Diagnosis of planktonic trophic network dynamics with sharp qualitative changes

Trophic interaction networks are notoriously difficult to understand and to diagnose. Such ecological networks welcome numerous feedbacks between species and populations and are not frozen at all, as soon as we observe them over a long enough term. These topological changes may be triggered by natural forcings (e.g. seasons) and/or by human influences (e.g. nutrient or pollution inputs). Aquatic trophic networks are especially dynamics and versatile, thus supporting new approaches for diagnosing network dynamics in a comprehensive way. In this study, we build a possibilistic model for this purpose. Borrowing discrete event models to theoretical computer sciences, we developed a mechanistic and qualitative model allowing computing exhaustive dynamics of a given trophic network. Once the model definition assumed, it provides all possible pathways of the trophic network from a chosen initial state. In a rigorous and analytical approach, we validated the model on one theoretical and two observed trajectories recorded at freshwater stations in La Rochelle region (Western France). The model appears easy to build and intuitive, and it provided other relevant pathways to the expert community. We hope such mathematical approach to open a new avenue in diagnosing and predicting trophic (and non-trophic) ecological networks. ### Competing Interest Statement The authors have declared no competing interest.