53 Population Ecology Lecture Presentation by - PowerPoint Presentation

1. 53Population EcologyLecture Presentation by Nicole Tunbridge andKathleen Fitzpatrick

2. Turtle TracksPopulation ecology explores how biotic and abiotic factors influence density, distribution, size, and age structure of populationsFor example, the number of loggerhead turtle hatchlings that survive their first journey to the ocean is affected by both biotic and abiotic factors

3. Figure 53.1

4. Figure 53.1a

5. Concept 53.1: Biological processes influence population density, dispersion, and demographicsA population is a group of individuals of a single species living in the same general areaPopulations are described by their boundaries and size

6. Density and DispersionDensity is the number of individuals per unit area or volumeDispersion is the pattern of spacing among individuals within the boundaries of the population

7. Density: A Dynamic PerspectiveIn most cases, it is impractical or impossible to count all individuals in a population*Precise density numbers are hard to get so we use a variety of methods to estimate population density. This can be either extrapolation from small samples, an index of population size (e.g., number of nests), or the mark-recapture method

8. Determining Population Size Using the Mark-recapture methodScientists capture, tag, and release a random sample of individuals (M)(marked) in a populationMarked individuals are given time to mix back into the populationScientists capture a second sample of individuals (T)(total caught 2nd time), and note how many of them are marked (R)(recapture marked)Population size (N) is estimated byMTRN 

9. Population Density--#/area (volume) ex---5 worms per square foot Mark and Recapture Method: R (marked recaptures) M (marked initially) _____________ = _____________ T (total in second sample) N (total pop. Size) so: N= MT R

10. Figure 53.2Hector’s dolphins

11. Density is the result of an interplay between processes that add individuals to a population and those that remove individualsImmigration is the influx of new individuals from other areasEmigration is the movement of individuals out of a population

12. Figure 53.3BirthsBirths and immigrationadd individuals toa population.ImmigrationDeathsDeaths and emigrationremove individualsfrom a population.Emigration

13. Patterns of DispersionEnvironmental and social factors influence the spacing of individuals in a populationIn a clumped dispersion, individuals aggregate in patchesA clumped dispersion may be influenced by resource availability and behavior

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

15. Dispersion—pattern of spacing 3 patterns: 1. clumped (limited resources, protection) 2. uniform (territoriality, limited resources) 3. random (wind blown seeds) 2.Dispersion—pattern of spacing 3 patterns: 1. clumped (limited resources, protection) 2. uniform (territoriality, limited resources) 3. random (wind blown seeds)

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

17. DemographicsDemography is the study of the vital statistics of a population and how they change over timeDeath rates and birth rates are of particular interest to demographers

18. Demography-study of pops. over timeTools:Life Tables—age specific summary with birth and death rates. Follows a cohort (group studied)Survivorship Curves- 3 types:1. Type 1—long life, large mammals2. Type II– steady deaths in all ages, small animals with many predators3. Type III—starts high but drops sharply, invertebratesIIIIII5010001101001,000Percentage of maximum life spanNumber of survivors (log scale)

19. Life TablesThe life table of Belding’s ground squirrels reveals many things about this populationFor example, it provides data on the proportions of males and females alive at each age

20. Table 53.1

21. Table 53.1c

22. Table 53.1dResearchers working with aBelding’s ground squirrel

23. Survivorship CurvesA survivorship curve is a graphic way of representing the data in a life tableThe survivorship curve for Belding’s ground squirrels shows a relatively constant death rate

24. Figure 53.5FemalesMalesAge (years)Number of survivors (log scale)0 2 4 6 8 101,000100101

25. Survivorship curves can be classified into three general typesType I: Low death rates during early and middle life and an increase in death rates among older age groupsType II: A constant death rate over the organism’s life spanType III: High death rates for the young and a lower death rate for survivorsMany species are intermediate to these curves

