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We describe an approach to partition a vertical profile of chlorophyll-a concentration into contributions from two communities of phytoplankton: one (community 1) that resides principally in the turbulent mixed-layer of the upper ocean and is observable through satellite visible radiometry; the other (community 2) residing below the mixed-layer, in a stably stratified environment, hidden from the eyes of the satellite. The approach is tuned to a time-series of profiles from a Biogeochemical-Argo float in the northern Red Sea, selected as its location transitions from a deep mixed layer in winter (characteristic of vertically well-mixed systems) to a shallow mixed layer in the summer with a deep chlorophyll-a maximum (characteristic of vertically stratified systems). The approach is extended to reproduce profiles of particle backscattering, by deriving the chlorophyll-specific backscattering coefficients of the two communities and a background coefficient assumed to be dominated by non-algal particles in the region. Analysis of the float data reveals contrasting phenology of the two communities, with community 1 blooming in winter and 2 in summer, community 1 negatively correlated with epipelagic stratification, and 2 positively correlated. We observe a dynamic chlorophyll-specific backscattering coefficient for community 1 (stable for community 2), positively correlated with light in the mixed-layer, suggesting seasonal changes in photoacclimation and/or taxonomic composition within community 1. The approach has the potential for monitoring vertical changes in epipelagic biogeography and for combining satellite and ocean robotic data to yield a three-dimensional view of phytoplankton distribution.

Photosynthesis parameters are routinely estimated from in vitro measurements of primary production under constant light reaching each incubation bottle, by fitting a photosynthesis- irradiance function to the measurements. Here we take one such function and integrate it in time for variable light input, similar to natural conditions, to obtain the analytical solution for the vertical profile of daily phytoplankton production in the field. This solution is then fitted to in situ measurements of primary production profiles in the same manner as a photosynthesis-irradiance function is fitted to in vitro measurements under controlled and constant light conditions to retrieve the photosynthesis-irradiance parameters. The method is tested on the Hawaii Ocean Time-series data set. The solution explained 97.88% of the variance in measured normalized production at individual depths. The recovered parameters were then used to model the normalized daily water-column production. The model explained 99.21% of variance in normalized watercolumn production of the entire data set. The seasonal cycle of the photosynthesis parameters recovered with the analytical solution was further studied for the Hawaii Ocean Time-series. With respect to the photosynthesis parameter determination, the solution bridges the gap between classical photosynthesis-irradiance measurements under controlled light conditions and in situ measurements which are made under natural, variable light conditions. It presents a new tool for the estimation of photosynthesis parameters from in situ measurements of primary production.

Size‐fractionated filtration (SFF) is a direct method for estimating pigment concentration in various size classes. It is also common practice to infer the size structure of phytoplankton communities from diagnostic pigments estimated by high‐performance liquid chromatography (HPLC). In this paper, the three‐component model of Brewin et al. (2010) was fitted to coincident data from HPLC and from SFF collected along Atlantic Meridional Transect cruises. The model accounted for the variability in each data set, but the fitted model parameters differed for the two data sets. Both HPLC and SFF data supported the conceptual framework of the three‐component model, which assumes that the chlorophyll concentration in small cells increases to an asymptotic maximum, beyond which further increase in chlorophyll is achieved by the addition of larger celled phytoplankton. The three‐component model was extended to a multicomponent model of size structure using observed relationships between model parameters and assuming that the asymptotic concentration that can be reached by cells increased linearly with increase in the upper bound on the cell size. The multicomponent model was verified using independent SFF data for a variety of size fractions and found to perform well (0.628 ≤ r ≤ 0.989) lending support for the underlying assumptions. An advantage of the multicomponent model over the three‐component model is that, for the same number of parameters, it can be applied to any size range in a continuous fashion. The multicomponent model provides a useful tool for studying the distribution of phytoplankton size structure at large scales.

[1] Phytoplankton are an important component of the oceanic carbon cycle. Yet, due to methodological constraints, the carbon biomass of phytoplankton is poorly characterized. To address this limitation, we have explored the bio-optical relationship between in situ measurements of the particle backscattering coefficient at 470 nm, bbp(470), and the phytoplankton carbon concentration for cells with diameter less than 20 µm (Cf). We found a significant relationship between bbp(470) and Cf for Atlantic oceanic waters with chlorophyll-a concentrations less than 0.4 mg m−3 (or bbp(470)

[1] Detecting the effect of climate change on ocean ecosystems is facilitated if the data are partitioned into ecological provinces. It is recognised that the boundaries of such provinces are dynamic, raising the imperative for frequent observations. Using satellite data, we have assembled a time series of ecosystem delineation for the Northwest Atlantic Ocean over a period of ten years. For each province identified in the study area, we have compiled data on sea-surface temperature, and on the biomass and community composition of phytoplankton. We find significant trends in these properties but they vary according to the province concerned, which emphasizes how the physical and biological changes are correlated at large scale. Comparisons between the trends computed using the average position of the provinces and the trends derived when accounting for the movements of the boundaries underline the value of the new approach.

