Alternative hypotheses linking the immune system and mate choice for good genes

Why do males often have extravagant morphological and behavioural traits, and why do females prefer to mate with such males? The answers have been the focus of considerable debate since Darwin's 'The descent of man, and selection in relation to sex' appeared in 1871. Recently, the broadening of investigation to include fields outside evolutionary biology has shed new light on mate choice and sexual selection. Here, we focus on a specific set of hypotheses relating the biology of resisting disease-causing organisms with the production of condition-dependent sexual signals (advertisements). We present a framework that distinguishes three different hypotheses about trade-offs within the immune system that affect general condition. The original Hamilton & Zuk hypothesis suggests that hosts fight off disease via resistance to particular pathogens, which lowers resistance to other pathogens. Changes in pathogens over evolutionary time in turn favours changes in which genes confer the best resistance. Alternatively, the immunocompetence hypotheses suggest that the energetic costs of mounting a response to any pathogen compete for resources with other things, such as producing or maintaining advertisements. Finally, improving resistance to pathogens could increase the negative impacts of the immune system on the host, via immunopathologies such as allergies or autoimmune diseases. If both disease and immunopathology affect condition, then sexual advertisements could signal a balance between the two. Studies of hypothesized links between genes, condition, the immune system and advertisements will require careful consideration of which hypothesis is being considered, and may necessitate different measures of immune system responses and different experimental protocols

Meta-analysis challenges a textbook example of status signalling and demonstrates publication bias.

The status signalling hypothesis aims to explain within-species variation in ornamentation by suggesting that some ornaments signal dominance status. Here, we use multilevel meta-analytic models to challenge the textbook example of this hypothesis, the black bib of male house sparrows (Passer domesticus). We conducted a systematic review, and obtained primary data from published and unpublished studies to test whether dominance rank is positively associated with bib size across studies. Contrary to previous studies, the overall effect size (i.e. meta-analytic mean) was small and uncertain. Furthermore, we found several biases in the literature that further question the support available for the status signalling hypothesis. We discuss several explanations including pleiotropic, population- and context-dependent effects. Our findings call for reconsidering this established textbook example in evolutionary and behavioural ecology, and should stimulate renewed interest in understanding within-species variation in ornamental traits

Cost of reproduction in a long-lived bird: incubation effort reduces immune function and future reproduction

Life-history theory predicts that increased current reproductive effort should lead to a fitness cost. This cost of reproduction may be observed as reduced survival or future reproduction, and may be caused by temporal suppression of immune function in stressed or hard-working individuals. In birds, consideration of the costs of incubating eggs has largely been neglected in favour of the costs of brood rearing. We manipulated incubation demand in two breeding seasons (2000 and 2001) in female common eiders (Somateria mollissima) by creating clutches of three and six eggs (natural range 3–6 eggs). The common eider is a long-lived sea-duck where females do not eat during the incubation period. Mass loss increased and immune function (lymphocyte levels and specific antibody response to the non-pathogenic antigens diphtheria and tetanus toxoid) was reduced in females incubating large clutches. The increased incubation effort among females assigned to large incubation demand did not lead to adverse effects on current reproduction or return rate in the next breeding season. However, large incubation demand resulted in long-term fitness costs through reduced fecundity the year after manipulation. Our data show that in eiders, a long-lived species, the cost of high incubation demand is paid in the currency of reduced future fecundity, possibly mediated by reduced immune function

Statistical Quantification of Individual Differences (SQuID): an educational and statistical tool for understanding multilevel phenotypic data in linear mixed models

Phenotypic variation exists in and at all levels of biological organization: variation exists among species, among-individuals within-populations, and in the case of l within-populations abile traits, within-individuals. Mixed-effects models represent ideal tools to quantify multilevel measurements of traits and are being increasingly used in evolutionary ecology. Mixed-effects models are relatively complex, and two main issues may be hampering their proper usage: (i) the relatively few educational resources available to teach new users how to implement and interpret them and (ii) the lack of tools to ensure that the statistical parameters of interest are correctly estimated. In this paper, we introduce Statistical Quantification of Individual Differences (SQuID), a simulation-based tool that can be used for research and educational purposes. SQuID creates a virtual world inhabited by subjects whose phenotypes are generated by a user-defined phenotypic equation, which allows easy translation of biological hypotheses into quantifiable parameters. Statistical Quantification of Individual Differences currently models normally distributed traits with linear predictors, but SQuID is subject to further development and will adapt to handle more complex scenarios in the future. The current framework is suitable for performing simulation studies, determining optimal sampling designs for user-specific biological problems and making simulation-based inferences to aid in the interpretation of empirical studies. Statistical Quantification of Individual Differences is also a teaching tool for biologists interested in learning, or teaching others, how to implement and interpret linear mixed-effects models when studying the processes causing phenotypic variation. Interface-based modules allow users to learn about these issues. As research on effects of sampling designs continues, new issues will be implemented in new modules, including nonlinear and non-Gaussian data.Peer Reviewe