Modelling a pike (Esox lucius) population in a lowland river using a cellular automaton

Abstract

Cellular automata (CAs) allow for transparent modelling of complex systems based on simple transition rules and are flexible in incorporating individual differences and local interactions. They may therefore be particularly suited to answer river management questions that could not be addressed by existing habitat suitability models, such as the optimal distance between spawning grounds. This study explores the usability of CAs for spatio-temporal modelling of a pike population to support river management. Specifically, we evaluated the usability of the CA model by analyzing its sensitivity to three model parameters: the number of pike in the grid, the initial pike distribution and the grid resolution. The model includes habitat characteristics and basic expert knowledge on the ecology of pike and was tested on a 10km stretch of the river Yser in Flanders (Belgium). Simulation results showed that the model converged to a realistic pike distribution over the study area only at high pike density and low grid resolution, irrespective of the initial pike distribution. Pike density and grid resolution affected the sensitivity to the initial pike distribution in the grid. Specifically, the sensitivity was high at low pike density and high grid resolution, and absent when pike density was high. This analysis indicated that initial conditions and cell size may have a severe impact on the model output, illustrating the importance of firstly analyzing this impact before conducting further analyses. Depending on the outcome of such analyses, CAs can be a promising modelling technique to evaluate and predict the effect of river restoration on pike populations.