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.
Peer reviewed Coupled demographic dynamics of herd and household in pastoral systems
Chelsea E Hunter Daniel C Peart Abigail Buffington Andrew Yoak Ian M Hamilton Mark Moritz | Published Sat Apr 8 14:32:18 2023This purpose of this model is to understand how the coupled demographic dynamics of herds and households constrain the growth of livestock populations in pastoral systems.
RaMDry - Rangeland Model in Drylands
Pascal Fust Eva Schlecht | Published Fri Jan 5 05:50:49 2018 | Last modified Fri Apr 1 07:09:52 2022RaMDry allows to study the dynamic use of forage ressources by herbivores in semi-arid savanna with an emphasis on effects of change of climate and management. Seasonal dynamics affects the amount and the nutritional values of the available forage.
Individual-based modelling as a tool for elephant poaching mitigation
Emily Neil Jens Koed Madsen Ernesto Carrella Nicolas Payette Richard Bailey | Published Tue Jun 18 14:07:24 2019 | Last modified Thu Aug 1 17:17:31 2019We develop an IBM that predicts how interactions between elephants, poachers, and law enforcement affect poaching levels within a virtual protected area. The model is theoretical at this stage and is not meant to provide a realistic depiction of poaching, but instead to demonstrate how IBMs can expand upon the existing modelling work done in this field, and to provide a framework for future research. The model could be further developed into a useful management support tool to predict the outcomes of various poaching mitigation strategies at real-world locations. The model was implemented in NetLogo version 6.1.0.
We first compared a scenario in which poachers have prescribed, non-adaptive decision-making and move randomly across the landscape, to one in which poachers adaptively respond to their memories of elephant locations and where other poachers have been caught by law enforcement. We then compare a situation in which ranger effort is distributed unevenly across the protected area to one in which rangers patrol by adaptively following elephant matriarchal herds.
Livestock drought insurance model
Felix John Birgit Müller Russell Toth Karin Frank Jürgen Groeneveld | Published Tue Dec 19 16:37:15 2017 | Last modified Sat Apr 14 13:56:11 2018The model analyzes the economic and ecological effects of a provision of livestock drought insurance for dryland pastoralists. More precisely, it yields qualitative insights into how long-term herd and pasture dynamics change through insurance.
Simulating the Transmission of Foot-And-Mouth Disease Among Mobile Herds in the Far North Region, Cameroon
Hyeyoung Kim Ningchuan Xiao Mark Moritz Rebecca Garabed Laura W Pomeroy | Published Wed Apr 13 14:35:33 2016This model simulates movements of mobile pastoralists and their impacts on the transmission of foot-and-mouth disease (FMD) in the Far North Region of Cameroon.
Peer reviewed Family Herd Demography
Abigail Buffington Andrew Yoak Ian M Hamilton Rebecca Garabed Mark Moritz | Published Mon Aug 15 19:41:24 2016 | Last modified Sat Jan 6 15:27:40 2018The model examines the dynamics of herd growth in African pastoral systems. We used it to examine the role of scale (herd size) stochasticity (in mortality, fertility, and offtake) on herd growth.