Pelagic Predators Food Habits Project

Tim Essington and Mary HunsickerUniversity of Washington

Robert Olsen and Mark MaunderIATTC

Enric CortesSWFSC

Using a Food Habits Database

Our hypothesis:Reduced abundance of large pelagic predators

may gave enhanced the productivity of economically important tunas

If true then:Tunas should comprise a significant component

of pelagic predator diets, throughout the range of their populations

No single sampling program can possibly address this question

Project Objectives

• Develop database of apex predator food habits

• How does predation vary with species, body size, season, location of capture?

• Also provide database “product” for wide use

• Evaluate the “scope” for predation impacts on tuna recruitment

• Simulation and mass-balance modeling

Towards a Food Habits Database

We presently have a database containing summarized data from 37 peer-reviewed publications

Predators (# studies):Tunas: Yellowfin (10); Skipjack (6); Bigeye (4); Albacore (5);

Bluefin (1)Billfish: Striped marlin (4); Blue marlin (3), Black marlin (2),

Swordfish (2)Sharks: Galapagos shark (1), Tiger shark (1); Hammerhead

sharks (3); Shortfin mako (1); Silky shark (1); Bigeye thresher (1)

Others: Mahi mahi (3), Indo-Pacific sailfish (1); Eastern spinner dolphin (1); Coastal spotted dolphin (1); Sailfish (1);

YellowfinYellowfinYellowfinSkipjack 7.8% Skipjack 7.8% Skipjack 7.8% ---11.5 V, 3.9%FO 11.5 V, 3.9%FO 11.5 V, 3.9%FO Yellowfin 2.2%V, <1% FOYellowfin 2.2%V, <1% FOYellowfin 2.2%V, <1% FO

Study locations: Tunas

Skipjack Yellowfin

BigeyeYellowfinSkipjack

SkipjackYellowfin

Tunas

Bigeye,Yellowfin

Data post 1980sData prior to1980s

Blue Marlin Striped Marlin

Study Locations: BillfishesData post 1980sData prior to1980s

Blue Marlin

Black Marlin

Striped MarlinBlue Marlin

Marlins

Summarized Data Reveal Substantial Predation on Skipjack Tuna

Predator

Skipjack Yellowfin Other tunas Billfish

% S

kipj

ack

(mea

n, S

D)

0

10

20

30

40

50

% occurrence% volume% number

Summarized Data Show Variation by Ocean Region

RegionCentral Pacific, H

awaii

Eastern Pacific

Western Pacific

New Zealand/Samoa

% T

hunn

us &

Kat

suw

onus

spp

. (m

ean,

SD

)

