Articles | Volume 17, issue 13
05 Jul 2020
Research article | 05 Jul 2020
Quantifying spatiotemporal variability in zooplankton dynamics in the Gulf of Mexico with a physical–biogeochemical model
Taylor A. Shropshire et al.
No articles found.
Michael R. Stukel, Moira Décima, and Michael R. Landry
Biogeosciences, 19, 3595–3624,Short summary
The biological carbon pump (BCP) transports carbon into the deep ocean, leading to long-term marine carbon sequestration. It is driven by many physical, chemical, and ecological processes. We developed a model of the BCP constrained using data from 11 cruises in 4 different ocean regions. Our results show that sinking particles and vertical mixing are more important than transport mediated by vertically migrating zooplankton. They also highlight the uncertainty in current estimates of the BCP.
Eric P. Chassignet, Stephen G. Yeager, Baylor Fox-Kemper, Alexandra Bozec, Frederic Castruccio, Gokhan Danabasoglu, Christopher Horvat, Who M. Kim, Nikolay Koldunov, Yiwen Li, Pengfei Lin, Hailong Liu, Dmitry V. Sein, Dmitry Sidorenko, Qiang Wang, and Xiaobiao Xu
Geosci. Model Dev., 13, 4595–4637,Short summary
This paper presents global comparisons of fundamental global climate variables from a suite of four pairs of matched low- and high-resolution ocean and sea ice simulations to assess the robustness of climate-relevant improvements in ocean simulations associated with moving from coarse (∼1°) to eddy-resolving (∼0.1°) horizontal resolutions. Despite significant improvements, greatly enhanced horizontal resolution does not deliver unambiguous bias reduction in all regions for all models.
Hiroyuki Tsujino, L. Shogo Urakawa, Stephen M. Griffies, Gokhan Danabasoglu, Alistair J. Adcroft, Arthur E. Amaral, Thomas Arsouze, Mats Bentsen, Raffaele Bernardello, Claus W. Böning, Alexandra Bozec, Eric P. Chassignet, Sergey Danilov, Raphael Dussin, Eleftheria Exarchou, Pier Giuseppe Fogli, Baylor Fox-Kemper, Chuncheng Guo, Mehmet Ilicak, Doroteaciro Iovino, Who M. Kim, Nikolay Koldunov, Vladimir Lapin, Yiwen Li, Pengfei Lin, Keith Lindsay, Hailong Liu, Matthew C. Long, Yoshiki Komuro, Simon J. Marsland, Simona Masina, Aleksi Nummelin, Jan Klaus Rieck, Yohan Ruprich-Robert, Markus Scheinert, Valentina Sicardi, Dmitry Sidorenko, Tatsuo Suzuki, Hiroaki Tatebe, Qiang Wang, Stephen G. Yeager, and Zipeng Yu
Geosci. Model Dev., 13, 3643–3708,Short summary
The OMIP-2 framework for global ocean–sea-ice model simulations is assessed by comparing multi-model means from 11 CMIP6-class global ocean–sea-ice models calculated separately for the OMIP-1 and OMIP-2 simulations. Many features are very similar between OMIP-1 and OMIP-2 simulations, and yet key improvements in transitioning from OMIP-1 to OMIP-2 are also identified. Thus, the present assessment justifies that future ocean–sea-ice model development and analysis studies use the OMIP-2 framework.
H. Jing, E. Rocke, L. Kong, X. Xia, H. Liu, and M. R. Landry
Manuscript not accepted for further reviewShort summary
Photosynthetic Dinoflagellates predominated in the surface, while potential parasitic Dinoflagellates and Ciliates dominated in the OMZ and deeper water in Costa Rica Dome. Total and active protists in the anoxic core were distinct from those in others depths. Reduced community diversity and presence of parasitic/symbiotic trophic lifestyles in the suboxic/anoxic OMZ suggests that oxygen deficiency could cause a change of protist community and the associated microbial food web as well.
P. G. Strutton, V. J. Coles, R. R. Hood, R. J. Matear, M. J. McPhaden, and H. E. Phillips
Biogeosciences, 12, 2367–2382,Short summary
In 2010, a first-of-its-kind deployment of biological sensors on a mooring in the central Indian Ocean revealed interesting variability in chlorophyll (a proxy for ocean productivity) at timescales of about 2 weeks. Using the mooring data with satellite observations and a biogeochemical model, it was determined that local wind mixing and entrainment, rather than mixed Rossby gravity waves, were likely responsible for much of the observed variability.
M. R. Stukel, V. J. Coles, M. T. Brooks, and R. R. Hood
Biogeosciences, 11, 3259–3278,
J. Peloquin, C. Swan, N. Gruber, M. Vogt, H. Claustre, J. Ras, J. Uitz, R. Barlow, M. Behrenfeld, R. Bidigare, H. Dierssen, G. Ditullio, E. Fernandez, C. Gallienne, S. Gibb, R. Goericke, L. Harding, E. Head, P. Holligan, S. Hooker, D. Karl, M. Landry, R. Letelier, C. A. Llewellyn, M. Lomas, M. Lucas, A. Mannino, J.-C. Marty, B. G. Mitchell, F. Muller-Karger, N. Nelson, C. O'Brien, B. Prezelin, D. Repeta, W. O. Jr. Smith, D. Smythe-Wright, R. Stumpf, A. Subramaniam, K. Suzuki, C. Trees, M. Vernet, N. Wasmund, and S. Wright
Earth Syst. Sci. Data, 5, 109–123,
P. Wang, A. B. Burd, M. A. Moran, R. R. Hood, V. J. Coles, and P. L. Yager
Revised manuscript not accepted
Related subject area
Biogeochemistry: Modelling, AquaticQuantifying biological carbon pump pathways with a data-constrained mechanistic model ensemble approachHydrodynamic and biochemical impacts on the development of hypoxia in the Louisiana–Texas shelf – Part 2: statistical modeling and hypoxia predictionModelling the effects of benthic fauna on carbon, nitrogen and phosphorus dynamics in the Baltic SeaImproved prediction of dimethyl sulfide (DMS) distributions in the northeast subarctic Pacific using machine-learning algorithmsNutrient transport and transformation in macrotidal estuaries of the French Atlantic coast: a modeling approach using the Carbon-Generic Estuarine ModelAssessing the spatial and temporal variability of MeHg biogeochemistry and bioaccumulation in the Mediterranean Sea with a coupled 3D modelA modelling study of temporal and spatial pCO2 variability on the biologically active and temperature-dominated Scotian ShelfModeling the marine chromium cycle: new constraints on global-scale processesNew insights into large-scale trends of apparent organic matter reactivity in marine sediments and patterns of benthic carbon transformationEvaluation of ocean dimethylsulfide concentration and emission in CMIP6 modelsZooplankton mortality effects on the plankton community of the northern Humboldt Current System: sensitivity of a regional biogeochemical modelMulti-compartment kinetic–allometric (MCKA) model of radionuclide bioaccumulation in marine fishImpact of bottom trawling on sediment biogeochemistry: a modelling approachCyanobacteria blooms in the Baltic Sea: a review of models and factsArctic Ocean acidification over the 21st century co-driven by anthropogenic carbon increases and freshening in the CMIP6 model ensembleModeling silicate–nitrate–ammonium co-limitation of algal growth and the importance of bacterial remineralization based on an experimental Arctic coastal spring bloom culture studyRole of jellyfish in the plankton ecosystem revealed using a global ocean biogeochemical modelExtreme event waves in marine ecosystems: an application to Mediterranean Sea surface chlorophyllUse of optical absorption indices to assess seasonal variability of dissolved organic matter in Amazon floodplain lakesThe role of sediment-induced light attenuation on primary production during Hurricane Gustav (2008)One size fits all? Calibrating an ocean biogeochemistry model for different circulationsAssessing the temporal scale of deep-sea mining impacts on sediment biogeochemistrySeasonal patterns of surface inorganic carbon system variables in the Gulf of Mexico inferred from a regional high-resolution ocean biogeochemical modelOxygen dynamics and evaluation of the single-station diel oxygen model across contrasting geologiesOceanic CO2 outgassing and biological production hotspots induced by pre-industrial river loads of nutrients and carbon in a global modeling approachGlobal trends in marine nitrate N isotopes from observations and a neural network-based climatologyMerging bio-optical data from Biogeochemical-Argo floats and models in marine biogeochemistryModel constraints on the anthropogenic carbon budget of the Arctic OceanModeling