Model Of Phytoplankton Growth Research Articles

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

AbstractThe 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 (RC: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 relating RC:P to 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 changing RC:P to 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.

Interactive effects of CO2 , temperature, irradiance, and nutrient limitation on the growth and physiology of the marine cyanobacterium Synechococcus (Cyanophyceae).

The marine cyanobacterium Synechococcus elongatus was grown in a continuous culture system to study the interactive effects of temperature, irradiance, nutrient limitation, and the partial pressure of CO2 (pCO2) on its growth and physiological characteristics. Cells were grown on a 14:10 h light:dark cycle at all combinations of low and high irradiance (50 and 300 μmol photons ⋅ m-2 ⋅ s-1 , respectively), low and high pCO2 (400 and 1000 ppmv, respectively), nutrient limitation (nitrate-limited and nutrient-replete conditions), and temperatures of 20-45°C in 5°C increments. The maximum growth rate was ~4.5 · d-1 at 30-35°C. Under nutrient-replete conditions, growth rates at most temperatures and irradiances were about 8% slower at a pCO2 of 1000 ppmv versus 400 ppmv. The single exception was 45°C and high irradiance. Under those conditions, growth rates were ~45% higher at 1000 ppmv. Cellular carbon:nitrogen ratios were independent of temperature at a fixed relative growth rate but higher at high irradiance than at low irradiance. Initial slopes of photosynthesis-irradiance curves were higher at all temperatures under nutrient-replete versus nitrate-limited conditions; they were similar at all temperatures under high and low irradiance, except at 20°C, when they were suppressed at high irradiance. A model of phytoplankton growth in which cellular carbon was allocated to structure, storage, or the light or dark reactions of photosynthesis accounted for the general patterns of cell composition and growth rate. Allocation of carbon to the light reactions of photosynthesis was consistently higher at low versus high light and under nutrient-replete versus nitrate-limited conditions.

Piecewise Linear Model of Phytoplankton Wave Propagation in Periodical Vortex Flow

A piecewise linear model of phytoplankton growth in the presence of a convective flow has been proposed in the paper. The model, in one-dimensional formulation, admits a stable autowave solution, propagating with a certain critical minimum velocity. The main purpose of the work is to study the features of the phytoplankton front propagation in the presence of vortex flow. The vortex flow represents chain of two-dimensional vortices described by the Taylor--Green solution of incompressible Navier--Stokes equations. Different regimes of wave propagation are revealed depending on the intensity of the vortex flow and the model parameters. In particular, the wobbling, zigzag, and jumping regimes are found if the velocity of convective flow is less or comparable, exceeds, and is much greater than the front propagation speed in still media, respectively. The front propagation velocity is characterized by definite types of dependence on the flow intensity in different regimes.

Control of a phytoplankton bloom by wind‐driven vertical mixing and light availability

AbstractThe balance of physical and biological processes governing phytoplankton growth rates and the accumulation of biomass is widely debated in the literature, notably during the winter–spring transition. Here we show, in a temperate shelf sea that variability in the depth of the actively mixing surface layer is the leading order control. During a 2‐week period preceding the peak of the spring bloom we observe two distinct regimes; first, growth within the euphotic zone during the day and re‐distribution of new biomass to the seasonal pycnocline at night by convective mixing; then, more rapid biomass accumulation trapped within a shallower, wind‐driven actively mixing layer that was decoupled from the pycnocline below. Our observations of the bloom in the Celtic Sea, Northwest European Shelf, were made using ocean gliders and include measurements of the dissipation of turbulent kinetic energy. A 1‐D phytoplankton growth model driven by our measurements of dissipation and incident irradiance replicates the observed bloom and reinforces the conclusion that physical processes that mediate light availability were key. Day‐to‐day variability in cloud cover and the ability of phytoplankton to acclimate to their light environment were also important factors in determining growth rates, and the timing of the biomass peak. Our results emphasize the need for accurate turbulent mixing parameterizations in coupled hydrodynamic‐ecosystem models. Our findings are applicable to any region where wind‐driven mixing can modify nutrient and light availability, especially across subpolar shelves in the northern hemisphere where light rather than nutrients is typically the limiting factor on phytoplankton growth.

