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ENSO-tuna relations in the eastern Pacific Ocean and its prediction as a non-linear dynamic system

机译:东太平洋ENSO-金枪鱼关系及其作为非线性动力系统的预测

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During the years between 1967 and 1994 the trimestral abundance of the yellowfin tuna fish (Thunnus albacares), 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 the Inter-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 behavior of the dynamics of this variable; this data was correlated with information on the presence of El Nino Southern Oscillation (ENSO) for the same period. The analysis suggests that the presence of strong ENSO events correlate with the decline of tuna fish biomass, which is followed by a rapid increase of this variable in a 3: 1 time ratio; this means that it takes three times as long for the biomass to decrease than it does to recover and return to similar or higher values. After the ENSO-tuna fish biomass relations were established, two types of models were adjusted to the tuna fish biomass information: neuronal network and ARIMA. Both models described adequately the tuna fish biomass dynamics; however, the ARIMA model also permitted an adequate prediction of the behavior of ENSO variable, emphasizing that this model correctly predicted the presence of 1997 ENSO.
机译:在1967年至1994年之间,黄鳍金枪鱼(Thunnus albacares)的三体丰度以东太平洋(EPO)的每组年龄和队列的个体数表示,用于计算该物种的生物量每三个月。该信息来自美洲热带金枪鱼委员会的出版物(ITTC)。图形方法应用于此数据(粗数据,相空间,每三个月的子系列以及年度平均值),以识别此变量的动态行为。该数据与同一时期内厄尔尼诺南方涛动(ENSO)的存在信息相关。分析表明,强烈的ENSO事件的存在与金枪鱼生物量的下降有关,随后该变量以3:1的时间比快速增加。这意味着生物量减少所需的时间比恢复并返回到相似或更高值所需的时间长三倍。建立了ENSO-金枪鱼生物量关系后,针对金枪鱼生物量信息调整了两种类型的模型:神经网络和ARIMA。两种模型都充分描述了金枪鱼的生物量动态。但是,ARIMA模型还允许对ENSO变量的行为进行充分的预测,强调该模型可以正确预测1997年ENSO的存在。

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