Computational Model Library

Peer reviewed MOOvPOPsurveillance

Aniruddha Belsare Matthew Gompper Joshua J Millspaugh | Published Tue Apr 4 17:03:40 2017 | Last modified Tue May 12 16:37:24 2020

MOOvPOPsurveillance was developed as a tool for wildlife agencies to guide collection and analysis of disease surveillance data that relies on non-probabilistic methods like harvest-based sampling.

Peer reviewed MOOvPOP

Aniruddha Belsare Matthew Gompper Joshua J Millspaugh | Published Mon Apr 10 20:03:42 2017 | Last modified Tue May 12 06:14:14 2020

MOOvPOP is designed to simulate population dynamics (abundance, sex-age composition and distribution in the landscape) of white-tailed deer (Odocoileus virginianus) for a selected sampling region.

This model is an extension of the Artificial Long House Valley (ALHV) model developed by the authors (Swedlund et al. 2016; Warren and Sattenspiel 2020). The ALHV model simulates the population dynamics of individuals within the Long House Valley of Arizona from AD 800 to 1350. Individuals are aggregated into households that participate in annual agricultural and demographic cycles. The present version of the model incorporates features of the ALHV model including realistic age-specific fertility and mortality and, in addition, it adds the Black Mesa environment and population, as well as additional methods to allow migration between the two regions.

As is the case for previous versions of the ALHV model as well as the Artificial Anasazi (AA) model from which the ALHV model was derived (Axtell et al. 2002; Janssen 2009), this version makes use of detailed archaeological and paleoenvironmental data from the Long House Valley and the adjacent areas in Arizona. It also uses the same methods as the original AA model to estimate annual maize productivity of various agricultural zones within the Long House Valley. A new environment and associated methods have been developed for Black Mesa. Productivity estimates from both regions are used to determine suitable locations for households and farms during each year of the simulation.

This model extends the original Artifical Anasazi (AA) model to include individual agents, who vary in age and sex, and are aggregated into households. This allows more realistic simulations of population dynamics within the Long House Valley of Arizona from AD 800 to 1350 than are possible in the original model. The parts of this model that are directly derived from the AA model are based on Janssen’s 1999 Netlogo implementation of the model; the code for all extensions and adaptations in the model described here (the Artificial Long House Valley (ALHV) model) have been written by the authors. The AA model included only ideal and homogeneous “individuals” who do not participate in the population processes (e.g., birth and death)–these processes were assumed to act on entire households only. The ALHV model incorporates actual individual agents and all demographic processes affect these individuals. Individuals are aggregated into households that participate in annual agricultural and demographic cycles. Thus, the ALHV model is a combination of individual processes (birth and death) and household-level processes (e.g., finding suitable agriculture plots).

As is the case for the AA model, the ALHV model makes use of detailed archaeological and paleoenvironmental data from the Long House Valley and the adjacent areas in Arizona. It also uses the same methods as the original model (from Janssen’s Netlogo implementation) to estimate annual maize productivity of various agricultural zones within the valley. These estimates are used to determine suitable locations for households and farms during each year of the simulation.

Peer reviewed CHIME ABM Hurricane Evacuation Model

Joshua Watts | Published Fri Mar 3 18:13:53 2017 | Last modified Wed May 29 19:07:52 2019

The CHIME ABM explores information distribution networks and agents’ protective decision making in the context of hurricane landfall.

Peer reviewed Hohokam Trade Networks Model

Joshua Watts | Published Sun Oct 26 01:07:30 2014

The Hohokam Trade Networks Model focuses on key features of the Hohokam economy to explore how differences in trade network topologies may show up in the archaeological record. The model is set in the Phoenix Basin of central Arizona, AD 200-1450.

This model is a small extension (rectangular layout) of Joshua Epstein’s (2001) model on development of thoughtless conformity in an artificial society of agents.

This model is based on Joshua Epstein’s (2001) model on development of thoughtless conformity in an artificial society of agents.

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