Abstract

We discuss the mechanistic (proximate) and selective (ultimate) factors that cause life history trade-offs such as the trade-off between offspring quality and quantity and that between current and future reproduction. We point out that key concepts in life history theory and evolutionary biology such as negative genetic correlations and trade-offs can be understood in terms of physiological mechanisms. More specifically, negative genetic correlations causing trade-offs between life history traits are caused by hormones and their regulatory genes that have multiple and opposing, pleiotropic effects on two or more traits. Consequently, investigations of these mechanisms is a natural complement to the classical population genetical approach. We critically dissect the argument, put forward by other workers, that experimental manipulations of organismal physiology or other phenotypic traits do not reveal genetic life history trade-offs, but only reflects phenotypic plasticity. We reject this idea and discuss the proposed alternative approach: laboratory selection experiments. We point out some problems associated with laboratory selection experiments and suggest that experimental manipulations of life history traits and secondary sexual characters in natural populations is an important and invaluable empirical method if one aims to get a better understanding of life history evolution in the wild. Finally, we discuss the proximate-ultimate dichotomy, the physiology of phylogenetic constraints, the role of physiological mechanisms in population differentiation in life history trade-offs and the importance of phenotypic plasticity in shaping such trade-offs. We suggest that life history plasticity in many cases may stem from the same endocrine mechanisms (gonadotropin, gonadal steroids, and adrenal glucocorticoids) as those involved in life history trade-offs. In particular, attempts to dichotomize life history trade-offs and life history plasticity may be unrealistic as the hormones governing both life history phenomena are likely to share key mechanisms in common.

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