Embed Size (px)
Citation preview
Are the apparent rapid declines in top pelagic predators real?
Mark Maunder, Shelton Harley, Mike Hinton, and others
IATTC
Outline• Definitions and terms• Why the declines don’t make sense
– Japanese longline catch and effort (EP0)– Population dynamics
• Explanatory hypotheses– Regime change– Ecosystem– Spatial distribution of effort– Habitat and gear distribution– Stupid fish hypothesis
• Summary
Definitions
• CPUE = catch-per-unit-of-effort
• Nominal CPUE
• Fitting a model
• Carrying capacity – Average abundance in the absence of fishing
Basic assumption
C = EqA C/E = qA
Where : C= catch, E = effort, and A = abundance
area
area
CCPUE
E
1950 1960 1970 1980 1990 2000
0
5
10
15
Albacore
1950 1960 1970 1980 1990 2000
0
5
10
15
Yellowfin
1950 1960 1970 1980 1990 2000
0
10
20
30
Bigeye
1950 1960 1970 1980 1990 2000
0.0
0.002
0.004
0.006
Bluefin
1950 1960 1970 1980 1990 2000
0.0
0.05
0.10
0.15
0.20
0.25
Black marlin
1950 1960 1970 1980 1990 2000
0
2
4
6
8
Blue marlin
1950 1960 1970 1980 1990 2000
0
1
2
3
4
5
Striped marlin
1950 1960 1970 1980 1990 2000
0.0
0.2
0.4
0.6
0.8
1.0
1.2
Swordfish
Year
CP
UE
(#
pe
r 1
00
0 h
oo
ks)
1950 1960 1970 1980 1990 2000
0
200
400
600
800
0
5
10
15
Year
Cat
ch (
000s
of
fish)
Albacore
CP
UE
(#
per
1000
hoo
ks)
CatchCPUE
Albacore
1950 1960 1970 1980 1990 2000
0
200
400
600
800
0
5
10
15
Yellowfin
1950 1960 1970 1980 1990 2000
0
200
400
600
0
5
10
15
Bigeye
1950 1960 1970 1980 1990 2000
0
500
1000
1500
0
10
20
30
Bluefin
1950 1960 1970 1980 1990 2000
0.0
0.1
0.2
0.3
0.0
0.002
0.004
0.006
Black marlin
1950 1960 1970 1980 1990 2000
0
2
4
6
0.0
0.05
0.10
0.15
0.20
0.25
Blue marlin
1950 1960 1970 1980 1990 2000
0
20
40
60
80
100
120
0
2
4
6
8
Striped marlin
1950 1960 1970 1980 1990 2000
0
100
200
300
0
1
2
3
4
5
Swordfish
1950 1960 1970 1980 1990 2000
0
20
40
60
80
100
120
0.0
0.2
0.4
0.6
0.8
1.0
1.2
Year
Ca
tch
(0
00
s o
f fis
h)
CP
UE
(#
pe
r 1
00
0 h
oo
ks)
1950 1960 1970 1980 1990 2000
0
200
400
600
800
0
5
10
15
Year
Cat
ch (
000s
of
fish)
Albacore
CP
UE
(#
per
1000
hoo
ks)
CatchCPUE
Fit model to data
• PellaTomlinson-model with Nmsy/N0 = 30% (based on numbers)
• Project population dynamics from an unexploited condition using observed catch
• Fit to CPUE data as a relative abundance index (assume CPUE proportional to abundance)
• Use only Japanese longline CPUE and Catch data
1950 1960 1970 1980 1990 2000
0
5
10
15
Year
CP
UE
(#
per
1000
hoo
ks)
Albacore
CPUE
1950 1960 1970 1980 1990 2000
0
5
10
15
Albacore
1950 1960 1970 1980 1990 2000
0
5
10
15
Yellowfin
1950 1960 1970 1980 1990 2000
0
10
20
30
Bigeye
1950 1960 1970 1980 1990 2000
0.0
0.002
0.004
0.006
Bluefin
1950 1960 1970 1980 1990 2000
0.0
0.05
0.10
0.15
0.20
0.25
Black marlin
1950 1960 1970 1980 1990 2000
0
2
4
6
8
Blue marlin
1950 1960 1970 1980 1990 2000
0
1
2
3
4
5
Striped marlin
1950 1960 1970 1980 1990 2000
0.0
0.2
0.4
0.6
0.8
1.0
1.2
Swordfish
Year
CP
UE
(#
pe
r 1
00
0 h
oo
ks)
1950 1960 1970 1980 1990 2000
0
5
10
15
Albacore
1950 1960 1970 1980 1990 2000
0
5
10
15
Yellowfin
1950 1960 1970 1980 1990 2000
0.0
0.002
0.004
