1. Flow, fish, and fishing — F 3 Understanding complex interactions of a nearshore ocean ecosystem: Southern California Bight case study

2. The model 1.The agents 2.The program 3.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 Animals Aristotle, 350 B.C. transl. by A.S.L. Farquharson

3. 1.The agents 2.The program 3.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? Agent based model of the San Diego sea urchin fishery

4. 1.The agents 2.The program 3.The results Fishers attributes Port location Boat speed (kh -1 ) NUT (minimum expected revenue) Islands go to (True or False) Nitrox Fuel # of Divers

5. 1.The agents 2.The program 3.The results Areas attributes Size Location (Lat, Long) Population Vulnerability Recovery rate Islands (Boolean) Numbers km -2

6. 1.The agents 2.The program 3.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)

7. 1.The agents 2.The program 3.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

8. 1.The agents 2.The program 3.The results Size Location (dist. from border) Population Vulnerability Recovery rate Islands (Boolean) Areas attributes

9. 1.The agents 2.The program 3.The results Size Location (dist. from border) Population Vulnerability Recovery rate Islands (Boolean) Areas attributes

10. 1.The agents 2.The program 3.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

11. 1.The agents 2.The program 3.The results Pricing attributes Fuel A quality (─) B quality ( - - )

12. 1.The agents 2.The program 3.The results Weather attributes Conditions inside Conditions outside

13. 1.The agents 2.The program 3.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 days end years

14. Simple example: 3 areas with identical attributes, 4 boats all from the same port, fishery is only five days 1 2 3

15. Day 1: Value ($) of the different areas for the different boats

16. Day 1: Profit ($) of the different areas for the different boats Dashed lines are the NUT

17. The value of different areas at the beginning of the day before fishing occurs during year 1.

18. The number of vessels days for a particular area for year 1 Number of vessel days

19. Serial depletion over a number of years

20. Managment Open access Daily quotas Cooperative fleets ITQ MPA

21. 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

22. Next steps 1.Common programming language 2.Stitching the links together 3.Some more suggestions, Ray???

23. Next steps 1.Common programming language 2.Stitching the links together