Phytoplankton Functional Types Research Articles

Regional Empirical Algorithms for an Improved Identification of Phytoplankton Functional Types and Size Classes in the Mediterranean Sea Using Satellite Data

Regional relationships to estimate the main Phytoplankton Functional Types (PFTs) and Size Classes (PSCs) from satellite data are presented. Following the abundance-based approach and selecting the Total Chlorophyll a (TChla) as descriptor of the trophic status of the environment, empirical relations between the TChla concentration and seven accessory pigments, marker for the main algal groups, have been developed for the Mediterranean Sea. Using only in-situ data acquired in this basin, firstly a previous regional diagnostic pigment analysis has been conducted to evaluate the specific pigment ratios featuring the phytoplankton assemblage that occurs in the Mediterranean Sea. Secondly, the new regional PFT and PSC algorithms have been calibrated and validated on the in-situ dataset. The statistical analysis showed a very good predictive power for all the new regional models. A quantitative comparison with global abundance-based models applied to our validation dataset showed that the regionalization improves the uncertainty and the spread of about one order of magnitude for all the classes (e.g. in the nano class, where the mean bias error improves from -0.056 to 0.001 mg m-3). These results highlighted that a regionalization for the PSC and PFT estimates are required, to take into account the peculiar bio-optical properties of the Mediterranean Sea. Finally, the new regional equations have been applied to the Mediterranean TChla satellite (1998-2015) time series to estimate annual and monthly PFT and PSC climatology. The analysis of the climatological maps, relative to the phytoplankton assemblage distribution patterns, reveals that all the three size classes reach their maxima in the higher nutrient areas, with absolute values greater than 3 mg m-3 of TChla for micro-, and about 1.6 and 0.4 mg m-3 for nano- and pico-phytoplankton respectively. Moreover, the nano component shows intermediate percentage values in the whole basin, ranging from 30 to 40% of the TChla in the western basin, up to 45% in the more productive areas. In terms of chlorophyll concentration, in the coastal areas we find the predominance of the Diatoms and Haptophytes, while in the ultra-oligotrophic waters Prokaryotes predominates on the other groups, constituting the principal component of the pico-phytoplankton.

Observing and modelling phytoplankton community structure in the North Sea

Abstract. Phytoplankton form the base of the marine food chain, and knowledge of phytoplankton community structure is fundamental when assessing marine biodiversity. Policy makers and other users require information on marine biodiversity and other aspects of the marine environment for the North Sea, a highly productive European shelf sea. This information must come from a combination of observations and models, but currently the coastal ocean is greatly under-sampled for phytoplankton data, and outputs of phytoplankton community structure from models are therefore not yet frequently validated. This study presents a novel set of in situ observations of phytoplankton community structure for the North Sea using accessory pigment analysis. The observations allow a good understanding of the patterns of surface phytoplankton biomass and community structure in the North Sea for the observed months of August 2010 and 2011. Two physical–biogeochemical ocean models, the biogeochemical components of which are different variants of the widely used European Regional Seas Ecosystem Model (ERSEM), were then validated against these and other observations. Both models were a good match for sea surface temperature observations, and a reasonable match for remotely sensed ocean colour observations. However, the two models displayed very different phytoplankton community structures, with one better matching the in situ observations than the other. Nonetheless, both models shared some similarities with the observations in terms of spatial features and inter-annual variability. An initial comparison of the formulations and parameterizations of the two models suggests that diversity between the parameter settings of model phytoplankton functional types, along with formulations which promote a greater sensitivity to changes in light and nutrients, is key to capturing the observed phytoplankton community structure. These findings will help inform future model development, which should be coupled with detailed validation studies, in order to help facilitate the wider application of marine biogeochemical modelling to user and policy needs.

Inter-comparison of phytoplankton functional type phenology metrics derived from ocean color algorithms and Earth System Models

