L. CiannelliL. Ciannelli - NOAA, Seattle - NOAA, SeattleK. BaileyK. Bailey - NOAA, Seattle - NOAA, Seattle N.C. StensethN.C. Stenseth – CEES, University of Oslo, Norway – CEES, University of Oslo, NorwayK.S. ChanK.S. Chan - University of Iowa - University of IowaA. BelgranoA. Belgrano - University of New Mexico - University of New Mexico

ICES annual symposium, Bergen, 14 May 2004

Non-additive effects of environmental Non-additive effects of environmental variables on the recruitment of walleye pollock variables on the recruitment of walleye pollock ((Theragra chalcogrammaTheragra chalcogramma) in the Gulf of ) in the Gulf of AlaskaAlaska

Does the intensity of density-dependent control change over contrasting environmental phases?

Pollock early life cyclePollock early life cycle

3

ACC

-Hypothesis: non-additive effect of DI and demographic variables on pre-recruitment survival: variable levels of DD

AnalysisAnalysis

tj

jtj

at

at EgXfbS )()(0GAM: additive

tkt

k

atk

j

jtj

at

at EXsEgXfbS )ˆˆ()()(0CGAM: non-additive

continuous

tj

jtj

at

at EgXfbS )()(11

tj

jtj

at

at EgXfbS )()(22

TGAM:if E<= E*

otherwise

non-additivethreshold

Model selection criteria

1975 1980 1985 1990 1995

32.6

33.0

33.4

Eggs

year

LN(E

ggs)

1975 1980 1985 1990 1995

22.5

23.5

24.5

Age-0

year

LN(A

ge-0

)

1975 1980 1985 1990 1995

21.0

22.0

23.0

Age-1

year

LN(A

ge-1

)

1975 1980 1985 1990 1995

1819

2021

22

Age-2

year

LN(A

ge-2

)

Data: demographic Data: demographic variablesvariables

F(SB) Survey

Survey Catch-at-agemodels

Wind

year

1975 1980 1985 1990 1995

WS

3 (

m3

s-3

)

0.00

0.01

0.02

0.03

0.04

0.05

Predation

year

1975 1980 1985 1990 1995

LN

(pre

da

tion

)

24.8

25.0

25.2

25.4

25.6

25.8

26.0

26.2

Fall and Spring temperature

year

1975 1980 1985 1990 1995

tem

pe

ratu

re (

oC

)

4

6

8

10 FTST

Eggs

year

1975 1980 1985 1990 1995

LN

(eg

gs)

32.4

32.6

32.8

33.0

33.2

33.4

33.6

Data: environmental Data: environmental variablesvariables

W and TS = egg to age-0PG and TF = age-0 to age-1

age-1 to age-2

(Wind speed)3 = W Spring (TS) and Fall (TF) SST

TF

TS

Groundfish predation index (PG)

Results: model selectionResults: model selection

Egg to Age-Egg to Age-00

GAMGAM

CGAMCGAM

TGAMTGAM

X, W, TX, W, TSS

X, W, TX, W, TSS, (X*T, (X*TSS))

X, W, (X*W*TX, W, (X*W*TS S ))

0,7280,728

0,6020,602

0,6170,617

Age-0 to Age-0 to Age-1Age-1

GAMGAM

CGAMCGAM

TGAMTGAM

X, PX, PGG, T, TFF

X, PX, PGG, T, TFF, (X*T, (X*TF F ))

X, TX, TFF, (X* P, (X* PGG*T*TF F ))

0,6270,627

0,7540,754

0,3290,329

Age-1 to Age-1 to Age-2Age-2

GAMGAM

CGAMCGAM

TGAMTGAM

PPGG, T, TFF

N/AN/A

NANA

0,2790,279

Model Structure Variables CV

Results: effectsResults: effects

Egg D

ensity

Survival

Egg D

ensity

Survival

Egg D

ensity

Survival

Age-0 D

ensity

Survival

Age-0 D

ensity

Survival

Age-0 D

ensity

Survival

Survival

T S T S T S

T F T F T F

T FPG

GAM CGAM TGAM

Egg to Age0

Age-0 to Age-1

Age-1 to Age-2

Results: TGAM partitionsResults: TGAM partitions

4.0 4.5 5.0 5.5 6.0 6.5

0.0

10

.02

0.0

30

.04

Egg to Age-0

TS

W

25.0 25.2 25.4 25.6 25.8 26.0

6.5

7.0

7.5

8.0

Age-0 to Age-1

PG

TF

1975 1980 1985 1990 1995

32.5

33.0

33.5

EGGS

LN(E

ggs)