26. Figure 53.6IPercentage of maximum life spanNumber of survivors (log scale)0 50 1001,000100101IIIII

27. Reproductive RatesFor species with sexual reproduction, demographers often concentrate on females in a populationEcologists use many approaches to estimate the number of breeding femalesFor example, DNA profiling was used to determine the number of female loggerhead turtles laying eggs in a season

28. Figure 53.7Part 1: Developing the DatabasePart 2: Comparing Samples to the DatabaseSkin samples collectedShort tandemrepeats at 14 lociamplified by PCRGeneticprofilesstored indatabaseGenetic profilescompared todatabaseShort tandemrepeats at 14 lociamplified by PCRGeneticprofilesdeterminedEggshell collected from nestEggshell sample #74

29. A reproductive table, or fertility schedule, is an age-specific summary of the reproductive rates in a population- shows the reproductive patterns of a population

30. Table 53.2

31. Concept 53.2: The exponential model describes population growth in an idealized, unlimited environmentIt is useful to study population growth in an idealized situationIdealized situations help us understand the capacity of species to increase and the conditions that may facilitate this growth

32. Per Capita Rate of IncreaseIf immigration and emigration are ignored, a population’s growth rate (per capita increase) equals birth rate minus death rateChange inpopulationsizeBirthsImmigrantsenteringpopulationDeathsEmigrantsleavingpopulation––

33. The per capita rate of increase (r) is given byZero population growth (ZPG) occurs when the birth rate equals the death rate (r  0)r  b – m

34. Change in population size can now be written asNtrNChange in pop./change in time = growth rate

35. Exponential GrowthExponential population growth is population increase under idealized conditionsUnder these conditions, the rate of increase is at its maximum, denoted as rmaxThe equation of exponential population growth isdNdtrinstN

36. Exponential population growth results in a J-shaped curveThe rate of increase is constant, but the population accumulates more new individuals per unit time when it is large than when it is small

37. Figure 53.8Number of generationsPopulation size (N)dNdt= 1.0NdNdt= 0.5N0 5 10 152,0001,5001,0005000

38. The J-shaped curve of exponential growth characterizes some rebounding populationsFor example, the elephant population in Kruger National Park, South Africa, grew exponentially after hunting was banned

39. Figure 53.9YearElephant population8,0006,0004,0002,00001900 1910 1920 1930 1940 1950 1960 1970

40. Figure 53.9a

41. Types of Population Growth:1. Exponential Growth:Only under ideal conditions, rate of reproduction at maximum. Graph shaped like a “J”2. Logistic Growth:Growth slowed as carrying capacity (K) is reached. Carrying capacity is the maximum amount of individuals the ecosystem can support.

42. Concept 53.3: The logistic model describes how a population grows more slowly as it nears its carrying capacityExponential growth cannot be sustained for long in any populationA more realistic population model limits growth by incorporating carrying capacityCarrying capacity (K) is the maximum population size the environment can supportCarrying capacity varies with the abundance of limiting resources

43. The Logistic Growth ModelIn the logistic population growth model, the per capita rate of increase declines as carrying capacity is reachedThe logistic model starts with the exponential model and adds an expression that reduces per capita rate of increase as N approaches KdNdt(K – N)KrinstN

44. When N is small compared to K, the term (K–N)/K is close to 1 and the per capita rate of increase approaches the maximumWhen N is large compared to K, the term (K–N)/K is close to 0 and the per capita rate of increase is smallWhen N equals K, the population stops growing

45. Table 53.3

46. The logistic model of population growth produces a sigmoid (S-shaped) curveNew individuals are added to the population most rapidly at intermediate population sizesThe population growth rate decreases as N approaches K

47. Figure 53.10ExponentialgrowthLogistic growthPopulation growthbegins slowing here.Number of generationsPopulation size (N)= 1.0N= 1.0NK = 1,500dNdNdtdt1,500 − N1,5002,0001,5001,000500001015 5

48. The Logistic Model and Real PopulationsThe growth of laboratory populations of paramecia fits an S-shaped curveThese organisms are grown in a constant environment lacking predators and competitors

