We analyzed a large dataset of simultaneous measurements of phytoplankton pigments, spectral specific absorption coefficient for phytoplankton [a*(l)], and photosynthesis versus irradiance (P versus E) curve parameters to examine the possible relationships between phytoplankton community structure and photophysiological properties at large spatial scales. Data were collected in various regions, mostly covering the trophic gradient encountered in the world's open ocean. The community composition is described in terms of biomass of three phytoplankton classes, determined using specific biomarker pigments. We present a general empirical model that describes the dependence of algal photophysiology on both the community composition and the relative irradiance within the water column (essentially reflecting photoacclimation). The application of the model to the in situ dataset enables the identification of vertical profiles of photophysiological properties for each phytoplankton class. The class-specific a*(l) obtained are consistent with results from the literature and with previous models developed for small and large cells, both in terms of the absolute values and the vertical patterns. Similarly, for the class-specific P versus E curve parameters, the magnitude and vertical distribution obtained with this method are coherent with previous observations. Large cells (mainly diatoms) may be more efficient in carbon storage than smaller cells, whereas their yield of light absorption is lower. We anticipate that such photophysiological parameterizations can improve primary production models by providing estimates of primary production that are specific to different phytoplankton classes on large scale.Estimates of marine primary production on large to global scales rely on the use of primary production models (e.g., Longhurst et al. 1995;Antoine et al. 1996;Behrenfeld et al. 2002a). Such models typically incorporate: (1) an estimate of the phytoplankton biomass, usually in the form of the chlorophyll a concentration ([Chl a], mg m 23 ); (2) the photosynthetically available irradiance (from 400 to 700 nm; PAR [mmol quanta m 22 s 21 ]); and (3) a relationship expressing changes in photosynthetic efficiency as a function of incident or absorbed irradiance. Although the mathematical description varies from one model to another (Behrenfeld and Falkowski 1997a), all models aim at parameterizing the primary production rate (P, mg C m 22 h 21 ) as followswhere a* is the chlorophyll-specific absorption coefficient of phytoplankton [m 2 (mg Chl a) 21 ], W c (PAR) is the irradiance-dependent quantum yield of carbon fixation [mol C (mol quanta) 21 ], and 12000 enables the conversion of moles of quanta into milligrams of carbon. Equation 1 includes two photophysiological variables: a* and W c (PAR). The relationship between their product, i.e., a* W c (PAR), and the incident PAR is often expressed by a photosynthesis versus irradiance (P vs. E) curve that can be represented by various mathematical formulations (see, for exa...
The photosynthesis‐irradiance (PE) relationship links indices of phytoplankton biomass (e.g. chl) to rates of primary production. The PE curve can be characterized by two variables: the light‐limited slope (αb) and the light‐saturated rate (Pbmax) of photosynthesis. Variability in PE curves can be separated into two categories: that associated with changes in the light saturation index, Ek (=Pbmax/αb) and that associated with parallel changes in αband Pbmax (i.e. no change in Ek). The former group we refer to as “Ek‐dependent” variability, and it results predominantly from photoacclimation (i.e. physiological adjustments in response to changing light). The latter group we refer to as “Ek‐independent” variability, and its physiological basis is unknown. Here, we provide the first review of the sporadic field and laboratory reports of Ek‐independent variability, and then from a stepwise analysis of potential mechanisms we propose that this important yet largely neglected phenomenon results from growth rate–dependent variability in the metabolic processing of photosynthetically generated reductants (and generally not from changes in the oxygen‐evolving PSII complexes). Specifically, we suggest that as growth rates decrease (e.g. due to nutrient stress), reductants are increasingly used for simple ATP generation through a fast (<1s) respiratory pathway that skips the carbon reduction cycle altogether and is undetected by standard PE methodologies. The proposed mechanism is consistent with the field and laboratory data and involves a simple new “twist” on established metabolic pathways. Our conclusions emphasize that simple reductants, not reduced carbon compounds, are the central currency of photoautotrophs.
