1. LECTURE PRESENTATIONS For CAMPBELL BIOLOGY, NINTH EDITION Jane B. Reece, Lisa A. Urry, Michael L. Cain, Steven A. Wasserman, Peter V. Minorsky, Robert B. Jackson © 2011 Pearson Education, Inc. Lectures by Erin Barley Kathleen Fitzpatrick Population Ecology Chapter 53

2. Overview: Counting Sheep A small population of Soay sheep were introduced to Hirta Island in 1932 They provide an ideal opportunity to study changes in population size on an isolated island with abundant food and no predators © 2011 Pearson Education, Inc.

3. Figure 53.1

4. Population ecology is the study of populations in relation to their environment, including environmental influences on density and distribution, age structure, and population size © 2011 Pearson Education, Inc.

5. Concept 53.1: Dynamic biological processes influence population density, dispersion, and demographics A population is a group of individuals of a single species living in the same general area Populations are described by their boundaries and size © 2011 Pearson Education, Inc.

6. Density and Dispersion Density is the number of individuals per unit area or volume Dispersion is the pattern of spacing among individuals within the boundaries of the population © 2011 Pearson Education, Inc.

7. Density: A Dynamic Perspective In most cases, it is impractical or impossible to count all individuals in a population Sampling techniques can be used to estimate densities and total population sizes Population size can be estimated by either extrapolation from small samples, an index of population size (e.g., number of nests), or the mark-recapture method © 2011 Pearson Education, Inc.

8. Mark-recapture method –Scientists capture, tag, and release a random sample of individuals (s) in a population –Marked individuals are given time to mix back into the population –Scientists capture a second sample of individuals (n), and note how many of them are marked (x) –Population size (N) is estimated by © 2011 Pearson Education, Inc. sn x N 

9. Figure 53.2 Hector’s dolphins APPLICATION

10. Density is the result of an interplay between processes that add individuals to a population and those that remove individuals Immigration is the influx of new individuals from other areas Emigration is the movement of individuals out of a population © 2011 Pearson Education, Inc.

11. Figure 53.3 BirthsDeaths ImmigrationEmigration Births and immigration add individuals to a population. Deaths and emigration remove individuals from a population.

12. Patterns of Dispersion Environmental and social factors influence the spacing of individuals in a population In a clumped dispersion, individuals aggregate in patches A clumped dispersion may be influenced by resource availability and behavior © 2011 Pearson Education, Inc.

13. Video: Flapping Geese (Clumped)

14. Figure 53.4 (a) Clumped (b) Uniform (c) Random

15. Figure 53.4a (a) Clumped

16. A uniform dispersion is one in which individuals are evenly distributed It may be influenced by social interactions such as territoriality, the defense of a bounded space against other individuals © 2011 Pearson Education, Inc.

17. Video: Albatross Courtship (Uniform)

18. Figure 53.4b (b) Uniform

19. In a random dispersion, the position of each individual is independent of other individuals It occurs in the absence of strong attractions or repulsions © 2011 Pearson Education, Inc.

20. Video: Prokaryotic Flagella (Salmonella typhimurium) (Random)

21. Figure 53.4c (c) Random

22. Demographics Demography is the study of the vital statistics of a population and how they change over time Death rates and birth rates are of particular interest to demographers © 2011 Pearson Education, Inc.

23. Life Tables A life table is an age-specific summary of the survival pattern of a population It is best made by following the fate of a cohort, a group of individuals of the same age The life table of Belding’s ground squirrels reveals many things about this population –For example, it provides data on the proportions of males and females alive at each age © 2011 Pearson Education, Inc.

24. Table 53.1

25. Table 53.1a

26. Table 53.1b

27. Survivorship Curves A survivorship curve is a graphic way of representing the data in a life table The survivorship curve for Belding’s ground squirrels shows a relatively constant death rate © 2011 Pearson Education, Inc.

28. Figure 53.5 Males Females 1,000 100 10 1 Age (years) Number of survivors (log scale) 0246810

29. Survivorship curves can be classified into three general types –Type I: low death rates during early and middle life and an increase in death rates among older age groups –Type II: a constant death rate over the organism’s life span –Type III: high death rates for the young and a lower death rate for survivors Many species are intermediate to these curves © 2011 Pearson Education, Inc.

