ENSO-tuna relations in the eastern Pacific Ocean and its prediction as a non-linear dynamic system.
During the years between 1967 and 1994 the trimestral abundance of the yellowfin tuna fish (Thunnusalbacares), expressed as the number of individuals per group age and cohort, for the Eastern Pacific Ocean(EPO), was used to calculate the biomass of this species per trimester. This information was ob...
| Autores: | , , , |
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| Formato: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2004 |
| País: | México |
| Recursos: | Universidad Nacional Autónoma de México |
| Repositorio: | Redalyc-UNAM |
| OAI Identifier: | oai:redalyc.org:56517404 |
| Acesso em linha: | https://www.redalyc.org/articulo.oa?id=56517404 |
| Access Level: | acceso abierto |
| Palavra-chave: | Ciencias de la Tierra non El Niño linear dynamic system Southern Oscillation (ENSO) Yellowfin tuna fish (Thunnus albacares) |
| Resumo: | During the years between 1967 and 1994 the trimestral abundance of the yellowfin tuna fish (Thunnusalbacares), expressed as the number of individuals per group age and cohort, for the Eastern Pacific Ocean(EPO), was used to calculate the biomass of this species per trimester. This information was obtained from theInter-American Tropical Tuna Commission publications (ITTC). Graphic methods were applied to this data(crude data, phase space, subseries per trimester as well as annual averages) in order to identify the behaviorof the dynamics of this variable; this data was correlated with information on the presence of El NiñoSouthern Oscillation (ENSO) for the same period. The analysis suggests that the presence of strong ENSOevents correlate with the decline of tuna fish biomass, which is followed by a rapid increase of this variable ina 3:1 time ratio; this means that it takes three times as long for the biomass to decrease than it does to recoverand return to similar or higher values. After the ENSO-tuna fish biomass relations were established, two typesof models were adjusted to the tuna fish biomass information: neuronal network and ARIMA. Both modelsdescribed adequately the tuna fish biomass dynamics; however, the ARIMA model also permitted an adequateprediction of the behavior of ENSO variable, emphasizing that this model correctly predicted the presence of1997 ENSO. |
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