Standardizing catch and effort data of the Taiwanese distant-water longline fishery in the western and central Pacific Ocean for bigeye tuna, Thunnus obesus

• Published in: Fisheries research Vol. 90; no. 1; pp. 235 - 246
• Main Authors: Su, Nan-Jay, Yeh, Su-Zan, Sun, Chi-Lu, Punt, André E., Chen, Yong, Wang, Sheng-Ping
• Format: Journal Article
• Language: English
• Published: Amsterdam Elsevier B.V 01-04-2008; Elsevier
• Subjects: Agnatha. Pisces; Animal, plant and microbial ecology; Applied ecology; Bigeye tuna; Biological and medical sciences; CPUE; Delta approach; Exploitation and management of natural biological resources (hunting, fishing and exploited populations survey, etc.); Fundamental and applied biological sciences. Psychology; GAM; GLM; Marine; Standardization; Thunnus albacares; Thunnus obesus; Vertebrates: general zoology, morphology, phylogeny, systematics, cytogenetics, geographical distribution; West Pacific; Pacific Ocean; I, Central Pacific; GLM; CPUE; GAM; Bigeye tuna; Delta approach; Standardization; Additive model; Marine environment; Longline; Vertebrata; Fishery; Delta; Pisces; Catch effort
• ISSN: 0165-7836; 1872-6763
• DOI: 10.1016/j.fishres.2007.10.024

Catch per unit effort (CPUE) is often used as an index of relative abundance in fisheries stock assessments. However, the trends in nominal CPUE can be influenced by many factors in addition to stock abundance, including the choice of fishing location and target species, and environmental conditions. Consequently, catch and effort data are usually ‘standardized’ to remove the impact of such factors. Standardized CPUE for bigeye tuna,
Thunnus obesus, caught by the Taiwanese distant-water longline fishery in the western and central Pacific Ocean (WCPO) for 1964–2004 were derived using three alternative approaches (GLM, GAM and the delta approach), and sensitivity was explored to whether catch-rates of yellowfin tuna and albacore tuna are included in the analyses. Year, latitude, and the catch-rate of yellowfin explained the most of the deviance (32–49%, depending on model configuration) and were identified consistently among methods, while trends in standardized catch-rate differed spatially. However, the trends in standardized catch-rates by area were found to be relatively insensitive to the approach used for standardization, including whether the catch-rates of yellowfin and albacore were included in the analyses.