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1. Reconciling models of primary production and photoacclimation [Invited]

   https://doi.org/10.1364/AO.386252  

   Sathyendranath, Shubha ; Platt, Trevor ; Kovač, Žarko ; Dingle, James ; Jackson, Thomas ; Brewin, Robert J. W. ; Franks, Peter ; Marañón, Emilio ; Kulk, Gemma ; Bouman, Heather A. ( April 2020 , Applied Optics)

   Primary production and photoacclimation models are two important classes of physiological models that find applications in remote sensing of pools and fluxes of carbon associated with phytoplankton in the ocean. They are also key components of ecosystem models designed to study biogeochemical cycles in the ocean. So far, these two classes of models have evolved in parallel, somewhat independently of each other. Here we examine how they are coupled to each other through the intermediary of the photosynthesis–irradiance parameters. We extend the photoacclimation model to accommodate the spectral effects of light penetration in the ocean and the spectral sensitivity of the initial slope of the photosynthesis–irradiance curve, making the photoacclimation model fully compatible with spectrally resolved models of photosynthesis in the ocean. The photoacclimation model contains a parameter${\mathrm{\theta <\#comment/>}}_m$, which is the maximum chlorophyll-to-carbon ratio that phytoplankton can attain when available light tends to zero. We explore how size-class-dependent values of${\mathrm{\theta <\#comment/>}}_m$could be inferred from field data on chlorophyll and carbon content in phytoplankton, and show that the results are generally consistent with lower bounds estimated from satellite-based primary production calculations. This was accomplished using empirical models linking phytoplankton carbon and chlorophyll concentration, and the range of values obtained in culture measurements. We study the equivalence between different classes of primary production models at the functional level, and show that the availability of a chlorophyll-to-carbon ratio facilitates the translation between these classes. We discuss the importance of the better assignment of parameters in primary production models as an important avenue to reduce model uncertainties and to improve the usefulness of satellite-based primary production calculations in climate research.

    

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2. Acclimation of Phytoplankton Fe:C Ratios Dampens the Biogeochemical Response to Varying Atmospheric Deposition of Soluble Iron

   https://doi.org/10.1029/2022GB007491  

   Wiseman, N. A. ; Moore, J. K. ; Twining, B. S. ; Hamilton, D. S. ; Mahowald, N. M. ( April 2023 , Global Biogeochemical Cycles)

   Dissolved iron (dFe) plays an important role in regulating marine productivity. In high nutrient, low chlorophyll regions (>33% of the global ocean), iron is the primary growth limiting nutrient, and elsewhere iron can regulate nitrogen fixation by diazotrophs. The link between iron availability and carbon export is strongly dependent on the phytoplankton iron quotas or cellular Fe:C ratios. This ratio varies by more than an order of magnitude in the open ocean and is positively correlated with ambient dFe concentrations in field observations. Representing Fe:C ratios within models is necessary to investigate how ocean carbon cycling will interact with perturbations to iron cycling in a changing climate. The Community Earth System Model ocean component was modified to simulate dynamic, group‐specific, phytoplankton Fe:C that varies as a function of ambient iron concentration. The simulated Fe:C ratios improve the representation of the spatial trends in the observed Fe:C ratios. The acclimation of phytoplankton Fe:C ratios dampens the biogeochemical response to varying atmospheric deposition of soluble iron, compared to a fixed Fe:C ratio. However, varying atmospheric soluble iron supply has first order impacts on global carbon and nitrogen fluxes and on nutrient limitation spatial patterns. Our results suggest that pyrogenic Fe is a significant dFe source that rivals mineral dust inputs in some regions. Changes in dust flux and iron combustion sources (anthropogenic and wildfires) will modify atmospheric Fe inputs in the future. Accounting for dynamic phytoplankton iron quotas is critical for understanding ocean biogeochemistry and projecting its response to variations in atmospheric deposition.

    

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3. Photopigment, Absorption, and Growth Responses of Marine Cryptophytes to Varying Spectral Irradiance

   https://doi.org/10.1111/jpy.12962  

   Heidenreich, Kristin M. ; Richardson, Tammi L. ; Collier, ed., J. ( February 2020 , Journal of Phycology)

