MULTIFAN a Likelihood-Based Method for Estimating Growth Parameters and Age Composition from Multiple Length Frequency Data Sets Illustrated using Data for Southern Bluefin Tuna (Thunnus maccoyii)

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Abstract
We present a method for simultaneously analyzing multiple length frequency data sets. The method utilizes a robust likelihood-based estimation procedure that provides an objective criterion for hypothesis testing. The method is applied to length frequency data from southern bluefin tuna (Thunnus maccoyii) for which independent estimates of growth parameters based on tag return data are available. The estimates of the growth parameters from the new method were found to be in substantial agreement with the values previously obtained for these parameters. The strength of the likelihood approach is demonstrated by discriminating between alternative structural hypotheses for describing the data. The ability to simultaneously analyze multiple samples permits the method to exploit the extra information not available when analyzing samples one by one. The computer program maintains a database of fits to the data which enable the user to organize the results of the analysis. Graphical displays permit the user to view any of the fits, and an interactive graphics routine aids the user to find good initial parameter estimates.