oceanic nitrate and nitrite concentrations and isotopes using a 3-D inverse N cycle modelBiogeochemical response of the Mediterranean Sea to the transient SRES-A2 climate change scenarioModelling the biogeochemical effects of heterotrophic and autotrophic N2 fixation in the Gulf of Aqaba (Israel), Red SeaA perturbed biogeochemistry model ensemble evaluated against in situ and satellite observationsDiazotrophy as the main driver of the oligotrophy gradient in the western tropical South Pacific Ocean: results from a one-dimensional biogeochemical–physical coupled modelCauses of simulated long-term changes in phytoplankton biomass in the Baltic proper: a wavelet analysisModelling N2 fixation related to Trichodesmium sp.: driving processes and impacts on primary production in the tropical Pacific OceanLong-term response of oceanic carbon uptake to global warming via physical and biological pumpsSeasonal patterns in phytoplankton biomass across the northern and deep Gulf of Mexico: a numerical model studySea-surface dimethylsulfide (DMS) concentration from satellite data at global and regional scalesA new look at the multi-G model for organic carbon degradation in surface marine sediments for coupled benthic–pelagic simulations of the global oceanGroundwater data improve modelling of headwater stream CO2 outgassing with a stable DIC isotope approachThe influence of the ocean circulation state on ocean carbon storage and CO2 drawdown potential in an Earth system modelModelling potential production of macroalgae farms in UK and Dutch coastal watersAssimilating bio-optical glider data during a phytoplankton bloom in the southern Ross SeaPrimary production sensitivity to phytoplankton light attenuation parameter increases with transient forcingOn the long-range offshore transport of organic carbon from the Canary Upwelling System to the open North AtlanticImproving the inverse modeling of a trace isotope: how precisely can radium-228 fluxes toward the ocean and submarine groundwater discharge be estimated?Implications of sea-ice biogeochemistry for oceanic production and emissions of dimethyl sulfide in the ArcticA numerical analysis of biogeochemical controls with physical modulation on hypoxia during summer in the Pearl River estuaryPotential sources of variability in mesocosm experiments on the response of phytoplankton to ocean acidificationA data–model synthesis to explain variability in calcification observed during a CO2 perturbation mesocosm experiment
Michael R. Stukel, Moira Décima, and Michael R. Landry
Biogeosciences, 19, 3595–3624,Short summary
The biological carbon pump (BCP) transports carbon into the deep ocean, leading to long-term marine carbon sequestration. It is driven by many physical, chemical, and ecological processes. We developed a model of the BCP constrained using data from 11 cruises in 4 different ocean regions. Our results show that sinking particles and vertical mixing are more important than transport mediated by vertically migrating zooplankton. They also highlight the uncertainty in current estimates of the BCP.
Yanda Ou, Bin Li, and Z. George Xue
Biogeosciences, 19, 3575–3593,Short summary
Over the past decades, the Louisiana–Texas shelf has been suffering recurring hypoxia (dissolved oxygen < 2 mg L−1). We developed a novel prediction model using state-of-the-art statistical techniques based on physical and biogeochemical data provided by a numerical model. The model can capture both the magnitude and onset of the annual hypoxia events. This study also demonstrates that it is possible to use a global model forecast to predict regional ocean water quality.
Eva Ehrnsten, Oleg Pavlovitch Savchuk, and Bo Gustav Gustafsson
Biogeosciences, 19, 3337–3367,Short summary
We studied the effects of benthic fauna, animals living on or in the seafloor, on the biogeochemical cycles of carbon, nitrogen and phosphorus using a model of the Baltic Sea ecosystem. By eating and excreting, the animals transform a large part of organic matter sinking to the seafloor into inorganic forms, which fuel plankton blooms. Simultaneously, when they move around (bioturbate), phosphorus is bound in the sediments. This reduces nitrogen-fixing plankton blooms and oxygen depletion.
Brandon J. McNabb and Philippe D. Tortell
Biogeosciences, 19, 1705–1721,Short summary
The trace gas dimethyl sulfide (DMS) plays an important role in the ocean sulfur cycle and can also influence Earth’s climate. Our study used two statistical methods to predict surface ocean concentrations and rates of sea–air exchange of DMS in the northeast subarctic Pacific. Our results show improved predictive power over previous approaches and suggest that nutrient availability, light-dependent processes, and physical mixing may be important controls on DMS in this region.
Xi Wei, Josette Garnier, Vincent Thieu, Paul Passy, Romain Le Gendre, Gilles Billen, Maia Akopian, and Goulven Gildas Laruelle
Biogeosciences, 19, 931–955,Short summary
Estuaries are key reactive ecosystems along the land–ocean aquatic continuum and are often strongly impacted by anthropogenic activities. We calculated nutrient in and out fluxes by using a 1-D transient model for seven estuaries along the French Atlantic coast. Among these, large estuaries with high residence times showed higher retention rates than medium and small ones. All reveal coastal eutrophication due to the excess of diffused nitrogen from intensive agricultural river basins.
Ginevra Rosati, Donata Canu, Paolo Lazzari, and Cosimo Solidoro
Revised manuscript accepted for BGShort summary
Methylmercury (MeHg) is accumulated in marine food webs, posing concerns for human exposure through seafood consumption. We develop a numerical model to integrate the main physical, chemical, and biological processes affecting the Hg cycle. We explore the spatial-temporal changes of MeHg distribution and bioaccumulation in the Mediterranean Sea highlighting important biological processes, as well as physical processes such as winter mixing, which is declining in some areas due to climate change.
Krysten Rutherford, Katja Fennel, Dariia Atamanchuk, Douglas Wallace, and Helmuth Thomas
Biogeosciences, 18, 6271–6286,Short summary
Using a regional model of the northwestern North Atlantic shelves in combination with a surface water time series and repeat transect observations, we investigate surface CO2 variability on the Scotian Shelf. The study highlights a strong seasonal cycle in shelf-wide pCO2 and spatial variability throughout the summer months driven by physical events. The simulated net flux of CO2 on the Scotian Shelf is out of the ocean, deviating from the global air–sea CO2 flux trend in continental shelves.
Frerk Pöppelmeier, David J. Janssen, Samuel L. Jaccard, and Thomas F. Stocker
Biogeosciences, 18, 5447–5463,Short summary
Chromium (Cr) is a redox-sensitive element that holds promise as a tracer of ocean oxygenation and biological activity. We here implemented the oxidation states Cr(III) and Cr(VI) in the Bern3D model to investigate the processes that shape the global Cr distribution. We find a Cr ocean residence time of 5–8 kyr and that the benthic source dominates the tracer budget. Further, regional model–data mismatches suggest strong Cr removal in oxygen minimum zones and a spatially variable benthic source.
Felipe S. Freitas, Philip A. Pika, Sabine Kasten, Bo B. Jørgensen, Jens Rassmann, Christophe Rabouille, Shaun Thomas, Henrik Sass, Richard D. Pancost, and Sandra Arndt
Biogeosciences, 18, 4651–4679,Short summary
It remains challenging to fully understand what controls carbon burial in marine sediments globally. Thus, we use a model–data approach to identify patterns of organic matter reactivity at the seafloor across distinct environmental conditions. Our findings support the notion that organic matter reactivity is a dynamic ecosystem property and strongly influences biogeochemical cycling and exchange. Our results are essential to improve predictions of future changes in carbon cycling and climate.
