food-web implications for pelagic top predators: … implications for pelagic top predators: from...

Food-web Implications for Pelagic Top Predators:from Guts and Isotopes to Models

Robert J. OlsonInter-American Tropical Tuna CommissionLa Jolla, California

Photo compliments of Dr. Frederic Menard, IRD, France

Food webs and Ecosystem-based Fisheries Science

• “Ecosystem” “Ecology”: multispecies approaches to management, reduction of bycatch, including environmental factors in stock assessment models.

• Ecosystem: a geographically specified system of organisms, including humans, the environment, and the processes that control its dynamics (NOAA 2005).

• “The time has come for community ecology to replace population ecology as the fundamental ecological science underlying fisheries” (Mangel and Levin 2005).

• Communities are assemblages of species. Interactions makes the community more than the sum of its parts.

• Communities interact via the food web.

NOAA. 2005. New priorities for the 21st century: NOAA's strategic plan. NOAA, Washington, D.C.Mangel, M., and P.S. Levin. 2005. Regime, phase and paradigm shifts: making community

ecology the basic science for fisheries. Phil. Trans. R. Soc. B, 360 (1453): 95-105.

Why study food webs?

• Trophic structure represented in food webs is thought to be the central organizing concept in ecology (Martinez 1995).

• Knowledge of pelagic food webs is still rudimentary, in many aspects. Better food-web models are needed (preferably, spatially-explicit).

• Review an assortment of information about food-web research in eastern Pacific, and (less-so) on modeling efforts.

Eight ecosystem characteristics

1. The ability to predict ecosystem behavior is limited2. Ecosystems have thresholds and limits which, when

exceeded, can effect major ecosystem restructuring3. Once thresholds and limits have been exceeded,

changes can be irreversible4. Diversity is important to ecosystem functioning5. Multiple scales interact within and among ecosystems6. Components of ecosystems are linked7. Ecosystem boundaries are open8. Ecosystems change over time

NMFS Ecosystem Principles Advisory Panel:

Components of ecosystems are linked

How do we determine what the important components and linkages are? Critical food-web connections.

•Keystone species•Dietary specialists•Models can help

The tools for food-web research:•Diet studies (stomach-contents analysis)•Stable isotope analysis•Compound specific stable isotope analysis (amino-acids)•Fatty acid analysis

Stomach-contents analysis (species identification) (and monitoring)

V. Allain, SPCF. Galvan, CICIMARIATTC, Manta, Ecuador

Perc

ent

wei

ght

TunasDolphins

SharksBillfishes

Dorado, Wahoo, R. Runner

0%

20%

40%

60%

80%

100%

Diet data for eastern Pacific predators (’92-’94)

Colleagues:•Felipe Galván-M, CICIMAR, La Paz, BCS, Mexico•Julio Martínez, Cumaná, Venezuela

Diet data formulated food web (ETP)Tr

ophi

c le

vel –

Niv

eltró

fico

Olson, R.J., and G.M. Watters. 2003. A model of the pelagic ecosystem in the eastern tropical Pacific Ocean. Inter-American Tropical Tuna Commission, Bulletin 22 (3): 133-218.

Yellowfin tuna stomach-contents (1990s, 2000s)

Set Locations

1990s

2000s

Feeding Ecology of Surface Migrating Myctophid Fishesin the eastern Tropical Pacific

Joel Van Noord, Univ. of San DiegoJessica Redfern et al., NMFS SWFSC

Trophic position: stable isotopes

Isotopic fractionation – the light 14N isotope is excreted more than the heavy 15N isotope, leaving the animal enriched by 3‰ in δ15N relative to its food source.

