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Subject: Re: fisheries data analysis
From: "Donald R. Kobayashi" <[log in to unmask]>
Reply-To:Scientific forum on fish and fisheries <[log in to unmask]>
Date:Wed, 23 Jun 2004 08:59:51 -1000

TEXT/PLAIN (49 lines)

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Agree, and it might be useful to build a simulation model which takes
into account known growth, mortality, and any pertinant spatial
population structure, and play with selection curves. Size/age dependent
gear selection, and likewise for retention/marketing. Basically you're
building a time series dataset of landed size/age frequencies, changes
therein reflect a lot of processes, certainly growth, recruitment,
mortality, and the entire catching/retaining/marketing process. It's not
too astounding that there will be significant differences in the landed
sizes when comparing season, location, and vessel. And I don't think
treating average size or age as a normal variable is wise, size/age
frequencies are very complex usually multimodal distributions.  I'd
suggest caution, unless the coverage is very complete it would be easy
to start finding significant relationships everywhere when it could be
something as basic as -growth-.  Just my $0.02, consult a lot of people
on this and find consensus on appropriate analysis and experimental
design of your port sampling...  -Don

On Tue, 22 Jun 2004, Trevor J. Kenchington wrote:

> ...
> However, the various replies to date, with their recommendation of using
>   a Generalized Linear Model, all appear (to me) to face a problem that
> Antonio's ANOVA would also face. That is, each observation would have to
> comprise a single value for shell height, whereas the data are more
> likely to take the form of a shell-height frequency.
> Can GLM cope with that extra dimension in the data, treating the
> frequency as a frequency? That would be ideal, if it can be done.

Donald R. Kobayashi, Fishery Biologist
Ecosystems & Oceanography Division
Pacific Islands Fisheries Science Center
2570 Dole Street, Honolulu HI 96822-2396
Voice:808-983-5394 FAX:808-983-2902 ([log in to unmask])

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