Ocean color remote sensing of chlorophyll concentration has revolutionized our understanding of the biology of the oceans. However, a comprehensive understanding of the structure and function of oceanic ecosystems requires the characterization of the spatio-temporal variability of various phytoplankton functional types (PFTs), which have differing biogeochemical roles. Thus, recent bio-optical algorithm developments have focused on retrieval of various PFTs. It is important to validate and inter-compare the existing PFT algorithms; however direct comparison of retrieved variables is non-trivial because in those algorithms PFTs are defined differently. Thus, it is more plausible and potentially more informative to focus on emergent properties of PFTs, such as phenology. Furthermore, ocean color satellite PFT data sets can play a pivotal role in informing and/or validating the biogeochemical routines of Earth System Models. Here, the phenological characteristics of 10 PFT satellite algorithms and 7 latest-generation climate models from the Coupled Model Inter-comparison Project (CMIP5) are inter-compared as part of the International Satellite PFT Algorithm Inter-comparison Project. The comparison is based on monthly satellite data (mostly SeaWiFS) for the 2003–2007 period. The phenological analysis is based on the fraction of microplankton or a similar variable for the satellite algorithms and on the carbon biomass due to diatoms for the climate models. The seasonal cycle is estimated on a per-pixel basis as a sum of sinusoidal harmonics, derived from the Discrete Fourier Transform of the variable time series. Peak analysis is then applied to the estimated seasonal signal and the following phenological parameters are quantified for each satellite algorithm and climate model: seasonal amplitude, percent seasonal variance, month of maximum, and bloom duration. Secondary/double blooms occur in many areas and are also quantified. The algorithms and the models are quantitatively compared based on these emergent phenological parameters. Results indicate that while algorithms agree to a first order on a global scale, large differences among them exist; differences are analyzed in detail for two Longhurst regions in the North Atlantic: North Atlantic Drift Region (NADR) and North Atlantic Subtropical Gyre West (NASW). Seasonal cycles explain the most variance in zonal bands in the seasonally-stratified subtropics at about 30° latitude in the satellite PFT data. The CMIP5 models do not reproduce this pattern, exhibiting higher seasonality in mid and high-latitudes and generally much more spatially homogeneous patterns in phenological indices compared to satellite data. Satellite data indicate a complex structure of double blooms in the Equatorial region and mid-latitudes, and single blooms on the poleward edges of the subtropical gyres. In contrast, the CMIP5 models show single annual blooms over most of the ocean except for the Equatorial band and Arabian Sea.

Variability of Particle Size Distributions in the Bohai Sea and the Yellow Sea

Particle size distribution (PSD) is an important parameter that is relevant to many aspects of marine ecosystems, such as phytoplankton functional types, optical absorption and scattering from particulates, sediment fluxes, and carbon export. However, only a handful of studies have documented the PSD variability in different regions. Here, we investigate the PSD properties and variability in two shallow and semi-enclosed seas (the Bohai Sea (BS) and Yellow Sea (YS)), using in situ laser diffraction measurements (LISST-100X Type C) and other measurements at 79 stations in November 2013. The results show large variability in particle concentrations (in both volume and number concentrations), with volume concentrations varying by 57-fold. The median particle diameter (Dv50) from each of the water samples also covers a large range (22.4–307.0 μm) and has an irregular statistical distribution, indicating complexity in the PSD. The PSD slopes (2.7–4.5), estimated from a power-law model, cover nearly the entire range reported previously for natural waters. Small mineral particles (with large PSD slopes) are characteristic of near-shore waters prone to sediment resuspension by winds and tides, while large biological particles (with small PSD slopes) dominate the total suspended particulates for waters away from the coast. For the BS and YS, this study provides the first report on the properties and spatial variability of the PSD, which may influence the optical properties of the ocean surface and remote sensing algorithms that are based on estimations of particle concentrations and sizes.

Investigation of Spectral Band Requirements for Improving Retrievals of Phytoplankton Functional Types

Studying phytoplankton functional types (PFTs) from space is possible due to recent advances in remote sensing. Though a variety of products are available, the limited number of wavelengths available compared to the number of model parameters needed to be retrieved is still a major problem in using ocean-color data for PFT retrievals. Here, we investigated which band placement could improve retrievals of three particular PFTs (diatoms, coccolithophores and cyanobacteria). In addition to analyzing dominant spectral features in the absorption spectra of the target PFTs, two previously-developed methods using measured spectra were applied to simulated data. Such a synthetic dataset allowed for significantly increasing the number of scenarios and enabled a full control over parameters causing spectral changes. We evaluated the chosen band placement by applying an adapted ocean reflectance inversion, as utilized in the generalized inherent optical properties (GIOP) retrieval. Results show that the optimal band settings depend on the method applied to determine the bands placement, as well as on the internal variability of the dataset investigated. Therefore, continuous hyperspectral instruments would be most beneficial for discriminating multiple PFTs, though a small improvement in spectral sampling and resolution does not significantly modify the results. Bands, which could be added to future instruments (e.g., Ocean and Land Colour Instrument (OLCI) instrument on the upcoming Sentinel-3B,-3C,-3D, etc., and further satellites) in order to enhance PFT retrieval capabilities, were also determined.

