Predator-Prey assignment.

• You probably will want to work in groups of two to four for this assignment ("two to four for"... cool!). Extra minds will come in handy (but not more than four). You can hand in a single paper if you want. Make sure you all work on the assignment (why let some lazy slob hang on your work?)
• Download the predator-prey simulation from my website. This model couples the predator-prey relationships so that the population density for each is completely dependent on the other. Thus, there is no K value for this simulation. Make your way through the entire simulation and answer all the questions. I
• Adjust the spreadsheet-based population growth model to simulate a predator-prey scenario that will take into account K, r, and predator/prey efficiencies. The original spreadsheet model is here and you can review the use of Excel here, if need be. If you lost your Excel logistic model from the lab, you can save your a lot of work by downloading it here.
• Use the spreadsheet model as a template for your work. You will, of course, need two columns of equations now. One for the predator, and the other for the prey. The columns will have to refer to themselves and to the other species so that they will interact.
• Use the simultaneous equations from the competition exercise as a start. For the prey, your predator effects could be either inside or outside the parentheses. You will need to take into account K, r, and N for each species.

• Your model should have a coefficient to describe the ability of the prey to escape the predator. Another coefficient is required to describe predator efficiency.
• Run your model for 100 generations and make a graph of population size (predator and prey on same graph) vs. generations.
• Find converging, diverging, and extinction examples for your model. Don't be surprised if your model is "twitchy" and it's difficult to get a stable solution. This is normal for predator-prey models. Just keep at it and make small changes to r and the predator/prey efficiency coefficients. If your model is reasonable, you'll probably have better luck playing with the predator coefficients first (don't mess with both at the same time).
• How would you change your model to show a Type III functional response on the part of the predator (Functional Response is here). Hint: You need another variable that acts like K, but in the "other direction" for one of the participants in the simulation. Make the change to your spreadsheet and do several runs to discover the effect of a functional response on predator/prey relationships. Discuss what you found out.
• Discuss why your first simulation is a Type I functional response.
• Return to my predator-prey simulation (here). Now explore the effects of environmental instability on the model (random effects for the predator and prey).
  • Choose coefficients for the predator and prey that provide a stable distribution for both (you can use the default values).
  • Change either the prey or predator stochastic effects to determine which population is affected more by random environmental changes.
  • Choose predator/prey  stochastic effects that result in an intermediate level of success for both the predator and prey populations They can't both be at 50% since the predator populations depend completely on the prey. If the prey go extinct, so will the predators. NOTE: you may need to adjust parameters again for the following situations.
  • Now model a situation where both the predator and prey are r-selected. Follow with coefficients where both are K-selected. What real predator-prey situations fir these two parameters? Discuss what you have discovered and explain why the model makes sense.
  • Next, model situations where the predator is K-selected and the prey are r-selected. Then switch (r-selected predators, K-selected prey). What real predator-prey situations fir these two parameters? Discuss what you have discovered and explain why the model makes sense.