Open AccessRelationship between effective and demographic population size in continuously distributed populations
Author(s) -
Pierson Jennifer C.,
Graves Tabitha A.,
Banks Sam C.,
Kendall Katherine C.,
Lindenmayer David B.
Publication year - 2018
Publication title -
evolutionary applications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.776
H-Index - 68
ISSN - 1752-4571
DOI - 10.1111/eva.12636
Subject(s) - biology , effective population size , biological dispersal , context (archaeology) , population , metric (unit) , population size , estimation , statistics , abundance (ecology) , sample size determination , mark and recapture , evolutionary biology , ecology , econometrics , genetic variation , demography , mathematics , paleontology , operations management , management , sociology , economics
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, N e . We used four long‐term genetic and demographic studies (≥9 years) to evaluate the temporal stability of the relationship between N e and demographic population size ( N c ). These case studies focused on mammals that are continuously distributed, yet dispersal‐limited within the spatial scale of the study. We estimated local, contemporary N e 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 N e varied widely within each case study suggesting interpretation of estimates is challenging. We found inconsistent correlations and trends both among estimates of N e and between N e and N c suggesting the value of N e as an indicator of N c is limited in some cases. In the two case studies with consistent trends between N e and N c , F IS was more stable over time and lower, suggesting F IS may be a good indicator that the population was sampled at a spatial scale at which genetic structure is not biasing estimates of N e . These results suggest that more empirical work on the estimation of N e in continuous populations is needed to understand the appropriate context to use LDN e as a useful metric in a monitoring programme to detect temporal trends in either N e or N c .