Assessing spatial and temporal variability of phytoplankton communities' composition in the Iroise Sea ecosystem (Brittany, France): A 3D modeling approach. Part 1: Biophysical control over plankton functional types succession and distribution

Understanding the dynamic interplay between physical, biogeochemical and biological processes represents a key challenge in oceanography, particularly in shelf seas where complex hydrodynamics are likely to drive nutrient distribution and niche partitioning of phytoplankton communities. The Iroise Sea includes a tidal front called the ‘Ushant Front’ that undergoes a pronounced seasonal cycle, with a marked signal during the summer. These characteristics as well as relatively good observational sampling make it a region of choice to study processes impacting phytoplankton dynamics. This innovative modeling study employs a phytoplankton-diversity model, coupled to a regional circulation model to explore mechanisms that alter biogeography of phytoplankton in this highly dynamic environment. Phytoplankton assemblages are mainly influenced by the depth of the mixed layer on a seasonal time scale. Indeed, solar incident irradiance is a limiting resource for phototrophic growth and small phytoplankton cells are advantaged over larger cells. This phenomenon is particularly relevant when vertical mixing is intense, such as during winter and early spring. Relaxation of wind-induced mixing in April causes an improvement of irradiance experienced by cells across the whole study area. This leads, in late spring, to a competitive advantage of larger functional groups such as diatoms as long as the nutrient supply is sufficient. This dominance of large, fast-growing autotrophic cells is also maintained during summer in the productive tidally-mixed shelf waters. In the oligotrophic surface layer of the western part of the Iroise Sea, small cells coexist in a greater proportion with large, nutrient limited cells. The productive Ushant tidal front's region (1800mgC·m−2·d−1 between August and September) is also characterized by a high degree of coexistence between three functional groups (diatoms, micro/nano-flagellates and small eukaryotes/cyanobacteria). Consistent with previous studies, the biogeography of phytoplankton functional types at the Ushant front during summer displays an intermediate community composition between contrasted sub-regions on either side of the front. Strong mixing conditions within the frontal sub-region result in a short residence time of water masses, not allowing speciation or long term adaptation to occur.

MERIS Phytoplankton Time Series Products from the SW Iberian Peninsula (Sagres) Using Seasonal-Trend Decomposition Based on Loess

The European Space Agency has acquired 10 years of data on the temporal and spatial distribution of phytoplankton biomass from the MEdium Resolution Imaging Spectrometer (MERIS) sensor for ocean color. The phytoplankton biomass was estimated with the MERIS product Algal Pigment Index 1 (API 1). Seasonal-Trend decomposition of time series based on Loess (STL) identified the temporal variability of the dynamical features in the MERIS products for water leaving reflectance (ρw(λ)) and API 1. The advantages of STL is that it can identify seasonal components changing over time, it is responsive to nonlinear trends, and it is robust in the presence of outliers. One of the novelties in this study is the development and the implementation of an automatic procedure, stl.fit(), that searches the best data modeling by varying the values of the smoothing parameters, and by selecting the model with the lowest error measure. This procedure was applied to 10 years of monthly time series from Sagres in the Southwestern Iberian Peninsula at three Stations, 2, 10 and 18 km from the shore. Decomposing the MERIS products into seasonal, trend and irregular components with stl.fit(), the ρw(λ) indicated dominance of the seasonal and irregular components while API 1 was mainly dominated by the seasonal component, with an increasing effect from inshore to offshore. A comparison of the seasonal components between the ρw(λ) and the API 1 product, showed that the variations decrease along this time period due to the changes in phytoplankton functional types. Furthermore, inter-annual seasonal variation for API 1 showed the influence of upwelling events and in which month of the year these occur at each of the three Sagres stations. The stl.fit() is a good tool for any remote sensing study of time series, particularly those addressing inter-annual variations. This procedure will be made available in R software.

