Using CWT’s to assess survival, ocean distribution and maturation for Chinook stocks across the...
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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)