Peter WardPeter WardRAM MyersRAM Myers

Dalhousie UniversityDalhousie University

The effects of soak time andThe effects of soak time anddepth on longlinedepth on longline

catch ratescatch rates

EB WP-3 EB WP-3

EB WP-12EB WP-12

200 m

400 m

500 m

1950s1950s 1990s 1990s

DepthDepth 25–175 m25–175 m 25–500 m 25–500 mDawnDawn 35%35% 30%30%DuskDusk 0% 0% 70% 70% Soak timeSoak time 5 hr 5 hr 9 hr 9 hr

Observer data from six fisheriesObserver data from six fisheries

00

20S20S

40S40S

20N20N

40N40N

140E140E 180E180E 140W140W

Western PacificWestern Pacific Bigeye Bigeye (1,915 sets) (1,915 sets)

Central PacificCentral PacificBigeye (3,243 sets)Bigeye (3,243 sets)

Western Pacific Western Pacific Distant (234 sets)Distant (234 sets)

North Pacific Swordfish (1,539 sets)North Pacific Swordfish (1,539 sets)

South PacificSouth PacificYellowfin (1,419 sets)Yellowfin (1,419 sets)

South Pacific SBT (666 sets)South Pacific SBT (666 sets)

>500,000 fish>500,000 fish>6,000 daily sets>6,000 daily sets

Swordfish2.52.5

2.02.0

1.51.5

1.01.0

0.50.5

00

Cat

ch r

ate

(no.

/100

0 ho

oks)

Soak time (hr)00 55 1010 1515 2020

DataData

++Estimate of Estimate of deployment time deployment time from start and end from start and end of time of setof time of set

Observer record of Observer record of time when each time when each hook was retrievedhook was retrieved

(1) Random effects (O)(1) Random effects (O)

• soak time (soak time (TT))

• season (season (SS))

• year (year (Y)Y)

• dawn (dawn (AA))

• dusk (dusk (PP))

OPAYST 543210 PAYST 543210 AYST 43210 YST 3210 ST 210 T10

Generalized linear mixed modelGeneralized linear mixed model

(2) Fixed effects(2) Fixed effects

Soak time effect-0.2 0.0 +0.2

bigeyebigeye

skipjackskipjack

swordfishBillfishes

Tunas

blue sharkblue shark

Sharks and rays

albatrossalbatross

Other fishes

Soak time effect varies among speciesSoak time effect varies among speciesSeabirds

Soak time effect correlated with survivalSoak time effect correlated with survival

00 2020 4040 6060 8080 100100

Alive (%)Alive (%)

Soa

k ti

me

effe

ctS

oak

tim

e ef

fect

0.0

0.0

-0.1

-0.1

+0.

1+

0.1

r = 0.54r = 0.54

blue sharkblue shark

skipjack tunaskipjack tuna

-1.0-1.0 -0.5-0.5 0.00.0 0.50.5 1.01.0

-1.0

-1.0

-0.5

-0.5

0.0

0.0

0.5

0.5

1.0

1.0

Dus

k ef

fect

Dus

k ef

fect

Dawn effectDawn effect

oilfishoilfish

Dusk has a positive Dusk has a positive effect for many effect for many speciesspecies

blackblackmarlinmarlin

Ray’s breamRay’s bream

Effects make a substantial differenceEffects make a substantial difference

$1,500 vs $5,000$1,500 vs $5,000

SwordfishSwordfish 5 hr5 hr 20 hr20 hr

no dawn or duskno dawn or dusk 1 4dawn and duskdawn and dusk 3 10

00 11 22

Bigeye tunaBigeye tunaDayDay

500500

400400

300300

200200

100100

Dep

th (

m)

Dep

th (

m)

Relative catchabilityRelative catchability

00

NightNight

Striped marlinStriped marlinBlue sharkBlue sharkOpahOpah Distribution of Distribution of catches of most catches of most species varies with species varies with depthdepth. . . and with time . . . and with time

of dayof day

ConclusionsConclusions(1) Abundance indices need to be adjusted for:(1) Abundance indices need to be adjusted for:

• soak timesoak time

• dawn and duskdawn and dusk

• depth rangedepth range

(2) Mortality of several species may be greater (2) Mortality of several species may be greater than indicated by catch recordsthan indicated by catch records

Logistic regressionLogistic regression

ππ is the probability of catching a fish:is the probability of catching a fish:

hp

p=÷

ø

öçè

æ-1

log

( )h

hp

e

e+

=1

Generalized linear mixed modelGeneralized linear mixed model

catch catch y y has a binomial distribution:has a binomial distribution: y~b(n,y~b(n,ππ))

ηη is the ‘soak time effect’: is the ‘soak time effect’:

RandomRandom effects effects

• Operations drawn from a larger Operations drawn from a larger population of operationspopulation of operations

• Random effects in catch rate – soak Random effects in catch rate – soak time relationship for each operationtime relationship for each operationare independent and normally are independent and normally distributed: distributed:

),0(~ 2 Ni

Catch is the product of capture and loss Catch is the product of capture and loss ratesrates

2020151510105500

Soak time (hr)

Pro

babi

lity

of

bein

g on

a h

ook

No captures afterNo captures afterdeployment e.g. seabirdsdeployment e.g. seabirds

ββ < 0 < 0

Captures exceed lossesCaptures exceed lossese.g. blue sharke.g. blue shark ββ > 0> 0

ββ = 0= 0

ββ < 0< 0Losses eventually Losses eventually exceed capturesexceed capturese.g. skipjacke.g. skipjackCaptures balance lossesCaptures balance lossese.g. yellowfine.g. yellowfin

Sth slope

NE

slo

pe

0.0 0.05 0.10 0.15 0.20

-0.0

4-0

.02

0.0

0.02

0.04

0.06

0.08

0.10

porbeagle

swordfishoilfish

escolar

blue shark

Soak time effect generally consistent Soak time effect generally consistent among areasamong areas

Mesopelagic communityMesopelagic community

swordfishswordfish opahopahbigeye tunabigeye tuna

500m500m

400m400m

300m300m

200m200m

100m100m

0m0m

Epipelagic communityEpipelagic community

striped marlinstriped marlin

yellowfin tunayellowfin tuna

wahoowahoo