30. Figure 53.6 1,000 III II I 100 10 1 100500 Percentage of maximum life span Number of survivors (log scale)

31. Reproductive Rates For species with sexual reproduction, demographers often concentrate on females in a population A reproductive table, or fertility schedule, is an age-specific summary of the reproductive rates in a population It describes the reproductive patterns of a population © 2011 Pearson Education, Inc.

32. Table 53.2

33. Concept 53.2: The exponential model describes population growth in an idealized, unlimited environment It is useful to study population growth in an idealized situation Idealized situations help us understand the capacity of species to increase and the conditions that may facilitate this growth © 2011 Pearson Education, Inc.

34. Per Capita Rate of Increase If immigration and emigration are ignored, a population’s growth rate (per capita increase) equals birth rate minus death rate © 2011 Pearson Education, Inc. Change in population size Births Immigrants entering population Deaths Emigrants leaving population  

35. The population growth rate can be expressed mathematically as © 2011 Pearson Education, Inc. where  N is the change in population size,  t is the time interval, B is the number of births, and D is the number of deaths

36. Births and deaths can be expressed as the average number of births and deaths per individual during the specified time interval © 2011 Pearson Education, Inc. where b is the annual per capita birth rate, m (for mortality) is the per capita death rate, and N is population size B  bN D  mN

37. The population growth equation can be revised © 2011 Pearson Education, Inc.

38. The per capita rate of increase (r) is given by © 2011 Pearson Education, Inc. r  b  mr  b  m Zero population growth (ZPG) occurs when the birth rate equals the death rate (r  0)

39. Change in population size can now be written as NN tt  rN © 2011 Pearson Education, Inc.

40. Instantaneous growth rate can be expressed as dN dt  r inst N © 2011 Pearson Education, Inc. where r inst is the instantaneous per capita rate of increase

41. Exponential Growth Exponential population growth is population increase under idealized conditions Under these conditions, the rate of increase is at its maximum, denoted as r max The equation of exponential population growth is © 2011 Pearson Education, Inc. dN dt  r max N

42. Exponential population growth results in a J- shaped curve © 2011 Pearson Education, Inc.

43. Number of generations Population size (N) 051015 2,000 1,500 1,000 500 dN dt = 1.0N = 0.5N Figure 53.7

44. The J-shaped curve of exponential growth characterizes some rebounding populations –For example, the elephant population in Kruger National Park, South Africa, grew exponentially after hunting was banned © 2011 Pearson Education, Inc.

45. Figure 53.8 Year Elephant population 8,000 6,000 4,000 2,000 0 19001910192019301940195019601970

46. Figure 53.8a

47. Concept 53.3: The logistic model describes how a population grows more slowly as it nears its carrying capacity Exponential growth cannot be sustained for long in any population A more realistic population model limits growth by incorporating carrying capacity Carrying capacity (K) is the maximum population size the environment can support Carrying capacity varies with the abundance of limiting resources © 2011 Pearson Education, Inc.

48. The Logistic Growth Model In the logistic population growth model, the per capita rate of increase declines as carrying capacity is reached The logistic model starts with the exponential model and adds an expression that reduces per capita rate of increase as N approaches K dN dt  (K  N) K r max N © 2011 Pearson Education, Inc.

49. Table 53.3

50. The logistic model of population growth produces a sigmoid (S-shaped) curve © 2011 Pearson Education, Inc.

51. Number of generations Population growth begins slowing here. Exponential growth Logistic growth Population size (N) 051510 2,000 1,500 1,000 500 0 K = 1,500 dN dt = 1.0N dN dt = 1.0N 1,500 – N 1,500 () Figure 53.9

52. The Logistic Model and Real Populations The growth of laboratory populations of paramecia fits an S-shaped curve These organisms are grown in a constant environment lacking predators and competitors © 2011 Pearson Education, Inc.

