Substantial energy input to the mesopelagic ecosystem from the seasonal mixed-layer pump

This is the author accepted manuscript. The final version is available from Nature Research via the DOI in this record.The ocean region known as the mesopelagic zone, which is at depths of about 100-1,000 m, harbours one of the largest ecosystems and fish stocks on the planet. Life in this region is believed to rely on particulate organic carbon supplied by the biological carbon pump. Yet this supply appears insufficient to meet mesopelagic metabolic demands. An additional organic carbon source to the mesopelagic zone could be provided by the seasonal entrainment of surface waters in deeper layers, a process known as the mixed-layer pump. Little is known about the magnitude and spatial distribution of this process globally or its potential to transport carbon to the mesopelagic zone. Here we combine mixed-layer depth data from Argo floats with satellite estimates of particulate organic carbon concentrations to show that the mixed-layer pump supplies an important seasonal flux of organic carbon to the mesopelagic zone. We estimate that this process is responsible for a global flux of 0.1-0.5 Pg C yr-1. In high-latitude regions where the mixed layer is usually deep, this flux amounts on average to 23% of the carbon supplied by fast sinking particles, but it can be greater than 100%. We conclude that the seasonal mixed-layer pump is an important source of organic carbon for the mesopelagic zone.UK National Centre for Earth Observation, UK NERCMarie Curie(UK) NERC National Capability in Sustained Observations and Marine ModellingEuropean Research CouncilH2020 ATLANTOS EU projec

Assimilation of ocean-colour plankton functional types to improve marine ecosystem simulations

We assimilated plankton functional types (PFTs) derived from ocean colour into a marine ecosystem model, to improve the simulation of biogeochemical indicators and emerging properties in a shelf sea. Error-characterized chlorophyll concentrations of four PFTs (diatoms, dinoflagellates, nanoplankton and picoplankton), as well as total chlorophyll for comparison, were assimilated into a physical-biogeochemical model of the North East Atlantic, applying a localized Ensemble Kalman filter. The reanalysis simulations spanned the years 1998 to 2003. The skill of the reference and reanalysis simulations in estimating ocean colour and in situ biogeochemical data were compared by using robust statistics. The reanalysis outperformed both the reference and the assimilation of total chlorophyll in estimating the ocean-colour PFTs (except nanoplankton), as well as the not-assimilated total chlorophyll, leading the model to simulate better the plankton community structure. Crucially, the reanalysis improved the estimates of not-assimilated in situ data of PFTs, as well as of phosphate and pCO2, impacting the simulation of the air-sea carbon flux. However, the reanalysis increased further the model overestimation of nitrate, in spite of increases in plankton nitrate uptake. The method proposed here is easily adaptable for use with other ecosystem models that simulate PFTs, for, e.g., reanalysis of carbon fluxes in the global ocean and for operational forecasts of biogeochemical indicators in shelf-sea ecosystems

Flexible C : N ratio enhances metabolism of large phytoplankton when resource supply is intermittent

Abstract. Phytoplankton cell size influences particle sinking rate, food web interactions and biogeographical distributions. We present a model in which the uptake, storage and assimilation of nitrogen and carbon are explicitly resolved in different-sized phytoplankton cells. In the model, metabolism and cellular C : N ratio are influenced by the accumulation of carbon polymers such as carbohydrate and lipid, which is greatest when cells are nutrient starved, or exposed to high light. Allometric relations and empirical data sets are used to constrain the range of possible C : N, and indicate that larger cells can accumulate significantly more carbon storage compounds than smaller cells. When forced with extended periods of darkness combined with brief exposure to saturating irradiance, the model predicts organisms large enough to accumulate significant carbon reserves may on average synthesize protein and other functional apparatus up to five times faster than smaller organisms. The advantage of storage in terms of average daily protein synthesis rate is greatest when modeled organisms were previously nutrient starved, and carbon storage reservoirs saturated. Small organisms may therefore be at a disadvantage in terms of average daily growth rate in environments that involve prolonged periods of darkness and intermittent nutrient limitation. We suggest this mechanism is a significant constraint on phytoplankton C : N variability and cell size distribution in different oceanic regimes. </jats:p

Modeling the Seasonality and Controls of Nitrous Oxide Emissions on the Northwest European Continental Shelf

Estimates of oceanic emissions of nitrous oxide (N2O) are surrounded by a considerable degree of uncertainty, particularly regarding the contribution of productive shelf regions, where assessments are based on limited observations. In this paper, we have applied a coupled hydrodynamic‐biogeochemical model resolving N2O dynamics to estimate N2O emissions within the northwest European continental shelf. Based on 10‐year average distributions (2006–2015), dominant seasonal patterns of N2O air‐sea exchange were identified. Within the southwest region of the shelf and deep parts of the North Sea, emissions are highest during winter. Peak emissions during late autumn are typical for the northwest part of the shelf and central North Sea, while in the western English Channel, Irish Sea and western North Sea peak outflux shifts toward early autumn. Within these regions, most N2O production occurs below the seasonal pycnocline, and duration and intensity of stratification defines the timing and rate of its subsequent release to the atmosphere. In contrast, within the southeast North Sea and most of the coastal areas, lack of stratification allows the excess N2O to outgas as soon as it is produced, driven by ammonium availability, resulting in peak emissions in summer. We estimate that N2O emissions from the northwest European shelf contribute 0.02224 Tg N to the atmosphere annually, that is, between 3.3–6.8% of total emissions from European shelves and estuaries

