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.
Please check out our model archive tutorial or contact us if you have any questions or concerns about archiving your model.
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 aim of this model is to explore and understand the factors driving adoption of treatment strategies for ecological disturbances, considering payoff signals, learning strategies and social-ecological network structure
Exploring how learning and social-ecological networks influence management choice set and their ability to increase the likelihood of species coexistence (i.e. biodiversity) on a fragmented landscape controlled by different managers.
This model aims to investigate how different type of learning (social system) and disturbance specific attributes (ecological system) influence adoption of treatment strategies to treat the effects of ecological disturbances.
The model includes different formulations how agents make decisions in irrigation games and this is compared with empirical data. The aim is to test different theoretical models, especially explaining effect of communication.
The model objective’s is to explore the management choice set to uncover which subsets of strategies are most effective at maximizing species coexistence on a fragmented landscape.
Comparing 7 alternative models of human behavior and assess their performance on a high resolution dataset based on individual behavior performance in laboratory experiments.
A simple model to assess the effect of connectivity on interacting species (i.e. predator-prey type)
A very simple model elaborated to explore what may happens when buyers (travelers) have more information than sellers (tourist destinations)