Population Mixture Analysis (PMA)
Effective management of fisheries that exploit mixtures of fish from multiple populations requires identification of those populations and assessments of their contributions to fisheries. Accurate estimates of population composition of mixed harvests allow managers to reduce the risk of overharvesting smaller populations and to maximize the yield from larger populations through harvest limits. Characters, and most effectively genetic characters, measured on individual animals of separate populations and in the mixed harvest are used in the estimation of population composition. Software for performing population mixture analysis (PMA) developed and maintained by OCC staff includes GIRLSEM (Genotypes and Iteratively Reweighted Least Squares) for performing conditional maximum likelihood estimation, SIMULATR for simulating mixed samples from baseline data, BAYES for performing Bayesian PMA, and HWLER for performing PMA with incomplete or completely missing baselines. Software, user's manuals, and example data sets can be downloaded from the anonymous ftp site.
Contact:
Michele Masuda
Auke Bay Laboratories
Alaska Fisheries Science Center, NOAA Fisheries
Ted Stevens Marine Research Institute
17109 Pt Lena Loop Rd
Juneau AK 99801
(907) 789-6087
Michele.Masuda@noaa.gov
Supporting Research
- Pella, J., and M. Masuda 2006. The Gibbs and split-merge
sampler for population mixture analysis from genetic data
with incomplete baselines. Can. J. Fish. Aquat. Sci.
63, 576-596.
- Pella, J., and M. Masuda 2005. Classical discriminant
analysis, classification of individuals, and source population
composition of mixtures. in Stock identification
methods: applications in fishery science (S. X. Cadrin,
K. D. Friedland, and J. R. Waldman), 517-552 , Elsevier,
Inc. San Diego, CA.
- Koljonen, M. L., J. Pella, and M. Masuda 2005. Classical
individual assignments versus mixture modeling to estimate
stock proportions in Atlantic salmon (Salmo salar)
catches from DNA microsatellite data. Can. J. Fish. Aquat.
Sci. 62, 2143-2158.
- Pella, J. and M. Masuda 2001. Bayesian methods for analysis
of stock mixtures from genetic characters. Fish. Bull.
99, 151-167.
- Debevec, E. M., R. B. Gates, M. Masuda, J. Pella, J. Reynolds,
and L. W. Seeb 2000. SPAM (version 3.2): statistics program
for analyzing mixtures. J. Hered. 91, 509-510.
See the publications and posters databases for additional listings.
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