0.006
Bluefin
1950 1960 1970 1980 1990 2000
0
1
2
3
4
5
6
Striped marlin
1950 1960 1970 1980 1990 2000
0.0
0.2
0.4
0.6
0.8
1.0
1.2
Swordfish
Year
CP
UE
(#
pe
r 1
00
0 h
oo
ks)
Remove first few data points
Only fit to decline
1950 1960 1970 1980 1990 2000
0
5
10
15
Albacore
1950 1960 1970 1980 1990 2000
0
5
10
15
Yellowfin
1950 1960 1970 1980 1990 2000
0.0
0.002
0.004
0.006
Bluefin
1950 1960 1970 1980 1990 2000
0
2
4
6
8
Blue marlin
Year
CP
UE
(#
pe
r 1
00
0 h
oo
ks)
Regime change hypothesis
Blue marlin production residuals
-1.5
-1
-0.5
0
0.5
1
1.5
2
2.5
1950 1960 1970 1980 1990 2000 2010
Year
Pro
duct
ivity
dev
iatio
n0
0.001
0.002
0.003
0.004
0.005
0.006
0.007
0.008
0.009
1950 1960 1970 1980 1990 2000
Year
CP
UE
Change in productivity, yellowfin example
Year
Re
lativ
e R
ecr
uitm
en
t
75 77 79 81 83 85 87 89 91 93 95 97 99 01
0
1
2
3
Maunder 2002. IATTC Stock Assessment Report 3
Change in productivity, bigeye example
Year
Re
lativ
e R
ecr
uitm
en
t
81 83 85 87 89 91 93 95 97 99 01
0
1
2
3
4
Maunder and Harley 2002. IATTC Stock Assessment Report 3
Ecosystem model
High Adult Biomass Low Adult Biomass
Ecosystem model
1t
speciest
species
N
f NK
K = carrying capacity N = numbers f(N) is the single species production
0
0.2
0.4
0.6
0.8
1
0 0.2 0.4 0.6 0.8 1
Sum(N)/Sum(K)
Pro
po
rtio
n o
f pro
du
ctio
n
Ecosystem results
• Fits the data significantly better
• Nearly all improvement from fit to bluefin tuna data
• Also improves fit to blue marlin data
Bluefin tuna
Single Species
Ecosystem
1950 1960 1970 1980 1990 2000
Year
CP
UE
1950 1960 1970 1980 1990 2000
Year
CP
UE
Blue marlin
Single Species
Ecosystem
1950 1960 1970 1980 1990 2000
YearC
PU
E
1950 1960 1970 1980 1990 2000
Year
CP
UE
Spatial expansion of the longline fishery
Spatial hypothesesT
ime
Highest CPUE Highest Profit Equal distribution
Simulation of effort expansion
• Effort increases by 100 units every 5 years
• Movement of effort only occurs every five years
• No movement of fish among areas
• In highest profit hypothesis, new effort goes into new area and old effort stays in the same area
• In highest CPUE hypothesis, all effort goes into new area
CPUE trends
00.10.20.30.40.50.60.70.80.9
1
0 10 20 30 40 50
Time
Re
lati
ve
CP
UE
Highest CPUE (smoothed) Highest Profits (smoothed) Equal Effort (Abundance)
Expansion of the fishery
0
0.2
0.4
0.6
0.8
1
1.2
1950 1960 1970 1980 1990 2000
Year
Hooks Squares
30% of striped marlin catch
Limited stock distribution: striped marlin
0
0.2
0.4
0.6
0.8
1
1.2
1950 1960 1970 1980 1990 2000
Year
CP
UE
05
1015202530354045
1950 1960 1970 1980 1990 2000
Year
% c
atch
in c
oast
al a
rea
Habitat, gear, and fish behavior
• Fish have habitats that they prefer• Habitat changes with the environment • Fishermen’s behavior determines where
the gear fishes• Gear, habitat, and fish behavior have to
match for fishing to be successful• Gear, habitat, and fish behavior have to be
taken into consideration when interpreting CPUE
Bigelow et al. 2000
Environment
Thermocline
Depth of gear
50-15050-400
Current
Current
Increasing depth of longlines
1970 1975 1980 1985 1990 1995 2000
