Abstract
There is enduring debate over the question of which early-life effects are adaptive and which ones are not. Mathematical modelling shows that early-life effects can be adaptive in environments that have particular statistical properties, such as reliable cues to current conditions and high autocorrelation of environmental states. However, few empirical studies have measured these properties, leading to an impasse. Progress, therefore, depends on research that quantifies cue reliability and autocorrelation of environmental parameters in real environments. These statistics may be different for social and non-social aspects of the environment. In this paper, we summarize evolutionary models of early-life effects. Then, we discuss empirical data on environmental statistics from a range of disciplines. We highlight cases where data on environmental statistics have been used to test competing explanations of early-life effects. We conclude by providing guidelines for new data collection and reflections on future directions.This article is part of the theme issue ‘Developing differences: early-life effects and evolutionary medicine'.
Highlights
Early-life effects are widely observed in nature, from tiny Daphnia to long-lived humans
We argue that the social environment may be relevant to the evolution of early-life effects, because it is likely to have the prerequisite properties of variability over evolutionary time, but considerable stability over developmental time
We look forward to future studies that measure the lived experiences of animals over their entire juvenile periods, or even longer, as these will provide a rich source of information relevant to formal models of early-life effects
Summary
Early-life effects are widely observed in nature, from tiny Daphnia to long-lived humans. These models all find conditions under which it could potentially be adaptive to use early experience to set the adult phenotype Whether it is fitness-enhancing to do so or not always depends on the assumed statistical properties of the environment, as well as assumptions about the properties of the organisms. Burgess & Marshall [34,35] have analysed the role of environmental predictability in shaping adaptive maternal effects and the evolution of life histories, formally and empirically Because of their focus on maternal effects in particular, their analyses emphasize the statistics of non-social environments across generations, such as correlations between parent and offspring conditions (e.g. in temperature or rainfall).
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