1. Flow, Fish & Fishing
A Biocomplexity Project
Investigation of the role of larval behavior in determining nearshore habitat connectivity
Satoshi Mitarai, David Siegel, Robert Warner
University of California, Santa Barbara, CA
Kraig Winters
Scripps Institution of Oceanography, La Jolla, CA

2. GOAL OF THIS WORK
Investigate the role of vertical positioning in determining habitat connectivity
Dispersal kernel
Q: Does vertical positioning do this?
# of successful recruits
The goal of this work is to investigate the role of the vertical position of fish larvae in determining nearshore fish habitat connectivity. This diagram, often called the dispersal kernel, shows the role of larval behaviors in determining habitat connectivity and in sustaining populations. I took this figure from Steneck’s paper. The number of successful recruits is plotted against the distance from the larval source. Two cases are shown. The first case; fish larvae are transported passively by coastal circulation processes. In this case, larval recruitment peaks at some location downstream, and recruitment at the source is not enough to sustain local fish populations there. Second case; fish larvae change dispersal by active behaviors so that the recruitment peaks near the source and local fish population is sustained. Now, the question is “among many other behaviors, can vertical positioning do this?”
Distance from larval source (km)
Taken from Steneck, Science (2006)

3. TARGET AREA Central California Mean wind stress Wind is variable
Wind is dominant
Mean wind stress
Along the coast
Stronger in summer, weaker in winter
Wind is variable
Larval dispersal in turbulence
Our target area is Central California. In this area, wind is the dominant force that drives coastal circulation processes. The mean wind is along shore year round. It is stronger in summer, and weaker in winter. Due to the earth rotation, mean offshore transport is observed at near surface. Larval dispersal occurs in turbulence generated by highly variable wind.
Mean wind
Mean offshore current at surface

4.  IDEALIZED SIMULATION Top view Side view Poleward
Periodic 
Open
Wall
Poleward
We use idealized simulations of coastal circulation processes driven by observation data. The top surface domain is 250 km by 250 km. The boundary conditions are a wall at the coast, periodic at the north and south boundaries, and open at the west boundary. The depth changes from 20 m at the coast to 500 m offshore. The bathymetry is uniform in the alongshore direction. The stochastic wind stress is applied on the top surface, and the alongshore pressure gradient is applied as an external force. These forces are taken from observation data.
Periodic
Stochastic wind stress
estimated from observation data
Alongshore pressure gradient obtained from observation data

5. SEA SURFACE TEMPERATURE
Summer
Winter
These movies show the evolution of the sea surface temperature obtained from the simulations for the summer case (left) and winter case (right). In summer, offshore transport is stronger, leading to strong upwelling at nearshore region. In winter, offshore transport is weaker, and less upwelling is observed at nearshore region.
Offshore transport: strong
Offshore transport: weak

6. MODELED LARVAE Release many (105) particles as modeled larvae
Modeled after typical rocky reef fish
Habitat: within 20 km from coast
Release: one season (90 days)
Competency window: one month (20 to 40 days)
Settlement: in habitat during competency
Passive transport horizontal
We release many particles, mimicking typical rocky reef fish larvae. The nearshore habitat is defined as waters within 20 km from the coast. Release is over one season, i.e., 90 days. The competency time window is set to 20 to 40 days. Settlement occurs when the particles are found in the nearshore habitat within their competency time window. All particles are transported passively in horizontal directions.

7. VERTICAL POSITIONING Release location Migration location
Surface
Centered at 30 m
Centered at 20 m
Centered at 40 m
Migration location
-> Surface
-> Passive transport
-> Centered at 30 m
-> Centered at 37.5 m
-> Centered at 55 m
The vertical positioning of the larvae is defined by six different scenarios. The first three scenarios release larvae near the surface. #1 stays at the surface; #2 is passively transported; and #3 shifts to 30 m. The remaining three scenarios release larvae below the depth #4 is released at 30 m and stay at 30m; #4 and #5 are released at 20 m and 40 m, and move deeper. All shifts occur after 5 days from release.
Shifts occur 5 days after release (post-flexion)

8. LARVAL DISPERSAL Summer Winter Surface -> passive
The movie shows larval dispersal in the summer (left) and winter (right). Red dots indicate settling larvae, meaning they are found in the nearshore waters during their competency, i.e., 20 to 40 days after release. As you see, stronger offshore transport is observed in summer.
Red dots: settling larvae

9. DISPERSAL KERNEL Sample dispersal kernel (from a 10-km subpopulation)
Ensemble averaged (& normalized)
Gaussian fit
Using the obtained simulation data, we constructed a dispersal kernel. The sample dispersal kernel from a 10-km subpopulation is plotted on the left panel. You can see that the dispersal kernel is not a smooth Gaussian-type function. This is because larval settlement events are episodic; i.e., the two peaks account for two large settlement pulses. If dispersal kernels are ensemble-averaged over many subpopulations, then they can be well approximated by Gaussian distribution, as shown on the right panel. Here, the vertical axis indicates probability density function instead of the number.
(south)
(north)
(south)
(north)
Non-Gaussian kernel (unless ensemble averaging) is general

