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Investigation of demersal fish using Autonomous Underwater Vehicle - Kichiji Rockfish,Sebastrobus macrochir (Günther,1877),surveys and challenges

Investigation of demersal fish using Autonomous Underwater Vehicle - Kichiji Rockfish,Sebastrobus macrochir (Günther,1877),surveys and challenges
Investigation of demersal fish using Autonomous Underwater Vehicle - Kichiji Rockfish,Sebastrobus macrochir (Günther,1877),surveys and challenges
This study examines the survey of demersal fish resources using Autonomous Underwater Vehicles (AUVs) equipped with cameras. We have surveyed Kichiji Rockfish (Sebastolobus macrochir) and analyzed multi-year field data collected by the AUV Tuna-Sand in the Sea of Okhotsk (mean depth 600m) between 2013 and 2015. More than18,800 strobe-illuminated images covering 4.7 ha along a total 26.5 km transect were analyzed to determine the distribution of individuals and their sizes at different time periods,and to generate biomass estimates. The results were validated using trawl data,and showed good agreement. The major advantages of the introduction of AUVs are 1) it provides high resolution information on the relative position of individuals based on accurate AUV location data,2) it has significantly less environmental impact,3) it allows for high repeatability that conventional trawl surveys. The results demonstrate that the natural sparsity of the Kichiji distribution is an important factor in survey track-line design and data analysis. Consequently,this paper recommends best practices for reliable resource estimation
Sugimatsu, Harumi
397df4fb-cbf7-4a12-abcf-df2245976a37
Nishida, Yuya
3128a94d-c57f-4933-8433-d2c57e3bd1ca
Takashima, Sotaro
cea6bb02-4779-48e9-8487-9901adacea7f
Nagano, Kazunori
49129778-f2c4-4e6c-ac1d-8ac67dce16a4
Inoue, Shogo
3b160baf-aa12-4c6d-b418-b4f8b17cb0f0
Thornton, Blair
8293beb5-c083-47e3-b5f0-d9c3cee14be9
Ura, Tamaki
b8fea5ba-e731-40fd-8544-1db1ca9f356b
Hamatsu, Tomonori
284de275-240d-42ef-89b0-d34b1d7fd308
Sugimatsu, Harumi
397df4fb-cbf7-4a12-abcf-df2245976a37
Nishida, Yuya
3128a94d-c57f-4933-8433-d2c57e3bd1ca
Takashima, Sotaro
cea6bb02-4779-48e9-8487-9901adacea7f
Nagano, Kazunori
49129778-f2c4-4e6c-ac1d-8ac67dce16a4
Inoue, Shogo
3b160baf-aa12-4c6d-b418-b4f8b17cb0f0
Thornton, Blair
8293beb5-c083-47e3-b5f0-d9c3cee14be9
Ura, Tamaki
b8fea5ba-e731-40fd-8544-1db1ca9f356b
Hamatsu, Tomonori
284de275-240d-42ef-89b0-d34b1d7fd308

Sugimatsu, Harumi, Nishida, Yuya, Takashima, Sotaro, Nagano, Kazunori, Inoue, Shogo, Thornton, Blair, Ura, Tamaki and Hamatsu, Tomonori (2023) Investigation of demersal fish using Autonomous Underwater Vehicle - Kichiji Rockfish,Sebastrobus macrochir (Günther,1877),surveys and challenges. Journal of the Japan Society for Marine Surveys and Technology.

Record type: Article

Abstract

This study examines the survey of demersal fish resources using Autonomous Underwater Vehicles (AUVs) equipped with cameras. We have surveyed Kichiji Rockfish (Sebastolobus macrochir) and analyzed multi-year field data collected by the AUV Tuna-Sand in the Sea of Okhotsk (mean depth 600m) between 2013 and 2015. More than18,800 strobe-illuminated images covering 4.7 ha along a total 26.5 km transect were analyzed to determine the distribution of individuals and their sizes at different time periods,and to generate biomass estimates. The results were validated using trawl data,and showed good agreement. The major advantages of the introduction of AUVs are 1) it provides high resolution information on the relative position of individuals based on accurate AUV location data,2) it has significantly less environmental impact,3) it allows for high repeatability that conventional trawl surveys. The results demonstrate that the natural sparsity of the Kichiji distribution is an important factor in survey track-line design and data analysis. Consequently,this paper recommends best practices for reliable resource estimation

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e-pub ahead of print date: 16 March 2023

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Local EPrints ID: 483359
URI: http://eprints.soton.ac.uk/id/eprint/483359
PURE UUID: 1773a97d-428e-4a14-ad48-989c6e4d4686

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Date deposited: 30 Oct 2023 09:21
Last modified: 17 Mar 2024 02:31

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Contributors

Author: Harumi Sugimatsu
Author: Yuya Nishida
Author: Sotaro Takashima
Author: Kazunori Nagano
Author: Shogo Inoue
Author: Blair Thornton
Author: Tamaki Ura
Author: Tomonori Hamatsu

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