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Chapter 52

Chapter 52. Population Ecology. Overview: Earth’s Fluctuating Populations To understand human population growth We must consider the general principles of population ecology. Population ecology is the study of populations in relation to environment

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Chapter 52

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  1. Chapter 52 Population Ecology

  2. Overview: Earth’s Fluctuating Populations • To understand human population growth • We must consider the general principles of population ecology

  3. Population ecology is the study of populations in relation to environment • Including environmental influences on population density and distribution, age structure, and variations in population size

  4. The fur seal population of St. Paul Island, off the coast of Alaska • Is one that has experienced dramatic fluctuations in size Figure 52.1

  5. Concept 52.1:Dynamic biological processes influence population density, dispersion, and demography • A population • Is a group of individuals of a single species living in the same general area

  6. density and spacing of individuals • growth rate >>>> birth rate and death rate • exponential growth and its limits • carrying capacity of the environment • density dependent and independent factors • human population growth

  7. 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

  8. Density: A Dynamic Perspective • Determining the density of natural populations • Is possible, but difficult to accomplish • In most cases • It is impractical or impossible to count all individuals in a population

  9. Births and immigration add individuals to a population. Births Immigration PopuIationsize Emigration Deaths Deaths and emigration remove individuals from a population. • Density is the result of a dynamic interplay • Between processes that add individuals to a population and those that remove individuals from it Figure 52.2

  10. Patterns of Dispersion • Environmental and social factors • Influence the spacing of individuals in a population

  11. (a) Clumped. For many animals, such as these wolves, living in groups increases the effectiveness of hunting, spreads the work of protecting and caring for young, and helps exclude other individuals from their territory. Figure 52.3a • A clumped dispersion • Is one in which individuals aggregate in patches • May be influenced by resource availability and behavior

  12. (b) Uniform. Birds nesting on small islands, such as these king penguins on South Georgia Island in the South Atlantic Ocean, often exhibit uniform spacing, maintained by aggressive interactions between neighbors. Figure 52.3b • A uniform dispersion • Is one in which individuals are evenly distributed • May be influenced by social interactions such as territoriality

  13. A random dispersion • Is one in which the position of each individual is independent of other individuals (c) Random. Dandelions grow from windblown seeds that land at random and later germinate. Figure 52.3c

  14. Demography • 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

  15. addition = birth (survivability) + immigration • subtraction = mortality (death) + emigration • Age structure - relative number of each age • important for determining future birth & death rates • fecundity (birth rate) - usually highest in middle age • death rate - usually highest at low and high age • generation time - average time between birth and having offspring

  16. Life Tables • A life table • Is an age-specific summary of the survival pattern of a population • Is best constructed by following the fate of a cohort

  17. The life table of Belding’s ground squirrels • Reveals many things about this population Table 52.1

  18. Survivorship Curves • A survivorship curve • Is a graphic way of representing the data in a life table

  19. 1000 100 Number of survivors (log scale) Females 10 Males 1 2 8 10 4 6 0 Age (years) Figure 52.4 • The survivorship curve for Belding’s ground squirrels • Shows that the death rate is relatively constant

  20. 1,000 I 100 II Number of survivors (log scale) 10 III 1 100 50 0 Percentage of maximum life span • Survivorship curves can be classified into three general types • Type I, Type II, and Type III Figure 52.5

  21. Reproductive Rates • A reproductive table, or fertility schedule • Is an age-specific summary of the reproductive rates in a population

  22. Table 52.2 • A reproductive table • Describes the reproductive patterns of a population

  23. Concept 52.2:Life history traits are products of natural selection • Life history traits are evolutionary outcomes • Reflected in the development, physiology, and behavior of an organism

  24. Life history - the schedule of reproduction and death of an organism • Darwinian fitness - natural selection occurs for traits that allow for BOTH survivability and reproductive success !! • parent survives to reproductive age • parent is able to reproduce • offspring are able to survive • offspring themselves have offspring • Compromise between these factors: • clutch size (offspring per birthing event) • frequency of reproduction • investment in parental care

  25. Life History Diversity • Life histories are very diverse

  26. Figure 52.6 • Species that exhibit semelparity, or “big-bang” reproduction • Reproduce a single time and die

  27. Species that exhibit iteroparity, or repeated reproduction • Produce offspring repeatedly over time

  28. semelparity - energy spent toward one successful reproductive event followed by death (insects) • iteroparity - production of fewer offspring on several different occasions (mammals) • Factors which influence strategy that evolves: • survivability of adult and newborn • longer survivability >>> fewer offspring/event • shorter survivability >>> more offspring/event

