Using CWT’s to assess survival, ocean distribution and maturation for Chinook stocks across the Pacific Northwest: Are there any predictive capabilities to assess year to year

variation, and build them into our assessment tools

Using CWT’s to assess survival, ocean distribution and maturation for Chinook stocks across the Pacific Northwest: Are there any predictive capabilities to assess year to year

variation, and build them into our assessment tools

Rishi Sharma, QERM

Dr. Bob Francis & Dr.Nate Mantua

School of Fisheries and Aquatic Sciences,

University of Washington,

Seattle, WA 98195

Rishi Sharma, QERM

Dr. Bob Francis & Dr.Nate Mantua

School of Fisheries and Aquatic Sciences,

University of Washington,

Seattle, WA 98195

Primary Objectives

• Does the ocean affect survival, distribution, and maturation rates of different stocks in the Northwest in a yearly and/or a longer time scale oscillation?

• Do certain stocks in the Northwest cluster in terms of the above mentioned dynamics?

• Are there any predictive capabilities to assess this year to year (or decadal) variation and can we use those to improve our preseason management capabilities ?

• Do implicit assumptions of fixed ocean distribution, and maturation based on CWT’s effect our management capability ?

• Does the ocean affect survival, distribution, and maturation rates of different stocks in the Northwest in a yearly and/or a longer time scale oscillation?

• Do certain stocks in the Northwest cluster in terms of the above mentioned dynamics?

• Are there any predictive capabilities to assess this year to year (or decadal) variation and can we use those to improve our preseason management capabilities ?

• Do implicit assumptions of fixed ocean distribution, and maturation based on CWT’s effect our management capability ?

Overview of the data and methods

• History of the CWT Indicator stock program for Chinook management

• Stocks represented• Methods used• Illustrate methods with the URBS, Lower Fraser or

Harrison, and Salmon River Indicator tag codes.• General outline of hypotheses and possible ocean data

selection.• Using CWT’s to estimate natural production: A

statistical catch at age analysis for Chinook

History of the Indicator Tag Program

• 36 indicator stocks are used by the Chinook Technical Committee (CTC) for ocean distribution.

• For 14 of these stocks escapement data not good enough for use by the CTC in the Exploitation Rate Analysis (ERA) for ocean fisheries.

• 22 stocks used by the CTC to assess ocean impacts, and estimate an index to survival, maturation, distribution and Adult Equivalence rates.

• Some of these estimates are then used in the Cohort Model used by the Pacific Salmon Commission for setting catch quotas based on ocean abundance forecasts.

• 36 indicator stocks are used by the Chinook Technical Committee (CTC) for ocean distribution.

• For 14 of these stocks escapement data not good enough for use by the CTC in the Exploitation Rate Analysis (ERA) for ocean fisheries.

• 22 stocks used by the CTC to assess ocean impacts, and estimate an index to survival, maturation, distribution and Adult Equivalence rates.

• Some of these estimates are then used in the Cohort Model used by the Pacific Salmon Commission for setting catch quotas based on ocean abundance forecasts.

List of CWT tags usedOrigin Stock Name Location Run Type Smolt

Age S.E. Alaska Alaska Spring Southeast Alaska Spring Age 1 British Columbia

Kitsumkalum North/Central BC Summer Age 1

Snootli Creek1 North/Central BC Spring/Summer

Age 0

Kitimat River1 North/Central BC Summer Age 0 Robertson Creek WCVI Fall Age 0 Quinsam Georgia Strait Fall Age 0 Puntledge Georgia Strait Summer Age 0 Big Qualicum Georgia Strait Fall Age 0 Cowichan Georgia Strait Fall Age 0 Chehalis (Harrison Stock)1 Lower Fraser River Fall Age 0 Chilliwack (Harrison Stock) Lower Fraser River Fall Age 0 Puget Sound South Puget Sound Fall Yearling South Puget Sound Summer/Fall Age 1 Squaxin Pens Fall Yearling South Puget Sound Summer/Fall Age 1 University of Wash. Accelerated Central Puget

Sound Summer/Fall Age 0

Samish Fall Fingerling North Puget Sound Summer/Fall Age 0 Stillaguamish Fall Fingerling Central Puget

