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Complex Ecological and Evolutionary Systems

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Opportunities

Opportunities

I do not currently have any funded positions, however there are several personal awards available in Ireland (e.g. IRC) that allow people to pursue a PhD or post-doctoral research through scholarships and fellowships. I am happy to consider top-quality applicants who can find their own source of funding.

I am always keen to hear from highly qualified prospective PhD students (generally in theoretical ecology / evolution but I expand on potential topics below) to apply for funding from the Irish Research Council - submission late 2015. The IRC fund 4-year PhD fellowships which cover a €16,000p.a. stipend, tuition fees and research costs.  The IRC is competitive and uses the calibre of the student as one of their main assessment criteria, therefore excellent grades, research experience and publications will improve chances of success.  The next call for applications will likely be November 2015 with a deadline in January 2016, this would allow the student to start their PhD in September 2016.  Applications are submitted by the prospective student together with their supervisor.


Evolution and Ecology of Information Processing in Animal behaviour

I am broadly interested in how animals acquire, process, and act upon information they obtain from their environment in complex situations such as predator-prey scenarios and social situations. My research group predominantly uses computational, mathematical and statistical models to study these systems. Examples include: evolving artificial neural networks playing iterated prisoner’s dilemma; evolutionary game theory; individual agent based models of vulture and gannet foraging; comparative analyses of “perception of time” abilities across vertebrate species. Several researchers in my team have combined modelling with experimental behavioural work and data analysis to test their hypotheses. I am open to suggestions if someone has specific ideas (preferably but not exclusively with some modelling element) about what they want to do, but some more specific directions this project could take include:


Predator-prey interactions

close up photo of a human eye with a clock superimposed on the iris

How do limits on ability to acquire and process information on your opponent in predator-prey interaction drive selection of strategies to maximise survival and what are the ecological consequences of these contraints? We have already shown that variation in the ability of animals' visual systems to perceive dynamic temporal information (such as for example the movement of your opponent) scales with both body mass and metabolic rate. I am very interested in exploring what this means in terms of constraining predator-prey interactions by body mass in an ecological sense. Some very large animals feed on very small prey, while more typically, they are more closely matched in body mass. In a more evolutionary sense, selection pressures on their visual systems, physiology, anatomy and behavioural strategies are all likely constrained by body mass in some way, and I am interested in explroing the co-evolution of these games of survival. Very interseting to me in t his context is this esssay by Floreano and Keller on the Evolutionary of Adaptive Behaviour in Robots by Means of Darwinian Selection.

I would be very keen to develop models of predator-prey chases that include artificial neural networks to model the cognitive limitations of tracking your opponent in light of the correlated body size scaling of maneuverability and maximum speed.

Healy, K., McNally, L., Ruxton, G.D., Cooper, N. & Jackson, A.L. 2013. Metabolic rate and body size linked with perception of temporal information. Animal Behaviour, 86(4), 685-696 doi. This paper got a lot of media coverage, including BBC news - a fuller list available from Luke McNally and collated in a media book from our press office. It was also highlighted in the editorial of the same issue.

Tosh, C.R.T., Jackson, A.L. & Ruxton, G.D. 2006. The confusion effect in predatory neural networks. American Naturalist 167, E52-E65. doi

Evolution and maintenance of cooperation

stylised image of a brain inside a human head in profile

Explaining how cooperative behaviours evolve and are maintained in social groups is challenging, as theory predicts that selfish acting invididuals will tend to bring about the downfall of cooperators. We have been working on how intelligence is positively associated with cooperative behaviour using classic games such as the Iterated Prisoner's Dilemma and the Iterated Snowdrift Game. To study this system, we built artificial neural networks capable of storing information on groupmates' previous behaviour and integrating across this information to inform current behaviour in this social setting. We then allowed these artificial brains to evolve in an evolutionary genetic algorithm and observed the spontaneous evolution of cooperation in tandem with investment in energetically costly intelligence, providing support for the social brain hypothesis. We have also used game theory models to show that tactical deception, the ability to misrepresent the state of the world to another, can be sustained in an evolutionary sense through the exploitation of conditional cooperators who possess flexible behaviours whose benefit is being able to spot potential cheaters.

There are lots of options to take these lines of research further and in new directions, for example the artificial neural networks have enormous potential to further explore the additional benefits intelligence might offer in terms of deception, network formation (associative grouping) and social eaves-dropping among other mechanisms.

McNally, L., Jackson, A.L. 2013. Cooperation creates selection for tactical deception. Proceedings of the Royal Society of London B, 280(1762), doi Some associated media coverage: ABC Science, A nice blog post from Prof Rob Brooks, we even got the attention of some creationists and were awarded a "Darwin Balony medal" (see also my own blog post in reply)... im quite proud of this!

McNally, L., Brown, S.P. & Jackson, A.L. 2012. Cooperation and the evolution of intelligence. Proceedings of the Royal Society of London B, 279, 3027-3034. doi (Open Access). Some associated media coverage: Discovery News,Science News & Live Science.


Social foraging

photo of african white backed vulture, Gyps africanus

There are many potential benefits to being part of a group, and locating food is one often mentioned and obvious benefit. There are however costs involved, as competition for food can arise and counteract the benefit of finding it in the first place. Furthermore, the behavioural mechanisms used to obtain this informatoin from groupmates is not always obvious, and there are various routes to both active and passive forms of information sharing. We have been developing individual agent based computer simulation models of social foraging to understand how this complex system of interactions affects both the ecology of various species and also to understand the selection pressures that changes in individuas' behaviours has on group members. We have been focussing on the social foraging of vultures to better understand how conservation efforts might be designed to improve foraging efficiency and hence surivival in these threatened species of gyps vultures (Jackson et al 2008; Dermody et al 2011). We are currently working on a game theory model of the producer-scrounger game potentially at play between raptors and vultures, which has consequences for ecosystem based conservation efforts. Recently we adapted our foraging model to idenfity the behavioural rules foraging gannets are using to locate food. This is a particularly interesting system as massive colonies of these gannets that are geographically close forage with almost little or no overlap at all. The explanation comes down to information transfer at the colony. We have recently been adapting these models further to explore the efficacy of scavenging in dinosaurs.

For this project, I would be intersted in developing more evolutionary models of social foraging behaviour in order to understand where the selection pressures are, and what behavioural strategies maximise fitness.

Dermody, B.J.Tanner, C.J. Jackson, A.L. 2011. The evolutionary pathway to obligate scavenging in Gypsvultures. PLoS ONE 6(9) e24635. doi (Open Access)

Jackson, A.L., Ruxton, G.D. & Houston, D.C. 2008. The effect of social facilitation on foraging success in vultures: a modelling study. Biology Letters 4(3) 311-313. doi

Wakefield, E.D., Bodey, T.W., Bearhop, S., Blackburn, J., Colhoun, K., Davies, R., Dwyer, R.G., Green, J., Grémillet, D.,Jackson, A.L., Jessopp, M.J., Kane, A., Langston, R.H.W., Lescroël, A., Murray, S., Le Nuz, M., Patrick, S.C., Péron, C., Soanes, L., Wanless, S., Votier, S.C., & Hamer, K.C. 2013. Space Partitioning Without Territoriality in Gannets. Science, 341(6141), 68-70. doi

 


Last updated 22 April 2015 by SHASSETT@tcd.ie.