Elva Joan Hilda Robinson

Elva Joan Hilda Robinson

Prof

Former affiliations

Accepting PhD Students

PhD projects

All my advertised funded PhD projects for the next academic year have now closed to new applications, but I welcome enquiries from potential students who have identified their own sources of funding.

MSc by Research opportunities


Quality-distance trade-offs in resource-sharing networks of wood ants


Funding: Self-funded with funding contribution made by the National Trust


Background
Many animals collect resources and defend them from others; peaceful sharing of resources between groups is very rare. In some species of ant, resource-sharing networks emerge, with ants from different nests exchanging food without any conflict. Theoretical modelling predicts that these 'polydomous' colony networks are shaped by the trade-off between exploiting nearby resources, and travelling further to access higher quality resources. The proposed work will test this idea by directly measuring the nature and quality of the honeydew resources collected by the ants and shared between nests. The project will include fieldwork on a population of the wood ant Formica lugubris, at a long-term study site in the UK.


Objectives
1 To test theoretical quality-distance trade-off hypotheses in the field.
2 To assess the role of resource quality in shaping cooperation networks in wood ants


Methodology
This project will involve both fieldwork and laboratory analyses, and involve working with theoretical modellers. Fieldwork will involve mapping colonies and collecting samples of resources; lab work will involve proteomic techniques to analysing food resources. Training in these techniques and in interpreting network models will be provided.


Impact
The results will provide insights into how these extreme cooperative networks emerge and function, providing novel information about an unusual behaviour, and into the drivers of cooperation between groups, something of wide interest. More locally, the information gathered will feed into the management of the site to promote population health: as this species is an ecosystem engineer, this has knock-on positive effects for the whole forest community.


Project Partners
This project will be supervised by Dr Elva Robinson, University of York and Dr Adria LeBoeuf, https://www.unifr.ch/bio/en/groups/leboeuf-group/, University of Fribourg. The work will be in partnership with site managers The National Trust to ensure management information is disseminated effectively.


More information
To discuss suitability for the project, contact elva.robinson@york.ac.uk; details on the Biology Department’s MSc by Research programme and how to apply can be found here: http://www.york.ac.uk/biology/postgraduate/#tab-298035-3



Post-doctoral research opportunities


Dynamic ant networks: How environmental constraints and ecological context shape resource transport systems


Funding: Fully-funded, NSF, post for 9 months in first instance.


Background
The goal of the project is to develop a general theory for how environmental constraints and opportunities shape dynamic transport networks in biological systems. The project seeks to create a unifying modelling framework predicting how biological transport systems respond dynamically and adaptively to environmental pressures, balancing competing priorities such as cost, efficiency and robustness. This new model will be parameterised with existing data from Formica wood ants and newly collected data from Cephalotes turtle ants, and used to make broad testable predictions about the organisation of biological transport systems.


Team
The post holder will join the team of the National Science Foundation project “Dynamic ant networks: How environmental constraints and ecological context shape resource transport systems”. This international team is led by Matina Donaldson-Matasci, Harvey Mudd College, USA, Scott Powell, George Washington University, USA, and Elva Robinson, University of York, UK. The post holder will be based in the Department of Biology at the University of York under direct supervision of Elva Robinson.


More information
To discuss suitability for the project, contact elva.robinson@york.ac.uk; more information and details of how to apply can be found here: https://jobs.york.ac.uk/vacancy/research-associate-482101.html. Application deadline, 13th May 2022

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Personal profile

Research interests

Social structure in animal groups affects how robust a population is to stresses such as disease, disturbance by humans, or habitat fragmentation. Effects of environmental change on animal social structure are challenging to study but have wide reaching implications for conservation and management. I use ants as a model system which can be manipulated at both the individual and group levels, allowing thorough exploration of the rules governing social behaviour and interaction with the environment. Understanding social structure is essential to for the conservation of any social species, and is also essential for successful control of those social species which have become invasive pests. I use a range of ant species for my research, including the ecologically dominant Formica rufa group wood ants and the invasive garden ant, Lasius neglectus.

I combine controlled lab experiments, field experiments in a more natural context, and computational/analytical modelling, to investigate the organisation of social behaviours and how these relate to environmental conditions and change. I used radio-frequency identification technology to gain individual-level insights into the roles of certain ants within a colony. I collaborate on the analysis of complex patterns of behaviour with other members of the York Centre for Complex Systems Analysis (YCCSA). This work will help explain the mechanisms of organisation and resilience to change in a highly successful group of insects, which will provide insights into the workings of other animal social systems, and even into man-made network systems.

Network

Recent external collaboration on country/territory level. Dive into details by clicking on the dots or