Application of Fishery-independent Data as an Alternative Source for Determining Relative Abundance Indices of Blue Marlin, Makaira nigricans (Actinopterygii: Perciformes: Istiophoridae) in the North-eastern Indian Ocean
The present study aimed to determine the abundance index of blue marlin, Makaira nigricans (Lacepède, 1802) utilizing fishery-independent data, i.e., scientific observer, and attempted to bridge the research's gap for low coverage information in the north eastern Indian Ocean. A total of 2,984...
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Veröffentlicht in: | Turkish journal of fisheries and aquatic sciences 2022-05, Vol.22 (5) |
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creator | Setyadji, Bram Parker, Denham Wang, Sheng-Ping |
description | The present study aimed to determine the abundance index of blue marlin, Makaira nigricans (Lacepède, 1802) utilizing fishery-independent data, i.e., scientific observer, and attempted to bridge the research's gap for low coverage information in the north eastern Indian Ocean. A total of 2,984 set-by-set observer data from 2006-2018, spatially disaggregated by one-degree blocks, were obtained from the Indonesian scientific observer program following commercial longline fleets. A delta-lognormal model was chosen to fit the dataset, using catch as the response variable with seven covariates. A backward procedure based on AIC, BIC and R2 were used to select the best model. Overall, the delta-Gamma performs better when modelling data with a high proportion of zeros than other traditional models. The blue marlin CPUE trend is relatively stable over time, despite the inter-annual fluctuations, which are likely a result of natural variation in the population as opposed to operational changes or inter-annual environmental variation. Given the low spatial coverage compared to logbook data, scientific observer data performed well and produced a robust abundance index of blue marlin in the northeastern Indian Ocean. |
doi_str_mv | 10.4194/TRJFAS19142 |
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A total of 2,984 set-by-set observer data from 2006-2018, spatially disaggregated by one-degree blocks, were obtained from the Indonesian scientific observer program following commercial longline fleets. A delta-lognormal model was chosen to fit the dataset, using catch as the response variable with seven covariates. A backward procedure based on AIC, BIC and R2 were used to select the best model. Overall, the delta-Gamma performs better when modelling data with a high proportion of zeros than other traditional models. The blue marlin CPUE trend is relatively stable over time, despite the inter-annual fluctuations, which are likely a result of natural variation in the population as opposed to operational changes or inter-annual environmental variation. 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A total of 2,984 set-by-set observer data from 2006-2018, spatially disaggregated by one-degree blocks, were obtained from the Indonesian scientific observer program following commercial longline fleets. A delta-lognormal model was chosen to fit the dataset, using catch as the response variable with seven covariates. A backward procedure based on AIC, BIC and R2 were used to select the best model. Overall, the delta-Gamma performs better when modelling data with a high proportion of zeros than other traditional models. The blue marlin CPUE trend is relatively stable over time, despite the inter-annual fluctuations, which are likely a result of natural variation in the population as opposed to operational changes or inter-annual environmental variation. Given the low spatial coverage compared to logbook data, scientific observer data performed well and produced a robust abundance index of blue marlin in the northeastern Indian Ocean.</description><subject>Abundance</subject><subject>Annual variations</subject><subject>Catch per unit effort</subject><subject>Fisheries</subject><subject>Fishery data</subject><subject>Logbooks</subject><subject>Longline fishing</subject><subject>Makaira nigricans</subject><subject>Marine fishes</subject><subject>Observers</subject><subject>Relative abundance</subject><issn>1303-2712</issn><issn>1303-2712</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><recordid>eNpNUU1v1DAQjSoqtbSc-AMjcQGVgD-SOOktbVlYVChqyzmadSa7Llk7tb2V9r_yY_CyPfQybzTz9N7TTJa95exTwZvi8_3t91l7xxteiIPsmEsmc6G4ePWiP8peh_DAWKlEIY-zv-00jUZjNM6CG2Bmwor8Nje2p4lSsRGuMCJgALTQjpG8Tewngju38ZpgcB6uKI3Xxhq7hFsa9_t2sbE92kSZ295oCjv9i3FD8AP9aOzHhH_QeARrlj5lsAHetzoa66Ykt10acw6_yGuTLNYUzmEeUsxp5bzpkT6AsRBXBD-dj6ucMOyi_fdKQW80oT3NDgccA715xpPs9-zL_eW3_Prm6_yyvc41r6uYF6LBmklWNhoV1krxRaUFk4WiXui-oEo0i1IL1TREyKREJUouy0FqVlVsIU-yd3vdybvHDYXYPaTb2GTZiaqsRV2qUibW2Z6lvQvB09BN3qzRbzvOut37uhfvk_8AnjGQvQ</recordid><startdate>20220501</startdate><enddate>20220501</enddate><creator>Setyadji, Bram</creator><creator>Parker, Denham</creator><creator>Wang, Sheng-Ping</creator><general>Central