NetLogo banner

 Home
 Download
 Help
 Resources
 Extensions
 FAQ
 References
 Contact Us
 Donate

 Models:
 Library
 Community
 Modeling Commons

 User Manuals:
 Web
 Printable
 Chinese
 Czech
 Japanese

  Donate

NetLogo User Community Models

(back to the NetLogo User Community Models)

Population Dynamics_v4

by David W. Rudge and William Merrow (Submitted: 08/07/2008 )

[screen shot]

Download Population Dynamics_v4
If clicking does not initiate a download, try right clicking or control clicking and choosing "Save" or "Download".

(You can also run this model in your browser, but we don't recommend it; details here.)

WHAT IS IT?

NetLogo-Population Dynamics introduces students to the concept of a carrying capacity by means of an open-ended problem, namely how to create the best bass fishing pond possible. To begin addressing this question, students are invited to consider a very simple pond ecosystem containing only algae, the producer in this system. Students will explore how the carrying capacity of the pond for algae is affected by available sunlight. Students then study the effects of predation and competition by systematically introducing sunfish (a predator on pondlife), bass (a predator on sunfish), and gar (a competitor with bass for sunfish). As a final activity, students explore the effect of fishing on the system.

USING THE SIMULATION

1. Elements of the ecosystem are introduced by several sliders. Set sunlight to some value greater than 1000 and algae to some number greater than 0. Click on the light blue SETUP button to populate the pond with the chosen initial starting biomass value for algae. Click the light blue GO button to start the simulation. Clicking the GO button a second time stops the simulation.

2. The BIOMASS bar graph displays currrent information regarding the relative biomasses of all living organisms. Two line graphs chart fluctuations in the relative biomasses of PRODUCERS and CONSUMERS as they change over time. (Note that to faciliate study a smaller y-scale is used to measure consumer biomass because biomasses associated with producers (plants) are always much larger than that associated with consumers in any stable ecosystem.

3. One can think about the dynamics of this ecosystem in terms of energy flow as follows:

SUNLIGHT ==> ALGAE ==> SUNFISH ==> BASS ==> FISHING

The flow of energy through almost all ecosystems requires the conversion of radiant energy from the sun into chemical energy by plants (producers) through the process of photosysnthesis. The presence of plants makes it possible for other organisms that lack the capacity to directly use sunlight energy (aka consumers) to survive in this ecosystem. Herbivores get energy from plants; carnivores get energy from herbivores and other carnivoes. Transfer of energy between levels as well as the use of energy by organisms results in its conversion from one form (e.g. chemical energy) to another form (e.g. mechanical energy). Such transformations are never perfect, they always involve the loss of energy in the form of heat, which dissipates into the surrounding environment and ultimately outer space. In the NetLogo-Population Dynamics simulation. algae represent producers, sunfish represent herbivores, and bass, gar and fisherman all represent carnivores.

The following step-wise appraach to this simulation can be cast as an attempt to figure out how to create the bess bass fishing pond possible. We know that a bass fishing pond will miniimally include sunlight, algae, sunfish, bass and the presence of fishermen. How do we determine which values will ensure the best bass fishing pond possible? We can figurre out how the elements of the bass pond are related to one another by systematically creating a series of ever more complicated pond ecosystems, beginning with a very simple system composed of sunlight and algae.

A SIMPLE ECOSYSTEM: A POND COMPOSED OF ALGAE
Algae (green) is the producer for this ecosystem. The first stage in our inquiry is to figure out what relationship (if any) exists between algae and sunlight. To do this we will study the effects of two different independent variables (amount of sunlight, initial-algae-biomass) on two dependent variables, the carrying capacity of the system for algae, A(k), and the time it takes to reach this carrying capacity, A(kt).

1. Stop the simulation if you haven't already done so by clicking on the GO button.
2. Set the sunlight value to 4,000 kilocalories per hectare and the initial-algae-biomass slider to 10 kilograms per hectare. Make sure all other sliders are set to zero and click the SETUP button to introduce algae into the pond.
3. Click the GO button to start the simulation. Observe the growth of the algae over time in the PRODUCERS graph.
4. After about 500 days, stop the simulation by clicking on the GO button once more. The curve depicted on the PRODUCERS graph is a classic example of a logorthmic growth curve.

