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Overview: Counting Sheep • Soay sheep were introduced to Hirta Island in 1932 • Opportunity to study changes in population on isolated island with abundant food and no predators • Population ecology: study of populations in relation to environment; influences on density, distribution, age structure, population size © 2011 Pearson Education, Inc. Population Ecology Chapter 53 Population density, dispersion, and demographics • Population: group of individuals of one species, living in an area • Density: number of individuals per unit area or vol. – Immigration and emigration – Impractical to count all individuals – Sampling techniques, as mark-recapture method © 2011 Pearson Education, Inc. Figure 53.3 Births Births and immigration add individuals to a population. Immigration Deaths Deaths and emigration remove individuals from a population. Emigration Patterns of Dispersion • Dispersion: pattern of spacing among individuals • Environmental and social factors influence spacing – Clumped: resource availability, behavior – Uniform: social interactions such as territoriality, defense of a space against other individuals – Random: absence of strong attractions or repulsions © 2011 Pearson Education, Inc. Figure 53.4 (a) Clumped (b) Uniform (c) Random Demographics • Demography: study of vital statistics of a population • Death rates and birth rates • Life table: age-specific summary of survival pattern; follows fate of a cohort (individual) © 2011 Pearson Education, Inc. Example of a Life Table Figure 53.5 Survivorship Curve for Belding’s ground squirrels Number of survivors (log scale) 1,000 100 Females 10 Males 1 0 2 4 6 Age (years) 8 10 Survivorship Curves • Type I – low death rates early, middle; death rates increase among old age – Large mammals, – Produce few offspring but give good care • Type III – high death rate for young; few survive early dieoff – Large numbers of offspring, little or no care of young – Plants, fish, marine invertebrates • Type II – constant death rate over lifespan – Rodents, invertebrates, some lizards • Many species don’t fall into any of these categories © 2011 Pearson Education, Inc. Figure 53.6 Survivorship Curves are of three types Number of survivors (log scale) 1,000 I 100 II 10 III 1 0 50 Percentage of maximum life span 100 Reproductive Rates • For species with sexual reproduction, demographers often concentrate on females • Reproductive table or fertility schedule = age-specific summary of reproductive rates © 2011 Pearson Education, Inc. Exponential model of population growth • Useful to study population growth in an idealized situation • Per capita rate of increase • Often, migration is ignored © 2011 Pearson Education, Inc. Expected number of births/deaths per year B bN D mN b = annual per capita birth rate m = per capita death rate N = population size © 2011 Pearson Education, Inc. r = per capita rate of increase rbm • Zero population growth (ZPG) when r 0 © 2011 Pearson Education, Inc. Exponential Population Growth • Population increase under ideal conditions • Rate of increase at maximum – rmax • Exponential population growth is dN rmaxN dt • Exponential growth results in J-shaped curve © 2011 Pearson Education, Inc. Figure 53.7 Population growth predicted by the exponential model. 2,000 dN = 1.0N dt Population size (N) 1,500 dN = 0.5N dt 1,000 500 0 5 10 Number of generations 15 Figure 53.8 Exponential growth in the African elephant population Elephant population 8,000 6,000 4,000 2,000 0 1900 1910 1920 1930 1940 Year 1950 1960 1970 Logistic model • Describes how a population grows more slowly as it reaches its Carrying Capacity • Exponential growth cannot be sustained • More realistic model incorporates carrying capacity (K); produces sigmoid (S-shaped) curve • Carrying capacity varies with abundance of resources • Per capita rate of increase declines as carrying capacity reached (as N approaches K) © 2011 Pearson Education, Inc. Table 53.3 Figure 53.9 Exponential growth dN = 1.0N dt Population size (N) 2,000 1,500 K = 1,500 Population growth predicted by the logistic model. Logistic growth 1,500 – N dN = 1.0N 1,500 dt ( 1,000 Population growth begins slowing here. 500 0 0 5 10 Number of generations 15 ) Figure 53.10 1,000 Number of Daphnia/50 mL Number of Paramecium/mL In a constant environment lacking competitors and predators, how well do these populations fit the logistic growth model? 800 600 400 200 0 0 5 10 Time (days) (a) A Paramecium population in the lab 15 180 150 120 90 60 30 0 0 20 40 60 80 100 120 140 160 Time (days) (b) A Daphnia population in the lab Logistic Model and Real Populations • Some populations overshoot K • Some populations fluctuate greatly; difficult to define K • Logistic model assumes instant adjustment to growth • Logistic model can be used to estimate possible growth • Conservation biologists use model to estimate critical size below which populations may become extinct © 2011 Pearson Education, Inc. Life history traits are products of natural selection • Life history comprises traits that affect schedule of reproduction and survival – Age at which reproduction begins – How often organism reproduces – How many offspring are produced during each reproductive cycle • Life history traits – evolutionary outcomes reflected in development, physiology, behavior © 2011 Pearson Education, Inc. Evolution and Life History Diversity • Species that exhibit semelparity, or big-bang reproduction, reproduce once and die – Highly variable environments favor semelparity – Century plant or Agave • Other species show iteroparity (repeated reproduction) – Dependable environments favor iteroparity – Some Lizards • Organisms have finite resources – may lead to trade-offs – Trade-off between survival & paternal care in kestrels © 2011 Pearson Education, Inc. How does caring for offspring affect parental survival in kestrels? RESULTS 100 Parents surviving the following