Presentation is loading. Please wait.

Presentation is loading. Please wait.

Estimating long term yield of cod from Bifrost Sigurd Tjelmeland.

Similar presentations

Presentation on theme: "Estimating long term yield of cod from Bifrost Sigurd Tjelmeland."— Presentation transcript:

1 Estimating long term yield of cod from Bifrost Sigurd Tjelmeland

2 Estimating long-term yield Must be done by long term simulation Since cod and capelin interact recruitment relations (recruits as function of spawning stock) for both cod and capelin are needed

3 Basics of Bifrost - Steps Calculate stochastic inputs –Capelin –Consumption per cod Estimate perameters Estimate recruitment relations Simulate

4 Basics of Bifrost (documented on Capelin-cod simulator Herring affects capelin recruitment –Forward simulations: Bifrost and SeaStar are coupled Input data –Stochastic September estimates of capelin –Catch data for capelin Monthly by age Divided by maturing component –Stochastic consumption per cod by quarter of Capelin Cod Other food –Cod assessment from Arctic Fisheries WG –Stochastic herring assessment from SeaStar

5 Basics of Bifrost (documented on Modelling –Large number of recruitment relations per historic replicate, AIC –Overlap model depending on cod and capelin stock size –Cannibalism modelled after size distributions –Weight and maturation estimated internally, malformation of eggs implemented –Proportion immature capelin being preyed, proportion mature cod preying Estimation –Overall likelihood Capelin: Age 4 during 1970s, lognormal Consumption by quarter of capelin,cod and other food, lognormal Inner loop –Capelin age 1 –Cod age 0 –Capelin residual M Other parameters

6 Recruitment in Bifrost A large number of apriori possible formulations of the spawning stock – recruitment relation exist –Part of the model uncertainty –Estimates a large number on each historic replicate –Draws one using Akaike’s weights for each run Best balance between fit and number of parameters Capelin independent variables –Herring –0-group herring –Temperature –0-group cod –Inflection point –Different levels of lowest herring abundance Cod independent variables –Temperature –Mean weight –Mean Age Possible estimation of exponents Lognormal, gamma, weibull Covariates possibly in halfvalue Different months for temperature in Kola section

7 Recruitment in Bifrost Capelin Cod

8 Fit to data - Consumption

9 Fit to data - Capelin

10 Results

11 Warning – periods of different productivity!

Download ppt "Estimating long term yield of cod from Bifrost Sigurd Tjelmeland."

Similar presentations

Ads by Google