49. Figure 53.111,0008006004002000051015Time (days)(a) A Paramecium population in the lab(b) A Daphnia population in the lab0204060801001201401601801501209060300Time (days)Number of Daphnia/50 mLNumber of Paramecium/mL

50. Some populations overshoot K before settling down to a relatively stable density

51. Some populations fluctuate greatly and make it difficult to define KSome populations show an Allee effect, in which individuals have a more difficult time surviving or reproducing if the population size is too small

52. The logistic model fits few real populations but is useful for estimating possible growthConservation biologists can use the model to estimate the critical size below which populations may become extinct

53. Figure 53.12

54. Concept 53.4: Life history traits are products of natural selectionAn organism’s life history comprises the traits that affect its schedule of reproduction and survivalLife history traits are evolutionary outcomes reflected in the development, physiology, and behavior of an organism

55. Evolution and Life History DiversityA life history entails three main variablesThe age at which reproduction beginsHow often the organism reproducesHow many offspring are produced per reproductive episode

56. Natural selection will select for certain life history traits based on pop. density:K-selection, or density-dependent selectionSelects for life history traits that are sensitive to population density (better competitors, so more survive)r-selection, or density-independent selectionSelects for life history traits that maximize reproduction(will see this in a newly inhabited area)

57. Just keep in mind…….The concepts of K-selection and r-selection are somewhat controversial and have been criticized by ecologists as oversimplifications

58. 2 life history types:1. Semelparity (“big bang”)One big reproduction and die (mayflies)2. Iteroparity (repeated reproduction) mammals, humans*Highly variable or unpredictable environments likely favor semelparity, while dependable environments may favor iteroparity

59. Figure 53.13Semelparity, one-timereproducer(b) Iteroparity, repeat reproducer(a)

60. EXAMPLE OF BOTH:Some plants produce a large number of small seeds, ensuring that at least some of them will grow and eventually reproduce (dandelion)Other types of plants produce a moderate number of large seeds that provide a large store of energy that will help seedlings become established (Brazil Nut)

61. Figure 53.15(a) Dandelion(b)Brazil nut tree(right) and seedsin pod (above)

62.

63. “Trade-offs” and Life HistoriesOrganisms have finite resources…so:*It is a tradeoff with reproduction efforts and survival of oneself.For example, there is a trade-off between survival and paternal care in European kestrels

64. Figure 53.14MaleParents surviving the following winter (%)Female100806040200Reducedbrood sizeNormalbrood sizeEnlargedbrood size

65. Figure 53.14a

66. Concept 53.5: Many factors that regulate population growth are density dependentThere are two general questions about regulation of population growthWhat environmental factors stop a population from growing indefinitely?Why do some populations show radical fluctuations in size over time, while others remain stable?

67. Population change and Population Density:In density-independent populationsBirth rate and death rate do not change with population densityIn density-dependent populationsBirth rates fall and death rates rise with population density(an example of negative feedback regulating growth rates)(examples of factors regulating this: competition, territoriality, health, predation, toxins, intrinsic factors)

68. Figure 53.16Population densityDensity-dependentbirth rate (b)Density-independentdeath rate (m)When populationdensity is low, b > m. Asa result, the populationgrows until the densityreaches Q.When populationdensity is high, m > b. and the populationshrinks until thedensity reaches Q.Equilibrium density (Q)Birth or death rateper capita

69. MECHANISMS OF DENSITY DEPENDENT POPULATION REGULATION:

70. Figure 53.18Competition for resourcesTerritorialityIntrinsic factorsDiseasePredationToxic wastes5 µm

71. Competition for ResourcesIn crowded populations, increasing population density intensifies competition for resources and results in a lower birth rate10010010001,00010,000Average number of seeds per reproducing individual (log scale)Average clutch sizeSeeds planted per m2Density of females070102030405060802.83.03.23.43.63.84.0(a) Plantain. The number of seeds produced by plantain (Plantago major) decreases as density increases.(b) Song sparrow. Clutch size in the song sparrow on Mandarte Island, British Columbia, decreases as density increases and food is in short supply.

