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Modeling Larval Connectivity for the SoCal Bight Satoshi Mitarai, James Watson & David Siegel Institute for Computational Earth System Science University.

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Presentation on theme: "Modeling Larval Connectivity for the SoCal Bight Satoshi Mitarai, James Watson & David Siegel Institute for Computational Earth System Science University."— Presentation transcript:

1 Modeling Larval Connectivity for the SoCal Bight Satoshi Mitarai, James Watson & David Siegel Institute for Computational Earth System Science University of California, Santa Barbara Changming Dong & James McWilliams Institute of Geophysical and Planetary Physics University of California, Los Angeles

2 Why Larval Connectivity? Some places are better fishing than others –Habitat type & quality, oceanographic connection to other sites, humankind history, etc. Larval connectivity measures the probability that sites are connected for a given species –Measures larval source / sink characteristics –Required for spatial demographic stock models –Provides scales of connectivity for MPA network design

3 Why Model Larval Connectivity? Knowledge of how larvae are transported from one site to any other on all time scales Need continuous descriptions of velocity on time scales from hours to decades Data sets are just getting to this point Models naturally integrate over all scales

4 December 14, 2008 HF Radar Current Observations HF radar surface currents 0.5 to 6.5 km resolution coverage is getting better www.sccoos.org/data/hfrnet/ December 14, 2007 December 14, 2006

5 Talk Outline Introduce the circulation model (ROMS) configuration & its fidelity to observations Determine dispersal patterns for the SoCal Bight using Lagrangian techniques Assess patterns of potential & realized larval connectivity for SoCal Bight

6 Regional Ocean Modeling System (ROMS) (www.myroms.org) One-way nested grids (~20km  ~6.7km  1km) Surface Forcing from NARR obs (MM5 18km, 6km, 2 km) Open Boundary Forcings from obs (SODA, monthly updates) Initialized with climatology Integration from 1996 to 2003 Integration to present in progress 20km 6.7km 1 km Dong & McWilliams CSR (2007) Model Configuration

7 Pacific Ocean Los Angeles Model Domain Dong & McWilliams CSR (2007)

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10 Dong et al. [in review]

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12 Dong et al. (in review)

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14 Comparison to ADCP Current Profiles Profiles from SBC Red observations Blue model Dashes show stdev Mean currents are well modeled Envelope shows variability is also well modeled

15 Topex/Jason - satellite sea level observations Interannual Variations of Sea Level Dong et al. (in review)

16 Sea level (m)

17 Dong & McWilliams (2007) Eddy Variability anticyclonic cyclonic Pattern is highly dynamic & contains most of the KE

18 Dong et al. (in review) Sea level (m)

19 Modeling of SoCal Bight Circulation Good fidelity of mean, seasonal & inter- annual circulation patterns Mean & fluctuating velocity profiles are also well modeled –Currents are fairly uniform with depth Eddy driven circulation is large Can be better… but it is best available data for the circulation of the SoCal Bight

20 Connectivity Domain Work to follow from Mitarai et al (in review - JGR) & Watson et al (in prep)

21 Red dots: locations after 30 days Example 30 Day Trajectories Surface following…

22 [ km ] -2 Dispersal from San Nicolas millions of water parcel releases

23 Dispersal from Other Sites Advection time = 30 days [ km ] -2

24 Advection time = 30 days Seasonal Variability

25 Advection time = 30 days Interannual Variability

26 Dispersal in the SoCal Bight Surface water parcels spread out throughout the Bight within 60 days Strong position-dependence Poleward transport along mainland Retention in SB Channel & around San Clemente Island Strong seasonal & interannual variability Mitarai, Siegel, Watson, Dong & McWilliams (in review)

27 Quantifying Connectivity 135 x 135 source-to-destination matrix (connectivity matrix) Repeat for all source sites Larval life history is now included (PLD, spawning period, etc.) Quantifies probability of larval transport from site to site Assumes all sites have equal larval production potential connectivity Watson, Mitarai, Caselle, Siegel, Dong & McWilliams (in prep)

28 Kelp Bass Potential Connectivity PLD = 25 – 33 d, Spawning = Apr – Nov Connectivity is heterogeneous & asymmetric Strong transport from mainland to islands

29 Assumes uniform larval production PLD = 25-33 d; Spawning from Apr to Nov Good Sources: Long Beach, Santa Monica, Ventura Good Destinations: Chinese Harbor, Avalon Kelp Bass Source / Destination Strength

30 PLD = 3 – 12 days, all year aroundPLD = 60 – 120 days, Jan – May The Larval Time Course Matters Watson et al (in prep)

31 Kelp Bass Realized Connectivity Account for non-uniform larval production Kelp bass egg prod from CRANE obs Watson et al (in prep) Mainland North South (S to N) Islands Islands Destination Site Source Site Mainland North South (S to N) Islands Islands

32 Larval Connectivity in the SoCal Bight Connectivity is heterogeneous & asymmetric Mainland sites are good sources while islands are poor potential sources Nearby islands are often good destinations Potential connectivity patterns differ for different larval time histories Realized connectivity patterns differ due to differences in larval production


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