# Rabbits

Published on January 1, 2008

Author: Gabrielle

Source: authorstream.com

Rabbits, Foxes and Mathematical Modeling:  Rabbits, Foxes and Mathematical Modeling Peter Pang University Scholars Programme and Department of Mathematics, NUS SMS Workshop July 24, 2004 Mathematical Modeling of Population Dynamics :  Mathematical Modeling of Population Dynamics How does population grow? Denote the population by “x”. Suppose the population x(t) at time t changes to x + Δx in the time interval [t, t + Δt]. Then the growth rate is Slide4:  The growth rate depends on many things, such as Per capita food supply – call it “s” A minimum supply of food, say s0, is needed to sustain life Say growth rate is proportional to s – s0 Call the constant “a” the growth coefficient Slide6:  Is infinite growth realistic? Suppose population reaches saturation at x0 Say the growth coefficient is proportional to x0 – x We can interpret the x2 term as a number proportional to the average number of encounters between x individuals. Hence it measures a kind of social friction. Foxes and Rabbits:  Foxes and Rabbits Slide9:  Let’s look at the fox population Let’s assume that the fox population doesn’t get really huge so that the issue of “population saturation” can be ignored Recall that the model for unlimited growth is Now, suppose that the only food for foxes is rabbits; then s is proportional to the population of rabbits Denote rabbit population by “y” Slide10:  As for the rabbit population, let’s again assume we have unlimited growth while the rabbits are being eaten by the foxes -- we further assume that the number of rabbits eaten is proportional to the fox population The Lotka-Volterra (Predator-Prey) Equations:  The Lotka-Volterra (Predator-Prey) Equations Population of foxes – x Population of rabbits – y where c, d, f, g are constant parameters Slide13:  Let’s introduce a saturation for the rabbit population: Functional Response:  Functional Response Lotka-Volterra System (with unlimited growth for prey) The term p(y) measures the number of prey susceptible to each predator as the prey population changes -- this is known as the functional response p(y) = gy says that the number of prey for each predator is a constant proportion of the prey population What if the prey population really shoots up? Slide15:  Michaelis-Menten or Holling type II functional response Slide16:  Sigmoidal functional response Slide17:  Holling type III functional response Slide18:  Holling type IV or Monod-Haldane type functional response Ratio-Dependent Theory:  Ratio-Dependent Theory Recall that functional response measures the number of prey susceptible to each predator as the prey population changes. We have seen various types of functional response functions of the type p(y). The ratio-dependent theory asserts that functional response should be dependent of the ratio of prey to predator (especially if the predator needs to search for the prey), i.e., instead of being just a function of y, p should be a function of y/x : Spatial Dependence:  Spatial Dependence What can happen to a spatially inhomogeneous population? Diffusion Cross Diffusion Partial differential equations Two Predators and One Prey:  Two Predators and One Prey Defense switching Cross diffusion

04. 01. 2008
0 views

13. 04. 2008
0 views

30. 03. 2008
0 views

27. 03. 2008
0 views

18. 03. 2008
0 views

14. 03. 2008
0 views

12. 03. 2008
0 views

11. 03. 2008
0 views

04. 03. 2008
0 views

28. 02. 2008
0 views

26. 02. 2008
0 views

09. 10. 2007
0 views

29. 11. 2007
0 views

29. 11. 2007
0 views

02. 11. 2007
0 views

05. 11. 2007
0 views

05. 11. 2007
0 views

05. 11. 2007
0 views

12. 11. 2007
0 views

15. 11. 2007
0 views

15. 11. 2007
0 views

16. 11. 2007
0 views

27. 12. 2007
0 views

29. 12. 2007
0 views

28. 11. 2007
0 views

03. 01. 2008
0 views

13. 11. 2007
0 views

05. 11. 2007
0 views

03. 10. 2007
0 views

05. 12. 2007
0 views

31. 12. 2007
0 views

19. 12. 2007
0 views

23. 12. 2007
0 views

04. 01. 2008
0 views

11. 10. 2007
0 views

01. 12. 2007
0 views

29. 10. 2007
0 views

07. 01. 2008
0 views

23. 11. 2007
0 views

05. 11. 2007
0 views

18. 12. 2007
0 views

20. 11. 2007
0 views

15. 11. 2007
0 views

28. 11. 2007
0 views

19. 11. 2007
0 views

18. 12. 2007
0 views

05. 01. 2008
0 views

19. 11. 2007
0 views