72. DiseasePopulation density can influence the health and survival of organismsIn dense populations, pathogens can spread more rapidly

73. Figure 53.18bDisease

74. PredationAs a prey population builds up, predators may feed preferentially on that species

75. Figure 53.17Kelp perch(prey)Kelp bass(predator)Kelp perch density (number/plot)Proportional mortality1.00.80.60.40.200102030405060

76. Figure 53.18cPredation

77. TerritorialityIn many vertebrates and some invertebrates, competition for territory may limit density

78. Figure 53.18dTerritoriality

79. Intrinsic FactorsFor some populations, intrinsic (physiological) factors appear to regulate population size

80. Figure 53.18eIntrinsic factors

81. Toxic WastesAccumulation of toxic wastes can contribute to density-dependent regulation of population size

82. Figure 53.18fToxic wastes5 µm

83. Population DynamicsThe study of population dynamics focuses on the complex interactions between biotic and abiotic factors that cause variation in population size

84. Different species show a variety of population fluctuations…*Extreme fluctuations are more common in invertebrates than mammals.*Many often go in “boom” and “bust” cycles. (interplay of biotic and abiotic factors can cause this)Figure 52.191950196019701980Year199010,000100,000730,000Commercial catch (kg) of male crabs (log scale)

85. Stability and FluctuationLong-term population studies have challenged the hypothesis that populations of large mammals are relatively stable over timeBoth weather and predator population can affect population size over timeFor example, the moose population on Isle Royale collapsed during a harsh winter, and when wolf numbers peaked

86. Stability and FluctuationFigure 52.18The pattern of population dynamics observedin this isolated population indicates that various biotic and abiotic factors can result in dramatic fluctuations over time in a moose population.Researchers regularly surveyed the population of moose on Isle Royale, Michigan, from 1960 to 2003. During that time, the lake never froze over, and so the moose population was isolated from the effects of immigration and emigration.FIELD STUDYOver 43 years, this population experiencedtwo significant increases and collapses, as well as several less severe fluctuations in size.RESULTSCONCLUSION19601970198019902000YearMoose population size05001,0001,5002,0002,500Steady decline probably caused largely by wolf predationDramatic collapse caused by severe winter weather and food shortage, leading to starvation of more than 75% of the population

87. Figure 53.19WolvesMoose2,5002,0001,5001,0005000200519951985197519651955YearNumber of mooseNumber of wolves50403020100

88. Population Cycles: Scientific InquirySome populations undergo regular boom-and-bust cyclesLynx populations follow the 10-year boom-and-bust cycle of hare populations Two main hypotheses have been proposed to explain the hare’s 10-year interval

89. Figure 53.20Snowshoe hareLynx16012080400185018751900Year19259630Number of lynx(thousands)Number of hares(thousands)

90. Figure 53.20a

91. Hypothesis: The hare’s population cycle follows a cycle of winter food supplyIf this hypothesis is correct, then the cycles should stop if the food supply is increasedAdditional food was provided experimentally to a hare population, and the whole population increased in size but continued to cycleThese data do not support the first hypothesis

92. 2nd Hypothesis: The hare’s population cycle is driven by pressure from other predatorsIn a study conducted by field ecologists, 95% of the hares were killed by predators, including lynx, coyotes, hawks, and owlsThese data support the second hypothesis

93. The availability of prey is a major factor influencing predator population dynamicsWhen prey become scarce, predator species begin to prey on one another, accelerating the collapse of predator populations

94. Immigration, Emigration, and MetapopulationsWhen a population becomes crowded and resource competition increases, emigration often increases

95. Metapopulations are groups of populations linked by immigration and emigrationLocal populations in a metapopulation occupy patches of suitable habitat surrounded by unsuitable habitatLocal populations lost through extinctions can be recolonized by immigration from other patches

96. Figure 53.21ÅlandIslandsEUROPEOccupied patchUnoccupied patch5 km

97. An individual’s ability to move between populations depends on a number of factors, including its genetic makeupFor example, Glanville fritillary butterflies that are heterozygous at the Pgi gene fly further at low temperatures than homozygous individuals

