The Role of Genetics in Managing Declining Fisheries Resources
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Keywords:
Fisheries science fishery management management unit evolutionary significant unit impact assessment fishery supplementation
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Abstract
With increasing human population, rising consumer demand, and intensification of industrial fishing, many valued fisheries are in decline. This review and synthesis explores how genetics informs classical fisheries management programs, especially in the context of managing declining fisheries resources. Discussing underlying principles and illustrative case studies drawn as possible from Southeast Asia, I focus upon application of genetics to: (1) define biologically based management units, (2) monitor the impacts of fisheries and fishery management actions, and (3) guide and evaluate fisheries restoration activities. Because overexploitation and declining fisheries arise from issues of economics, sociology, and politics, an effective approach to their solution must itself be interdisciplinary; application of genetic principles provides a valuable addition to such a holistic fisheries management program. Increasingly, progressive fisheries management agencies have in-house capabilities for genetic assessment and monitoring functions. Against this background, developing countries might seek to build their capacity for applied population genetics, either within fisheries management agencies or via scientific collaboration with research-oriented universities. While much progress has been achieved, the task of applying genetics to the effective management of declining fisheries is large and mostly before us.
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Hallerman, E. (2015). The Role of Genetics in Managing Declining Fisheries Resources. Journal of Fisheries and Environment, 39(2), 40–74. Retrieved from https://li01.tci-thaijo.org/index.php/JFE/article/view/80537
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References
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3. Appleyard, S.A., and R.D. Ward. 2006. Genetic diversity and effective population size in mass selection lines of Pacific oyster (Crassostrea gigas). Aquaculture 254:148-159.
4. Ayllon, F., J.L. Martinez, F. Juanes, S. Gephard and E. Garcia-Vazquez. 2006. Genetic history of the population of Atlantic salmon, Salmo salar L., under restoration in the Connecticut River, USA. ICES Journal of Marine Science 63:1286-1289.
5. Bartley, D., M. Bagley, G. Gall and B. Bentley. 1992. Use of linkage disequilibrium data to estimate effective size of hatchery and natural fish populations. Conservation Biology 6:365-375.
6. Beerli, P. and J. Felsenstein. 1999. Maximum-likelihood estimation of migration rates and effective population numbers in two populations using a coalescent approach. Genetics 152:763-773.
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8. Busack, C.A. and K.P. Currens. 1995. Genetic risks and hazards in hatchery operations: fundamental concepts and issues. Pages 71-80 in H.L. Schramm and R.G. Piper, eds. Uses and Effects of Cultured Fishes in Aquatic Ecosystems. American Fisheries Society Symposium 15, Bethesda, MD.
9. Carey, C.S., J.W. Jones, R.S. Butler, and E.M. Hallerman. Restoring the endangered oyster mussel (Epioblasma capsaeformis) to the upper Clinch River, Virginia: an evaluation of population restoration techniques. Manuscript in review.
10. Chaney, M.L. and A.Y. Gracey. 2011. Mass mortality in Pacific oysters is associated with a specific gene expression signature. Molecular Ecology 20:2942-2954.
11. Cooke, S.J., S.G. Hinch, M.R. Donaldson, T.D. Clark, E.J. Eliason, G.T. Crossin, G.D. Raby, K.M. Jeffries, M. Lapointe, K. Miller, D.A. Patterson and A.P. Farrell. 2012. Conservation physiology in practice: how physiological knowledge has improved our ability to sustainably manage Pacific salmon during up-river migration. Philosophical Transactions of the Royal Society B 370:1757–1769.
12. Cornuet, J.-M. and G. Luikart. 1996. Description and power analysis of two tests for detecting recent demographic bottlenecks from allele frequency data. Genetics 144:2001-2014.
13. Crandall, K.A., D. Posada and D. Vasco. 1999. Effective population sizes: missing measures and missing concepts. Animal Conservation 2:317-319.
14. Dizon, A.E., C. Lockyear, W.F. Perrin, D.P. Demaster and J. Sisson. 1992. Rethinking the stock concept – a phylogeographic approach. Conservation Biology 6:24-36.
