In nature, species do not live in isolation. Rather, they coexist and interact with a myriad of other species in their
biological communities. These interspecific interactions can affect the species involved positively, negatively, or not
much at all. This exercise explores competitive interactions, where both species a negatively affected by each other,
and predator-prey interactions, where one species benefits and the other is harmed. The classic experiments of G.F.
Gause are simulated.
Background
Competition is an interspecific interaction that occurs when two or more species are utilizing the same resources.
These resources can be space, water, or energy, none of which are unlimited. Because the resources are limited, those
used by one species necessarily reduce those available to other species. Without competition with other species, a
population will typically grow in numbers until competition for resources within the population (intraspecific
competition) leads to a balancing of births and deaths. This balance point is referred to as the ‘carrying capacity’ of
that population, and is seen in the typical logistic population growth curve (Fig. 1).
There are several possible results of interspecific competition. One result is that both species can persist, but each with
their stable population sizes depressed by competition with the other. This is most likely to occur when the resources
being competed for are only a portion of the resources each species can utilize. However, if two species are competing
for exactly the same resources, it is generally thought that one species will have a competitive ‘edge’ and drive the
other to local extinction (Fig. 2). A possible long-term result of interspecific competition is niche partitioning, or
character displacement. In this case the species evolve (morphologically or behaviorally) to exploit different
resources, effectively easing the competition between them.
In the case of predator-prey relationships, one species is the resource for the other. It is easy to imagine that the
relative success of each species is affected by the other. In the classic lynx (predator) and hare (prey) relationship,
when there are a lot of hares around, the lynx population gets a lot to eat and consequently grows in number. With the
increased lynx population, more of the hares get eaten and the hare population declines, which in turn leads to
starvation and decline in the lynx. The resulting pattern observed for these species was multi-year population size
cycles in each species, with the lynx cycles lagging behind the hare.
Figure 1: Intraspecific competition
Figure 2: Interspecific competition
In 1934, G.F. Gause wrote a book called ‘The Struggle for Existence’ in which he empirically explored the
interspecific interactions of competition and predator-prey. He conducted experiments on a small scale (called
microcosms), with various unicellular organisms in dishes. Some of his most famous experiments involved the ciliated
protists Paramecium and Didinium. This exercise will simulate experiments based on Gause’s early work. In our
virtual microcosm there will be bacteria which are food for two species of Paramecia. One Paramecium species is P.
aurelia, which is smaller, and reproduces faster than the other species P. bursaria. P. bursaria has an endosymbiotic
relationship with green algae (called zoochlorellae) which photosynthesize and provide the host Paramecium with
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food. The predator in this microcosm is also a ciliated protest, Didinium. Didinium feed on Paramecia (which are
usually larger than themselves), by ‘harpooning’ them with a toxicyst, and slowly ingesting them over time.
Using the Model
With a java-enabled web browser go to:
http://faculty.etsu.edu/jonestc/Virtualecology.htm
Under the Community Ecology menu, click the ‘Microcosm’ model.
The model opens to a virtual petri dish, which is initially filled with sterile nutrient broth. When ‘Go’ is clicked on,
you can add a specified amount of each microbe, and watch them move about the dish (Fig. 3). Bacteria gain nutrient
from the broth, and the population grows to a carrying capacity related to the volume of the dish. Paramecia gain
energy by feeding on bacteria, and will reproduce by dividing when they have enough energy. Didinium gain energy
to reproduce by eating Paramecium, with one meal being enough to divide. Both Paramecium and Didinium use
energy as they move about the dish, and will die if their energy reserves hit zero. The volume and light level of the
microcosm can be adjusted in the simulation (Table 1). Take some time to familiarize yourself with the model before
beginning the exercise.
