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Lagrangian description of 2-D marine larval dispersal kernels. Karen Pehrson Edwards, Jon Hare, Cisco Werner, Harvey Seim Ocean Sciences, Feb. 2006. Outline. Background: Dispersal Kernels Model Region: The South Atlantic Bight Methods: Lagrangian Particle Tracking

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Lagrangian description of 2 d marine larval dispersal kernels l.jpg

Lagrangian description of 2-D marine larval dispersal kernels

Karen Pehrson Edwards, Jon Hare, Cisco Werner, Harvey Seim

Ocean Sciences, Feb. 2006


Outline l.jpg

Outline

  • Background: Dispersal Kernels

  • Model Region: The South Atlantic Bight

  • Methods: Lagrangian Particle Tracking

  • Results: Quantifying the dispersal kernels

  • Next steps

Provided by Harvey Walsh, NOAA Beaufort


Dispersal kernels l.jpg

1D dispersal kernel -Passive, Mean Flow- Diffusion

Dispersal Kernels

  • A dispersal curve, or dispersal kernel (probability density function), the probability that a larva will settle at a given distance from its release location.

    Cowen et al. (2002)

  • Factors affecting dispersal include:

    • Physical factors:

      • Advection & diffusion

      • Intermittent/ episodic events,

      • interannual variability,

      • long-term modulations

    • Biological factors:

      • Spawning time & location

      • Larval behavior

      • Along-trajectory mortality

      • Larval condition and the ability to respond to cues for suitable habitat.

        Cowen et al. (2002), Mora & Sale (2002)

Provided by Harvey Walsh, NOAA Beaufort


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Understanding larval dispersal provides important information about:

  • Population connectivity

  • Population persistence or sustainability

  • Effectiveness and design of management strategies such as MPAs

    Cowen et al, 2002


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Question: what is the relative importance of the following factors on larval dispersal and population connectivity?

  • time of release,

  • location of release,

  • larval duration,

  • larval behavior, and

  • larval dispersion

  • Focusing on a case study in the South Atlantic Bight


The south atlantic bight l.jpg

Cape Hatteras

NC

SC

GA

Cape Canaveral

FL

The South Atlantic Bight

Gulf Stream


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The South Atlantic Bight

Inner Shelf (<15-20m):

  • River runoff

  • Atmospheric fluxes and tides

Mid- Shelf (20-40m):

  • Winds

  • Tides and Gulf Stream

Outer- Shelf (>40m):

  • Gulf Stream

http://www.skio.peachnet.edu/

Lee et al. 1991


Methods lagrangian particle tracking model l.jpg

Methods: Lagrangian Particle Tracking Model

  • 3D long-term monthly mean circulation fields (Blanton et al., 2003)

  • Plus the M2 tide

  • and turbulent random kick (providing larval dispersion).

  • 300 particles released in each model run.


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Results: GRNMS Dispersal

  • Monthly releases

  • Mid-depth releases

  • 30d passive

  • Principal Component Analysis (PCA) defines the dispersal kernel.


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Monthly Mean Dispersal from GRNMS


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  • Using MANOVA (1620 model runs) quantify the relative importance:


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Larval Behavior

Resulting mean dispersal for each behavior:

Simple Model Behaviors


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Larval Behavior

Dispersal for particles released at 60m isobath:

Mid-depth

Shallow

Deep


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Physics

Tracks of drifters released at GRNMS

  • Model 2002-2004 to look at interannual variability


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www.martinreefs.com/pages/species_index/species_common.html

Adult Black Sea Bass Species Occurrence

Hare et al., 1999

http://map.mapwise.com/safmc MARMAP survey

Modeling specific species


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Dispersal in the SAB

  • Dominant factors: Time and Location of Release

    • with strong seasonal modulation

  • Behavioral Implications

    • Adult behavior (spawning time & location):

      • most important factor in quantifying dispersal with spawning in (apparently) retentive inner- to mid-shelf

    • Larval behavior: smaller effects possibly due to

      • Weak vertical structure on inner-shelf

      • Long-term (average) flow fields don’t account for transient features.


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