Dear SS experts,
I am working with a sex-specific length-based model for hake
and I have a question regarding the Recruitment Deviation Setup. To
give some context, the model data starts in 1960 and the
length-frequency information starts in 1982, before which only catch
data are available. The current setup of recruitment deviations is
shown below (the last four values were established following the SS
suggestion in the html RecDev page).
1983 # first year of main recr_devs; early devs can preceed this
era
2022 # last year of main recr_devs; forecast devs start in
following year
-10 #_recdev_early_start (0=none; neg value
makes relative to recdev_start)
1965
#_last_yr_nobias_adj_in_MPD; begin of ramp
1989
#_first_yr_fullbias_adj_in_MPD; begin of plateau
2019
#_last_yr_fullbias_adj_in_MPD
2023 #_end_yr_for_ramp_in_MPD
As see above there are several parameters that need to be defined in
the Recruitment Deviation Setup. The first two are the main
recruitment deviations start and end year. I understand that the main
recruitment deviations should start when there is meaningful data to
support it, for example in our case it can start when the length
frequency distribution starts and we can end the period in the last
year of the model. However, we also have more parameters:
Last year with no bias adjustment.
First year with full bias
adjustment
Last year with full bias adjustment
First
recent year with no bias adjustment
I understand that the years with full bias adjustment are supposed to
be the years where there is enough information to do this, but what is
enough information to do this? I see that the default is start year
Nages because of the cohorts information, is there other hints to
establish it? Another doubt is why the last year without bias
adjustment can be before the main recruitment deviations start
year?
Other doubt is the role of the Early Recruitment
Deviation Start Year because I read Method (2011) and this clarify how
Main Recruitment Deviations are geneared but I don't manage to
understand the role of the Early?
Thank you very much for helping, if you can provide any ideas
regarding this, we really appreciate that.
Methot, R.D., Taylor, I.G. and Chen, Y. 2011. Adjusting for bias due
to variability in estimated recruitment in fishery assessment models.
Canadian Journal of Fisheries and Aquatic Sciences 68(10): 1744–1760. doi:10.1139/f2011-092.