1 / 18

Modeling Presence/Absence Data

Modeling Presence/Absence Data. Acknowledgements to WyomingFishing.net (electro-fishing pics ) and Michael Houts (Wolf data and article). Counting Fish. How are fish numbers calculated?

jenny
Download Presentation

Modeling Presence/Absence Data

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Modeling Presence/Absence Data Acknowledgements to WyomingFishing.net (electro-fishing pics) and Michael Houts (Wolf data and article)

  2. Counting Fish • How are fish numbers calculated? • “There are approximately 3200 trout per mile that are greater than 6” on the Miracle Mile…66% are Browns, 29% are Rainbows and 5% are Snake River Cutts • Where does this information come from? • Lots of ways to count fish and do fish surveys…will discuss a bit about electrofishing

  3. The Miracle Mile

  4. Background – Electrofishing • Electrofishing • Portable generator • DC current from generator is at ??? volts to immobilize fish • Probes are electrodes which provide positive end of current • Nets are called “dip nets” • Back-up samplers catch missed fish • Fish placed in a flooded net

  5. How Much Voltage to Use?? • Determining correct voltage is important…too little voltage will not allow sufficient capture…too much…well, we know what that means! • Voltage studies involve setting up tanks with similar water chemistry to stream of interest…place fish in tank, provide a voltage amount, observe if fish immobilized • electricfish.csv contains such a dataset

  6. Need “Legal” Estimates

  7. “Legal” continued…

  8. Using R

  9. Plotting Using ‘Lattice’ R Code:

  10. Predicted Probabilities

  11. Small change in prob Big change in prob

  12. Resource Selection • Understanding habitat selection by animals, plants, and aquatic species is an important problem faced by ecologists and wildlife biologists worldwide • If we know what sort of habitat critters select for, we can better manage these species • Will consider a data set, wolves_geo.csv, which reports wolf occurrence in two years following wolf re-introduction in the Greater Yellowstone Area

  13. Data Description • RD_DENSITY is a measure of, well, road density • WOLVES_99 = 2 means the data came after 1999 • MAJOR_LC = codes for major land cover types (descriptions in landcover.txt) • Paper: Houts03.pdf

  14. Project Fit the logistic regression model to the 1999 data set and create a column of predicted “probabilities” of wolf occurrence. Are the “predicted probabilities” really “probabilities”? Can we use this model to predict likely wolf occurrence across the five state region? Why/why not? Can you think of a better ‘design’ for building the initial model?

More Related