Discrete numerical solution for modelling of Phytoplankton growth

Phytoplankton growth model has been observed extensively to track the movement of elements through aquatic food webs and ecological processes. This study is purposed to find numerical solution of The modelling of phytoplankton growth and know the dynamic behavior. The method used to transform the phytoplankton growth model is Finite Difference Euler Method. We focused on the existence and stability of the fixed-points. We break into two cases. The result is that all of cases is dynamically consistent with its continous model only for relatively small-step size. We present some numerical simulation to illustrate those cases. We break into two cases. The result is that all cases is dynamically consistent with its continous model only for relatively small-step size. We present some numerical simulation to illustrate those cases.

Less Nutrients but More Phytoplankton: Long-Term Ecosystem Dynamics of the Southern North Sea

We here assess long-term trends in marine primary producers in the southern North Sea (SNS) with respect to ongoing regional Earth system changes. We applied a coupled high-resolution (1.5–4.5 km) 3d-physical-biogeochemical regional Earth System model that includes an advanced phytoplankton growth model and benthic biogeochemistry to hindcast ecosystem dynamics in the period 1961–2012. We analyzed the simulation together with in situ observations. Coinciding with the decreasing nutrient level at the beginning of the 1990s, we find a surprising increase in phytoplankton in the German Bight, but not in the more offshore parts of the SNS. We explain these complex patterns by a series of factors which are lacking in many state-of-the-art coupled ecosystem models such as changed light availability and physiological acclimation in phytoplankton. We also show that many coastal time-series stations in the SNS are located in small patches where our model predicts an opposite trend than found for the surrounding waters. Together, these findings call for a reconsideration of current modeling and monitoring schemes.

Turbulent mixing and phytoplankton life history: a Lagrangian versus Eulerian model comparison

MEPS Marine Ecology Progress Series Contact the journal Facebook Twitter RSS Mailing List Subscribe to our mailing list via Mailchimp HomeLatest VolumeAbout the JournalEditorsTheme Sections MEPS 600:55-70 (2018) - DOI: https://doi.org/10.3354/meps12634 Turbulent mixing and phytoplankton life history: a Lagrangian versus Eulerian model comparison Jérémy Baudry1, Dany Dumont1,*, Irene R. Schloss2,3,4 1Institut des sciences de la mer de Rimouski (ISMER), Université du Québec à Rimouski (UQAR), Rimouski, Québec G5L 3A1, Canada 2Instituto Antártico Argentino, Buenos Aires, Argentina 3Centro Austral de Investigaciones Científicas (CADIC), CONICET, Argentina 4Universidad Nacional de Tierra del Fuego, Ushuaia, Argentina *Corresponding author: dany_dumont@uqar.ca ABSTRACT: Phytoplankton dynamics models follow either an Eulerian or a Lagrangian approach. The Eulerian formulation assumes that all individuals of a population living in homogeneous environmental conditions, i.e. within a model grid cell, are in a single average physiological state, which generally depends on local conditions. By tracking each individual cell or cluster of cells, the Lagrangian formulation allows population behaviour to emerge from a broader range of individual physiological states inherited from different life histories. In order to determine in which mixing conditions the widely used Eulerian approach differs from a more representative but also more computationally costly Lagrangian formulation, we compared the results obtained from a simple 1-dimensional phytoplankton growth model using both formulations under various mixing conditions. The chosen model is based on Droop kinetics, where growth is a function of light and an internal nutrient cell quota. It is applied in cases with constant and uniform diffusivity, and in more realistic cases of wind-induced and tidal mixing. The 2 main outcomes of our study are: (1) results from both formulations converge in weakly stratified environments for any level of turbulent mixing, and (2) results diverge in stratified environments and intermediate mixing up to a diffusivity value above which the environment appears homogeneous to moving cells, and both formulations converge. These results suggest that in heterogeneous and dynamic marine environments, strong variability among individuals may prevent Eulerian models from accurately predicting phytoplankton production. KEY WORDS: Biogeochemistry · Individual Based Modelling · Population Based Modelling · Intrapopulation variability Full text in pdf format PreviousNextCite this article as: Baudry J, Dumont D, Schloss IR (2018) Turbulent mixing and phytoplankton life history: a Lagrangian versus Eulerian model comparison. Mar Ecol Prog Ser 600:55-70. https://doi.org/10.3354/meps12634 Export citation RSS - Facebook - Tweet - linkedIn Cited by Published in MEPS Vol. 600. Online publication date: July 30, 2018 Print ISSN: 0171-8630; Online ISSN: 1616-1599 Copyright © 2018 Inter-Research.

