Preprints
https://doi.org/10.5194/gmd-2020-396
https://doi.org/10.5194/gmd-2020-396

Submitted as: model description paper 12 Feb 2021

Submitted as: model description paper | 12 Feb 2021

Review status: this preprint is currently under review for the journal GMD.

FABM-NflexPD 1.0: Assessing an Instantaneous Acclimation Approach for Modelling Phytoplankton Growth

Onur Kerimoglu1,2, Prima Anugerahanti3, and Sherwood Lan Smith3 Onur Kerimoglu et al.
  • 1Institute for Chemistry and Biology of the Marine Environment, University of Oldenburg, Germany
  • 2Helmholtz Center for Coastal Research, Germany
  • 3Earth SURFACE Research Center, Research Institute for Global Change, JAMSTEC, Japan

Abstract. Coupled physical-biogeochemical models can generally reproduce large-scale patterns of primary production and biogeochemistry, but they often underestimate observed variability and gradients. This is partially caused by insufficient representation of systematic variations in the elemental composition and pigment density of phytoplankton. Although progress has been made through approaches accounting for the dynamics of phytoplankton composition with additional state variables, formidable computational challenges arise when these are applied in spatially explicit setups. The Instantaneous Acclimation (IA) approach addresses these challenges by assuming that Chl : C : nutrient ratios are instantly optimized locally (within each modelled grid cell, at each timestep), such that they can be resolved as diagnostic variables. Here we present the first tests of IA in an idealized, 1D setup: we implemented the IA in the Framework for Aquatic Biogeochemical Models (FABM), and coupled it with the General Ocean Turbulence Model (GOTM) to simulate the spatio-temporal dynamics in a 1-D water column. We show that the IA model and a fully dynamic, otherwise equivalently acclimative (DA) variant with an additional state variable behave similarly, and both resolve nutrient and growth dynamics not captured by a third, non-acclimative and fixed-stoichiometry (FS) variant.

Onur Kerimoglu et al.

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • CEC1: 'Comment on gmd-2020-396', Juan Antonio Añel, 23 Feb 2021
    • AC1: 'Reply on CEC1', Onur Kerimoglu, 10 May 2021
      • CEC2: 'Reply on AC1', Juan Antonio Añel, 14 May 2021
        • AC2: 'Reply on CEC2', Onur Kerimoglu, 14 May 2021
  • RC1: 'Comment on gmd-2020-396', Anonymous Referee #1, 24 May 2021
  • RC2: 'Comment on gmd-2020-396', Anonymous Referee #2, 23 Jun 2021

Onur Kerimoglu et al.

Onur Kerimoglu et al.

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Latest update: 29 Jul 2021
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Short summary
In large-scale models, variations in cellular composition of phytoplankton are often insufficiently represented. Detailed modelling approaches exist, but they require additional state variables that increase the computational costs. In this study, we test an instantaneous acclimation model in a spatially explicit setup, and show that its behavior is similar to that of a variant with an additional state variable, but significantly different from that of a fixed composition variant.