1. Oct. 6, 20101 Lecture 9 Population Ecology

2. Oct. 6, 20102 Today’s topics What is population ecology? Population change and regulation – Density independence – Density dependence Life history traits Alaska example – Predator control

3. Oct. 6, 20103 Population- groups of organisms of the same species, present at the same place and time Population ecologists are often concerned with population dynamics: the changes that occur over time and what causes those changes.

4. Oct. 6, 20104 Population ecology questions… What is the the size of the population? – Census – try to count every individual – Estimate – survey a portion of the population and extrapolate.

5. Oct. 6, 20105 Caribou census – aerial photographs

6. Oct. 6, 20106 Moose estimate – aerial surveys

7. Oct. 6, 20107 Deer estimate - DNA

8. Oct. 6, 20108 Spotlight counts

9. Oct. 6, 20109 Population ecology questions… Is the population increasing or decreasing? – Birth rates – individuals added per unit time – Death rates – individuals deleted per unit time – Immigration rates – individual moving in per unit time – Emigration rates – individuals moving out per unit time

10. Oct. 6, 201010 Not all individual are identical For instance, birth rates, death rates, and movement rates depend on age, sex, and many other characteristics of an individual and the environment.

11. Oct. 6, 201011 Senescence – decrease in fecundity and increase in mortality rate resulting from deterioration in physiological function with age. Age Offspring per individual female

12. Oct. 6, 201012 Life tables – summary by age of survivorship of an individual in a population (simple version) Need to know how many are dying in each age interval. For example: Age interval, years, xNumber dying, dx 0-110 1-26 2-32 3-41

13. Oct. 6, 201013 From there, we can compute number surviving (nx) and cumulative survival rate from birth until age x (lx) Age interval, years, x Number dying, dx nxlx 0-110201.0 1-26140.7 2-32120.6 3-42100.5

14. Oct. 6, 201014 Survivorship Curves Age interval, years, x Number dying, dx nxlx 0-110201.0 1-26140.7 2-32120.6 3-42100.5 If we know this, we can graphically illustrate the pattern of mortality across different age groups

15. Oct. 6, 201015 Hypothetical survivorship curves Most mammals are type I or II. With regards to “r” and “K” selected species, which one is type I?

16. Oct. 6, 201016 More complex life tables Fecundity (mx) = number of offspring produced by an average female of age x during that age period Survival rate (sx) = survival rate at age x Mortality rate (qx) = mortality rate at age x

17. Oct. 6, 201017 If we know change over time, then we can compute λ (lamda) λ = population growth rate from one point in time (t) to some future time (t + 1) For example, if there is 100 individuals in the population one year ago and there is 110 now, then.. N(t+1) = λN(t) 110 = λ100 λ = 1.1 λ sometimes called finite rate of population increase

18. Oct. 6, 201018 Assuming λ is constant over time How much will the population grow in 10 years? N t = λ t N 0 Nt = 1.1 10 *100 Nt = ? Important note = this equation assumes unimpeded growth (no density dependence factors operating on population)

19. Oct. 6, 201019 Populations increase exponentially rather than arithmetically

20. Oct. 6, 201020 Density Dependence It is impossible for an population to continue to grow indefinitely at a constant rate. Growth will slow as limiting factors exert influence – Food supply – Shelter – Predators – Competitors – Parasites – Disease The influence often increases as the size and density of the population increases

21. Oct. 6, 201021 With density dependence As density increases, birth rates decrease, death rates increase, and/or emigration increases The logistic curve represents population change over time in a density dependent system. “K” plays a key role the logistic curve model.

22. Oct. 6, 201022 Logistic curve

23. Oct. 6, 201023 Logistic Equation dN/dt = Population growth rate K = carrying capacity of the population r = growth rate per individual or intrinsic rate of natural increase “r” can be calculated as individual birth rate minus individual death rate

24. Oct. 6, 201024 Logistic Equation The term in parenthesis is a density dependent term that ranges from 0 to 1. As N approaches K, then the density dependent term approaches 0. As the density dependent term approaches 0, the growth rate slows.

25. Oct. 6, 201025 Logistic Equation Simply, as the size of a mammal population approaches the maximum number that the habitat can support, the growth rate of the population slows..

26. Oct. 6, 201026 Lets try it. (hypothetically) “K” for moose in the Tanana Flats (just south of Fairbanks) is 2,000 individuals. What is the growth rate if the actual population is 500? What is the growth rate if the population is 1,900? How about 2,500? Let “r” = 0.2

27. Oct. 6, 201027

28. Oct. 6, 201028 Cycles – populations fluctuating widely in constant periods 1960 19641968 Lemmings in Barrow

29. Oct. 6, 201029 Alaska Example Intensive Management (i.e., predator control)

30. Oct. 6, 201030 Increase in moose, caribou, and wolves following wolf control in Alaska (Boertje et al. 1996) 14 wolves/1,000 km2 Before 1975 1975 1975-1982 4-5 wolves/1,000 km2 Predator control for 7 years 1982 Stop predator control 1986 15-16 wolves/1,000 km2

31. Oct. 6, 201031 How did moose respond 183 moose/1,000 km2 Before 1975 1975 1975-1982 481 moose/1,000 km2 Predator control for 7 years 1982 Stop predator control λ = 1.15 1982-1994 λ = 1.05 1,020 moose/1,000 km2

32. Oct. 6, 201032 Why did killing wolves increase the wolf population? Why did the moose population continue to increase after the wolf population recovered?

33. Oct. 6, 201033 Predator Pit hypothesis – predation regulate prey at a low and stable density well below “K” Time Population size Predator pit – under maximum growth potential

34. Oct. 6, 201034 Predator control allows prey to escape pit Time Population size Increase growth rate of a larger prey population can sustain impact of predators without population decline

35. Oct. 6, 201035 Danger! Knowing “K” is important Time Population size K Unsustainable level

36. Oct. 6, 201036 Elevating prey base above “K” may result in habitat damage, crash the population, and potential reduce future “K”. Time K Pop Time K K Pop

37. Oct. 6, 201037 The story gets even more ecologically complex and political. Maybe a report topic???