A Framework for Understanding Variation in Pelagic Gross Primary Production of Lake Ecosystems

Light and nutrient availability are key physiological constraints for primary production. Widespread environmental changes are causing variability in loads of terrestrial dissolved organic carbon (DOC) and nutrients from watersheds to lakes, contributing to simultaneous changes in both light and nutrient supply. Experimental evidence highlights the potential for these watershed loads to create complex and context-dependent responses of within-lake primary production; however, the field lacks a predictive model to investigate these responses. We embedded a well-established physiological model of phytoplankton growth within an ecosystem model of nutrient and DOC supply to assess how simultaneous changes in DOC and nutrient loads could impact pelagic primary production in lakes. The model generated a unimodal relationship between GPP and DOC concentration when loads of DOC and nutrients were tightly correlated across space or time. In this unimodal relationship, the magnitude of the peak GPP was primarily determined by the DOC-to-nutrient ratio of the load, and the location of the peak along the DOC axis was primarily determined by lake area. Greater nutrient supply relative to DOC load contributed to greater productivity, and larger lake area increased light limitation for primary producers at a given DOC concentration, owing to the positive relationship between lake area and epilimnion depth. When loads of DOC and nutrients were not tightly correlated in space or time, the model generated a wedge-shaped pattern between GPP and DOC, consistent with spatial surveys from a global set of lakes. Our model is thus capable of unifying the diversity of empirically observed spatial and temporal responses of lake productivity to DOC and mineral nutrient supply presented in the literature, and provides qualitative predictions for how lake pelagic primary productivity may respond to widespread environmental changes.

The acclimative biogeochemical model of the southern North Sea

Abstract. Ecosystem models often rely on heuristic descriptions of autotrophic growth that fail to reproduce various stationary and dynamic states of phytoplankton cellular composition observed in laboratory experiments. Here, we present the integration of an advanced phytoplankton growth model within a coupled three-dimensional physical–biogeochemical model and the application of the model system to the southern North Sea (SNS) defined on a relatively high resolution (∼ 1.5–4.5 km) curvilinear grid. The autotrophic growth model, recently introduced by Wirtz and Kerimoglu (2016), is based on a set of novel concepts for the allocation of internal resources and operation of cellular metabolism. The coupled model system consists of the General Estuarine Transport Model (GETM) as the hydrodynamical driver, a lower-trophic-level model and a simple sediment diagenesis model. We force the model system with realistic atmospheric and riverine fluxes, background turbidity caused by suspended particulate matter (SPM) and open ocean boundary conditions. For a simulation for the period 2000–2010, we show that the model system satisfactorily reproduces the physical and biogeochemical states of the system within the German Bight characterized by steep salinity; nutrient and chlorophyll (Chl) gradients, as inferred from comparisons against observation data from long-term monitoring stations; sparse in situ measurements; continuous transects; and satellites. The model also displays skill in capturing the formation of thin chlorophyll layers at the pycnocline, which is frequently observed within the stratified regions during summer. A sensitivity analysis reveals that the vertical distributions of phytoplankton concentrations estimated by the model can be qualitatively sensitive to the description of the light climate and dependence of sinking rates on the internal nutrient reserves. A non-acclimative (fixed-physiology) version of the model predicted entirely different vertical profiles, suggesting that accounting for physiological flexibility might be relevant for a consistent representation of the vertical distribution of phytoplankton biomass. Our results point to significant variability in the cellular chlorophyll-to-carbon ratio (Chl : C) across seasons and the coastal to offshore transition. Up to 3-fold-higher Chl : C at the coastal areas in comparison to those at the offshore areas contribute to the steepness of the chlorophyll gradient. The model also predicts much higher phytoplankton concentrations at the coastal areas in comparison to its non-acclimative equivalent. Hence, findings of this study provide evidence for the relevance of physiological flexibility, here reflected by spatial and seasonal variations in Chl : C, for a realistic description of biogeochemical fluxes, particularly in the environments displaying strong resource gradients.

The Size Dependence of Phytoplankton Growth Rates: A Trade-Off between Nutrient Uptake and Metabolism

Rates of metabolism and population growth are often assumed to decrease universally with increasing organism size. Recent observations have shown, however, that maximum population growth rates among phytoplankton smaller than ∼6 μm in diameter tend to increase with organism size. Here we bring together observations and theory to demonstrate that the observed change in slope is attributable to a trade-off between nutrient uptake and the potential rate of internal metabolism. Specifically, we apply an established model of phytoplankton growth to explore a trade-off between the ability of cells to replenish their internal quota (which increases with size) and their ability to synthesize new biomass (which decreases with size). Contrary to the metabolic theory of ecology, these results demonstrate that rates of resource acquisition (rather than metabolism) provide the primary physiological constraint on the growth rates of some of the smallest and most numerically abundant photosynthetic organisms on Earth.

