CoMSES Net maintains cyberinfrastructure to foster FAIR data principles for access to and (re)use of computational models. Model authors can publish their model code in the Computational Model Library with documentation, metadata, and data dependencies and support these FAIR data principles as well as best practices for software citation. Model authors can also request that their model code be peer reviewed to receive a DOI. All users of models published in the library must cite model authors when they use and benefit from their code.
CoMSES Net also maintains a curated database of over 7500 publications of agent-based and individual based models with additional metadata on availability of code and bibliometric information on the landscape of ABM/IBM publications that we welcome you to explore.
The model simulates agents in a spatial environment competing for a common resource that grows on patches. The resource is converted to energy, which is needed for performing actions and for surviving.
The model explores food distribution patterns that emerge in a small-scale non-agricultural group when sharing individuals engage in intentional consumption leveling with a given probability.
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.
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.
The purpose of the model is to simulate the cultural hitchhiking hypothesis to explore how neutral cultural traits linked with advantageous traits spread together over time
Our model is hybrid agent-based and equation based model for human air-borne infectious diseases measles. It follows an SEIR (susceptible, exposed,infected, and recovered) type compartmental model with the agents moving be-tween the four state relating to infectiousness. However, the disease model canswitch back and forth between agent-based and equation based depending onthe number of infected agents. Our society model is specific using the datato create a realistic synthetic population for a county in Ireland. The modelincludes transportation with agents moving between their current location anddesired destination using predetermined destinations or destinations selectedusing a gravity model.
MIOvPOPsurveillance is set up to simulate harvest-based chronic wasting disease (CWD) surveillance of white-tailed deer (Odocoileus virginianus) populations in select Michigan Counties. New regions can be readily added, also the model can be readily adapted for other disease systems and used for informed-decision making during planning and implementation stages of disease surveillance in wildlife and free-ranging species.
PoliSEA represents a continuous policy process cycle, integrated with the dynamics of a fishery social-ecological system. The policy process in the model is represented by interactions between policymakers and interest groups and subsequent voting during which policymaker decide to increase or decrease the fishing quota for the next season. Policymakers’ positions can be influenced by lobbying of interest groups or interest group coalitions. The quota adopted through the policy process determines the amount of fish that can be harvested from the fish population during the season.
An ABM simulating white-tailed deer population dynamics for selected Michigan counties. The model yields pre-harvest and post-harvest realistic population snapshots that can be used to initialize the surveillance model (MIOvPOPsurveillance) and the CWD transmission dynamics model (MIOvCWD) respectively.
The model aims at reproducing the evolution of the land-use in an agricultural territory at the plot scale. It enables to simulate the affectation of land-use, the crop rotation and technical operations for each plot of the different farms of the territory. It allows as well for crop farms to simulate the daily state of plots (sowed, plowed, harvested, biomass indicator). The model is used as an input for the water pollution model allowing to determine the flow of nitrate, phosphorus and suspended matter in the territory according to the landscape configuration.