   The underwater light field of lakes, estuaries, and oceans may vary greatly in spectral composition. Phytoplankton in these environments must contain pigments that absorb the available colors of light. If spectral quality changes, acclimation to the new spectral environment would confer an ecological advantage in terms of photosynthesis and growth. Here, we explored the capacity of eight marine cryptophytes to adjust pigmentation in response to changes in spectral irradiance and related effects on light absorption, photosynthetically useable radiation (PUR), and growth rate. The pigment composition of all species changed in some way in response to shifts in spectral irradiance, but not all pigment changes could be considered advantageous in the context of chromatic acclimation. For most species, absorption by chl‐aand chl‐c₂resulted in highest absorption in the blue region, highestPURvalues for blue‐light grown cells, and highest growth rates in blue light. The exception wasChroomonas mesostigmatica(CCMP1168), which contains a high percentage of Cryptophyte‐Phycocyanin (Cr‐PC) 645, absorbs strongly in the orange‐to‐red region of the spectrum, and grew fastest under red light. The position and magnitude of the maximum and secondary absorption peak of Cr‐PC569, the phycobiliprotein pigment ofHemiselmis cryptochromatica, varied with spectral irradiance. The underlying cause remains unknown, but may represent a mechanism by which cryptophytes optimize photon capture.

    

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4. Integrating Trait‐Based Stoichiometry in a Biogeochemical Inverse Model Reveals Links Between Phytoplankton Physiology and Global Carbon Export

   https://doi.org/10.1029/2023GB007986  

   Sullivan, Megan R. ; Primeau, François W. ; Hagstrom, George I. ; Wang, Wei‐Lei ; Martiny, Adam C. ( March 2024 , Global Biogeochemical Cycles)

   The elemental ratios of carbon, nitrogen, and phosphorus (C:N:P) within organic matter play a key role in coupling biogeochemical cycles in the global ocean. At the cellular level, these ratios are controlled by physiological responses to the environment. But linking these cellular‐level processes to global biogeochemical cycles remains challenging. We present a novel model framework that combines knowledge of phytoplankton cellular functioning with global scale hydrographic data, to assess the role of variable carbon‐to‐phosphorus ratios (R_C:P) on the distribution of export production. We implement a trait‐based mechanistic model of phytoplankton growth into a global biogeochemical inverse model to predict global patterns of phytoplankton physiology and stoichiometry that are consistent with both biological growth mechanisms and hydrographic carbon and nutrient observations. We compare this model to empirical parameterizations relatingR_C:Pto temperature or phosphate concentration. We find that the way the model represents variable stoichiometry affects the magnitude and spatial pattern of carbon export, with globally integrated fluxes varying by up to 10% (1.3 Pg C yr⁻¹) across models. Despite these differences, all models exhibit strong consistency with observed dissolved inorganic carbon and phosphate concentrations (R² > 0.9), underscoring the challenge of selecting the most accurate model structure. We also find that the choice of parameterization impacts the capacity of changingR_C:Pto buffer predicted export declines. Our novel framework offers a pathway by which additional biological information might be used to reduce the structural uncertainty in model representations of phytoplankton stoichiometry, potentially improving our capacity to project future changes.

    

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5. Impact of Lagrangian Sea Surface Temperature Variability on Southern Ocean Phytoplankton Community Growth Rates

   https://doi.org/10.1029/2020GB006880  

   Zaiss, Jessica ; Boyd, Philip W. ; Doney, Scott C. ; Havenhand, Jon N. ; Levine, Naomi M. ( August 2021 , Global Biogeochemical Cycles)

   Ocean phytoplankton play a critical role in the global carbon cycle, contributing ∼50% of global photosynthesis. As planktonic organisms, phytoplankton encounter significant environmental variability as they are advected throughout the ocean. How this variability impacts phytoplankton growth rates and population dynamics remains unclear. Here, we systematically investigated the impact of different rates and magnitudes of sea surface temperature (SST) variability on phytoplankton community growth rates using surface drifter observations from the Southern Ocean (>30°S) and a phenotype‐based ecosystem model. Short‐term SST variability (<7 days) had a minimal impact on phytoplankton community growth rates. Moderate SST changes of 3–4°C over 7–45 days produced a large time lag between the temperature change and the biological response. The impact of SST variability on community growth rates was nonlinear and a function of the rate and magnitude of change. Additionally, the nature of variability generated in a Lagrangian reference frame (following trajectories of surface water parcels) was larger than that within an Eulerian reference frame (fixed point), which initiated different phytoplankton responses between the two reference frames. Finally, we found that these dynamics were not captured by the Eppley growth model commonly used in global biogeochemical models and resulted in an overestimation of community growth rates, particularly in dynamic, strong frontal regions of the Southern Ocean. This work demonstrates that the timescale for environmental selection (community replacement) is a critical factor in determining community composition and takes a first step towards including the impact of variability and biological response times into biogeochemical models.

    

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