Northwest Fisheries Science Center

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Document Type: Journal Article
Center: NWFSC
Document ID: 4799
Title: Intermittent breeding and constraints on litter size:  consequences for effective population size per generation (Ne) and per reproductive cycle (Nb)
Author: Robin S. Waples, Tiago Antao
Publication Year: 2014
Journal: Evolution
Volume: 68
Issue: 6
Pages: 1722-1734
Keywords: overlapping generations,reproductive succes,litter size,computer simulations,vital rates

In iteroparous species, it is easier to estimate Nb (effective number of breeders in one reproductive cycle) than Ne (effective population size per generation).  Nb can be used as a proxy for Ne and also can provide crucial insights into eco-evolutionary processes that occur during reproduction.  We used analytical and numerical methods to evaluate effects of intermittent breeding and litter/clutch size on inbreeding Nb and Ne.  Fixed or random litter sizes ≥ 3 have little effect on either effective-size parameter; however, in species (e.g., many large mammals) in which females can produce only one offspring per cycle, female Nb = ∞ and overall Nb = 4Nb(male).  Intermittent breeding reduces the pool of female breeders, which reduces both female and overall Nb; reductions are larger in high-fecundity species with high juvenile mortality and increase when multiple reproductive cycles are skipped.  Simulated data for six model species showed that both intermittent breeding and litter-size constraints increase Ne, but only slightly.  We show how to quantitatively account for these effects, which are important to consider when (1) using Nb to estimate Ne, or (2) drawing inferences about male reproductive success based on estimates of female Nb.

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Theme: Recovery, Rebuilding and Sustainability of Marine and Anadromous Species
Foci: Characterize vital rates and other demographic parameters for key species, and develop and improve methods for predicting risk and viability/sustainability from population dynamics and demographic information.
Develop methods to use physiological and biological information to predict population-level processes.