Chapter 53 Population Ecology.

Chapter 53 Population Ecology

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 They were studied for over 50 yrs. Their numbers were found to vary greatly from year to year. Why? Think of possible reasons.

Population ecology is the study of populations in relation to environment, including environmental influences on density and distribution, age structure, and population size A population is a group of individuals of a single species living in the same general area. Three characteristics of a population are its density, dispersion, and demographics.

Density and Dispersion
Density is the number of individuals per unit area or volume Ex: Number of maple trees in Cambria County Dispersion is the pattern of spacing among individuals within the boundaries of the population Demographics is the study of the vital statistics of a population and how they change over time

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, or the mark-recapture method

APPLICATION Hector’s dolphins
Fig. 53-2 APPLICATION This rare species of dolphin was studied by ecologists in New Zealand using the mark-recapture method. 1. Start by capturing and tagging (or photograph distinctive markings) to identify a sample of dolphins were identified 2. Release them—they mix back into the population. 3. Recapture a second sample about a week later. (44 were captured—7 already tagged or identified by photographs) 4. x = m solve for N N = mn n N x N= (180)(44)/7 = 1, 131 individuals Hector’s dolphins X = number of marked animals recaptured n = total number of animals recaptured m = number of individuals marked at beginning N= estimated population size Figure 53.2 Determining population size using the mark-recapture method Note: This is truly an estimate because it assumes that marked and unmarked individuals have the same probability of being captured, that the marked individuals have completely mixed back into the population, and that no individuals are born, die, immigrate or emigrate during the study.

Immigration is the influx of new individuals from other areas
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 Birth rate is the number of new individuals born into a population Death rate is the number of individuals that die in a population Deaths Births Remove individuals from populations Add individuals to populations Emigration Immigration

Video: Flapping Geese (Clumped)
Patterns of Dispersion Environmental and social factors influence spacing of individuals in a population In a clumped dispersion, individuals aggregate in patches. It is most common. A clumped dispersion may be influenced by resource availability and behavior Clumped Dispersion Video: Flapping Geese (Clumped)

Video: Albatross Courtship (Uniform)
A uniform dispersion is one in which individuals are evenly distributed. Not as common as clumped. It may be influenced by social interactions such as territoriality Uniform Dispersion Video: Albatross Courtship (Uniform)

Video: Prokaryotic Flagella (Salmonella typhimurium) (Random)
In a random dispersion, the position of each individual is independent of other individuals. Wind-blown seeds for example, are randomly dispersed. This is not real common in nature. It occurs in the absence of strong attractions or repulsions Random Dispersion Video: Prokaryotic Flagella (Salmonella typhimurium) (Random)

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 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

Table 53-1

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

Number of survivors (log scale)
Fig. 53-5 1,000 100 Number of survivors (log scale) Females 10 Males Figure 53.5 Survivorship curves for male and female Belding’s ground squirrels 1 2 4 6 8 10 Age (years)

Survivorship curves can be classified into three general types:
Type I: low death rates during early and middle life, then an increase among older age groups Type II: the death rate is constant over the organism’s life span Type III: high death rates for the young, then a slower death rate for survivors Many species actually fall somewhere between these basic types of curves and show more complex patterns.

Number of survivors (log scale)
Fig. 53-6 Common in animals that have few young and provide extensive care for them 1,000 I Common in a few species of rodents, Lizards, invertebrates and annual plants. 100 II Number of survivors (log scale) Common in animals that have many young and provide little or no care for them. 10 Figure 53.6 Idealized survivorship curves: Types I, II, and III III 1 50 100 Percentage of maximum life span

Concept 53.2: Life history traits are products of natural selection
An organism’s life history comprises the traits that affect its schedule of reproduction and survival: It entails three basic variables: 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 (i.e. except for humans, organisms do not really choose when to reproduce or how many offspring to have.)

Evolution and Life History Diversity
Life histories are very diverse. Some species that exhibit semelparity, or big-bang reproduction, reproduce once and die. Ex: Pacific Salmon Some species that exhibit iteroparity, or repeated reproduction, produce offspring repeatedly. Ex: Animals with seasonal mating seasons. Highly variable or unpredictable environments likely favor big-bang reproduction. Survival rate is low—even for adults. So they produce a lot of young once—in hopes that a few will survive to reproduce. Dependable environments may favor repeated reproduction. Survival rate is good—for young and adults. The adults will survive to reproduce again. A few large young should also be able to survive to reproductive age.

