The plastic fly: the effect of sustained fluctuations in adult food supply on life-history traits.
Bottom Line: Remarkably, both the manner and extent to which life-history traits varied in relation to food depended on whether flies initially experienced high or low food after eclosion.We therefore conclude that the expression of life-history traits in adult life is affected not only by adult plasticity, but also by early adult life experiences.This is an important but often overlooked factor in studies of life-history evolution and may explain variation in life-history experiments.
Affiliation: Laboratory of Genetics, Wageningen University, Wageningen, The Netherlands; Evolutionary Biology Group, Leiden University, Leiden, The Netherlands; Institute for Ageing and Health, Newcastle University, Campus for Aging and Vitality, Newcastle Upon Tyne, UK.Show MeSH
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Mentions: In Exp #2, we also measured the egg production for each female at every transfer. A visual inspection of the data clearly indicates that the relationship between age and number of eggs is not linear (Fig.6). Therefore, we first tested what the best fit was for the data using a polynomial model with Poisson errors. This was first performed with a GLM (therefore without individual as a random factor). Using AIC as test for improvement of the model, a polynomial model with terms with an exponent of 15 was the best fit, including all (and significant) two-way interactions between age, food, yoyo and start treatments. A GLMM (therefore including individual as random effect) verified that a polynomial model of age with high exponent number was the most significant, whereas the AIC was already lower for a linear model with individuals as random effect compared to the polynomial with exponent 15 without individual as random effect. Further verification of the interaction was performed by fitting a GAM, which uses smoothing functions over a covariate rather than terms for polynomial functions. The best model was one with specific smoothers for every separate food level in every food treatment for the yoyo groups and start treatment for the constant groups, indicating that flies respond differently to food dependent on yoyo treatment and initial vial food level (Table S4). This is the outcome of three separate different statistical models and therefore is perceived to be a robust outcome of the analysis. Therefore, egg number was affected by food level, yoyo treatment, initial adult food level treatment and age. In addition, how flies responded to food was dependent on age, yoyo treatment and initial food treatment (i.e. their interactions). For instance, although on low food the yoyo flies always produced more eggs on average, the difference between egg number on low and high food on consecutive time points is larger in slow yoyo flies compared to fast yoyo flies, and larger for flies that started on low food (for SYL; 27.19, SYH; 25.78, FYL; 16.41, FYH; 13.69 eggs more on low food). Furthermore, as flies get older, they first increase and decrease in plasticity (Fig.6). Lastly, the improvement of explanatory variation from a GLM to a GLMM indicates that there is substantial variation among individuals. The average number of eggs per individual on both the high and the low food varies between individuals, resulting in more eggs on low food for most, but not all individuals (Fig. S2).
Affiliation: Laboratory of Genetics, Wageningen University, Wageningen, The Netherlands; Evolutionary Biology Group, Leiden University, Leiden, The Netherlands; Institute for Ageing and Health, Newcastle University, Campus for Aging and Vitality, Newcastle Upon Tyne, UK.