Josué Bock, Martine Michou, Pierre Nabat, Manabu Abe, Jane P. Mulcahy, Dirk J. L. Olivié, Jörg Schwinger, Parvadha Suntharalingam, Jerry Tjiputra, Marco van Hulten, Michio Watanabe, Andrew Yool, and Roland Séférian
Biogeosciences, 18, 3823–3860,Short summary
In this study we analyse surface ocean dimethylsulfide (DMS) concentration and flux to the atmosphere from four CMIP6 Earth system models over the historical and ssp585 simulations. Our analysis of contemporary (1980–2009) climatologies shows that models better reproduce observations in mid to high latitudes. The models disagree on the sign of the trend of the global DMS flux from 1980 onwards. The models agree on a positive trend of DMS over polar latitudes following sea-ice retreat dynamics.
Mariana Hill Cruz, Iris Kriest, Yonss Saranga José, Rainer Kiko, Helena Hauss, and Andreas Oschlies
Biogeosciences, 18, 2891–2916,Short summary
In this study we use a regional biogeochemical model of the eastern tropical South Pacific Ocean to implicitly simulate the effect that fluctuations in populations of small pelagic fish, such as anchovy and sardine, may have on the biogeochemistry of the northern Humboldt Current System. To do so, we vary the zooplankton mortality in the model, under the assumption that these fishes eat zooplankton. We also evaluate the model for the first time against mesozooplankton observations.
Roman Bezhenar, Kyeong Ok Kim, Vladimir Maderich, Govert de With, and Kyung Tae Jung
Biogeosciences, 18, 2591–2607,Short summary
A new approach to predicting the accumulation of radionuclides in fish was developed by taking into account heterogeneity of distribution of contamination in the organism and dependence of metabolic process rates on the fish mass. Predicted concentrations of radionuclides in fish agreed well with the laboratory and field measurements. The model with the defined generic parameters could be used in marine environments without local calibration, which is important for emergency decision support.
Emil De Borger, Justin Tiano, Ulrike Braeckman, Adriaan D. Rijnsdorp, and Karline Soetaert
Biogeosciences, 18, 2539–2557,Short summary
Bottom trawling alters benthic mineralization: the recycling of organic material (OM) to free nutrients. To better understand how this occurs, trawling events were added to a model of seafloor OM recycling. Results show that bottom trawling reduces OM and free nutrients in sediments through direct removal thereof and of fauna which transport OM to deeper sediment layers protected from fishing. Our results support temporospatial trawl restrictions to allow key sediment functions to recover.
Britta Munkes, Ulrike Löptien, and Heiner Dietze
Biogeosciences, 18, 2347–2378,Short summary
Cyanobacteria blooms can strongly aggravate eutrophication problems of water bodies. Their controls are, however, not comprehensively understood, which impedes effective management and protection plans. Here we review the current understanding of cyanobacteria blooms. Juxtaposition of respective field and laboratory studies with state-of-the-art mathematical models reveals substantial uncertainty associated with nutrient demands, grazing, and death of cyanobacteria.
Jens Terhaar, Olivier Torres, Timothée Bourgeois, and Lester Kwiatkowski
Biogeosciences, 18, 2221–2240,Short summary
The uptake of carbon, emitted as a result of human activities, results in ocean acidification. We analyse 21st-century projections of acidification in the Arctic Ocean, a region of particular vulnerability, using the latest generation of Earth system models. In this new generation of models there is a large decrease in the uncertainty associated with projections of Arctic Ocean acidification, with freshening playing a greater role in driving acidification than previously simulated.
Tobias R. Vonnahme, Martial Leroy, Silke Thoms, Dick van Oevelen, H. Rodger Harvey, Svein Kristiansen, Rolf Gradinger, Ulrike Dietrich, and Christoph Völker
Biogeosciences, 18, 1719–1747,Short summary
Diatoms are crucial for Arctic coastal spring blooms, and their growth is controlled by nutrients and light. At the end of the bloom, inorganic nitrogen or silicon can be limiting, but nitrogen can be regenerated by bacteria, extending the algal growth phase. Modeling these multi-nutrient dynamics and the role of bacteria is challenging yet crucial for accurate modeling. We recreated spring bloom dynamics in a cultivation experiment and developed a representative dynamic model.
Rebecca M. Wright, Corinne Le Quéré, Erik Buitenhuis, Sophie Pitois, and Mark J. Gibbons
Biogeosciences, 18, 1291–1320,Short summary
Jellyfish have been included in a global ocean biogeochemical model for the first time. The global mean jellyfish biomass in the model is within the observational range. Jellyfish are found to play an important role in the plankton ecosystem, influencing community structure, spatiotemporal dynamics and biomass. The model raises questions about the sensitivity of the zooplankton community to jellyfish mortality and the interactions between macrozooplankton and jellyfish.
Valeria Di Biagio, Gianpiero Cossarini, Stefano Salon, and Cosimo Solidoro
Biogeosciences, 17, 5967–5988,Short summary
Events that influence the functioning of the Earth’s ecosystems are of interest in relation to a changing climate. We propose a method to identify and characterise
wavesof extreme events affecting marine ecosystems for multi-week periods over wide areas. Our method can be applied to suitable ecosystem variables and has been used to describe different kinds of extreme event waves of phytoplankton chlorophyll in the Mediterranean Sea, by analysing the output from a high-resolution model.
Maria Paula da Silva, Lino A. Sander de Carvalho, Evlyn Novo, Daniel S. F. Jorge, and Claudio C. F. Barbosa
Biogeosciences, 17, 5355–5364,Short summary
In this study, we analyze the seasonal changes in the dissolved organic matter (DOM) quality (based on its optical properties) in four Amazon floodplain lakes. DOM plays a fundamental role in surface water chemistry, controlling metal bioavailability and mobility, and nutrient cycling. The model proposed in our paper highlights the potential to study DOM quality at a wider spatial scale, which may help to better understand the persistence and fate of DOM in the ecosystem.
Zhengchen Zang, Z. George Xue, Kehui Xu, Samuel J. Bentley, Qin Chen, Eurico J. D'Sa, Le Zhang, and Yanda Ou
Biogeosciences, 17, 5043–5055,
Iris Kriest, Paul Kähler, Wolfgang Koeve, Karin Kvale, Volkmar Sauerland, and Andreas Oschlies
Biogeosciences, 17, 3057–3082,Short summary
Constants of global biogeochemical ocean models are often tuned
by handto match observations of nutrients or oxygen. We investigate the effect of this tuning by optimising six constants of a global biogeochemical model, simulated in five different offline circulations. Optimal values for three constants adjust to distinct features of the circulation applied and can afterwards be swapped among the circulations, without losing too much of the model's fit to observed quantities.
Laura Haffert, Matthias Haeckel, Henko de Stigter, and Felix Janssen
Biogeosciences, 17, 2767–2789,Short summary
Deep-sea mining for polymetallic nodules is expected to have severe environmental impacts. Through prognostic modelling, this study aims to provide a holistic assessment of the biogeochemical recovery after a disturbance event. It was found that the recovery strongly depends on the impact type; e.g. complete removal of the surface sediment reduces seafloor nutrient fluxes over centuries.
Fabian A. Gomez, Rik Wanninkhof, Leticia Barbero, Sang-Ki Lee, and Frank J. Hernandez Jr.
Biogeosciences, 17, 1685–1700,Short summary
We use a numerical model to infer annual changes of surface carbon chemistry in the Gulf of Mexico (GoM). The main seasonality drivers of partial pressure of carbon dioxide and aragonite saturation state from the model are temperature and river runoff. The GoM basin is a carbon sink in winter–spring and carbon source in summer–fall, but uptake prevails near the Mississippi Delta year-round due to high biological production. Our model results show good correspondence with observational studies.
Simon J. Parker
Biogeosciences, 17, 305–315,Short summary
Dissolved oxygen (DO) models typically assume constant ecosystem respiration over the course of a single day. Using a data-driven approach, this research examines this assumption in four streams across two (hydro-)geological types (Chalk and Greensand). Despite hydrogeological equivalence in terms of baseflow index for each hydrogeological pairing, model suitability differed within, rather than across, geology types. This corresponded with associated differences in timings of DO minima.
