Spatiotemporal distribution of shrimp assemblages in the western coastal waters off Taiwan at the Tropic of Cancer, Western Pacific Ocean-Reference-Cited by-同舟云学术

Spatiotemporal distribution of shrimp assemblages in the western coastal waters off Taiwan at the Tropic of Cancer, Western Pacific Ocean

Published:2021-07 Issue: Volume:255 Page:107356
ISSN:0272-7714
Container-title:Estuarine, Coastal and Shelf Science
language:en
Short-container-title:Estuarine, Coastal and Shelf Science

Author:

Chen Hsu-Sen^ORCID,Chen Kuo-Shu^ORCID,Chen Chiee-Young,Hung Chin-Chang,Meng Pei-Jie,Chen Meng-Hsien^ORCID

Funder

Ministry of Science and Technology, Taiwan

Publisher

Elsevier BV

Subject

Aquatic Science,Oceanography

Reference40 articles.

1. Pandalid shrimp as indicators of ecosystem regime shift;Anderson;J. Northwest Atl. Fish. Sci.,2000

2. Sediment and distribution of penaeid shrimp in the Sudanese Red Sea;Branford;Estuar. Coast Shelf Sci.,1981

3. Biology of the cocktail shrimp, Trachysalambria curvirostris (Decapoda: penaeidae) in the yellow sea of korea;Cha;J. Mar. Biol. Assoc. U. K.,2004

4. Comparison of the catch compositions of the shrimp beam trawl fishery in the three areas off the southwestern coast of Taiwan;Chen;J. Fish. Soc. Taiwan,2001

5. Life history tactics of southern velvet shrimp Metapenariopsis palmensis (Crustacea, Decapoda) in the waters off southwestern Taiwan;Chen;Hydrobiologia,2014

Cited by 5 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Effects of juvenile mortality on population dynamics of Penaeus semisulcatus: A case study from Sri Lanka;Fisheries Research;2024-06

2. A 2 °C difference affecting the spatiotemporal distribution of small demersal fish assemblages in shallow tropical and subtropical waters of Western Taiwan;Scientific Reports;2023-11-17

3. Groundwater monitoring and specific yield estimation using time-lapse electrical resistivity imaging and machine learning;Frontiers in Environmental Science;2023-07-14

4. Integrate deep learning and physically-based models for multi-step-ahead microclimate forecasting;Expert Systems with Applications;2022-12

5. Deep neural networks for spatiotemporal PM2.5 forecasts based on atmospheric chemical transport model output and monitoring data;Environmental Pollution;2022-08