Predator/Prey with Functional Response
The Homework has the assignment to hand in.
These Questions are basically drill to build an intuitive grasp of functional
response and isoclines, so that you expect the answer you get.
- On Scenario | Functional Response, look at
Types I and II. With the preset parameter values (killrate 0.05 and handling
time 0.02), the Type I and II responses seem colinear for a little ways.
At what prey population do they appear to diverge?
- Using the same Scenario, set Type II killrate to 0.1.
- The difference between the predator/prey Scenario |
Linear Codependent and Scenario | Saturated Predator is their functional responses
(Type I vs. Type II). To simplify your comparisons, the preset parameters match
(i.e., both have killrate 0.05.) Now look at (in sequence):
Tell yourself a story about what this means. Based on your story, predict what
will happen with a Saturated Predator killrate 0.01 and 0.2. Test your theories.
- "Linear Codependent" with its default killrate 0.05.
- "Saturated Predator" with its default killrate 0.05. (How many cycles
are there on the time series?)
- "Saturated Predator" with killrate 0.1. (What happens to the
phase plot (top) trajectory shape? How many cycles on the time series?)
- Back to "Linear Codependent".
- Play the Question 2/Question 3 game again, this time varying only the
handling time. (Set parameter "predator saturation" to killrate times handling
time. See Details.) Again, what does this mean?
Does the handling time affect the number of cycles on the time series?
- Pick Scenario | Saturated Predator again, to make sure you've got the default parameters. Now try doubling and halving the prey birthrate. What happens?
- Now try doubling and halving the predator deathrate. What happens?
- The number of cycles is determined by the period, or length of each cycle. Are the
cycles of equal length in the Saturated Predator system? Which parameters affect the period? Why
would that make sense?
- The quantities Prey and Predator are population densities. Let's
say you wanted to scale these. For instance, you have data from Idaho on a
one-meter-square map and data from Wyoming on a ten-meter-square map. How do
you adjust your parameters to scale the one-meter data down two orders of
magnitude? (0.01 per (10m)2 = 0.01 per 100m2 = 1.0 per 1m2.)
- In the natural world, there are extremely few predators who depend on a
single sort of prey. What aspects of these models do you think would be relevant
in practice? Which are probably less useful?
- Take a predator/prey ecosystem you're familiar with, like cats catching mice and
baby moles in Connecticut, but include the cat's food bowl. Pick
one of the models here and describe its fitness to describe your sample
ecosystem. What ought to happen when you add more prey types? What do you think
the equations suggest about adding prey types?
Ginger Booth, revised April 2005, orig. December 1998, for