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dc.contributor.advisorRuxton, Graeme Douglas
dc.contributor.advisorSmith, V. Anne
dc.contributor.authorInvernizzi, Edith
dc.coverage.spatial170en_US
dc.date.accessioned2023-03-28T11:22:24Z
dc.date.available2023-03-28T11:22:24Z
dc.date.issued2022-11-29
dc.identifier.urihttps://hdl.handle.net/10023/27278
dc.description.abstractThis thesis focuses on wall building behaviour in Temnothorax ants as a case study of self-organised collective behaviour. It contains a progressing series of research packages, building towards one evolutionary question: how eusocial insect nest building algorithms successfully make the transition between two rule variants. I start by revising the existent behavioural model of Temnothorax wall building. By replicating the original agent-based model, I identify two issues: 1. the behavioural model performs poorly in conditions of low building material availability; and 2. the behavioural model lacks behavioural termination. I then introduce a revised version of the behavioural model (the gradual model) in which high stone density at building sites triggers a decrease in building activity, eventually leading to behavioural termination. I then compare the fit of both models to empirical data using laboratory observations of T. rugatulus wall building, applying a hidden Markov model framework to interpret the data. The gradual model provides the best match to the observed data. Finally, I use the revised model to test, in an agent-based model setting, how wall quality responds to different types of inter-worker variation in the building rule used: the presence of a mutant variant spreading within the colony; the co-existence of multiple variants; and widespread epigenetic individual variation. I find wall quality to be very robust to nearly any degree and frequency of variants. With additional simulations, I identify the two key elements of the building algorithm that provide robustness: the positive feedback effect, co-localising worker effort despite starting individual variation; and the existence of an area of overlap where activity occurs with high frequency under all variants (a buffer zone). I predict that these two components have been under selection for evolvability in wall building Temnothorax ants.en_US
dc.description.sponsorship"This work was supported by the John Templeton Foundation as part of the research programme 'Putting the Extended Evolutionary Synthesis to the test' [grant number 60501]. EI’s training and conference travels were partially supported by the Santander-St Leonard’s College Research Mobility Scholarship and by the Sir Ken Murray Endowment Fund." --Fundingen
dc.language.isoenen_US
dc.relationBuilding models: Developing the behavioural model of Temnothorax collective wall building to study the evolutionary robustness of self-organised algorithms (dataset) Invernizzi, E., University of St Andrews, GitHub, 2022. URL: https://github.com/invernie/PhD-thesis
dc.relation.urihttps://github.com/invernie/PhD-thesisen
dc.rightsCreative Commons Attribution-NoDerivatives 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by-nd/4.0/*
dc.subjectGroup behaviouren_US
dc.subjectSelf-organisationen_US
dc.subjectAnten_US
dc.subjectTemnothoraxen_US
dc.subjectNest buildingen_US
dc.subjectEvolutionen_US
dc.subjectEvolution of collective behaviouren_US
dc.subjectEvolution and self-organisationen_US
dc.titleBuilding models : developing the behavioural model of Temnothorax collective wall building to study the evolutionary robustness of self-organised algorithmsen_US
dc.typeThesisen_US
dc.contributor.sponsorTempleton Foundationen_US
dc.type.qualificationlevelDoctoralen_US
dc.type.qualificationnamePhD Doctor of Philosophyen_US
dc.publisher.institutionThe University of St Andrewsen_US
dc.identifier.doihttps://doi.org/10.17630/sta/374
dc.identifier.grantnumber60501en_US


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