Comparisons on Adopted Production Models of Assessing the South Atlantic Albacore Stock

• Main Authors: Feng-Chen Chang, 張鳳貞
• Other Authors: Shean-Ya Yeh
• Format: Others
• Language: en_US
• Published: 2012
• Online Access: http://ndltd.ncl.edu.tw/handle/90812951293195273237

博士 === 國立臺灣大學 === 海洋研究所 === 100 === Mainly based on 1967-2010 area-time catch and effort data reported from Taiwanese vessels fishing on South Atlantic albacore, this study aimed at (1) comparing generalized linear (GLM) and generalized additive (GAM) models with/without sea surface temperature (SST) factor for obtaining a better abundance indices trend of the stock; (2) comparing the age-structured production (ASPM), a stock production model incorporating covariates (ASPIC), and Baysian surplus production (BSP) models for obtaining a precautious criteria of 50% risk at which the sustainable total allowable catch (TAC) level can be determined. The results obtained as follows: (1) area factor appears to be the most explanatory factor to express the total variation in GLM; (2) the addition of SST factor into GLM will only add small explanatory power as compared to without SST factor, adding SST into GAM, on the other hand, does explain its concentration at 14~19℃ SST; (3) mean body weight of measured albacore in Alb_34 appeared higher in the years of 1997~1999 as compared with other years; (4) the monthly mean SST (June ~ October) in the period of 1997~1999 (years of heavy El Nino) of Alb_34 appeared to be significantly different from those of 2002~2004 based on NOAA data; (5) if the criteria of a constant TAC "which assures that there appears a risk of smaller than 50% chance that the prospecting SSB/SSB2010 will reach the value always greater than 1 in 5-years" is proposed as such, the model-predicted TACs were: 24,000mt, 20,000mt, and 25,000mt by using ASPM, ASPIC and BSP models, respectively; (6) an overall comparison on these three models suggested the ASPM appeared to be the most promising, judged by its structural soundness of model components and managerial applicability on fishing practice, for assessing and managing the South Atlantic albacore resource.