A substantial fraction of phytoplankton-derived DON is resistant to degradation by a metabolically versatile, widely distributed marine bacterium

The capacity of bacteria for degrading dissolved organic nitrogen (DON) and remineralising ammonium is of importance for marine ecosystems, as nitrogen availability frequently limits productivity. Here, we assess the capacity of a widely distributed and metabolically versatile marine bacterium to degrade phytoplankton-derived dissolved organic carbon (DOC) and nitrogen. To achieve this, we lysed exponentially growing diatoms and used the derived dissolved organic matter (DOM) to support an axenic culture of Alteromonas sp.. Bacterial biomass (as particulate carbon and nitrogen) was monitored for 70 days while growth dynamics (cell count), DOM (DOC, DON) and dissolved nutrient concentrations were monitored for up to 208 days. Bacterial biomass increased rapidly within the first 7 days prior to a period of growth/death cycles potentially linked to rapid nutrient recycling. We found that ≈75% of the initial DOC and ≈35% of the initial DON were consumed by bacteria within 40 and 4 days respectively, leaving a significant fraction of DOM resilient to degradation by this bacterial species. The different rates and extents to which DOC and DON were accessed resulted in changes in DOM stoichiometry and the iterative relationship between DOM quality and bacterial growth over time influenced bacterial cell C:N molar ratio. C:N values increased to 10 during the growth phase before decreasing to values of ≈5, indicating a change from relative N-limitation/C-sufficiency to relative C-limitation/N-sufficiency. Consequently, despite its reported metabolic versatility, we demonstrate that Alteromonas sp. was unable to access all phytoplankton derived DOM and that a bacterial community is likely to be required. By making the relatively simple assumption that an experimentally derived fraction of DOM remains resilient to bacterial degradation, these experimental results were corroborated by numerical simulations using a previously published model describing the interaction between DOM and bacteria in marine systems, thus supporting our hypothesis

Substantial energy input to the mesopelagic ecosystem from the seasonal mixed-layer pump

The ocean region known as the mesopelagic zone, which is at depths of about 100–1,000 m, harbours one of the largest ecosystems and fish stocks on the planet. Life in this region is believed to rely on particulate organic carbon supplied by the biological carbon pump. Yet this supply appears insufficient to meet mesopelagic metabolic demands. An additional organic carbon source to the mesopelagic zone could be provided by the seasonal entrainment of surface waters in deeper layers, a process known as the mixed-layer pump. Little is known about the magnitude and spatial distribution of this process globally or its potential to transport carbon to the mesopelagic zone. Here we combine mixed-layer depth data from Argo floats with satellite estimates of particulate organic carbon concentrations to show that the mixed-layer pump supplies an important seasonal flux of organic carbon to the mesopelagic zone. We estimate that this process is responsible for a global flux of 0.1–0.5 Pg C yr−1. In high-latitude regions where the mixed layer is usually deep, this flux amounts on average to 23% of the carbon supplied by fast sinking particles, but it can be greater than 100%. We conclude that the seasonal mixed-layer pump is an important source of organic carbon for the mesopelagic zone

Modelling the Stoichiometric Regulation of C-Rich Toxins in Marine Dinoflagellates

Toxin production in marine microalgae was previously shown to be tightly coupled with cellular stoichiometry. The highest values of cellular toxin are in fact mainly associated with a high carbon to nutrient cellular ratio. In particular, the cellular accumulation of C-rich toxins (i.e., with C:N > 6.6) can be stimulated by both N and P deficiency. Dinoflagellates are the main producers of C-rich toxins and may represent a serious threat for human health and the marine ecosystem. As such, the development of a numerical model able to predict how toxin production is stimulated by nutrient supply/deficiency is of primary utility for both scientific and management purposes. In this work we have developed a mechanistic model describing the stoichiometric regulation of C-rich toxins in marine dinoflagellates. To this purpose, a new formulation describing toxin production and fate was embedded in the European Regional Seas Ecosystem Model (ERSEM), here simplified to describe a monospecific batch culture. Toxin production was assumed to be composed by two distinct additive terms; the first is a constant fraction of algal production and is assumed to take place at any physiological conditions. The second term is assumed to be dependent on algal biomass and to be stimulated by internal nutrient deficiency. By using these assumptions, the model reproduced the concentrations and temporal evolution of toxins observed in cultures of Ostreopsis cf. ovata, a benthic/epiphytic dinoflagellate producing C-rich toxins named ovatoxins. The analysis of simulations and their comparison with experimental data provided a conceptual model linking toxin production and nutritional status in this species. The model was also qualitatively validated by using independent literature data, and the results indicate that our formulation can be also used to simulate toxin dynamics in other dinoflagellates. Our model represents an important step towards the simulation and prediction of marine algal toxicity

