1. Predator/Prey

2. Two big themes: 1.Predators can limit prey populations. This keeps populations below K.

3. 2.Predator and prey populations increase and decrease in regular cycles. K= Carrying Capacity The maximum population size an environment can support

6. A verbal model of predator-prey cycles: 1.Predators eat prey and reduce their numbers 2.Predators go hungry and decline in number 3.With fewer predators, prey survive better and increase 4.Increasing prey populations allow predators to increase And repeat…

7. Why don’t predators increase at the same time as the prey?

8. The Lotka-Volterra Model: Assumptions 1.Prey grow exponentially in the absence of predators. 2.Predation is directly proportional to the product of prey and predator abundances (random encounters). 3.Predator populations grow based on the number of prey. Death rates are independent of prey abundance.

11. Predator-prey cycles can be unstable –efficient predators can drive prey to extinction –if the population moves away from the equilibrium, there is no force pulling the populations back to equilibrium –eventually random oscillations will drive one or both species to extinction

12. Factors promoting stability in predator-prey relationships 1.Inefficient predators (prey escaping) –less efficient predators (lower c) allow more prey to survive –more living prey support more predators 2.Outside factors limit populations –higher d for predators –lower r for prey

13. 3.Alternative food sources for the predator –less pressure on prey populations 4.Refuges from predation at low prey densities –prevents prey populations from falling too low 5.Rapid numeric response of predators to changes in prey population

14. Huffaker’s experiment on predator-prey coexistence 2 mite species, predator and prey

15. Initial experiments – predators drove prey extinct then went extinct themselves Adding barriers to dispersal allowed predators and prey to coexist.

16. Refuges from predation allow predator and prey to coexist.

17. Density of prey population Per capita population growth rate K roro Population growth curve for logistic population growth Prey population outbreaks

18. Density of prey population Per capita death rate K Type III functional response curve for predators

19. Multiple stable states are possible.

20. Below A – birth rate > death rate; population increases A

21. Point A – stable equilibrium; population increases below A and decreases above A A

22. Between A & B – predators reduce population back to A A B

23. Unstable equilibrium – equilibrium point from which a population will move to a new, different equilibrium if disturbed

24. Point B – unstable equilibrium; below B, predation reduces population to A; above B, predators are less efficient, so population grows to C B

25. Between B & C – predators are less efficient, prey increase up to C B

26. Point C – stable equilibrium B

27. Predator-prey systems can have multiple stable states Reducing the number of predators can lead to an outbreak of prey

28. Growth rate Death rate