ReMCASA: Constraints on adaptation in social animals: kin recognition mechanisms and the fitness consequences of discrimination rules

The process of evolutionary adaptation is limited by the mechanistic constraints acting on phenotypic traits. We aim to investigate kin recognition mechanisms in a social bird to determine the extent to which they constrain adaptive decision-making, resulting in apparently maladaptive behaviours. Recognition systems are ubiquitous at every level of biological organisation from genes to complex societies, and discrimination in these diverse situations often has major fitness consequences. Therefore, selection should engineer effective recognition mechanisms. However, recognition systems are rarely error-free, so how is the frequency of errors optimised in order to maximise inclusive fitness? We will address this evolutionary puzzle by studying kin recognition mechanisms in a social bird, the long-tailed tit Aegithalos caudatus, whose remarkable kin-selected cooperative breeding system makes them wonderfully well suited to investigation of kin discrimination and its fitness consequences. Long-tailed tits discriminate against close kin as mates and in favour of kin when helping, but make frequent, apparently maladaptive errors in both contexts. We will employ a range of state-of-the-art methods to quantify and analyse metrics of social affiliation and two putative phenotypic cues to kinship, acoustic and olfactory, determining how accurately they encode relatedness information. We will also address the persistent evolutionary problem of how variance in inherited recognition cues is maintained when they are subjected to positive frequency dependent selection (Crozier's paradox). Finally, we will determine the extent to which phenotypic cues and social familiarity are integrated to optimise behavioural decisions, conducting field experiments to directly test that understanding. The outcome will be a major advance in understanding of why maladaptive social behaviours occur, and how errors in a recognition system are optimised to maximise inclusive fitness.