Concept 53.3: 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

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

Zero population growth occurs when the birth rate equals the death rate
Most ecologists use differential calculus to express population growth as growth rate at a particular instant in time: N t  rN where N = population size, t = time, and r = per capita rate of increase = birth – death

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

Equation of exponential population growth:
dN dt  rmaxN

Exponential population growth results in a J-shaped curve

2,000 = 1.0N 1,500 = 0.5N Population size (N) 1,000 500 5 10 15
Fig 2,000 dN = 1.0N dt 1,500 dN = 0.5N dt Population size (N) 1,000 500 Figure Population growth predicted by the exponential model 5 10 15 Number of generations

The J-shaped curve of exponential growth characterizes some rebounding populations

Fig 8,000 6,000 Elephant population 4,000 2,000 Figure Exponential growth in the African elephant population of Kruger National Park, South Africa 1900 1920 1940 1960 1980 Year

Concept 53.4: 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

The Logistic Growth Model
In the logistic population growth model, the per capita rate of increase declines as carrying capacity is reached We construct the logistic model by starting with the exponential model and adding an expression that reduces per capita rate of increase as N approaches K dN dt  (K  N) K rmax N

Table 53-3 Table 53.3

The logistic model of population growth produces a sigmoid (S-shaped) curve

Exponential growth 2,000 = 1.0N 1,500 K = 1,500 Population size (N)
Fig Exponential growth 2,000 dN = 1.0N dt 1,500 K = 1,500 Population size (N) Logistic growth 1,000 dN 1,500 – N = 1.0N dt 1,500 Figure Population growth predicted by the logistic model 500 5 10 15 Number of generations

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

Number of Paramecium/mL
Fig a 1,000 800 Number of Paramecium/mL 600 400 200 Figure 53.13a How well do these populations fit the logistic growth model? 5 10 15 Time (days) (a) A Paramecium population in the lab

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

(b) A Daphnia population in the lab
Fig b 180 150 120 Number of Daphnia/50 mL 90 60 30 Figure 53.13b How well do these populations fit the logistic growth model? 20 40 60 80 100 120 140 160 Time (days) (b) A Daphnia population in the lab

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

The logistic model fits few real populations but is useful for estimating possible growth
Scientists can use it to estimate the critical size below which a population, like the white rhino, may become extinct

The Logistic Model and Life Histories
Life history traits favored by natural selection may vary with population density and environmental conditions 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 The concepts of K-selection and r-selection are oversimplifications but have stimulated alternative hypotheses of life history evolution

There are two general questions about regulation of population growth:
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?

Limiting Factors Environmental factors that work to keep populations in check are known as limiting factors. Examples: Food Temperature Access to mates Space

Population Change and Population Density
A birth rate or death rate that does not change with population density is said to be density-independent. Density-independent limiting factors include things like natural catastrophies (volcanic eruption or flood) A birth rate or death rate that does change with population density is said to be density-dependent populations. Density-dependent limiting factors include competition for resources, territoriality, disease, predation, toxic wastes, and intrinsic factors They are all examples of negative feedback that controls growth.

Competition for Resources
As population density increases, individuals compete more intensely for food, water and other nutrients. Such competition helps to establish carrying capacity.

Territoriality In many vertebrates and some invertebrates, competition for territory may limit density Ex: Cheetahs are highly territorial, using chemical communication to warn other cheetahs of their boundaries Oceanic birds exhibit territoriality in nesting behavior

Population density can influence the health and survival of organisms
Disease Population density can influence the health and survival of organisms In dense populations, pathogens can spread more rapidly This fungal infection will spread more rapidly in a densely populated garden

Predation As a prey population builds up, predators may feed preferentially on that species

Toxic Wastes Accumulation of toxic wastes can contribute to density-dependent regulation of population size Example: Ethanol accumulates as a byproduct of yeast fermentation. Most wine is less than 13% alcohol because that is the maximum concentration of ethanol that most wine-producing yeast cells can tolerate.

Intrinsic Factors For some populations, intrinsic (physiological) factors appear to regulate population size Mice in high density populations will become more aggressive. The aggression will create a stress syndrome that causes hormonal changes which delay sexual maturation and depress the immune system. Thus, birth rates decrease and death rates increase

Population Dynamics The study of population dynamics focuses on the complex interactions between biotic and abiotic factors that cause variation in population size Two examples: Long-term population studies have challenged the hypothesis that populations of large mammals are relatively stable over time. The sheep mentioned at the beginning of the chapter are an example of this. Weather seems to greatly affect their population size over time as well as disease spread by parasites.

Fig 2,100 Most of the population drops coincide with harsh, cold winters. A few are due to parasites spreading quickly when the population is dense. 1,900 1,700 1,500 Number of sheep 1,300 1,100 900 Figure Variation in size of the Soay sheep population on Hirta Island, 1955–2002 700 500 1955 1965 1975 1985 1995 2005 Year

In another example: Changes in predation pressure can drive population fluctuations. The following graph shows the fluctuations in moose and wolf populations on an isolated island. The moose population crashed twice: once when the wolf population was at its peak and once following a terribly harsh winter.

