The habitat preference of commercial tuna species based on a daily environmental database approach in the tropical region of the Eastern Indian Ocean off Java-Bali waters

IF 2.3 3区 地球科学 Q2 OCEANOGRAPHY
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Abstract

This paper explores the habitat characteristics of commercial tuna species based on daily oceanography parameters in the Eastern Indian Ocean Off Java-Bali Waters. Moreover, more research is needed combining the daily spatial distribution of oceanographic variables of surface and sub-surface data to analyse the habitat characteristics of large pelagic fish, including tuna species. In this study, we used five main daily oceanography parameters: sea surface temperature (SST), sea surface chlorophyll (CHLa), sea surface height (SSH), dissolved oxygen at 100m (DO100), the temperature at 100m (temp100) and the combination of the catch of yellowfin (YFT), albacore (ALT) and bigeye (BET) tuna that use long lines. To analyse the relationship between the environmental database and tuna catch, we utilized Generalized Additive Models (GAMs) from univariate variables until the combination of all variables. The result stated that all the variables influence the existence of all tuna species with P-values <0.001. Temperature is the most critical predictor variable, SST is the most vital predictor for BET and YFT tuna, and temp100 is the most critical for ALT. The second most essential variables were DO100 for BET, Temp 100 for YFT, and SSH for ALT. Moreover, BET and YFT prefer to stay at a lower temp100, and ALT tuna remains at a higher temp100. However, all of them avoid an SST higher than 29 °C. Further assessment of the long-term SST trend specific to tuna species is required to fully account for the effects of global warming on the oceans.

基于日环境数据库方法的东印度洋热带地区爪哇-巴厘海域商业金枪鱼物种的生境偏好
本文根据东印度洋爪哇-峇里水域的每日海洋学参数,探讨商业金枪鱼物种的栖息地特征。此外,还需要开展更多的研究,结合表层和次表层海洋学变量的日空间分布数据,分析包括金枪鱼物种在内的大型中上层鱼类的栖息地特征。在这项研究中,我们使用了五个主要的日海洋学参数:海面温度(SST)、海面叶绿素(CHLa)、海面高度(SSH)、100 米处溶解氧(DO100)、100 米处温度(temp100)以及使用长线捕捞的黄鳍金枪鱼(YFT)、长鳍金枪鱼(ALT)和大眼金枪鱼(BET)的渔获量组合。为了分析环境数据库与金枪鱼渔获量之间的关系,我们利用了从单变量到所有变量组合的广义相加模型(GAMs)。结果表明,所有变量都会影响所有金枪鱼物种的存在,P 值均为 0.001。温度是最关键的预测变量,SST 是 BET 和 YFT 金枪鱼最重要的预测变量,temp100 是 ALT 最关键的预测变量。其次是 BET 的 DO100、YFT 的 Temp 100 和 ALT 的 SSH。此外,BET 和 YFT 金枪鱼喜欢保持较低的温度 100,而 ALT 金枪鱼则保持较高的温度 100。然而,它们都避免海温超过 29 °C。需要进一步评估金枪鱼物种特有的长期海温趋势,以充分考虑全球变暖对海洋的影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
6.40
自引率
16.70%
发文量
115
审稿时长
3 months
期刊介绍: Deep-Sea Research Part II: Topical Studies in Oceanography publishes topical issues from the many international and interdisciplinary projects which are undertaken in oceanography. Besides these special issues from projects, the journal publishes collections of papers presented at conferences. The special issues regularly have electronic annexes of non-text material (numerical data, images, images, video, etc.) which are published with the special issues in ScienceDirect. Deep-Sea Research Part II was split off as a separate journal devoted to topical issues in 1993. Its companion journal Deep-Sea Research Part I: Oceanographic Research Papers, publishes the regular research papers in this area.
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