53. Figure 53.10 Time (days) (a) A Paramecium population in the lab (b) A Daphnia population in the lab Number of Paramecium/mL Number of Daphnia/50 mL 1,000 800 600 400 200 0 051020150160406080100120140 180 150 120 90 60 30 0

54. Figure 53.10a Time (days) (a) A Paramecium population in the lab Number of Paramecium/mL 1,000 800 600 400 200 0 051015

55. Some populations overshoot K before settling down to a relatively stable density © 2011 Pearson Education, Inc.

56. Figure 53.10b Time (days) (b) A Daphnia population in the lab Number of Daphnia/50 mL 200160406080100120140 180 150 120 90 60 30 0

57. Some populations fluctuate greatly and make it difficult to define K Some populations show an Allee effect, in which individuals have a more difficult time surviving or reproducing if the population size is too small © 2011 Pearson Education, Inc.

58. The logistic model fits few real populations but is useful for estimating possible growth Conservation biologists can use the model to estimate the critical size below which populations may become extinct © 2011 Pearson Education, Inc.

59. Figure 53.11

60. Concept 53.4: Life history traits are products of natural selection An organism’s life history comprises the traits that affect its schedule of reproduction and survival –The age at which reproduction begins –How often the organism reproduces –How many offspring are produced during each reproductive cycle Life history traits are evolutionary outcomes reflected in the development, physiology, and behavior of an organism © 2011 Pearson Education, Inc.

61. Evolution and Life History Diversity Species that exhibit semelparity, or big-bang reproduction, reproduce once and die Species that exhibit iteroparity, or repeated reproduction, produce offspring repeatedly Highly variable or unpredictable environments likely favor big-bang reproduction, while dependable environments may favor repeated reproduction © 2011 Pearson Education, Inc.

62. Figure 53.12

63. “Trade-offs” and Life Histories Organisms have finite resources, which may lead to trade-offs between survival and reproduction –For example, there is a trade-off between survival and paternal care in European kestrels © 2011 Pearson Education, Inc.

64. Figure 53.13 Male Female RESULTS Reduced brood size Normal brood size Enlarged brood size Parents surviving the following winter (%) 100 80 60 40 20 0

65. Figure 53.13a

66. Some plants produce a large number of small seeds, ensuring that at least some of them will grow and eventually reproduce © 2011 Pearson Education, Inc.

67. Figure 53.14 (a) Dandelion (b) Brazil nut tree (right) and seeds in pod (above)

68. Figure 53.14a (a) Dandelion

69. Other types of plants produce a moderate number of large seeds that provide a large store of energy that will help seedlings become established © 2011 Pearson Education, Inc.

70. Figure 53.14ba (b) Brazil nut tree seeds In seed pod

71. Figure 53.14bb (b) Brazil nut tree

72. K-selection, or density-dependent selection, selects for life history traits that are sensitive to population density r-selection, or density-independent selection, selects for life history traits that maximize reproduction © 2011 Pearson Education, Inc.

73. The concepts of K-selection and r-selection are oversimplifications but have stimulated alternative hypotheses of life history evolution © 2011 Pearson Education, Inc.

74. Concept 53.5: Many factors that regulate population growth are density dependent There are two general questions about regulation of population growth –What environmental factors stop a population from growing indefinitely? –Why do some populations show radical fluctuations in size over time, while others remain stable? © 2011 Pearson Education, Inc.

75. Population Change and Population Density In density-independent populations, birth rate and death rate do not change with population density In density-dependent populations, birth rates fall and death rates rise with population density © 2011 Pearson Education, Inc.

76. When population density is low, b > m. As a result, the population grows until the density reaches Q. When population density is high, m > b, and the population shrinks until the density reaches Q. Equilibrium density (Q) Density-independent death rate (m) Density-dependent birth rate (b) Population density Birth or death rate per capita Figure 53.15

77. Mechanisms of Density-Dependent Population Regulation Density-dependent birth and death rates are an example of negative feedback that regulates population growth Density-dependent birth and death rates are affected by many factors, such as competition for resources, territoriality, disease, predation, toxic wastes, and intrinsic factors © 2011 Pearson Education, Inc.

78. Figure 53.16 Population size % of young sheep producing lambs 200300400500600 100 80 60 40 20 0

79. Competition for Resources In crowded populations, increasing population density intensifies competition for resources and results in a lower birth rate © 2011 Pearson Education, Inc.

