Quantifying Connectivity in the Coastal Ocean With Application to the Southern California Bight Satoshi Mitarai, Dave Siegel, James Watson (UCSB) Charles.

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Presentation transcript:

Quantifying Connectivity in the Coastal Ocean With Application to the Southern California Bight Satoshi Mitarai, Dave Siegel, James Watson (UCSB) Charles Dong & Jim McWilliams (UCLA) “Flow, Fish & Fishing”

Quantification of “Coastal Connectivity” Important for applications (e.g., fisheries management) = connectivity of nearshore sites via advection of water parcels Rocky reefs in Southern California Bight Rocky reefs by Michael Robinson Larval transport by coastal circulations Advected 100’s km over months Rocky reefs

Marine Protected Areas (MPAs) Good MPA = larval source, but where? Larval source?

Goal of This Study Quantify coastal connectivity in the SCB Using ROMS simulations validated with observations [ C ] Dong, Idica & McWilliams, Progress in Oceanography (in review) Examined against: MMS current meter & drifters, NDBC buoy, HF radar, AHVRR... Simulated sea surface temperature (Southern California Bight)

Lagrangian PDF methods Describe expected dispersal patterns from a single site Delineate nearshore waters into 135 sites Cover most of rocky reefs Release many particles from each site From each site, around 100 particles are released every 12 hours from Jan – Dec. 2002

Sample Trajectories From Single Site Chaotic dominated by mesoscale eddy motions Red dots: locations after 30 days

Expected Location (Lagrangian PDF) Nearly isotropic from this particular site [ km ] -2 (averaged for 1996 – 2002)

Lagrangian PDFs From Different Sites Heterogeneous reflecting distinctive circulation patterns (advection time = 30 days, averaged for 1996 – 2002) [ km ] -2

Seasonal Variability in Lagrangian PDFs Reflect seasonal variability in circulations (advection time = 30 days, averaged for 1996 – 2002) WinterSpringSummerAutumn Strong equatorward wind Reduced current in SB Channel

Interannual Variability in Lagrangian PDFs Reflect El Niño & La Niña transitions (advection time = 30 days, averaged for all seasons) El Niño La Niña

Quantifying Coastal Connectivity Connectivity can be deduced from Lagrangian PDFs Spawning: Apr – Nov Planktonic: 25 – 33 days Kelp bass Lagrangian PDF for kelp bass from site #43 Mainland to Islands Islands to Mainland

Connectivity for Different Species Different due to different life histories Spawning: Jan – May Planktonic: 60 – 180 days Spawning: year around Planktonic: 3 – 12 days Spawning: Apr – Nov Planktonic: 25 – 33 days

Potential Larval Source Locations Useful for MPA implementation Where are larval sources? Summation Averaged for kelp bass, blue rockfish, lingcod, cabezon, canary rockfish & red sea urchin Santa Barbara x Santa Cruz Island San Miguel Island Santa Barbara Island San Nicholas Island x Oceanside San Miguel Island Anacapa Island San Clemente Island Santa Catalina Island

Summary Quantified connectivity in SCB using ROMS simulations Lagrangian PDF method is employed Reflect distinctive circulation Show strong dependency on release location & season Respond to El Niño & La Niña Connectivity is deduced from Lagrangian PDFs Different for different species (life histories) Potential larval sources are suggested Mitarai, Siegel, Watson, Dong & McWilliams, JGR - Oceans (in review)

Thank you!

ROMS Simulations Driven by realistic winds & BCs Conil & Hall (2006) Realistic wind simulations (MM5 simulations, 18, 6, 2 km) Dong & McWilliams, Cont. Shelf Res. (2007) Domain configuration Wind forcing

ROMS Validations ROMS vs HF radar ROMS vs CalCOFI ROMS vs AVHRR C. Dong, E. Icida and J. McWilliams "Circulation and Multiple-Scale Variability in the Southern California Bight" (2008)

ROMS Validations ROMS vs NDBC ADCP NDBC Station Map Blue lines(ROMS) Red lines (ADCP) Mean STD C. Dong, E. Icida and J. McWilliams "Circulation and Multiple- Scale Variability in the Southern California Bight" (2008) ZonalMeridional

1D Dispersal Kernel Along Mainland (Kelp bass, PLD = days, Spawning = April - November) Simulations Gaussian fit Mean = 56 km (5.6 sites) STD = 170 km (17.0 sites) Poleward transportEquatorward transport Alongshore distance between sites 1 and 62 = 470 km