Background
Engineering efficient transport systems that deliver resources from many suppliers to many consumers is a challenging problem. With dynamic supply and demand, the challenge is magnified, and if the transport network is disrupted, (e.g. local lockdowns, supply failures), system resilience relies on dynamic restructuring to mitigate changes. While we grapple with these engineering problems nationally and globally, biological systems have already evolved efficient, resilient network systems for dynamic resource transport under similar spatial constraints. Certain ant species form networks of connected nests, between which resources are shared. Nests differ in resource supply, and ants create a network to redistribute resources effectively, while remaining robust to local failures, e.g. nest destruction. This system shares many features of complex multi-source multi-sink human transport networks. This project will model resource flow in these complex transport networks, informed by 10 years of detailed empirical data on ant network structure and usage. The modelling results will identify core underlying processes involved in dynamic network restructuring, and will generate solutions to complex transport problems.
Objectives
i) To model dynamic resource flow in complex spatially embedded networks and identify candidate mechanisms for maintaining resilience under stress/disruption
ii) To develop and apply novel tools for analysis of dynamic resource flow on spatial networks
iii) To generate feasible solutions to network disruptions, assess their costs and benefits, and generate empirically testable predictions for their application to transport systems
Student training
The supervisory team have extensive experience of interdisciplinary projects and expertise in behavioural ecology, theoretical ecology, social network analysis and long-term field studies. The student will be trained in network modelling and analysis techniques and will have the opportunity to visit the field sites where the empirical data on which the model will be based are collected.
The Department of Biology at the University of York is committed to recruiting extraordinary future scientists regardless of age, ethnicity, gender, gender identity, disability, sexual orientation or career pathway to date. We understand that commitment and excellence can be shown in many ways and have built our recruitment process to reflect this. We welcome applicants from all backgrounds, particularly those underrepresented in science, who have curiosity, creativity and a drive to learn new skills.
Entry Requirements: Students with, or expecting to gain, at least an upper second class honours degree, or equivalent, are invited to apply. The interdisciplinary nature of this programme means that we welcome applications from students with backgrounds in any biological, chemical, and/or physical science, or students with mathematical backgrounds who are interested in using their skills in addressing biological questions.
Programme: PhD in Biology (3.5 years)
Start date: 1st October 2022
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