Process models of phytoplankton production are discussed with respect to their suitability for incorporation into global-scale numerical ocean circulation models. Exact solutions are given for integrals over the mixed layer and the day of analytic, wavelength-independent models of primary production. Within this class of model, the bias incurred by using a triangular approximation (rather than a sinusoidal one) to the variation of surface irradiance through the day is computed. Efficient computation algorithms are given for the nonspectral models. More exact calculations require a spectrally sensitive treatment. Such models exist but must be integrated numerically over depth and time. For these integrations, resolution in wavelength, depth, and time are considered and recommendations made for efficient computation. The extrapolation of the one-(spatial)-dimension treatment to large horizontal scale is discussed.

[1] A method is presented for estimation of seasonally-varying, total loss rate of phytoplankton from time series of satellite-derived phytoplankton biomass data. The loss is calculated as the difference between the (modelled) rate of photosynthesis and the observed, realized rate of change of phytoplankton biomass. A Monte Carlo procedure is used to recover the loss rates. The (biomass-normalized) total loss rate shows a seasonal cycle with values ranging from 0.5 to 3 mg C (mg Chl)−1 h−1 and shows an abrupt shift during the spring bloom. On the other hand, the absolute loss rate increases during blooms, a consequence of the increase in the biomass. The normalized total loss rate can be further expressed as a time-varying fraction of the assimilation number. The fraction lies in the range from 0.2 to 0.8. During the increasing (decreasing) phase of phytoplankton blooming, the ratio of growth to total loss increases (decreases), such that this ratio may have value as an ecological indicator for blooms.

[1] The mechanisms of nutrient resupply for an episodic phytoplankton bloom observed in the central Labrador Sea in July 2006 were investigated. Two physical processes, mixed-layer deepening and Ekman pumping, are proposed to account for the implied nutrient replenishment. The nutrient flux and chlorophyll concentration before and during the bloom were estimated from a simple coupled nitrate-phytoplankton model. The model results show that the enrichment of nutrients in the euphotic layer and the subsequent bloom were related to two wind events (storms) in the period July 7–10. As the mixed layer deepened, nutrient from below the nitricline were entrained into the euphotic zone. The Ekman pumping, which was most intense at the storm centre, enhanced the transport of the nutrients by raising the nitricline. However, Ekman pumping alone was not able to transport sufficient nitrate to the euphotic layer to support the observed phytoplankton bloom.

[1] Conversion between upwelling irradiance and radiance at the sea surface, essential for some aspects of remote sensing of ocean colour, requires knowledge of the Q factor. The Q factor depends on solar zenith angle, satellite viewing angle and the optical properties of the water. For simulated data for two fixed solar zenith angles, we express the Q factor as a function of total absorption and backscattering coefficients. The new parameterisation is used in an algorithm to retrieve total water backscattering from in situ ocean-colour data. The algorithm performs better than those in which the Q factor is expressed as a function of chlorophyll-a concentration alone.

[1] The two-population absorption model of Sathyendranath et al. is extended to retrieve the specific absorption coefficients (absorption per unit concentration of chlorophyll-a) of the component populations of phytoplankton. The model relates the absorption coefficient of phytoplankton to chlorophyll-a concentration, assuming that the assemblages of phytoplankton comprise mixtures of two populations whose proportions vary as the total concentration of cells changes. The model is applied to in situ data collected from six regions during 34 cruises. The model compares well with earlier models of phytoplankton absorption but brings the additional advantage of parameters that have clear bio-optical and biological interpretation. Size structure of the phytoplankton populations was inferred from the values of the specific absorption coefficients. The results are consistent with pigment analyses performed on the same samples. Seasonal analysis of data from the northwest Atlantic, southeast Pacific, and the Arabian Sea showed significant changes in the spectral form and magnitude of the specific absorption coefficients of small- and large-celled populations, which appear to be related to changes in species composition. The model serves thus as an optical tool to explore the large-scale biogeography of phytoplankton.

Every year, several hundred ocean research cruises are conducted by academic institutions and government agencies worldwide, with major expenditures of finances and human resources. Ships may be in the same ocean area at the same time without prior knowledge of one another's activities, missing opportunities for joint work. Some ships go to sea with empty berths, which might have been filled if scientists from other institutions or countries had known about the availability of space. Many scientists using in situ instruments have missed opportunities to deploy them in seldom visited parts of the ocean because the scientists did not realize a ship was going to that area, and opportunities for ”sea truthing“ of satellite observations in remote regions are missed. In an era of stagnant or shrinking budgets for research and ship operations, and increasing operational costs, it is imperative that scientists and ship operators look for ways to increase the efficiency of research cruises, for example, by reducing transit time and sharing research cruises. In addition, synergy of observations and opportunities for intercalibrations can be achieved in coordinated, multiple-ship operations.

