1. DARTER: Diffusion Approximation Tools for Extinction Risk Estimation
Brice semmens
Eli Holmes

2. Typical PVA: Two Parts
parameterize a model of a population based on data by finding the best fit (Max Like)
Use the best-fit parameters to project future states of the population.

3. PVA: Step One

4. PVA: Step One
Parameters: GROWTH RATE AND ERROR

5. PVA: Step Two Use best parameter fits to simulate future
Do 1000’s of times to get probs of extinction per timestep

6. % Chance of Extinction By Year

7. Why is better (part 1)?
It uses a state-space Kalman filter that allows for both process and non-process error. So what's the big deal? --Functionally it filters the data, and allows a more accurate fit for population parameters of interest.

8. Problem 1

9. FIX!
We use a state-space model to simultaneously account for process and non-process errors
Functionally it filters the data, and allows a more accurate fit for population parameters of interest

10. Problem 2
The best fit is not the only fit!

11. Problem 2
The best fit is not the only fit!