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 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:

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 beingenough 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

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. Aureliaand restart. After 1000 ticks stop the simulation again, and sketch the population growth patterns of the bacteria and P. aureliaon 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.

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- Parameciumcompetition

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 Parameciaon the axes below.

Repeat this experiment with the light level at 2,and sketch the population growth patterns of the bacteria and Parameciaon the axes below.

Repeat this experiment with the light level at 9,and sketch the population growth patterns of the bacteria and Parameciaon 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- Parameciumpredation 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 microbeson the axes below.

Repeat this experiment with the volume at 3, and sketch the population growth patterns of the bacteria and Parameciaon 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 doesDidinium 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 itusing this microcosm.

References

Gause, G.F. 1934. The Struggle For Existence. The zoological Institute of the University of Moscow.

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