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2008 REU

2008 REU. ODE and Population Models. Intro. Often know how populations change over time (e.g. birth rates, predation, etc.), as opposed to knowing a ‘population function’ Differential Equations! Knowing how population evolves over time w/ initial population  population function.

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2008 REU

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  1. 2008 REU ODE and Population Models

  2. Intro • Often know how populations change over time (e.g. birth rates, predation, etc.), as opposed to knowing a ‘population function’ Differential Equations! • Knowing how population evolves over time w/ initial population  population function

  3. A: x(t) itself! more bunnies  more baby bunnies • Example – Hypothetical rabbit colony lives in a field, no predators. Let x(t) be population at time t; Want to write equation for dx/dt Q: What is the biggest factor that affects dx/dt?

  4. 1st Model—exponential, MalthusianSolution: x(t)=x(0)exp(at)

  5. Critique • Unbounded growth • Non integer number of rabbits • Unbounded growth even w/ 1 rabbit! Let’s fix the unbounded growth issue dx/dt = ????

  6. Logistic Model • dx/dt = ax(1-x/K) K-carrying capacity we can change variables (time) to get dx/dt = x(1-x/K) • Can actually solve this DE Example: dx/dt = x(1-x/7)

  7. Solutions: • Critique: • Still non-integer rabbits • Still get rabbits with x(0)=.02

  8. Fixed Points (equilibria) • In Previous example: x=0 and x=7 are fixed points • Fixed Point: dx/dt = 0 (so it’s fixed!) • Stability: stable – near solutions tend to fixed point unstable = not stable

  9. Stability • Note: near x=7 d/dx ( du/dt) <0 (stable)

  10. Stability • Note: near x=0 d/dx ( du/dt) > 0 (unstable)

  11. Taylor series at x* • dx/dt=f(x) (no dependence on t) • dx/dt = f(x)= c0+c1(x-x*)+c2(x-x*)^2+ …. (c0 = 0) If c1≠0, we can tell stability.

  12. Moral: • If dx/dt = f(x) and f(x*)=0 1) d/dx( f(x)) <0 at x* then x* is stable. 2) d/dx( f(x) ) >0 at x* then x* is unstable.

  13. x’ versus x • For first order autonomous equations, plotting x’ versus x encapsulates all this info x’ positive (unstable) x’ negative (stable)

  14. Reality check • Find and classify all equilibria of dx/dt = sin (x(t)) • Firefly example (tomorrow)

  15. Rabbit vs. Deer http://www.dcnr.state.pa.us/polycomm/pressrel/presqueislesp1100.htm

  16. Let x(t) rabbits and y(t) deer compete for the same food source. dx/dt = dy/dt = Ax(1-x/K) -Cxy By(1-y/W) -Dxy Or…. (after changes of coordinates…) dx/dt = x(1-x-ay) dy/dt = y(b-by-cx)

  17. Analysis of one case dx/dt = x(1-x-2y) dy/dt = y(2-2y-5x) Equlibria/Fixed Points: (0,0) , (0,1), (1,0), (1/4,3/8) Q: How do we know if these are stable or unstable? A: Linear approximation (derivative)

  18. Linear Systems • dx/dt= Ax (given by matrix mult) • Fixed Point(s)?

  19. What’s an eigenvalue again? • Ax = λx (λ,x) are eigenvalue eigenvector pair • Who cares? Think about: x(t) = exp (λt)x (Handout/Maple)

  20. Other Tools • Trapping regions • Poincare Bendixson • Nullclines • Series solutions ,etc. • Invariant Sets • Bifurcations

  21. Suppose we have 2 species; one predator y(t) (e.g. wolf) and one its prey x(t) (e.g. hare)

  22. Actual Data

  23. Model • Want a DE to describe this situation • dx/dt= ax-bxy = x(a-by) dy/dt=-cy+dxy = y(-c+dx) • Let’s look at: dx/dt= x(1-y) dy/dt=y(-1+x)

  24. Called Lotka-Volterra Equation, Lotka & Volterra independently studied this post WW I. • Fixed points: (0,0), (c/d,a/b) (in example (1,1)).

  25. Phase portrait y (1,1) x

  26. A typical portrait: a ln y – b y + c lnx – dx=C

  27. Solution vs time

  28. Critiques • Nicely captures periodic nature of data • Orbits are all bounded, so we do not need a logistic term to bound x. • Periodic cycles not seen in nature

  29. Previte’s Population Projects • 3-species chains - 2000 REU • 3 Competing Species 2002/3 REU • 4-species chains - 2004/5 REUs • Adding a scavenger 2005/7 REUs • (other interactions possible!)

  30. 3-species model (REU 2000) • 3 species food chain! • x = worms; y= robins; z= eagles dx/dt = ax-bxy =x(a-by)dy/dt= -cy+dxy-eyz =y(-c+dx-ez)dz/dt= -fz+gyz =z(-f+gy)

  31. Critical analysis of 3-species chain • ag > bf → unbounded orbits • ag < bf → species z goes extinct • ag = bf → periodicity

  32. ag ≠ bf ag=bf

  33. 2000 REU and paper

  34. Tools used in analysis • Linearization • Trapping regions • Invariant sets • Liapunov functions (“energy” functions)

  35. One open conjecture • ag>bf y tends to a limit as time increases all numerical evidence shows this, but no analytic proof.

  36. 4-species model dw/dt = aw-bxw =w(a-bx)dx/dt= -cx+dwx-exy =x(-c+dw-ey)dy/dt= -fy+gxy - hyz =y(-f+gx-hz) dz/dt= -iz+jyz =z(-i+jy)

  37. 2004/5 REU did analysis • Orbits bounded again as in n=2 • Quasi periodicity (next slide) • ag<bf gives death to top 2 • ag=bf gives death to top species • ag>bf gives quasi-periodicity

  38. Quasi-periodicity

  39. Previte’s doughnut conjecture (ag>bf)

  40. This is wide open • Project never finished • Proof seems too hard, may involve deep topics such as KAM theory, Hamiltonian systems

  41. Simple Scavenger Model lynx beetle hare

  42. Semi-Simple scavenger– Ben Nolting 2005 Know (x,y) -> (c, 1-bc) use this to see fc+gc+h=e every solution is periodic fc+gc+h<eimplies z goes extinct fc+gc+h>e implies z to a periodic on the cylinder

  43. Ben Nolting and his poster in San Antonio, TX

  44. Scavenger Model with feedback (Malorie Winters & James Greene 2006/7)

  45. crayfish Scavenger of trout carcasses Predator of mayfly nymph Biological Example (crowding prey) Rainbow Trout (predator) Mayfly nymph (Prey) Crayfish are scavenger & predator

  46. Analysis (Malorie Winters) • Regions of periodic behavior and Hopf bifurcations and stable coexistence. Regions with multi stability and dependence on initial conditions

  47. Malorie Winters, and in New Orleans, LA

  48. REU 2007 James Greene finds a model that exhibits chaos

  49. 2007 scavenger system • dx/dt=x(1-bx-y-z) b, c, e, f, g, β > 0 • dy/dt=y(-c+x) • dz/dt=z(-e+fx+gy-βz)

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