ROMS Modeling for Marine Protected Area (MPA) Connectivity
Satoshi Mitarai, Dave Siegel, James Watson (UCSB)Charles Dong & Jim McWilliams (UCLA)
A biocomplexity project
“Flow, Fish & Fishing”
Coastal Environmental Quality Initiative (CEQI)
Marine Protected Areas (MPAs)
• To be implemented in Southern California Bight in 2009
Biomass DiversitySizeDensity
Per
cent
cha
nge 446%
166%
21%28%
30 cm 45 cm 60 cm
= 100,000 young
Science of marine reserve (2007)
Quantification of “Coastal Connectivity”
• Key info in designing a network of MPAs
= connectivity of nearshore sites via advection of water parcels
Rocky reefs in Southern California Bight
Rocky reefsRocky reefs
by Michael Robinson
Larval transport by coastal circulations
Advected 100’s km over months
Rocky reefs Rocky reefs
Good MPAcandidate
Good MPAcandidate
Natural mortality Harvesting
Population Dynamics Model
• Requires coastal connectivity info
# of adults at x in year n+1
# of recruits to x from everywhere
# of survivors at x in year n
= +
# of larvae produced at y
Fraction of water parcels transported to x
Recruitment success (%)
xy
Coastal connectivity
Goal of This Study
• Quantify coastal connectivity in the SCB
Using ROMS simulations validated with observations
[ C ]
Dong, Idica & McWilliams, Progress in Oceanography
(in revision)
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. 1996 – Dec. 2002
QuickTime™ and a decompressor
are needed to see this picture.
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)
Winter Spring Summer Autumn
Strong equatorward windReduced currentin SB Channel
Interannual Variability in Lagrangian PDFs
• Reflect El Niño & La Niña transitions
(advection time = 30 days, averaged for all seasons)
1996 1997 1998 1999
El Niño La Niña
Quantifying Coastal Connectivity
• Connectivity can be deduced from Lagrangian PDFs
Spawning: Apr – NovPlanktonic: 25 – 33 days
Kelp bass
Lagrangian PDF for kelp bass from site #43
Mainland to IslandsMainland to Islands
Islands to MainlandIslands to Mainland
Connectivity for Different Species
• Different due to different life histories
Spawning: Jan – MayPlanktonic: 60 – 180 days
Spawning: year aroundPlanktonic: 3 – 12 days
Potential Larval Source Locations
• Useful for MPA implementationWhere are larval sources?
Summation
Averaged for kelp bass, blue rockfish, Averaged for kelp bass, blue rockfish, lingcod, cabezon, canary rockfish & lingcod, cabezon, canary rockfish & red sea urchinred sea urchin
Santa Barbarax
Santa Cruz Santa Cruz IslandIslandSan MiguelSan Miguel
IslandIsland
Santa Barbara Santa Barbara IslandIsland
San Nicholas San Nicholas IslandIsland
x
Oceanside
San Miguel San Miguel IslandIsland
Anacapa Anacapa IslandIsland
San Clemente San Clemente IslandIsland
Santa CatalinaSanta CatalinaIslandIsland
Poor sources...Poor sources...
Summary
• Quantified connectivity in SCB using ROMS simulations
Lagrangian PDF method is employed
Connectivity is deduced from Lagrangian PDFs
• Potential larval sources are suggested
Some ongoing MPAs on Northern Islands are not really….
Mitarai, Siegel, Watson, Dong & McWilliams, JGR - Oceans (in review)
Questions
• How can we tell if the simulated connectivity is accurate?
Accurate enough for what?
To predict nearshore marine population dynamics
Distinctive biogeographic regions
Can we reproduce this?
Courtesy – Pete Raimondi
Two Species Abundance (CRANE Data)
• Q: can we reproduce this, given the simulated connectivity?Kelp bass Kelp rockfish
(Paralabrax clathratus)(Sebastes atrovirens)
CoexistCoexist
Kelp bass Kelp bass dominatesdominates
CoexistCoexist
Kelp bass Kelp bass dominatesdominates
CRANE survey (2004)
A Thought Experiment
• Two species population dynamics
Given the simulated connectivity matrices
Initialization (randomly seeded)
Species #2Species #2
Species #1Species #1
Spawning: Summer
Larval duration: 1 month
Life time: 20 years
#1. Kelp bass type
#2. Kelp rockfish type
Spawning: Winter
Larval duration: 2 months
Life time: 20 years
Population Dynamics Model
• Let’s integrate the model, given the simulated connectivity
# of adults at x in year n+1
# of recruits to x from everywhere
# of survivors at x in year n
= +
xy
Natural mortality Coastal connectivityHarvesting
Population Composition
• Shows reasonable agreement with CRANE data
Regardless of the initial condition
100 %species #1
100 %species #2
75 %species #1
75 %species #2
50-50
Kelp rockfish (#2)Kelp rockfish (#2)
Kelp bass (#1)Kelp bass (#1)
F1 / F2 = 1.1(when they coexist)
After reaches equilibrium
Kelp bass Kelp bass dominatesdominates
CoexistCoexist
Future Direction
• Integrate the framework into SCCOOS
Forecast dispersal, connectivity & population dynamics
Data assimilation?
• Clarify connectivity through boundaries
With Central Coast, across the international border
Important to address species invasion
• Lagrangian validation
Examine dispersal patterns against drifters & HF radar
(A part of Carter’s talk)