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Predicting the Electron Requirement for Carbon Fixation in Seas and Oceans
Lawrenz, E.; Silsbe, G.; Capuzzo, E.; Ylöstalo, P.; Forster, R.M.; Simis, S.G.H.; Prásil, O.; Kromkamp, J.C.; Hickman, A.E.; Moore, C.M.; Geider, R.J.; Suggett, D.J. (2013). Predicting the Electron Requirement for Carbon Fixation in Seas and Oceans. PLoS One 8(3).
In: PLoS One. Public Library of Science: San Francisco. ISSN 1932-6203, more
Peer reviewed article  

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  • Lawrenz, E.
  • Silsbe, G., more
  • Capuzzo, E.
  • Ylöstalo, P.
  • Forster, R.M.
  • Simis, S.G.H.
  • Prásil, O.
  • Kromkamp, J.C., more
  • Hickman, A.E.
  • Moore, C.M.
  • Geider, R.J.
  • Suggett, D.J.

    Marine phytoplankton account for about 50% of all global net primary productivity (NPP). Active fluorometry, mainly Fast Repetition Rate fluorometry (FRRf), has been advocated as means of providing high resolution estimates of NPP. However, not measuring CO2-fixation directly, FRRf instead provides photosynthetic quantum efficiency estimates from which electron transfer rates (ETR) and ultimately CO2-fixation rates can be derived. Consequently, conversions of ETRs to CO2-fixation requires knowledge of the electron requirement for carbon fixation (Phi(e,C), ETR/CO2 uptake rate) and its dependence on environmental gradients. Such knowledge is critical for large scale implementation of active fluorescence to better characterise CO2-uptake. Here we examine the variability of experimentally determined Phi(e,C) values in relation to key environmental variables with the aim of developing new working algorithms for the calculation of Phi(e,C) from environmental variables. Coincident FRRf and C-14-uptake and environmental data from 14 studies covering 12 marine regions were analysed via a meta-analytical, non-parametric, multivariate approach. Combining all studies, Phi(e,C) varied between 1.15 and 54.2 mol e(-) (mol C)(-1) with a mean of 10.9 +/- 6.91 mol e(-) mol C)(-1). Although variability of Phi(e,C) was related to environmental gradients at global scales, region-specific analyses provided far improved predictive capability. However, use of regional Phi(e,C) algorithms requires objective means of defining regions of interest, which remains challenging. Considering individual studies and specific small-scale regions, temperature, nutrient and light availability were correlated with Phi(e,C) albeit to varying degrees and depending on the study/region and the composition of the extant phytoplankton community. At the level of large biogeographic regions and distinct water masses, Phi(e,C) was related to nutrient availability, chlorophyll, as well as temperature and/or salinity in most regions, while light availability was also important in Baltic Sea and shelf waters. The novel Phi(e,C) algorithms provide a major step forward for widespread fluorometry-based NPP estimates and highlight the need for further studying the natural variability of Phi(e,C) to verify and develop algorithms with improved accuracy.

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