The Role of External Inputs and Internal Cycling in Shaping the Global Ocean Cobalt Distribution: Insights From the First Cobalt Biogeochemical Model

Abstract. Jellyfish are increasingly recognised as important components of the marine ecosystem, yet their specific role is poorly defined compared to that of other zooplankton groups. This paper presents the first global ocean biogeochemical model that includes an explicit representation of jellyfish, and uses the model to gain insight into the influence of jellyfish on the plankton community. The PlankTOM11 model groups organisms into Plankton Functional Types (PFT). The jellyfish PFT is parameterised here based on our synthesis of observations on jellyfish growth, grazing, respiration and mortality rates as functions of temperature and on jellyfish biomass. The distribution of jellyfish is unique compared to that of other PFTs in the model. The jellyfish global biomass of 0.13 PgC is within the observational range, and comparable to the biomass of other zooplankton and phytoplankton PFTs. The introduction of jellyfish in the model has a large direct influence on the crustacean macrozooplankton PFT, and influences indirectly the rest of the plankton ecosystem through trophic cascades. The zooplankton community in PlankTOM11 is highly sensitive to the jellyfish mortality rate, with jellyfish increasingly dominating the zooplankton community as its mortality diminishes. Overall the results suggest that jellyfish play an important and unique role in regulating marine plankton ecosystems, which has been neglected so far.

Download Full-text

Petrobactin, a siderophore produced by Alteromonas, mediates community iron acquisition in the global ocean

The ISME Journal ◽

10.1038/s41396-021-01065-y ◽

2021 ◽

Author(s):

Lauren E. Manck ◽

Jiwoon Park ◽

Benjamin J. Tully ◽

Alfonso M. Poire ◽

Randelle M. Bundy ◽

...

Keyword(s):

Biosynthetic Pathway ◽

Iron Acquisition ◽

Biogeochemical Cycling ◽

Iron Bioavailability ◽

Siderophore Production ◽

Global Ocean ◽

The North ◽

The North Pacific ◽

Alteromonas Macleodii

AbstractIt is now widely accepted that siderophores play a role in marine iron biogeochemical cycling. However, the mechanisms by which siderophores affect the availability of iron from specific sources and the resulting significance of these processes on iron biogeochemical cycling as a whole have remained largely untested. In this study, we develop a model system for testing the effects of siderophore production on iron bioavailability using the marine copiotroph Alteromonas macleodii ATCC 27126. Through the generation of the knockout cell line ΔasbB::kmr, which lacks siderophore biosynthetic capabilities, we demonstrate that the production of the siderophore petrobactin enables the acquisition of iron from mineral sources and weaker iron-ligand complexes. Notably, the utilization of lithogenic iron, such as that from atmospheric dust, indicates a significant role for siderophores in the incorporation of new iron into marine systems. We have also detected petrobactin, a photoreactive siderophore, directly from seawater in the mid-latitudes of the North Pacific and have identified the biosynthetic pathway for petrobactin in bacterial metagenome-assembled genomes widely distributed across the global ocean. Together, these results improve our mechanistic understanding of the role of siderophore production in iron biogeochemical cycling in the marine environment wherein iron speciation, bioavailability, and residence time can be directly influenced by microbial activities.

Download Full-text

Effects of light and phosphorus on summer DMS dynamics in subtropical waters using a global ocean biogeochemical model

Environmental Chemistry ◽

10.1071/en14265 ◽

2016 ◽

Vol 13 (2) ◽

pp. 379 ◽

Cited By ~ 5

Author(s):

Italo Masotti ◽

Sauveur Belviso ◽

Laurent Bopp ◽

Alessandro Tagliabue ◽

Eva Bucciarelli

Keyword(s):

General Circulation ◽

North Atlantic Ocean ◽

Model Simulation ◽

Global Ocean ◽

Longitudinal Distribution ◽

Biogeochemical Model ◽

Relative Role ◽

Sargasso Sea ◽

Ecological Processes ◽

Climatological Data

Environmental context Models are needed to predict the importance of the changes in marine emissions of dimethylsulfide (DMS) in response to ocean warming, increased stratification and acidification, and to evaluate the potential effects on the Earth’s climate. We use complementary simulations to further our understanding of the marine cycle of DMS in subtropical waters, and show that a lack of phosphorus may exert a more important control on surface DMS concentrations than an excess of light. Abstract The occurrence of a summer DMS paradox in the vast subtropical gyres is a strong matter of debate because approaches using discrete measurements, climatological data and model simulations yielded contradictory results. The major conclusion of the first appraisal of prognostic ocean DMS models was that such models need to give more weight to the direct effect of environmental forcings (e.g. irradiance) on DMS dynamics to decouple them from ecological processes. Here, the relative role of light and phosphorus on summer DMS dynamics in subtropical waters is assessed using the ocean general circulation and biogeochemistry model NEMO-PISCES in which macronutrient concentrations were restored to monthly climatological data values to improve the representation of phosphate concentrations. Results show that the vertical and temporal decoupling between chlorophyll and DMS concentrations observed in the Sargasso Sea during the summer months is captured by the model. Additional sensitivity tests show that the simulated control of phosphorus on surface DMS concentrations in the Sargasso Sea is much more important than that of light. By extending the analysis to the whole North Atlantic Ocean, we show that the longitudinal distribution of DMS during summer is asymmetrical and that a correlation between the solar radiation dose and DMS concentrations only occurs in the Sargasso Sea. The lack of a widespread summer DMS paradox in our model simulation as well as in the comparison of discrete and climatological data could be due to the limited occurrence of phosphorus limitation in the global ocean.

