1. Modelling salmon and habitat

2. What is a model A simplified abstraction of a more complex object A model airplane - has some of the characteristics - Boeing used to build physical models of airplanes and wings Now they build computer models An architects model

3. Why models for salmon recovery We may have several options for habitat –Improve spawning area –Improve rearing area –Improve estuary The effectiveness will depend on where the limits are for the stock in question

4. Need an accounting system To understand how changing habitat at one life history stage affect total returns

5. Modelling terms State variables parameters forcing functions rules of change the state variables in the future depend upon the current state, the parameters (constants), any external perturbations (the forcing functions), and the rules of change

6. State variables The complete description of the current state of the system -- complete enough that you can “rebuild” the system with this amount of information examples – the number of fish in a river, the amount of large woody debris in a section of stream, the maximum winter flow ….

7. Parameters Do not change over time and are the constants that describe the rates or limits Examples – eggs per female at each age, fry to smolt survival when rearing habitat is not limiting, concentration of fine sediments above which egg survival starts to drop

8. Forcing functions Natural or anthropogenic factors that affect the state weather impacts on survival or reproduction harvesting These are “external” to the model -- that is we don’t attempt to describe the dynamics of these factors

9. Rules of change The equations that describe how the state variables change over time in relation to the current values of the state, the parameters, the the forcing functions. S t+1 = f(S t,p,u t )

10. Components of rules of change Logical relationships –statements that are true by definition –Fry = eggs * egg to fry survival –also known as tautologies Functional relationships –specify the relationship between a rate and a state variable or something related to a state variable (egg survival as a function of fine sediments)

11. Deterministic or stochastic Do we allow for random events, or not

12. Basic life stage model Survival from one stage to the next depends on Carrying capacity for that stage “productivity” that is survival when capacity is not limiting

13. Habitat impacts Productivity and capacity For example egg to fry survival depends on fine sediments

14. Spawners to Egg capacity depends on gravel area productivity depends on age specific fecundity and age distribution of spawners

15. Eggs to Fry capacity is unlimited productivity depends upon % fines

16. Fry to Smolt capacity determined by rearing area productivity determined by % impervious

17. This approach is used In the EDT approach of Mobrand et al In work currently underway with Muckelshoot Tribe

18. The role of models in this seminar To serve as a focus for discussion for individual speakers To provide key questions for speakers To determine what an analytic framework should do for planners To move towards a PRISM salmon model