Abstract.Iron is an essential nutrient involved in a variety of biological processes in the ocean, including photosynthesis, respiration and dinitrogen fixation. Atmospheric deposition of aerosols is recognized as the main source of iron for the surface ocean. In high nutrient, low chlorophyll areas, it is now clearly established that iron limits phytoplankton productivity but its biogeochemical role in low nutrient, low chlorophyll environments has been poorly studied. We investigated this question in the unexplored southeast Pacific, arguably the most oligotrophic area of the global ocean. Situated far from any continental aerosol source, the atmospheric iron flux to this province is amongst the lowest of the world ocean. Here we report that, despite low dissolved iron concentrations (∼0.1 nmol l −1 ) across the whole gyre (3 stations located in the center and at the western and the eastern edges), primary productivity are only limited by iron availability at the border of the gyre, but not in the center. The seasonal stability of the gyre has apparently allowed for the development of populations acclimated to these extreme oligotrophic conditions. Moreover, despite clear evidence of nitrogen limitation in the central gyre, we were unable to measure dinitrogen fixation in our experiments, even after iron and/or phosphate additions, and cyanobacterial nif H gene abundances were extremely low compared to the North Pacific Gyre. The South Pacific gyre is therefore unique with respect to the physiological status of its phytoplankton populations.
During summer, phytoplankton can bloom in the Arctic Ocean, both in open water and under ice, often strongly linked to the retreating ice edge. There, the surface ocean responds to steep lateral gradients in ice melt, mixing, and light input, shaping the Arctic ecosystem in unique ways not found in other regions of the world ocean. In 2016, we sampled a high-resolution grid of 135 hydrographic stations in Baffin Bay as part of the Green Edge project to study the ice-edge bloom, including turbulent vertical mixing, the under-ice light field, concentrations of inorganic nutrients, and phytoplankton biomass. We found pronounced differences between an Atlantic sector dominated by the warm West Greenland Current and an Arctic sector with surface waters originating from the Canadian archipelago. Winter overturning and thus nutrient replenishment was hampered by strong haline stratification in the Arctic domain, whereas close to the West Greenland shelf, weak stratification permitted winter mixing with high-nitrate Atlantic-derived waters. Using a space-for-time approach, we linked upper ocean dynamics to the phytoplankton bloom trailing the retreating ice edge. In a band of 60 km (or 15 days) around the ice edge, the upper ocean was especially affected by a freshened surface layer. Light climate, as evidenced by deep 0.415 mol m–2 d–1 isolumes, and vertical mixing, as quantified by shallow mixing layer depths, should have permitted significant net phytoplankton growth more than 100 km into the pack ice at ice concentrations close to 100%. Yet, under-ice biomass was relatively low at 20 mg chlorophyll-a m–2 and depth-integrated total chlorophyll-a (0–80 m) peaked at an average value of 75 mg chlorophyll-a m–2 only around 10 days after ice retreat. This phenological peak may hence have been the delayed result of much earlier bloom initiation and demonstrates the importance of temporal dynamics for constraints of Arctic marine primary production.
Abstract. Probably because it is a readily available ocean color product, almost all models of primary productivity use chlorophyll as their index of phytoplankton biomass. As other variables become more readily available, both from remote sensing and in situ autonomous platforms, we should ask if other indices of biomass might be preferable. Herein, we compare the accuracy of different proxies of phytoplankton biomass for estimating the maximum photosynthetic rate (Pmax) and the initial slope of the production versus irradiance (P vs. E) curve (α). The proxies compared are: the total chlorophyll a concentration (Tchla, the sum of chlorophyll a and divinyl chlorophyll), the phytoplankton absorption coefficient, the phytoplankton photosynthetic absorption coefficient, the active fluorescence in situ, the particulate scattering coefficient at 650 nm (bp (650)), and the particulate backscattering coefficient at 650 nm (bbp (650)). All of the data (about 170 P vs. E curves) were collected in the South Pacific Ocean. We find that when only the phytoplanktonic biomass proxies are available, bp (650) and Tchla are respectively the best estimators of Pmax and alpha. When additional variables are available, such as the depth of sampling, the irradiance at depth, or the temperature, Tchla becomes the best estimator of both Pmax and α. From a remote sensing perspective, error propagation analysis shows that, given the current algorithms errors for estimating bbp(650), Tchla remains the best estimator of Pmax.
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