Improving the Accuracy of Single Turnover Active Fluorometry (STAF) for the Estimation of Phytoplankton Primary Productivity (PhytoPP)

Boatman, Tobias G.; Geider, Richard J.; Oxborough, Kevin

doi:10.3389/fmars.2019.00319

Cited by 22 publications

(43 citation statements)

References 40 publications

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“…Moreover, from the point of view of implementing a method of parameter assignment for remote sensing applications, of the variables listed above, only sea-surface temperature can be retrieved directly from space. As the gaps in our knowledge of the biotic and abiotic factors governing variation in the PE parameters are slowly being filled by conventional 14 C productivity experiments conducted at sea, there is also the potential of acquiring information on the photosynthetic characteristics of marine phytoplankton in a non-intrusive manner and over wider spatio-temporal scales using single turnover active chlorophyll fluorometry [ 39 ], although the conversion of electron transport rates into primary productivity estimates remains a challenge [ 23 , 40 , 41 ].…”

Section: Resultsmentioning

confidence: 99%

Vertical structure in chlorophyll profiles: influence on primary production in the Arctic Ocean

Bouman

Jackson

Sathyendranath

et al. 2020

Phil. Trans. R. Soc. A.

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Subsurface chlorophyll maximum (SCM) layers are prevalent throughout the Arctic Ocean under stratified conditions and are observed both in the wake of retreating sea ice and in thermally stratified waters. The importance of these layers on the overall productivity of Arctic pelagic ecosystems has been a source of debate. In this study, we consider the three principal factors that govern productivity within SCMs: the shape of the chlorophyll profile, the photophysiological characteristics of phytoplankton and the availability of light in the layer. Using the information on the biological and optical parameters describing the vertical structure of chlorophyll, phytoplankton absorption and photosynthesis–irradiance response curves, a spectrally resolved model of primary production is used to identify the set of conditions under which SCMs are important contributors to water-column productivity. Sensitivity analysis revealed systematic errors in the estimation of primary production when the vertical distribution of chlorophyll was not taken into account, with estimates of water-column production using a non-uniform profile being up to 97% higher than those computed using a uniform one. The relative errors were shown to be functions of the parameters describing the shape of the biomass profile and the light available at the SCM to support photosynthesis. Given that SCM productivity is believed to be largely supported by new nutrients, it is likely that the relative contribution of SCMs to new production would be significantly higher than that to gross primary production. We discuss the biogeochemical and ecological implications of these findings and the potential role of new ocean sensors and autonomous underwater vehicles in furthering the study of SCMs in such highly heterogeneous and remote marine ecosystems. This article is part of the theme issue ‘The changing Arctic Ocean: consequences for biological communities, biogeochemical processes and ecosystem functioning'.

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Section: Resultsmentioning

confidence: 99%

Vertical structure in chlorophyll profiles: influence on primary production in the Arctic Ocean

Bouman

Jackson

Sathyendranath

et al. 2020

Phil. Trans. R. Soc. A.

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“…The concentration of PSII reaction center (RCII, nmol m −3 ) was estimated fluorometrically according to Oxborough et al [28] as follows: where K R is an instrument-specific constant (photons m −3 s −1 ), F o is the fluorescence intensity at the zeroth flashlet of a single turnover measurement when all RCII are open, and σ PSII is the absorption cross section of PSII photochemistry under dark (m 2 ). A recent study showed K R / E FRRf can vary among phytoplankton taxonomic group and growth condition, and affect estimation of productivity [62]. In this study, we did not examine sample-specific K R / E FRRf values.…”

Section: Methodsmentioning

confidence: 91%

Development of photosynthetic carbon fixation model using multi-excitation wavelength fast repetition rate fluorometry in Lake Biwa

