Abstract
Although most genetic estimates of contemporary effective population size (Ne) are based on models that assumeNeis constant, in real populationsNechanges (often dramatically) over time, and estimates (N̂e) will be influenced byNein specific generations. In such cases, it is important to properly match N̂eto the appropriate time periods (for example, in computingNe/Nratios). Here I consider this problem for semelparous species with two life histories (discrete generations and variable age at maturity — the ‘salmon’ model), for two different sampling plans, and for estimators based on single samples (linkage disequilibrium, heterozygote excess) and two samples (temporal method). Results include the following.Discrete generations: (i) Temporal samples from generations 0 andtestimate the harmonic meanNein generations 0 throught − 1 but do not provide information aboutNein generationt; (ii) Single samples provide an estimate ofNein the parental generation, not the generation sampled; (iii) single‐sample and temporal estimates never provide information aboutNein exactly the same generations; (iv) Recent bottlenecks can downwardly bias estimates based on linkage disequilibrium for several generations.Salmon model: (i) A pair of single‐cohort (typically juvenile) samples from years 0 andtprovide a temporal estimate of the harmonic mean of the effective numbers of breeders in the two parental years (Nb(0)andNb(t)), but adult samples are more difficult to interpret because they are influenced byNbin a number of previous years; (ii) For single‐cohort samples, both one‐sample and temporal methods provide estimates ofNbin the same years (contrast with results for discrete generation model); (iii) Residual linkage disequilibrium associated with past population size will not affect single‐sample estimates ofNbas much as in the discrete generation model because the disequilibrium diffuses among different years of breeders. These results lead to some general conclusions about genetic estimates ofNein iteroparous species with overlapping generations and identify areas in need of further research.