Figure 3: Screen shot of the ‘Microcosm’ simulation
Table 1: Controls and reporters for the ‘Microcosm’ simulation
Control
Effect
Setup
Resets the model to the parameters shown
Go
Sets the model in motion, individuals breeding and dying
Volume
The diameter of the virtual petri dish (2-10)
Light
The light level of the microcosm (2-9)
Init-‘x’
The number of the specified microbe to be added
Add ‘x’
Adds the specified number of the specified microbe
Rem. ‘x’
Removes all of the specified microbe
Reporter
Description
Count ‘x’
The number of the specified microbe in the microcosm
Population Size (graph) The population sizes of each microbe over time
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Exercise
The general procedure for these exercises will be to conduct the experiments in each section, and then sketch and
describe the results. It would be helpful to have different colored pencils or pens, because you will be drawing curves
for multiple species on one set of axes. At any time you can speed up the simulation with the speed slider on top of the
world-view.
Answers to the questions should be typed. Graphs should be drawn on this handout.
Part 1- Bacterial growth
Set the volume of the dish to 7, the light level to 6. Set ‘Init-Bacteria’ to 50, and click ‘Add Bacteria’. (The scroller
may be too coarse to get exactly 50, so get as close as you can below 50, and then click on the scroll bar to the right
and that will advance the number of bacteria by 1). Click ‘Go’ and watch how the bacteria grow in the dish. After
approximately 1000 ticks stop the simulation by clicking ‘Go’ again. Sketch the population growth pattern on the axes
below.
1A. Describe the patterns you see.
1B. What type of population growth model best describes what you observe?
Part 2- Paramecium growth
Set the volume of the dish to 7, the light level to 6. Set ‘Init-Bacteria’ to 50, and click ‘Add Bacteria’. Click ‘Go’, to
allow the bacteria to grow to carrying capacity, and then stop the simulation. With the simulation stopped, add 5 P.
Aurelia and restart. After 1000 ticks stop the simulation again, and sketch the population growth patterns of the
bacteria and P. aurelia on the axes below, and describe the pattern in words.
Restart the simulation again, and let it run to 10,000 ticks. Sketch and describe the results below.
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2A. Describe the pattern of growth shown by bacteria and Paramecium in both graphs in part 2.
2B. How does P. aurelia influence the population of bacteria?
Part 3- Paramecium competition
Set the volume of the dish to 7, the light level to 6. Set ‘Init-Bacteria’ to 50, and click ‘Add Bacteria’. Click ‘Go’, to
allow the bacteria grow to carrying capacity, and then stop the simulation. With the simulation stopped, add 5 P.
aurelia, 5 P. bursaria, and then restart. After 5000 ticks stop the simulation again, and sketch the population growth
patterns of the bacteria and Paramecia on the axes below.
Repeat this experiment with the light level at 2, and sketch the population growth patterns of the bacteria and
Paramecia on the axes below.
Repeat this experiment with the light level at 9, and sketch the population growth patterns of the bacteria and
Paramecia on the axes below.
3A. Describe the results for each graph.
3B. How do different light levels influence the effect of P. bursaria on P. aurelia?
Part 4- Paramecium predation by Didinium
Set the volume of the dish to 7, the light level to 6. Set ‘Init-Bacteria’ to 50, and click ‘Add Bacteria’. Click ‘Go’, to
allow the bacteria grow to carrying capacity, and then stop the simulation. With the simulation stopped, add 5 P.
aurelia, then restart, let them grow to their carrying capacity, and then stop the simulation again. At this point add 5
Didinium, and restart the simulation. After 6,000 ticks stop the simulation again, and sketch the population growth
patterns of all three microbes on the axes below.
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Repeat this experiment with the volume at 3, and sketch the population
growth patterns of the bacteria and Paramecia on the axes below.
Repeat this experiment with the volume at 3 a few more times.
4A. Describe the results for each graph.
4B. What is the impact of Didinium predation on P. aurelia?
4C. How does Didinium predation on Paramecium influence the bacteria population? Why does this happen?
4D. How do your results differ when you reduce the volume of your microcosm? Explain your answer.
4E. Do you always get the same results when you run the simulation multiple times with a smaller volume?
Explain your answer.
Extra Credit
Ask any question of your choice and answer it using this microcosm.
References
Gause, G.F. 1934. The Struggle For Existence. The zoological Institute of the University of Moscow.
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