Modeled Chl:C ratio and derived estimates of phytoplankton carbon biomass and its contribution to total particulate organic carbon in the global surface ocean

AbstractChlorophyll (Chl) is a distinctive component of autotrophic organisms, often used as an indicator of phytoplankton biomass in the ocean. However, assessment of phytoplankton biomass from Chl relies on the accurate estimation of the Chl:carbon(C) ratio. Here we present global patterns of Chl:C ratios in the surface ocean obtained from a phytoplankton growth model that accounts for the optimal acclimation of phytoplankton to ambient nutrient, light, and temperature conditions. The model agrees largely with observed/expected global patterns of Chl:C. Combining our Chl:C estimates with satellite Chl and particulate organic carbon (POC), we infer phytoplankton C concentration in the surface ocean and its contribution to the total POC pool. Our results suggest that the portion of POC corresponding to living phytoplankton is higher in subtropical latitudes and less productive regions (∼30–70%) and decreases to ∼10–30% toward high latitudes and productive regions. An important caveat of our model is the lack of iron limiting effects on phytoplankton physiology. Comparison of our predicted phytoplankton biomass with an independent estimate of total POC reveals a positive correlation between nitrate concentrations and nonphotosynthetic POC in the surface ocean. This correlation disappears when a constant Chl:C is applied. Our analysis is not constrained by assumptions of constant Chl:C or phytoplankton:POC ratio, providing a novel independent analysis of phytoplankton biomass in the surface ocean. These results highlight the importance of accounting for the variability in Chl:C and its application in distinguishing the autotrophic and heterotrophic components in the assemblage of the marine plankton ecosystem.

Optimality-basedTrichodesmiumdiazotrophy in the North Atlantic subtropical gyre

A recent optimality-based model for phytoplankton growth and diazotrophy was applied at two stations located in the oligotrophic western and the ultra-oligotrophic eastern subtropical North Atlantic. Contrary to the common view that diazotrophy is favoured by nitrogen (N) depletion relative to the Redfield equivalent of phosphorus (P), we find that optimality-based diazotrophy could explain N fixation in both regions in spite of relatively high N:P supply ratios. This is possible because the availability of an additional source of N for diazotrophs makes them strong competitors for P under oligotrophic conditions. The best reproduction of observations, especially of net primary production, is only achieved with preferential remineralization of P relative to N and atmospheric deposition. In line with observations, a higher rate of nitrogen fixation is predicted for the eastern site, owing to a larger niche for diazotrophs resulting from stronger oligotrophy and lower N:P supply ratios due to weaker atmospheric N deposition. Because the competitive advantage of diazotrophs under nutrient starvation diminishes with increasing supply N:P ratio, the predicted increase of atmospheric N deposition due to anthropogenic activity could negatively affect N2 fixation in the Atlantic Ocean.

Modeling photosynthesis and the growth of marine phytoplankton

The paper analyzes the most popular models of photosynthesis and growth of marine phytoplankton in the literature and demonstrates their limitations. A new approach to modeling is proposed and used to obtain new models of marine phytoplankton photosynthesis and growth. An important feature of the proposed models is their ability to describe coupled multisubstrate cyclical interactions typical of biochemical and physiological processes. As a first approximation, the mathematical models are represented by equations of nonrectangular hyperbolas. The models describe the stoichiometry of extraction of elements from the medium, whatever the degree of their limitation, an important feature in describing biogeochemical cycles of elements. This stoichiometry is governed by measurable internal parameters of an organism (substrate parameters) and can be a key cause of stoichiometric formation of elements in the ambient medium, described, for example, by the Redfield ratio. The substrate constants are fundamental characteristics of the models, which form “automatically” in the construction of model equations in arbitrary units.