winter (%) Figure 53.13 Male Female 80 60 40 20 0 Reduced brood size Normal brood size Enlarged brood size f Trade offs between reproduction and survival • Some plants produce large number of small seeds, ensuring that some will grow & eventually reproduce • Other plants produce moderate number of large seeds that provide large store of energy that will help seedlings become established – r-selection (density-independent) – selects for life history traits that maximize reproduction – K-selection (density-dependent) – selects for life history traits sensitive to population density © 2011 Pearson Education, Inc. Figure 53.14 (a) Dandelion (b) Brazil nut tree (right) and seeds in pod (above) Density-dependent factors • Density-independent = birth and death rates do not change with population density • Density- dependent = birth and death rates do change with population density © 2011 Pearson Education, Inc. Density-dependent factors • Density-dependent birth and death rates • Negative feedback between population density and birth/death rates • Affected by competition for resources, territoriality, disease, predation, toxic wastes © 2011 Pearson Education, Inc. Figure 53.15 Birth or death rate per capita 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 Determining equilibrium for population density. Figure 53.16 Decreased reproduction at high population densities. % of young sheep producing lambs 100 80 60 40 20 0 200 300 400 Population size 500 600 Population Dynamics • Focuses on complex interactions between biotic and abiotic factors that cause variation in population size • Long-term studies have challenged hypothesis that populations of large mammals are relatively stable • Weather and predators can affect population size – Moose population on Isle Royale © 2011 Pearson Education, Inc. Figure 53.18 50 2,500 Moose 40 2,000 30 1,500 20 1,000 10 500 0 1955 Number of moose Number of wolves Wolves 0 1965 1975 1985 Year 1995 2005 Fluctuations in moose and wolf populations on Isle Royale, 1959–2008. Population Cycles • Some populations undergo regular boom-andbust – Lynx populations follow 10-year boom-and-bust cycle of hare populations – Three hypotheses have been proposed © 2011 Pearson Education, Inc. Figure 53.19 Snowshoe hare 120 9 Lynx 80 6 40 3 0 0 1850 1875 1900 Year 1925 Number of lynx (thousands) Number of hares (thousands) 160 Hypothesis 1 • Hare’s cycle follows cycle of winter food supply • If hypothesis correct, then cycles should stop if food supply is increased • Additional food was provided experimentally; whole population increased, but continued to cycle • Rejected! © 2011 Pearson Education, Inc. Hypothesis 2 • Hare’s cycle driven by pressure from other predators • In study by field ecologists, 90% of hares were killed by predators • Second hypothesis supported! © 2011 Pearson Education, Inc. Hypothesis 3 • Hare’s cycle linked to sunspot cycles • Sunspot activity affects light quality, which in turn affects quality of hares’ food • Good correlation between sunspot activity & population size © 2011 Pearson Education, Inc. Figure 53.20 How does food availability affect emigration and foraging in a cellular slime mold?` Immigration / Emigration – Dictyostelium amoebas can emigrate and forage better than individual amoebas EXPERIMENT 200 m Dictyostelium amoebas Dictyostelium discoideum slug Dictyostelium movement Topsoil Bacteria Figure 53.21 Metapopulations – groups of populations linked by immigration and emigration ˚ Aland Islands EUROPE Glanville fritillary 5 km Occupied patch Unoccupied patch Human population • Human population increased relatively slowly until about 1650, then began to grow exponentially • Global population now ~7 billion people • Though global population still growing, rate of growth began to slow during 1960s © 2011 Pearson Education, Inc. Figure 53.22 6 5 4 3 2 The Plague 1 0 8000 BCE 4000 BCE 3000 BCE 2000 BCE 1000 BCE 0 1000 CE 2000 CE Human population (billions) 7 Figure 53.23 2.2 Annual percent increase in the global human population (as of 2009). 2.0 Annual percent increase 1.8 1.6 1.4 2009 1.2 Projected data 1.0 0.8 0.6 0.4 0.2 0 1950 1975 2000 Year 2025 2050 Regional Patterns of Population Change • To maintain stability, regional human population can exist in one of two configurations ZPG = High birth rate – High death rate or ZPG = Low birth rate – Low death rate • Demographic transition = move from first state to second state – Associated with increase in quality of health care and improved access to education – Most of current population growth concentrated in developing countries © 2011 Pearson Education, Inc. Age Structure • Important demographic factor in present and future growth trends • Relative number of individuals at each age • Diagrams can predict growth trends & help future planning © 2011 Pearson Education, Inc. Figure 53.24 Age-structure pyramids for the human population of three countries (2009). Rapid growth Afghanistan Male 10 8 Female 6 4 2 0 2 4 6 Percent of population Slow growth United States 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 8 10 8 Male Female 6 4 2 0 2 4 6 Percent of population No growth Italy 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 8 8 Male Female 6 4 2 0 2 4 6 Percent of population 8 Figure 53.25 Infant Mortality and Life Expectancy 80 50 Life expectancy (years) Infant mortality (deaths per 1,000 births) 60 40 30 20 60 40 20 10 0 0 Industrialized countries Less industrialized countries Industrialized countries Less industrialized countries Global Carrying Capacity • Predicted population of 7.810.8 billion in 2050 • Carrying capacity of Earth for humans is uncertain • Average estimate is 10–15 billion • Ecological footprint – aggregate land and water area needed to sustain people • Countries vary greatly in footprint size and available ecological capacity © 2011 Pearson Education, Inc. Figure 53.26 Average per capita energy use Gigajoules > 300 150–300 50–150 10–50 < 10