Sound Summer/Fall Age 0

George Adams Fall Fingerling Hood Canal Summer/Fall Age 0 South Puget Sound Fall

Fingerling South Puget Sound Summer/Fall Age 0

Nisqually Fall Fingerling South Puget Sound Summer/Fall Age 0 Elwha Fall Fingerling Strait of Juan de

Fuca Summer/Fall Age 0

Hoko Fall Fingerling Strait of Juan de Fuca

Summer/Fall Age 0

Skagit Spring Yearling Central Puget Sound

Spring Age 1

Nooksack Spring Yearling North Puget Sound Spring Age 1 White River Spring Yearling South Puget Sound Spring Age 1

Origin Stock Name Location Run Type Smolt Age

Washington Coast

Sooes Fall Fingerling North Wash. Coast Fall Age 0

Queets Fall Fingerling North Wash. Coast Fall Age 0

Columbia River

Cowlitz Tule Columbia Rvr. (WA)

Fall Tule Age 0

Spring Creek Tule Columbia Rvr. (WA)

Fall Tule Age 0

Columbia Lower River Hatchery Columbia River (OR)

Fall Tule Age 0

Upriver Bright Upper Columbia Rvr.

Fall Bright Age 0

Hanford Wild Upper Columbia Rvr.

Fall Bright Age 0

Leavenworth Spring 2 Upper Columbia Rvr.

Spring Age 1

Lewis River Wild Lower Columbia Rvr.

Fall Bright Age 0

Lyons Ferry3 Snake River Fall Bright Age 0 Willamette Spring Lower Columbia

Rvr. Spring Age 1

Summers Columbia Rvr. (WA)

Summer Age 1

Oregon Coast

Salmon River North Oregon Coast

Fall Age 0

Idaho Sawtooth Spring 2 Idaho Spring Age 1

Rapid River Spring 2 Idaho Spring Age 1 McCall Summer 2 Idaho Summer Age 1

Parameters estimated with CWT’s

• Age 2 cohort size and an index of survival

• Maturation rates by age

• ocean distribution

• exploitation rates

Stocks that data was compiled for

• Columbia Upriver Bright Fall stock

• Chilliwack or the Lower Fraser Harrison River Fall stock

• Oregon coastal Fall stocks

Ocean Distributions and Exploitation ratesSalmon River, OR

Columbia Upriver Brights, WA

Lower Fraser (Harrison BC)

Methods used to estimate survival and maturation

a

aaaaa NM

OETCOCO

11

1

aaa

aaa OETC

ETCMR

rel

aa BY

OS

Where:O is the ocean cohort at age a, OC, TC and E are the ocean catch, terminal catch and escapement at age a, NM is natural mortality at age aMR is the maturity rate at age a, andS is an index of survival

Survival Index for URBS, Lower Fraser and NOC's

0

0.05

0.1

0.15

0.2

0.25

0.3

1977 1982 1987 1992 1997 2002

Brood Year

Su

rviv

al In

dex

Surv (URB) Surv (Sal) Surv (lower Fr)

URB Maturity schedule

0

0.2

0.4

0.6

0.8

1

1.2

1974 1978 1982 1986 1990 1994 1998 2002

Year

% M

atu

re

Age 2

Age 3

Age 4

Age 5

Lower Fraser (Harrison) Maturity schedule

0

0.2

0.4

0.6

0.8

1

1.2

1980 1984 1988 1992 1996 2000

Year

% M

atu

re

Age 2

Age 3

Age 4

Age 5

Salmon River (NOC) Maturity schedule

0

0.2

0.4

0.6

0.8

1

1.2

1974 1978 1982 1986 1990 1994 1998 2002

Year

% M

atu

re

Age 2

Age 3

Age 4

Age 5

Stock Distributions in SEAK over time

0.00%

2.00%

4.00%

6.00%

8.00%

10.00%

12.00%

14.00%

16.00%

18.00%

1975 1980 1985 1990 1995 2000 2005

Year

Sto

ck %

\

URB SEAK

NOC SEAK

WCVI SEAK

Stock Distributions in NCBCover time

0.00%

5.00%

10.00%

15.00%

20.00%

25.00%

30.00%

35.00%

1975 1980 1985 1990 1995 2000 2005

Year

Per

cen

t d

istr

ibu

ted

URB

NOC

WCVI

Age 4 distributions of URB in SEAK and NCBC over time (adjusted for effort and survival)

0.000

0.200

0.400

0.600

0.800

1.000

1.200

1975 1980 1985 1990 1995 2000

Brood Year

Dis

trib

uti

on

Ind

ex

URB 4 (SEAK) URB 4 (NCBC)

assuming effort is constant (100,000 fish recovered), and you adjust the recovery for Survival (S),

i.e. in years of low survival you would adjust the recovery to a higher amount and vice versa in a year of increased survival, and have no effect at

000,100

i

i

rel

a

S

SEff

BY

C

Index

Frame hypothesis around these patterns

• Ocean Conditions affect survival of Chinook in the North Pacific.

