Browsing by Author "Miyagawa, Mitsuyo"

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    Open Access
    Further exploratory investigations of some simple candidate management procedures for southern bluefin tuna
    (2018) Butterworth, Doug S; Miyagawa, Mitsuyo; Jacobs, Melissa
    Target type CMPs for SBT presented to the Seattle meeting are refined and extended to include the input of CKMR information through use of the associated TRO index developed by Hillary. Essentially CMPs, tuned to median recovery to 30% of the pristine TRO in 2035 are developed for each of the CPUE, gene tagging and CKMR data sets alone, and then weighted combinations of these are considered. A subset of the robustness tests which show the gre atest differences in performance compared to the base/reference c ase (RC) OM are selected. Overall the CMP based on the CKMR data only seems to perform best for the RC, but when the selected robustness test results are also taken into account, a variant based on a weighted combination of CMPs using all three data types seems marginally preferable.
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    Open Access
    Initial exploratory investigations of some simple candidate management procedures for southern Bluefin tuna.
    (2018) Butterworth, Doug S; Miyagawa, Mitsuyo; Jacobs, Melissa
    Simple constant proportion and target based empirical candidate management procedures are applied to the basic grid operating model and a low recruitment robustness test for SBT . The first two approaches , DMM1 and DMM2 , respectively use CPUE index data only, while DMM3 ad ds gene tagging data to the DMM2 approach. The key results are that the DMM2 target based approach substantially outperforms the constant proportion DMM1 one in terms of smoothness of the TAC trajectories, and that (at least as far as investigations have b een possible to date) the addition of gene tagging data offers little improvement to depletion statistics in instances where low recruitment has occurred . Performance under DMM2 is unusually good, but this approach still needs to be subjected to the other robustness tests, and further attempts need to be made to seek more improvement in performance when gene tagging data are used.