Year
Mea
sure
of
dept
h (H
PB
)
EPO examples
Bigeye tuna
Yellowfin tuna
From Keith Bigelow
1960 1970 1980 1990 2000
CPUEY
ear
Nominal CPUE Abundance
1960 1970 1980 1990 2000
Year
CP
UE
Nominal CPUE Abundance
Habitat standardization
• Used to remove the changes of gear depth and the environment from the relative index of abundance
• Method developed by Hinton and Nakano 1996• Applied to bigeye and yellowfin tuna by Bigelow
et al. 2002• Used in the assessments of yellowfin tuna,
bigeye tuna, blue marlin, striped marlin, and swordfish in the EPO
The “stupid” fish hypothesis
The stupid fish hypothesis under historic effort
1950 1960 1970 1980 1990 2000
Year
CPUE Catch
CPUE vs abundance
0
0.2
0.4
0.6
0.8
1
1950 1960 1970 1980 1990 2000
Time
Ab
un
da
nce
or
CP
UE
Abundance CPUE
The big “stupid” fish hypothesis (size-specific vulnerability)
Size-specific vulnerability
The size specific vulnerable hypothesis under historic effort
1950 1960 1970 1980 1990 2000
Year
CPUE catch
Blue marlin example
0
0.2
0.4
0.6
0.8
1
0 2 4 6 8 10
Age
Vul
nera
bilit
y
Constant vulnerability Big stupid fish
1950 1960 1970 1980 1990 2000
Year
CP
UE
Big stupid fish Constant vulnerability
Historic yellowfin length frequency data
60 cm 150 cm
Purse seine Longline
Suda and Schaefer 1965
Size at 50% maturity
Other Hypotheses• Multiple stocks (e.g. northern and southern
albacore)• Fraction of stock (bluefin)• Stock distribution limited (e.g. Striped Marlin,
Swordfish, sailfish, shortbill spearfish)• Gear saturation/interference• Increase in fishing power• Targeting (swordfish, bait, setting at night)• Age specific natural mortality• Fishing regulations (e.g. EEZ)
Myers Dalhousie Group
• Soak time – increases current CPUE– Has slightly increased – Increased soak time increases CPUE
• Shark damage – increases current CPUE– 25% in early data and about 4% in recent data – Lower shark damage increases CPUE
• Hook saturation - increases current CPUE– Bait loss due to catching other species has decreased– More bait available increases CPUE
• Depth of gear• Ecosystem• Also looking at non-pelagic species and dada from trawl• World wide patterns similar
Summary– Regime change
• Same for all species?• Implies that the stocks are depleted• New management values for new regime
– Ecosystem• Implies that the stocks are depleted• Does not explain all increase in production
– Spatial distribution of effort• Spatial expansion occurred when the rapid
declines occurred• CPUE declines faster than abundance• Final depletion level is the same
Summary continued– Habitat and gear distribution
• Did not change during period of depletion• Current abundance may be underestimated for
most species explaining current catches
– Stupid fish hypothesis• Both stupid fish and age-specific vulnerability could
explain some of the decline• Indicates stocks are less depleted
– Limited distribution of stock• Probably explains increase in CPUE for striped
marlin, swordfish, sailfish, and spearfish
Conclusions
• Regime change, ecosystem, and spatial distribution result in high depletion levels
