MIHS-18 Period 5 Eden V, Munasip E, Andre B

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Default-person Eden Voss (Author)


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This is a simple model of population genetics. There are two populations, the REDS and the BLUES. Each has settable birth rates. The reds and blues move around and reproduce according to their birth rates. When the carrying capacity of the terrain is exceeded, some agents die (each agent has the same chance of being selected for death) to maintain a relatively constant population. The model allows you to explore how differential birth rates affect the ratio of reds to blues.


Each pass through the GO function represents a generation in the time scale of this model.

The CARRYING-CAPACITY slider sets the carrying capacity of the terrain. The model is initialized to have a total population of CARRYING-CAPACITY with half the population reds and half blues.

The RED-FERTILITY and BLUE-FERTILITY sliders sets the average number of children the reds and blues have in a generation. For example, a fertility of 3.4 means that each parent will have three children minimum, with a 40% chance of having a fourth child.

The # BLUES and # REDS monitors display the number of reds and blues respectively.

The GO button runs the model. A running plot is also displayed of the number of reds, blues and total population (in green).

The RUN-EXPERIMENT button lets you experiment with many trials at the same settings. This button outputs the number of ticks it takes for either the reds or the blues to die out given a particular set of values for the sliders. After each extinction occurs, the world is cleared and another run begins with the same settings. This way you can see the variance of the number of generations until extinction.


How does differential birth rates affect the population dynamics?

Does the population with a higher birth rate always start off growing faster?

Does the population with a lower birth rate always end up extinct?


Try running an experiment with the same settings many times.

Does one population always go extinct? How does the number of generations until extinction vary?


In this model, once the carrying capacity has been exceeded, every member of the population has an equal chance of dying. Try extending the model so that reds and blues have different saturation rates. How does the saturation rate compare with the birthrate in determining the population dynamics?

In this model, the original population is set to the carrying capacity (both set to CARRYING-CAPACITY). Would population dynamics be different if these were allowed to vary independently?

In this model, reds are red and blues blue and progeny of reds are always red, progeny of blues are always blue. What if you allowed reds to sometimes have blue progeny and vice versa? How would the model dynamics be different?


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

For the model itself:

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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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  red-count            ; population of red turtles
  blue-count           ; population of blue turtles
  yellow-count         ; population of yellow turtles

  fertility            ; the whole number part of fertility
  fertility-remainder  ; the fractional part (after the decimal point)

to setup

to setup-experiment
  create-turtles carrying-capacity
    setxy random-xcor random-ycor         ; randomize turtle locations
    ifelse who < (carrying-capacity / 3)  ; start out with equal numbers of reds, blues, and yellows
      [ set color blue ]
      [ set color red ]
      [ set color yellow ]
    set size 3                            ; easier to see

to go

;; to enable many repetitions with same settings

to go-experiment
  if red-count = 0
    output-print (word "red extinct after " ticks " generations")
  if blue-count = 0
    output-print (word "blue extinct after " ticks " generations")

to wander  ;; turtle procedure
  rt random-float 30 - random-float 30
  fd 1

to reproduce
  ask turtles
    ifelse color = red
      set fertility floor red-fertility
      set fertility-remainder red-fertility - (floor red-fertility)
      set fertility floor blue-fertility
      set fertility-remainder blue-fertility - (floor blue-fertility)
    ifelse (random-float 100) < (100 * fertility-remainder)
      [ hatch fertility + 1 [ wander ]]
      [ hatch fertility     [ wander ]]

;; kill turtles in excess of carrying capacity
;; note that reds and blues have equal probability of dying

to grim-reaper
  let num-turtles count turtles
  if num-turtles <= carrying-capacity
    [ stop ]
  let chance-to-die (num-turtles - carrying-capacity) / num-turtles
  ask turtles
    if random-float 1.0 < chance-to-die
      [ die ]

; Copyright 1997 Uri Wilensky.
; See Info tab for full copyright and license.

There is only one version of this model, created about 1 month ago by Eden Voss.

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