Coincident patterns of waste water suspended solids reduction, water transparency increase and chlorophyll decline in Narragansett Bay

Dramatic changes occurred in Narragansett Bay during the 1980s: water clarity increased, while phytoplankton abundance and chlorophyll concentration decreased. We examine how changes in total suspended solids (TSS) loading from wastewater treatment plants may have influenced this decline in phytoplankton chlorophyll. TSS loading, light and phytoplankton observations were compiled and a light- and temperature-dependent Skeletonema-based phytoplankton growth model was applied to evaluate chlorophyll supported by TSS nitrogen during 1983–1995. TSS loading declined 75% from ~0.60×106kgmonth−1 to ~0.15×106kgmonth−1 during 1983–1995. Model results indicate that nitrogen reduction related to TSS reduction was minor and explained a small fraction (~15%) of the long-term chlorophyll decline. The decline in NBay TSS loading appears to have increased water clarity and in situ irradiance and contributed to the long-term chlorophyll decline by inducing a physiological response of a ~20% reduction in chlorophyll per cell.

Flexible phytoplankton functional type (FlexPFT) model: size-scaling of traits and optimal growth

Recent studies have analysed valuable compilations of data for the size-scaling of phytoplankton traits, but these cannot be employed directly in most large-scale modelling studies, which typically do not explicitly resolve the relevant trait values. Although some recent large-scale modelling studies resolve species composition and sorting within communities, most do not account for the observed flexible response of phytoplankton communities, such as the dynamic acclimation often observed in laboratory experiments. In order to derive a simple yet flexible model of phytoplankton growth that can be useful for a wide variety of ocean modelling applications, we combine two trade-offs, one for growth and the other for nutrient uptake, under the optimality assumption, i.e. that intracellular resources are dynamically allocated to maximize growth rate. This yields an explicit equation for growth as a function of nutrient concentration and daily averaged irradiance. We furthermore show how with this model effective Monod parameter values depend on both the underlying trait values and environmental conditions. We apply this new model to two contrasting time-series observation sites, including idealized simulations of size diversity. The flexible model responds differently compared with an inflexible control, suggesting that acclimation by individual species could impact models of plankton diversity.

Exploration of the critical depth hypothesis with a simple NPZ model

AbstractThe critical depth hypothesis (CDH) is a predictive criteria for the onset of phytoplankton blooms that comes from the steady-state analytical solution of a simple mathematical model for phytoplankton growth presented by Sverdrup in 1953. Sverdrup's phytoplankton-only model is very elementary compared with state-of-the-art ecosystem models whose numerical solution in a time-varying environment do not systematically conform to the CDH. To highlight which model ingredients make the bloom onset deviate from the CDH, the complexity of Sverdrup's model is incrementally increased, and the impact that each new level of complexity introduced is analysed. Complexity is added both to the ecosystem model and to the parameterization of physical forcing. In the most complete experiment, the model is a one-dimensional Nutrient-Phytoplankton-Zooplankton model that includes seasonally varying mixed layer depth and surface irradiance, light and nutrient limitation, variable grazing, self-shading, export, and remineralization. When complexity is added to the ecosystem model, it is found that the model solution only marginally deviates from the CDH. But when the physical forcing is also changed, the model solution can conform to two competing theories for the onset of phytoplankton blooms—the critical turbulence hypothesis and the disturbance recovery hypothesis. The key roles of three physical ingredients on the bloom onset are highlighted: the intensity of vertical mixing at the end of winter, the seasonal evolution of the mixed-layer depth from the previous summer, and the seasonal evolution of surface irradiance.

Sensitivity of phytoplankton distributions to vertical mixing along a North Atlantic transect

Abstract. Using in situ data of upper ocean vertical mixing along a transect in the North Atlantic and a one-dimensional phytoplankton growth model, we study the sensitivity of the surface phytoplankton concentration to vertical mixing distributions. The study is divided into two parts. In the first part, the model is calibrated to the observations. The optical model parameters are determined from measurements of the light attenuation. The biological parameters are calibrated to three different reference stations with observed vertical profiles of the chlorophyll a (Chl a) concentration and the nutrient concentration. In the second part, the sensitivity of the three model calibrations to the vertical mixing is studied. Therefore measured vertical mixing profiles are applied to the model. These mixing profiles are based on the measurements along the transect and are treated as a set of possible mixing situations of the North Atlantic. Results show that shifts in vertical mixing are able to induce a transition from an upper chlorophyll maximum to a deep one and vice versa. Furthermore, a clear correlation between the surface phytoplankton concentration and the mixing induced nutrient flux is found for nutrient-limited cases. This may open up the possibility to extract characteristics of vertical mixing from satellite ocean colour data using data-assimilation methods.