Fabrice Lacroix, Tatiana Ilyina, and Jens Hartmann
Biogeosciences, 17, 55–88,Short summary
Contributions of rivers to the oceanic cycling of carbon have been poorly represented in global models until now. Here, we assess the long–term implications of preindustrial riverine loads in the ocean in a novel framework which estimates the loads through a hierarchy of weathering and land–ocean export models. We investigate their impacts for the oceanic biological production and air–sea carbon flux. Finally, we assess the potential incorporation of the framework in an Earth system model.
Patrick A. Rafter, Aaron Bagnell, Dario Marconi, and Timothy DeVries
Biogeosciences, 16, 2617–2633,Short summary
The N isotopic composition of nitrate (
nitrate δ15N) is a useful tracer of ocean N cycling and many other ocean processes. Here, we use a global compilation of marine nitrate δ15N as an input, training, and validating dataset for an artificial neural network (a.k.a.,
machine learning) and examine basin-scale trends in marine nitrate δ15N from the surface to the seafloor.
Elena Terzić, Paolo Lazzari, Emanuele Organelli, Cosimo Solidoro, Stefano Salon, Fabrizio D'Ortenzio, and Pascal Conan
Biogeosciences, 16, 2527–2542,Short summary
Measuring ecosystem properties in the ocean is a hard business. Recent availability of data from Biogeochemical-Argo floats can help make this task easier. Numerical models can integrate these new data in a coherent picture and can be used to investigate the functioning of ecosystem processes. Our new approach merges experimental information and model capabilities to quantitatively demonstrate the importance of light and water vertical mixing for algae dynamics in the Mediterranean Sea.
Jens Terhaar, James C. Orr, Marion Gehlen, Christian Ethé, and Laurent Bopp
Biogeosciences, 16, 2343–2367,Short summary
A budget of anthropogenic carbon in the Arctic Ocean, the main driver of open-ocean acidification, was constructed for the first time using a high-resolution ocean model. The budget reveals that anthropogenic carbon enters the Arctic Ocean mainly by lateral transport; the air–sea flux plays a minor role. Coarser-resolution versions of the same model, typical of earth system models, store less anthropogenic carbon in the Arctic Ocean and thus underestimate ocean acidification in the Arctic Ocean.
Taylor S. Martin, François Primeau, and Karen L. Casciotti
Biogeosciences, 16, 347–367,Short summary
Nitrite is a key intermediate in many nitrogen (N) cycling processes in the ocean, particularly in areas with low oxygen that are hotspots for N loss. We have created a 3-D global N cycle model with nitrite as a tracer. Stable isotopes of N are also included in the model and we are able to model the isotope fractionation associated with each N cycling process. Our model accurately represents N concentrations and isotope distributions in the ocean.
Camille Richon, Jean-Claude Dutay, Laurent Bopp, Briac Le Vu, James C. Orr, Samuel Somot, and François Dulac
Biogeosciences, 16, 135–165,Short summary
We evaluate the effects of climate change and biogeochemical forcing evolution on the nutrient and plankton cycles of the Mediterranean Sea for the first time. We use a high-resolution coupled physical and biogeochemical model and perform 120-year transient simulations. The results indicate that changes in external nutrient fluxes and climate change may have synergistic or antagonistic effects on nutrient concentrations, depending on the region and the scenario.
Angela M. Kuhn, Katja Fennel, and Ilana Berman-Frank
Biogeosciences, 15, 7379–7401,Short summary
Recent studies demonstrate that marine N2 fixation can be carried out without light. However, direct measurements of N2 fixation in dark environments are relatively scarce. This study uses a model that represents biogeochemical cycles at a deep-ocean location in the Gulf of Aqaba (Red Sea). Different model versions are used to test assumptions about N2 fixers. Relaxing light limitation for marine N2 fixers improved the similarity between model results and observations of deep nitrate and oxygen.
Prima Anugerahanti, Shovonlal Roy, and Keith Haines
Biogeosciences, 15, 6685–6711,Short summary
Minor changes in the biogeochemical model equations lead to major dynamical changes. We assessed this structural sensitivity for the MEDUSA biogeochemical model on chlorophyll and nitrogen concentrations at five oceanographic stations over 10 years, using 1-D ensembles generated by combining different process equations. The ensemble performed better than the default model in most of the stations, suggesting that our approach is useful for generating a probabilistic biogeochemical ensemble model.
Audrey Gimenez, Melika Baklouti, Thibaut Wagener, and Thierry Moutin
Biogeosciences, 15, 6573–6589,Short summary
During the OUTPACE cruise conducted in the oligotrophic to ultra-oligotrophic region of the western tropical South Pacific, two contrasted regions were sampled in terms of N2 fixation rates, primary production rates and nutrient availability. The aim of this work was to investigate the role of N2 fixation in the differences observed between the two contrasted areas by comparing two simulations only differing by the presence or not of N2 fixers using a 1-D biogeochemical–physical coupled model.
Jenny Hieronymus, Kari Eilola, Magnus Hieronymus, H. E. Markus Meier, Sofia Saraiva, and Bengt Karlson
Biogeosciences, 15, 5113–5129,Short summary
This paper investigates how phytoplankton concentrations in the Baltic Sea co-vary with nutrient concentrations and other key variables on inter-annual timescales in a model integration over the years 1850–2008. The study area is not only affected by climate change; it has also been subjected to greatly increased nutrient loads due to extensive use of agricultural fertilizers. The results indicate the largest inter-annual coherence of phytoplankton with the limiting nutrient.
Cyril Dutheil, Olivier Aumont, Thomas Gorguès, Anne Lorrain, Sophie Bonnet, Martine Rodier, Cécile Dupouy, Takuhei Shiozaki, and Christophe Menkes
Biogeosciences, 15, 4333–4352,Short summary
N2 fixation is recognized as one of the major sources of nitrogen in the ocean. Thus, N2 fixation sustains a significant part of the primary production (PP) by supplying the most common limiting nutrient for phytoplankton growth. From numerical simulations, the local maximums of Trichodesmium biomass in the Pacific are found around islands, explained by the iron fluxes from island sediments. We assessed that 15 % of the PP may be due to Trichodesmium in the low-nutrient, low-chlorophyll areas.
Akitomo Yamamoto, Ayako Abe-Ouchi, and Yasuhiro Yamanaka
Biogeosciences, 15, 4163–4180,Short summary
Millennial-scale changes in oceanic CO2 uptake due to global warming are simulated by a GCM and offline biogeochemical model. Sensitivity studies show that decreases in oceanic CO2 uptake are mainly caused by a weaker biological pump and seawater warming. Enhanced CO2 uptake due to weaker equatorial upwelling cancels out reduced CO2 uptake due to weaker AMOC and AABW formation. Thus, circulation change plays only a small direct role in reduction of CO2 uptake due to global warming.
Fabian A. Gomez, Sang-Ki Lee, Yanyun Liu, Frank J. Hernandez Jr., Frank E. Muller-Karger, and John T. Lamkin
Biogeosciences, 15, 3561–3576,Short summary
Seasonal patterns in nanophytoplankton and diatom biomass in the Gulf of Mexico were examined with an ocean–biogeochemical model. We found silica limitation of model diatom growth in the deep GoM and Mississippi delta. Zooplankton grazing and both transport and vertical mixing of biomass substantially influence the model phytoplankton biomass seasonality. We stress the need for integrated analyses of biologically and physically driven biomass fluxes to describe phytoplankton seasonal changes.
Martí Galí, Maurice Levasseur, Emmanuel Devred, Rafel Simó, and Marcel Babin
Biogeosciences, 15, 3497–3519,Short summary
We developed a new algorithm to estimate the sea-surface concentration of dimethylsulfide (DMS) using satellite data. DMS is a gas produced by marine plankton that, once emitted to the atmosphere, plays a key climatic role by seeding cloud formation. We used the algorithm to produce global DMS maps and also regional DMS time series. The latter suggest that DMS can vary largely from one year to another, which should be taken into account in atmospheric studies.
