AP Environmental Science
Survivorship Lab
Name __________________________________
Period ________ Date ___________________
INTRODUCTION
Within a population, some
individuals die very young
while others live into old
age. To a large extent, the
pattern of survivorship is
species dependent.
Generally, three patterns of
survivorship have been
identified. These three have
been summarized by
survivorship curves, graphs
that indicate the pattern of
mortality (death) in a
population.
A Type I curve shows high
survivorship until old age,
then high mortality. This
type of curve describes
humans in highly developed countries with good health care services. A Type II curve shows
moderate survivorship of all different ages of a population. Type III curves show low survivorship
at the younger ages, with survivorship increasing as the population ages.
While survivorship curves for humans are relatively easy to generate, information about other
species is more difficult to determine. It can be quite a trick to simple determine the age of an
individual plant or animal, not to mention watching an entire population over a period of years.
However, the principle of determining survivorship can be demonstrated in the laboratory using
nonliving objects.
In this exercise we will study the populations of dice and soap bubbles, using them as models of real
populations to construct survivorship curves. We will subject these populations to different kinds
of stress to determine the effects upon survivorship curves.
MATERIALS
Metric ruler
Bucket of 50 dice
Soap bubbles and a wand
Survivorship frame
Stopwatch or digital watch
Graph paper (both regular and semilog)
PROCEDURE
Work in groups of 3.
Part 1: Dice Population #1
1. Empty the bucket of fifty dice onto the floor.
2. Assume that all individuals that come up as 1s die of heart disease. All others survive.
3. Pick up all the 1s, set them aside (in the cemetery) and count the number of individuals who
have survived. Record the number of survivors in this generation in table 1.
4. Return the survivors to the bucket.
5. Dump the survivors onto the floor again and remove the deaths (1s) that occurred during
this second generation. Count and record the number of survivors.
6. Continue this process until all the dice have died from heart disease, keeping track along the
way.
Part 2: Dice Population #2
1. Start again with a full bucket of 50 dice. Assume that the 1s die of heart disease and the 2s
die of cancer. Proceed as described for population #1, recording your data in table 1, until
all the dice are dead.
2. Now, determine the percentage of survivors for each generation with the following formula
%Survival = 100% * number surviving/50
(Create the following data table in Excel)
TABLE 1: DICE POPULATION DATA
Population 1 (Heart Disease
Only)
Generation
Number
% Surviving
Surviving
0
1
2
3
4
Population 2 (Cancer & Heart
Disease)
Number Surviving
% Surviving
Part 3: Soap Bubble Survivorship – Bubble Population #1 (nurturing)
1. Get a cup of bubble solution and a wand. Dip the wand into the solution and blow gently
through the wand.
2. Once a bubble leaves the wand, group members wave, blow, or fan in an effort to keep the
bubble in the air and prevent it from popping (dying).
3. Note the “age at death” of the bubble and keep a tally of these times on table 2.
4. Blow 50 bubbles this way.
Part 4: Soap Bubble Survivorship – Bubble Population #2 (sink or swim babies)
1. Get a cup of bubble solution and a wand. Dip the wand into the solution and blow gently
through the wand.
2. Once a bubble leaves the wand, group members do NOTHING prevent it from popping
(dying).
3. Note the “age at death” of the bubble and tally of survivorship times on table 2.
4. Blow 50 bubbles this way.
Part 4: Soap Bubble Survivorship – Bubble Population #3 (getting to maturity)
1. Set up a “Survivorship Frame” by having one person in your group hold a frame through
which bubbles must pass. The frame represents reaching the age at which the bubbles reach
maturity. Get a cup of bubble solution and a wand. Dip the wand into the solution and blow
gently through the wand.
2. Once the bubble is free of the wand, start the timer. When the bubble bursts, the timer notes
the time and puts a check mark next to the appropriate age at death in table 2.
a. Bubbles that burst prior to passing through the frame are included in the data.
(These bubbles died as “children”.)
b. Bubbles that burst hitting the frame are included in the data. (These bubbles died as
“adolescents”).
c. Bubbles that fall without passing through the frame ARE NOT INCLUDED!
d. Bubbles that burst after passing through the frame are included. (These bubbles
died as “adults”.)
3. Blow fifty bubbles this way.
Summarize your ALL your bubble data:
a. Count the number of checks (bubbles dying) at each age.
b. Record the total number of checks in the column “Total Number Dying at This Age”
c. Subtract the number dying at each age from 50, determine and record the number
surviving at each age. For example, if five bubbles broke (died) at age one second,
then 50-5=45 survived at least 1 second.
d. Calculate the percentage surviving at each age. Since at birth (the moment the
bubble left the wand) fifty bubbles were alive at age 0. Use the following formula:
% Survival at this age = 100% * number Surviving/50
e. Plot the percentage surviving on the graph.
(Create the following data table in Excel.)
TABLE 2: BUBBLE POPULATION DATA (
Bubble Population 1
(Nurturing)
Generation
Number
%
Surviving
Surviving
0
1
2
3
4
Bubble Population 2
(Sink or Swim babies)
%
Number
Surviving
Surviving
Population 3
(Reaching Maturity)
Number
%
Surviving
Surviving
PLOTTING SURVIVORSHIP CURVES
1. Use the %Surviving data in tables 1 and 2 to make a scatterplot with a line connecting the
points. Print out your graph.
2. You are going to convert your graph into a semilog graph. Right click on the y-axis, choose
“format axis”, choose “scale” and click the box “logarithmic scale”. Print out this graph.
INTERPRETING SURVIVORSHIP CURVES
Examine the plots from the dice populations. In Dice Population #1 (heart disease only), a constant
17% of the population dies at each age. In Dice Population #2 (heart disease and cancer), 33% of
the population dies at each age. On the first graph, the data form a smooth curve and on the second
graph, the data form a straight line. A straight line on a logarithmic plot indicates the death rate is
constant, the curved line on the first graph shows that more individuals die at a young age than at
older ages.
In natural populations, three basic trends of survivorship affecting population size have been
identified. These are represented in the diagram on page one of lab.
1. Compare the curves on that diagram with the curves for Type I, II, and III.
2. Do any of the soap bubble populations show a constant death rate for at least part of their
lifespan? Is so, which?
3. How did the treatments that the different bubble populations were subjected to affect the
shape of the curves?
4. Which type of survivorship curve describes a population of organisms that produces a very
large number of offspring, most of which die at a very early age, only a few surviving to old
age? Give an example of a population of this type.
5. Would you expect a population in which most members survive for a long time to produce
few or many offspring? Which would be most advantageous to the population as a whole?
Give an example of such a species.
6. Suppose a human population exhibits a Type III survival curve.
a. What would you expect to happen to the curve over time if a dramatic improvement
in medical technology takes place?
b. What would you expect to happen to the curve over time if medical technologies
suddenly fails?
7. What would you expect to happen to a population whose birth rate is about equal to the
death rate?