1. Populations Outline: Properties of populations Population growth Intraspecific population Metapopulation Readings: Ch. 9, 10, 11, 12

2. Definition Population is a group of individuals of the same species that inhabit a given area

3. Unitary organisms

4. Modular organisms

5. genet ramet

6. Distribution of a population

7. Red maple

8. Distribution of a population Moss (Tetraphis pellucida)

9. Abundance versus Population density

10. Patterns of dispersion

11. Effect of scale on pattern of dispersion

12. Populations have age structure

14. Determining age

15. wild turkeyquail grey squirelbat Determining age

16. Dispersal Movement of individuals in space Moving out of subpopulation = emigration Moving into a subpopulation = immigration Moving and returning= migration

17. Yellow-poplar

18. Ring-necked duck Gray whale

19. Gypsy-moth

20. POPULATION GROWTH

21. Darwin’s 1 st observation: All species have such great potential fertility that their population size would increase exponentially if all individuals that are born reproduce successfully.

22. Example of exponential growth: the ring-necked pheasant, Phasianus colchicus Native to Eurasia 1937: Eight birds introduced to Protection Island (Washington state) 1942: Population had increased to 1,325 birds (a 166-fold increase!)

23.  N/  t = (b - d) N t

24. Population Growth Models Assume no immigration or emigration Let N = population size Let  N/  t = change in population size/unit time = total # births - total # deaths Let mean birth rate per individual = b = # births / individual / unit time Let mean death rate per individual = d = probability of death for an individual / unit time  N/  t = bN - dN Let r = b-d

25. Population Growth Models r = instantaneous rate of increase a.k.a. per capita rate of increase Calculus notation is commonly used;  N/  t = dN/dt If r > 0, population will increase exponentially at rate, dN/dt, = rN For an exponentially growing population, the number of individuals at time t, N t = N 0 e (rt) where N o = initial population size and e = base of natural logarithms

26. Exponential growth model: N t = N 0 e (rt)

27. St. Paul reindeer

28. Life tables cohort - all individuals born within a period cohort life table – survivorship of a cohort over time

29. l x = represents the probability at birth of surviving to any given age Life tables

30. d x = represents the age-specific mortality Life tables

31. q x = represents the age-specific mortality rate Life tables

32. Mortality curves

33. sedum Mortality curves

34. Survivorship curves - plot of l x vs. time

36. Red deer

37. Theoretical survivorship curves

38. What happened to population in 1940s?

40. Human population growth

41. Darwin’s 2 nd observation: Populations tend to remain stable in size, except for seasonal fluctuations Darwin’s 3 rd observation: Environmental resources are limited

42. In real world, populations don’t increase exponentially for very long --> run out of resources An N increases, b decreases and/or d increases

43. Population limiting factors Density-dependent: effect intensifies as N increases. E.g.: 1.Intraspecific competition – Between members of same species 2.Toxic waste accumulation – E.g. yeast cells: produce ethanol as by- product of fermentation (see next slide) 3.Disease – Spreads more easily in crowded environments

44. Effect of crowding on birth rate

45. Effect of crowding on survivorship

46. Intraspecific population regulation

47. Carrying capacity, K = maximum number of individuals that a particular environment can support Take into account by the Logistic Growth Equation, dN/dt = rN (1-N/K)

48. Logistic model

50. Exponential vs. logistic model Gray squirrel

51. How good is the logistic model? Describes growth of simple organisms well, e.g. Paramecium in a lab Water fleas (Daphnia spp.): population initially overshoots K until individuals use up stored lipids --> crash down to K Song sparrows: populations crash frequently due to harsh winter conditions –N never have time to reach K –Population growth not well described by the logistic model

53. Life History Strategies When N is usually << K, natural selection favors adaptations that increase r --> lots of offspring = r selection –E.g. species that colonize short-lived environments When N is usually close to K, better to produce fewer, “better quality” (i.e. more competitive) offspring = K selection E.g species that live in stable, crowded environments

54. Density dependence

55. with Allee effect

56. American ginseng Density dependence with Allee effect

57. Types of competition Competition: individuals use a common resource that is in short supply relative to the number seeking it Intraspecific vs. interspecific Scramble vs. contest Exploitation vs. interference

58. Density effect on growth

61. Horseweed Density effect on growth Self thinning

62. Density effect on reproduction

63. Territoriality

64. Grasshopper sparrow Ammodramus savannarum

65. Banding study in California: 24% of current territory holders had been floaters for 2- 5 yrs. before acquiring a territory. White-crowned sparrow, Zonotrichia leucophrys

67. Uniform distribution of plants occurs due to the development of resource depletion zones around each individual

68. Population limiting factors Density-independent: effect does not depend on N. –E.g. weather / climate –Thrips insects: Feed on Australian crops (pest) Population growth very rapid in early summer Drops in late summer due to heat, dryness --> N never has time to get close to K

69. Density-independent factors

70. DRY Turbid WET Clear Density-independent factors

71. e.g. Dungeness crabs Density-dependent factors: competition; cannibalism Density-independent factors: water temperature

72. Metapopulations a population of populations Chapter 12

73. Metapopulation: A group of moderately isolated populations linked by dispersal

74. Criteria for a metapopulation 1.Habitat occurs in discrete patches 2.Patches are not so isolated as to prevent dispersal 3.Individual populations have a chance of going extinct 4.The dynamics of populations in different patches are not synchronized – i.e., they do not fluctuate or cycle in synchrony

75. Metapopulation dynamics: spatial scales 1.Local (within-patch) 2.Metapopulation (regional)  Shifting mosaic of occupied and unoccupied patches

76. Checkerspot butterfly

77. Levin’s model of metapopulation dynamics E - subpopulation extinction rate = eP e – probability of a patch going extinct/unit time P – proportion of occupied patches C – colonization rate = mP (1-P) m – dispersal rate (1-P) – unoccupied habitats

78. E = C equilibrium point, Where 0 = [mP(1-P)] - eP If C>E, P increases; If C<E, P decreases P equilibrium = 1-e/m

79. Bush cricket

80. Larger patches have larger populations (and therefore lower risk of extinction)

81. Skipper butterfly

83. Effect of habitat heterogeneity

84. Mainland-island population structure: one large population (low extinction risk) provides colonists for many small populations (high risk) Rescue effect: island recolonized from “mainland” High quality / permanent population = source population Temporary patches = sink populations Checker-spot butterfly

85. Skipper butterfly