Relationship between effective and demographic population size in continuously distributed populations

Jennifer C. Pierson*, Tabitha A. Graves, Sam C. Banks, Katherine C. Kendall, David B. Lindenmayer

*Corresponding author for this work

    Research output: Contribution to journalArticlepeer-review

    15 Citations (Scopus)

    Abstract

    Genetic monitoring of wild populations can offer insights into demographic and genetic information simultaneously. However, widespread application of genetic monitoring is hindered by large uncertainty in the estimation and interpretation of target metrics such as contemporary effective population size, Ne. We used four long-term genetic and demographic studies (≥9 years) to evaluate the temporal stability of the relationship between Ne and demographic population size (Nc). These case studies focused on mammals that are continuously distributed, yet dispersal-limited within the spatial scale of the study. We estimated local, contemporary Ne with single-sample methods (LDNE, Heterozygosity Excess, and Molecular Ancestry) and demographic abundance with either mark–recapture estimates or catch-per-unit effort indices. Estimates of Ne varied widely within each case study suggesting interpretation of estimates is challenging. We found inconsistent correlations and trends both among estimates of Ne and between Ne and Nc suggesting the value of Ne as an indicator of Nc is limited in some cases. In the two case studies with consistent trends between Ne and Nc, FIS was more stable over time and lower, suggesting FIS may be a good indicator that the population was sampled at a spatial scale at which genetic structure is not biasing estimates of Ne. These results suggest that more empirical work on the estimation of Ne in continuous populations is needed to understand the appropriate context to use LDNe as a useful metric in a monitoring programme to detect temporal trends in either Ne or Nc.

    Original languageEnglish
    Pages (from-to)1162-1175
    Number of pages14
    JournalEvolutionary Applications
    Volume11
    Issue number7
    DOIs
    Publication statusPublished - Aug 2018

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