Modeling the potential distribution of the neon flying squid (Ommastrephes bartramii) in the Northwest Pacific Ocean based on a MaxEnt model
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1. College of Marine Sciences, Shanghai Ocean University, Shanghai 201306, China;
2. Key Laboratory of Oceanic Fisheries Exploration, Ministry of Agriculture and Rural Affairs, Shanghai 201306, China;
3. National Engineering Research Center for Oceanic Fisheries, Shanghai Ocean University, Shanghai 201306, China;
4. Key Laboratory of Sustainable Exploitation of Oceanic Fisheries Resources, Ministry of Education, Shanghai Ocean University, Shanghai 201306, China;
5. Scientific Observing and Experimental Station of Oceanic Fishery Resources, Ministry of Agriculture and Rural Affairs, Shanghai 201306, China

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S93

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    Abstract:

    The neon flying squid (), found in the Northwest Pacific Ocean, is a species of great economic importance. It is mainly caught by fishing fleets from and consumed in China (including Taiwan), Japan, and other countries and regions. The winter-spring cohort of is a short-lived species with a lifespan of about one year. The abundance and distribution of are influenced by global climate change and local marine environmental changes, such as El Nia events, Pacific interdecadal oscillation, currents, sea surface temperature (SST), chlorophyll-a (Chl a) concentrations, etc. The monthly potential habitat distribution of neon flying squid in the Northwest Pacific Ocean during the peak fishing season (July-October) was explored by using maximum entropy (MaxEnt) models; these models were fitted with squid fishery data obtained from Chinese commercial squid-jigging vessels from 2011 to 2015 and five oceanographic environmental factors derived from remote sensing data (SST; Chl a concentration; net primary productivity, NPP; mixed layer depth, MLD; sea level anomaly, SLA). The accuracy of the monthly MaxEnt models was evaluated by the area under receiver operating characteristic (ROC) curve (AUC). The simulated by a different MaxEnt model for each month, were imported into ArcGIS for visual analysis. The values obtained from probabilistic modeling were defined as habitat suitability index (HSI) and divided manually. When HSI>0.6, the sea area was considered as the most suitable area for ; when 0.4

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龚彩霞,陈新军,高峰. 基于最大熵模型模拟西北太平洋柔鱼潜在栖息地分布[J]. Jounal of Fishery Sciences of China, 2020,[volume_no](3):336-345

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  • Received:
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  • Online: March 11,2020
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