  29. Researchers in the Netherlands studied the effects of parental caregiving in European kestrels over 5 years. The researchers transferred chicks among nests to produce reduced broods (three or four chicks), normal broods (five or six), and enlarged broods (seven or eight). They then measured the percentage of male and female parent birds that survived the following winter. (Both males and females provide care for chicks.) EXPERIMENT 100 Male Female 80 60 Parents surviving the following winter (%) 40 20 The lower survival rates of kestrels with larger broods indicate that caring for more offspring negatively affects survival of the parents. CONCLUSION 0 Reduced brood size Normal brood size Enlarged brood size “Trade-offs” and Life Histories • Organisms have finite resources • Which may lead to trade-offs between survival and reproduction RESULTS Figure 52.7

  30. (a) Most weedy plants, such as this dandelion, grow quickly and produce a large number of seeds, ensuring that at least somewill grow into plants and eventually produce seeds themselves. Figure 52.8a • Some plants produce a large number of small seeds • Ensuring that at least some of them will grow and eventually reproduce

  31. (b) Some plants, such as this coconut palm, produce a moderate number of very large seeds. The large endosperm provides nutrients for the embryo, an adaptation that helps ensure the success of a relatively large fraction of offspring. Figure 52.8b • Other types of plants produce a moderate number of large seeds • That provide a large store of energy that will help seedlings become established

  32. Parental care of smaller broods • May also facilitate survival of offspring

  33. Concept 52.3:The exponential model describes population growth in an idealized, unlimited environment • It is useful to study population growth in an idealized situation • In order to understand the capacity of species for increase and the conditions that may facilitate this type of growth

  34. Using a mathematical model for exponential growth in unlimited environment • Consider the case for a bacterium ( N = 2 n ) • n = number of generations • one generation every 20 minutes • one day = 72 generations • N = 2 72 >>> 10 50

  35. Per Capita Rate of Increase Assume for ideal population growth model: • a small group of individuals • unlimited resources DN = change in population # Dt = change in time B = # of births during Dt D = # of deaths during Dt DN / Dt = B - D

  36. generalized equation for population change N = # in population at start of year b = # of births/year (0.034) (birth RATE) m = # of deaths/year (0.016) (death RATE) DN / Dt = bN - mN = N (b-m) • r = (b - d) = difference in birth and death rate • then DN / Dt = r N • or at any instant in time dN / dt = r N

  37. dN  rN dt • Zero population growth • Occurs when the birth rate equals the death rate • The population growth equation can be expressed as

  38. Exponential Growth • Exponential population growth • Is population increase under idealized conditions • Under these conditions • The rate of reproduction is at its maximum, called the intrinsic rate of increase

  39. dN  rmaxN dt • The equation of exponential population growth is

  40. 2,000 dN  1.0N dt 1,500 dN  0.5N dt Population size (N) 1,000 500 0 0 10 15 5 Number of generations Figure 52.9 • Exponential population growth • Results in a J-shaped curve

  41. 8,000 6,000 Elephant population 4,000 2,000 0 1900 1920 1940 1960 1980 Year Figure 52.10 • The J-shaped curve of exponential growth • Is characteristic of some populations that are rebounding

  42. Concept 52.4:The logistic growth model includes the concept of carrying capacity • Exponential growth • Cannot be sustained for long in any population • A more realistic population model • Limits growth by incorporating carrying capacity

  43. Carrying capacity (K) • Is the maximum population size the environment can support

  44. carrying capacity (K) - maximum stable population size that a habitat can support for a sustained period • dependent upon resources that are available • can vary over space and time • change in b or d will affect r

  45. The Logistic Growth Model • In the logistic population growth model • The per capita rate of increase declines as carrying capacity is reached

  46. Maximum Per capita rate of increase (r) Positive N  K 0 Negative Population size (N) Figure 52.11 • We construct the logistic model by starting with the exponential model • And adding an expression that reduces the per capita rate of increase as N increases

  47. (K  N) dN  rmax N dt K • The logistic growth equation • Includes K, the carrying capacity

  48. logistic population growth - in the real world, r is somewhere between rmaxand 0 . • as N approaches K , r decreases !!! dN / dt = rmax N (K - N) / K • as N approaches K , (K - N) / K approaches 0 • this results in an “S - shaped” growth curve

  49. Table 52.3 • A hypothetical example of logistic growth

  50. 2,000 dN  1.0N Exponential growth dt 1,500 K  1,500 Logistic growth Population size (N) 1,000 dN 1,500  N  1.0N dt 1,500 500 0 0 5 10 15 Number of generations • The logistic model of population growth • Produces a sigmoid (S-shaped) curve Figure 52.12

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