Mathematical Basis for Diatom Growth Modeling

Sardari, Dariush

doi:10.1002/9781119751939.ch5

Cited by 2 publications

(1 citation statement)

References 45 publications

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“…Therefore, the Michaelis-Menten (MM) function (Michaelis and Menten, 1913), traditionally linked to enzyme kinetics but broadly applicable to various biological phenomena demonstrating an asymptotic behavior, was selected as the most suitable fitting function. This decision was supported by its demonstrated effectiveness in other biological contexts, such as growth modeling studies (Walters et al 2024;Sardari et al 2023). The MM function's adaptability stems from its simplicity, encapsulating the dynamics of planktonic Foraminifera test size distributions with only two parameters: the maximum potential abundance (( #*+ ) and the initial response rate or sharpness of the curve (+ ,*-. )…”

Section: Multiplication Factor Calculationmentioning

confidence: 99%

Size normalizing planktonic Foraminifera abundance in the water column

Chaabane,

Garidel-Thoron,

Giraud

et al. 2024

Preprint

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Planktonic Foraminifera have been collected from the water column with different plankton sampling devices equipped with nets of various mesh sizes, which impedes direct comparison of observed quantifications. Here, we use data on the community size structure of planktonic Foraminifera to assess the impact of mesh size on the measured abundance (ind/m 3 ) of planktonic Foraminifera. We use data from the FORCIS database (Chaabane et al., 2023) on the global ocean at different sampling depths over the past century. We find a global cumulative increase in abundance with size, which is best described using a Michaelis-Menten function.This function yields multiplication factors by which one size fraction can be normalized to any other size fraction equal to or larger than 100 µm. The resulting size normalization model is calibrated over a range of different depth intervals, and validated with an independent dataset from various depth ranges. The comparison to the Berger, 1969 equivalent catch approach shows a significant increase in the predictive skill of the model. The new size normalization scheme enables comparison of Foraminifera abundance data sampled with plankton nets of different mesh sizes, such as compiled in the FORCIS database. The correction methodology may be effectively employed for various other plankton groups such as diatoms and dinoflagellates.

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Section: Multiplication Factor Calculationmentioning

confidence: 99%

Size normalizing planktonic Foraminifera abundance in the water column

Chaabane,

Garidel-Thoron,

Giraud

et al. 2024

Preprint

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A Mathematical Model of Marine Mucilage, the Case of the Liga on the Basque Coast

Pierre,

Vallet

2023

Math. Model. Nat. Phenom.

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In this paper, we are interested in modeling the production of mucus by diatoms under the constraint of a nutrient limitation and carbon overabundance. The initial questioning comes from the observation of the so-called “liga” on the Aquitaine coast. The biological origin of the phenomenon is presented and discussed based on the existing literature. An original mathematical model incorporating mucus secretion is proposed and its theoretical properties are analized: well-posedness and differentiability with respect to the model parameters. Finally, numerical experiments are provided, investigating the possibility of parameter identification for the model using chemostat-type experiments.

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Mathematical Basis for Diatom Growth Modeling

Cited by 2 publications

References 45 publications

Size normalizing planktonic Foraminifera abundance in the water column

Size normalizing planktonic Foraminifera abundance in the water column

A Mathematical Model of Marine Mucilage, the Case of the Liga on the Basque Coast

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