Phytoplankton Functional Types Research Articles

Characterization of phytoplankton functional types in the western Bay of Bengal: HPLC- and CHEMTAX-based approach.

This study investigates phytoplankton functional group variations in the western Bay of Bengal (WBoB) during the Spring Intermonsoon. Samples were collected from four cross-shore transects: Mahanadi (MN), Vamsadhara (VD), Godavari (GD), and Krishna (KS). East India Coastal Current and warm gyre influenced the southern transects (KS, GD), VD was experiencing moderate upwelling and MN was characterized by low salinity and oligotrophic conditions due to freshwater input. In response to hydrography, phytoplankton biomass and functional types differed within and between the transects. Chlorophyll-a (Chl-a) was spatially high in VD and low in MN. The subsurface Chlorophyll-a maxima (SSCM) was prominent and shallow in the MN and VD, compared to the southern transects. Total diagnostic pigments concentration was high in VD, followed by GD, KS and MN. Phytoplankton functional groups and each groups contribution to Chl-a was calculated through CHEmical Taxonomy (CHEMTAX). Diatoms and cyanophytes were the dominant functional types in the surface layers. Progressive shift from diatoms in the nearshore region to cyanophytes in the offshore was observed. The low saline and low-nutrient conditions were conducible for the growth of cyanophytes, while nutrient-rich optimum light layer of SSCM and upper layer of VD were favorable for diatoms. Cryptophytes contribution to Chl-a was higher in southern transects compared to the north. Prymnesiophytes and prasinophytes were high in the subsurface and deep layers could be due to their adaptions to light and nutrients. The present study highlights the significance of physical processes associated hydrography in structuring the phytoplankton functional types.

Phytoplankton thermal trait parameterization alters community structure and biogeochemical processes in a modeled ocean.

Phytoplankton exhibit diverse physiological responses to temperature which influence their fitness in the environment and consequently alter their community structure. Here, we explored the sensitivity of phytoplankton community structure to thermal response parameterization in a modelled marine phytoplankton community. Using published empirical data, we evaluated the maximum thermal growth rates (μmax ) and temperature coefficients (Q10 ; the rate at which growth scales with temperature) of six key Phytoplankton Functional Types (PFTs): coccolithophores, cyanobacteria, diatoms, diazotrophs, dinoflagellates, and green algae. Following three well-documented methods, PFTs were either assumed to have (1) the same μmax and the same Q10 (as in to Eppley, 1972), (2) a unique μmax but the same Q10 (similar to Kremer etal., 2017), or (3) a unique μmax and a unique Q10 (following Anderson etal., 2021). These trait values were then implemented within the Massachusetts Institute of Technology biogeochemistry and ecosystem model (called Darwin) for each PFT under a control and climate change scenario. Our results suggest that applying a μmax and Q10 universally across PFTs (as in Eppley, 1972) leads to unrealistic phytoplankton communities, which lack diatoms globally. Additionally, we find that accounting for differences in the Q10 between PFTs can significantly impact each PFT's competitive ability, especially at high latitudes, leading to altered modeled phytoplankton community structures in our control and climate change simulations. This then impacts estimates of biogeochemical processes, with, for example, estimates of export production varying by ~10% in the Southern Ocean depending on the parameterization. Our results indicate that the diversity of thermal response traits in phytoplankton not only shape community composition in the historical and future, warmer ocean, but that these traits have significant feedbacks on global biogeochemical cycles.

Remote sensing of phytoplankton community composition in the northern Benguela upwelling system

Marine phytoplankton in the northern Benguela upwelling system (nBUS) serve as a food and energy source fuelling marine food webs at higher trophic levels and thereby support a lucrative fisheries industry that sustain local economies in Namibia. Microscopic and chemotaxonomic analyses are among the most commonly used techniques for routine phytoplankton community analysis and monitoring. However, traditional in situ sampling methods have a limited spatiotemporal coverage. Satellite observations far surpass traditional discrete ocean sampling methods in their ability to provide data at broad spatial scales over a range of temporal resolution over decadal time periods. Recognition of phytoplankton ecological and functional differences has compelled advancements in satellite observations over the past decades to go beyond chlorophyll-a (Chl-a) as a proxy for phytoplankton biomass to distinguish phytoplankton taxa from space. In this study, a multispectral remote sensing approach is presented for detection of dominant phytoplankton groups frequently observed in the nBUS. Here, we use a large microscopic dataset of phytoplankton community structure and the Moderate Resolution Imaging Spectroradiometer of aqua satellite match-ups to relate spectral characteristics of in water constituents to dominance of specific phytoplankton groups. The normalised fluorescence line height, red-near infrared as well as the green/green spectral band-ratios were assigned to the dominant phytoplankton groups using statistical thresholds. The ocean colour remote sensing algorithm presented here is the first to identify phytoplankton functional types in the nBUS with far-reaching potential for mapping the phenology of phytoplankton groups on unprecedented spatial and temporal scales towards advanced ecosystem understanding and environmental monitoring.

