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Easy, fast and reproducible Stochastic Cellular Automata with choucause asterix (*) to get italics
Alexandre Génin, Guillaume Dupont, Daniel Valencia, Mauro Zucconi, M. Isidora Ávila-Thieme, Sergio A. Navarrete, Evie A. WietersPlease use the format "First name initials family name" as in "Marie S. Curie, Niels H. D. Bohr, Albert Einstein, John R. R. Tolkien, Donna T. Strickland"
2024
<p style="text-align: justify;">Stochastic cellular automata (SCA) are models that describe spatial dynamics using a grid of cells that switch between discrete states over time. They are widely used to understand how small-scale processes scale up to affect ecological dynamics at larger spatial scales, and have been applied to a wide diversity of theoretical and applied problems in all systems, such as arid ecosystems, coral reefs, forests, bacteria, or urban growth.</p> <p style="text-align: justify;">Despite their wide applications, SCA implementations are often ad-hoc, lacking performance, guarantees of correctness and poorly reproducible. De novo implementation of SCA for each specific system and application also represents a major barrier for many practitioners. To provide a unifying, well-tested technical basis to this class of models and facilitate their implementation, we built chouca, an R package that translates definitions of SCA models into compiled code, and runs simulations in an efficient way.</p> <p style="text-align: justify;">chouca supports SCA based on rectangular grids where transition probabilities are defined for each cell, with performance typically two to three orders of magnitude above typical implementations in interpreted languages (e.g. R, Python), all while maintaining an intuitive interface in the R environment. Exact and mean-field simulations can be run, and both numerical and graphical results can be easily exported.</p> <p style="text-align: justify;">Besides providing better reproducibility and accessibility, a fast engine for SCA unlocks novel, computationally intensive statistical approaches, such as simulation-based inference of ecological interactions from field data, which represents by itself an important avenue for research. By providing an easy and efficient entry point to SCAs, chouca lowers the bar to the use of this class of models for ecologists, managers and general practitioners, providing a leveled-off reproducible platform while opening novel methodological approaches.</p>
You should fill this box only if you chose 'All or part of the results presented in this preprint are based on data'. URL must start with http:// or https://
https://doi.org/10.5281/zenodo.11567662You should fill this box only if you chose 'Scripts were used to obtain or analyze the results'. URL must start with http:// or https://
https://doi.org/10.5281/zenodo.11567662You should fill this box only if you chose 'Codes have been used in this study'. URL must start with http:// or https://
spatial ecology, spatial modelling, cellular automaton, R package, chouca
NonePlease indicate the methods that may require specialised expertise during the peer review process (use a comma to separate various required expertises).
Community ecology, Landscape ecology, Spatial ecology, Metacommunities & Metapopulations, Statistical ecology, Theoretical ecology
Pablo Inchausti <pablo.inchausti.f@gmail.com>, Juan Keymer <juan.keymer@uaysen.cl>, Aurélien Boyé <aurelien.tj.boye@gmail.com>, Ranjan Muthukrishnan <ranjan.muthukrishnan@gmail.com>, Jelmer Nijp <jelmer.nijp@kwrwater.nl>, Matthias Grenié <matthias.grenie@univ-grenoble-alpes.fr> No need for them to be recommenders of PCIEcology. Please do not suggest reviewers for whom there might be a conflict of interest. Reviewers are not allowed to review preprints written by close colleagues (with whom they have published in the last four years, with whom they have received joint funding in the last four years, or with whom they are currently writing a manuscript, or submitting a grant proposal), or by family members, friends, or anyone for whom bias might affect the nature of the review - see the code of conduct
e.g. John Doe [john@doe.com]
2024-03-11 10:54:39
Samuel Alizon