中西太平洋金枪鱼围网渔场聚类及其原因分析

本文根据1995-2010年我国中西太平洋金枪鱼围网生产统计数据，按年和月不同时间空间分辨率对金枪鱼围网渔场进行聚类分析，划定不同渔场类型；同时结合海表温度（SST）及Niño3.4区指数，探讨其渔场类型形成的原因。研究表明，在月为时间尺度下气候异常事件（El Niño和La Niña事件）发生频次与渔场聚类结果类别相关联，在1-12月发生气候异常事件频数分布可划分为以下几个阶段:1-3月、4-6、7-9月、10-12月，与月时间尺度下金枪鱼围网中心渔场4种聚类结果的时间范围具有一致性。通过渔场重心聚类结果和El Niño和La Niña事件分类统计对比发现，在年时间尺度下，气候异常事件的类型与聚类结果相关联，聚类结果同一类别包含的年份发生的气候异常事件具有一致性，即在同一类别下1995年、1997年为强El Niño年；1998年、2007、年、2009年为正常年份；2010年为强La Niña年；1999年、2000年、2001年为La Niña年；1996年、2008年为La Niña年；2002年、2004年为El Niño年。研究认为，中心渔场的年际聚类变化与El Niño、La Niña事件的发生分布具有很强的相关性，因此可以利用El Niño、La Niña指标来预测渔场的年间和月份间的变化。

Cluster analysis of tuna purse seine fishery in the Western and Central Pacific

According to production statistics from tuna purse seine fishery during 1995 to 2010, cluster analysis of purse seine fishery by year and month different time scale is analyzed. Combined with sea surface temperature (SST) and Niño 3.4 zone index, the causes of different fishing ground type are discussed. The studies shown that the frequency distribution of abnormal weather events (El Niño and La Niña events)are closely related to the class of clustering results of fishing ground in a monthly time scale, which can be divided into the following phases, i.e. January to March, April to June, July to September and October to December, this results is basically consistent with the time range of clustering results of fishing ground. Compared with center of clustering fishing ground and classification statistical of El Niño and La Niña events, it is found that the type of abnormal climate event associated with the results of clustering. Under the same category, the first category is in 1995 and 1997 with strong El Niño years, the second category is 1998, 2007 and 2009 with normal year, the third category is 2010 with a strong La Niña year, the fourth category is 1999, 2000 and 2001 with La Niña years, the fifth category is 1996 and 2008 with La Niña Year, and category VI is 2002 and 2004 with El Niño years. It is concluded that the changing annual fishing grounds has a strong correlation with the occurrence of El Niño and La Niña events, the index of the El Niño and La Niña can be used to predict the changes of fishing grounds at year and month scales.