Pelagic Predators Food Habits Projectimina.soest.hawaii.edu/PFRP/Nov07mtg/Essington.pdfProject...
Transcript of Pelagic Predators Food Habits Projectimina.soest.hawaii.edu/PFRP/Nov07mtg/Essington.pdfProject...
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