1. Markov Chain Update

2. GIS Coastline

3. Rasterize Coastline in Matlab

4. Habitat = Spiny Lobster

5. Split up Patches

6. What we have: A rasterized coastline based on a real GIS map Patches that are based on the suitable habitat for Spiny Lobster geometric/flow structures (e.g. the north side of an island will be a different patch to the south side)

7. Now – setup a Markov particle tracking simulation with a spatially explicit flow field (provided by Michael, from Sea Surface Height measurements)…

8. Flow Field from SSH

10. Velocity m/s

11. … and v component Velocity m/s

12. Lots of fiddling to get Markov script to ‘sample’ u and v velocities from the flow field

14. New method for starting particles … Randomly seeded within each patch

15. + when they hit land they bounce better… to their last “ocean” positon

16. For example Michael kindly got two flow fields – Jan 99 and June 99. I used our new Markov technique to generate connectivity matrixes for these two ocean states. PLD = 20days, competency after 2 days. Spiny Lobster habitat …. Unreal, but worth a look.

17. The i and j patches

18. Total Count Connectivity Matrixes JANUARY 1999 JUNE 1999 j j i i

19. Area Normalized Connectivity Matrixes JANUARY 1999 JUNE 1999

20. So getting there, we now need better flow fields and biological parameters to proceed. Game over