• Ocean Conditions affect Maturation Rates on a year to year (or decadal) basis for Chinook salmon.

• Ocean currents and conditions affect distributions of Chinook in the North Pacific.

Data for ocean indicators

Figures A and B are the Pacific Decadal Oscillation (PDO)

Figures C and D are the Artic Oscillation (AO)

Figures E and F are the Aleutian Low Pressure Index (ALPI).

Regime shifts occur in 1925, 1947, 1977, 1989 and 1998 (Minobe 1997, Mantua et. al (1998) and Mantua and Hare (2000)

Can we use CWT’s to estimate Natural production for a system

estimatedt Recruitmen,2 tN

Ocean

tatata PMNNT ,,,

TtTTt FfullqE

Tt

ta

Tta

F

TtaTta

Ffull

VF

eNC

T

Tta

,,

)(

,, )1( ,

TT tatata CNEsc ,,,

Terminal Area

Where:

N(a,t) is the population age a in the ocean at time t, and N(a,t)T is the population in terminal areas

M is natural mortality for age a

PM(a,t) is the proportion mature at age a and time t,

q(o) and q(T) is the catchability coefficient in the ocean and terminal areas respectively,

V is the vulnerability and F is the fishing Mortality

)(,1,1

, ata MFtata eNN

t

tata

ata

taMFtata

tOt

Ffull

VF

MF

FeNC

FfullqE

ta

,,

1,

,)(,, )1( ,

Vulnerability at Age

0

0.2

0.4

0.6

0.8

1

1.2

0 1 2 3 4 5 6 7

Age

Vu

lner

abili

ty

ocean inriver

URBS age 2 Recruits and OCN Fishing Mort

0

500000

1000000

1500000

2000000

1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996

Yr

Ag

e 2

rec

0.000

0.500

1.000

Fish

ing

mor

talit

y In

dex

age 2 rec

Fishing mortalityIndex (OCN)

Fishing Mort (OCN and IN River)

0.00

0.10

0.20

0.30

0.40

0.50

0.60

0.70

0.80

0.90

1.00

1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996

Year

F

0.000

0.050

0.100

0.150

0.200

0.250

0.300

0.350

0.400

0.450

0.500

Fishing mortality Index (TERM) Fishing mortality Index (OCN)

Estimated Maturation Rates (URBS)

0.00

0.50

1.00

1975 1980 1985 1990 1995 2000

Year

% M

atu

re

AGE 2 AGE 3 AGE 4

Observed vs predicted Fit (OCNCatch)

0

50000

100000

150000

200000

250000

300000

1975 1980 1985 1990 1995 2000 2005

Yr

catc

h

sum(pred) sum(obs)

magnbias (OCN)

-2

-1

0

1

2

3

4

5

6

7

1975 1980 1985 1990 1995 2000 2005

Yr

Per

cen

t b

ias

(X 1

00)

Observed vs predicted Fit (ESC)

0

50000

100000

150000

200000

250000

300000

350000

400000

450000

500000

1975 1980 1985 1990 1995 2000 2005

Yr

catc

h

sum(pred) sum(obs)

Observed vs predicted Fit (TERM Catch)

0

50000

100000

150000

200000

250000

300000

1975 1980 1985 1990 1995 2000 2005

Yr

catc

h

sum(pred) sum(obs)

magnbias (TERM)

-0.6

-0.4

-0.2

0

0.2

0.4

0.6

0.8

1

1.2

1975 1980 1985 1990 1995 2000 2005

Yr

Per

cen

t b

ias

(X 1

00)

magnbias (ESC)

-1

-0.5

0

0.5

1

1.5

2

2.5

1975 1980 1985 1990 1995 2000 2005

Yr

Per

cen

t b

ias

(X 1

00)