Seasonal and spatial dynamics of the phytoplankton community in the Salish Sea, 2015–2019

A chemotaxonomic approach (HPLC) was used to determine the phytoplankton composition for the Salish Sea (coastal NE Pacific Ocean). The method was applied to 721 samples collected between 2015 and 2019. Microscopy was used to build then verify the CHEMTAX matrix and CHEMTAX outputs. Statistical methods were used to describe the patterns of phytoplankton composition over space and time. HPLC produced a more complete picture of the phytoplankton community than previous studies relying on microscopy. Nine taxonomic groups and four phytoplankton functional types were identified: (1) centric diatoms were present year round and were dominant during the spring bloom; (2) small flagellates (cryptophytes, haptophytes, prasinophytes) and pennate diatoms were ubiquitous but generally not bloom-forming; (3) large flagellates (dinoflagellates, dictyochophytes, raphidophytes) were mostly absent but with occasional very large blooms; and (4) cyanobacteria were rare. The pigment violaxanthin was diagnostic for Heterosigma akashiwo, which formed the largest bloom observed in our study (75 μg/L Tchl a). Cluster and network analyses identified three regions based on similarities in phytoplankton composition: (1) Juan de Fuca Strait and tidally mixed areas, (2) central Strait of Georgia, and (3) northern Strait of Georgia. Seasonally, significant differences in taxonomic composition occurred between winter and spring, and interannually between 2015 (a warmer year) and 2017 (a cooler year). Centric diatoms were associated with stronger vertical mixing, whereas haptophytes were associated with higher temperatures, reduced vertical mixing and lower nutrients. The CHEMTAX matrix we present is robust and useful for future studies in this area.

Flow Structures With High Lagrangian Coherence Rate Promote Diatom Blooms in Oligotrophic Waters

AbstractDiatoms are among the most efficient autotrophic organisms for oceanic primary production and carbon sequestration. Yet, the spatial distributions of these planktonic organisms remain puzzling and the underlying physical processes poorly known, especially in oligotrophic open waters. Here we investigate what dynamical conditions are conducive to episodic diatom blooms in oceanic deserts based on Lagrangian diagnosis and satellite‐derived phytoplankton functional types and currents. The coherence of the flow is diagnosed in space and time simultaneously through the Lagrangian coherence rate (LCR) to identify which dynamical structures favor diatom growth. Observations evidence that flow structures with high LCR (40 days or longer) in areas with elevated eddy kinetic energy and vorticity sustain high diatom concentrations in the sunlit layers. Our findings show that the integration of Eulerian kinematic variables into a Lagrangian frame reveals new dynamical aspects of geophysical turbulence and unveil their biological impacts.

Response of phytoplankton functional types to Hurricane Fabian (2003) in the Sargasso Sea

Understanding how tropical cyclones affect phytoplankton communities is important for studies on ecological variability. Most studies assessing the post-storm phytoplankton response rely on satellite observations of chlorophyll a concentration, which inform on the ocean surface conditions and the whole phytoplankton community. In this work, we assess the potential of the Massachusetts Institute of Technology marine ecosystem model to account for the response of individual phytoplankton functional types (PFTs, coccolithophores, diatoms, diazotrophs, mixotrophic dinoflagellates, picoeukaryotes, Prochlorococcus and Synechococcus) in the euphotic zone to the passage of Hurricane Fabian (2003) across the tropical and subtropical Sargasso Sea. Fabian induced a significant mean concentration increase (t-test, p < 0.05) of all PFTs in the tropical waters (except for Prochlorococcus), which was driven by the mean nutrient concentration increase and by a limited zooplankton grazing pressure. More specifically, the post-storm nutrient enrichment increased the contribution of fast-growing PFTs (e.g. diatoms and coccolithophores) to the total phytoplankton concentration and decreased the contribution of slow-growing dominant groups (e.g. picoeukaryotes, Prochlorococcus and Synechococcus), which lead to a significant increase (t-test, p < 0.05) of the Shannon diversity index values. Overall, the model captured the causal relationship between nutrient and PFT concentration increases in the tropical waters, although it only reproduced the most pronounced PFT responses such as those in the deep euphotic zone. In contrast, the model did not capture the oceanic perturbations induced by Fabian as observed in satellite imagery in the subtropical waters, probably due to its limited performance in this complex oceanographic area.

