AgeStrucNb: Software for simulating and detecting changes in the effective number of breeders (Nb)

Tiago Antao, Ted Cosart, Brian Trethewey, Robin S. Waples, Mike W. Ackerman, Gordon Luikart, Brian K. Hand

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

Estimation of the effective number of breeders per reproductive event (Nb) using single sample DNAmarker- based methods has rapidly grown in recent years. However, estimating Nb is difficult in agestructured populations because the performance of estimators is influenced by the Nb / Ne ratio, which varies among species with different life histories. We provide a computer program, AgeStrucNb, to simulate age-structured populations (including life history) and also estimate Nb. The AgeStrucNb program is composed of 4 major components to simulate, subsample, estimate, and then visualize Nb time series data. AgeStrucNb allows users to also quantify the precision and accuracy of any set of loci or sample size to estimate Nb for many species and populations. AgeStrucNb allows users to conduct power analysis to evaluate sensitivity to detect changes in Nb or the power to detect a correlation between trends in Nb and environmental variables (e.g., temperature, habitat quality, predator or pathogen abundance) that could be driving changes in Nb. The software provides Nb estimates for empirical data sets using the LDNe (linkage disequilibrium) method, includes publication-quality output graphs, and outputs genotype files in Genepop format for use in other programs. AgeStrucNb will help advance the application of genetic markers for monitoring Nb, which will help biologists to detect population declines and growth, which is crucial for research and conservation of natural and managed populations.

Original languageEnglish
Pages (from-to)491-497
Number of pages7
JournalJournal of Heredity
Volume111
Issue number5
DOIs
StatePublished - Jul 1 2020

Keywords

  • Conservation genomics
  • Genetic monitoring
  • Individual-based simulation
  • Population viability

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