On phytoplankton aggregation: a view from an IBM approach

Abstract

In this paper, we build up an individual-based model (IBM) that describes the aggregative behavior in phytoplankton. The processes in play at the individual level (an individual = a phytoplankton cell) are: a random dispersal, a displacement due to the net effect of cells present in a suitable neighborhood (spatial interactions) and a branching (cell division and death). The IBM model provides a virtual world where phytoplankton cells appear to form clusters. Using this model, we explore the spatial structure of phytoplankton and present some numerical simulations that help the understanding of the aggregation phenomenon. To cite this article: N.

Numerical Simulations of a Nonlinear Stochastic Partial Differential Equation Modeling Phytoplankton Aggregation

“…(1) in [0, T ] × Ω, where Ω = ]0, L[ is a bounded domain with boundary ∂Ω in R, x is a one dimensional coordinate, t is time. The motivation in studying this SPDE is that equation (1) arises as a model of phytoplankton aggregation ( [9], [10], [11], [12]). In fact, the authors in ( [9], [10], [11], [12]) have investigated an individual-based model (IBM) of a population of phytoplankton that takes into account small scales biological mechanisms for phytoplankton cells.…”

“…The motivation in studying this SPDE is that equation (1) arises as a model of phytoplankton aggregation ( [9], [10], [11], [12]). In fact, the authors in ( [9], [10], [11], [12]) have investigated an individual-based model (IBM) of a population of phytoplankton that takes into account small scales biological mechanisms for phytoplankton cells. These processes are: random dispersal of phytoplankton cells due to turbulence, spatial interactions between phytoplankton cells caused by chemical signals and random division and death of phytoplankton cells.…”

Analysis on the dynamic mechanism of Acetes aggregation near a nuclear power cooling water system based on the Lagrangian flow network

“…However, this statistical model cannot reveal the dynamic mechanisms. Therefore, the particle tracking model (Hufnagl et al, 2017) or the individualbased model (IBM) (El Saadi and Bah, 2006;Falcini et al, 2020) is often applied to study the transport of biological particles, but describing the transport pathway and the connectivity between regions from complex particle trajectories is quite difficult.…”