Konstantin Stolpovsky, Andrew W. Dale, and Klaus Wallmann
Biogeosciences, 15, 3391–3407,Short summary
The paper describes a new way to parameterize G-type models in marine sediments using data about reactivity of organic carbon sinking to the seafloor.
Anne Marx, Marcus Conrad, Vadym Aizinger, Alexander Prechtel, Robert van Geldern, and Johannes A. C. Barth
Biogeosciences, 15, 3093–3106,Short summary
CO2 outgassing from small streams causes one of the main uncertainties in global carbon budgets. These are caused by variable flow conditions, changing stream surface areas, and groundwater seeps. Here we used groundwater data to improve a novel stable carbon isotope modelling approach. We found that CO2 outgassing contributed more than three-fourths of annual stream inorganic carbon loss in a small, silicate catchment. We underline the potential of this approach for global applications.
Malin Ödalen, Jonas Nycander, Kevin I. C. Oliver, Laurent Brodeau, and Andy Ridgwell
Biogeosciences, 15, 1367–1393,Short summary
We conclude that different initial states for an ocean model result in different capacities for ocean carbon storage due to differences in the ocean circulation state and the origin of the carbon in the initial ocean carbon reservoir. This could explain why it is difficult to achieve comparable responses of the ocean carbon system in model inter-comparison studies in which the initial states vary between models. We show that this effect of the initial state is quantifiable.
Johan van der Molen, Piet Ruardij, Karen Mooney, Philip Kerrison, Nessa E. O'Connor, Emma Gorman, Klaas Timmermans, Serena Wright, Maeve Kelly, Adam D. Hughes, and Elisa Capuzzo
Biogeosciences, 15, 1123–1147,Short summary
Macroalgae farming may provide biofuel. Modelled macroalgae production is given for four sites in UK and Dutch waters. Macroalgae growth depended on nutrient concentrations and light levels. Macroalgae carbohydrate content, important for biofuel use, was lower for high nutrient concentrations. The hypothetical large-scale farm off the UK north Norfolk coast gave high, stable yields of macroalgae from year to year with substantial carbohydrate content.
Daniel E. Kaufman, Marjorie A. M. Friedrichs, John C. P. Hemmings, and Walker O. Smith Jr.
Biogeosciences, 15, 73–90,Short summary
Computer simulations of the highly variable phytoplankton in the Ross Sea demonstrated how incorporating data from different sources (satellite, ship, or glider) results in different system interpretations. For example, simulations assimilating satellite-based data produced lower carbon export estimates. Combining observations with models in this remote, harsh, and biologically variable environment should include consideration of the potential impacts of data frequency, duration, and coverage.
Karin F. Kvale and Katrin J. Meissner
Biogeosciences, 14, 4767–4780,Short summary
Climate models containing ocean biogeochemistry contain a lot of poorly constrained parameters, which makes model tuning difficult. For more than 20 years modellers have generally assumed phytoplankton light attenuation parameter value choice has an insignificant affect on model ocean primary production; thus, it is often overlooked for tuning. We show that an empirical range of light attenuation parameter values can affect primary production, with increasing sensitivity under climate change.
Elisa Lovecchio, Nicolas Gruber, Matthias Münnich, and Zouhair Lachkar
Biogeosciences, 14, 3337–3369,Short summary
We find that a big portion of the phytoplankton, zooplankton, and detrital organic matter produced near the northern African coast is laterally transported towards the open North Atlantic. This offshore flux sustains a relevant part of the biological activity in the open sea and reaches as far as the middle of the North Atlantic. Our results, obtained with a state-of-the-art model, highlight the fundamental role of the narrow but productive coastal ocean in sustaining global marine life.
Guillaume Le Gland, Laurent Mémery, Olivier Aumont, and Laure Resplandy
Biogeosciences, 14, 3171–3189,Short summary
In this study, we computed the fluxes of radium-228 from the continental shelf to the open ocean by fitting a numerical model to observations. After determining appropriate model parameters (cost function and number of source regions), we found a lower and more precise global flux than previous estimates: 8.01–8.49×1023 atoms yr−1. This result can be used to assess nutrient and trace element fluxes to the open ocean, but we cannot identify specific pathways like submarine groundwater discharge.
Hakase Hayashida, Nadja Steiner, Adam Monahan, Virginie Galindo, Martine Lizotte, and Maurice Levasseur
Biogeosciences, 14, 3129–3155,Short summary
In remote regions, cloud conditions may be strongly influenced by oceanic source of dimethylsulfide (DMS) produced by plankton and bacteria. In the Arctic, sea ice provides an additional source of these aerosols. The results of this study highlight the importance of taking into account both the sea-ice sulfur cycle and ecosystem in the flux estimates of oceanic DMS near the ice margins and identify key uncertainties in processes and rates that would be better constrained by new observations.
Bin Wang, Jiatang Hu, Shiyu Li, and Dehong Liu
Biogeosciences, 14, 2979–2999,Short summary
We proposed a novel method named the physical modulation method to quantify the contributions of boundary conditions, the source and sink processes occurring in local and adjacent waters to DO conditions. A mass balance analysis of DO based on the physical modulation method indicated that the DO conditions were mainly controlled by source and sink processes, among which the sediment oxygen demand and re-aeration were two main processes controlling the spatial extent and the duration of hypoxia.
Maria Moreno de Castro, Markus Schartau, and Kai Wirtz
Biogeosciences, 14, 1883–1901,Short summary
Observations from different mesocosms exposed to the same treatment level typically show variability that hinders the detection of potential treatments effects. To unearth relevant sources of variability, we developed and performed a data-based model analysis that simulates uncertainty propagation. With this method we investigate the divergence in the outcomes due to the amplification of differences in experimentally unresolved ecological factors within replicates of the same treatment level.
Shubham Krishna and Markus Schartau
Biogeosciences, 14, 1857–1882,Short summary
This study combines experimental data with results from numerical modelling. Data of an ocean acidification mesocosm experiment are used to constrain parameter values of a plankton model. Three different intensities of calcification are resolved with ensembles of optimised model results. Observed variability in data can be well explained by these ensemble model solutions. The simulated ocean acidification effect on calcification is small compared to the spread of the ensemble model solutions.
Anderson, T. R.: Plankton functional type modelling: Running before we can walk?, J. Plankton Res., 27, 1073–1081, https://doi.org/10.1093/plankt/fbi076, 2005.
Anderson, T. R., Gentleman, W. C., and Sinha, B.: Influence of grazing formulations on the emergent properties of a complex ecosystem model in a global ocean general circulation model, Prog. Oceanogr., 87, 201–213, https://doi.org/10.1016/j.pocean.2010.06.003, 2010.
Anderson, T. R., Gentleman, W. C., and Yool, A.: EMPOWER-1.0: an Efficient Model of Planktonic ecOsystems WrittEn in R, Geosci. Model Dev., 8, 2231–2262, https://doi.org/10.5194/gmd-8-2231-2015, 2015.
Arreguin-Sanchez, F., Zetina-Rejón, M., Manickchand-Heileman, S., Ramírez-Rodríguez, M., and Vidal, L.: Simulated response to harvesting strategies in an exploited ecosystem in the southwestern Gulf of Mexico, Ecol. Model., 172, 421–432, https://doi.org/10.1016/j.ecolmodel.2003.09.016, 2004.
Bakun, A.: Ocean eddies, predator pits and bluefin tuna: Implications of an inferred “low risk-limited payoff” reproductive scheme of a (former) archetypical top predator, Fish Fish., 14, 424–438, https://doi.org/10.1111/faf.12002, 2013.
Bakun, A. and Broad, K.: Environmental “loopholes” and fish population dynamics: Comparative pattern recognition with focus on El Niño effects in the Pacific, Fish. Oceanogr., 12, 458–473, https://doi.org/10.1046/j.1365-2419.2003.00258.x, 2003.
