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Consequences of changing climate for North Atlantic cod stocks and implications for fisheries management Keith Brander ICES/GLOBEC Coordinator. Cod stocks included in the analysis of recruitment. NE Arctic. Baltic. Iceland. Faroe. W Baltic. North Sea. W Scotland. 2J3KL. Georges Bank.

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Baltic

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  1. Consequences of changing climate for North Atlantic cod stocks and implications for fisheries managementKeith BranderICES/GLOBEC Coordinator

  2. Cod stocks included in the analysis of recruitment NE Arctic Baltic Iceland Faroe W Baltic NorthSea W Scotland 2J3KL Georges Bank IrishSea 4X 4VsW CelticSea

  3. Why use NAO? • Well studied climate indicator • Range of biological effects • Values are timely and free • NAO does not have local values {With T and other hydroclimatic variables you have to select a specific value} • There is a geographic pattern of NAO effects on T, cloud, wind, precipitation

  4. “Classic surface signature” Correlation between winter NAO (DJFM) and sea surface temperature (SST) in March to May 1948-2000 SST values are from NCEP/NCAR reanalysis

  5. Decadal mean NAO values 2004 Further reading on how the NAO is coupled to global climate processes: http://www.cgd.ucar.edu/~jhurrell/press.html#trs

  6. Stock and recruitment data for 13 cod stocks

  7. Fitting stock-recruit relations (1) Ricker function relating stock (SSB) to recruitment (R) : R = a •SSB • exp(-b •SSB) Eq. 1 Parameters redefined to curve’s maximum point, SSBmax, Rmax: R = exp(Rmax/ SSBmax)• SSB• exp(-SSB/SSBmax) Eq. 2

  8. Fitting stock-recruit relations (2) add NAO term (3rd parameter) R = exp( Rmax/ SSBmax) • SSB•exp(-SSB/SSBmax)• exp(c•NAO) Eq. 3 (this eq. has been used in several studies) exp(c•NAO) >1 exp(c•NAO) <1 2 parameter and 3 parameter fit to the data using a Markov Chain Monte Carlo (MCMC) algorithm

  9. Akaike Information Criterion (AIC) used to compare the 2 parameter and 3 parameter fits. Δ AIC values marked * show statistically significant improved fit when third parameter is added. Values of c

  10. The symbols (+, +, 0, -, -) indicate the sign and strength of the relationship between NAO and cod recruitment in the 3-parameter Ricker model.

  11. What processes could be at work? • NAO  Temperature  growth  survival  recruitment(many papers deal with this) • NAO  plankton production  survival  recruitment(Brander, Dickson and Shepherd 2001) • NAO  spawning conditions  survival  recruitment(Baltic inflows – Andersen et al. this Symposium) There are many possible processes and they may not be the same for all stocks.

  12. Conclusions • 4/13 cod stocks show significant effects of the NAO on recruitment. Changes in R and SSB since 1960 are partly due to the NAO • Geographic influence of the NAO on recruitment for all stocks is consistent with influence on physical factors • Medium and long term strategiesfor fisheries managementinclude explicit or implicit assumptions about future states of the NAO

  13. Effects on North Sea cod(Brander and Mohn CJFAS,in press) Low NAO Target and limit reference points for fisheries management are strongly influenced by the assumptions which are made about future levels of NAO. (Ignoring the issue is making an implicit assumption about future NAO levels.) High NAO Low NAO High NAO

  14. But… is the S/R model adequate? A multiplier which is independent of SSB Can we test the hypothesis that the environmental effect is independent of SSB? R = exp( Rmax/ SSBmax) • SSB•exp(-SSB/SSBmax)• exp(c•NAO) Time series for individual stocks are too short and noisy, but the European shelf stocks south of 62o respond to the NAO in the same way, so a joint analysis can be undertaken.

  15. Divide data (SSB, R and NAO) into 3 categories to overcome scale differences and carry out frequency analysis. Rothschild B.J. and Mullen A.J. 1985. The information content of stock-and-recruitment data and its non-parametric classification. Journal du Conseil International pour l'Exploration de la Mer 42: 116-124

  16. Joint frequency analysis (200 values) and 2p that R is independent of NAO <0.001 at low SSB <0.1 at med SSB >0.5 at high SSB NAO has a strong effect on recruitment when SSB is lowEnvironmental effect is not independent of SSB

  17. Why should environmental effects be stronger at low SSB? • Fewer age classes and fewer old fish at low SSB • Spawning distribution may be reduced at low SSB Marteinsdottir G. and Thorarinsson,K. 1998. Improving the stock-recruitment relationship in Icelandic cod (Gadus morhua L.) by including age-diversity of spawners. Canadian Journal of Fisheries and Aquatic Sciences 55: 1372-1377. Begg,G.A. and Marteinsdottir,G. 2002. Environmental and stock effects on spatial distribution and abundance of mature cod (Gadus morhua). Marine Ecology Progress Series 229: 245-262

  18. Conclusion The effect of environmental variability on European cod recruitment is not adequately represented by a standard Ricker S/R model with a multiplicative term.

  19. What are the management implications? • Even stronger reason to avoid low SSB • If low SBB occurs then recovery is very dependent on favourable environmental conditions • New non-linear models are needed to explore medium and long-term consequences We are already witnessing strong environmental effects on stocks with low SSB

  20. Any Questions?

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