0

10

20

30

40

50% occurrence% volume% number% mass

Summary Statistics from Enric Cortes’ Shark database

0.00%

5.00%

10.00%

15.00%

20.00%

25.00%

SE Pacific SW Pacific C Pacific

Region

% K

. pel

amis

in th

e di

et o

f sha

rks

%N%W%O%IRI

N = 42

N = 5

Katsuwonus pelamis

0.00%

5.00%

10.00%

15.00%

20.00%

25.00%

30.00%

35.00%

40.00%

SE Pacific C Pacific

Region

% T

. alb

acar

es in

the

diet

of

shar

ks

%N%W%O%IRI

N = 45

Thunnus albacares

0.00%

5.00%

10.00%

15.00%

20.00%

25.00%

SE Pacific

Region

% T

. obe

sus

in th

e di

et o

fsh

arks

%N%W%O%IRI

Thunnus obseus

PS set locations for two ETP diet studies

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

Acanth

ocyb

ium so

landri

Carcha

rhinus f

alciform

is

Carcha

rhinus l

ongim

anus

Coryph

aena hi

ppurus

Elagatis

bipinn

ulata

Katsuw

onus

pelam

isLo

botes p

acific

usMak

aira in

dica

Makaira

nigrica

nsSph

yrnida

e

Tetraptu

rus an

gustiro

stris

Thunnu

s alba

cares

Thunnu

s obe

sus

Die

t Pro

port

ion

Unid. Thunnus spp

Thunnus obesus

Thunnus albacares

Thunnus alalunga

Unid.Scombridae

Sarda orientalis

Katsuwonus pelamis

Elagatis bipinnulata

Coryphaena hippurus

Auxis spp

Acanthocybium solandri

Predators

Yellowfin tuna

ETP 2003-2005

13%

11%10%

Prey

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

Acanth

ocyb

ium so

landri

Carcha

rhinus f

alciform

is

Carcha

rhinus l

ongim

anus

Coryph

aena hi

ppurus

Elagatis

bipinn

ulata

Katsuw

onus

pelam

isLo

botes p

acific

usMak

aira in

dica

Makaira

nigrica

nsSph

yrnida

e

Tetraptu

rus an

gustiro

stris

Thunnu

s alba

cares

Thunnu

s obe

sus

Die

t Pro

port

ion

Unid. Thunnus spp

Thunnus obesus

Thunnus albacares

Thunnus alalunga

Unid.Scombridae

Sarda orientalis

Katsuwonus pelamis

Elagatis bipinnulata

Coryphaena hippurus

Auxis spp

Acanthocybium solandri

Predators

Bigeye tuna

0.02%

ETP 2003-2005

Prey

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

Acanth

ocyb

ium so

landri

Carcha

rhinus f

alciform

is

Carcha

rhinus l

ongim

anus

Coryph

aena hi

ppurus

Elagatis

bipinn

ulata

Katsuw

onus

pelam

isLo

botes p

acific

usMak

aira in

dica

Makaira

nigrica

nsSph

yrnida

e

Tetraptu

rus an

gustiro

stris

Thunnu

s alba

cares

Thunnu

s obe

sus

Die

t Pro

port

ion

Unid. Thunnus spp

Thunnus obesus

Thunnus albacares

Thunnus alalunga

Unid.Scombridae

Sarda orientalis

Katsuwonus pelamis

Elagatis bipinnulata

Coryphaena hippurus

Auxis spp

Acanthocybium solandri

Predators

Albacore tuna 6%

ETP 2003-2005

Prey

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

Acanth

ocyb

ium so

landri

Carcha

rhinus f

alciform

is

Carcha

rhinus l

ongim

anus

Coryph

aena hi

ppurus

Elagatis

bipinn

ulata

Katsuw

onus

pelam

isLo

botes p

acific

usMak

aira in

dica

Makaira

nigrica

nsSph

yrnida

e

Tetraptu

rus an

gustiro

stris

Thunnu

s alba

cares

Thunnu

s obe

sus

Die

t Pro

port

ion

Unid. Thunnus spp

Thunnus obesus

Thunnus albacares

Thunnus alalunga

Unid.Scombridae

Sarda orientalis

Katsuwonus pelamis

Elagatis bipinnulata

Coryphaena hippurus

Auxis spp

Acanthocybium solandri

Prey

Skipjack

ETP 2003-2005

Predators

40%

22%11%

6%

33%

Why do we need primary data?

• Summarized data don’t allow us to address:– Size-structure of feeding relations– Variation in feeding due to:

• Location• Method of Capture• Season• Other confounding variables

Primary Data Sources: Acquired

• Olson et al. 1992-1994 (ongoing)• Alverson 1950’s data (ongoing, 75%

complete)• POFI data 1950’s (ongoing, just obtained)• Olson et al. 1970’s (not yet started)• Wish List:

– ECOTAP data, plus ongoing SPC data collection efforts

– Anything else!

Why the details matter:Size Selectivity and Cannibalism

Juvenile Skipjack account for 10 – 30 % of adult skipjack diets

What does this mean for juvenile skipjack ?

How many survive?

Model Schematic

Inputs:

Diet contribution (% mass)Mean Size Consumed (variance)Allometry of consumption rateSize-at-agePost “recruit” age-structure (M, F)Pre-”recruit” other mortalityOnset of cannibalism

Model Calculations

Size-based vulnerability functionRecruitment rate (age 0.125 mo)Age-specific predation mortality rate

Proportion of cohort surviving cannibalism

NaturalMortality

NaturalMortality

NaturalMortality

NaturalMortality

Stock

Rec

ruit

FishingMortality

FishingMortality

FishingMortality

FishingMortality

Size structure of feeding is critical

Results based on age-structured modeling analysis

0.0%

5.0%

10.0%

15.0%

20.0%

25.0%

8 10 12

Mean Size of Consumed Skipjack (cm)

Prop

ortio

n of

Coh

ort S

urvi

ving

2%

4%

21%

Next Steps: Modeling

• Sensitivity analysis and write up skipjack model for publication

• Apply to skipjack, yellowfin and bigeye

• Realistic expectations!

A new culture of data sharing

• We can all benefit from a centralized database

• Without archival efforts, hard – earned data have limited life span

• Some questions can only be addressed via synthesis of many studies

• Archival and analysis promotes serendipitous discoveries

“But I’m not done with my data yet”

• This new culture of data sharing also requires an ethic of data use

• No data will be used without the permission of the provider for a specific requested use

• We are developing guidelines to ensure fair data use and exchange

Want to learn more?

www.fish.washington.edu/tunapred

Funding is provided by Pelagic Fisheries Research Program