A model-derived short-term estimation method of effective size for small populations with overlapping generations

Annegret Grimm, Bernd GRUBER, Marion Hoehn, Katrin Enders, Klaus Henle

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5 Citations (Scopus)


If not actively managed, small and isolated populations lose their genetic variability and the inbreeding rate increases. Combined, these factors limit the ability of populations to adapt to environmental changes, increasing their risk of extinction. The effective population size (N e) is proportional to the loss of genetic diversity and therefore of considerable conservation relevance. However, estimators of N e that account for demographic parameters in species with overlapping generations require sampling of populations across generations, which is often not feasible in long-lived species. We created an individual-based model that allows calculation of N e based on demographic parameters that can be obtained in a time period much shorter than a generation. It can be adapted to every life-history parameter combination. The model is freely available as an r-package NEff. The model was first used in a simulation experiment observing changes in N e in response to different degrees of generational overlap. Results showed that increased generational overlap slowed annual rates of heterozygosity loss, resulting in higher annual effective sizes (N y) but decreased N e per generation. Adding the effect of different recruitment rates only affected N e for populations with low generational overlap. The model was further tested using real population data of the Australian arboreal gecko Gehyra variegata. Simulation results were compared to genetic analyses and matched estimates of the real population very well. Unlike other estimation methods of N e, NEff neither requires long time series of population monitoring nor genetic analyses of changes in gene frequencies. Thus, it seems to be the first method for calculating N e within short time periods and comparably low costs facilitating the use of N e in applied conservation and management.

Original languageEnglish
Pages (from-to)734-743
Number of pages10
JournalMethods in Ecology and Evolution
Issue number6
Publication statusPublished - 2016


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