Peter Ward RAM Myers

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The effects of soak time anddepth on
longlinecatch rates

• Peter WardRAM Myers
• Dalhousie University

EB WP-3 EB WP-12
2
Dawn 35 30 Dusk 0 70
Soak time 5 hr 9 hr
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Observer data from six fisheries
North Pacific Swordfish (1,539 sets)
40N
Western Pacific Bigeye
(1,915 sets)
20N
gt500,000 fishgt6,000 daily sets
Central PacificBigeye (3,243 sets)
0
20S
Western Pacific Distant (234 sets)
South PacificYellowfin (1,419 sets)
40S
South Pacific SBT (666 sets)
140E
180E
140W
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Data
Observer record of time when each hook was
retrieved
Swordfish
2.5
2.0
Estimate of deployment time from
start and end of time of set
1.5
Catch rate (no./1000 hooks)
1.0
0.5
0
0
5
10
15
20
Soak time (hr)
5
(1) Random effects (O)
Generalized linear mixed model
(2) Fixed effects

• soak time (T)
• season (S)
• year (Y)
• dawn (A)
• dusk (P)

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Soak time effect varies among species
albatross
swordfish
blue shark
skipjack
Tunas
bigeye
-0.2
0.0
0.2
Soak time effect
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Soak time effect correlated with survival
0.1
blue shark
Soak time effect
0.0
skipjack tuna
r 0.54
-0.1
0
20
40
60
80
100
Alive ()
8
1.0
Rays bream
0.5
oilfish
Dusk effect
0.0
Dusk has a positive effect for many species
-0.5
black marlin
-1.0
-1.0
-0.5
0.0
0.5
1.0
Dawn effect
9
Effects make a substantial difference


1,500 vs 5,000


10
0
Distribution of catches of most species varies
with depth
100
200
. . . and with time of day
Depth (m)
300
400
500
0
1
2
Relative catchability
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Conclusions

• (1) Abundance indices need to be adjusted for
• soak time
• dawn and dusk
• depth range
• (2) Mortality of several species may be greater
  than indicated by catch records

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Logistic regression
Generalized linear mixed model
catch y has a binomial distribution
yb(n,p)

• p is the probability of catching a fish

? is the soak time effect
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Random effects

• Operations drawn from a larger population of
  operations
• Random effects in catch rate soak time
  relationship for each operationare independent
  and normally distributed

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Catch is the product of capture and loss rates
No captures after deployment e.g. seabirds
ß lt 0
Captures exceed losses e.g. blue shark
ß gt 0
Probability of being on a hook
Losses eventually exceed capturese.g. skipjack
ß lt 0
Captures balance losses e.g. yellowfin
ß 0
20
15
10
5
0
Soak time (hr)
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Soak time effect generally consistent among areas
swordfish
escolar
oilfish
blue shark
porbeagle
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Epipelagic community
0m
striped marlin
100m
yellowfin tuna
200m
wahoo
300m
400m
bigeye tuna
swordfish
opah
500m
Mesopelagic community