Precision of Estimated Growth Parameters of Yellowfin Tuna (<i>Thunnus albacares</i>) From Length‐Frequency Data Estimated by Bootstrapping

ABSTRACT Over 60% of the world's fish stocks suffer from limited data, which hampers effective fisheries management. Researchers have developed stock assessment methods for data‐limited fisheries using length‐frequency data, but reliability was questionable and not well researched. We evaluated the precision of the widely used length‐based method ELEFAN using 24 months of length‐frequency data from 14,190 individual yellowfin tuna and sequential and interval data fractions. Using bootstrapping (1000 times) and data reduction, growth parameters and precision , , and Φ ′ were estimated. The CVs of , , and Φ ′ were 2.55%, 23.04%, and 2.35%, respectively. From the result of data reduction, at least once in 1 or 2 months and 12 times measurements with 500 data per measurement on average is recommended for achieving high precision with CV of Φ ′ &lt; 3%.