%0 journal article
%@ 0142-7873
%A Mandal, S.,Homma, H.,Priyadarshi, A.,Burchard, H.,Smith, S.L.,Wirtz, K.W.,Yamazaki, H.

%D 2016
%J Journal of Plankton Research
%N 4
%P 964-976 
%R doi:10.1093/plankt/fbw019
%T A 1D physical–biological model of the impact of highly intermittent phytoplankton distributions
%U https://doi.org/10.1093/plankt/fbw019
4 
%X Highly intermittent spatial variability of phytoplankton is observed ubiquitously in marine ecosystems, especially when measurements are performed at the micro-scale level. Therefore, theoretical developments and new modelling tools are required to understand the observed small-scale vertical structure and its relationship to ecosystem behaviour. Nearly all current ecosystem models are formulated entirely based on the mean field approximation, ignoring sub-grid scale variability. Even if such approximation may be reasonable for meso-scales (and above), it cannot account for micro-scale dynamics, which may also impact macroscopic properties at the larger scale. To consider intermittency of variables in plankton ecosystem models, we apply a newly developed modelling approach called the closure approach. Detailed simulations were conducted, combining fluid-dynamics of the 1D water column with the nutrient-phytoplankton closure ecosystem model for application to a site in the northern North Sea. Compared with a control model, which does not account for such intermittency, the closure model produced substantially different spatio-temporal patterns of mean phytoplankton biomass and growth rate, which depended on the overall level of variability. In this study, we (i) seek to explore the effects of sub-scale variability coupled with physical transport and (ii) begin to address the yet unresolved question of how to consistently model the advection and diffusion of the variances and co-variances used to represent sub-scale variability in the closure approach. Our results suggest that it may be necessary to account explicitly for the intermittent distribution of plankton and nutrients, even in large-scale biogeochemical models.