I show that the compositions of these bacteria in drones and queens are sufficiently different that their microbiomes can be distinguished from those of workers. In Part II, I study the honeybee society at the level of its individual constituents, in particular, the set of foragers. I characterize the distribution of foraging activity across these individuals in the society, and find that this is highly skewed, with some individuals contributing much more to the activity of the colony than others. I establish these results in the framework used to describe the wealth of individuals in human society, and also characterize the temporal variation and resilience of foraging activity. In Part III, I describe a system to track individual honeybees and their interactions inside a two-dimensional observation hive with high spatiotemporal resolution. At the level of individual honeybees, I study the temporal statistics of trophallaxis, an important social interaction that occurs in honeybee societies, and find that the distribution of trophallaxis durations is similar to the distribution of face-to-face interactions among humans. I propose a scaling argument to explain the scaling exponent of these distributions, and test the argument in simple random-walk models of proximity interactions. I then study the honeybee society at the collective scale of the trophallaxis interaction network, and find that although bees exhibit bursty patterns of trophallaxis just as humans do in communication, the dynamics of simulated spreading on the trophallaxis networks is fast relative to randomized reference models, unlike in human temporal networks.
Issue Date:2016-11-10
Rights Information:Copyright 2016 Vikyath Deviprasad Rao
Date Available in IDEALS:2017-03-01
Date Deposited:2016-12

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