Download Full-text

The Role of Averaging for Improving Sea Surface Salinity Retrieval from the Soil Moisture and Ocean Salinity (SMOS) Satellite and Impact of Auxiliary Data

Journal of Atmospheric and Oceanic Technology ◽

10.1175/jtech1954.1 ◽

2007 ◽

Vol 24 (2) ◽

pp. 255-269 ◽

Cited By ~ 10

Author(s):

Sabine Philipps ◽

Christine Boone ◽

Estelle Obligis

Keyword(s):

Soil Moisture ◽

Sensitivity Study ◽

Sea Surface ◽

Sea Surface Salinity ◽

Global Ocean ◽

Surface Salinity ◽

Auxiliary Data ◽

Additional Information ◽

Ocean Salinity

Abstract Soil Moisture and Ocean Salinity (SMOS) was chosen as the European Space Agency’s second Earth Explorer Opportunity mission. One of the objectives is to retrieve sea surface salinity (SSS) from measured brightness temperatures (TBs) at L band with a precision of 0.2 practical salinity units (psu) with averages taken over 200 km by 200 km areas and 10 days [as suggested in the requirements of the Global Ocean Data Assimilation Experiment (GODAE)]. The retrieval is performed here by an inverse model and additional information of auxiliary SSS, sea surface temperature (SST), and wind speed (W). A sensitivity study is done to observe the influence of the TBs and auxiliary data on the SSS retrieval. The key role of TB and W accuracy on SSS retrieval is verified. Retrieval is then done over the Atlantic for two cases. In case A, auxiliary data are simulated from two model outputs by adding white noise. The more realistic case B uses independent databases for reference and auxiliary ocean parameters. For these cases, the RMS error of retrieved SSS on pixel scale is around 1 psu (1.2 for case B). Averaging over GODAE scales reduces the SSS error by a factor of 12 (4 for case B). The weaker error reduction in case B is most likely due to the correlation of errors in auxiliary data. This study shows that SSS retrieval will be very sensitive to errors on auxiliary data. Specific efforts should be devoted to improving the quality of auxiliary data.

Download Full-text

Marine productivity response to Heinrich events: a model-data comparison

Climate of the Past ◽

10.5194/cp-8-1581-2012 ◽

2012 ◽

Vol 8 (5) ◽

pp. 1581-1598 ◽

Cited By ~ 23

Author(s):

V. Mariotti ◽

L. Bopp ◽

A. Tagliabue ◽

M. Kageyama ◽

D. Swingedouw

Keyword(s):

North Atlantic ◽

General Circulation ◽

Circulation Model ◽

Global Ocean ◽

Biogeochemical Model ◽

Heinrich Events ◽

The North ◽

Heinrich Event ◽

The North Atlantic ◽

Marine Productivity

Abstract. Marine sediments records suggest large changes in marine productivity during glacial periods, with abrupt variations especially during the Heinrich events. Here, we study the response of marine biogeochemistry to such an event by using a biogeochemical model of the global ocean (PISCES) coupled to an ocean-atmosphere general circulation model (IPSL-CM4). We conduct a 400-yr-long transient simulation under glacial climate conditions with a freshwater forcing of 0.1 Sv applied to the North Atlantic to mimic a Heinrich event, alongside a glacial control simulation. To evaluate our numerical results, we have compiled the available marine productivity records covering Heinrich events. We find that simulated primary productivity and organic carbon export decrease globally (by 16% for both) during a Heinrich event, albeit with large regional variations. In our experiments, the North Atlantic displays a significant decrease, whereas the Southern Ocean shows an increase, in agreement with paleo-productivity reconstructions. In the Equatorial Pacific, the model simulates an increase in organic matter export production but decreased biogenic silica export. This antagonistic behaviour results from changes in relative uptake of carbon and silicic acid by diatoms. Reasonable agreement between model and data for the large-scale response to Heinrich events gives confidence in models used to predict future centennial changes in marine production. In addition, our model allows us to investigate the mechanisms behind the observed changes in the response to Heinrich events.

