Hostname: page-component-76fb5796d-skm99 Total loading time: 0 Render date: 2024-04-26T03:13:49.594Z Has data issue: false hasContentIssue false

Annual indices of Atlantic bluefin tuna (Thunnus thynnus) larvae in the Gulf of Mexico developed using delta-lognormal and multivariate models*

Published online by Cambridge University Press:  17 March 2010

G. Walter Ingram Jr.
Affiliation:
National Marine Fisheries Service, Southeast Fisheries Science Center, Mississippi Laboratories, 3209 Frederic Street, Pascagoula, MS, 39567, USA
William J. Richards
Affiliation:
National Marine Fisheries Service, Southeast Fisheries Science Center, Protected Resources and Biodiversity Division, 75 Virginia Beach Drive, Miami, FL, 33149-1099, USA
John T. Lamkin
Affiliation:
National Marine Fisheries Service, Southeast Fisheries Science Center, Protected Resources and Biodiversity Division, 75 Virginia Beach Drive, Miami, FL, 33149-1099, USA
Barbara Muhling
Affiliation:
National Marine Fisheries Service, Southeast Fisheries Science Center, Protected Resources and Biodiversity Division, 75 Virginia Beach Drive, Miami, FL, 33149-1099, USA
Get access

Abstract

Fishery independent indices of spawning biomass of Atlantic bluefin tuna in western North Atlantic Ocean are presented which utilize National Marine Fisheries Service ichthyoplankton survey data collected from 1977 through 2007 in the Gulf of Mexico. Indices were developed using similarly standardized data from which previous indices were developed (i.e. abundance of larvae with a first daily otolith increment formed per 100 m2 of water sampled with bongo gear). Indices were also developed for the first time from standardized data collected with neuston gear [i.e. abundance of 5-mm larvae (i.e. seven-day-old larvae) per 10 minute tow]. Indices of larval abundance were developed using delta-lognormal models, including following covariates: time of day, time of month, area sampled and year. Due to the large frequency of zero catches during ichthyoplankton surveys, a zero-inflated delta-lognormal approach was also used to develop indices. Finally, a multivariate delta-lognormal approach was employed to develop indices of annual abundance based on both bongo and neuston catches. The results of these approaches were compared with one another and with other indices of larval abundance previously developed for the Gulf of Mexico. Residual analyses indicated that abundance indices of Atlantic bluefin tuna larvae were more appropriately developed from bongo-collected data through the zero-inflated delta-lognormal approach than other data sets and modeling approaches. Also, when modeling bongo-collected data with the zero-inflated delta-lognormal approach, the index values increased, indicating some correction for zero-inflation, and their variability decreased as compared to indices developed with the delta-lognormal approach.

Type
Research Article
Copyright
© EDP Sciences, IFREMER, IRD, 2010

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Footnotes

*

Supporting information is only available in electronic form at www.alr-journal.org