80. Figure 53.17a

81. Toxic Wastes Accumulation of toxic wastes can contribute to density-dependent regulation of population size © 2011 Pearson Education, Inc.

82. Figure 53.17c 5  m

83. Predation As a prey population builds up, predators may feed preferentially on that species © 2011 Pearson Education, Inc.

84. Figure 53.17b

85. Figure 53.17ba

86. Figure 53.17bb

87. Intrinsic Factors For some populations, intrinsic (physiological) factors appear to regulate population size © 2011 Pearson Education, Inc.

88. Figure 53.17d

89. Territoriality In many vertebrates and some invertebrates, competition for territory may limit density © 2011 Pearson Education, Inc.

90. Figure 53.17e

91. Figure 53.17ea

92. Figure 53.17eb

93. Disease Population density can influence the health and survival of organisms In dense populations, pathogens can spread more rapidly © 2011 Pearson Education, Inc.

94. Figure 53.17f

95. Population Dynamics The study of population dynamics focuses on the complex interactions between biotic and abiotic factors that cause variation in population size © 2011 Pearson Education, Inc.

96. Stability and Fluctuation Long-term population studies have challenged the hypothesis that populations of large mammals are relatively stable over time Both weather and predator population can affect population size over time –For example, the moose population on Isle Royale collapsed during a harsh winter, and when wolf numbers peaked © 2011 Pearson Education, Inc.

97. WolvesMoose Year Number of wolves Number of moose 195519651975198519952005 50 40 30 20 10 0 2,500 2,000 1,500 1,000 500 0 Figure 53.18

98. Population Cycles: Scientific Inquiry Some populations undergo regular boom-and-bust cycles Lynx populations follow the 10-year boom-and- bust cycle of hare populations Three hypotheses have been proposed to explain the hare’s 10-year interval © 2011 Pearson Education, Inc.

99. Snowshoe hare Lynx Year 1850187519001925 Number of hares (thousands) Number of lynx (thousands) 160 120 80 40 0 96309630 Figure 53.19

100. Figure 53.19a

101. Hypothesis: The hare’s population cycle follows a cycle of winter food supply If this hypothesis is correct, then the cycles should stop if the food supply is increased Additional food was provided experimentally to a hare population, and the whole population increased in size but continued to cycle These data do not support the first hypothesis © 2011 Pearson Education, Inc.

102. Hypothesis: The hare’s population cycle is driven by pressure from other predators In a study conducted by field ecologists, 90% of the hares were killed by predators These data support the second hypothesis © 2011 Pearson Education, Inc.

103. Hypothesis: The hare’s population cycle is linked to sunspot cycles Sunspot activity affects light quality, which in turn affects the quality of the hares’ food There is good correlation between sunspot activity and hare population size © 2011 Pearson Education, Inc.

104. The results of all these experiments suggest that both predation and sunspot activity regulate hare numbers and that food availability plays a less important role © 2011 Pearson Education, Inc.

105. Immigration, Emigration, and Metapopulations A group of Dictyostelium amoebas can emigrate and forage better than individual amoebas © 2011 Pearson Education, Inc.

106. Figure 53.20 Topsoil Bacteria EXPERIMENT Dictyostelium amoebas Dictyostelium discoideum slug 200  m

107. Figure 53.20a Dictyostelium discoideum slug 200  m

108. Metapopulations are groups of populations linked by immigration and emigration High levels of immigration combined with higher survival can result in greater stability in populations © 2011 Pearson Education, Inc.

109. Aland Islands ˚ EUROPE Occupied patch Unoccupied patch 5 km Figure 53.21

110. Figure 53.21a

111. Concept 53.6: The human population is no longer growing exponentially but is still increasing rapidly No population can grow indefinitely, and humans are no exception © 2011 Pearson Education, Inc.

112. The Global Human Population The human population increased relatively slowly until about 1650 and then began to grow exponentially © 2011 Pearson Education, Inc.