δ15Npredator 3.0 + δ15Nprey (‰)=δ15N [(15N/14N) / Rstd – 1] x 1000=

Trophic position: stable isotopes,stomach contents

0

2

4

6

8

10

12

14

16

18

-15 -10 -5 0 5 10 15 20 25 30Latitude (degrees)

δ15N

(‰)

Yellowfin tuna (5-deg areas)

Yellowfin tuna (outside 5-deg areas)

Mesozooplankton (5-deg areas)

Mesozoopl. (outside 5-deg areas)

CSIA samples

Mean TP = 4.5

PFRP, B. Popp, B. Graham, C. Hannides, F. Galván, G. López, B. Fry

Copepods δ15N = 6-12‰

YFT δ15N = 13-16‰

Gladis Lopez-I., CICIMAR, Mexico

Yellowfin trophic position (TP)

ΔYFT-COP = 4.0 – 7.6 ‰

TP ≈ 4.3 - 5.3,spanning ~ 1 trophic level

B. Popp, UHB. Graham, UHF. Galvan-Magana, CICIMARC. Lennert-Cody, IATTCPFRP

δ15N of Amino Acids

TL 4.5

Bulk white muscle

Yellowfin tuna – eastern tropical Pacific

(“Source” AA)

(“Trophic” AA)

Popp

, B.N

., B.

S. G

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TP shift≈1

E-W shift in trophic position in ETP

Traditional techniques problematic, e.g. gut content analysis

Prey species have unique lipid / fatty acid compositions

Many fatty acids readily transferred from prey to predator with minimal modification

Constituent fatty acids therefore represent, to some extent, a temporal integration of diet

Can be quantitative and allows temporal integration (cf gut content analysis)

Signature fatty acids: combinations of fatty acids preserved as they pass up the food chain

Complements other approaches

Lipids as Dietary Tracers

* Jock Young, CSIRO

Can models predict ecosystem behavior?

• Nature is seldom linear, and often unpredictable (Francis et al. 2007) .

• Ecosystem resilience depends on “stability domain” of existing food web: how broad is it, how resistant is it to change, how close is it to reorganizing? (Francis et al. 2007) Models are required.

• How should components of the food web be represented in models?

• Can models highlight key areas for field/lab studies?

Francis, R.C., M.A. Hixon, M.E. Clarke, S.A. Murawski, and S. Ralston. 2007. Ten commandments for ecosystem-based fisheries scientists. Fisheries, 32 (5): 217-233.

Taxonomy in modelsTr

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(Olson, R.J., and G.M. Watters. 2003. A model of the pelagic ecosystem in the eastern tropical Pacific Ocean. Inter-American Tropical Tuna Commission, Bulletin 22 (3): 133-218.)

Epipelagic

Epi-Meso

Meso

Bathy

Meso-Bathy

Epi-Bathy

Epi

Meso

Bathy

Functional groups in models

Qualitative analysis of Pacific Ocean predators

20 N20 N20 N20 N20 N20 N20 N20 N20 N

South-Western Pacific Ocean

Trop

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5.0

4.5

4.0

3.5

3.0

2.5

2.0

1.5

1.0

Food webs composed of 200+ taxa

Aggregated food webs composed of 24 nodes with similar predator prey relationships

0 20 40 60 80 100 120 140 160

Producers

Primary Consumers

Secondary Consumers

Misc. Epipelagic Fishes

Flyingfishes

Misc. Mesopelagic Fishes

Crabs

Sea Turtles

Grazing Birds

Rays

Baleen Whales

Auxis spp.

Bluefin Tuna

Misc. Piscivores

Small Swordfish

Cephalopods

Skipjack Tuna

Small Yellowfin Tuna

Small Bigeye Tuna

Small Wahoo

Mesopelagic Dolphins

Large Yellowfin Tuna

Large Mahimahi

Small Sailfish

Small Mahimahi

Pursuit Birds

Large Sailfish

Large Swordfish

Large Wahoo

Large Sharks

Spotted Dolphins

Large Bigeye Tuna

Toothed Whales

Small Marlins

Small Sharks

Large MarlinsLarge marlinsSmall sharks

Small marlinsToothed whales

Large bigeyeSpotted dolphins

Large sharksLarge wahoo

Large swordfishLarge sailfishPursuit birds

Small mahimahiSmall sailfish

Large mahimahiLarge yellowfin

Mesopelagic dolphinsSmall wahooSmall bigeye

Small yellowfinSkipjack

CephalopodsSmall swordfishMisc. piscivores

Bluefin tunaAuxis spp.

