Latitudinal complexity in the deep scattering layers and top predator distribution in the Central Equatorial Pacific Elliott L. Hazen Duke University Marine Lab, 135 Duke Marine Lab Rd., Beaufort, NC 28516, USA Research Questions 1. What drives prey distribution? – Oceanography – Their prey – Predation Risk

Mason and Brandt 1996 Ocean-predator models • Model with most explanatory power (30% variation explained) • What about prey?

Redfern et al. 2008

Thermocline Depth Study site • O.E. Sette March 6th-29th 2006 Hawaii

NEC 1) HI

NECC

SEC (N) 2) EQ EUC SEC (S)

3) AS SECC

American Samoa Hypotheses

1. Horizontal density of prey is greatest in upwelling systems with highest chlorophyll density 2. Vertical distribution of prey is a function of upwelling, chlorophyll density, and time of day 3. Marine mammal distribution is best predicted from both prey and oceanographic data Methods

• CTDs: • Temperature • Salinity • Dissolved oxygen • Chlorophyll-a

• Downward looking SIMRAD EK60 echosounders • Relative density of prey (Sv) in decibels (dB) Methods • Continuous Acoustic Doppler Current Profiler – Phase shift to detect current speeds • Marine mammal sighting data • Satellite remotely sensed data Current patterns

SECC SEC (S) SEC (N) NEC East NE CC

EUC

West

AS EQ HI Temperature patterns

AS EQ HI Fluorescence patterns

AS EQ HI Deep Scattering Layers

b

Hawaii

b a a Surf a a b a 1)H a b a c I Mid

Deep 2)E Q

3)AS

AS EQ HI American Samoa Marine Mammals

Convergence

n=5

n=22

n=6 Marine Mammals Marine Mammals Conclusions • Cold water, nutrient rich upwelling at the equator with increased chlorophyll • In turn, total backscatter greatest at the equator • Marine mammal sightings agreed with foraging preferences • Productivity high enough at the equator for individuals to remain at surface / midwater

(Ballance et al. 2006, Sinclair 1992, Baird et al. 2008) Acknowledgements • Reka Domokos • Jeff Polovina • Matt Wilson • Jamie Gove • J. Roberts • O.E. Sette • Oak Foundation • PFRP