1. A case for environmental statistics of early-life effects
- Author
-
Daniel Nettle, Willem E. Frankenhuis, and Sasha R. X. Dall
- Subjects
0106 biological sciences ,History ,Evolution ,Development ,Biostatistics ,Social Development ,010603 evolutionary biology ,01 natural sciences ,Models, Biological ,General Biochemistry, Genetics and Molecular Biology ,Fetal Development ,03 medical and health sciences ,Early-life effects ,Sensitive periods ,evolution ,sensitive periods ,Humans ,Environmental statistics ,development ,030304 developmental biology ,0303 health sciences ,Articles ,environmental statistics ,Data science ,Adaptation, Physiological ,Biological Evolution ,Early life ,Opinion Piece ,early-life effects ,General Agricultural and Biological Sciences - 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'.
- Published
- 2019