Baleen whalesRays

Grazing birdsSea turtles

CrabsMisc. mesopelagic fishes

FlyingfishesMisc. epipelagic fishesSecondary consumers

Primary consumersProducers

Index of Sensitivity

(5.1)(5.1)(5.1)(4.9)(4.8)(4.8)(4.8)(4.8)(4.8)(4.7)(4.7)(4.7)

(5.3)(5.2)

(5.2)

(4.6)(4.5)(4.5)

(4.7)

(4.1)(3.9)(3.9)(3.8)(3.6)(3.6)(3.6)

(4.1)

(4.6)

(3.3)(3.0)

(2.0)(1.0)

(5.5)(5.4)

(5.4)(5.4)

CephalopodsAuxis spp.

Can models highlight research needs?Sensitivity analysis of ETP Ecopath model

Ecosystems change over time

• Jumbo (Humboldt) squid range expansion

• Are tunas effective biological samplers of the middle trophic levels*? Indicator species in stomach contents?– Squid consumption by tunas has increased over time

– Decadal changes in yellowfin tuna diet composition

* Generalist predators (opportunistic), high energy requirements, food limited, range widely, prey size-predator size ranges widely

Pelagic ommastrephid squids (e.g. Dosidicus gigas): Ecosystem indicators?

Olson, R.J., M.H. Román-Verdesoto, and G.L. Macías-Pita. 2006. Bycatch of jumbo squid Dosidicus gigas in the tuna purse-seine fishery of the eastern Pacific Ocean and predatory behaviour during capture. Fish. Res. 79(1-2): 48-55.

Percent frequency of cephalopods in the stomach contents of yellowfin tuna in the eastern Pacific Ocean

Hunsicker, Essington, Olson, Duffy. Manuscript in prep. “Evidence of increased cephalopod production in a large marine ecosystem.”

1955-1960 1969-1972 1992-1994 2003-2005

Per

cent

freq

uenc

y of

occ

urre

nce

0

20

40

60

80

100

UnidentifiedOctopusSquidAll cephalopods

PFRP, F. Galvan,N. Bocanegra, V. Alatorre, J. Martinez, F. Alverson

Decadal variation in yellowfin tuna diet composition

• Nonparametric: relationships between variables that may include: nonlinearity, high order interactions, lack of balance, missing values

• Combinations of explanatory variables used to explain variation of a response variable (prey groups % weight), by repeatedly splitting the data into groups that are as homogenous as possible

• Each possible value for each explanatory variable is considered as a potential candidate split

• The candidate split which provides the largest decrease in impurity, or minimizes the misclassification rate, is chosen to split the data into two subgroups

• Procedure is repeated with each subgroup until no significant decrease in impurity is possible, resulting in a terminal node (leaf).

• 10-fold cross-validation used to prune trees (1-SE Rule) • The proportions in each category are represented in each leaf

Classification tree model constructed using the Diet library of R written by Petra Kuhnert, CSIRO

Classification tree analysis

Classification tree analysis

Cephalopods• Argonauta spp.• Dosidicus gigas• Sthenoteuthis oualaniensis

Crustaceans• Pleuroncodes planipes• Portunidae family• Other Crustaceans

Fishes• Cetengraulis mysticetus• Engraulis mordax• Phosichthyidae family• Myctophidae family• Exocoetus spp.• Other Exocoetids• Oxyporhamphus micropterus• Carangidae family• Auxis spp.• Scomber japonicus• Cubiceps spp.• Lactoria diaphana

Response variable(18 dominant prey groups)