1975 1980 1985 1990 1995

2324

2526

27

AGE-0

LN(A

GE

-0)

1975 1980 1985 1990 1995

2122

2324

25

AGE-1

LN(A

GE

-1)

1975 1980 1985 1990 1995

1819

2021

2223

2425

AGE-2

LN(A

GE

-2)

Results: model simulationsResults: model simulations

DATAGAMCGAMTGAM

GAM-R2 = 0.43CGAM-R2 = 0.58TGAM-R2 = 0.65

GAM-R2 = 0.36CGAM-R2 = 0.44TGAM-R2 = 0.51 GAM-R2 = 0.59

CGAM-R2 = 0.64TGAM-R2 = 0.69

Results: model simulationsResults: model simulations

1975 1980 1985 1990 1995

32.5

33.0

33.5

EGGS

LN(E

ggs)

1975 1980 1985 1990 1995

2324

2526

27

AGE-0

LN(A

GE

-0)

1975 1980 1985 1990 1995

2122

2324

25

AGE-1

LN(A

GE

-1)

1975 1980 1985 1990 1995

1819

2021

2223

2425

AGE-2

LN(A

GE

-2)

DATAGAMCGAMTGAM

GAM-R2 = 0.43CGAM-R2 = 0.58TGAM-R2 = 0.65

GAM-R2 = 0.36CGAM-R2 = 0.44TGAM-R2 = 0.51 GAM-R2 = 0.59

CGAM-R2 = 0.64TGAM-R2 = 0.69

Results: model simulationsResults: model simulations

1975 1980 1985 1990 1995

32.5

33.0

33.5

EGGS

LN(E

ggs)

1975 1980 1985 1990 1995

2324

2526

27

AGE-0

LN(A

GE

-0)

1975 1980 1985 1990 1995

2122

2324

25

AGE-1

LN(A

GE

-1)

1975 1980 1985 1990 1995

1819

2021

2223

2425

AGE-2

LN(A

GE

-2)

DATAGAMCGAMTGAM

GAM-R2 = 0.43CGAM-R2 = 0.58TGAM-R2 = 0.65

GAM-R2 = 0.36CGAM-R2 = 0.44TGAM-R2 = 0.51 GAM-R2 = 0.59

CGAM-R2 = 0.64TGAM-R2 = 0.69

Factors affecting recruitment:Factors affecting recruitment: cross-scales (wind, temperature, community change)cross-scales (wind, temperature, community change) change across-stages (egg-age0; age0-1, age1-2)change across-stages (egg-age0; age0-1, age1-2) are non additive, i.e., interact with each other are non additive, i.e., interact with each other

(changes of DD)(changes of DD)

New Question:New Question: How do these patterns affect our ability to How do these patterns affect our ability to

forecast/manage pollock stocks in changing forecast/manage pollock stocks in changing environment?environment?

SummarySummary

Climate in North PacificClimate in North Pacific

Temperature in the GOATemperature in the GOA

Community changes in the Community changes in the GOAGOA

Mortality trends

0

1

2

3

4

5

6

1970 1975 1980 1985 1990 1995 2000

Year class

Mo

rta

lity

Juvenile mortality

Early larval mortality

Recruitment and larval mortality

18

18.5

19

19.5

20

20.5

21

21.5

0 1 2 3 4 5 6

Total larval mortality (mt)

ln(R

ec

ruit

s)

1981-88

1989-96 Immediately after the regime shift, larval mortality and recruitment were correlated

Afterwards, the relationship dissipated

There has been no trend in larval mortality

There has been a trend for increasing juvenile mortality

Control has shifted from environmental effects on larvae to predation of juveniles.

Bailey (2000) MEPS 198:215