Spatial Analysis of the Fishing Behaviour of Tuna Purse Seiners in the Western and Central Pacific Based on Vessel Trajectory Data

• Published in: Journal of marine science and engineering 2021-03, Vol.9 (3), p.322
• Main Authors: Zhang, Han, Yang, Sheng-Long, Fan, Wei, Shi, Hui-Min, Yuan, San-Ling
• Format: Article
• Language: English
• Subjects: automatic identification system (AIS) data; correlation coefficient; fishing effort; fishing intensity; spatial characteristics; tuna purse seiners
• ISSN: 2077-1312; 2077-1312
• DOI: 10.3390/jmse9030322

The Western and Central Pacific Oceans are the primary operational areas of tuna purse seiners worldwide. Describing and analysing the fishing behaviour of vessels is highly significant for the protection of sustainable tuna resources. This study uses Automatic Identification System (AIS) data of 130 tuna purse seiners from July 2017 to May 2018 and uses data mining methods to identify the operating status of tuna purse seiners; describes the spatial characteristics of fishing intensity and the distribution of hot spots; and analyses vessel spatial characteristics to describe their fishing behaviour. The results show that the tuna purse seiner speed has a marked bimodal distribution, which corresponds to high-speed transiting and low-speed seine operation. Additionally, from July to September 2017, the amount of fishing effort invested by tuna purse seiners was lower than that in other months. The tuna purse seiner activity range includes 120° E–60° W, 30° S–30° N, and the activities for fish and seine operations are primarily concentrated at 140° E–150° W, 15° S–15° N. There are differences between the space for fishing search operations and space where fishing events took place in each month. Spatial analysis shows that the high-speed transiting fishing effort map covers a large area, while seine fishing covers a small area. The global spatial autocorrelation analysis shows that the fishing effort devoted to searching for fish stocks has a spatial distribution pattern of aggregation and close aggregation. The results of a hot-spot analysis show that the hot spots on a heat map for finding fish, which are closely spatially clustered, correspond to vessels searching for fish concentration areas and seine operation areas. Correlation testing shows that under a 5° × 5° grid, there is a high positive correlation between the fishing effort invested in finding fish stocks and the yield data, nets (r > 0.8), and a moderate correlation with catch per unit of effort(CPUE) (r > 0.3). Based on vessel behaviour, the location of the fish school can be directly determined, and the distribution of fish clusters and fishing grounds can be predicted. This study can aid in managing tuna purse seiners in the Western and Central Pacific Oceans and analysing changes in fishery resources.