Multiple estimates of effective population size for monitoring a long‐lived vertebrate: an application to Yellowstone grizzly bears

Effective population size (Nₑ) is a key parameter for monitoring the genetic health of threatened populations because it reflects a population's evolutionary potential and risk of extinction due to genetic stochasticity. However, its application to wildlife monitoring has been limited because i...

Full description

Saved in:
Bibliographic Details
Published inMolecular ecology Vol. 24; no. 22; pp. 5507 - 5521
Main Authors Kamath, Pauline L, Haroldson, Mark A, Luikart, Gordon, Paetkau, David, Whitman, Craig, Manen, Frank T
Format Journal Article
LanguageEnglish
Published England Blackwell Scientific Publications 01.11.2015
Blackwell Publishing Ltd
Subjects
Online AccessGet full text

Cover

Loading…
More Information
Summary:Effective population size (Nₑ) is a key parameter for monitoring the genetic health of threatened populations because it reflects a population's evolutionary potential and risk of extinction due to genetic stochasticity. However, its application to wildlife monitoring has been limited because it is difficult to measure in natural populations. The isolated and well‐studied population of grizzly bears (Ursus arctos) in the Greater Yellowstone Ecosystem provides a rare opportunity to examine the usefulness of different Nₑ estimators for monitoring. We genotyped 729 Yellowstone grizzly bears using 20 microsatellites and applied three single‐sample estimators to examine contemporary trends in generation interval (GI), effective number of breeders (Nb) and Nₑ during 1982–2007. We also used multisample methods to estimate variance (NₑV) and inbreeding Nₑ (NₑI). Single‐sample estimates revealed positive trajectories, with over a fourfold increase in Nₑ (≈100 to 450) and near doubling of the GI (≈8 to 14) from the 1980s to 2000s. NₑV (240–319) and NₑI (256) were comparable with the harmonic mean single‐sample Nₑ (213) over the time period. Reanalysing historical data, we found NₑV increased from ≈80 in the 1910s–1960s to ≈280 in the contemporary population. The estimated ratio of effective to total census size (Nₑ/Nc) was stable and high (0.42–0.66) compared to previous brown bear studies. These results support independent demographic evidence for Yellowstone grizzly bear population growth since the 1980s. They further demonstrate how genetic monitoring of Nₑ can complement demographic‐based monitoring of Nc and vital rates, providing a valuable tool for wildlife managers.
Bibliography:http://dx.doi.org/10.1111/mec.13398
istex:F5E50C905988DC7A3BC350C39A8092114C9EA1CA
ark:/67375/WNG-WXNZ3GW5-W
ArticleID:MEC13398
Table S1 Altered PCR primer sequences for four additional microsatellite loci used to genotype grizzly bears in the Greater Yellowstone Ecosystem. Table S2 Sample sizes of grizzly bears by age class per year for EPA (estimator by parentage assignments) analyses of effective population size, Greater Yellowstone Ecosystem, 1982-2007. Table S3 Modeled estimates of null allele frequency at 20 microsatellite loci in grizzly bears of the Greater Yellowstone Ecosystem. Table S4 Genetic diversity indices for the Greater Yellowstone Ecosystem grizzly bear population compiled and recomputed (to correct for differences in sample size) across studies. Table S5 EPA-based estimates of grizzly bear effective population size (Ne) and generation interval (GI), Greater Yellowstone Ecosystem, 1982-2007. Table S6 SA-based estimates of effective number of breeders (Nb) of grizzly bears in the Greater Yellowstone Ecosystem, 1984-2007. Table S7 LD-based estimates of effective number of breeders (Nb) of grizzly bears in the Greater Yellowstone Ecosystem, 1984-2007. Fig. S1 Map of grizzly bear genetic sampling locations. Fig. S2Ne/Nc ratio over time of grizzly bears in the Greater Yellowstone Ecosystem. Fig. S3 Evaluating sensitivity of the EPA (estimator by parentage assignments) approach to assumed parentage threshold values. Fig. S4 Evaluating sensitivity of the EPA (estimator by parentage assignments) approach to sample size. Fig. S5 Evaluating sensitivity of Nb estimation approaches to sample size. Fig. S6 Percent differences in estimates with reductions in sampling.
U.S. Fish and Wildlife Service
NASA - No. NNX14AB84G
Chris Servheen
NSF - No. DEB-1258203
ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 23
ISSN:0962-1083
1365-294X
DOI:10.1111/mec.13398