• Longline depth, stupid fish hypothesis, and age-specific vulnerability result in lower depletion levels
• Ecosystem, spatial distribution, longline gear depth, and age-specific vulnerability most likely
Current depletion levelHypothesis More Same Less UnknownRegime change xEcosystem xSpatial distribution xGear depth x (most)Stupid fish xSize-specific vulnerability xMultiple stocks xFraction of stock xInterference xIncreased power xTargeting DependsAge-specific M xFishing regulations xSoaktime xShark damage xHook saturation x
Yellowfin and Bigeye selectivity
0
1
2
3
4FISHERY -- PESQUERIA 1
4 8 16 24 32 40
0
1
2
3
4
5
6
FISHERY -- PESQUERIA 2
4 8 16 24 32 40
0
1
2
3
FISHERY -- PESQUERIA 3
4 8 16 24 32 40
0
1
2
3
4
5FISHERY -- PESQUERIA 4
4 8 16 24 32 40
0
1
2
3
4
5
FISHERY -- PESQUERIA 5
4 8 16 24 32 40
0
1
2
3
4
5FISHERY -- PESQUERIA 6
4 8 16 24 32 40
0
1
2
3
4
5
FISHERY -- PESQUERIA 7
4 8 16 24 32 40
0
1
2
3
FISHERY -- PESQUERIA 8
4 8 16 24 32 40
0.0
0.5
1.0
1.5
FISHERY -- PESQUERIA 9
4 8 16 24 32 40
0
5
10
15
FISHERY -- PESQUERIA 10
4 8 16 24 32 40
0
5
10
15
FISHERY -- PESQUERIA 11
4 8 16 24 32 40
0
5
10
15
FISHERY -- PESQUERIA 12
4 8 16 24 32 40
0
5
10
15
FISHERY -- PESQUERIA 13
4 8 16 24 32 40
AGE IN QUARTERS -- EDAD EN TRIMESTRES
SE
LE
CT
IVIT
Y -
- S
EL
EC
TIV
IDA
D
Bigeye Yellowfin
0
1
2
3
4
5
6
FISHERY -- PESQUERIA 1
4 8 12 16 20 24 28
0
2
4
6
FISHERY -- PESQUERIA 2
4 8 12 16 20 24 28
0
1
2
3
4
FISHERY -- PESQUERIA 3
4 8 12 16 20 24 28
0
1
2
3
4
5
6 FISHERY -- PESQUERIA 4
4 8 12 16 20 24 28
0
1
2
3
4
FISHERY -- PESQUERIA 5
4 8 12 16 20 24 28
0
1
2
3
4
5
6FISHERY -- PESQUERIA 6
4 8 12 16 20 24 28
0
2
4
6
FISHERY -- PESQUERIA 7
4 8 12 16 20 24 28
0
1
2
3
4
5FISHERY -- PESQUERIA 8
4 8 12 16 20 24 28
0
1
2
3
FISHERY -- PESQUERIA 9
4 8 12 16 20 24 28
0
2
4
6
8
10
12FISHERY -- PESQUERIA 10
4 8 12 16 20 24 28
0.0
0.5
1.0
1.5
2.0
2.5
FISHERY -- PESQUERIA 11
4 8 12 16 20 24 28
0.0
0.2
0.4
0.6
0.8
1.0
1.2
1.4
FISHERY -- PESQUERIA 12
4 8 12 16 20 24 28
0
2
4
6
8
10
FISHERY -- PESQUERIA 13
4 8 12 16 20 24 28
0
2
4
6
8
10
FISHERY -- PESQUERIA 14
4 8 12 16 20 24 28
0
2
4
6
8
10
FISHERY -- PESQUERIA 15
4 8 12 16 20 24 28
0
2
4
6
8
10
FISHERY -- PESQUERIA 16
4 8 12 16 20 24 28
AGE IN QUARTERS -- EDAD EN TRIMESTRES
SE
LE
CT
IVIT
Y -
- S
EL
EC
TIV
IDA
D
Age in quarters Age in quarters
60 cm 150 cm
Size at 50% maturity
0.0
0.01
0.02
0.03
0.04
0.05FISHERY -- PESQUERIA 1
50 100 150 200
FISHERY -- PESQUERIA 2 FISHERY -- PESQUERIA 3
50 100 150 200
FISHERY -- PESQUERIA 4
FISHERY -- PESQUERIA 5 FISHERY -- PESQUERIA 6 FISHERY -- PESQUERIA 7
0.0
0.01
0.02
0.03
0.04
0.05FISHERY -- PESQUERIA 8
0.0
0.01
0.02
0.03
0.04
0.05FISHERY -- PESQUERIA 9 FISHERY -- PESQUERIA 10
50 100 150 200
FISHERY -- PESQUERIA 11 FISHERY -- PESQUERIA 12
50 100 150 200
LENGTH (cm) TALLA
PR
OP
OR
TIO
N O
F T
HE
C
AT
CH
-- P
RO
PO
RC
IO
N D
E LA
C
AP
TU
RA
Current yellowfin length frequency data
125 cm
Age-specific selectivity and recruitment residuals
0
0.001
0.002
0.003
0.004
0.005
0.006
0.007
0.008
0.009
1950 1960 1970 1980 1990 2000
Year
CP
UE
-1.5
-1
-0.5
0
0.5
1
1950 1960 1970 1980 1990 2000
Year
ln(r
esid
ual
)