Explanatory variables

• Year

• Quarter of year

• Purse-seine set time of day

• Latitude

• Longitude

• SST

• Yellowfin size

• Yellowfin sex

• Yellowfin stomach fullness

• Purse-seine set type

Yellowfin tuna stomach sample locations

Set Locations

1990s

2000s

Prop

ortio

n Re

lativ

e Im

port

ance

0.0

0.2

0.4

0.6

0.8

1.0

Classification Tree Analysis: Variable Importance Rankings

Predictor variable

Lat = latitude, Lon = longitude, SST = Sea Surface Temperature, YR = year,SA = set type, Qtr = quarter, Time = set time of day, FL = yellowfin fork length,Full = yellowfin stomach fullness

b-DG: Dosidicus gigasc-SO: Sthenoteuthis oualaniensise-PP: Pleuroncodes planipesg-CM: Cetengraulis mysticetush-EM: Engraulis mordaxi-Phos: Phosichthyidae familym-OM: Oxyporhamphus micripterusn-Car: Carangidae familyo-Aux: Auxis spp.p-SJ: Scomber japonicusq-Cub: Cubiceps spp.r-LD: Lactoria diaphana

squids

crustacean

fishes

R2 = 0.45

N of 17.3°N

Set Locations

1990s

2000s

North of Latitude 17.3°N


0%

5%

10%

15%

20%

25%

30%

35%

Mea

n %

Wei

ght (

±2S

E)

north of latitude 17.3N

south of latitude 17.3N

Yellowfin tuna diet composition at first split


squids

crustacean

fishes

R2 = 0.45

South of 4.8° S

Set Locations

1990s

2000s

North of Latitude 17.3°N


South of Latitude 4.8°S

0%

10%

20%

30%

40%

50%

60%

70%

mea

n %

W (±

2SE)

North of Latitude 4.8°SSouth of Latitude 4.8°S

Yellowfin tuna diet composition

Jumbo squid

Anchoveta

Set Locations

1990s

2000s

South of Latitude 17.3°N


North of Latitude 4.8°S


squids

crustacean

fishes

R2 = 0.45

0%

5%

10%

15%

20%

25%

30%

35%

40%

45%

Mea

n %

Wei

ght (

±2S

E)

Yellowfin tuna diet composition at time split (south of latitude 17.3 N, north of latitude 6.1 S, SST ≥23.42

1992-1994 diet composition2003-2005 diet composition

Yellowfin tuna diet composition at year split

Jumbo squid

Auxis spp.

Mesopel. fishesEpipel. fishes

Summary

• Research on pelagic food webs is progressing; should be encouraged.

• Chemical tracer methods are providing insight (SIA, AA-CSIA, fatty acids).

• Stomach contents analyses are still necessary (monitoring indicator prey species).

• Better ecosystem (food web) models are needed (spatially-explicit). Identify critical food-web connections.

• Food-web models should depict taxonomic ecosystem components (indicator species).

• Epipelagic ecosystems appear to change over time.

• Recommendation: low-level, well-designed, continuous stomach sampling of tunas, biological samplers, to monitor changes.

Acknowledgements• Pelagic Fisheries Research Program and John Sibert, Univ.

Hawaii• NOAA Fisheries STAR Project, Lisa Ballance, G. Watters, and

many others• IATTC observers and staff in Ecuador and Mexico• Brian Popp, B. Graham, N. Wallsgrove, E. Gier, J. Tanimoto, T.

Rust, A. Carter, Isotope Biogeochemistry Laboratory, Univ. Hawaii

• Felipe Galván-Magaña, G. López-Ibarra, N. Bocanegra-Castillo, V. Alatorre-Ramírez, CICIMAR, La Paz Mexico

• Tim Essington, M. Hunsicker, Univ. Washington• C. Lennert-Cody, M. Maunder, L. Duffy, M. Román-Verdesoto, C.

Patnode, G.L. Macías-Pita, IATTC • B. Fry, Louisiana State Univ., Baton Rouge• V. Allain, Secretariat of the Pacific Community, New Caledonia• Jock Young, Jeff Dambacher, CSIRO• Jim Kitchell, Univ. Wisconsin

food-web implications for pelagic top predators: … implications for pelagic top predators: from...

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