mortality of cod and haddock eggs on georges bank, 1995-1999 (…wind-driven mortality…) d....

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Mortality of Cod and haddock Eggs on Georges Bank, 1995-1999

(…wind-driven mortality…)

D. Mountain, J. Green, J. Sibunka and D. JohnsonNortheast Fisheries Science Center

NOAA/NMFS

-70 -69 -68 -67 -66 -6540

40.5

41

41.5

42

42.5

1

2

41

3

4

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7

89

10

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1920

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2324

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3926

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3031

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323334

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-70.00 -69.00 -68.00 -67.00 -66.00 -65.0040.00

40.50

41.00

41.50

42.00

42.50

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

Determined from difference in number of early and late stageeggs over the whole season.

(exponential decrease over period of average development time)

Egg Mortality Rate – percent per day

Cod Haddock

1995 13.7 12.0

1996 12.2 11.3

1997 20.4 13.4

1998 9.9 7.8

1999 15.4 9.9

Determined from difference in number of early and late stageeggs over the whole season.

(exponential decrease over period of average development time)

Egg Mortality Rate – percent per day

Cod Haddock

1995 13.7 12.0

1996 12.2 11.3

1997 20.4 13.4

1998 9.9 7.8

1999 15.4 9.9

1997 – high mortality rate1998 – low mortality rate

With a 17 day incubation time, egg survival rate 3 to 8 times higher in 1998

Variation in Egg Mortality

1. What caused it?

2. What are it implications for recruitment?

What caused the interannual variation in mortality rate?

1. Egg viability? (i.e., maternal factors)

2. Predation?

3. Wind Driven Transport off the Bank?

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)

Mor

tali

ty r

ate

(pp

d)

0.00 0.02 0.04 0.06 0.08 0.10

8

10

12

14

16

18

20

22

Cod

R2 = 0.81

0.00 0.01 0.02 0.03 0.04 0.05 0.06

7

8

9

10

11

12

13

14

Haddock

R2 = 0.58

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)

Mor

tali

ty r

ate

(pp

d)

0.00 0.02 0.04 0.06 0.08 0.10

8

10

12

14

16

18

20

22

Cod

R2 = 0.81

0.00 0.01 0.02 0.03 0.04 0.05 0.06

7

8

9

10

11

12

13

14

Haddock

R2 = 0.58

Relationship to SE winds suggeststransport is associated with time- dependent winds (i.e., episodic forcing)

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40.5

41

41.5

42

42.5

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?)

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

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 approachConsidering only near surface drift

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D

WC

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W

C

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D

W

C

Test of the Ekman current approach

Using satellite tracked drifters, drogued at 10m depthThree examples where drift track changed direction with a major wind event.

Red (‘D’) is drifter; Green (‘C’) is climatology; Blue (‘W’) is climatology + Ekman

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41

41.5

42

D

WC

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D

W

C

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41.5

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D

W

C

Test of the Ekman current approach

Using satellite tracked drifters, drogued at 10m depthThree 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

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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 ofearly eggs (#/10m2)for 10 day bins forcod and haddock

Drifting the eggs:

1. For each 20 eggs/10m2 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

Drift induced mortality rate (ppd)

Mor

tali

ty r

ate

(pp

d)

Modeled vs Observed Mortality Rate

No point for 1996 (Buoy 11 winds missing)

Conclusions:

Relationship between egg mortalityand SE wind stress likely is real.

~8 ppd mortality without drift loss

0 2 4 6 8

8

10

12

14

16

18

20

22

Cod

R2 = 0.51

0 2 4 6 8 10

7

8

9

10

11

12

13

14

R2 = 0.23

Haddock

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What was the difference between 1997 & 1998?

1997

Wind driven transportcross isobath (off-bank)

1998

Wind driven transportalong isobath 1997

1998

Wind-induced movement over 17 day drift period

D-45

D-75

D-75

D-45

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a) b)

c) d)

Drift of early Haddock eggs – 75 day bin

1997 1998

Initial

After 17 days

Cod Haddock

1995 11.9 3.8

1996 8.8 18.5

1997 15.8 7.6

1998 18.6 29.8

1999 16.5 9.2

% of Early Stage Eggs on Western George Bank

Implications For Recruitment

Compare:

R vs SSB x Egg survivorship

(i.e., R vs index of number of hatched eggs)0 1000 2000 3000 4000

0

2000

4000

6000

8000

10000

12000

14000

0 2000 4000 6000 8000 10000 12000

5000

10000

15000

20000

25000

30000

35000

40000

45000

SSB * Egg survivorship

Rec

ruit

men

t

Cod

R2 = 0.59

Haddock

R2 = 0.57

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’

SE wind stress (pascals)

0.00 0.01 0.02 0.03 0.04 0.05 0.06

7

8

9

10

11

12

13

14

HaddockM

orta

lity

rat

e (p

pd

)

2003

2003 Haddock Year Class

Cod (dropped 1985)R vs SSB*Egg SurvivorshipRevised R & SSB

SSB*Egg Survivorship

0 1000 2000 3000 4000 5000

R

0

5000

10000

15000

20000

25000

CodR vs SSB x Egg Survivorship

(1986, 1987, 1995-1999)

SSB * Egg survivorship

Rec

ruit

men

t

R2 = 0.81

0.00 0.02 0.04 0.06 0.08 0.10

8

10

12

14

16

18

20

22

SE wind stress (pascals)

Mor

tali

ty r

ate

(pp

d)

Cod

Egg Mortality Rate vs SE Wind Stress (1986, 1987, 1995-1999)

0 1000 2000 3000 4000

0

2000

4000

6000

8000

10000

12000

14000

Cod: ssb*survivorship vs RR2 = 0.59 slope = 2.4

0 2000 4000 6000 8000 10000 12000

5000

10000

15000

20000

25000

30000

35000

40000

45000

Haddock: ssb*survivorship vs rR2 = 0.57

Cod (dropped 1985)R vs SSB*Egg SurvivorshipRevised R & SSB

SSB*Egg Survivorship

0 1000 2000 3000 4000 5000

R

0

5000

10000

15000

20000

25000

R2 = 0.81, slope = 3.47

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a) b)

c) d)

Drift of early Cod eggs – 45 day bin

1997 1998

Initial

After 17 days

0.00 0.02 0.04 0.06 0.08

7

8

9

10

11

12

13

14

R2 = 0.24

0.00 0.02 0.04 0.06 0.08 0.10

8

10

12

14

16

18

20

22

R2 = 0.56

2D Graph 3

Egg Hatching

0.0 0.5 1.0 1.5 2.0

Re

gru

itme

nt

3

4

5

6

7

8

9

10

11

Cod – egg hatching vs recruitmentR2 = 0.63For every 1000 eggs, get 5.5 recruits

Egg Hatching

0.0 0.5 1.0 1.5 2.0

Re

cru

itme

nt

0

10

20

30

40

50

HaddockEgg hatching vs RecruitmentR2 = 0.50For every 1000 eggs get 14.6 recruits