flow, fish, and fishing — f 3 understanding complex interactions of a nearshore ocean ecosystem:...

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