Ocean color algorithm for the retrieval of the particle size distribution and carbon-based phytoplankton size classes using a two-component coated-sphere backscattering model

Abstract. The particle size distribution (PSD) of suspended particles in near-surface seawater is a key property linking biogeochemical and ecosystem characteristics with optical properties that affect ocean color remote sensing. Phytoplankton size affects their physiological characteristics and ecosystem and biogeochemical roles, e.g., in the biological carbon pump, which has an important role in the global carbon cycle and thus climate. It is thus important to develop capabilities for measurement and predictive understanding of the structure and function of oceanic ecosystems, including the PSD, phytoplankton size classes (PSCs), and phytoplankton functional types (PFTs). Here, we present an ocean color satellite algorithm for the retrieval of the parameters of an assumed power-law PSD. The forward optical model considers two distinct particle populations: phytoplankton and non-algal particles (NAPs). Phytoplankton are modeled as coated spheres following the Equivalent Algal Populations (EAP) framework, and NAPs are modeled as homogeneous spheres. The forward model uses Mie and Aden–Kerker scattering computations, for homogeneous and coated spheres, respectively, to model the total particulate spectral backscattering coefficient as the sum of phytoplankton and NAP backscattering. The PSD retrieval is achieved via spectral angle mapping (SAM), which uses backscattering end-members created by the forward model. The PSD is used to retrieve size-partitioned absolute and fractional phytoplankton carbon concentrations (i.e., carbon-based PSCs), as well as particulate organic carbon (POC), using allometric coefficients. This model formulation also allows the estimation of chlorophyll a concentration via the retrieved PSD, as well as percent of backscattering due to NAPs vs. phytoplankton. The PSD algorithm is operationally applied to the merged Ocean Colour Climate Change Initiative (OC-CCI) v5.0 ocean color data set. Results of an initial validation effort are also presented using PSD, POC, and picophytoplankton carbon in situ measurements. Validation results indicate the need for an empirical tuning for the absolute phytoplankton carbon concentrations; however these results and comparison with other phytoplankton carbon algorithms are ambiguous as to the need for the tuning. The latter finding illustrates the continued need for high-quality, consistent, large global data sets of PSD, phytoplankton carbon, and related variables to facilitate future algorithm improvements.

Process controlling iron-manganese regulation of the Southern Ocean biological carbon pump.

Iron (Fe) is a key limiting nutrient driving the biological carbon pump and is routinely represented in global ocean biogeochemical models. However, in the Southern Ocean, the potential role for other micronutrients has not received the same attention. For example, although manganese (Mn) is essential to photosynthetic oxygen production and combating oxidative stress, it is not included in ocean models and a clear understanding of its interaction with Fe in the region is lacking. This is especially important for the Southern Ocean because both Mn and Fe are strongly depleted. We use a hierarchical modelling approach to explore how the physiological traits associated with Fe and Mn contribute to driving the footprint of micronutrient stress across different phytoplankton functional types (PFTs). We find that PFT responses are driven by physiological traits associated with their physiological requirements and acclimation to environmental conditions. Southern Ocean-specific adaptations to prevailing low Fe, such as large photosynthetic antenna sizes, are of major significance for the regional biological carbon pump. Other traits more strongly linked to Mn, such as dealing with oxidative stress, may become more important under a changing Fe supply regime. This article is part of a discussion meeting issue 'Heat and carbon uptake in the Southern Ocean: the state of the art and future priorities'.

