1. Diagnostic Models Herring ECOFOR 2012 SECTION 1 Examples of simple diagnostic models of ecosystem response to climate forcing NORTH ATLANTIC HERRING Marc Hufnagl Myron Peck, Thomas Pohlmann, Mark Dickey-Collas, Richard Nash, Markus Kreus, Johannes Pätsch

2. Diagnostic Models Herring ECOFOR 2012 http://www.fisheries.is/main-species/pelagic-fishes/atlantic-herring/ http://www.gma.org/herring/biology/distribution/stocks.asp Toresen Østvedt, 2000 http://www.thefishsite.com Georges Bank Nova Scotia St. Lawrence Iceland Norway North Sea

3. Diagnostic Models Herring ECOFOR 2012 Calendar day Shetland Buchan Banks Downs Norway Firth of Clyde Downs Celtic/Irish west. Baltic latitude 50° 54° 56° 58° 62° 60° 0 3090 120150180210240270300330360 Iceland 60 Herring spawning periods North Sea

4. Diagnostic Models Herring ECOFOR 2012 Stock Collapse Recovery "Normal" Fishery Recent Period adults, F 2-6 juveniles, F 0-1 2.0 1.0 0.0 100 50 0 1 0 1970 1960 199019802000 2010 Mortality (F) (year -1 ) Recruits (10 9 ) SSB (Mt) Payne et al. (2009) North Sea Autumn Spawners

5. Diagnostic Models Herring ECOFOR 2012 Influenced by environmental factors? Toresen Østvedt, 2000, Fish and Fisheries Norwegian spring spawners

6. Diagnostic Models Herring ECOFOR 2012 standardized recuitment SSB [million t] AMO NAO Gröger et al. 2009 ICES JMS Influenced by environmental factors?

7. Diagnostic Models Herring ECOFOR 2012 1. What influenced the decrease in recruitment ? - what is the most important period ? - what are the best indicators ?

8. Diagnostic Models Herring ECOFOR 2012 Juveniles (IBTS age 1) Adult (SSB) Early larvae (MLAI) Late larvae (MIK) Payne et al. (2009)

9. Diagnostic Models Herring ECOFOR 2012

10. Diagnostic Models Herring ECOFOR 2012 Analyzing the experienced environmental conditions using drift models Approach 1:Specific herring drift model Approach 2: General analysis of potential indicators for different species Approach 3: IBM to analyze survival and growth

11. Diagnostic Models Herring ECOFOR 2012 Analyzing the experienced environmental conditions using drift models Approach 1:Specific herring drift model Approach 2: General analysis of potential indicators for different species Approach 3: IBM to analyze survival and growth

12. Diagnostic Models Herring ECOFOR 2012 Analyzing the experienced environmental conditions using drift models start areasstart times

13. Diagnostic Models Herring ECOFOR 2012 19802000 NAO 1994/19951995/1996 Drifter positions in February

14. Diagnostic Models Herring ECOFOR 2012 Proxies for each spawning component on drift day 150 (February, IBTS) - temperature - cumulative temperature - mean longitude - mean latitude - major axis of kernel - minor axis of kernel - tilt angle of kernel - isotropy - distance Drifter positions in February

15. Diagnostic Models Herring ECOFOR 2012 -8-6-4-20246810 -8 -6 -4 -2 0 2 4 6 8 eigenvector 1 (26.1 % of variance) eigenvector 2 (25.9 % of variance) 2.1 7 7 7.8 9.3 4.4 4.3 3.7 2.4 7 2.5 0.5 0.2 0.4 2.2 4.5 3.4 6.1 4.8 3.4 0.9 3.3 2.3 5.3 1.2 0.5 0.2 0.3 PCA of all indicators (labels overwinter survival) survival lower than average higher than average

16. Diagnostic Models Herring ECOFOR 2012 -8-6-4-202468 0 2 4 6 8 10 R²= 0.46 eigenvector 2 overwinter survival Recruitment is related to drift and temperature conditions

17. Diagnostic Models Herring ECOFOR 2012 -8-6-4-202468 0 2 4 6 8 10 R²= 0.46 eigenvector 2 overwinter survival Recruitment is related to drift and temperature conditions distance between start and end position Temperature

18. Diagnostic Models Herring ECOFOR 2012 Analyzing the experienced environmental conditions using drift models Approach 1:Specific herring drift model Approach 2: General analysis of potential indicators for different species Approach 3: IBM to analyze survival and growth