Kazama

Hayakawa

Kuwahara

et al. 2020

Preprint

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Direct measurements of gross primary productivity (GPP) in the water column are essential, but can be spatially and temporally restrictive. Fast repetition rate fluorometry (FRRf) is a bio-optical technique based on chlorophyll a (Chl- a ) fluorescence that can estimate the electron transport rate (ETR PSII ) at photosystem II (PSII) of phytoplankton in real time. However, derivation of phytoplankton GPP in carbon units from ETR PSII remains challenging because the electron requirement for carbon fixation (Ф e,C ) can vary depending on multiple factors. Also, the FRRf is still relatively novel, especially in freshwater ecosystems where phosphorus limitation and cyanobacterial blooms are common. The goal of the present study is to construct a robust Ф e,C model for freshwater ecosystems using simultaneous measurements of ETR PSII by FRRf with multi-excitation wavelengths coupled with traditional carbon fixation rate by the 13 C method. The study was conducted in oligotrophic and mesotrophic areas in Lake Biwa from July 2018 to May 2019. The combination of excitation light at 444, 512 and 633 nm correctly estimated ETR PSII of cyanobacteria. The range of Ф e,C in the phytoplankton community varied from 1.1 to 31.0 mol e − mol C −1 during the study period. Generalized liner model showed the best model including 12 physicochemical and biological factors explained 67% of the variance in Ф e,C . Among all factors, water temperature was the most significant, while PAR intensity was not. The GPP values estimated by FRRf ( GPP f ) with the best Ф e,C model relative to 13 C ( GPP 13C ) varied 0.5–1.5. Further, GPP f estimated with more parsimonious Ф e,C models were also comparable to GPP 13C . This study quantifies the applicability of the in situ FRRf methodology, and supports continuous monitoring of GPP by FRRf in lakes with large spatio-temporal variability of environmental conditions and phytoplankton assemblages.

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“…A recent study by Boatman et al. (2019) demonstrated that packaging of chlorophyll and light‐harvesting pigments into phytoplankton cells, referred to as the “package effect” (Kirk 1975, Bricaud et al. 1995) represents a potential source of error when calculating ETR PSII (and hence Φ e,C ) when using fluorometric estimation of [RCII] (FRRf) (e.g., Oxborough et al.…”

Section: Discussionmentioning

confidence: 99%

“…Specifically, this error arises when applying an instrument‐specific constant, K a , (m −1 ) not corrected to account for reabsorption of photons generated by PSII fluorescence within the cell before exiting, a phenomenon that increases in magnitude with increasing package effect (Boatman et al. 2019). While a corrective procedure is described by Boatman et al.…”

Section: Discussionmentioning

confidence: 99%

Taxonomic Variability in the Electron Requirement for Carbon Fixation Across Marine Phytoplankton

Hughes

Giannini

Ciotti

et al. 2020

Journal of Phycology

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Fast Repetition Rate fluorometry (FRRf) has been increasingly used to measure marine primary productivity by oceanographers to understand how carbon (C) uptake patterns vary over space and time in the global ocean. As FRRf measures electron transport rates through photosystem II (ETRPSII), a critical, but difficult to predict conversion factor termed the “electron requirement for carbon fixation” (Φe,C) is needed to scale ETRPSII to C‐fixation rates. Recent studies have generally focused on understanding environmental regulation of Φe,C, while taxonomic control has been explored by only a handful of laboratory studies encompassing a limited diversity of phytoplankton species. We therefore assessed Φe,C for a wide range of marine phytoplankton (n = 17 strains) spanning multiple taxonomic and size classes. Data mined from previous studies were further considered to determine whether Φe,C variability could be explained by taxonomy versus other phenotypic traits influencing growth and physiological performance (e.g., cell size). We found that Φe,C exhibited considerable variability (~4–10 mol e‐ · [mol C]−1) and was negatively correlated with growth rate (R2 = 0.7, P < 0.01). Diatoms exhibited a lower Φe,C compared to chlorophytes during steady‐state, nutrient‐replete growth. Inclusion of meta‐analysis data did not find significant relationships between Φe,C and class, or growth rate, although confounding factors inherent to methodological inconsistencies between studies likely contributed to this. Knowledge of empirical relationships between Φe,C and growth rate coupled with recent improvements in quantifying phytoplankton growth rates in situ, facilitate up‐scaling of FRRf campaigns to routinely derive Φe,C needed to assess ocean C‐cycling.

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Improving the Accuracy of Single Turnover Active Fluorometry (STAF) for the Estimation of Phytoplankton Primary Productivity (PhytoPP)

Cited by 22 publications

References 40 publications

Vertical structure in chlorophyll profiles: influence on primary production in the Arctic Ocean

Vertical structure in chlorophyll profiles: influence on primary production in the Arctic Ocean

Development of photosynthetic carbon fixation model using multi-excitation wavelength fast repetition rate fluorometry in Lake Biwa

Taxonomic Variability in the Electron Requirement for Carbon Fixation Across Marine Phytoplankton

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