Carbon-based phytoplankton size classes retrieved via ocean color estimates of the particle size distribution

Abstract. Owing to their important roles in biogeochemical cycles, phytoplankton functional types (PFTs) have been the aim of an increasing number of ocean color algorithms. Yet, none of the existing methods are based on phytoplankton carbon (C) biomass, which is a fundamental biogeochemical and ecological variable and the “unit of accounting” in Earth system models. We present a novel bio-optical algorithm to retrieve size-partitioned phytoplankton carbon from ocean color satellite data. The algorithm is based on existing methods to estimate particle volume from a power-law particle size distribution (PSD). Volume is converted to carbon concentrations using a compilation of allometric relationships. We quantify absolute and fractional biomass in three PFTs based on size – picophytoplankton (0.5–2 µm in diameter), nanophytoplankton (2–20 µm) and microphytoplankton (20–50 µm). The mean spatial distributions of total phytoplankton C biomass and individual PFTs, derived from global SeaWiFS monthly ocean color data, are consistent with current understanding of oceanic ecosystems, i.e., oligotrophic regions are characterized by low biomass and dominance of picoplankton, whereas eutrophic regions have high biomass to which nanoplankton and microplankton contribute relatively larger fractions. Global climatological, spatially integrated phytoplankton carbon biomass standing stock estimates using our PSD-based approach yield ∼ 0.25 Gt of C, consistent with analogous estimates from two other ocean color algorithms and several state-of-the-art Earth system models. Satisfactory in situ closure observed between PSD and POC measurements lends support to the theoretical basis of the PSD-based algorithm. Uncertainty budget analyses indicate that absolute carbon concentration uncertainties are driven by the PSD parameter No which determines particle number concentration to first order, while uncertainties in PFTs' fractional contributions to total C biomass are mostly due to the allometric coefficients. The C algorithm presented here, which is not empirically constrained a priori, partitions biomass in size classes and introduces improvement over the assumptions of the other approaches. However, the range of phytoplankton C biomass spatial variability globally is larger than estimated by any other models considered here, which suggests an empirical correction to the No parameter is needed, based on PSD validation statistics. These corrected absolute carbon biomass concentrations validate well against in situ POC observations.

Phenology of Size-Partitioned Phytoplankton Carbon-Biomass from Ocean Color Remote Sensing and CMIP5 Models

We use a novel satellite time series of size-partitioned phytoplankton biomass to construct and analyze classical and novel seasonality metrics. Biomass is computed from SeaWiFS ocean color data using retrievals of the particle size distribution with the KSM09 algorithm and existing allometric relationships to convert volume to carbon. The phenological metrics include the peak blooming date, bloom strength, shape of the seasonal cycle, and reproducibility of the seasonal cycle. We compare the seasonal cycle of total biomass with that of three classical size classes (pico-, nano-, and micro-phytoplankton), which are correlated with phytoplankton functional types (PFTs). The spatial distribution of phenological metrics based on the new biomass and PFT data is qualitatively realistic, and is strongly correlated with bottom-up drivers such as sea surface temperature, mixed layer depth, winds, and photosynthetic available radiation. We find that low-biomass regions and non-blooming seasons are dominated by small phytoplankton sizes while high-biomass regions and blooming seasons are dominated by large phytoplankton. The biomass peak date doesn't change much across PFTs, but the blooming period is more prominent for large PFTs. Small PFTs act as a more constant biomass background, with smoother (less pronounced) seasonal cycles. We find significant differences between seasonality metrics in the SeaWiFS data and the latest generation of IPCC AR5 Earth System models (CMIP5). Models in the CMIP5 archive do not capture the pronounced mid-latitude and frontal PFT patterns found in the satellite data. In models, phytoplankton biomass peaks later at high latitudes and earlier at low latitudes. The models exhibit a higher reproducibility of the biomass seasonal cycle and larger phenological differences between PFTs than observed. Models fail to capture secondary peaks at mid and high latitudes. Continuous improvement of satellite algorithms that retrieve phytoplankton groups is necessary to advance the modelization of phytoplankton in Earth System Models.