113. Figure 53.22 The Plague Human population (billions) 8000 BCE 4000 BCE 2000 CE 1000 BCE 2000 BCE 3000 BCE 1000 CE 0 7654321076543210

114. The global population is more than 6.8 billion people Though the global population is still growing, the rate of growth began to slow during the 1960s © 2011 Pearson Education, Inc.

115. Projected data 2009 Annual percent increase 19501975200020252050 Year 2.2 2.0 1.8 1.6 1.4 1.2 1.0 0.8 0.6 0.4 0.2 0 Figure 53.23

116. Regional Patterns of Population Change To maintain population stability, a regional human population can exist in one of two configurations –Zero population growth = High birth rate – High death rate –Zero population growth = Low birth rate – Low death rate The demographic transition is the move from the first state to the second state © 2011 Pearson Education, Inc.

117. The demographic transition is associated with an increase in the quality of health care and improved access to education, especially for women Most of the current global population growth is concentrated in developing countries © 2011 Pearson Education, Inc.

118. Age Structure One important demographic factor in present and future growth trends is a country’s age structure Age structure is the relative number of individuals at each age © 2011 Pearson Education, Inc.

119. Figure 53.24 Percent of population Rapid growth Afghanistan Slow growth United States No growth Italy Male Female Age 85+ 80–84 75–79 70–74 65–69 60–64 55–59 50–54 45–49 40–44 35–39 30–34 25–29 20–24 15–19 10–14 5–9 0–4 Age 85+ 80–84 75–79 70–74 65–69 60–64 55–59 50–54 45–49 40–44 35–39 30–34 25–29 20–24 15–19 10–14 5–9 0–4 100 88888866666644444422222200

120. Figure 53.24a Percent of population Rapid growth Afghanistan MaleFemale Age 85+ 80–84 75–79 70–74 65–69 60–64 55–59 50–54 45–49 40–44 35–39 30–34 25–29 20–24 15–19 10–14 5–9 0–4 10 886644220

121. Figure 53.24b Percent of population Slow growth United States MaleFemale 886644220 Age 85+ 80–84 75–79 70–74 65–69 60–64 55–59 50–54 45–49 40–44 35–39 30–34 25–29 20–24 15–19 10–14 5–9 0–4

122. Figure 53.24c Percent of population No growth Italy MaleFemale 088664422 Age 85+ 80–84 75–79 70–74 65–69 60–64 55–59 50–54 45–49 40–44 35–39 30–34 25–29 20–24 15–19 10–14 5–9 0–4

123. Age structure diagrams can predict a population’s growth trends They can illuminate social conditions and help us plan for the future © 2011 Pearson Education, Inc.

124. Infant Mortality and Life Expectancy Infant mortality and life expectancy at birth vary greatly among developed and developing countries but do not capture the wide range of the human condition © 2011 Pearson Education, Inc.

125. Indus- trialized countries Less indus- trialized countries Infant mortality (deaths per 1,000 births) Life expectancy (years) 60 50 40 30 20 10 0 80 60 40 20 0 Figure 53.25

126. Global Carrying Capacity How many humans can the biosphere support? Population ecologists predict a global population of 7.8  10.8 billion people in 2050 © 2011 Pearson Education, Inc.

127. Estimates of Carrying Capacity The carrying capacity of Earth for humans is uncertain The average estimate is 10–15 billion © 2011 Pearson Education, Inc.

128. Limits on Human Population Size The ecological footprint concept summarizes the aggregate land and water area needed to sustain the people of a nation It is one measure of how close we are to the carrying capacity of Earth Countries vary greatly in footprint size and available ecological capacity © 2011 Pearson Education, Inc.

129. Figure 53.26 Gigajoules > 300 150–300 50–150 10–50 < 10

130. Our carrying capacity could potentially be limited by food, space, nonrenewable resources, or buildup of wastes Unlike other organisms, we can regulate our population growth through social changes © 2011 Pearson Education, Inc.

131. Figure 53.UN01 Patterns of dispersion ClumpedUniformRandom

132. Figure 53.UN02 Number of generations Population size (N) = r max N dN dt

133. Figure 53.UN03 Number of generations Population size (N) = r max N dN dt K – N K K = carrying capacity ()

134. Figure 53.UN04

135. Figure 53.UN05

136. Figure 53.UN06