Download Full-text

Different processes shape prokaryotic and picoeukaryotic assemblages in the sunlit ocean microbiome

10.1101/374298 ◽

2018 ◽

Cited By ~ 3

Author(s):

Ramiro Logares ◽

Ina M. Deutschmann ◽

Caterina. R. Giner ◽

Anders K. Krabberød ◽

Thomas S. B. Schmidt ◽

...

Keyword(s):

Ecosystem Function ◽

Sequence Data ◽

Scale Effects ◽

Dispersal Limitation ◽

Global Scale ◽

Global Ocean ◽

Ecosystem Functions ◽

Ecological Processes ◽

Surface Ocean

ABSTRACTThe smallest members of the sunlit-ocean microbiome (prokaryotes and picoeukaryotes) participate in a plethora of ecosystem functions with planetary-scale effects. Understanding the processes determining the spatial turnover of this assemblage can help us better comprehend the links between microbiome species composition and ecosystem function. Ecological theory predicts thatselection,dispersalanddriftare main drivers of species distributions, yet, the relative quantitative importance of these ecological processes in structuring the surface-ocean microbiome is barely known. Here we quantified the role of selection, dispersal and drift in structuring surface-ocean prokaryotic and picoeukaryotic assemblages by using community DNA-sequence data collected during the global Malaspina expedition. We found that dispersal limitation was the dominant process structuring picoeukaryotic communities, while a balanced combination of dispersal limitation, selection and drift shaped prokaryotic counterparts. Subsequently, we determined the agents exerting abiotic selection as well as the spatial patterns emerging from the action of different ecological processes. We found that selection exerted via temperature had a strong influence on the structure of prokaryotic communities, particularly on species co-occurrences, a pattern not observed among communities of picoeukaryotes. Other measured abiotic variables had limited selective effects on microbiome structure. Picoeukaryotes presented a higher differentiation between neighbouring communities and a higher distance-decay when compared to prokaryotes, agreeing with their higher dispersal limitation. Finally, drift seemed to have a limited role in structuring the sunlit-ocean microbiome. The different predominance of ecological processes acting on particular subsets of the ocean microbiome suggests uneven responses to environmental change.SIGNIFICANCE STATEMENTThe global ocean contains one of the largest microbiomes on Earth and changes on its structure can impact the functioning of the biosphere. Yet, we are far from understanding the mechanisms that structure the global ocean microbiome, that is, the relative importance of environmentalselection,dispersaland random events (drift). We evaluated the role of these processes at the global scale, based on data derived from a circumglobal expedition and found that these ecological processes act differently on prokaryotes and picoeukaryotes, two of the main components of the ocean microbiome. Our work represents a significant contribution to understand the assembly of marine microbial communities, providing also insights on the links between ecological mechanisms, microbiome structure and ecosystem function.

Download Full-text

Using new observations and Machine Learning to improve organic sinking processes in the PlankTOM global ocean biogeochemical model

10.5194/egusphere-egu21-11356 ◽

2021 ◽

Author(s):

Anna Denvil-Sommer ◽

Corinne Le Quéré ◽

Erik Buitenhuis ◽

Lionel Guidi ◽

Jean-Olivier Irisson

Keyword(s):

Organic Carbon ◽

Carbon Cycle ◽

Deep Ocean ◽

Ecosystem Dynamics ◽

Global Ocean ◽

Biogeochemical Model ◽

Carbon Export ◽

Mixing Depth ◽

Chl A ◽

Biogeochemical Models

A lot of effort has been put in the representation of surface ecosystem processes in global carbon cycle models, in particular through the grouping of organisms into Plankton Functional Types (PFTs) which have specific influences on the carbon cycle. In contrast, the transfer of ecosystem dynamics into carbon export to the deep ocean has received much less attention, so that changes in the representation of the PFTs do not necessarily translate into changes in sinking of particulate matter. Models constrain the air-sea CO2 flux by drawing down carbon into the ocean interior. This export flux is five times as large as the CO2 emitted to the atmosphere by human activities. When carbon is transported from the surface to intermediate and deep ocean, more CO2 can be absorbed at the surface. Therefore, even small variability in sinking organic carbon fluxes can have a large impact on air-sea CO2 fluxes, and on the amount of CO2 emissions that remain in the atmosphere.In this work we focus on the representation of organic matter sinking in global biogeochemical models, using the PlankTOM model in its latest version representing 12 PFTs. We develop and test a methodology that will enable the systematic use of new observations to constrain sinking processes in the model. The approach is based on a Neural Network (NN) and is applied to the PlankTOM model output to test its ability to reconstruction small and large particulate organic carbon with a limited number of observations. We test the information content of geographical variables (location, depth, time of year), physical conditions (temperature, mixing depth, nutrients), and ecosystem information (CHL a, PFTs). These predictors are used in the NN to test their influence on the model-generation of organic particles and the robustness of the results. We show preliminary results using the NN approach with real plankton and particle size distribution observations from the Underwater Vision Profiler (UVP) and plankton diversity data from Tara Oceans expeditions and discuss limitations.

Download Full-text