1. How many possums and where? The National Possum Model James Shepherd & Mandy Barron

2. How many possums in NZ? (A = 30.3 million)

3. How many possums? Who cares? It’s how possums distributed in space and how their numbers change through time that is important

4. Possum control decisions When? (timing and frequency) Where? (site prioritisation) Need to know current (and predicted) state of possum populations across your sites to make these decisions

5. LCR possum-TB model LCR currently has a useful individual- based possum model that runs at local operational scales Also models bovine tuberculosis (TB) within possum population Can assess effect of management regimes on possums and TB by simulating possum control Possum abundance in model is determined by habitat carrying capacity

6. Bare Ground Water Pasture Gorse Narrow-leaved Scrub Regenerating Forest Indigenous Forest Exotic Forest Unspecified Woody EcoSat Basic Landcover

7. Indigenous Forest Composition

8. “Carrying Capacity” = potential possum density (in absence of control)

9. Possum TB model – patchy habitat

10. Possum TB Model (5x5 km) Bare Ground Water Pasture Narrow-leaved Scrub Regenerating Forest Indigenous Forest Exotic Forest Unspecified Woody

11. Scaling up to the national level Context is important National Possum Model (NPM), national coverage – high spatial detail –all of the information we would use in a local simulation but NZ-wide! –millions of individuals! Not just a static map – dynamic and interactive model –web input & output –online delivery of present and future population projections

12. NPM − Why do we want to do this? LCR is a national institute, efficient for us to provide a single national predictive tool to land managers – demonstrate our research Because we can… spatially-detailed vegetation, ecological, climate and soil layers all exist at national scale AND we now have the computing power

13. NPM − Why do we want to do this? Would provide a central integration point for possum control information –essential for accurate predictions Integrating the datasets & technology required for NPM would provide a framework for other pest species such as rats & goats

14. NPM − Why do we want to do this? Web delivery would provide easy user access to present and future pest densities and disease prevalence information Potential for the public to see an overview showing control effort and impact (compared with “no control” scenario)

15. NPM − How would we do this? Re-write possum-TB model code, processing distributed amongst a 100 CPU cluster Integrate and adapt national layers for vegetation to provide base data to assign carrying capacity –LCDB 1 & 2 (3) –Kyoto forestry maps 1990 & 2008 (2012) –EcoSat BLC & indigenous forest classes

16. NPM − How would we do this? Streamline model input for users to integrate their own control information (area, date and RTC) Continue underpinning ecological research –Relationship between land cover & pest density –Improve model parameters such as home range distribution, dispersal, probability of disease transmission

17. NPM − How would we do this? Provide user feedback to the underlying science when model predictions differ from reality –Focus future science effort Photo by Paul Horton

18. NPM − Results / Output No Control

19. NPM − Results / Output post AHB & DOC control in 2008/09

20. NPM – Web demonstration

31. Discussion End-user requirements, ideas –typical control scenarios –density / RTC thresholds Potential problems, data sensitivities Cost – free? Photo by Morgan Coleman