Partial pressure of CO2 is a nonlinear function of several seawater properties. Due to the nonlinearity in this relationship, the partial pressure of a uniform ocean would be different from that of a nonuniform ocean with the same bulk seawater properties. Assuming uniformity of seawater properties at some temporal and spatial scales in carbon models leads to systematic errors in partial pressure of CO2. In this paper we evaluate the magnitude of these errors. We partition the Geochemical Ocean Sections Study and Transient Tracers in the Oceans data according to the horizontal structure of several box models from the literature. Our results suggest that assumption of uniformity at large scales leads to understanding of underestimation of global surface ocean partial pressure of CO2 by at least 3 - 12 microatm. Nonlinear effects also introduce systematic errors in the buffer factor estimated from bulk seawater properties. We find the standard deviation of partial pressure of CO2 to be an indicator of the magnitude of the nonlinear effects. We discuss the implications of these errors for some conclusions drawn from carbon models. Biogeochemical processes, such as mixing, gas exchange, or biological activity, influence the distribution of the seawater properties. A shift in spatial or temporal patterns of these processes can modify the nonuniformity of the seawater properties and thus alter the partial pressure of the surface waters, even if the mean intensities of the processes remain constant.

The theoretical basis is explained for some commonly used estimators of daily primary production in a vertically uniform water column. These models are recast into a canonical form, with dimensionless arguments, to facilitate comparison with each other and with an analytic solution. The limitations of each model are examined. The values of the photoadaptation parameter I(k) observed in the ocean are analyzed, and I(k) is used as a scale to normalize the surface irradiance. The range of this scaled irradiance is presented. An equation is given for estimation of I(k) from recent light history. It is shown how the models for water column production can be adapted for estimation of the production in finite layers. The distinctions between model formulation, model implementation and model evaluation are discussed. Recommendations are given on the choice of algorithm for computation of daily production according to the degree of approximation acceptable in the result.

The contributions of detrital particles and phytoplankton to total light absorption are retrieved by nonlinear regression on the absorption spectra of total particles from various oceanic regions. The model used explains more than 96% of the variance in the observed particle absorption spectra. The resulting absorption spectra of phytoplankton are then decomposed into several Gaussian bands reflecting absorption by phytoplankton pigments. Such a decomposition, combined with high-performance liquid chromatography data on phytoplankton pigment concentrations, allows the computation of specific absorption coefficients for chlorophylls a, b, and c and carotenoids. The spectral values of these in vivo absorption coefficients are then discussed, considering the effects of secondary pigments which were not measured quantitatively. We show that these coefficients can be used to reconstruct the absorption spectra of phytoplankton at various locations and depths. Discrepancies that do occur at some stations are explained in terms of particle size effect. These coefficients can be used to determine the concentrations of phytoplankton pigments in the water, given the absorption spectrum of total particles.

Mie theory is applied to estimate scattering by polydispersions of marine heterotrophic bacteria, and a simple expression is derived for the bacterial scattering coefficient. The error incurred in deriving bacterial optical properties by use of the van de Hulst approximations is computed. The scattering properties of natural bacterial assemblages in three marine environments, Georges Bank, Northeast Channel, and Sargasso Sea, are assessed by applying Mie theory to field data on bacterial size and abundance. Results are used to examine the potential contribution of bacteria to the scattering properties of seawater. The utility of using pigment data to predict the magnitude of scattering by bacteria is discussed.

The monthly averaged CZCS data for 1979 are used to estimate annual primary production at ocean basin scales in the North Atlantic. The principal supplementary data used were 873 vertical profiles of chlorophyll and 248 sets of parameters derived from photosynthesis-light experiments. Four different procedures were tested for calculation of primary production. The spectral model with nonuniform biomass was considered as the benchmark for comparison against the other three models. The less complete models gave results that differed by as much as 50 percent from the benchmark. Vertically uniform models tended to underestimate primary production by about 20 percent compared to the nonuniform models. At horizontal scale, the differences between spectral and nonspectral models were negligible. The linear correlation between biomass and estimated production was poor outside the tropics, suggesting caution against the indiscriminate use of biomass as a proxy variable for primary production.

A spectral model of irradiance is presented for the computation of light energy available at the surface and at various depths in the ocean for the wavelength range from 400 to 700 nm. For any latitude, irradiances are computed as a function of geographic location, date, and time. Application of the model is demonstrated through computation of the profiles of vertical attenuation coefficient and of the effective specific absorption of phytoplankton. The model results are compared with those from conventional procedures, which disregard spectral and angular distributions of the underwater light field, for calculation of the effective specific absorption. The magnitude of the errors incurred by such simplifications is estimated and is shown to be nonnegligible and variable with solar elevation, depth, and the phytoplank-on pigment concentration in the water.