Life history and the ecology of stress: how do glucocorticoid hormones influence life-history variation in animals?

Glucocorticoids hormones (GCs) are intuitively important for mediation of age-dependent vertebrate life-history transitions through their effects on ontogeny alongside underpinning variation in life-history traits and trade-offs in vertebrates. These concepts largely derive from the ability of GCs to alter energy allocation, physiology and behaviour that influences key life-history traits involving age-specific life-history transitions, reproduction and survival. Studies across vertebrates have shown that the neuroendocrine stress axis plays a role in the developmental processes that lead up to age-specific early life-history transitions. While environmental sensitivity of the stress axis allows for it to modulate the timing of these transitions within species, little is known as to how variation in stress axis function has been adapted to produce interspecific variation in the timing of life-history transitions. Our assessment of the literature confirms that of previous reviews that there is only equivocal evidence for correlative or direct functional relationships between GCs and variation in reproduction and survival. We conclude that the relationships between GCs and life-history traits are complex and general patterns cannot be easily discerned with current research approaches and experimental designs. We identify several future research directions including: (i) integration of proximate and ultimate measures, including longitudinal studies that measure effects of GCs on more than one life-history trait or in multiple environmental contexts, to test explicit hypotheses about how GCs and life-history variation are related and (ii) the measurement of additional factors that modulate the effects of GCs on life-history traits (e.g. GC receptors and binding protein levels) to better infer neurendocrine stress axis actions. Conceptual models of HPA/I axis actions, such as allostatic load and reactive scope, to some extent explicitly predict the role of GCs in a life-history context, but are descriptive in nature. We propose that GC effects on life-history transitions, survival probabilities and fecundity can be modelled in existing quantitative demographic frameworks to improve our understanding of how GC variation influences life-history evolution and GC-mediated effects on population dynamics Lay Summary Functional Ecology