11th Joint Norwegian-Russian Fisheries Science Symposium
An evaluation of the
methodology for prediction of capelin biomass
B. Bogstad, H. Gjøsæter, N. Ushakov, D. Prozorkevitch
Aim of study
To evaluate one aspect of the methodology used in capelin
assessment, viz. the prediction of
capelin biomass one year ahead of time
Background
Since 1972, the capelin stock in the Barents Sea has been surveyed by an annual acoustic survey in autumn
The assessment of the stock for
management purposes is based solely on this survey, since it is difficult to
measure the stock size at other times of the year
Backgroud
The current methodology for
assessment of the Barents Sea capelin stock, using a combination of the
multispecies model Bifrost and the
spreadsheet model CapTool run in the
@RISK add-in to MS Excel, has been applied since 1997
Background
The models have been steadily
enhanced, and from 1999 a one-year prediction of biomass of 1+ capelin
from the autumn survey to the time of the next autumn survey was included
Background
Such predictions include many sources of uncertainty, but might be of value for some purposes, e.g. for giving a first
prediction of the amount of capelin available as food for cod and other predators during the coming year
Methods
The prediction model used in recent years, was rerun on materials back to 1981
The prediction made in year Y was compared with the measurement made in year Y+1
The period prior to 1981 was excluded because the coverage of 1-year-olds was defective
Results – stock history
Biomass and Catch of Barents Sea capelin
0 1 2 3 4 5 6 7 8 9
1973 1976 1979 1982 1985 1988 1991 1994 1997 2000 2003 Year
Million tonnes Biomass
Catch
Results – age 0 vs age 1
Capelin age 0 vs age 1 abundance
y = 1.8125x + 46.007 R2 = 0.5955
0 100 200 300 400 500 600 700 800
0 50 100 150 200 250 300 350 400
0-group
age 1
Results – total stock
0 2 4 6 8 10 12
1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004
Biomass (mill tonnes)
Predicted Observed
Results – one-year-olds
0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0
1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004
million tonnes
Predicted (age 1) Observed (age 1)
Results – ratio time series
0 1 2 3 4 5 6 7 8 9 10
1982 1985 1988 1991 1994 1997 2000 2003
Biomass (mill tonnes)
0 1 2 3 4 5 6 7 8 9 10
Ratio
Observed stock size
Ratio predicted/observed
Results – ratio vs stock size
0 1 2 3 4 5 6 7 8 9 10
0 2 4 6 8
Observed stock size (mill t.)
Ratio predicted/observed
Above 1 mill tonnes, no relationship between ratio predicted/observed and stock stize
Discussion
In this evaluation, we have not been able to compensate our predictions for catches of juveniles. This leads to
overestimation in such cases. The
predictions are in fact better than they seem to be based on this study
Conclusions
The average residual per year is 96 thousand tonnes, out of which 21 thousand tonnes stem from the
prediction of 1-year-olds from 0-group
The predictions lags behind the development of the stock: We
overestimate when stock is declining and vice versa
Future work
The models will be enhanced as soon as new knowledge is available
If, for instance, the mortality can be related to environmental factors
predictable one year ahead of time, this could be implemented in the model