15. Do, C., R.S. Waples, D. Peel, G.M. Macbeth, B.J. Tillett and J.R. Ovenden. 2014. NeEstimator v2: re‐implementation of software for the estimation of contemporary effective population size (Ne) from genetic data. Molecular Ecology Resources 14:209-214.
16. Evans, T.G., F. Chan, B. A. Menge and G.E. Hofmann. 2013. Transcriptomic responses to ocean acidification in larval sea urchins from a naturally variable pH environment. Molecular Ecology 22:1609-1625.
17. Evans, T.G. and G.E. Hofmann. 2012. Defining the limits of physiological plasticity: how gene expression can assess and predict the consequences of ocean change. Philosophical Transactions of the Royal Society B 367:1733-1745.
18. Ewart, K.V., J.C. Belanger, J. Williams, T. Karakach, S. Penny, S.C.M. Tsoi, R.C. Richards and S.E. Douglas. 2005. Identification of gene differentially expressed in Atlantic salmon (Salmo salar) in response to infection by Aeromonas salmonicida using cDNA microarray technology. Developmental and Comparative Immunology 29:333-347.
19. Faurby, S., T.L. King, M. Obst, E.M. Hallerman, C. Pertoldi, and P. Funch. 2010. Population dynamics of American horseshoe crabs – historic climatic events and recent anthropogenic pressures. Molecular Ecology 19:3088-3100.
20. Felsenstein, J. 1992. Estimating effective population size from samples of sequences: a bootstrap Monte Carlo integration method. Genetical Research 60:209-220.
21. Fu, Y.X. 1994a. A phylogenetic estimator of effective population size or mutation rate. Genetics 136:685-693.
22. Fu, Y.X. 1994b. Estimating effective population size or mutation rate using the frequencies of mutations of various classes in a sample of DNA sequences. Genetics 138:1375-1386.
23. Gaffney, P.M., V.P. Rubin, D. Hedgecock, D.A. Powers, G. Morris and L. Hereford. 1996. Genetic effects of artificial propagation: signals from wild and hatchery populations of red abalone in California. Aquaculture 143:257-266.
24. George, A.L., B.R. Kuhajda, J.D. Williams, M.A. Cantrell, P.L. Rakes and J.R. Shute. 2009. Guidelines for propagation and translocation for freshwater fish conservation. Fisheries 34:529-545.
25. Gustafson, R.G., T.C. Wainwright, G.A. Winans, F.W. Waknitz, L.T. Parker and R.S. Waples. 1997. Status review of sockeye salmon from Washington and Oregon. NOAA Technical Memorandum NMFS-NWFSC-33. http://www.nwfsc.noaa.gov/publications/scipubs/techmemos/tm33/int.html#wes.
26. Hastings, A. 1993. Complex interactions between dispersal and dynamics – lessons from coupled logistic equations. Ecology 74:1362–1372.
27. Hauser, L., G.J. Adcock, P.J. Smith, J.H. Bernal Ramírez and G.R. Carvalho. 2002. Loss of microsatellite diversity and low effective population size in an overexploited population of New Zealand snapper (Pagrus auratus). Proceedings of the National Academy of Sciences U.S.A. 99:11742-11747.
28. Hedgecock, D., V. Chow and R.S. Waples. 1992. Effective population numbers of shellfish broodstocks estimated from temporal variance in allele frequencies. Aquaculture 108:215-232.
29. Hedgecock, D. and F.L. Sly. 1990. Genetic drift and effective population size of hatchery-propagated stocks of the Pacific oyster Crassostrea gigas. Aquaculture 88:21-38.
30. Hellberg, M.E., R.S. Burton, J.E. Neigel and S.R. Palumbi. 2002. Genetic assessment of connectivity among marine populations. Bulletin of Marine Science 70(Suppl):273-290.
31. Hill, W.G. 1981. Estimation of effective population size from data on linkage disequilibrium. Genetical Research 38:209-216.
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