Luck can explain the positive link between fecundity and longevity: the Matthew effect in social insects and beyond.
Abstract
The universality of the trade-off between fecundity and longevity in life-history theory is sometimes contested. Social insects present the arguably strongest challenge, as (i) queens not only monopolize reproduction, but also live much longer than workers, and (ii) within a caste, those individuals that lay more eggs are also observed to live longer. Positive fecundity-longevity relationships can appear in observational data even though an underlying trade-off exists, as individual variation in resource acquisition (e.g., variation in habitat quality) can mask the trade-off. Here, we demonstrate theoretically that the fecundity-longevity trade-off in social insects can be easily masked even without differences in individual quality. Demographic stochasticity, caused by variable worker lifespans, leads to self-reinforcing dynamics (equivalent to the well-known Matthew effect), where "lucky" colonies exhibit healthy growth and long-lived, productive queens, while "unlucky" colonies show the opposite combination of traits. Allocation variation between individual queens, if present, can unmask the trade-off in principle, but the trade-off remains commonly concealed not only when measuring fecundity as a cumulative total (a strongly confounded measure as longer-lived queens have more time to produce eggs), but also when measuring fecundity as a rate. Our results help align superorganismal fitness components with general life-history principles, and highlight the necessity of experimental manipulations when making statements regarding trade-offs or the lack thereof.
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Research summary
The paper claims that demographic stochasticity in social insects can mask the fecundity-longevity trade-off, leading to misleading interpretations of longevity and reproductive success. This research is relevant as it explores fundamental biological principles that could inform our understanding of longevity and aging dynamics in broader contexts.
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