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## WHAT IS IT?

This model is an example of genetic drift. It shows that competing organisms, turtles of different colors, each with equal likelihood reproduction, will ultimately converge on one breed without any particular selection pressure.

## HOW IT WORKS

The model starts with a random distribution of colored turtles. They move by wiggling randomly across the world. Each turn, a turtle produces between 0 and 5 offspring, value that can be modified by the user. If the total number of turtles is greater than the original number, then turtles are randomly killed until the original number is restored. This can be achieved by randomly kill considering all turtles or by killing the older turtles first. When only one breed of turtles is alive it is said that the breed as come to fixation and the simulation ends.

## HOW TO USE IT

* The "setup" button initializes the model.
* The "go" button runs the model.
* Use the "colors" slider to select the number of competing colors (breeds).
* The "number" slider sets the number of turtles.
* Use the "walls" buttons to divide the world.
* Use the "remove-pop" button to randomly kill turtles and simulate bottle-neck effect.
* The "mutation-rate" buttons adds a turtle birth mutation rate.
* The "death-cause" chooser determines death cause when population exceeds "population" slider value.
* The "max-offspring" slider sets the maximum number of offspring for each turtles on each generation.
* Use the "clear-output" to clear the message log screen.

## THINGS TO TRY

This models adds several features compared to other models. It is recommended to change things one at a time and notice how that changes the outcome of the simulation. Here is a list of possible things to do:

Experiment with adding walls. When walls are added, groups of individuals can be geographically isolated. Groups that are geographically isolated with walls will often end up with a different dominant color than the larger population.

Experiment with the two different options of death cause. Run a few simulations for each type. Did you notice any difference?

Looking at the graphs, use the "remove-pop" button to randomly remove turtles from the world. How does that affect each alive breed?

Change the population value and keep the number of colors constant. How does that affect the number of generations that it takes for a breed to go to fixation? Then keep the population constant and change the number of colors. What is the effect this time? How many generations does it take before a breed goes extinct?

When introducing mutations fixation can take many generations. Try selecting continuous update instead of by tick. Furthermore, try unselecting the "view update" option and focus on the plots.

Experiment with the bottle-neck effect. For a more extreme scenario click the "remove-pop" button two or three times at once.

## THINGS TO NOTICE

Notice that often colors can get to quite a high population but still fail to win the race. Also notice that when a breed dies it can not come back, not even when mutation rate is greater than zero.

## EXTENDING THE MODEL

Add-ons to the model by Carlo Maley were kept (e.g. organisms moving more slowly).

Juan Garcia Mesa added a mutation rate option and the ability for fixation in each area when the world is divided by walls.

The grim reaper in the procedure death does a random harvesting of the population to keep it roughly constant. This might be somewhat like a natural environment with a limited food supply. Juan Garcia Mesa added an option where older turtles die first to simulate aging. Can you think of other ways to write this procedure? Are the results affected?

## RELATED MODELS

* GenDrift P global
* GenDrift P local
* GenDrift T interact
* GenDrift T reproduce
* Genetic Drift by Carlo Maley

## HOW TO CITE

If you mention this model or the NetLogo software in a publication, we ask that you include the citations below.

For the model itself:

* Wilensky, U. (1997). NetLogo GenDrift T reproduce model. http://ccl.northwestern.edu/netlogo/models/GenDriftTreproduce. Center for Connected Learning and Computer-Based Modeling, Northwestern University, Evanston, IL.

Please cite the NetLogo software as:

* Wilensky, U. (1999). NetLogo. http://ccl.northwestern.edu/netlogo/. Center for Connected Learning and Computer-Based Modeling, Northwestern University, Evanston, IL.

## COPYRIGHT AND LICENSE

Copyright 1997 Uri Wilensky.


This work is licensed under the Creative Commons Attribution-NonCommercial-ShareAlike 3.0 License. To view a copy of this license, visit https://creativecommons.org/licenses/by-nc-sa/3.0/ or send a letter to Creative Commons, 559 Nathan Abbott Way, Stanford, California 94305, USA.

Commercial licenses are also available. To inquire about commercial licenses, please contact Uri Wilensky at uri@northwestern.edu.

This model was created as part of the project: CONNECTED MATHEMATICS: MAKING SENSE OF COMPLEX PHENOMENA THROUGH BUILDING OBJECT-BASED PARALLEL MODELS (OBPML). The project gratefully acknowledges the support of the National Science Foundation (Applications of Advanced Technologies Program) -- grant numbers RED #9552950 and REC #9632612.

This model was converted to NetLogo as part of the projects: PARTICIPATORY SIMULATIONS: NETWORK-BASED DESIGN FOR SYSTEMS LEARNING IN CLASSROOMS and/or INTEGRATED SIMULATION AND MODELING ENVIRONMENT. The project gratefully acknowledges the support of the National Science Foundation (REPP & ROLE programs) -- grant numbers REC #9814682 and REC-0126227. Converted from StarLogoT to NetLogo, 2001.

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