There are four main research directions in the Group of Evolving Interactions.
Direction 1
Focuses on the effects of higher-order multi-player biological interactions on collective behavior and the maintenance of coexistence in spatially heterogeneous and temporally varying metacommunities. The research questions are motivated by pressing environmental and socioeconomic problems such as the transmission of pathogens by carrier species (e.g., the transmission of avian influenza to humans and farmed poultry by migrating birds). We combine evolutionary game theoretic modeling and lab experiments in microbial systems to make predictions about the effects of dispersal rates, habitat network structure and connectivity, and environmental fluctuations on coexistence that can be tested in diverse metacommunities of animals and microorganisms.
Direction 2
Focuses on developing Evolutionary Game Theory models to understand collective animal behaviors in changing social and natural environments, such as the initiation and resolution of intergroup conflicts in primates, the coevolution of sex-biased dispersal and mating system under the impact of climate change, and the evolution of social competence (e.g., the ability to take another’s perspective and adaptively change behavior according to the situation) in group-living animals. The distinct innovation of the project is to expand Evolutionary Game Theory to investigate an unexplored area of changing social and natural environments, besides answering outstanding open questions in collective animal behaviour. The success of the project will lead to a paradigm shift in the focus of Evolutionary Game Theory from the analysis of evolutionarily stable strategy (ESS) to stochastic temporal dynamics that are more relevant in the imminent timescale.
Direction 3
Focuses on the fundamental structure and components of Evolutionary Game Theory. While the theoretical framework has been powerful in studying frequency-dependent interactions, it is also surprisingly incomplete. It often ignores fundamental features of biology, such as sex and age, and is consequently unable to capture the effects of sexual reproduction, age/stage-dependent behaviours, and reproduction-survival tradeoffs. Considering that many prominent study systems of evolutionary games, including humans, are sexually reproducing and have overlapping generations, the current theoretical framework struggles to handle the growing complexity of empirical work. Therefore, there is a pressing need to extend the scope of Evolutionary Game Theory and enrich it by incorporating relevant biological factors, such as sex and age. To do so, we will systematically introduce age structure and sex into classic evolutionary game models (e.g., Prisoner’s Dilemma, Hawk-Dove games, etc.) step by step. Because the evolutionary dynamics of these classic games have been thoroughly worked out, we can isolate the effect of the additional biological factors conveniently by comparing our new results with their classic counterparts.
Direction 4
Focuses on developing real-world applications of Evolutionary Game Theory models and performing wet-lab experiments to predict and manipulate microbial interactions. One project we are working on is the bioremediation of polluted soils by bacteria and fungi. We combine modelling and experiments to optimize the efficiency of bacterial dispersal and their ecosystem functions in the soil ecosystem. Another project we are planning to work on is the biocontrol of pathogens by applying protective bacteria in ripening raw milk cheeses. The ripening cheese rind is an excellent model of bacterial-fungal interaction because it is featured in highly repeatable community dynamics with a limited number of bacterial and fungal strains. We aim to predict and suppress the growth and spread of the pathogenic bacterium Listeria monocytogenes by artificially supplementing a protective bacterium under different cheese ripening conditions, and to optimize for the timing and quantity of supplementation of the bio-control agent.
