气候振荡对印度洋鲣鱼的影响

IF 4.6 Q2 MATERIALS SCIENCE, BIOMATERIALS
Shigang Liu , Liyan Zhang , Rui Wang , Puqing Song , Xing Miao , Hai Li , Yuan Li , Longshan Lin
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引用次数: 0

摘要

鲣鱼(Katsuwonus pelamis)(SKJ)是分布在世界热带和亚热带海洋的最重要的商业海洋鱼类之一。印度洋是SKJ的主要渔场,其开采率略低于最大可持续产量。因此,SKJ股票可能会受到气候变化的重大影响。在本研究中,与印度洋有关的气候振荡指数,包括印度洋偶极子(IOD)、东印度洋和西印度洋的平均水温异常(EIO)、80°E的麦登-朱利安振荡指数(MJO80)和北极振荡指数(AOI),都与SKJ单位努力渔获量(CPUE)有关。本研究旨在了解这五种气候振荡对SKJ的影响,目的是优化印度洋鲣鱼的利用。我们将梯度森林分析(GFA)和广义加性模型(GAMs)相结合,以评估每个滞后0–5年的气候指数对SKJ CPUE影响的重要性,并建立最优预测模型。GFA结果表明,MJO80是影响SKJ CPUE的最重要的气候指标,其次是MJO80_1、AOI_2、IOD_4、WIO_2等。最佳GAM模型包括MJO80、AOI_ 2和WIO_2,这可能通过影响水温与SKJ的招募和幼虫存活有关。同时,在西印度洋和中印度洋热带地区,SST和SKJ CPUE之间存在显著的负相关。我们的研究结果表明,气候振荡对印度洋SKJ渔业具有0–2年的滞后效应,可用于预测未来2年SKJ的资源变化。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The effect of climate oscillations on skipjack tuna (Katsuwonus pelamis) in the Indian Ocean

Skipjack tuna (Katsuwonus pelamis) (SKJ) is one of the most commercially important marine fish species distributed throughout the world's tropical and subtropical oceans. The Indian Ocean is a main fishing ground for SKJ, whose exploitation rate is just below the maximum sustainable yield. Therefore, SKJ stocks may potentially be significantly affected by climate change. In this study, climatic oscillation indices related to the Indian Ocean, including the Indian Ocean Dipole (IOD), the mean water temperature anomaly in the Eastern Indian Ocean (EIO) and Western Indian Ocean (WIO), the Madden-Julian Oscillation Index at 80°E (MJO80) and the Arctic Oscillation Index (AOI), were associated with SKJ catch per unit effort (CPUE). This study aimed to understand the effect of these five climatic oscillations on SKJ, with the goal of optimizing the utilization of skipjack tuna in the Indian Ocean. We combined gradient forest analysis (GFA) and generalized additive models (GAMs) to evaluate the importance of each climatic index with a 0–5 year lag on the impact of SKJ CPUE and to establish an optimal prediction model. The GFA results show that MJO80 is the most important climatic index influencing SKJ CPUE, followed by MJO80_1, AOI_2, IOD_4, WIO_2, etc. The best GAM model includes MJO80, AOI_2, and WIO_2, which could be related to the recruitment and larval survival of SKJ by influencing water temperature. Meanwhile, there is a significant negative correlation between SST and SKJ CPUE in the tropical regions of the western and central Indian Ocean. Our results suggest that climate oscillations have a 0–2 year lag effect on the SKJ fishery in the Indian Ocean, which can be used to predict resource changes in SKJ over the next 2 years.

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来源期刊
ACS Applied Bio Materials
ACS Applied Bio Materials Chemistry-Chemistry (all)
CiteScore
9.40
自引率
2.10%
发文量
464
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