The Influence of Ocean Surface Temperature Variability on Saury Shoal Displacement

Goldman, R. S.; Ilyichev, V. I.; Smirnykh, L. P.

doi:10.1007/978-94-011-2773-8_15

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“…For example, the temperature has an influence on fish parasites 36 and fish community structure 37 . DT, belonging to the level two in group B, had an immense effect on bottom NASC, which was also one of the important dynamic factors in the first level, indicating that temperature change greatly influenced fish behavior 38,39 . However, the sensitivity and extent of the reaction to temperature variation differed with species and age 40 .…”

Section: Contribution Of the Factors To Surface And Bottom Nascmentioning

confidence: 99%

A method to analyze the sensitivity ranking of various abiotic factors to acoustic densities of fishery resources in the surface mixed layer and bottom cold water layer of the coastal area of low latitude: a case study in the northern South China Sea

Sun

Cai

Zhang

et al. 2020

Sci Rep

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This is an exploratory analysis combining artificial intelligence algorithms, fishery acoustics technology, and a variety of abiotic factors in low-latitude coastal waters. This approach can be used to analyze the sensitivity level between the acoustic density of fishery resources and various abiotic factors in the surface mixed layer (the water layer above the constant thermocline) and the bottom cold water layer (the water layer below the constant thermocline). The fishery acoustic technology is used to obtain the acoustic density of fishery resources in each water layer, which is characterized by Nautical Area Scattering Coefficient values (NASC), and the artificial intelligence algorithm is used to rank the sensitivity of various abiotic factors and NASC values of two water layers, and the grades are classified according to the cumulative contribution percentage. We found that stratified or multidimensional analysis of the sensitivity of abiotic factors is necessary. One factor could have different levels of sensitivity in different water layers, such as temperature, nitrite, water depth, and salinity. Besides, eXtreme Gradient Boosting and random forests models performed better than the linear regression model, with 0.2 to 0.4 greater R 2 value. The performance of the models had smaller fluctuations with a larger sample size. The thermocline in the low latitude sea area is permanent, the upper layer of the thermocline is a surface mixed layer, and the lower layer of the thermocline is the bottom cold water layer. The distribution of fishery organisms and their driving factors in the perfusing water layers (especially the surface mixed layer and the bottom cold water layer) deserves further investigation. The offshore of the northern South China Sea is a typical representative of low-latitude coastal waters, and it is also an important traditional fishery production operation in China, owing to its good climate that offers a conducive habitat for the marine life, a spawning site, and a place for fattening and farming of fish. However, fishery resources have increasingly become small and of reduced quality 1,2. Resource density, the single yield of fishing vessels, and catch quality are declining. The catch rates

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