The assessment of a global marine ecosystem model on the basis of emergent properties and ecosystem function: a case study with ERSEM

Abstract. Ecosystem models are often assessed using quantitative metrics of absolute ecosystem state, but these model–data comparisons are disproportionately vulnerable to discrepancies in the location of important circulation features. An alternative method is to demonstrate the models capacity to represent ecosystem function; the emergence of a coherent natural relationship in a simulation indicates that the model may have an appropriate representation of the ecosystem functions that lead to the emergent relationship. Furthermore, as emergent properties are large-scale properties of the system, model validation with emergent properties is possible even when there is very little or no appropriate data for the region under study, or when the hydrodynamic component of the model differs significantly from that observed in nature at the same location and time.A selection of published meta-analyses are used to establish the validity of a complex marine ecosystem model and to demonstrate the power of validation with emergent properties. These relationships include the phytoplankton community structure, the ratio of carbon to chlorophyll in phytoplankton and particulate organic matter, the ratio of particulate organic carbon to particulate organic nitrogen and the stoichiometric balance of the ecosystem.These metrics can also inform aspects of the marine ecosystem model not available from traditional quantitative and qualitative methods. For instance, these emergent properties can be used to validate the design decisions of the model, such as the range of phytoplankton functional types and their behaviour, the stoichiometric flexibility with regards to each nutrient, and the choice of fixed or variable carbon to nitrogen ratios.

Interannual variability of the phytoplankton community by the changes in vertical mixing and atmospheric deposition in the Ulleung Basin, East Sea: A modelling study

The East Sea (Japan Sea) ecosystem has experienced a significant warming and ever-increasing anthropogenic atmospheric deposition of nitrogen during recent decades. To understand the impacts of such environmental changes on the planktonic community, we set up a zero-dimensional European Regional Seas Ecosystem Model (ERSEM) in the Ulleung Basin, East Sea for the years 2001–2012. The model results show that as the winter maximum mixed layer depth (MMLD) changes, the growth and grazing loss of phytoplankton functional types (PFTs) are affected differently, resulting in differential success of PFTs in the upper mixed layer. Diatoms pre-empted the early spring growth by better utilization of light and nitrate. Diatoms’ advantages lessened as the MMLD decreased. Flagellates and picophytoplankton showed mixed responses to decreased MMLD. Their net primary productivity (NPP) and peak biomass decreased but their annual biomass increased due to decreased grazing. Dinoflagellates always did better when MMLD decreased. The model results also indicate that with an increase in atmospheric deposition, the picophytoplankton and the flagellates increased in summer, whereas the dinoflagellates and the diatoms decreased. For the study period, the atmospheric deposition in the Ulleung Basin increased the annual net primary production by 4.58% (mean; range 3.77–10.58%). Biological variables showed the largest responses in summer with high year-to-year variability. Picophytoplankton increased the most (summer increase mean: 23.23%; summer increase range: 9.12–42.6%) while dinoflagellates decreased the most (summer decrease mean: −2.33%; summer decrease range: −9.09 to 10.13%). The changes in flagellates and diatoms were much less. Taking the results together, it is likely that as the warming and atmospheric deposition continue to intensify into the future; the phytoplankton community in the region will shift to smaller phytoplankton with consequent changes of food web structure to follow.

Phenology of particle size distributions and primary productivity in the North Pacific subtropical gyre (Station ALOHA).

The particle size distribution (PSD) is a critical aspect of the oceanic ecosystem. Local variability in the PSD can be indicative of shifts in microbial community structure and reveal patterns in cell growth and loss. The PSD also plays a central role in particle export by influencing settling speed. Satellite‐based models of primary productivity (PP) often rely on aspects of photophysiology that are directly related to community size structure. In an effort to better understand how variability in particle size relates to PP in an oligotrophic ecosystem, we collected laser diffraction‐based depth profiles of the PSD and pigment‐based classifications of phytoplankton functional types (PFTs) on an approximately monthly basis at the Hawaii Ocean Time‐series Station ALOHA, in the North Pacific subtropical gyre. We found a relatively stable PSD in the upper water column. However, clear seasonality is apparent in the vertical distribution of distinct particle size classes. Neither laser diffraction‐based estimations of relative particle size nor pigment‐based PFTs was found to be significantly related to the rate of 14C‐based PP in the light‐saturated upper euphotic zone. This finding indicates that satellite retrievals of particle size, based on particle scattering or ocean color would not improve parameterizations of present‐day bio‐optical PP models for this region. However, at depths of 100–125 m where irradiance exerts strong control on PP, we do observe a significant linear relationship between PP and the estimated carbon content of 2–20 μm particles.