Impact of Pacific Ocean heatwaves on phytoplankton community composition

Since 2013, marine heatwaves have become recurrent throughout the equatorial and northeastern Pacific Ocean and are expected to increase in intensity relative to historic norms. Among the ecological ramifications associated with these high temperature anomalies are increased mortality of higher trophic organisms such as marine mammals and seabirds, which are likely triggered by changes in the composition of phytoplankton, the base of the marine trophic food web. Here, we assimilated satellite ocean color data into an ocean biogeochemical model to describe changes in the abundance of phytoplankton functional types (PFTs) during the last decade’s (2010s) warm anomalies in the equatorial and northeastern Pacific Ocean. We find important changes associated with the “Blob” warm anomaly in the Gulf of Alaska, where reduced silica supply led to a switch in community composition from diatoms to dinoflagellates, resulting in an increase in surface ocean chlorophyll during the Summer–Fall of 2014. A more dramatic change was observed in the equatorial Pacific, where the extreme warm conditions of the 2016 El Niño resulted in a major decline of about 40% in surface chlorophyll, which was associated with a nearly total collapse in diatoms.

Seasonal dynamics of major phytoplankton functional types in the coastal waters of the west coast of Canada derived from OLCI Sentinel 3A

Monitoring the spatial distribution and seasonal dynamics of phytoplankton functional types (PFTs) in coastal oceans is essential for understanding fisheries production, changes in water quality, and carbon export to the deep ocean. The launch of new generation ocean color sensors such as OLCI (Ocean Land Color Instrument) onboard Sentinel 3A provides an unprecedented opportunity to study the surface dynamics of PFTs at high spatial (300 m) and temporal (daily) resolution. Here we characterize the seasonal dynamics of the major PFTs over the surface waters of the west coast of Canada using OLCI imagery and Chemical Taxonomy (CHEMTAX, v1.95) software. The satellite-based approach was adapted from a previously proven Empirical Orthogonal Function (EOF)-based algorithm by using a local matchup dataset comprising CHEMTAX model output and EOF scores derived from OLCI remote sensing reflectance. The algorithm was developed for the following PFTs: diatoms, dinoflagellates, dictyochophytes, haptophytes, green algae, cryptophytes, cyanobacteria, raphidophytes, and total chlorophyll-a (TChla) concentration. Of these PFTs, first level evaluation of the OLCI-derived retrievals showed reliable performance for diatoms and raphidophytes. The second level of validation showed that TChla had the best performance, and green algae, cryptophytes, and diatoms followed seasonal trends of a high temporal resolution in situ CHEMTAX time-series. Somewhat reduced correspondence was observed for raphidophytes. Due to their low contribution to the phytoplankton community (26%) and low range of variation, weak performance was noted for haptophytes, dictyochophytes, cyanobacteria, and dinoflagellates. The EOF-based PFT maps from daily OLCI imagery showed seasonal spring and fall diatom blooms with succession from spring blooms to high diversity flagellate dominated summer conditions. Furthermore, strong localized summer raphidophyte blooms (Heterosigma akashiwo) were observed, which are a regionally important harmful species. Overall, this study demonstrates the potential of the OLCI in deriving the surface dynamics of major PFTs of the Strait of Georgia (SoG), a critical habitat for the juvenile Pacific Salmon.

Autonomous Shipborne In Situ Reflectance Data in Optically Complex Coastal Waters: A Case Study of the Salish Sea, Canada

Present limitations on using satellite imagery to derive accurate chlorophyll concentrations and phytoplankton functional types arise from insufficient in situ measurements to validate the satellite reflectance, Rrs0+. We installed a set of hyperspectral radiometers with autonomous solar tracking capability, collectively named SAS Solar Tracker (Satlantic Inc./Sea-Bird), on top of a commercial ferry, to measure the in situ reflectance as the ferry crosses the Salish Sea, Canada. We describe the SAS Solar Tracker installation procedure, which enables a clear view of the sea surface and minimizes the interference caused by the ship superstructure. Corrections for residual ship superstructure perturbations and non-nadir-viewing geometry are applied during data processing to ensure optimal data quality. It is found that the ship superstructure perturbation correction decreased the overall Rrs0+ by 0.00055 sr−1, based on a black-pixel assumption for the infrared band of the lowest acquired turbid water. The BRDF correction using the inherent optical properties approach lowered the spectral signal by ∼5–10%, depending on the wavelength. Data quality was evaluated according to a quality assurance method considering spectral shape similarity, and ∼92% of the acquired reflectance data matched well against the global database, indicating high quality.

