A spatial population dynamics simulation model of tropical tunas using a habitat index based on environmental parameters

We are developing a spatial, multigear, multispecies population dynamics simulation model for tropical tunas in the Pacific Ocean. The model is age‐structured to account for growth and gear selectivity. It includes a tuna movement model based on a diffusion–advection equation in which the advective...

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Bibliographic Details
Published inFisheries oceanography Vol. 7; no. 3-4; pp. 326 - 334
Main Authors Bertignac, M., Lehodey, P., Hampton, J.
Format Journal Article
LanguageEnglish
Published Oxford UK Blackwell Science Ltd 01.12.1998
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Summary:We are developing a spatial, multigear, multispecies population dynamics simulation model for tropical tunas in the Pacific Ocean. The model is age‐structured to account for growth and gear selectivity. It includes a tuna movement model based on a diffusion–advection equation in which the advective term is proportional to the gradient of a habitat index. The monthly geographical distribution of recruitment is defined by assuming that spawning occurs in areas where sea surface temperature is above 25°C. During the first 3 months of their life, simulated tunas are transported by oceanic currents, after which movement is conditioned by gradients in the habitat index. Independent estimates of natural mortality rates and population size from large‐scale tagging experiments carried out by the Secretariat of the Pacific Community are used in the simulations. The habitat index consists of components due to forage density and sea surface temperature, both of which are suspected to play major roles in determining tuna distribution. Because direct observations of forage are not available on a basin scale, we developed a submodel to simulate the surface tuna forage production (Lehodey et al., 1998). At present, only skipjack (Katsuwonus pelamis; a surface tuna species caught by purse seine and by pole‐and‐line) is considered, at a 1°‐square resolution and on a monthly climatological time series. Despite the simplicity of the model and the limitations of the data used, the simulation model is able to predict a distribution of skipjack catch rates, of the different fleets involved in the fishery, that is fairly consistent with observations.
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ISSN:1054-6006
1365-2419
DOI:10.1046/j.1365-2419.1998.00065.x