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Consequences of changing climate for North Atlantic cod stocks and implications for fisheries management Keith Brander

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Consequences of changing climate for North Atlantic cod stocks and implications for fisheries management Keith Brander

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    1. Consequences of changing climate for North Atlantic cod stocks and implications for fisheries management Keith Brander ICES/GLOBEC Coordinator I will concentrate on a specific analysis of climate effects on recruitment and the implications for management, but it has become evident over the past ten years that fundamental biological processes (growth, condition, maturity, fecundity, distribution) are affected strongly by environment and climate. Recruitment variability is not the only issue to address when looking at management implications of climate change. Original Abstract Evidence that changes in distribution, growth and recruitment of North Atlantic cod stocks can be ascribed, at least in part, to climate variability, has accumulated over the past decade. A combination of experimental work, field observations and modelling has given us quite detailed understanding of the processes for some areas, but no single, simple factor or process can be regarded as the principal cause of environmental effects in all cases. Thus in spite of the evidence that environmental variability influences fish stock dynamics, it is difficult to incorporate this information into assessments and advice for fisheries management. The paper will present some specific and some general arguments on how to improve advice for decision making in a situation of incomplete knowledge and uncertainty, using results which have arisen in the Cod and Climate Change programme. It will also comment on the development of our views on the influence of climate on fisheries since earlier Symposia in 1948 and 1993 I will concentrate on a specific analysis of climate effects on recruitment and the implications for management, but it has become evident over the past ten years that fundamental biological processes (growth, condition, maturity, fecundity, distribution) are affected strongly by environment and climate. Recruitment variability is not the only issue to address when looking at management implications of climate change. Original Abstract Evidence that changes in distribution, growth and recruitment of North Atlantic cod stocks can be ascribed, at least in part, to climate variability, has accumulated over the past decade. A combination of experimental work, field observations and modelling has given us quite detailed understanding of the processes for some areas, but no single, simple factor or process can be regarded as the principal cause of environmental effects in all cases. Thus in spite of the evidence that environmental variability influences fish stock dynamics, it is difficult to incorporate this information into assessments and advice for fisheries management. The paper will present some specific and some general arguments on how to improve advice for decision making in a situation of incomplete knowledge and uncertainty, using results which have arisen in the Cod and Climate Change programme. It will also comment on the development of our views on the influence of climate on fisheries since earlier Symposia in 1948 and 1993

    3. 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. Other variables, such as wind, cloud cover and precipitation show a similar geographic influence patternOther variables, such as wind, cloud cover and precipitation show a similar geographic influence pattern

    5. Decadal mean NAO values We happen to have data for fish stocks for a period of unprecedented change in the NAO. We happen to have data for fish stocks for a period of unprecedented change in the NAO.

    6. The work was carried out with Bob Mohn and is in pressThe work was carried out with Bob Mohn and is in press

    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)

    9. To compare the values of SSBmax and Rmax between the 2 and 3 parameter equations you have to use the mean value of the NAO over the time span.To compare the values of SSBmax and Rmax between the 2 and 3 parameter equations you have to use the mean value of the NAO over the time span.

    10. The geographic influence of the NAO on cod recruitment matches its influence on temperature and other physical variables.The geographic influence of the NAO on cod recruitment matches its influence on temperature and other physical variables.

    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) All correlation analyses of recruitment are vague concerning processes. Some may be vaguer than others.All correlation analyses of recruitment are vague concerning processes. Some may be vaguer than others.

    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 strategies for fisheries management include explicit or implicit assumptions about future states of the NAO The rising trend in the NAO since 1960s will cause a declining trend in R/SSB for several stocks. Ignoring such a trend in R can cause systematic bias in the assessment. The third conclusion is a general statement, which applies to any projection concerning the future. E.g. if you are designing and building storm drains, then what do you assume about future rainfall patterns? The rising trend in the NAO since 1960s will cause a declining trend in R/SSB for several stocks. Ignoring such a trend in R can cause systematic bias in the assessment. The third conclusion is a general statement, which applies to any projection concerning the future. E.g. if you are designing and building storm drains, then what do you assume about future rainfall patterns?

    14. But… is the S/R model adequate? R = exp( Rmax/ SSBmax) • SSB•exp(-SSB/SSBmax)• exp(c•NAO)

    16. Joint frequency analysis (200 values) and ?2 p 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 low Environmental 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

    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.

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