Modelling salmon and habitat

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. • St+1 = f(St,p,ut)

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