What drives the seasonality of air–sea CO2 fluxes in the ice-free zone of the Southern Ocean: A 1D coupled physical–biogeochemical model approach

The complex biogeochemical SWAMCO-3 model has been used to assess the response of the ice-free Southern Ocean to the physical and biological mechanisms governing air–sea CO2 exchanges. For this application, the model explicitly details the dynamics of three Phytoplankton Functional Types (PFTs) of importance for C, N, P, Si, Fe cycling and air–sea CO2 exchange in this area. These are the diatoms, the pico–nanophytoplankton and the coccolithophores whose growth regulation by light, temperature and nutrients has been obtained from a literature review of phenomenological observations available for these PFTs. The performance of the SWAMCO-3 model coupled to a vertical one-dimensional physical model was first assessed at the location of the JGOFS time-series station KERFIX. The model was able to reproduce a mean seasonal cycle based on years where a maximum of chemical and biological observations are available at this location (1993–1994, 1994–1995, 1998–1999 and 2000–2001). Ocean fCO2 in equilibrium with the atmosphere are simulated both in Austral winter associated with surface layer replenishment in DIC due to deep vertical mixing and in late summer as a consequence of the warming effect on the carbonate system. A clear under-saturation is found in spring/summer. Analysis of the modelled seasonal biogeochemical and physical features shows that thermodynamical conditions are driving the air–sea exchange of CO2 in the region, while the biological activity under the control of light and iron availability, is responsible for the predicted relatively modest annual carbon sink (−0.9molCm−2y−1).

Capturing optically important constituents and properties in a marine biogeochemical and ecosystem model

Abstract. We present a numerical model of the ocean that couples a three-stream radiative transfer component with a marine biogeochemical–ecosystem component in a dynamic three-dimensional physical framework. The radiative transfer component resolves the penetration of spectral irradiance as it is absorbed and scattered within the water column. We explicitly include the effect of several optically important water constituents (different phytoplankton functional types; detrital particles; and coloured dissolved organic matter, CDOM). The model is evaluated against in situ-observed and satellite-derived products. In particular we compare to concurrently measured biogeochemical, ecosystem, and optical data along a meridional transect of the Atlantic Ocean. The simulation captures the patterns and magnitudes of these data, and estimates surface upwelling irradiance analogous to that observed by ocean colour satellite instruments. We find that incorporating the different optically important constituents explicitly and including spectral irradiance was crucial to capture the variability in the depth of the subsurface chlorophyll a (Chl a) maximum. We conduct a series of sensitivity experiments to demonstrate, globally, the relative importance of each of the water constituents, as well as the crucial feedbacks between the light field, the relative fitness of phytoplankton types, and the biogeochemistry of the ocean. CDOM has proportionally more importance at attenuating light at short wavelengths and in more productive waters, phytoplankton absorption is relatively more important at the subsurface Chl a maximum, and water molecules have the greatest contribution when concentrations of other constituents are low, such as in the oligotrophic gyres. Scattering had less effect on attenuation, but since it is important for the amount and type of upwelling irradiance, it is crucial for setting sea surface reflectance. Strikingly, sensitivity experiments in which absorption by any of the optical constituents was increased led to a decrease in the size of the oligotrophic regions of the subtropical gyres: lateral nutrient supplies were enhanced as a result of decreasing high-latitude productivity. This new model that captures bio-optical feedbacks will be important for improving our understanding of the role of light and optical constituents on ocean biogeochemistry, especially in a changing environment. Further, resolving surface upwelling irradiance will make it easier to connect to satellite-derived products in the future.

Variation in phytoplankton composition between two North Pacific frontal zones along 158°W during winter–spring 2008–2011

Data from three research cruises along the 158°W meridian through the North Pacific Subtropical Frontal Zone (STF) during spring 2008, 2009, and 2011 were used to estimate phytoplankton functional types and size classes. These groups were used to describe phytoplankton composition at the North Pacific Subtropical (STF) and Transition Zone Chlorophyll (TZCF) Fronts, which represent ecologically important large-scale features in the central North Pacific. Phytoplankton class composition was consistent at each front through time, yet significantly different between fronts. The STF contained lower integrated chlorophyll-a concentrations, with surface waters dominated by picophytoplankton and a deep chlorophyll maximum equally comprised of pico- and nanophytoplankton. The TZCF contained significantly higher concentrations of nanophytoplankton through the water column, specifically the prymnesiophyte group. Integrated chlorophyll-a concentrations at the TZCF were 30–90% higher than at the STF, with the dominant increase in the signal from the nanophytoplanktonic prymnesiophyte group. The meridional position of the STF was consistently located near 32°N through these three years, with the more spatially variable TZCF ranging from 2° to 4° further north of the STF. This variability in the frontal position of the TZCF may lead to ecological impacts though the food web. Continued in-situ and remote monitoring, specifically during El Niño and ENSO neutral phases, will provide additional ecological information to help understand mechanistic causes of phytoplankton variability in this important ecological region.

