PT  - JOURNAL ARTICLE
AU  - Hilaire Drouineau
AU  - Benjamin Planque
AU  - Christian Mullon
TI  - RCaN : a software for Chance and Necessity modelling
AID  - 10.1101/2021.06.09.447734
DP  - 2021 Jan 01
TA  - bioRxiv
PG  - 2021.06.09.447734
4099  - http://biorxiv.org/content/early/2021/06/10/2021.06.09.447734.short
4100  - http://biorxiv.org/content/early/2021/06/10/2021.06.09.447734.full
AB  - Uncertainty is a challenge in modelling ecological systems and has been a source of misunderstandings between modelers and non-modelers. The “Chance and Necessity” (CaN) modelling approach has been proposed to address this issue, in the case of trophic network modelling. CaN modelling focuses exploring food-web trajectories that can satisfy fundamental physical and biological laws, while being compatible with observations and domain knowledge. This type of approach can facilitate discussion among actors as it promotes sharing of information and does not presuppose any knowledge of modelling practices. It is therefore suitable for participatory modelling, i.e. a modelling approach in which different actors can confront their knowledge and understanding of the marine system and of the associated uncertainties.One important ingredient to achieve participatory modelling is the availability of a modelling platform that is efficient, fast and transparent, so that all actors can understand and follow the modelling steps and choices, and can rapidly visualize and discuss the results. But, until now, there existed no software to easily perform CaN modelling. Here, we present RCaN and RCaNconstructor. Combined, these provide the first tool to build CaN models in an intuitive way that is 1) suitable within participatory frameworks, 2) transparent, 4) computationally efficient, 5) fully documented through the provision of meta-information and 6) supportive of exploratory analyses through predefined graphical functions.Competing Interest StatementThe authors have declared no competing interest.