1. Mortality of Cod and haddock Eggs on Georges Bank, 1995-1999 (…wind-driven mortality…) D. Mountain, J. Green, J. Sibunka and D. Johnson Northeast Fisheries Science Center NOAA/NMFS

2. 1. Vertically integrated Sampling for eggs 2. Cod and haddock egg abundance by stage for each survey 3. Peak abundance Cod: mid-Feb to mid-Apr Haddock: mid-Mar to mid-May Cod early stage eggs, February 1997

3. Determined from difference in number of early and late stage eggs over the whole season. (exponential decrease over period of average development time) Egg Mortality Rate – percent per day CodHaddock 199513.712.0 199612.211.3 199720.413.4 19989.97.8 199915.49.9

4. Determined from difference in number of early and late stage eggs over the whole season. (exponential decrease over period of average development time) Egg Mortality Rate – percent per day CodHaddock 199513.712.0 199612.211.3 199720.413.4 19989.97.8 199915.49.9 1997 – high mortality rate 1998 – low mortality rate With a 17 day incubation time, egg survival rate 3 to 8 times higher in 1998

5. Variation in Egg Mortality 1. What caused it? 2. What are it implications for recruitment?

6. What caused the interannual variation in mortality rate? 1. Egg viability? (i.e., maternal factors) 2. Predation? 3. Wind Driven Transport off the Bank?

7. SE Wind Stress vs Egg Mortality Rate 1. Winds from Georges Bank Buoy 2. No winds for 1996 3. Average SE wind stress: mid-Feb to mid-Apr for cod mid-Mar to mid-May for haddock SE wind stress (pascals) Mortality rate (ppd) Cod R 2 = 0.81 Haddock R 2 = 0.58

8. SE Wind Stress vs Egg Mortality Rate 1. Winds from Georges Bank Buoy 2. No winds for 1996 3. Average SE wind stress: mid-Feb to mid-Apr for cod mid-Mar to mid-May for haddock SE wind stress (pascals) Mortality rate (ppd) Cod R 2 = 0.81 Haddock R 2 = 0.58 Relationship to SE winds suggests transport is associated with time- dependent winds (i.e., episodic forcing)

9. Could wind driven transport actually have caused the interannual variability in egg mortality? (Was the temporal/spatial variability in the egg locations and in the wind forcing likely to have resulted in the observed mortality?)

10. Could wind driven transport actually have caused the interannual variability in egg mortality? (Was the temporal/spatial variability in the egg locations and in the wind forcing likely to have resulted in the observed mortality?) Use particle tracking model to test this. Two issues: 1. Estimating the currents 2. The egg distributions to be used

11. Currents: 1. Climatological flow fields from US GLOBEC models (3-D finite element model with mean winds; bi-monthly) 2. Time-dependent Ekman current, using observed winds (48 hour wind history) 3. Random displacement – for dispersion 4. Particle tracking by Drogue-3D by B. Blanton – hourly time step Caveats: Adding climatology and Ekman not a fully rigorous approach Considering only near surface drift

12. Test of the Ekman current approach Using satellite tracked drifters, drogued at 10m depth Three examples where drift track changed direction with a major wind event. Red (D) is drifter; Green (C) is climatology; Blue (W) is climatology + Ekman

13. Test of the Ekman current approach Using satellite tracked drifters, drogued at 10m depth Three examples where drift track changed direction with a major wind event. Red (D) is drifter; Green (C) is climatology; Blue (W) is climatology + Ekman Captures the cross-isobath movement

14. Early Egg distributions: 1. Interpolate each cruise to fine grid 2. Interpolate (in time) to daily values 3. Sum into 10 day bins (e.g., days 40-49, …) Have distributions of early eggs (#/10m 2 ) for 10 day bins for cod and haddock

15. Drifting the eggs: 1. For each 20 eggs/10m 2 at a grid point, assign one egg particle (about 500-1000 particles for each 10 day bin; up to 50 at a grid point) 2. Drift the particles for 17 days (average development time from the early stage to hatching) 3. If a particle moves across the 200m isobath, it has left the bank and is lost 4. After 17 days, determine how many particles have left the bank

16. Drift induced mortality rate (ppd) Mortality rate (ppd) Modeled vs Observed Mortality Rate No point for 1996 (Buoy 11 winds missing) Conclusions: Relationship between egg mortality and SE wind stress likely is real. ~8 ppd mortality without drift loss Cod R 2 = 0.51 R 2 = 0.23 Haddock

17. What was the difference between 1997 & 1998? 1997 Wind driven transport cross isobath (off-bank) 1998 Wind driven transport along isobath 1997 1998 Wind-induced movement over 17 day drift period D-45 D-75 D-45

18. Drift of early Haddock eggs – 75 day bin 1997 1998 Initial After 17 days

19. CodHaddock 1995 11.93.8 1996 8.818.5 1997 15.87.6 1998 18.629.8 1999 16.59.2 % of Early Stage Eggs on Western George Bank

20. Implications For Recruitment Compare: R vs SSB x Egg survivorship (i.e., R vs index of number of hatched eggs) SSB * Egg survivorship Recruitment Cod R 2 = 0.59 Haddock R 2 = 0.57

21. Conclusions: 1. Variability in egg mortality rates due (in large part) to variability in wind-driven loss from the bank. 2. Variability in egg surviorship a significant contributor to variation in recruitment. 3. Future modeling of the egg/larval period should address time-dependent wind forcing. P.S. Joseph Chase concluded much the same a long time ago 2003 haddock - boomer year class; SE Wind was NW

22. SE wind stress (pascals) Haddock Mortality rate (ppd) 2003 2003 Haddock Year Class

23. Cod R vs SSB x Egg Survivorship (1986, 1987, 1995-1999) SSB * Egg survivorship Recruitment R 2 = 0.81

25. SE wind stress (pascals) Mortality rate (ppd) Cod Egg Mortality Rate vs SE Wind Stress (1986, 1987, 1995-1999)

26. Cod: ssb*survivorship vs R R2 = 0.59 slope = 2.4

27. Haddock: ssb*survivorship vs r R2 = 0.57

28. R2 = 0.81, slope = 3.47

30. Drift of early Cod eggs – 45 day bin 1997 1998 Initial After 17 days

31. R2 = 0.24

32. R2 = 0.56

33. Cod – egg hatching vs recruitment R2 = 0.63 For every 1000 eggs, get 5.5 recruits

34. Haddock Egg hatching vs Recruitment R2 = 0.50 For every 1000 eggs get 14.6 recruits