Characterization of Seasonal Phytoplankton Pigments and Functional Types around Offshore Island in the East/Japan Sea, Based on HPLC Pigment Analysis

In this study, we investigated the seasonal phytoplankton community and phytoplankton functional types (PFTs) in the vicinity of Dokdo Island, located in the East/Japan Sea, in 2019. With strong seasonal winds, the water column was well mixed in winter. In spring and autumn, the upper mixed layer depth (MLD) was relatively deep, and the Subsurface Chlorophyll Maximum (SCM) formed in the middle layer. Small phytoplankton were dominant in the summer, which is a time of high water temperatures and strong stratification associated with a shallower MLD. Based on CHEMTAX analysis, in spring, the high phytoplankton biomass was mainly derived from cyanobacteria, diatoms, and dinoflagellates. In summer, &gt;73.2% of the surface biomass was comprised of cyanobacteria. In autumn, pelagophytes accounted for the highest proportion of the biomass. The fraction of microphytoplankton (fmicro) was highest in winter and spring, whereas the fraction of nanophytoplankton (fnano) was highest in autumn and summer. A high fraction of picophytoplankton (fpico) was evident in the surface layers in summer. Values for both the photoprotection index (PI) and the ratio of photoprotective carotenoids (PPC) to photosynthetic carotenoids (PSC) indicate that this study area had high primary productivity in 2019. In order to predict long-term changes in marine food webs due to climate change, it is important to evaluate the size and composition of phytoplankton.

Phytoplankton diversity emerging from chromatic adaptation and competition for light

The phytoplankton absorption cross-section is a fundamental quantity in biogeochemical ocean models that alters the underwater spectral light field and the photosynthetic response of phytoplankton. Phytoplankton taxa are characterized by absorption spectra with defined absorption bands in the visible region of the light spectrum that govern the capability of different taxa of phytoplankton to exploit light as a resource for growth. The interplay between the spatial and temporal gradients of underwater spectral light and the light absorption characteristics of different phytoplankton types contribute to the interactions and selection among groups and hence can be a determinant in shaping phytoplankton diversity and biogeography. In this work, we used a biogeochemical model of the Mediterranean Sea to simulate nine optically different phytoplankton functional types (PFTs) and coupled it to a radiative transfer model to simulate the spectral underwater light field where the PFTs interact. We investigated the competitive advantage provided by the different absorption spectra and the possibilities of coexistence emerging from the availability of different light habitats. By considering non-spectrally resolved optical differences among PFTs, our model results led to the dominance of Synechococcus sp. within picophytoplankton, coccolithophores within nanophytoplankton and dinoflagellates within microphytoplankton. By including the spectral dependency of photosynthesis, we observed how the availability of different spectral light habitats led to the coexistence of picophytoplankton groups in clear waters, whereas for nano- and microphytoplankton PFTs, the extent of coexistence permitted by light fluctuations was minimal. By combining optical and functional differences in the PFT description, we obtained PFT distributions that were in relative agreement with observed phytoplankton distributions in the Mediterranean Sea estimated from satellite and in situ high-performance liquid chromatography sampling. This result suggests that combining spectrally resolved optical traits with functional traits in the description of the autotrophic community can be a valuable tool to improve simulations of the diversity and biogeography of primary producers in the ocean.

Functional Stability of a Coastal Mediterranean Plankton Community During an Experimental Marine Heatwave

As heatwaves are expected to increase in frequency and intensity in the Mediterranean Sea due to global warming, we conducted an in situ mesocosm experiment for 20 days during the late spring and early summer of 2019 in a coastal Mediterranean lagoon to investigate the effects of heatwaves on the composition and function of coastal plankton communities. A heatwave was simulated by elevating the water temperature of three mesocosms to +3°C while three control mesocosms had natural lagoon water temperature, for 10 days. Further, the heating procedure was halted for 10 days to study the resilience and recovery of the system. Automated high frequency monitoring of dissolved oxygen concentration and saturation, chlorophyll-a fluorescence, photosynthetic active radiation, salinity, and water temperature was completed with manual sampling for nutrient and phytoplankton pigment analyses. High-frequency data were used to estimate different functional processes: gross primary production (GPP), community respiration (R), and phytoplankton growth (μ), and loss (l) rates. Ecosystem stability was assessed by calculating resistance, resilience, recovery, and temporal stability in terms of the key functions (GPP, R, μ, and l). Meanwhile, the composition of phytoplankton functional types (PFT) was assessed through chemotaxonomic pigment composition. During the heatwave, GPP, R, μ, and l increased by 31, 49, 16, and 21%, respectively, compared to the control treatment. These positive effects persisted several days after the offset of the heatwave, resulting in low resilience in these key functions. However, GPP and R recovered almost completely at the end of the experiment, suggesting that the effect of the heatwave on these two rates was reversible. The heatwave also affected the PFT composition, as diatoms, prymnesiophytes, and cyanobacteria were favored, whereas dinoflagellates were negatively affected. By highlighting important effects of a simulated marine heatwave on the metabolism and functioning of a coastal Mediterranean plankton community, this study points out the importance to extend this type of experiments to different sites and conditions to improve our understanding of the impacts of this climate-change related stressor that will grow in frequency and intensity in the future.

