Flow, fish, and fishing — F 3 Understanding complex interactions of a nearshore ocean ecosystem: Southern California Bight case study
Dec 22, 2015
Flow, fish, and fishing — F3
Understanding complex interactions of a nearshore ocean ecosystem: Southern California
Bight case study
The model
1. The agents2. The program3. The results
But how is it that thought (viz. sense, imagination, and thought proper) is sometimes followed by action, sometimes not; sometimes by movement, sometimes not?
On the Motion of AnimalsAristotle, 350 B.C.
transl. by A.S.L. Farquharson
1. The agents2. The program3. The results
How do fishers decide where to fish based on their attributes and the attributes of the other agents they are working in concert with?
-117.35 -117.30 -117.25 -117.20 -117.15 -117.10 -117.05
32
.55
32
.60
32
.65
32
.70
32
.75
32
.80
32
.85
Agent based model of the San Diego sea urchin fishery
1. The agents2. The program3. The results
Fishers attributes
•Port location•Boat speed (kh-1)•NUT (minimum expected revenue)•Islands go to (True or False)•Nitrox•Fuel•# of Divers
1. The agents2. The program3. The results
Areas attributes
•Size•Location (Lat, Long)•Population•Vulnerability•Recovery rate•Islands (Boolean) -117.35 -117.25 -117.15 -117.05
32.5
532
.60
32.6
532
.70
32.7
532
.80
32.8
5
01e+052e+053e+054e+055e+05
Numbers km-2
1. The agents2. The program3. The results
Areas
•Initial age structure is at equilibrium (assume only legal urchin are observed)
•Course scale
•Length-at-age model•Natural mortality = 0.2•Fecundity •Selectivity is knife-edge•Maturity ogive•Carrying capacity proportional to initial population•Recruitment (BV parameterized for steepness)
•Movement as function of dist and dist/habitat
•Size•Location (Lat, Long)•Population•Vulnerability•Recovery rate•Islands (Boolean)
1. The agents2. The program3. The results
•Size•Location (dist. from border)•Population•Vulnerability•Recovery rate•Islands (Boolean)
Movement
•Habitat – urchins may remain certain types of habitat•Area size – larger areas will have a smaller fraction of urchins moving; however, the relationship of perimeter to area makes a difference.•Urchin size – large urchins move further in search of food and they move more quickly Dumont et al. 2004
Area attributes
1. The agents2. The program3. The results
•Size•Location (dist. from border)•Population•Vulnerability•Recovery rate•Islands (Boolean)
Areas attributes
1. The agents2. The program3. The results
•Size•Location (dist. from border)•Population•Vulnerability•Recovery rate•Islands (Boolean)
-119.0 -118.5 -118.0 -117.5 -117.0
32.5
33.0
33.5
34.0
34.5
Areas attributes
1. The agents2. The program3. The results
•Size•Location (dist. from border)•Population•Vulnerability•Recovery rate•Habitat type (kelp)
Areas attributes
3
1
2
Kelp beds
Grazing fronts
Urchin barrens
1. The agents2. The program3. The results
Pricing attributes
•Fuel•A quality (─) •B quality ( - - )
Pri
ce p
er
lb0
5
10
15
20
25
30
Pri
ce p
er
lb
0
5
10
15
20
25
30
Jan March May July Sept Nov
1. The agents2. The program3. The results
Weather attributes
•Conditions inside•Conditions outside
-119.0 -118.5 -118.0 -117.5 -117.0
32
.53
3.0
33
.53
4.0
34
.5
1. The agents2. The program3. The results
Algorithm
Fishermen gets up and checks the weather
Loop years Update the population dynamics
Loop days Loop vessel and areas
Determine the best area for that boat end areas and vessels
Loop over vessels• Vessel determine most profitable place • Fish if most profitable place greater than the NUT• Reduce urchin population
end vessels end daysend years
Simple example: 3 areas with identical attributes, 4 boats all from the same port,fishery is only five days
1
2
3
Day 1: Value ($) of the different areas for the different boats
1 2 3
Boat 1
Area
Val
ue (
$)
0
200
400
600
800
1 2 3
Boat 2
Area
Val
ue (
$)
0
200
400
600
800
1 2 3
Boat 3
Area
Val
ue (
$)
0
200
400
600
800
1 2 3
Boat 4
Area
Val
ue (
$)
0
200
400
600
800
Day 1: Profit ($) of the different areas for the different boatsDashed lines are the NUT
1 2 3
Boat 1
Area
Pro
fit (
$)
0
200
400
600
800
1 2 3
Boat 2
Area
Pro
fit (
$)
0
200
400
600
800
1 2 3
Boat 3
Area
Pro
fit (
$)
0
200
400
600
800
1 2 3
Boat 4
Area
Pro
fit (
$)
0
200
400
600
800
The value of different areas at the beginning of the daybefore fishing occurs during year 1.
Boat # 1
days
Val
ue (
$) o
f ar
ea
400
500
600
700
800
900
1 2 3 4 5
area 1area 2area 3
Boat # 2
days
Val
ue (
$) o
f ar
ea
400
500
600
700
800
900
1 2 3 4 5
area 1area 2area 3
Boat # 3
days
Val
ue (
$) o
f ar
ea
400
500
600
700
800
900
1 2 3 4 5
area 1area 2area 3
Boat # 4
days
Val
ue (
$) o
f ar
ea
400
500
600
700
800
900
1 2 3 4 5
area 1area 2area 3
The number of vessels days for a particular area for year 1
Number of vessel days
Serial depletion over a number of years
Managment
•Open access•Daily quotas•Cooperative fleets•ITQ•MPA
Moving beyond the simple examples
• Vessels sharing information
• Recruitment– Habitat type– Current population size– Age structure of the population
• Urchin movement– Urchin size– Habitat type
Next steps
1. Common programming language2. Stitching the links together3. Some more suggestions, Ray???
Next steps
1. Common programming language2. Stitching the links together