Computational Model Library

Displaying 10 of 137 results for "Andrew Nelson" clear search

Socio-spatial segregation in Salzburg, Austria

Andreas Koch | Published Friday, September 25, 2009 | Last modified Saturday, April 27, 2013

This is a first preliminary simulation model to model segregation in the city of Salzburg, Austria.

segregation model with multiple variables and explit spatiality

Andreas Koch | Published Wednesday, October 28, 2009 | Last modified Saturday, April 27, 2013

This model is a more comprehensive version of the original model; descriptions and expanations are added

Musical Chairs

Andreas Angourakis | Published Wednesday, February 03, 2016 | Last modified Friday, March 11, 2016

This Agent-Based model intends to explore the conditions for the emergence and change of land use patterns in Central Asian oases and similar contexts.

Nice Musical Chairs

Andreas Angourakis | Published Friday, February 05, 2016 | Last modified Friday, November 17, 2017

The Nice Musical Chairs (NMC) model represent the competition for space between groups of stakeholders of farming and herding activities in the arid Afro-Eurasia.

This model simulates networking mechanisms of an empirical social network. It correlates event determinants with place-based geography and social capital production.

Overview

The Weather model is a procedural generation model designed to create realistic daily weather data for socioecological simulations. It generates synthetic weather time series for solar radiation, temperature, and precipitation using algorithms based on sinusoidal and double logistic functions. The model incorporates stochastic variation to mimic unpredictable weather patterns and aims to provide realistic yet flexible weather inputs for exploring diverse climate scenarios.

The Weather model can be used independently or integrated into larger models, providing realistic weather patterns without extensive coding or data collection. It can be customized to meet specific requirements, enabling users to gain a better understanding of the underlying mechanisms and have greater confidence in their applications.

A proof-of-concept agent-based model ‘SimDrink’, which simulates a population of 18-25 year old heavy alcohol drinkers on a night out in Melbourne to provide a means for conducting policy experiments to inform policy decisions.

This purpose of this model is to understand how the coupled demographic dynamics of herds and households constrain the growth of livestock populations in pastoral systems.

In CmLab we explore the implications of the phenomenon of Conservation of Money in a modern economy. This is one of a series of models exploring the dynamics of sustainable economics – PSoup, ModEco, EiLab, OamLab, MppLab, TpLab, CmLab.

Peer reviewed soslivestock model

Marco Janssen Irene Perez Ibarra Diego J. Soler-Navarro Alicia Tenza Peral | Published Wednesday, May 28, 2025 | Last modified Tuesday, June 10, 2025

The purpose of this model is to analyze how different management strategies affect the wellbeing, sustainability and resilience of an extensive livestock system under scenarios of climate change and landscape configurations. For this purpose, it simulates one cattle farming system, in which agents (cattle) move through the space using resources (grass). Three farmer profiles are considered: 1) a subsistence farmer that emphasizes self-sufficiency and low costs with limited attention to herd management practices, 2) a commercial farmer focused on profit maximization through efficient production methods, and 3) an environmental farmer that prioritizes conservation of natural resources and animal welfare over profit maximization. These three farmer profiles share the same management strategies to adapt to climate and resource conditions, but differ in their goals and decision-making criteria for when, how, and whether to implement those strategies. This model is based on the SequiaBasalto model (Dieguez Cameroni et al. 2012, 2014, Bommel et al. 2014 and Morales et al. 2015), replicated in NetLogo by Soler-Navarro et al. (2023).

One year is 368 days. Seasons change every 92 days. Each step begins with the growth of grass as a function of climate and season. This is followed by updating the live weight of animals according to the grass height of their patch, and grass consumption, which is determined based on the updated live weight. Animals can be supplemented by the farmer in case of severe drought. After consumption, cows grow and reproduce, and a new grass height is calculated. This updated grass height value becomes the starting grass height for the next day. Cows then move to the next area with the highest grass height. After that, cattle prices are updated and cattle sales are held on the first day of fall. In the event of a severe drought, special sales are held. Finally, at the end of the day, the farm balance and the farmer’s effort are calculated.

Displaying 10 of 137 results for "Andrew Nelson" clear search

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