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Scaling and Modeling of Larval Settlement Satoshi Mitarai Oct. 19, 2005

Scaling and Modeling of Larval Settlement Satoshi Mitarai Oct. 19, 2005

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Page 1: Scaling and Modeling of Larval Settlement Satoshi Mitarai Oct. 19, 2005

Scaling and Modeling of Larval Settlement

Satoshi Mitarai

Oct. 19, 2005

Page 2: Scaling and Modeling of Larval Settlement Satoshi Mitarai Oct. 19, 2005

GOAL OF “FLOW”

• Assess larval dispersal scales using idealized simulations of California Current

• Develop simple modeling to establish source-destination relationships– Without fluid dynamics simulations, which are

time consuming

Page 3: Scaling and Modeling of Larval Settlement Satoshi Mitarai Oct. 19, 2005

WHAT’S NEW?

• Weak upwelling case is added

• Larval dispersal scales are quantified

• A simple model to establish source-destination relationships is proposed– Accounts for spatial scales properly

Page 4: Scaling and Modeling of Larval Settlement Satoshi Mitarai Oct. 19, 2005

TEMPERATURE FIELD(TOP VIEW)

Strong upwelling Weak upwelling

Summer Winter

Page 5: Scaling and Modeling of Larval Settlement Satoshi Mitarai Oct. 19, 2005

MEAN TEMPERATURE FIELD(SUMMER)

Simulation CalCOFI

Shows reasonable agreement with CalCOFI data

(Averaged over 6 realizations)

Page 6: Scaling and Modeling of Larval Settlement Satoshi Mitarai Oct. 19, 2005

MEAN TEMPERATURE FIELD(WINTER)

Simulation CalCOFI

Shows a good agreement with CalCOFI data

(Averaged over 6 realizations)

Page 7: Scaling and Modeling of Larval Settlement Satoshi Mitarai Oct. 19, 2005

LARVAL TRAJECTORIESSummer Winter

Eddies sweep larvae into “packet” which stays together thru much of pelagic stage

Page 8: Scaling and Modeling of Larval Settlement Satoshi Mitarai Oct. 19, 2005

LAGRANGIAN STATISTICS

3.4 / 4.340 / 484.2 / 4.6Poulain et al

(1998)

4.3 / 4.532 / 382.9 / 3.5Swenson et al

(2001)

1.6 / 1.829 / 296.9 / 5.7Winter

Simulations

3.1 / 4.131 / 353.7 / 3.7Summer

Simulations

Diffusivity

Zonal / Merid

Length Scale

Zonal / Merid

Time scale

Zonal / MeridData Set

Winter shows more correlation in time

& less diffusivity

Page 9: Scaling and Modeling of Larval Settlement Satoshi Mitarai Oct. 19, 2005

LARVAL TRANSPORT& SETTLEMENT

Summer Winter

More settlers are observed in winter

Page 10: Scaling and Modeling of Larval Settlement Satoshi Mitarai Oct. 19, 2005

ONLY SETTLERSSummer Winter

Page 11: Scaling and Modeling of Larval Settlement Satoshi Mitarai Oct. 19, 2005

ALONGSHORE DISPERSAL KERNEL

Summer Winter

Gaussian fitting

More alongshore travel distance in summer

(Obtained from 6 realizations)

AVG = -122 km, STD = 103 km AVG = -80 km, STD = 92 km

Page 12: Scaling and Modeling of Larval Settlement Satoshi Mitarai Oct. 19, 2005

CROSS-SHORE DISPERSAL KERNEL

Lognormal fitting

Summer Winter

More offshore travel distance in summerSettlers move out nearshore habitat before settle

(Obtained from 6 realizations)

Page 13: Scaling and Modeling of Larval Settlement Satoshi Mitarai Oct. 19, 2005

ARRIVAL DIAGRAMSummer

15 days

21 days

43 km

64 km

Using variogram …

Winter

Page 14: Scaling and Modeling of Larval Settlement Satoshi Mitarai Oct. 19, 2005

CONNECTIVITY MATRIXSummer Winter

48 km 53 km

Page 15: Scaling and Modeling of Larval Settlement Satoshi Mitarai Oct. 19, 2005

SUMMARY

• Travel distance & survivability shows difference between summer & winter– More travel distance in summer

– Lower survivability in summer

• Settlement scales do not show much difference between summer & winter– Arrival length ~ 50 km

– Arrival time ~ a few weeks

– Connectivity length ~ 50 km

Page 16: Scaling and Modeling of Larval Settlement Satoshi Mitarai Oct. 19, 2005

CONNECTIVITY MATRIX MODELDiffusion model Spiky kernel model

Neither one accounts for spatial structures

Page 17: Scaling and Modeling of Larval Settlement Satoshi Mitarai Oct. 19, 2005

A NEW MODEL FOR CONNECTIVITY MATRIX

• Idea: model settlement events as a summation of “settlement packets”– Number

– Size

– Source locations

– Travel distance

Rossby radius (~50 km)

Randomly (uniform distribution)

Randomly (dispersal kernel)

Page 18: Scaling and Modeling of Larval Settlement Satoshi Mitarai Oct. 19, 2005

• Determine # of settlement packets N = (T/t) (L/l) f (D/l)

NUMBER OF SETTLEMENT PACKETS

T: Larval release duration t: Lagrangian correlation time L: domain size l: Rossby radius f: survivabilityD: standard deviation of dispersal kernel

Total # of released packets

# of settlement events per packet

Page 19: Scaling and Modeling of Larval Settlement Satoshi Mitarai Oct. 19, 2005

MODEL PREDICTIONSSummer Winter

Accounts for spatial structures

Page 20: Scaling and Modeling of Larval Settlement Satoshi Mitarai Oct. 19, 2005

DIFFUSION LIMIT

Packet model

1 season 6 seasons 12 seasons 120 seasons

1 season 6 seasons 12 seasons Diffusion

Flow simulation Diffusion model

Page 21: Scaling and Modeling of Larval Settlement Satoshi Mitarai Oct. 19, 2005

NEXT STEPS

• Use proposed model in F3 model

• Investigate effect of larval behavior– Preliminary study has been already done

• Investigate effect of coastal topography

Page 22: Scaling and Modeling of Larval Settlement Satoshi Mitarai Oct. 19, 2005
Page 23: Scaling and Modeling of Larval Settlement Satoshi Mitarai Oct. 19, 2005

LAGRANGIAN STATISTICS

3.4 / 4.340 / 484.2 / 4.6Poulain et al

(1998)

4.3 / 4.532 / 382.9 / 3.5Swenson et al

(2001)

1.6 / 1.829 / 296.9 / 5.7Winter

Simulations

3.1 / 4.131 / 353.7 / 3.7Summer

Simulations

Diffusivity

Zonal / Merid

Length Scale

Zonal / Merid

Time scale

Zonal / MeridData Set

Simulations: 6 realizations, 6000 particles

Swenson et al (2001): late spring to early fall, 1985-1990, 124 drifters, 18N-40N

Poulain et al (1998): early spring to late fall, 1985-1986, 29 drifters, 18N-36N