19. Diagnostic Models Herring ECOFOR 2012 - Coupling of a Langrangian Drifter model with NPZD - Starting drifters in each box each day from 1980 to 2006 - Tracking of all available idices over 60 days - T, S, Phytoplankton (small, large), Zooplankton (small, large) - Kernel statistics

20. Diagnostic Models Herring ECOFOR 2012 - Coupling of a Langrangian Drifter model with NPZD - Starting drifters in each box each day from 1980 to 2006 - Tracking of all available idices over 60 days - T, S, Phytoplankton (small, large), Zooplankton (small, large) - Kernel statistics 161 areas 365 days 12 months 25 proxies year proxy

21. Diagnostic Models Herring ECOFOR 2012 proxy3 proxy2 year proxy1 Correlation of proxy series with Recruitment/SBB series correlation prediction correlation in the first half significant 3 neighboring areas also significant r² in the second half > 0.3 R/SSB = a x Proxy + b Identification of area, month and proxy Future prediction of R/SSB

22. Diagnostic Models Herring ECOFOR 2012 month R/SSB year 1990198020002010 spawning period proxy P2 P12 Z1 Z2 Z12 # correl.

23. Diagnostic Models Herring ECOFOR 2012 x spawning areas correlations

24. Diagnostic Models Herring ECOFOR 2012 Preliminary results of a herring forecasts and a similar approach for other species

25. Diagnostic Models Herring ECOFOR 2012 2070208020902100 R/SSB mean ± sd observations mean ± sd hindcast mean ± sd forecast

26. Diagnostic Models Herring ECOFOR 2012 Preliminary results for other species

27. Diagnostic Models Herring ECOFOR 2012 time R/SSB

28. Diagnostic Models Herring ECOFOR 2012 month # correlation

29. Diagnostic Models Herring ECOFOR 2012 # correlations

30. Diagnostic Models Herring ECOFOR 2012 x spawning areas correlations

31. Diagnostic Models Herring ECOFOR 2012 year R/SSB forecast

32. Diagnostic Models Herring ECOFOR 2012 Thank you for your attention !

33. Diagnostic Models Herring ECOFOR 2012 Approach 1:Specific herring drift model Approach 2: General analysis of potential indicators for different species Approach 3: IBM to analyze survival and growth What are the mechanisms how is recruitment influenced ?

34. Diagnostic Models Herring ECOFOR 2012

35. Diagnostic Models Herring ECOFOR 2012 What are the mechanisms/reasons ? Prey concentrations during first feeding have to be high Combination of temperature and daylength restricts survival Size of the zooplankton and match mismatch influences survival

36. Diagnostic Models Herring ECOFOR 2012 Overview North Atlantic Herring North Sea Herring Recruitment variability Climate influece Recruitment models What are the mechanisms ? http://www.gma.org

37. Diagnostic Models Herring ECOFOR 2012 Do we get similar results to the study before? YES, …. Number of significant correlations between T°C and R/SSB

38. Diagnostic Models Herring ECOFOR 2012 Do we get similar results to the study before? YES, …. … but other indicators have an even higher predictive capacity

39. Diagnostic Models Herring ECOFOR 2012 AUTUMN and WINTER SPAWNERS Nash et al. (2009)

40. Diagnostic Models Herring ECOFOR 2012 AUTUMN and WINTER SPAWNERS Nash et al. (2009) IHLS MLAI - INDEX (multiplicative larvae abundance index)

41. Diagnostic Models Herring ECOFOR 2012 AUTUMN and WINTER SPAWNERS Nash et al. (2009) IHLS MLAI - INDEX (multiplicative larvae abundance index) 1st quarter IBTS MIK 0-group index 20 to 30 mm SL

42. Diagnostic Models Herring ECOFOR 2012 AUTUMN and WINTER SPAWNERS Nash et al. (2009) IHLS MLAI - INDEX (multiplicative larvae abundance index) 1st quarter IBTS MIK 0-group index 20 to 30 mm SL Aug-Jan IHLS Feb IBTS

43. Diagnostic Models Herring ECOFOR 2012 Experienced Temperatures

44. Diagnostic Models Herring ECOFOR 2012 Changes in Experienced Temperatures

45. Diagnostic Models Herring ECOFOR 2012 North Atlantic Herring

46. Diagnostic Models Herring ECOFOR 2012 So what do early life stages experience? 5 15 10 5 1970198019902000 T°C 15 10 5 15 10 15 10 5 1970198019902000 Orkney Buchan Banks Downs Larvaepre-metarmorphosis Juvenile 0 Juvenile 1