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 the spatial patterns of secondary forest succession above the current alpine tree line in the context of land use and climate change. Three scenarios are offered: (1) climate change, (2) land use change, (3) species composition.
Implemented as a virtual laboratory, this model explores transitions in land-use and livelihood decisions that emerge from changing local and global conditions.
The Pampas Model is an Agent-Based Model intended to explore the dynamics of structural and land use changes in agricultural systems of the Argentine Pampas in response to climatic, technological economic, and political drivers.
CHALMS simulates housing and land market interactions between housing consumers, developers, and farmers in a growing ex-urban area.
An agent-based model to investigate the history of irrigated agriculture in the Upper Guadiana Basin, Spain, in order to learn about the influence of farmers’ characteristics (inter alia profit orientation, risk aversion, skills, available labour force and farm size) on land-use change and associated groundwater over-use in this region.
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.