Hydrodynamic Connectivity in Marine Population DynamicsSatoshi Mitarai1, David A. Siegel1, Bruce E. Kendall1, Robert R. Warner1, Steven D. Gaines1, Christopher E. Costello1 and Kraig B Winters2
1Institute for Computational Earth System Science University of California, Santa Barbara, CA 93106 2Integrative Oceanographic Division, Scripps Institution of Oceanography, La Jolla, CA 92307
“Flow, Fish & Fishing” Project
Destination location (km)
Connectivity in physical space
N
Season #1 #2 #3
Sou
rce
loca
tion
(km
)
Spawning season #1
Spawning season #2
Spawning season #3
Three independent spawning seasons
y
x
Mean windMean offshore current at surface
Santa Barbara
San Franciscox
Target Area
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Stay near the top surface
Question:
Will understanding marine life cycle in turbulence improve predictablity of marine ecosystems?
Habitat
Harvest
RegulationFisherme
n
Market INFO
Flow
Fish
Settlement
Recruitment
Climate
Flow
Fish
Settlement
Recruitment
Harvest
Fishermen
Biophysical Model
Role of Stochastic Connectivity in Population Dynamics
# 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 larvae transported to x
Recruitment success (%)
# of adults harvestedNatural mortality Connectivity matrix
Connectivity estimated from coastal circulation simulations
Particles are released daily for 90 days uniformly in nearshore waters.
Particles are passively transported in horizontal directions while they can actively change their vertical positions.
Settlement is defined when pparticles are found in nearshore during competency window (20 to 40 d)
Consider dynamics of species among sites on a long straight coastline
Marine species have a two life stage (larva-adult) and a sessile adult stage
Connectivity is Stochastic
Connectivity is stochastic on annual time scales
Larval behavior can change connectivity
Stay surface Migrate 50 m
+
•Larvae are transported by coastal eddies as coherent packets
•Coastal eddy motion is chaotic
•Only a few arriving larval packets for single spawning season
Siegel et al, Proceedings of National Academy of Science (accepted for publication)
Mitarai et al., Journal of Marine Systems (in press)
Spatially-explicit population dynamics model We propose to examine five areas in which issues of predictability or scale render decision-making process difficult. These are the missing links in: 1. The physical drivers of larval settlement 2. The spatial scales of nearshore fish populations 3. The role of uncertainty and use of information in fishery management 4. The mismatch in scale between harvesting and regulatory decisions 5. The difficulties associated with multi-species management
Smoothed out if averaged 10+ seasons•Consider single unharvested species
2. Stochastic connectivity
Turbulent structures exist.....
1. Diffusion model
Turbulence is ignored
Diffusion model
Stochastic connectivity
Predictions
...
Mea
n A
dult
Pop
ulat
ion
(%)
Thoughtful experiment 1 - single species case
Thoughtful experiment 2 - two species case
•Consider two similar species A & B
•Species A has a slightly better ability to utilize resources They compete for limited resources at settlement sites
1. Same Behavior 2. Different behavior
A = 100
B = 0
Without difference in behavior With a difference in behavior
A = 60
B = 40
Different behavior leads to species coexistence
Consider single unharvested species
This work is a contribution of the Flow, Fish and Fishing biocomplexity project work and is supported by the National Science Foundation (NSF grant # 0308440).
•Understanding marine life cycle in turbulence changes population dynamics predictions
•A small difference in biological processes can change community structure
Sea surface temperature
=Focus of this poster
Density of settlers (%)
Rec
ruitm
ent R
ate
Particle trajectories & sea level