Phytoplankton community structure in relation to vertical stratification along a north‐south gradient in the Northeast Atlantic Ocean

AbstractClimate change is affecting the hydrodynamics of the world's oceans. How these changes will influence the productivity, distribution and abundance of phytoplankton communities is an urgent research question. Here we provide a unique high‐resolution mesoscale description of the phytoplankton community composition in relation to vertical mixing conditions and other key physicochemical parameters along a meridional section of the Northeast Atlantic Ocean. Phytoplankton, assessed by a combination of flow cytometry and pigment fingerprinting (HPLC‐CHEMTAX), and physicochemical data were collected from the top 250 m water column during the spring of 2011 and summer of 2009. Multivariate analysis identified water column stratification (based on 100 m depth‐integrated Brunt–Väisälä frequency N2) as one of the key drivers for the distribution and separation of different phytoplankton taxa and size classes. Our results demonstrate that increased stratification (1) broadened the geographic range of Prochlorococcus as oligotrophic areas expanded northward, (2) increased the contribution of picoeukaryotic phytoplankton to total autotrophic organic carbon (< 20 μm), and (3) decreased the abundances of diatoms and cryptophytes. We discuss the implications of our findings for the classification of phytoplankton functional types in biogeochemical and ecological ocean models. As phytoplankton taxonomic composition and size affects productivity, biogeochemical cycling, ocean carbon storage and marine food web dynamics, the results provide essential information for models aimed at predicting future states of the ocean.

Remote sensing of phytoplankton functional types in the coastal ocean from the HyspIRI Preparatory Flight Campaign

The 2013–2015 Hyperspectral Infrared Imager (HyspIRI) Preparatory Flight Campaign, using the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) and MODIS/ASTER Airborne Simulator (MASTER), seeks to demonstrate appropriate sensor signal, spatial and spectral resolution, and orbital pass geometry for a global mission to reveal ecological and climatic gradients expressed in the selected California, USA study area. One of the awarded projects focused on the flight transects covering the coastal ocean to demonstrate that the AVIRIS data can be used to infer phytoplankton functional types at the land–sea interface. Specifically, this project directly assesses whether HyspIRI can provide adequate signal in the complex aquatic environment of the coastal zone to address questions of algal bloom dynamics, water quality, transient responses to human disturbance, river runoff, and red tides. Phytoplankton functional type (PFT), or biodiversity, can be determined from ocean color using the Phytoplankton Detection with Optics (PHYDOTax) algorithm and this information can be used to detect and monitor for harmful algal blooms. PHYDOTax is sensitive to spectral shape and accurate retrievals of ocean color across the visible spectral range is needed. The specific goal of this paper is to address the challenges of sensor capabilities and atmospheric correction in coastal environments by assessing two atmospheric correction methods using AVIRIS data for the retrieval of ocean color for use in derived products of chlorophyll-a and phytoplankton functional type. The atmospheric correction algorithms Atmospheric Removal (ATREM) and Tafkaa were applied to AVIRIS imagery of Monterey Bay, CA collected on 10 April 2013 and 31 October 2013. Data products from the imagery were compared with shipboard measurements including chlorophyll-a from whole-water samples and phytoplankton community structure estimated from diagnostic pigment markers using CHEMical TAXonomy (CHEMTAX). Using ATREM and Tafkaa and a selected set of input parameters for the scenes, we were unable to produce accurate retrievals of ocean color for the determination of chlorophyll-a and phytoplankton diversity. A modified ATREM correction produced science-quality data in which chlorophyll-a was accurately estimated using the Ocean Color 3 (OC3) chlorophyll-a algorithm, but biodiversity using PHYDOTax was not accurately estimated. Improvements in sensor calibration, sensitivity, and atmospheric correction of the HyspIRI imagery data set is needed in order to adequately estimate biogeochemically meaningful data products for the ocean such as chlorophyll-a, inherent optical properties, or PFTs. The HyspIRI Science Team is seeking improvements so the HyspIRI Airborne Campaign data set can be used for algorithm development to understand biodiversity and ecosystem function of coastal habitats that are facing increasing threats of human impact and climate change.