Marine phytoplankton functional types exhibit diverse responses to thermal change

Marine phytoplankton generate half of global primary production, making them essential to ecosystem functioning and biogeochemical cycling. Though phytoplankton are phylogenetically diverse, studies rarely designate unique thermal traits to different taxa, resulting in coarse representations of phytoplankton thermal responses. Here we assessed phytoplankton functional responses to temperature using empirically derived thermal growth rates from four principal contributors to marine productivity: diatoms, dinoflagellates, cyanobacteria, and coccolithophores. Using modeled sea surface temperatures for 1950–1970 and 2080–2100, we explored potential alterations to each group’s growth rates and geographical distribution under a future climate change scenario. Contrary to the commonly applied Eppley formulation, our data suggest phytoplankton functional types may be characterized by different temperature coefficients (Q10), growth maxima thermal dependencies, and thermal ranges which would drive dissimilar responses to each degree of temperature change. These differences, when applied in response to global simulations of future temperature, result in taxon-specific projections of growth and geographic distribution, with low-latitude coccolithophores facing considerable decreases and cyanobacteria substantial increases in growth rates. These results suggest that the singular effect of changing temperature may alter phytoplankton global community structure, owing to the significant variability in thermal response between phytoplankton functional types.

Trends in phytoplankton communities within large marine ecosystems diverge from the global ocean

Large marine ecosystems (LMEs) are highly productive regions of the world ocean under anthropogenic pressures; we analyzed trends in sea surface temperature (SST), cloud fraction (CF), and chlorophyll concentration (CHL) over the period 1998–2019. Trends in these parameters within LMEs diverged from the world ocean. SST and CF inside LMEs increased at greater rates inside LMEs, whereas CHL decreased at a greater rates. CHL declined in 86% of all LMEs and of those trends, 70% were statistically significant. Complementary analyses suggest phytoplankton functional types within LMEs have also diverged from those characteristic of the world ocean, most notably, the contribution of diatoms and dinoflagellates, which have declined within LMEs. LMEs appear to be warming rapidly and receiving less solar radiation than the world ocean, which may be contributing to changes at the base of the food chain. Despite increased fishing effort, fishery yields in LMEs have not increased, pointing to limitations related to productivity. These changes raise concerns over the stability of these ecosystems and their continued ability to support services to human populations.

Global Chlorophyll a Concentrations of Phytoplankton Functional Types With Detailed Uncertainty Assessment Using Multisensor Ocean Color and Sea Surface Temperature Satellite Products

AbstractFirst, we retune an algorithm based on empirical orthogonal functions (EOFs) for globally retrieving the chlorophyll a concentration (Chl‐a) of phytoplankton functional types (PFTs) from multisensor merged ocean color (OC) products. The retuned algorithm, referred to as EOF‐SST hybrid algorithm, is improved by: (i) using 23% more matchups between the updated global in situ pigment database and satellite remote sensing reflectance (Rrs) products, and (ii) including sea surface temperature (SST) as an additional input parameter. In addition to the Chl‐a of the six PFTs (diatoms, haptophytes, dinoflagellates, green algae, prokaryotes, and Prochlorococcus), the fractions of prokaryote and Prochlorococcus Chl‐a to total Chl‐a (TChl‐a), are also retrieved by the EOF‐SST hybrid algorithm. Matchup data are separated for low and high‐temperature regimes based on different PFT dependences on SST, to establish SST‐separated hybrid algorithms which demonstrate further improvements in performance as compared to the EOF‐SST hybrid algorithm. The per‐pixel uncertainty of the retrieved TChl‐a and PFT products is estimated by taking into account the uncertainties from both input data and model parameters through Monte Carlo simulations and analytical error propagation. The algorithm and its method to determine uncertainties can be transferred to similar OC products until today, enabling long‐term continuous satellite observations of global PFT products. Satellite PFT uncertainty is essential to evaluate and improve coupled ecosystem‐ocean models which simulate PFTs, and furthermore can be used to directly improve these models via data assimilation.

