an mse for pacific sardine lecture 15. fisheries management (or what goes up must…) 2 murphy...
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An MSE for Pacific Sardine
Lecture 15
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Fisheries Management(or what goes up must…)
Murphy (1966) & Hill et al. (2009)
0
100,000
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Season
Lan
din
gs
(mt)
0%
10%
20%
30%
40%
50%
60%
70%
Har
vest
Rat
e
Landings (mt) Harvest Rate
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Fishery Development and Management-I
• Fishery developed during World War I• Peak catch over ~700,000t (largest fishery in
the western hemisphere in the 1930s and 1940s).
• Southeast shift in catch as fishery collapsed. Landings stopped in– 1947-48 in the Pacific Northwest– 1953-52 off San Francisco
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Fishery Development and Management-II
• In the early 1980s, sardines were taken incidentally with Pacific and jack mackerel
• Incidental fishery for sardines ended in 1991• Management authority for the fishery transferred
to the Pacific Fishery Management Council (PFMC) in January 2000
• The Coastal Pelagic Species Management Plan includes:– Pacific sardine, Pacific mackerel, jack mackerel, anchovy,
market squid
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Pacific Sardine Recovery and Expansion
1980s: low abundance,
confined to SCA; minor fisheries in SCA & Mexico
1990s: Expansion offshore
and north to Central California;
CCA fishery begins; Pop’n growth = 33%; Sardine in Oregon
Washington and Canada
2000s: Fisheries in PNW Seasonal
movements N-S, inshore/offshore
San Pedro
Ensenada
WashingtonOregon
Monterey
British Columbia
2000s
90s
80s
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Challenges for Assessment and Management-I
• Multinational fishery:– US, Mexico, Canada
• Time-varying migration• Multiple fisheries in the US (Southern
California, Central California, Pacific Northwest)
• Environmental-related variation in biomass
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Challenges for Assessment and Management
Sardine scale-deposition in the Santa Barbara Basin (Soutar & Isaacs 1969; Baumgartner et al. 1992).
•Extreme population variability even in absence of fishing;• periods of peak abundance ~ 50-60 years• link to environmental forcing is assumed
•Typical population dynamic for an ‘R-selected’ species:• small body, rapid growth, early maturation, high fecundity, short generation time,
and the ability to disperse offspring widely
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NSP Distribution and Fishing Areas
U.S. Department of Commerce | National Oceanic
and Atmospheric Administration | NOAA
Fisheries | Page 8
Northern Subpopulation DistributionFishing Areas, & Modeled Fleets
Summer/Fall (Feeding)
Winter/Spring(Spawning) So. Calif. (SCA)
Ensenada(ENS)
Washington (WA)
Oregon (OR)
Monterey Bay (CCA)
Vancouver Island (BC)
PacNW Fleet
MexCal Fleet
Southern subpopulation
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NSP Distribution & General Survey Areas
U.S. Department of Commerce | National Oceanic
and Atmospheric Administration | NOAA
Fisheries | Page 9
So. Calif. (SCA)
Ensenada(ENS)
Washington (WA)
Oregon (OR)
Monterey Bay (CCA)
Vancouver Island (BC)
NWSS Aerial Survey (summer):2009-2012
Summer ATM Surveys:2008, 2012, 2013
SWFSC Spring Survey:DEPM/TEP 1994-2013;
ATM 2006-2013
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Estimated Stock Biomass Series from Base Model and Previous Stock Synthesis Models
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Harvest Control (US)HG2010 = (BIOMASS2009 – CUTOFF) • FRACTION • DISTRIBUTION
To determine an appropriate (sustainable) FRACTION value:
FMSY = 0.248649805(T2)−8.190043975(T)+67.4558326
where T (oC) is the running average sea-surface temperature at Scripps Pier during the three preceding seasons (July-June), and exploitation FRACTION is bounded between 5% and 15%.Maximum catch allowed = 200,000 mt
Stock biomass
(age 1+, mt) Cutoff (mt)Harvest Fraction
U.S. Distribution
U.S. Harvest for 2011 (mt)
537,173 150,000 0.15 0.87 50,526
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Pacific Sardine: Management Process(Amendment 8 & 13)
Overfishing Level(OFL)
Harvest Guideline(HG)
Acceptable BiologicalCatch (ABC)
P*1+ biomass
OFL
Increasing SST
Increasing SST
1+ biomass
HG
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Calculate OFLOFL=Biomass*Fraction*Distribution
Calculate ABCABC=OFL*P*
Calculate HGHG=(Biomass-Cutoff)*
Fraction*Distribution
Final HG
SST
SSTE M
SY
Select the minimum from these two quantities
The HG is set following this basic process
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Risk Assessment Framework
OFL, ABC, HGControl Rules
Remove catch from population
Recruitment
EnvironmentalDriver
Monitoringdata
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Performance measures
The performance measures are selected to quantify performance relative to [some] management goals.• Average catch (total)• Average population size (1+ biomass)• Probability [total] catch is less than some threshold (e.g. 50,000t)• Probability 1+ biomass is below a threshold.
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SIO is the index being used in the current harvest control rule. CalCOFI is the index
that better explains recruitment
Year
SS
T (
C)
1940 1960 1980 2000
14
16
18
20
SIOCalCOFI
SIO and CalCOFI indices have different scales, and are representative of different geographical areas.
