Demographic stochasticity can drive population variability even in large populations

Demographic stochasticity is generally expected to contribute little to population variability when census abundance is large, because random demographic events are increasingly averaged across many individuals. This expectation, however, depends on how evenly individuals contribute to reproduction. In many natural populations, reproductive success is highly skewed, so that a large census population can coexist with a much smaller effective number of breeders (Nb). Although Nb is commonly used as a genetic measure of contemporary effective size, it also summarizes variation in reproductive contribution and may therefore contain information about demographic variability. Here, we develop a female-based age-structured theoretical framework linking Nb to temporal variability in mature population abundance, with N denoting the census number of mature females and Nb the effective number of female breeders. Recruitment variability arises from non-Poisson reproductive variation and environmental stochasticity, and its transmission to mature abundance is described by a life-history coefficient, {gamma}, determined by survival, maturation, and the contribution of overlapping cohorts. When the Poisson component of recruitment variance is negligible and Nb/N is sufficiently small, the coefficient of variation in mature abundance, CV[N], can be approximated from Nb, environmental variability, and {gamma}, with little additional information from census abundance. This approximation does not require specification of the functional form of the relationship between adult abundance and recruitment. Stochastic age-structured simulations closely reproduced the analytical prediction, even when additional demographic stochasticity in survival was included. Substantial fluctuations in mature abundance occurred at census sizes on the order of 105 when Nb was small, whereas overlapping cohorts buffered recruitment fluctuations. Because Nb can be estimated genetically from samples of a single cohort, the framework provides a direct link between genetic monitoring and population dynamics. More broadly, these results show that large census abundance alone does not guarantee weak demographic variability and highlight the potential of genetic data to inform expected population fluctuations when detailed demographic information is limited.