J Jackson2; I Friberg2; N Masud1; A Stewart3; J Cable1;
1 Cardiff University, UK; 2 University of Salford, UK; 3 University of Surrey, UK
DiscussionIt is increasingly recognized that immunity in vertebrates is highly plastic and driven by the environment. Many studies have found piecemeal effects of individual environmental variables on immunity, but we lack a quantitative, mechanistic understanding of how different environmental players combine to regulate immune allocation and defence against infection in real-world situations. Using a systems biology-like approach and a combination of intensive field monitoring at multiple sites, mesocosm experiments and laboratory experiments, we have begun to dissect the main environmental variables that drive immune allocation and defence in wild 3-spined sticklebacks (Gasterosteus aculeatus). We have chosen this natural system because it allows us to work with genuinely wild animals in the field and with animals as close to a wild phenotype as realistically achievable in experiments (wild fish that very easily acclimate to semi-natural mesocosms or laboratory tanks). Importantly, we focus on seasonal effects as a proxy for environmental effects in general. Season reflects a major environmental axis that tends to influence all individuals in a population the same way - and whose effects may thus be appropriately addressed at a population level. Based on our field monitoring and matched experiments we have very firm results indicating that temperature drives much of the seasonal immune variation and variance in disease resistance observable in the field - up to about 50% in more stable still-water habitats. We report further experimental results demonstrating a major effect of season-specific diet that qualitatively re-capitulates immunophenotypic changes seen seasonally in the field. When these effects and thermal effects (both estimated in the experiments) are quantitatively combined with field records of diet and temperature, using an inverse modelling approach, we are able to predict the great majority of seasonal immune variance in still-water natural habitats.