Our research aim is to understand the evolution of social behaviour and the way in which this affects population dynamics. A social system defines how individuals in a population interact and includes all relationships of a sexual, agonistic and/or aid-related nature. All group-dwelling animals are influenced by their social environment to some degree, through processes of social stress, phenotypic plasticity, and learning. This can be a great advantage, especially in fast-changing environments, as individuals can benefit from strategies learned and adaptations gained by their parents. It may, however, also present a limiting factor when individuals are shaped by the previous generation to a situation that is no longer present. Consequently, individuals must constantly balance the costs and benefits of social life. Therefore, individuals in social species cannot be understood via their adaptations to the physical and ecological environments alone; their social dimension also needs to be considered.
In empirical studies, we aim to understand how the social environment in which individuals live, and the degree of social interactions between individuals affect individual phenotypes (behaviours), and the consequences this has for fitness. We also aim to identify the genes important for adaptation and contemporary fitness in individuals and populations.
In theoretical studies, we aim to unravel the importance of how changing social environments may bias evolutionary predictions in natural systems. This will have direct applications for evolutionary studies wishing to understand how environmental and social factors influence the evolution of phenotypes in field settings.
Our powerful combination of developing (experimental) field studies, molecular ecology, immunology, endocrinology, theoretical modelling and quantitative genetics will provide novel insights into social evolution, which can be used to inform conservation programs. We focus on natural systems for which we have comprehensive genetic parentage relationships and long-term data. Our main research themes are:
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