东太平洋大眼金枪鱼自由鱼群栖息地偏好的时空分布特征

Spatio-temproal distribution pattern of habitat preference of bigeye tuna free-swimming schools in the eastern Pacific Ocean

基于美洲间热带金枪鱼委员会(Inter-American Tropical Tuna Commission, IATTC)收集的2015—2017年东太平洋大眼金枪鱼自由鱼群围网捕捞数据和相匹配的卫星遥感数据,使用二阶提升回归树模型(boosted regression tree, BRT)建立该鱼群的栖息地模型,以探究其时空分布特征。研究结果表明,相对于环境因子,空间因子对大眼金枪鱼自由鱼群的丰度有更大的影响。环境因子方面,纬度、经度、混合层深度、月份和海表面温度是影响大眼金枪鱼捕获成功率的主要影响因子,而影响丰度的主要因子为经度和海表面叶绿素a浓度。空间上,大眼金枪鱼主要处于10°S以南, 95°W以西的海域。在2016年7—9月和2017年2—4月,BRT模型预测的空间分布显示:一些高度密集的自由鱼群分别栖息在远离海岸,经度为150°W、纬度为0°的赤道海域和经度为120°W,纬度为10°S附近的海域。时间序列上,大眼金枪鱼丰度月平均值的年际间变化差异很小,月间差异较大,在7月达到最高值,但在8月立刻下降到最低值。研究结果可以为东太平洋大眼金枪鱼的资源养护和管理提供参考依据。

Based on the data collected by Inter-American Tropical Tuna Commission(IATTC) from 2015 to 2017 and the matched satellite remote sensing data, a two-stage boosted regression tree(BRT) model was built to model the habitat of bigeye tuna free-swimming schools in the eastern Pacific Ocean and explore its temporal and spatial distribution pattern. The results showed that, compared to environmental factors, spatial factors had a greater impact on the abundance of bigeye tuna free-swimming schools. In terms of environmental factors, latitude, longitude, mixed layer depth, month, and sea surface temperature are the main influential factors that affect the fishing success rate of bigeye tuna free-swimming schools, while the main factors affecting the abundance of bigeye tuna free-swimming schools are longitude and sea surface chlorophyll-a concentration. Bigeye tuna is mainly located in the sea area south of 10°S and west of 95°W. From July to September in 2016 and Febuary to April in 2017, the spatial distribution predicted by the two-stage BRT model showed that some highly dense tuna free-swimming schools inhabited the equatorial waters with longitude of 150°W and latitude of 0° and waters with longitude of 120°W and latitude of 10°S, respectively. With respect to temporal trend, the inter-annual variation of the monthly average of the abundance of bigeye tuna is small, but the monthly difference is large. The monthly variation revealed that the highest value occurred in July and then dropped to the lowest value in August. The results of this study can provide reference for conservation and management of tuna resources in the EPO.