Biggs, D. C. and Ressler, P. H.: Distribution and abundance of phytoplankton, zooplankton, icthyoplankton, and micronekton in the deepwater Gulf of Mexico, Gulf Mex. Sci., 19, 7–29, https://doi.org/10.18785/goms.1901.02, 2001.
Buitenhuis, E., Le Quéré, C., Aumont, O., Beaugrand, G., Bunker, A., Hirst, A., Ikeda, T., O'Brien, T., Piontkovski, S., and Straile, D.: Biogeochemical fluxes through mesozooplankton, Global Biogeochem. Cy., 20, GB2003, https://doi.org/10.1029/2005GB002511, 2006.
Calbet, A.: Mesozooplankton grazing effect on primary production: A global comparative analysis in marine ecosystems, Limnol. Oceanogr., 46, 1824–1830, https://doi.org/10.4319/lo.2001.46.7.1824, 2001.
Calbet, A. and Landry, M. R.: Phytoplankton growth, microzooplankton grazing, and carbon cycling in marine systems, Limnol. Oceanogr., 49, 51–57, https://doi.org/10.4319/lo.2004.49.1.0051, 2004.
Caron, D. A. and Hutchins, D. A.: The effects of changing climate on microzooplankton grazing and community structure: Drivers, predictions and knowledge gaps, J. Plankton Res., 35, 235–252, https://doi.org/10.1093/plankt/fbs091, 2013.
Chaigneau, A., Le Texier, M., Eldin, G., Grados, C., and Pizarro, O.: Vertical structure of mesoscale eddies in the eastern South Pacific Ocean: A composite analysis from altimetry and Argo profiling floats, J. Geophys. Res.-Oceans, 116, 1–16, https://doi.org/10.1029/2011JC007134, 2011.
Chassignet, E. P., Smith, L. T., Halliwell, G. R., and Bleck, R.: North Atlantic simulations with the Hybrid Coordinate Ocean Model (HYCOM): Impact of the vertical coordinate choice, reference pressure, and thermobaricity, J. Phys. Oceanogr., 33, 2504–2526, https://doi.org/10.1175/1520-0485(2003)033<2504:NASWTH>2.0.CO;2, 2003.
Chikaraishi, Y., Ogawa, N. O., Kashiyama, Y., Takano, Y., Suga, H., Tomitani, A., Miyashita, H., Kitazato, H. and Ohkouchi, N.: Determination of aquatic food-web structure based on compound-specific nitrogen isotopic composition of amino acids, Limnol. Oceanogr.-Methods, 7, 740–750, https://doi.org/10.4319/lom.2009.7.740, 2009.
Cleary, A. C., Durbin, E. G., Rynearson, T. A., and Bailey, J.: Feeding by Pseudocalanus copepods in the Bering Sea: Trophic linkages and a potential mechanism of niche partitioning, Deep-Sea Res. Pt. II, 134, 181–189, https://doi.org/10.1016/j.dsr2.2015.04.001, 2016.
Coles, V. J., Stukel, M. R., Brooks, M. T., Burd, A., Crump, B. C., Moran, M. A., Paul, J. H., Satinsky, B. M., Yager, P. L., Zielinski, B. L., and Hood, R. R.: Ocean biogeochemistry modeled with emergent trait-based genomics, Science, 358, 1149–1154, https://doi.org/10.1126/science.aan5712, 2017.
Cornic, M. and Rooker, J. R.: Influence of oceanographic conditions on the distribution and abundance of blackfin tuna (Thunnus atlanticus) larvae in the Gulf of Mexico, Fish. Res., 201, 1–10, https://doi.org/10.1016/j.fishres.2017.12.015, 2018.
Damien, P., Pasqueron de Fommervault, O., Sheinbaum, J., Jouanno, J., Camacho-Ibar, V. F., and Duteil, O.: Partitioning of the Open Waters of the Gulf of Mexico Based on the Seasonal and Interannual Variability of Chlorophyll Concentration, J. Geophys. Res.-Oceans, 123, 2592–2614, https://doi.org/10.1002/2017JC013456, 2018.
Décima, M., Landry, M. R., and Rykaczewski, R. R.: Broad scale patterns in mesozooplankton biomass and grazing in the eastern equatorial Pacific, Deep-Sea Res. Pt. II, 58, 387–399, https://doi.org/10.1016/j.dsr2.2010.08.006, 2011.
Décima, M., Landry, M. R., Stukel, M. R., Lopez-Lopez, L., and Krause, J. W.: Mesozooplankton biomass and grazing in the Costa Rica Dome: Amplifying variability through the plankton food web, J. Plankton Res., 38, 317–330, https://doi.org/10.1093/plankt/fbv091, 2016.
Décima, M., Landry, M. R., Bradley, C. J., and Fogel, M. L.: Alanine δ15N trophic fractionation in heterotrophic protists, Limnol. Oceanogr., 62, 2308–2322, https://doi.org/10.1002/lno.10567, 2017.
Domingues, R., Goni, G., Bringas, F., Muhling, B., Lindo-Atichati, D., and Walter, J.: Variability of preferred environmental conditions for Atlantic bluefin tuna (Thunnus thynnus) larvae in the Gulf of Mexico during 1993–2011, Fish. Oceanogr., 25, 320–336, https://doi.org/10.1111/fog.12152, 2016.
Doney, S. C., Lima, I., Moore, J. K., Lindsay, K., Behrenfeld, M. J., Westberry, T. K., Mahowald, N., Glover, D. M., and Takahashi, T.: Skill metrics for confronting global upper ocean ecosystem-biogeochemistry models against field and remote sensing data, J. Marine Syst., 76, 95–112, https://doi.org/10.1016/j.jmarsys.2008.05.015, 2009.
Everett, J. D., Baird, M. E., Buchanan, P., Bulman, C., Davies, C., Downie, R., Griffiths, C., Heneghan, R., Kloser, R. J., Laiolo, L., Lara-Lopez, A., Lozano-Montes, H., Matear, R. J., McEnnulty, F., Robson, B., Rochester, W., Skerratt, J., Smith, J. A., Strzelecki, J., Suthers, I. M., Swadling, K. M., van Ruth, P., and Richardson, A. J.: Modeling what we sample and sampling what we model: Challenges for zooplankton model assessment, Front. Mar. Sci., 4, 1–19, https://doi.org/10.3389/fmars.2017.00077, 2017.
Fasham, M. J. R., Ducklow, H. W., and McKelvie, S. M.: A nitrogen-based model of plankton dynamics in the ocean mixed layer, J. Mar. Res., 48, 591–639, 1990.
Fennel, K., Wilkin, J., Levin, J., Moisan, J., O'Reilly, J., and Haidvogel, D.: Nitrogen cycling in the Middle Atlantic Bight: Results from a three-dimensional model and implications for the North Atlantic nitrogen budget, Global Biogeochem. Cy., 20, 1–14, https://doi.org/10.1029/2005GB002456, 2006.
Fennel, K., Hetland, R., Feng, Y., and DiMarco, S.: A coupled physical-biological model of the Northern Gulf of Mexico shelf: model description, validation and analysis of phytoplankton variability, Biogeosciences, 8, 1881–1899, https://doi.org/10.5194/bg-8-1881-2011, 2011.
Follows, M. J., Dutkiewicz, S., Grant, S., and Chisholm, S. W.: Emergent biogeography of microbial communities in a model ocean., Science, 315, 1843–1846, https://doi.org/10.1126/science.1138544, 2007.
Forristall, G. Z., Schaudt, K. J., and Cooper, C. K.: Evolution and kinematics of a loop current eddy in the Gulf of Mexico during 1985, J. Geophys. Res., 97, 2173, https://doi.org/10.1029/91jc02905, 1992.
Franks, P. J. S.: NPZ models of plankton dynamics: Their construction, coupling to physics, and application, J. Oceanogr., 58, 379–387, https://doi.org/10.1023/A:1015874028196, 2002.
