Testing the predictions of energy allocation decisions in the evolution of life‐history trade‐offs

Abstract

Summary Allocating a greater amount of limited resources, such as energy, to current reproduction can reduce the amount of energy available for somatic maintenance and can ultimately impair future breeding success or maternal survival (i.e. cost of reproduction hypothesis). Although there is some support for the cost of reproduction hypothesis in birds, few empirical studies of mammals have demonstrated a trade‐off between current and future reproduction. More importantly, most studies testing ultimate costs have neglected to confirm that the proximate costs of reproduction are high. We experimentally manipulated litter size in a wild population of Columbian ground squirrels for 2 years to examine both the proximate energetic and ultimate fitness (i.e. survival and breeding) costs of reproduction. We predicted that females raising augmented litters would have the highest rates of daily energy expenditure and as a result would experience lower survival rates or future fecundity. Females raising augmented litters weaned more pups, had the highest litter masses at weaning, and had field metabolic rates that were almost 1·5 times greater than females raising control or reduced litters. Contrary to our prediction, there were no negative impacts of greater maternal investment and higher energy expenditure on the probability of maternal survival or future reproduction. Pups from augmented litters grew more slowly during the lactation period were smaller at weaning and had a lower probability of survival over‐winter. Thus, although females were capable of raising more young than they gave birth to without short‐term costs of reduced survival or fecundity, our observations suggest that limitations to litter size are not due to a trade‐off in the allocation of energy, but rather due to the reduced survival of offspring from larger litters. Examining the proximate mechanisms hypothesized to underlie life‐history trade‐offs can be challenging but is critical for a comprehensive understanding of the evolution of life histories.