About the CoMSES Model Library more info
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.
Survival analysis and Population viability analysis of the Northern Bald Ibis
Sinah Drenske Viktoriia Radchuk Cédric Scherer Corinna Esterer Ingo Kowarik Johannes Fritz Stephanie Kramer-Schadt | Published Thu Aug 4 17:13:06 2022This is the full repository to run the survival analysis (in R) and run the population viability model and its analysis (NetLogo + R) of the Northern Bald Ibis (NBI) presented in the study
On the road to self-sustainability: Reintroduced migratory European Northern Bald Ibises (Geronticus eremita) still need management interventions for population viability
by Sinah Drenske, Viktoriia Radchuk, Cédric Scherer, Corinna Esterer, Ingo Kowarik, Johannes Fritz, Stephanie Kramer-Schadt
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Risks and Hedonics in Empirical Agent-based land market (RHEA) model
Koen de Koning Tatiana Filatova | Published Mon Apr 1 11:37:22 2019RHEA aims to provide a methodological platform to simulate the aggregated impact of households’ residential location choice and dynamic risk perceptions in response to flooding on urban land markets. It integrates adaptive behaviour into the spatial landscape using behavioural theories and empirical data sources. The platform can be used to assess: how changes in households’ preferences or risk perceptions capitalize in property values, how price dynamics in the housing market affect spatial demographics in hazard-prone urban areas, how structural non-marginal shifts in land markets emerge from the bottom up, and how economic land use systems react to climate change. RHEA allows direct modelling of interactions of many heterogeneous agents in a land market over a heterogeneous spatial landscape. As other ABMs of markets it helps to understand how aggregated patterns and economic indices result from many individual interactions of economic agents.
The model could be used by scientists to explore the impact of climate change and increased flood risk on urban resilience, and the effect of various behavioural assumptions on the choices that people make in response to flood risk. It can be used by policy-makers to explore the aggregated impact of climate adaptation policies aimed at minimizing flood damages and the social costs of flood risk.