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Exploiter-Victim Relationships Host-Parasite: Host death need not occur, and often does not; birth rate of host reduced by parasite Host-Parasitoid: Host.

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Presentation on theme: "Exploiter-Victim Relationships Host-Parasite: Host death need not occur, and often does not; birth rate of host reduced by parasite Host-Parasitoid: Host."— Presentation transcript:

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

16

17 Amboseli Elephants

18 Elephants not excluded

19 Elephants Excluded

20 Baobab

21

22 Baobab, Elephant Damage

23 Functional Response Change in predator’s attack behavior as prey density increases 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 # attacked/pred/time Prey density I II III

24 Toxorhynchites

25 Toxorhynchites brevipalpus

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

27 Fraction killed per predator/time Type IType IIType 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: 1)Random search, producing encounters between prey and predators (and subsequent attacks) proportional to the product of their densities (attack rate = a’) 2)Exponential prey population growth in absence of predator, with constant growth rate, r 3)Death rate of predator is constant = q 4)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 Prey: dN/dt = rN - a’CN = 0 r-a’C = 0 C = r/a’ C N Too many predators Not enough predators

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

33 Changes in both species: C N

34 The prey curve has a hump

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

36 Why the Prey curve has a Hump 1.Resource limits for prey at high densities (fewer preds needed to keep in check) 2.But, predator is most effective at low prey densities

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

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


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