Computational Model Library

An empirical ABM for regional land use/cover change: a Dutch case study

Diego Valbuena | Published Sat Mar 12 12:58:20 2011 | Last modified Thu Nov 11 09:55:25 2021

This is an empirical model described in http://dx.doi.org/10.1016/j.landurbplan.2010.05.001. The objective of the model is to simulate how the decision-making of farmers/agents with different strategies can affect the landscape structure in a region in the Netherlands.

Charcoal Record Simulation Model (CharRec)

Grant Snitker | Published Mon Nov 16 14:48:43 2015 | Last modified Thu Sep 30 15:39:55 2021

This model (CharRec) creates simulated charcoal records, based on differing natural and anthropogenic patterns of ignitions, charcoal dispersion, and deposition.

This code is for an agent-based model of collective problem solving in which agents with different behavior strategies, explore the NK landscape while they communicate with their peers agents. This model is based on the famous work of Lazer, D., & Friedman, A. (2007), The network structure of exploration and exploitation.

Peer reviewed Multilevel Group Selection I

Garry Sotnik Thaddeus Shannon Wayne W. Wakeland | Published Tue Apr 21 18:07:27 2020 | Last modified Sat Jul 3 20:38:55 2021

The Multilevel Group Selection I (MGS I) model simulates a population of contributing and non-contributing agents, competing on a social landscape for higher-value spots in an effort to withstand some selection pressure. It may be useful to both scientists and students in hypothesis testing, theory development, or more generally in understanding multilevel group selection.

Peer reviewed Evolution of Ecological Communities: Testing Constraint Closure

Steve Peck | Published Sun Dec 6 19:37:54 2020 | Last modified Fri Apr 16 22:17:46 2021

Ecosystems are among the most complex structures studied. They comprise elements that seem both stable and contingent. The stability of these systems depends on interactions among their evolutionary history, including the accidents of organisms moving through the landscape and microhabitats of the earth, and the biotic and abiotic conditions in which they occur. When ecosystems are stable, how is that achieved? Here we look at ecosystem stability through a computer simulation model that suggests that it may depend on what constrains the system and how those constraints are structured. Specifically, if the constraints found in an ecological community form a closed loop, that allows particular kinds of feedback may give structure to the ecosystem processes for a period of time. In this simulation model, we look at how evolutionary forces act in such a way these closed constraint loops may form. This may explain some kinds of ecosystem stability. This work will also be valuable to ecological theorists in understanding general ideas of stability in such systems.

The model is designed to analyse the effects of mitigation measures on the European brown hare (Lepus europaeus), which is directly affected by ongoing land use change and has experienced widespread decline throughout Europe since the 1960s. As an input, we use two 4×4 km large model landscapes, which were generated by a landscape generator based on real field sizes and crop proportions and differed in average field size and crop composition. The crops grown annually are evaluated in terms of forage suitability, breeding suitability and crop richness for the hare. Six mitigation scenarios are implemented, defined by a 10 % increase in: (1) mixed silphie, (2) miscanthus, (3) grass-clover ley, (4) alfalfa, (5) set-aside, and (6) general crop richness. The model shows that that both landscape configuration and composition have a significant effect on hare population development, which responds particularly strongly to compositional changes.

Change and Senescence

André Martins | Published Tue Nov 10 20:28:59 2020

Agers and non-agers agent compete over a spatial landscape. When two agents occupy the same grid, who will survive is decided by a random draw where chances of survival are proportional to fitness. Agents have offspring each time step who are born at a distance b from the parent agent and the offpring inherits their genetic fitness plus a random term. Genetic fitness decreases with time, representing environmental change but effective non-inheritable fitness can increase as animals learn and get bigger.

HomininSpace

Fulco Scherjon | Published Fri Nov 25 12:00:02 2016 | Last modified Tue Oct 6 11:01:00 2020

A modelling system to simulate Neanderthal demography and distribution in a reconstructed Western Europe for the late Middle Paleolithic.

Sugarscape with spice

Marco Janssen | Published Tue Jan 14 17:09:12 2020 | Last modified Fri Sep 18 16:31:42 2020

This is a variation of the Sugarspace model of Axtell and Epstein (1996) with spice and trade of sugar and spice. The model is not an exact replication since we have a somewhat simpler landscape of sugar and spice resources included, as well as a simple reproduction rule where agents with a certain accumulated wealth derive an offspring (if a nearby empty patch is available).
The model is discussed in Introduction to Agent-Based Modeling by Marco Janssen. For more information see https://intro2abm.com/

Peer reviewed Population Genetics

Kristin Crouse | Published Thu Feb 8 22:07:51 2018 | Last modified Wed Sep 9 03:31:32 2020

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

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