Effect of phytoplankton size classes on bio-optical properties of phytoplankton in the Western Iberian coast: Application of models

Chlorophyll-a satellite products are routinely used in oceanography, providing a synoptic and global view of phytoplankton abundance. However, these products lack information on the community structure of the phytoplankton, which is crucial for ecological modelling and ecosystem studies. To assess the usefulness of existing methods to differentiate phytoplankton functional types (PFT) or phytoplankton size classes from satellite data, in-situ phytoplankton samples collected in the Western Iberian coast, on the North-East Atlantic, were analysed for pigments and absorption spectra. Water samples were collected in five different locations, four of which were located near the shore and another in an open-ocean, seamount region. Three different modelling approaches for deriving phytoplankton size classes were applied to the in situ data. Approaches tested provide phytoplankton size class information based on the input of pigments data (Brewin et al., 2010), absorption spectra data (Ciotti et al., 2002) or both (Uitz et al., 2008).Following Uitz et al. (2008), results revealed high variability in microphytoplankton chlorophyll-specific absorption coefficients, ranging from 0.01 to 0.09m2 (mg chl)−1 between 400 and 500nm. This spectral analysis suggested, in one of the regions, the existence of small cells (<20μm) in the fraction of phytoplankton presumed to be microphytoplankton (based on diagnostic pigments). Ciotti et al. (2002) approach yielded the highest differences between modelled and measured absorption spectra for the locations where samples had high variability in community structure and cell size. The Brewin et al. (2010) pigment-based model was adjusted and a set of model coefficients are presented and recommended for future studies in offshore water of the Western Iberian coast.

Identification of dominant phytoplankton functional types in the Mediterranean Sea based on a regionalized remote sensing approach

During the last decade, the analysis of the ocean color satellite imagery has allowed determining the dominant phytoplankton groups in surface waters through the development of bio-optical models aimed at identifying the main phytoplankton functional types (PFTs) or size classes from space. One of these bio-optical model is PHYSAT, which is a global method applied for oceanic Case I water and used to identify in satellite pixels specific dominant phytoplankton groups, such as nanoeukaryotes, Prochlorococcus, Synechococcus, diatoms, Phaeocystis-like and coccolithophores. Here, we present a regionalized version of the PHYSAT method that has been specifically developed for the Mediterranean Sea due to the peculiarities of phytoplankton assemblages and succession than can be found in the basin and its particular optical properties. The updated version of the method, the so called PHYSAT-Med, has been validated successfully with large in situ datasets available for this oceanic region, mainly for nanoeukaryotes, Prochlorococcus, Synechococcus and diatoms. PHYSAT-Med allows to include a much higher number of pixels for the Mediterranean than PHYSAT does, through the use of a new Look-Up-Table created specifically for this oceanic region. Results provided by PHYSAT-Med showed the dominance of Synechococcus versus prochlorophytes throughout the year at the basin level, although nanoeukaryotes were more abundant during winter months. In addition, PHYSAT-Med data identified a rise in the eukaryote biomass (mainly diatoms) during the spring period (March to April), especially in the Ligurian and Adriatic seas. PHYSAT-Med represents a useful tool for the spatio-temporal monitoring of different dominant phytoplankton functional types in Mediterranean surface waters at a high resolution.

How important is diversity for capturing environmental-change responses in ecosystem models?

Abstract. Marine ecosystem models used to investigate how global change affects ocean ecosystems and their functioning typically omit pelagic plankton diversity. Diversity, however, may affect functions such as primary production and their sensitivity to environmental changes. Here we use a global ocean ecosystem model that explicitly resolves phytoplankton diversity by defining subtypes within four phytoplankton functional types (PFTs). We investigate the model's ability to capture diversity effects on primary production under environmental change. An idealized scenario with a sudden reduction in vertical mixing causes diversity and primary-production changes that turn out to be largely independent of the number of coexisting phytoplankton subtypes. The way diversity is represented in the model provides a small number of niches with respect to nutrient use in accordance with the PFTs defined in the model. Increasing the number of phytoplankton subtypes increases the resolution within the niches. Diversity effects such as niche complementarity operate between, but not within PFTs, and are constrained by the variety of traits and trade-offs resolved in the model. The number and nature of the niches formulated in the model, for example via trade-offs or different PFTs, thus determines the diversity effects on ecosystem functioning captured in ocean ecosystem models.