{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/95563"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/95563","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Multiscale dynamics in honeybee societies","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.","abstract_html":"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.","abstract_has_math":false,"creators":["Deviprasad Rao, Vikyath"],"institution":"University of Illinois at Urbana-Champaign","degree_name":"Ph.D.","degree_level":"Dissertation","degree_discipline":"Physics","degree_department":null,"school":null,"contributors":["Goldenfeld, Nigel","Maslov, Sergei","DeVille, Robert E.","Kuehn, Seppe"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2017,"date_issued":"2017-03-01T17:01:08Z","date_published":"2017-03-01T17:01:08Z","updated_at":"2026-07-22T22:26:37Z","subjects":["honey bee","biological physics","complex systems","social networks","microbiome","metagenomics"],"languages":["en"],"rights":["Copyright 2016 Vikyath Deviprasad Rao"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/2142/95563","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Goldenfeld, Nigel","Maslov, Sergei","DeVille, Robert E.","Kuehn, Seppe"]},{"key":"dc:creator","label":"Author","values":["Deviprasad Rao, Vikyath"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2017-03-01T17:01:08Z","2019-03-02T10:15:33Z","2016-11-10","2016-12"]},{"key":"dc:type","label":"Dc Type","values":["text"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Physics"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Dissertation"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Ph.D."]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["University of Illinois at Urbana-Champaign"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["honey bee","biological physics","complex systems","social networks","microbiome","metagenomics"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["en"]},{"key":"dc:rights","label":"Dc Rights","values":["Copyright 2016 Vikyath Deviprasad Rao"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["http://hdl.handle.net/2142/95563"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["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.","Submission published under a 24 month embargo labeled 'Closed Access', the embargo will last until 2018-12-01","The student, Vikyath Deviprasad Rao, accepted the attached license on 2016-11-03 at 11:03.","The student, Vikyath Deviprasad Rao, submitted this Dissertation for approval on 2016-11-03 at 11:19.","This Dissertation was approved for publication on 2016-11-10 at 10:14.","DSpace SAF Submission Ingestion Package generated from Vireo submission #10218 on 2017-02-28 at 14:41:18","Made available in DSpace on 2017-03-01T17:01:08Z (GMT). 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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.","Submission published under a 24 month embargo labeled 'Closed Access', the embargo will last until 2018-12-01","The student, Vikyath Deviprasad Rao, accepted the attached license on 2016-11-03 at 11:03.","The student, Vikyath Deviprasad Rao, submitted this Dissertation for approval on 2016-11-03 at 11:19.","This Dissertation was approved for publication on 2016-11-10 at 10:14.","DSpace SAF Submission Ingestion Package generated from Vireo submission #10218 on 2017-02-28 at 14:41:18","Made available in DSpace on 2017-03-01T17:01:08Z (GMT). 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