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Exploiter-Victim Relationships

Exploiter-Victim Relationships. Host-Parasite: Host death need not occur, and often does not; birth rate of host reduced by parasite Host-Parasitoid: Host death always occurs Predator-Prey: Death rate of prey increased by predators Herbivore-Plant: May resemble predation or parasitism.

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Exploiter-Victim Relationships

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  1. Exploiter-Victim Relationships Host-Parasite: Host death need not occur, and often does not; birth rate of host reduced by parasite Host-Parasitoid: Host death always occurs Predator-Prey: Death rate of prey increased by predators Herbivore-Plant: May resemble predation or parasitism

  2. Parasitoids

  3. Weevils and wasps

  4. Lynx and Snowshoe Hare

  5. Orange Mites, simple universe

  6. Orange Mites, increased patchiness

  7. Orange Mites, complex habitat

  8. Field Studies: Dingoes and kangaroos

  9. Dingoes and Boars

  10. Lamprey and Lake Trout

  11. Fox and Rabbit

  12. Plant-Herbivore

  13. Herbivore-- positive effect?

  14. N-fertilization effects

  15. N-fertilization effects

  16. Big Herbivores

  17. Amboseli Elephants

  18. Elephants not excluded

  19. Elephants Excluded

  20. Baobab

  21. Baobab

  22. Baobab, Elephant Damage

  23. Functional Response Basic forms to consider: Type I: Linear increase in # attacked with increasing # prey (insatiable predator) Type II: Gradual levelling off As predators become satiated Type III: Predators satiable as in Type II, but hunt inefficiently at low prey densities I Change in predator’s attack behavior as prey density increases # attacked/pred/time II III Prey density

  24. Toxorhynchites

  25. Toxorhynchites brevipalpus

  26. Toxorhynchites Functional Response, sympatric & allopatric prey: IL (allopatric) NC (sympatric)

  27. Fraction killed per predator/time Type I Type II Type III Prey Density Type II and III: satiable predators become less effective at controlling prey as prey become more abundant.

  28. Lotka-Volterra Predator-Prey Model: Assume: Random search, producing encounters between prey and predators (and subsequent attacks) proportional to the product of their densities (attack rate = a’) Exponential prey population growth in absence of predator, with constant growth rate, r Death rate of predator is constant = q Birth rate of predator proportional to #prey consumed

  29. Prey growth equation Prey: Without predator, dN/dt=rN If predator searches with attack rate a’, and there are C Predators, then deaths due to predation = a’CN dN/dt = rN - a’CN

  30. Predator Growth Equation dC/dt = (birth rate - death rate)C Death rate assumed constant = q Birth rate: #prey consumed x conversion constant, f = (#prey consumed)x f # prey consumed = a’CN (see prey equation) births = a’CNf birth rate = a’Nf dC/dt = (a’Nf - q)C

  31. Equilibrium Conditions, Prey Too many predators Prey: dN/dt = rN - a’CN = 0 r-a’C = 0 C = r/a’ C = r/a’ C Not enough predators N

  32. Equilibrium conditions, predators dC/dt = (a’Nf - q)C = 0 a’Nf - q = 0 N = q/a’f More than enough prey Not enough prey C N = q/a’f N

  33. Changes in both species: C N

  34. The prey curve has a hump

  35. Humped Prey curves Change in phytoplankton density at different combinations of Rotifer density and phytoplankton density Rotifer density Phytoplankton density

  36. Why the Prey curve has a Hump Resource limits for prey at high densities (fewer preds needed to keep in check) But, predator is most effective at low prey densities

  37. Effects of a humped prey curve: C N Damped oscillation (stable point) Neutral stability Increasing oscillation (unstable)

  38. Effects of a humped prey curve: C N time Damped oscillation (stable point) Neutral stability Increasing oscillation (unstable)

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