MESMO 3: Flexible phytoplankton stoichiometry and refractory dissolved organic matter

Abstract. We describe the third version of Minnesota Earth System Model for Ocean biogeochemistry (MESMO 3), an Earth system model of intermediate complexity, with a dynamical ocean, dynamic–thermodynamic sea ice, and an energy–moisture-balanced atmosphere. A major feature of version 3 is the flexible C:N:P ratio for the three phytoplankton functional types represented in the model. The flexible stoichiometry is based on the power law formulation with environmental dependence on phosphate, nitrate, temperature, and light. Other new features include nitrogen fixation, water column denitrification, oxygen and temperature-dependent organic matter remineralization, and CaCO3 production based on the concept of the residual nitrate potential growth. In addition, we describe the semi-labile and refractory dissolved organic pools of C, N, P, and Fe that can be enabled in MESMO 3 as an optional feature. The refractory dissolved organic matter can be degraded by photodegradation at the surface and hydrothermal vent degradation at the bottom. These improvements provide a basis for using MESMO 3 in further investigations of the global marine carbon cycle to changes in the environmental conditions of the past, present, and future.

Assessment of a regional physical–biogeochemical stochastic ocean model. Part 2: Empirical consistency

In this Part 2 article of a two-part series, observations based on satellite missions were used to evaluate the empirical consistency of model ensembles generated via stochastic modelling of ocean physics and biogeochemistry. A high-resolution Bay of Biscay configuration was used as a case study to explore the model error subspace in both the open and coastal ocean. In Part 1 of this work, three experiments were carried out to generate model ensembles by perturbing only physics, only biogeochemistry, and both of them simultaneously. In Part 2 of this work, empirical consistency was checked, first by means of rank histograms projecting the data onto the model ensemble classes, and second, by pattern-selective consistency criteria in the space of “array modes” defined as eigenvectors of the representer matrix. Rank histograms showed large dependency on geographical region and on season for sea surface temperature (SST), sea-level anomaly (SLA), and phytoplankton functional types (PFT), shifting from consistent model-data configurations to large biases because of model ensemble underspread. Consistency for SST array modes was found to be verified at large, small and coastal scales soon after the ensemble spin-up. Array modes for the along-track sea-level showed useful consistent information at large scales and at the mesoscale; for the gridded SLA was verified only at large scale. Array modes showed that biogeochemical model uncertainties generated by stochastic physics, were effectively detected by PFT measurements at large scales, as well as at mesoscale and small-scale. By contrast, perturbing only biogeochemistry, with an identical physical forcing across the ensemble, limits the potential of PFT measurements at detecting and possibly correcting small-scale biogeochemical model errors. When an ensemble was found to be inconsistent with observations along a particular direction (here, an array mode), a plausible reason is that other error processes must have been active in the model, in addition to the ones at work across the ensemble.

Changing Physical Conditions and Lower and Upper Trophic Level Responses on the US Northeast Shelf

Sea surface temperature (SST), salinity, and chlorophyll concentration (CHL) have changed in the US Northeast Shelf ecosystem over recent decades. The changes in these parameters were distinctly marked by change points around the year 2012 resulting in a 0.83°C increase in SST, a 0.3 PSU increase in salinity, and decrease in CHL in excess of 0.4 mg m-3. Where temperature and salinity shifted in mean level around their respective change points, CHL declined in a more monotonic fashion. Modelled data suggest that the shift in CHL resulted in a greater contribution of pico- and nanophytoplankton and a decreased contribution of microphytoplankton to overall CHL. Complementary estimates of the contribution of different phytoplankton functional types suggest a diminished contribution of diatoms to the phytoplankton community. Hence, not only is there evidence of a decline in the overall primary production capacity of the ecosystem, but also evidence of a fundamental change in the size and quality of phytoplankton supporting food webs. Two ecosystem responses to the observed changes in SST, salinity, and CHL were analyzed. Both length and weight at age have declined for a number of species, and both measures of growth appear to be negatively associated with temperature and positively associated with CHL. Biomass of fish and macroinvertebrates has declined in recent years, with a decrease in pelagic species associated with a decrease in CHL, while the decline in demersal species was more associated with an increase in temperature. Collectively, these ecosystem changes appear to be the result of the complex interactions of both thermal effects and changes at the base of the food web.