98. High levels of immigration combined with higher survivalCan result in greater stability in populationsFigure 52.20Mandarte islandSmall islandsNumber of breeding females1988198919901991Year0102030405060

99. Concept 53.6: The human population is no longer growing exponentially but is still increasing rapidlyNo population can grow indefinitely, and humans are no exception

100. The Global Human PopulationThe human population increased relatively slowly until about 1650 and then began to grow exponentially

101. Figure 53.228000BCE4000BCE3000BCE2000BCE1000BCE01000CE2000CE01234567Human population (billions)

102. The global population is now more than 7 billion peopleThough the global population is still growing, the rate of growth began to slow during the 1960s

103. Figure 53.232.22.01.81.61.41.21.00.80.60.40.201950197520002025YearAnnual percent increase2050Projecteddata2011

104. Regional Patterns of Population ChangeTo maintain population stability, a regional human population can exist in one of two configurationsZero population growth = High birth rate  High death rateZero population growth =Low birth rate  Low death rateThe demographic transition is the move from the first state to the second state

105. The demographic transition is associated with an increase in the quality of health care and improved access to education, especially for womenMost of the current global population growth is concentrated in developing countries

106. The demographic transitionIs the move from the first toward the second stateFigure 52.24504020030101750180018501900195020002050Birth rateDeath rateBirth rateDeath rateYearSwedenMexicoBirth or death rate per 1,000 people

107. Age StructureOne important demographic factor in present and future growth trends is a country’s age structureAge structure is the relative number of individuals at each age

108. Figure 53.24Rapid growthSlow growthNo growthAfghanistanUnited StatesItalyFemaleMaleFemaleMaleFemaleMaleAge85+80–8475–7970–7465–6960–6455–5950–5445–4940–4435–3930–3425–2920–2415–1910–145–90–41086420246810Percent of populationPercent of populationPercent of populationAge85+80–8475–7970–7465–6960–6455–5950–5445–4940–4435–3930–3425–2920–2415–1910–145–90–45432101234554321012345

109. Age structure diagrams can predict a population’s growth trendsThey can illuminate social conditions and help us plan for the future

110. Infant Mortality and Life ExpectancyInfant mortality and life expectancy at birth vary greatly among developed and developing countries but do not capture the wide range of the human condition

111. Global Carrying CapacityHow many humans can the biosphere support?Population ecologists predict a global population of 8.1–10.6 billion people in 2050

112. Estimates of Carrying CapacityThe carrying capacity of Earth for humans is uncertainScientists have based estimates on logistic growth models, area of habitable land, and food availability

113. Limits on Human Population SizeThe ecological footprint concept summarizes the aggregate land and water area needed to sustain the people of a nationIt is one measure of how close we are to the carrying capacity of EarthCountries vary greatly in footprint size and available ecological capacity

114. Figure 53.25

115. Ecological footprints can also be calculated using energy useAverage per capita energy use differs greatly between developed and developing nations

116. Ecological footprints for 13 countriesShow that the countries vary greatly in their footprint size and their available ecological capacityFigure 52.2716141210864200246810121416New ZealandAustraliaCanadaSwedenWorldChinaIndiaAvailable ecological capacity (ha per person)SpainUKJapanGermanyNetherlandsNorwayUSAEcological footprint (ha per person)

117. Figure 53.26Energy use (GJ):> 300< 10150–30050–15010–50

118. Our carrying capacity could potentially be limited by food, space, nonrenewable resources, or buildup of wastesUnlike other organisms, we can regulate our population growth through social changes

119. Figure 53.UN02Patterns of dispersionClumpedUniformRandom

120. Figure 53.UN03dNdt= rinst NNumber of generationsPopulation size (N)

121. Figure 53.UN04Number of generationsPopulation size (N)dNdt= rinst N(K − N)KK = carrying capacity

122. Figure 53.UN05