Early mortality saves energy: estimating the energetic cost of excess offspring in a seabird

Abstract

Offspring are often produced in excess as insurance against stochastic events or unpredictable resources. This strategy may result in high early-life mortality, yet age-specific mortality before offspring independence and its associated costs have rarely been quantified. In this study, we modelled age-specific survival from hatching to fledging using 24 years of data on hatching order (HO), growth and age of mortality of more than 15 000 common tern (Sterna hirundo) chicks. We found that mortality peaked directly after hatching, after which it declined rapidly. Mortality hazard was best described with the Gompertz function, and was higher with later HO, mainly due to differences in baseline mortality hazard, rather than age-dependent mortality. Based on allometric mass-metabolism relationships and detailed growth curves of starving chicks, we estimated that the average metabolizable energy intake of non-fledged chicks was only 8.7% of the metabolizable energy intake of successful chicks during the nestling phase. Although 54% of hatchlings did not fledge, our estimates suggest them to have consumed only 9.3% of the total energy consumption of all hatched chicks in the population before fledging. We suggest that rapid mortality of excess offspring is part of an adaptive brood reduction strategy to the benefit of the parents.

Telomere attrition and growth: a life‐history framework and case study in common terns

“…In particular, long-lived species living in stochastic environments may benefit from rapid mortality of excess offspring under unfavourable conditions, as the allocation of resources to the offspring with the best prospects may yield larger fitness benefits if the lifespan of those offspring is largely determined by their somatic state, rather than by extrinsic causes of mortality (O. Vedder & S. Bouwhuis, unpublished results). In these species, canalization of investment in telomere maintenance, and not growth, may indeed be the strategy with the highest fitness return, even when it entails a rapid mortality for the offspring that hatched in unfavourable conditions (Vedder et al, 2017). In shorter-lived species, selection for growth and telomere maintenance may be more balanced, predicting positive covariance between the traits under circumstances of heterogeneity in resource acquisition.…”

“…We predicted that (i) both telomere length and body mass should be positively affected by resource acquisition, and thus negatively related to hatching order. However, both traits may not be equally affected by resource acquisition, and as in our study population, nearly all chick mortality is due to starvation (Vedder et al ., ), we also predicted that (ii) the trait most sensitive to resource availability should be the best predictor of survival. Moreover, we predicted that (iii) the trait least affected by hatching order should show less variation between individuals, as indicative of it being insensitive to resource variation in general (i.e.…”

Age-Specific Offspring Mortality Economically Tracks Food Abundance in a Piscivorous Seabird

“…They lay small clutches of one to three eggs, with egg size decreasing and eggs hatching asynchronously in the order of laying (Nisbet and Cohen 1975;Bollinger 1994;Garcia et al 2011). Survival of hatchlings to fledging is highly variable and heavily dependent on hatching order (Langham 1972;Bollinger 1994;Vedder et al 2017) and food abundance (Dänhardt and Becker 2011). We have previously shown that the agespecific chick mortality hazard is best described by a Gompertz function (Vedder et al 2017).…”

“…Survival of hatchlings to fledging is highly variable and heavily dependent on hatching order (Langham 1972;Bollinger 1994;Vedder et al 2017) and food abundance (Dänhardt and Becker 2011). We have previously shown that the agespecific chick mortality hazard is best described by a Gompertz function (Vedder et al 2017). The Gompertz hazard function is defined by parameters a, b, and time t:…”

“…Differences in fledging success may thus arise from effects on baseline mortality (a) and/or effects on how fast mortality changes with age (b). Although the same fledging success can result from different combinations of a and b, these combinations may have different consequences for the amount of energy the nonsurviving chicks have consumed before their death (Vedder et al 2017).…”