50 2,500 Wolves Moose 40 2,000 30 1,500 Number of wolves
Fig 50 2,500 Wolves Moose 40 2,000 30 1,500 Number of wolves Number of moose 20 1,000 10 500 Figure Fluctuations in moose and wolf populations on Isle Royale, 1959–2006 1955 1965 1975 1985 1995 2005 Year

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

Number of hares (thousands) Number of lynx (thousands)
Fig Snowshoe hare 160 120 9 Figure Population cycles in the snowshoe hare and lynx Lynx Number of hares (thousands) Number of lynx (thousands) 80 6 40 3 1850 1875 1900 1925 Year

Hypothesis #1: 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

Hypothesis #2: 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 No hares appeared to have died of starvation These data support this second hypothesis

Hypothesis #3: 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

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

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 Human population increased rather slowly until 1650, at which time there were about 500 million people on Earth. We doubled to 1 billion within the next two centuries Doubled again to 2 billion between 1850 and 1930. Doubled again to 4 billion by 1975 We are now more than 7.3 billion (increasing by about 75 million each year; or 200,000 each day) It is predicted that a population of 7.8 – 10.8 billion people will inhabit Earth by 2050.

7 6 5 4 3 2 1 Human population (billions) The Plague 8000 B.C.E. 4000
Fig 7 6 5 4 Human population (billions) 3 2 The Plague Figure Human population growth (data as of 2006) 1 8000 B.C.E. 4000 B.C.E. 3000 B.C.E. 2000 B.C.E. 1000 B.C.E. 1000 C.E. 2000 C.E.

Annual percent increase
Fig Though the global population is still growing, the rate of growth began to slow during the 1960s The annual rate of increase peaked in 1962 at 2.2%. It declined to 1.15% by 2005. Current models show it a 0.4% by 2050. 2.2 2.0 1.8 1.6 1.4 The sharp dip in the 1960s is due to the famine in China, which killed 60 million people 2005 Annual percent increase 1.2 Projected data 1.0 0.8 0.6 Figure Annual percent increase in the global human population (data as of 2005) The departure from true exponential growth is due to diseases (AIDS) and to voluntary population control. 0.4 0.2 1950 1975 2000 2025 2050 Year

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 toward the second state

Birth or death rate per 1,000 people
Fig 50 40 30 Birth or death rate per 1,000 people 20 Figure Demographic transition in Sweden and Mexico, 1750–2025 (data as of 2005) 10 Sweden Mexico Birth rate Birth rate Death rate Death rate 1750 1800 1850 1900 1950 2000 2050 Year

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

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

Rapid growth Slow growth No growth Afghanistan United States Italy
Fig Rapid growth Slow growth No growth Afghanistan United States Italy Male Female Age Male Female Age Male Female 85+ 85+ 80–84 80–84 75–79 75–79 70–74 70–74 65–69 65–69 60–64 60–64 55–59 55–59 50–54 50–54 45–49 45–49 40–44 40–44 35–39 35–39 30–34 30–34 25–29 25–29 20–24 20–24 Figure Age-structure pyramids for the human population of three countries (data as of 2005) 15–19 15–19 10–14 10–14 5–9 5–9 0–4 0–4 10 8 6 4 2 2 4 6 8 10 8 6 4 2 2 4 6 8 8 6 4 2 2 4 6 8 Percent of population Percent of population Percent of population

Global Carrying Capacity
How many humans can the biosphere support? The carrying capacity of Earth for humans is uncertain The average estimate is 10–15 billion

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

One way to estimate the ecological footprint of the human population is to add up all the ecologically productive land on the planet and divide by the population. This calculates to about 2 hectares (ha) per person. Typically, we reserve some land for parks and conservation so the actual number used is 1.7 ha per person. One who consumes more resources than can be produced on 1.7 ha is using more than their share of Earth’s resources. The average person in the U.S. has an ecological footprint of 10 ha.

13.4 9.8 5.8 Not analyzed Log (g carbon/year)
Fig Log (g carbon/year) 13.4 9.8 Figure The amount of photosynthetic products that humans use around the world 5.8 Not analyzed This shows the amount of photosynthetic products that humans use around the world. The unit is a Logarithm of the number of grams of photosynthetic products consumed each year. The greatest Usage is where population density is high or where people consume the most resources individually (high per capita consumption---like the U.S)

Our carrying capacity could potentially be limited by food, space, nonrenewable resources, or buildup of wastes Unlike other organisms, we can decide whether zero population growth will be attained through social changes based on human choices or through increased mortality due to resource limitation, plagues, war and environmental degradation.

Patterns of dispersion
Fig. 53-UN1 Patterns of dispersion Clumped Uniform Random

Fig. 53-UN2 dN = rmax N dt Population size (N) Number of generations

K = carrying capacity Population size (N) dN K – N = rmax N dt K
Fig. 53-UN3 K = carrying capacity Population size (N) dN K – N = rmax N dt K Number of generations

You should now be able to:
Define and distinguish between the following sets of terms: density and dispersion; clumped dispersion, uniform dispersion, and random dispersion; life table and reproductive table; Type I, Type II, and Type III survivorship curves; semelparity and iteroparity; r-selected populations and K-selected populations Explain how ecologists may estimate the density of a species

Explain how limited resources and trade-offs may affect life histories
Compare the exponential and logistic models of population growth Explain how density-dependent and density-independent factors may affect population growth Explain how biotic and abiotic factors may work together to control a population’s growth

Describe the problems associated with estimating Earth’s carrying capacity for the human species
Define the demographic transition

Chapter 53 Population Ecology.

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