SIO
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Recruitment is related to both environment and spawning biomass
Series AIC R2
SST_CC_ann 44.49 0.76
SIO_SST_ann 56.81 0.61
ERSST_ann 55.3 0.63
The relation between several environmental indices and recruitment was evaluated.CalCOFI SST provides a better fit than SIO or ERSST to the stock-recruitment data for 1984-2008
From PFMC 2013, Table App.E.6
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Modeling environmental drivers
1940 1960 1980 2000
17
.01
7.5
18
.01
8.5
19
.01
9.5
20
.0
Year
En
v. v
ari
ab
le
SQ wave, no ACSQ wave, With ACSine wave
Fit the environmental variable to the ERSTT time series
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Calibrating the “CalCOFI” HG control rule
13 14 15 16 17 18
0.0
0.2
0.4
0.6
SST (C)
EM
SY
EMSY
E=0.05-0.18
SEMSY
PFMC June Meeting; Costa Mesa, CA, June, 2013
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Calibrating the “CalCOFI” HG control rule
13 14 15 16 17 18
0.0
0.2
0.4
0.6
SST (C)
EM
SY
EMSY
E=0.05-0.18SST_CC_ann quartiles
Maximum harvest rate for computing OFL
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CalCOFI-based harvest control rule
CalCOFI OFL
0
500
10001500
14.014.5
15.015.5
16.016.5
17.00
100
200
300
BiomassSST
OFL
CalCOFI HG
0
500
10001500
14.014.5
15.015.5
16.016.5
17.00
50
100
150
200
BiomassSST
HG
CalCOFI HG with ABC
0
500
10001500
14.014.5
15.015.5
16.016.5
17.00
50
100
150
200
BiomassSST
HG
OFL control rule HG control rule HG control rule < ABC
Cutoff
Maxcatch
Maximum harvest rate for OFL Maximum harvest
rate for HGPFMC June Meeting; Costa Mesa, CA, June, 2013
The harvest control rule depends on both the 1+ biomass and the CalCOFI SST
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Bio
mas
s ('0
00t)
010
0020
0030
0040
00
Bio
ma
ss (
'00
0t)
ERSSTR
ecru
its (
'000
0)
050
010
0015
0020
00
Re
cru
its (
'00
00
t)
Year
SS
T
0 50 100 150 200
1415
1617
1819
20
SS
TCalCOFI
Year
0 50 100 150 200
Year
This is a comparison of model runs using ERSST (left) and CalCOFI (right) as the environmental driver of recruitment, and no catches
PFMC June Meeting; Costa Mesa, CA, June, 2013
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50 100 150 200 250 300 3500
200
400
600
800
1000
1200
1400
1600
Average Catch ('000t)
Aver
age
1+ P
opul
ation
“current” HG
50 100 150 200 250 300 3500
20
40
60
80
100
120
Mean Catch ('000t)
Prob
(Bio
mas
s 1+
> 40
0,00
0t)
Performance measures aredefined over many cycles of the environmental variable and arenot predictions of short-termcatches / biomass.
45% harvest rate &high CUTOFF (variant 5)
No CUTOFF (variants 3&4)
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50 100 150 200 250 300 3500
5
10
15
20
25
30
35
40
Mean Catch ('000t)
Prob
abili
ty ze
ro c
atch
50 100 150 200 250 300 3500
10
20
30
40
50
60
Mean Catch ('000t)
Prob
abili
ty C
atch
< 5
0,00
0t
“current” HG
45% harvest rate &high CUTOFF (variant 5)
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20 25 30 35 40 45 5080
85
90
95
100
Probability catch < 50,000t
Prob
abili
ty 1
+ Bi
omas
s >
400,
000t
Performance depends on the values for the parameters determining, for example, how the environment impacts recruitment.
More extreme variation inthe environment than assumedfor the base-case
Base-case
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60 80 100 120 140 160 180 200 220 240 2600
100
200
300
400
500
600
700
800
900
1000
Mean Catch
Mea
n 1+
bio
mas
s
“current” HG OFL only
Key Major Sensitivity: The assumption everyone follows the US control rules (for this test Mexico and Canada areassumed to have a constant fishing mortality rate no matter what)
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Control Rules and MSE-I
• Design of the operating model– Single-species: Workshop with Council
involvement (Council members, staff, SSC, advisory bodies)
– Multi-species: Ongoing – currently being funding through a Packard grant
– Operating model reviewed by the Council Scientific and Statistical Committee (SSC)
• Selection of OFL control rules: the SSC!
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Control Rules and MSE-II
• Selection of HG control variants:– Initially based on those considered when the
current Harvest Guideline control rule was adopted
– Additional options added by:• The Coastal Pelagic Species management team• The public (via the Council)
– Software made available to the public who provided suggestions based on their analyses.
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Control Rules and MSE-III
• Performance measures for the MSE:• Initially based on those considered when the current
Harvest Guideline control rule was adopted• Performance statistics added based on input from the:
– Coastal Pelagic Species Management Team, – Coastal Pelagic Species Advisory Subpanel, and– Public (NGOs, industry).