Rapid formation of large aggregates during the spring bloom of Kerguelen Island: observations and model comparisons

Abstract. While production of aggregates and their subsequent sinking is known to be one pathway for the downward movement of organic matter from the euphotic zone, the rapid transition from non-aggregated to aggregated particles has not been reported previously. We made one vertical profile of particle size distributions (PSD; sizes ranging from 0.052 to several millimeters in equivalent spherical diameter) at pre-bloom stage and seven vertical profiles 3 weeks later over a 48 h period at early bloom stage using the Underwater Vision Profiler during the Kerguelen Ocean and Plateau Compared Study cruise 2 (KEOPS2, October–November 2011). In these naturally iron-fertilized waters southeast of Kerguelen Island (Southern Ocean), the total particle numerical abundance increased by more than fourfold within this time period. A massive total volume increase associated with particle size distribution changes was observed over the 48 h survey, showing the rapid formation of large particles and their accumulation at the base of the mixed layer. The results of a one-dimensional particle dynamics model support coagulation as the mechanism responsible for the rapid aggregate formation and the development of the VT subsurface maxima. The comparison of VT profiles between early bloom stage and pre-bloom stage indicates an increase of particulate export below 200 m when bloom has developed. These results highlight the role of coagulation in forming large particles and triggering carbon export at the early stage of a naturally iron-fertilized bloom, while zooplankton grazing may dominate later in the season. The rapid changes observed illustrate the critical need to measure carbon export flux with high sampling temporal resolution. Our results are the first published in situ observations of the rapid accumulation of marine aggregates and their export and the general agreement of this rapid event with a model of phytoplankton growth and coagulation.

Global patterns of phytoplankton nutrient and light colimitation inferred from an optimality‐based model

AbstractThe widely used concept of constant ”Redfield” phytoplankton stoichiometry is often applied for estimating which nutrient limits phytoplankton growth in the surface ocean. Culture experiments, in contrast, show strong relations between growth conditions and cellular stoichiometry with often substantial deviations from Redfield stoichiometry. Here we investigate to what extent both views agree by analyzing remote sensing and in situ data with an optimality‐based model of nondiazotrophic phytoplankton growth in order to infer seasonally varying patterns of colimitation by light, nitrogen (N), and phosphorus (P) in the global ocean. Our combined model‐data analysis suggests strong N and N‐P colimitation in the tropical ocean, seasonal light, and N‐P colimitation in the Northern Hemisphere, and strong light limitation only during winter in the Southern Ocean. The eastern equatorial Pacific appears as the only ocean area that is essentially not limited by N, P, or light. Even though our optimality‐based approach specifically accounts for flexible stoichiometry, inferred patterns of N and P limitation are to some extent consistent with those obtained from an analysis of surface inorganic nutrients with respect to the Redfield N:P ratio. Iron is not part of our analysis, implying that we cannot accurately predict N cell quotas in high‐nutrient, low‐chlorophyll regions. Elsewhere, we do not expect a major effect of iron on the relative distribution of N, P, and light colimitation areas. The relative importance of N, P, and light in limiting phytoplankton growth diagnosed here by combining observations and an optimal growth model provides a useful constraint for models used to predict future marine biological production under changing environmental conditions. © 2014. American Geophysical Union. All Rights Reserved.

Comparing diatom and Alexandrium catenella/tamarense blooms in Thau lagoon: Importance of dissolved organic nitrogen in seasonally N-limited systems

Diatom blooms in Thau lagoon are always related to rain events leading to inputs of inorganic nutrients such as phosphate, ammonium and nitrate through the watershed with time lags of about 1 week. In contrast, blooms of Alexandrium catenella/tamarense can occur following periods of 3 weeks without precipitation and no significant input of conventional nutrients such as nitrate and phosphate. Field results also indicate a significant drop (from 22–25 to 15–16μM over 3 days) in dissolved organic nitrogen (DON) at the bloom peak, as well as a significant inverse relationship between A. catenella/tamarense cell density and DON concentrations that is not apparent for diatom blooms. Such dinoflagellate blooms are also associated with elevated (6–9μM) ammonium concentrations, a curious feature also observed by other investigators, possibly the results of ammonium excretion by this organism during urea or other organic nitrogen assimilation.The potential use of DON by this organism represents short cuts in the nitrogen cycle between plants and nutrients and requires a new model for phytoplankton growth that is different from the classical diatom bloom model. In contrast to such diatom blooms that are due to conventional (nitrate, phosphate) nutrient pulses, Alexandrium catenella/tamarense blooms on the monthly time scale are due to organic nutrient enrichment, a feature that allows net growth rates of about 1.3d−1, a value higher than that generally attributed to such organisms.