Franks, P. J. S.: Planktonic ecosystem models: Perplexing parameterizations and a failure to fail, J. Plankton Res., 31, 1299–1306, https://doi.org/10.1093/plankt/fbp069, 2009.
Geers, T. M., Pikitch, E. K., and Frisk, M. G.: An original model of the northern Gulf of Mexico using Ecopath with Ecosim and its implications for the effects of fishing on ecosystem structure and maturity, Deep-Sea Res. Pt. II, 129, 319–331, https://doi.org/10.1016/j.dsr2.2014.01.009, 2016.
Geider, R. J., Maclntyre, H. L., and Kana, T. M.: A dynamic regulatory model of phytoplanktonic acclimation to light, nutrients, and temperature, Limnol. Oceangr., 43, 679–694, https://doi.org/10.4319/lo.1998.43.4.0679, 1998.
Gentleman, W., Leising, A., Frost, B., Strom, S., and Murray, J.: Functional responses for zooplankton feeding on multiple resources: a review of assumptions and biological dynamics, Deep-Sea Res. Pt. II, 50, 2847–2875, https://doi.org/10.1016/j.dsr2.2003.07.001, 2003a.
Gentleman, W., Leising, A., Frost, B., Strom, S., and Murray, J.: Functional responses for zooplankton feeding on multiple resources: A review of assumptions and biological dynamics, Deep-Sea Res. Pt. II, 50, 2847–2875, https://doi.org/10.1016/j.dsr2.2003.07.001, 2003b.
Gentleman, W. C. and Neuheimer, A. B.: Functional responses and ecosystem dynamics: How clearance rates explain the influence of satiation, food-limitation and acclimation, J. Plankton Res., 30, 1215–1231, https://doi.org/10.1093/plankt/fbn078, 2008.
Gomez, F. A., Lee, S.-K., Liu, Y., Hernandez Jr., F. J., Muller-Karger, F. E., and Lamkin, J. T.: Seasonal patterns in phytoplankton biomass across the northern and deep Gulf of Mexico: a numerical model study, Biogeosciences, 15, 3561–3576, https://doi.org/10.5194/bg-15-3561-2018, 2018.
Gregg, W. W., Ginoux, P., Schopf, P. S., and Casey, N. W.: Phytoplankton and iron: Validation of a global three-dimensional ocean biogeochemical model, Deep-Sea Res. Pt. II, 50, 3143–3169, https://doi.org/10.1016/j.dsr2.2003.07.013, 2003.
Gutiérrez-Rodríguez, A., Décima, M., Popp, B. N., and Landry, M. R.: Isotopic invisibility of protozoan trophic steps in marine food webs, Limnol. Oceanogr., 59, 1590–1598, https://doi.org/10.4319/lo.2014.59.5.1590, 2014.
Hill, H., Hill, C., Follows, M., and Dutkiewicz, S.: Is there a computational advantage to offline tracer modelling at very high resolution?, Geophis. Res. Abstr., 6, 2005.
Holl, C. M., Waite, A. M., Pesant, S., Thompson, P. A., and Montoya, J. P.: Unicellular diazotrophy as a source of nitrogen to Leeuwin Current coastal eddies, Deep-Sea Res. Pt. II, 54, 1045–1054, https://doi.org/10.1016/j.dsr2.2007.02.002, 2007.
Hu, C., Lee, Z., and Franz, B.: Chlorophyll a algorithms for oligotrophic oceans: A novel approach based on three-band reflectance difference, J. Geophys. Res.-Oceans, 117, 1–25, https://doi.org/10.1029/2011JC007395, 2012.
Ikeda, T., Kanno, Y., Ozaki, K., and Shinada, A.: Metabolic rates of epipelagic marine copepods as a function of body mass and temperature, Mar. Biol., 139, 587–596, https://doi.org/10.1007/s002270100608, 2001.
Kishi, M. J., Kashiwai, M., Ware, D. M., Megrey, B. a., Eslinger, D. L., Werner, F. E., Noguchi-Aita, M., Azumaya, T., Fujii, M., Hashimoto, S., Huang, D., Iizumi, H., Ishida, Y., Kang, S., Kantakov, G. a., Kim, H. C., Komatsu, K., Navrotsky, V. V., Smith, S. L., Tadokoro, K., Tsuda, A., Yamamura, O., Yamanaka, Y., Yokouchi, K., Yoshie, N., Zhang, J., Zuenko, Y. I., and Zvalinsky, V. I.: NEMURO-a lower trophic level model for the North Pacific marine ecosystem, Ecol. Model., 202, 12–25, https://doi.org/10.1016/j.ecolmodel.2006.08.021, 2007.
Kitchens, L. L. and Rooker, J. R.: Habitat associations of dolphinfish larvae in the Gulf of Mexico, Fish. Oceanogr., 23, 460–471, https://doi.org/10.1111/fog.12081, 2014.
Kjellerup, S., Dünweber, M., Swalethorp, R., Nielsen, T. G., Møller, E. F., Markager, S., and Hansen, B. W.: Effects of a future warmer ocean on the coexisting copepods Calanus finmarchicus and C. glacialis in Disko Bay, western Greenland, Mar. Ecol.-Prog. Ser., 447, 87–108, https://doi.org/10.3354/meps09551, 2012.
Landry, M., Haas, L., and Fagerness, V.: Dynamics of microbial plankton communities: experiments in Kaneohe Bay, Hawaii, Mar. Ecol.-Prog. Ser., 16, 127–133, https://doi.org/10.3354/meps016127, 1984.
Landry, M. R. and Calbet, A.: Microzooplankton production in the oceans, ICES J. Mar. Sci., 61, 501–507, https://doi.org/10.1016/j.icesjms.2004.03.011, 2004.
Landry, M. R. and Hassett, R. P.: Estimating the grazing impact of marine micro-zooplankton, Mar. Biol., 67, 283–288, https://doi.org/10.1007/BF00397668, 1982.
Landry, M. R., Decima, M., Simmons, M. P., Hannides, C. C. S., and Daniels, E.: Mesozooplankton biomass and grazing responses to Cyclone Opal, a subtropical mesoscale eddy, Deep-Sea Res. Pt. II, 55, 1378–1388, https://doi.org/10.1016/j.dsr2.2008.01.005, 2008.
Landry, M. R., Ohman, M. D., Goericke, R., Stukel, M. R., and Tsyrklevich, K.: Lagrangian studies of phytoplankton growth and grazing relationships in a coastal upwelling ecosystem off Southern California, Prog. Oceanogr., 83, 208–216, https://doi.org/10.1016/j.pocean.2009.07.026, 2009.
Landry, M. R., Selph, K. E., Decima, M., Gutierrez-Rodríguez, A., Stukel, M. R., Taylor, A. G., and Pasulka, A. L.: Phytoplankton production and grazing balances in the Costa Rica Dome, J. Plankton Res., 38, 366–379, https://doi.org/10.1093/plankt/fbv089, 2016.
Landry, M. R., Beckley, L. E., and Muhling, B. A.: Climate sensitivities and uncertainties in food-web pathways supporting larval bluefin tuna in subtropical oligotrophic oceans, ICES J. Mar. Sci., 76, 359–369, https://doi.org/10.1093/icesjms/fsy184, 2019.
Large, W. G., McWilliams, J. C., and Doney, S. C.: Oceanic vertical mixing: A review and a model with a nonlocal boundary layer parameterization, Rev. Geophys., 32, 363–403, https://doi.org/10.1029/94RG01872, 1994.
Laxenaire, R., Speich, S., Blanke, B., Chaigneau, A., Pegliasco, C., and Stegner, A.: Anticyclonic Eddies Connecting the Western Boundaries of Indian and Atlantic Oceans, J. Geophys. Res.-Oceans, 123, 7651–7677, https://doi.org/10.1029/2018JC014270, 2018.