10. ENSEMBLE-AVERAGED DISPERSAL KERNELS (SUMMER)
Retention
1) Surface -> surface
2) Surface -> passive
3) Surface -> 30 m
4) 30 m -> 30 m
5) 20 m -> 37.5 m
6) 40 m -> 55 m
-106 ± 61 km
-110 ± 63 km
-85 ± 67 km
-78 ± 69 km
-78 ± 66 km
-67 ± 68 km
Change in dispersal scale is insignificant
Ensemble-averaged dispersal kernels for the summer case are shown here. Each color indicates the six different previously mentioned scenarios. Gaussian fitting parameters are tabulated here. As you see, no change can be found in dispersal scale; i.e., settlers are found from 100 km north to 300 km south regardless the larval type. But, if you look at the retention, there is significant difference for surface-released larvae. A comparison between 2) passive larvae and 3) migrating larvae indicates that vertical migration can double the retention probability. But, this is not the case for non-surface released larvae. Movement between 20 m and 60 m does not make difference.
Surface-released larvae can increase retention probability by vertical migration (90%)
(south)
(north)

11. ENSEMBLE-AVERAGED DISPERSAL KERNELS (WINTER)
Retention
1) Surface -> surface
2) Surface -> passive
3) Surface -> 30 m
4) 30 m -> 30 m
5) 20 m -> 37.5 m
6) 40 m -> 55 m
-67 ± 72 km
-66 ± 71 km
-56 ± 77 km
-45 ± 76 km
-52 ± 77 km
-39 ± 83 km
Change in dispersal scale is insignificant
This is the winter case. Again, no significant change can be found in the dispersal scale. The is no significant change in retention probability, either. There is significant retention probability for all cases, which is much higher than summer case.
Change in retention probability is insignificant
(south)
(north)
High retention probability

12. SETTLEMENT RATES Summer Winter
Settlement increases with migration (72%)
No significant change in winter
No significant change for non-surface released larvae
Since the PDF is normalized so that the summation is unity, it do not account for the number of settlers. Here, settlement rates are shown for the six different scenarios for the summer and winter. These settlement rates do not account for natural mortality. No significant change is found in winter or non-surface released larvae in summer. But, significant change can be found for surface-released larvae in summer. Combined with the increase for retention probability in previous slides, surface-released larvae in summer can increase retention by 300% by doing vertical migration for this particular case.

13. CONCLUSIONS
Simulation results suggest that, in Central California, larval vertical positioning
Does not change dispersal scale (not as in Steneck’s figure)
Yet, can significantly increase retention if larvae are released near surface in summer
Dispersal kernel is not smooth Gaussian
Will create uncertainties in fishery management
Simulation results suggest that in central california vertical migration does not change

14. FUTURE PLANS Investigate the role of other behaviors
e.g., swimming toward shore, diel migration, turbulence avoidance
Investigate the role of head land
May create consistent connectivity between particular subpopulations every year
Investigate stochasticity in dispersal kernel
How behavior affects?

15. FUTURE PLANS (2)
Investigate the temperature time series of settlers -> Moose
(diel variations are not captured, though)

17. ONLY SETTLERS Summer Winter Surface -> passive
Red dots: settling larvae

18. LARVAL DISPERSAL (SIDE VIEW)
Summer
Surface -> passive
Winter
Surface -> passive
Red dots: settling larvae

19. ONLY SETTLERS (SIDE VIEW)
Summer
Surface -> passive
Winter
Surface -> passive
Red dots: settling larvae

20. SIMULATION VALIDATION: MEAN TEMPERATURE (SUMMER)
CalCOFI seasonal mean
Shows good agreement with CalCOFI seasonal mean (Line 70)

21. SIMULATION VALIDATION: MEAN TEMPERATURE (WINTER)
CalCOFI seasonal mean
Shows good agreement with CalCOFI seasonal mean (Line 70)

22. SIMULATION VALIDATION: LAGRANGIAN STATISTICS
Time scale Length scale Diffusivity
Data set
zonal/meridional zonal/meridional zonal/meridional
Simulation data
2.7/2.9 days /31 km /4.3 x107 cm2/s
Surface drifter data
(Swenson & Niiler)
2.9/3.5 days /38 km /4.5 x107 cm2/s
Shows good agreement with surface drifter data

23. CONNECTIVITY MATRIX (SUMMER)
Surface -> surface
40 m -> 55 m
Gaussian
Connectivity changes with vertical positioning

24. EXTREME CASE (SUMMER) Significant change in dispersal scale
Retention
1) Surface -> surface
2) Surface -> passive
3) Surface -> 200 m
4) 30 m -> 30 m
5) 20 m -> 37.5 m
6) 40 m -> 55 m
-106 ± 61 km
-110 ± 63 km
23 ± 106 km
-78 ± 69 km
-78 ± 66 km
-67 ± 68 km
Significant change in dispersal scale
Insignificant increase in retention probability
(south)
(north)

25. HABITAT CONNECTIVITY WILL BE A FUNCTION OF…
Spawning timing, locations & structures
Interactions with small scale turbulence
Mesoscale transport (currents, eddies, waves)
Larval behaviors
Larval development, growth rate & mortality
Complex geometry
Q: what to be included in “realistic” models?

26. LARVAL DISPERSAL & EDDY
Eddies sweep newly released larvae together into “packets” which stay coherent through much of their pelagic stage

27. SETTLEMENT IS EPISODIC
Larvae settle in infrequent pulses
Onshore Ekmann transport is not the only process