Management of large-scale pelagic fisheries relies heavily on fishery data to provide information on tuna population status because, for widely distributed populations, the cost of collecting survey data is often prohibitively high. However, fishery data typically do not provide direct information on interactions among fishing vessels, and thus methods of analysis often assume that vessels operate independently, despite the belief that cooperative fishing occurs. Cluster analysis methods were applied to daily vessel location data collected by onboard fisheries observers to identify groups of tuna purse-seine vessels searching for fish close to each other in space. Some vessel groups were found to reoccur through time, both on daily and monthly or longer time scales. This temporal persistence and reoccurrence are interpreted as an indication of cooperative fishing. Results indicate that there may be multiple layers of vessel interactions, from groups of a few vessels to networks of larger numbers of vessels. The use of reoccurring vessel group characteristics to study the temporal and spatial persistence of areas of high tuna abundance is discussed.

大型远洋渔业的管理在很大程度上依靠渔业数据来提供有关金枪鱼种群状况的信息，因为对于分布广泛的种群而言，收集调查数据的成本往往高得令人望而却步。然而，渔业数据通常不提供有关渔船之间相互作用的直接信息，因此，尽管相信发生了合作捕捞，但分析方法经常假定渔船是独立运行的。机群分析方法应用于船上渔业观察员收集的每日船只位置数据，以识别金枪鱼围网渔船组，在太空中寻找彼此靠近的鱼。发现某些船群会在每天和每月或更长时间范围内随时间重新出现。这种暂时的持续性和再次发生被解释为合作捕鱼的迹象。结果表明，可能存在多层血管交互作用，从少量血管的组到大量血管的网络。讨论了使用重复发生的船只群特​​征研究金枪鱼丰度高的地区的时间和空间持久性。