Ecoregions in the Mediterranean Sea Through the Reanalysis of Phytoplankton Functional Types and Carbon Fluxes

In this work we produced a long‐term reanalysis of the phytoplankton community structure in the Mediterranean Sea and used it to define ecoregions. These were based on the spatial variability of the phytoplankton type fractions and their influence on selected carbon fluxes. A regional ocean color product of four phytoplankton functional types (PFTs; diatoms, dinoflagellates, nanophytoplankton, and picophytoplankton) was assimilated into a coupled physical‐biogeochemical model of the Mediterranean Sea (Proudman Oceanographic Laboratory Coastal Ocean Modelling System‐European Regional Seas Ecosystem Model, POLCOMS–ERSEM) by using a 100‐member ensemble Kalman filter, in a reanalysis simulation for years 1998–2014. The reanalysis outperformed the reference simulation in representing the assimilated ocean color PFT fractions to total chlorophyll, although the skill for the ocean color PFT concentrations was not improved significantly. The reanalysis did not impact noticeably the reference simulation of not assimilated in situ observations, with the exception of a slight bias reduction for the situ PFT concentrations, and a deterioration of the phosphate simulation. We found that the Mediterranean Sea can be subdivided in three PFT‐based ecoregions, derived from the spatial variability of the PFT fraction dominance or relevance. Picophytoplankton dominates the largest part of open ocean waters; microphytoplankton dominates in a few, highly productive coastal spots near large‐river mouths; nanophytoplankton is relevant in intermediate‐productive coastal and Atlantic‐influenced waters. The trophic and carbon sedimentation efficiencies are highest in the microphytoplankton ecoregion and lowest in the picophytoplankton and nanophytoplankton ecoregions. The reanalysis and regionalization offer new perspectives on the variability of the structure and functioning of the phytoplankton community and related biogeochemical fluxes, with foreseeable applications in Blue Growth of the Mediterranean Sea

Assimilation of remotely-sensed optical properties to improve marine biogeochemistry modelling

In this paper we evaluate whether the assimilation of remotely-sensed optical data into a marine ecosystem model improves the simulation of biogeochemistry in a shelf sea. A localized Ensemble Kalman filter was used to assimilate weekly diffuse light attenuation coefficient data, Kd(443) from SeaWiFs, into an ecosystem model of the western English Channel. The spatial distributions of (unassimilated) surface chlorophyll from satellite, and a multivariate time series of eighteen biogeochemical and optical variables measured in situ at one long-term monitoring site were used to evaluate the system performance for the year 2006. Assimilation reduced the root mean square error and improved the correlation with the assimilated Kd(443) observations, for both the analysis and, to a lesser extent, the forecast estimates, when compared to the reference model simulation. Improvements in the simulation of (unassimilated) ocean colour chlorophyll were less evident, and in some parts of the Channel the simulation of this data deteriorated. The estimation errors for the (unassimilated) in situ data were reduced for most variables with some exceptions, e.g. dissolved nitrogen. Importantly, the assimilation adjusted the balance of ecosystem processes by shifting the simulated food web towards the microbial loop, thus improving the estimation of some properties, e.g. total particulate carbon. Assimilation of Kd(443) outperformed a comparative chlorophyll assimilation experiment, in both the estimation of ocean colour data and in the simulation of independent in situ data. These results are related to relatively low error in Kd(443) data, and because it is a bulk optical property of marine ecosystems. Assimilation of remotely-sensed optical properties is a promising approach to improve the simulation of biogeochemical and optical variables that are relevant for ecosystem functioning and climate change studies

Modelling the Effects of Traits and Abiotic Factors on Viral Lysis in Phytoplankton

A mechanistic system dynamics description is developed of the interactions between a single lytic-virus – phytoplankton-host couple. The model has state variables for virus, uninfected and infected host biomass, and describes virus and host allometry and physiology. The model, analogous to experimental laboratory virus-host systems but more amenable to hypothesis testing, enables us to explore the relative importance of some of the poorly understood factors suspected to impact plankton virus-host dynamics. Model behaviour is explored with respect to abiotic factors (light, mixed layer depth, nutrient and suspended particle loading), host traits (size, growth rate, motility) and virus traits (size, latent period and burst size including linkage to compromised host physiology, and decay rates). Simulations show that the optimal performance of a virus (i.e., optimal trait characterisation) is a function of many factors relating to the virus, its host, and the environment. In general, smaller viruses and smaller motile hosts give rise to more productive infection outcomes that result in rapid demise of the host and high post-infection virus abundance. However, the timing of the development of the interaction (relative abundance of virus to host at the start of rapid host population growth), overlain on the growth rate and physiological status of the host, was seen to be critical. Thus, for any one configuration of the model, the inoculum level of the virus (multiplicity of infection- MOI) displayed an optimum time-point between the infection developing too quickly, limiting biomass accumulation, or too late so that nutrient or light limitation compromised host physiology and hence the burst size. Importantly, the success of an infection depended also upon the suspended particle load which, if high enough, adsorbs so many viruses that the infection does not develop. We conclude that adding viruses to plankton ecosystem models in a realistic fashion is a complicated process due to the way that the individual and coupled virus-host processes interact with the environment