References

Anonymous, 2008, Report of the 2008 Atlantic Bluefin Tuna Stock Assessment Session, Madrid, June 2008.
Boyce, M.S., Vernier, P.R., Nielson, S.E., Schmiegelow, F.K.A., 2002, Evaluating resource selection functions. Ecol. Model. 157, 281300. CrossRef
Coull, B.A., Agresti, A., 2000, Random effects modeling of multiple binomial responses using the multivariate binomial logit-normal distribution. Biometrics 56, 7380. CrossRef
Cumming, G.S., 2000, Using between-model comparisons to fine-tune linear models of species ranges. J. Biogeogr. 27, 44155. CrossRef
Hall, D.B., 2000, Zero-inflated Poisson and binomial regression with random effects: a case study. Biometrics 56, 10301039. CrossRef
Lehmann E.L., 1998, Nonparametrics: Statistical Methods Based on Ranks, New Jersey: Prentice Hall.
Lo, N.C.H., Jacobson, L.D., Squire, J.L., 1992, Indices of relative abundance from fish spotter data based on delta-lognormal models. Can. J. Fish. Aquat. Sci. 49, 15151526. CrossRef
Martin, T.G., Wintle, B.A., Rhodes, J.R., Kuhnert, P.M., Field, S.A., Low-Choy, S.J., Tyre, A.J., Possingham, H.P., 2005, Zero tolerance ecology: improving ecological inference by modeling the source of zero observations. Ecol. Lett. 8, 12351246. CrossRef
McConnaughey, R.A., Conquest, L.L., 1993, Trawl survey estimation using a comparative approach based on lognormal theory. Fish. Bull. 91, 107118.
McGowan, M.F., Richards, W.J., 1986, Distribution and abundance of bluefin tuna (Thunnus thynnus) larvae in the Gulf of Mexico in 1982 and 1983 with estimates of the biomass and population size of the spawning stock for 1977, 1978, and 1981-1983. ICCAT. Coll. Vol. Sci. Pap. 24, 182195.
McPherson, J.A., Jetz, W., Rogers, D.J., 2004, The effects of species' range sizes on the accuracy of distribution models: ecological phenomenon or statistical artefact? J. Appl. Ecol. 41, 811823. CrossRef
Minami, M., Lennert-Cody, C.E., Gao, W., Roman-Verdesoto, M.H., 2007, Modeling shark bycatch: The zero-inflated negative binomial regression model with smoothing. Fish. Res. 84, 210221. CrossRef
Murphy, G.I., 1990, A review of Atlantic bluefin tuna larval surveys. ICCAT. Coll. Vol. Sci. Pap. 32, 262269.
Pennington, M., 1983, Efficient estimators of abundance, for fish and plankton surveys. Biometrics 39, 281286. CrossRef
Pennington, M., 1996, Estimating the mean and variance from highly skewed data. Fish. Bull. 94, 498505.
Richards, W.J., 1990, Results of a review of the U.S. bluefin tuna larval assessment with a brief response. ICCAT. Coll. Vol. Sci. Pap. 32, 240247.
Richards, W.J., Potthoff, T., 1980, Distribution and abundance of bluefin tuna larvae in the Gulf of Mexico in 1977 and 1978. ICCAT. Coll. Vol. Sci. Pap. 9, 433441.
Rooker, J.R., Alvarado Bremer, J.R., Block, B.A., de Metrio, G., Corriero, A., Krause, R.T., Prince, E.D., Rodriguez-Marin, E., Secor, D.H., 2007, Life history and stock structure of Atlantic bluefin tuna (Thunnus thynnus). Rev. Fish. Sci. 15, 265310. CrossRef
Scott G.P., Turner S.C., Grimes C.B., Richards W.J., Brothers E.B., 1993, Indices of larval bluefin tuna, Thunnus thynnus, abundance in the Gulf of Mexico; modeling variability in growth, mortality, and gear selectivity. Bull. Mar. Sci. 53, 912–929.
Scott, G.P., Turner, S.C., 1994, An updated index of west Atlantic bluefin spawning biomass based on larval surveys in the Gulf of Mexico. ICCAT Coll. Vol. Sci. Pap. 62, 211213.
Steventon J.D., Bergerud W.A., Ott P.K., 2005, Analysis of presence/absence data when absence is uncertain (false zeroes): an example for the northern flying squirrel using SAS ®. Res. Br., Bristish Cololumbia Min. Forests, Victoria BC, Exten. Note 74.
Tyre, A.J., Tenhumberg, B., Field, S.A., Niejalke, D., Parris, K., Possingham, H.P., 2003, Improving precision and reducing bias in biological surveys: estimating false-negative error rates. Ecol. Appl. 13, 17901801. CrossRef
Vieira, A.M.C., Hinde, J.P., Demetrio, C.G.B., 2000, Zero-inflated proportion data models applied to a biological control assay. J. Appl. Stat. 27, 373389. CrossRef
Supplementary material: PDF

OLM - alr 23(1) 2010 p.35 - Annual indices of Atlantic bluefin tuna (Thunnus ...

Appendix: Tables A.1–A.8

Download OLM - alr 23(1) 2010 p.35 - Annual indices of Atlantic bluefin tuna (Thunnus ...(PDF)
PDF 483.4 KB