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Modelling marine phytoplankton growth under eutrophic conditions
Flynn, K.J. (2005). Modelling marine phytoplankton growth under eutrophic conditions, in: Mills, D.K. et al. (Ed.) Contrasting approaches to understanding eutrophication effects on phytoplankton. Journal of Sea Research, 54(1): pp. 92-103
In: Mills, D.K.; Gowen, R.J. (Ed.) (2005). Contrasting approaches to understanding eutrophication effects on phytoplankton. Journal of Sea Research, 54(1). Elsevier: Amsterdam. 1-124 pp., more
In: Journal of Sea Research. Elsevier/Netherlands Institute for Sea Research: Amsterdam; Den Burg. ISSN 1385-1101, more
Peer reviewed article  

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    Eutrophication; Models; Nitrates; Phosphorus; Phytoplankton; Primary production; Silicates; Marine
Author keywords
    nitrate; silicate phosphorus; phytoplankton model; eutrophication

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  • Flynn, K.J.

    Comparisons are made between the behaviour of Monod, Shuter, different quota model formulations and a mechanistic model of algal physiology containing a full photoacclimative component (MAP2). All models were tuned so that for a notional diatom and a non-diatom under steady-state single factor (light, N, P, Si) limitation outputs were comparable. Each model, simulating diatom and non-diatom in competition, was then run within a simple dynamic ecosystem scenario. Even after some additional tuning to optimise the phytoplankton N:P:Si within the dynamic scenario, the Monod and Shuter models gave unrealistic descriptions of nutrient consumption; this is because the control of all nutrient uptake is keyed to the most limiting nutrient in these models. A model in which all three nutrients were described by quota terms performed even worse, using previously accumulated Si to incorrectly support diatom growth in the absence of external Si. These events have important implications for the simulated growth of subsequent generations of phytoplankton. The more complex quota and MAP2 models, both of which used a Monod-type term for Si-limitation, differed primarily in the use of a simple light-growth curve in the former versus a photoacclimation ability with chl:C as a state-variable in the latter. These models behaved in a similar but not exactly the same way. A comparison between the C-biomass output of MAP2 with transformed estimates of biomass from chl, assuming a fixed chl:C or chl:N, suggested potential for a serious under or over estimation of phytoplankton growth in models configured against real data assuming fixed chl:biomass ratios. It is recommended that for simulations of phytoplankton production in eutrophic conditions, which invariably involve multi-nutrient-light interactions, simple phytoplankton models are not used and that if possible a photoacclimative (or at least a variable chl:biomass) function should be employed to control the light interaction and provide a direct simulation of chl.

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