Robustness of Hills overlapping-generation method for calculating Ne to extreme patterns of reproductive success

Abstract

For species with overlapping generations, the most widely-used method to calculate effective population size (Ne) is Hills, the key parameter for which is lifetime variance in offspring number (Vk*). Hills model assumes stable age structure and constant abundance, and sensitivity to those assumptions has been evaluated previously. Here I evaluate robustness of Hills model to extreme patterns of reproductive success, whose effects have not been previously examined: 1) very strong reproductive skew; 2) strong temporal autocorrelations in individual reproductive success; and 3) strong covariance of individual reproduction and survival. Genetic drift (loss of heterozygosity and increase in allele-frequency variance) was simulated in age-structured populations using methods that: generated no autocorrelations or covariances (Model NoCor); or created strong positive (Model Positive) or strong negative (Model Negative) temporal autocorrelations in reproduction and covariances between reproduction and survival. Compared to Model NoCor, the other models led to greatly elevated or reduced Vk*, and hence greatly reduced or elevated Ne, respectively. A new index is introduced ({rho},+), which is the correlation between 1) the number of offspring produced by each individual at the age at maturity (), and 2) the total number of offspring produced during the rest of their lifetimes. Mean {rho},+ was {approx}0 under Model NoCor, strongly positive under Model Positive, and strongly negative under Model Negative. Even under the most extreme reproductive scenarios in Models Positive and Negative, when Vk* was calculated from the realized population pedigree and used to calculate Ne in Hills model, the result accurately predicted the rate of genetic drift in simulated populations. These results held for scenarios where age-specific reproductive skew was random (variance{approx}mean) and highly overdispersed (variance up to 20 times the mean). Collectively, these results are good news for researchers as they demonstrate the robustness of Hills model even to extreme repro0ductive scenarios.