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Predicting the Electron Requirement for Carbon Fixation in Seas and Oceans
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 CO(2)-fixation directly, FRRf instead provide...
Autores principales: | , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2013
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3596381/ https://www.ncbi.nlm.nih.gov/pubmed/23516441 http://dx.doi.org/10.1371/journal.pone.0058137 |
Sumario: | 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 CO(2)-fixation directly, FRRf instead provides photosynthetic quantum efficiency estimates from which electron transfer rates (ETR) and ultimately CO(2)-fixation rates can be derived. Consequently, conversions of ETRs to CO(2)-fixation requires knowledge of the electron requirement for carbon fixation (Φ(e,C), ETR/CO(2) uptake rate) and its dependence on environmental gradients. Such knowledge is critical for large scale implementation of active fluorescence to better characterise CO(2)-uptake. Here we examine the variability of experimentally determined Φ(e,C) values in relation to key environmental variables with the aim of developing new working algorithms for the calculation of Φ(e,C) from environmental variables. Coincident FRRf and (14)C-uptake and environmental data from 14 studies covering 12 marine regions were analysed via a meta-analytical, non-parametric, multivariate approach. Combining all studies, Φ(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 Φ(e,C) was related to environmental gradients at global scales, region-specific analyses provided far improved predictive capability. However, use of regional Φ (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 Φ (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, Φ (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 Φ (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 Φ(e,C) to verify and develop algorithms with improved accuracy. |
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