Fisheries Research Institute</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7QH</scope><scope>7TN</scope><scope>7UA</scope><scope>C1K</scope><scope>F1W</scope><scope>H95</scope><scope>H97</scope><scope>L.G</scope><orcidid>https://orcid.org/0000-0002-0647-160X</orcidid></search><sort><creationdate>20220501</creationdate><title>Application of Fishery-independent Data as an Alternative Source for Determining Relative Abundance Indices of Blue Marlin, Makaira nigricans (Actinopterygii: Perciformes: Istiophoridae) in the North-eastern Indian Ocean</title><author>Setyadji, Bram ; Parker, Denham ; Wang, Sheng-Ping</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c186t-429a803059ca7a8771b6c20347ed2cd4e629b5c2799eea033a725135f3c0660b3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>Abundance</topic><topic>Annual variations</topic><topic>Catch per unit effort</topic><topic>Fisheries</topic><topic>Fishery data</topic><topic>Logbooks</topic><topic>Longline fishing</topic><topic>Makaira nigricans</topic><topic>Marine fishes</topic><topic>Observers</topic><topic>Relative abundance</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Setyadji, Bram</creatorcontrib><creatorcontrib>Parker, Denham</creatorcontrib><creatorcontrib>Wang, Sheng-Ping</creatorcontrib><collection>CrossRef</collection><collection>Aqualine</collection><collection>Oceanic Abstracts</collection><collection>Water Resources Abstracts</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ASFA: Aquatic Sciences and Fisheries Abstracts</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) 1: Biological Sciences & Living Resources</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) 3: Aquatic Pollution & Environmental Quality</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) Professional</collection><jtitle>Turkish journal of fisheries and aquatic sciences</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Setyadji, Bram</au><au>Parker, Denham</au><au>Wang, Sheng-Ping</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Application of Fishery-independent Data as an Alternative Source for Determining Relative Abundance Indices of Blue Marlin, Makaira nigricans (Actinopterygii: Perciformes: Istiophoridae) in the North-eastern Indian Ocean</atitle><jtitle>Turkish journal of fisheries and aquatic sciences</jtitle><date>2022-05-01</date><risdate>2022</risdate><volume>22</volume><issue>5</issue><issn>1303-2712</issn><eissn>1303-2712</eissn><abstract>The present study aimed to determine the abundance index of blue marlin, Makaira nigricans (Lacepède, 1802) utilizing fishery-independent data, i.e., scientific observer, and attempted to bridge the research's gap for low coverage information in the north eastern Indian Ocean. A total of 2,984 set-by-set observer data from 2006-2018, spatially disaggregated by one-degree blocks, were obtained from the Indonesian scientific observer program following commercial longline fleets. A delta-lognormal model was chosen to fit the dataset, using catch as the response variable with seven covariates. A backward procedure based on AIC, BIC and R2 were used to select the best model. Overall, the delta-Gamma performs better when modelling data with a high proportion of zeros than other traditional models. The blue marlin CPUE trend is relatively stable over time, despite the inter-annual fluctuations, which are likely a result of natural variation in the population as opposed to operational changes or inter-annual environmental variation. Given the low spatial coverage compared to logbook data, scientific observer data performed well and produced a robust abundance index of blue marlin in the northeastern Indian Ocean.</abstract><cop>Trabazon</cop><pub>Central Fisheries Research Institute</pub><doi>10.4194/TRJFAS19142</doi><orcidid>https://orcid.org/0000-0002-0647-160X</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Abundance Annual variations Catch per unit effort Fisheries Fishery data Logbooks Longline fishing Makaira nigricans Marine fishes Observers Relative abundance |
title | Application of Fishery-independent Data as an Alternative Source for Determining Relative Abundance Indices of Blue Marlin, Makaira nigricans (Actinopterygii: Perciformes: Istiophoridae) in the North-eastern Indian Ocean |
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