Relationship between effective and demographic population size in continuously distributed populations. (20th May 2018)

• Record Type: Journal Article
• Authors: Pierson, Jennifer C.; Graves, Tabitha A.; Banks, Sam C.; Kendall, Katherine C.; Lindenmayer, David B.
• Is Part Of: Evolutionary applications. Volume 11:Number 7(2018)
• Page Start: 1162
• Page End: 1175
• Publication Date: 2018-05-20
• Subjects: effective population size -- genetic indicator -- genetic monitoring -- LDNe -- population trends; Evolution (Biology) -- Periodicals; Genetics -- Periodicals; Natural selection -- Periodicals; Ecology -- Periodicals; 576.8
• DOI: 10.1111/eva.12636
• Languages: English
• ISSNs: 1752-4571

Abstract

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 LDNe as a useful metric in a monitoring programme to detect temporal trends in either N e or N c .