Computational Model Library

Displaying 10 of 16 results for "Kirstin Holfelder" clear search

We seek to improve understanding of roles enzyme play in soil food webs. We created an agent-based simulation of a simple food web that includes enzymatic activity. The model was used in a publication, Moore et al. (in press; Biochemistry).

Peer reviewed Evolution of Sex

Kristin Crouse | Published Sunday, June 05, 2016 | Last modified Monday, February 15, 2021

Evolution of Sex is a NetLogo model that illustrates the advantages and disadvantages of sexual and asexual reproductive strategies. It seeks to demonstrate the answer to the question “Why do we have sex?”

Peer reviewed Population Genetics

Kristin Crouse | Published Thursday, February 08, 2018 | Last modified Wednesday, September 09, 2020

This model simulates the mechanisms of evolution, or how allele frequencies change in a population over time.

Peer reviewed Dawkins Weasel

Kristin Crouse | Published Thursday, February 08, 2018 | Last modified Tuesday, February 04, 2020

Dawkins’ Weasel is a NetLogo model that illustrates the principle of evolution by natural selection. It is inspired by a thought experiment presented by Richard Dawkins in his book The Blind Watchmaker (1996).

Fertility Tradeoffs

Kristin Crouse | Published Tuesday, November 05, 2019 | Last modified Thursday, April 06, 2023

Fertility Tradeoffs is a NetLogo model that illustrates the emergencent tradeoffs between the quality and quantity of offspring. Often, we associate high fitness with maximizing the number of offspring. However, under certain circumstances, it pays instead to optimize the number of offspring, having fewer offspring than is possible. When the number of offspring is reduced, more energy can be invested in each offspring, which can have fitness benefits.

The Hawk-Dove Game

Kristin Crouse | Published Tuesday, November 05, 2019

This model simulates the Hawk-Dove game as first described by John Maynard Smith, and further elaborated by Richard Dawkins in “The Selfish Gene”. In the game, two strategies, Hawks and Doves, compete against each other, and themselves, for reproductive benefits. A third strategy can be introduced, Retaliators, which act like either Hawks or Doves, depending on the context.

Prisoner's Tournament

Kristin Crouse | Published Wednesday, November 06, 2019 | Last modified Wednesday, December 15, 2021

This model replicates the Axelrod prisoner’s dilemma tournaments. The model takes as input a file of strategies and pits them against each other to see who achieves the best payoff in the end. Change the payoff structure to see how it changes the tournament outcome!

BEGET Classic

Kristin Crouse | Published Monday, November 11, 2019 | Last modified Monday, November 25, 2019

BEGET Classic includes previous versions used in the classroom and for publication. Please check out the latest version of B3GET here, which has several user-friendly features such as directly importing and exporting genotype and population files.

The classic versions of B3GET include: version one and version three were used in undergraduate labs at the University of Minnesota to demonstrate principles in primate behavioral ecology; version two first demonstrated proof of concept for creating virtual biological organisms using decision-vector algorithms; version four was presented at the 2017 annual meeting at the American Association of Physical Anthropologists; version five was presented in a 2019 publication from the Journal of Human Evolution (Crouse, Miller, and Wilson, 2019).

Peer reviewed B3GET

Kristin Crouse | Published Thursday, November 14, 2019 | Last modified Tuesday, September 20, 2022

B3GET simulates populations of virtual organisms evolving over generations, whose evolutionary outcomes reflect the selection pressures of their environment. The model simulates several factors considered important in biology, including life history trade-offs, investment in fighting ability and aggression, sperm competition, infanticide, and competition over access to food and mates. Downloaded materials include starting genotype and population files. Edit the these files and see what changes occur in the behavior of virtual populations!

View the B3GET user manual here.

Peer reviewed Lethal Geometry

Kristin Crouse | Published Friday, February 21, 2020 | Last modified Wednesday, December 15, 2021

LethalGeometry was developed to examine whether territory size influences the mortality risk for individuals within that territory. For animals who live in territoral groups and are lethally aggressive, we can expect that most aggression occurs along the periphery (or border) between two adjacent territories. For territories that are relatively large, the periphery makes up a proportionately small amount of the of the total territory size, suggesting that individuals in these territories might be less likely to die from these territorial skirmishes. LethalGeometry examines this geometric relationship between territory size and mortality risk under realistic assumptions of variable territory size and shape, variable border width, and stochastic interactions and movement.

The individuals (agents) are programmed to walk randomly about their environment, search for and eat food to obtain energy, reproduce if they can, and act aggressively toward individuals of other groups. During each simulation step, individuals analyze their environment and internal state to determine which actions to take. The actions available to individuals include moving, fighting, and giving birth.

Displaying 10 of 16 results for "Kirstin Holfelder" clear search

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