Stock Production Models of Blue Marlin and White Marlin in the Atlantic Ocean: A Case History

Stock Production Models of Blue Marlin and White Marlin in the Atlantic Ocean: A Case History

C.D. Jones, E.D. Prince, G.P. Scott, and M.I. Farber

Stock Production Models of Blue Marlin and White Marlin in the Atlantic Ocean: A Case HistoryThis is part of Fishery Stock Assessment Models
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Description

Historically, stock assessments of Atlantic blue marlin (Makaira nigricans) and white marlin (Tetrapturus albidus), conducted under the auspices of the International Commission for the Conservation of Atlantic Tunas (ICCAT), have been restricted to production modeling approaches. Production models are used due to the unique fisheries and biological aspects of the species which result in a paucity of detailed information on the size or age structure of the catch. These analyses have evolved from single index equilibrium, to multiple index non-equilibrium models, as the ICCAT Enhanced Research Program for Billfish improved the Atlantic-wide data and new non-equilibrium multifishery production models became available. Analyses of these fisheries data have been conducted over the last two decades through a series of intersessional billfish workshops held by ICCAT, under various stock structure hypotheses, to provide estimates of historical relative biomass, fishing mortalities, and maximum sustainable yield. Among the difficulties in modeling stock biomass, there have been conflicting indices of abundance for several fisheries, difficulties in modeling the dynamics of precipitous drops in CPUE through non–age structured approaches, and typically flat solution surfaces which cause difficulty in searches for optimal, unconstrained model solutions. However, in each case various assumptions were made, or certain parameters fixed, generally based on working group consensus, and solutions were achieved. A case history of multi fishery Atlantic billfish assessments is presented, along with approaches that enabled specific problems to be addressed in the model fitting.

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