The carrying capacity for a species represents an upper limit on the total number of organisms representing that species that can coexist together in that ecosystem once the system stabilizes. It is important to think of carrying capacities as dynamic equilibrium, in which the number of births is roughly equal to the number of deaths.
Thus, although the algae population continues to fluctuate over time, these fluctuations appear to converge upon a single biomass value, namely 6,200 kg/ha.This occurs after about 375 days.

At this point one can ask a series of "What if?" questions that represent separate experimnents, e.g. What if the sunlight value were higher (i.e. we considered a pond that was closer to the equator where it would receive more direct sunlight)? Will this affect the carrying capacity or the time it takes the system to reach it? Predict what you think will happen and then run the simulation using those values. Do at least three experimental runs and then analyze the results of your trials to see if you can detect any patterns. If you do, consider how an ecologist might explain the trend(s) you observe.

One can similarly ask what would happen if one chose a different initial-algae-biomass value to seed the pond. Predict what you think will happen and then run the simulation using those values. Do at least three experimental runs and then analyze the results of your trials to see if you can detect any patterns. If you do, consider how an ecologist might explain the trend(s) you observe.

A SLIGHTLY MORE COMPLICATED ECOSYSTEM: ADDDING SUNFISH
We can simulate the introduction of sunfish likewise by setting the initial-sunfish-biomass value to some number greater than zero. Again, try predicting what the effects of this introduction will be. It may be that the relationships previously observed between sunlight and initial-algae-biomass values on the carrying capacity and time it takes to reach the carrying capacity will no longer hold. We also want to consider what the effect of changing sunlight or the initial biomass values for algae and sunfish will be on the sunfish carrying capacity and the time it takes to reach its carrying capacity. For each of the independent variables (sunlight, initial-algae-biomass, initial-sunfish-biomass) conduct three experimental runs using different values. Measure the effects of each of these on the carrying capacities of the algae and sunfish, as well as the time it takes them to reach their carrying capacities. Do the patterns you observed in the simpler system still hold? Do you see any new patterns? Once more consider how an ecologist might explain your findings.

A MORE COMPLICATED ECOSYSTEM: ADDDING BASS
We can simulate the introduction of bass likewise by setting the initial-bass-biomass value to some number greater than zero. Again, try predicting what the effects of this introduction will be. It may be that the relationships previously observed between sunlight, initial-algae-biomass and initial-sunfish-biomass values on the carrying capacity and time it takes them to reach the carrying capacity will no longer hold. We also want to consider what the effect of changing sunlight or the initial biomass values for algae, sunfish and bass will be on the bass carrying capacity and the time it takes to reach its carrying capacity. For each of the independent variables (sunlight, initial-algae-biomass, initial-sunfish-biomass, initial-bass-biomass) conduct three experimental runs using different values. Measure the effects of each of these on the carrying capacities of the algae, sunfish and bass, as well as the time it takes them to reach their carrying capacities. Do the patterns you observed in the simpler system still hold? Do you see any new patterns? Once more consider how an ecologist might explain your findings.

AN EVEN MORE COMPLICATED ECOSYSTEM: ADDDING GAR
We can simulate competition in this ecosystem by adding gar, which like bass preys upon sunfish, by setting the initial-gar-biomass value to some number larger than zero. Predict what the effects of this introduction will be. Can bass and gar coexist over time in this system? Or does one go extinct? If the latter, is there some way (by changing the starting values for sunlight and initial-biomasses) to prevent this from happening? If you want to create the best bass fishing pond possible, what do these experiments tell you to do?

FINAL STEP: THE EFFECTS OF FISHING
The preceding steps will give students insight into how to maximize the bass population. As a final step we need to consider how much time per day the fisherman should fish on average to maximize his catch. After setting the other values to what you think will result in the largest bass population possible, shift the hours-fishing slider to one, two, three or four hours per day. Fishing begins on day 100 (after the system has stabilized), average yields are computed after one year on day 465. Is there a best amount of time the fisherman should fish to maximize his catch? If so, how might an ecologist explain this?

CREDITS AND REFERENCES

This is based on elements from the several WolfSheep Predation NetLogo Programs by Uri Wilensky and was inspired by an earlier simulated ecosystem program called "Environmental Decision Making", originally developed as part of the BioQuest Library by Elizabeth C. Odum, H.T. Odum, and Niles S. Peterson.

RELATED MODELS

Look at "Rabbit Grass Weeds" and "Wolf Sheep Predation" for other models of interacting populations with different rules.

VERSION

$Id$

(back to the NetLogo User Community Models)