Laxenaire, R., Speich, S., and Stegner, A.: Evolution of the Thermohaline Structure of One Agulhas Ring Reconstructed from Satellite Altimetry and Argo Floats, J. Geophys. Res.-Oceans, 124, 8969–9003, https://doi.org/10.1029/2018JC014426, 2019.
Li, Q. P., Franks, P. J. S., Landry, M. R., Goericke, R., and Taylor, A. G.: Modeling phytoplankton growth rates and chlorophyll to carbon ratios in California coastal and pelagic ecosystems, J. Geophys. Res.-Biogeo., 115, 1–12, https://doi.org/10.1029/2009JG001111, 2010.
Lindo-Atichati, D., Bringas, F., Goni, G., Muhling, B., Muller-Karger, F. E., and Habtes, S.: Varying mesoscale structures influence larval fish distribution in the northern Gulf of Mexico, Mar. Ecol.-Prog. Ser., 463, 245–257, https://doi.org/10.3354/meps09860, 2012.
The Relationship between Variations in the Gulf of Mexico Loop Current and Straits of Florida Volume Transport 23, 785–796, https://doi.org/10.1175/1520-0485(1993)023<0785:TRBVIT>2.0.CO;2, 1993.
McKinley, G. A., Follows, M. J., and Marshall, J.: Mechanisms of air-sea CO2 flux variability in the equatorial Pacific and the North Atlantic, Global Biogeochem. Cy., 18, 1–14, https://doi.org/10.1029/2003GB002179, 2004.
Mitra, A., Flynn, K. J., Burkholder, J. M., Berge, T., Calbet, A., Raven, J. A., Granéli, E., Glibert, P. M., Hansen, P. J., Stoecker, D. K., Thingstad, F., Tillmann, U., Våge, S., Wilken, S., and Zubkov, M. V.: The role of mixotrophic protists in the biological carbon pump, Biogeosciences, 11, 995–1005, https://doi.org/10.5194/bg-11-995-2014, 2014.
Moeller, H. V., Laufkötter, C., Sweeney, E. M., and Johnson, M. D.: Light-dependent grazing can drive formation and deepening of deep chlorophyll maxima, Nat. Commun., 10, 1–8, https://doi.org/10.1038/s41467-019-09591-2, 2019.
Morey, S. L., Martin, P. J., O'Brien, J. J., Wallcraft, A. A., and Zavala-Hidalgo, J.: Export pathways for river discharged fresh water in the northern Gulf of Mexico, J. Geophys. Res.-Oceans, 108, 1–1, https://doi.org/10.1029/2002jc001674, 2003a.
Morey, S. L., Schroeder, W. W., O'Brien, J. J., and Zavala-Hidalgo, J.: The annual cycle of riverine influence in the eastern Gulf of Mexico basin, Geophys. Res. Lett., 30, 1867, https://doi.org/10.1029/2003GL017348, 2003b.
Morey, S. L., Zavala-Hidalgo, J., and O'Brien, J. J.: The Seasonal Variability of Continental Shelf Circulation in the Northern and Western Gulf of Mexico from a High-Resolution Numerical Model, in Circulation in the Gulf of Mexico: Observations and Models, GMS, 161, 203–218, 2013.
Moriarty, R. and O'Brien, T. D.: Distribution of mesozooplankton biomass in the global ocean, Earth Syst. Sci. Data, 5, 45–55, https://doi.org/10.5194/essd-5-45-2013, 2013.
Morrow, R. M., Ohman, M. D., Goericke, R., Kelly, T. B., Stephens, B. M., and Stukel, M. R.: CCE V: Primary production, mesozooplankton grazing, and the biological pump in the California Current Ecosystem: Variability and response to El Niño, Deep-Sea Res. Pt. I, 140, 52–62, https://doi.org/10.1016/j.dsr.2018.07.012, 2018.
Muhling, B. A., Lamkin, J. T., Alemany, F., García, A., Farley, J., Ingram, G. W., Berastegui, D. A., Reglero, P., and Carrion, R. L.: Reproduction and larval biology in tunas, and the importance of restricted area spawning grounds, Rev. Fish Biol. Fish., 27, 697–732, https://doi.org/10.1007/s11160-017-9471-4, 2017.
Mulholland, M. R., Bernhardt, P. W., Heil, C. A., Bronk, D. A., and O'Neil, J. M.: Nitrogen fixation and release of fixed nitrogen by Trichodesmium spp. in the Gulf of Mexico, Limnol. Oceanogr., 51, 2484, https://doi.org/10.4319/lo.2006.51.5.2484, 2006.
Murray, A. G. and Parslow, J. S.: The analysis of alternative formulations in a simple model of a coastal ecosystem, Ecol. Model., 119, 149–166, https://doi.org/10.1016/S0304-3800(99)00046-0, 1999.
Oey, L., Ezer, T., and Lee, H.: Loop Current, rings and related circulation in the Gulf of Mexico: A review of numerical models and future challenges, Geophys. Monogr., 161, 31–56, 2005.
Parker, R. A.: Dynamic models for ammonium inhibition of nitrate uptake by phytoplankton, Ecol. Model., 66, 113–120, https://doi.org/10.1016/0304-3800(93)90042-Q, 1993.
Pegliasco, C., Chaigneau, A., and Morrow, R.: Main eddy vertical structures observed in the four major Eastern Boundary Upwelling Systems, J. Geophys. Res.-Oceans, 120, 6008–6033, https://doi.org/10.1002/2015JC010950, 2015.
Platt, T., Gallegos, C. L., and Harrison, W. G.: Photoinhibition of photosynthesis in natural assemblages of marine phytoplankton, J. Mar. Res., 38, 687–701, 1980.
Pörtner, H. O. and Farrell, A. P.: Physiology and Climate Change Hans, Science, 322, 690–692, 2008.
Richardson, A. J.: In hot water: Zooplankton and climate change, ICES J. Mar. Sci., 65, 279–295, https://doi.org/10.1093/icesjms/fsn028, 2008.
Riley, G. A.: Factors controlling phytoplankton populations on Georges Bank, J. Mar. Res., 6, 54–73, 1946.
Rooker, J. R., Simms, J. R., David Wells, R. J., Holt, S. A., Holt, G. J., Graves, J. E., and Furey, N. B.: Distribution and habitat associations of billfish and swordfish larvae across mesoscale features in the gulf of Mexico, PLoS One, 7, e34180, https://doi.org/10.1371/journal.pone.0034180, 2012.
Rooker, J. R., Kitchens, L. L., Dance, M. A., Wells, R. J. D., Falterman, B., and Cornic, M.: Spatial, Temporal, and Habitat-Related Variation in Abundance of Pelagic Fishes in the Gulf of Mexico: Potential Implications of the Deepwater Horizon Oil Spill, PLoS One, 8, e76080, https://doi.org/10.1371/journal.pone.0076080, 2013.
Sailley, S. F., Vogt, M., Doney, S. C., Aita, M. N., Bopp, L., Buitenhuis, E. T., Hashioka, T., Lima, I., Le Quéré, C., and Yamanaka, Y.: Comparing food web structures and dynamics across a suite of global marine ecosystem models, Ecol. Model., 261–262, 43–57, https://doi.org/10.1016/j.ecolmodel.2013.04.006, 2013.
Sailley, S. F., Polimene, L., Mitra, A., Atkinson, A., and Allen, J. I.: Impact of zooplankton food selectivity on plankton dynamics and nutrient cycling, J. Plankton Res., 37, 519–529, https://doi.org/10.1093/plankt/fbv020, 2015.
Selph, K. E., Landry, M. R., Taylor, A. G., Gutierrez-Rodríguez, A., Stukel, M. R., Wokuluk, J., and Pasulka, A.: Phytoplankton production and taxon-specific growth rates in the Costa Rica Dome, J. Plankton Res., 38, 199–215, https://doi.org/10.1093/plankt/fbv063, 2016.
Sherr, E. B. and Sherr, B. F.: Significance of predation by protists in aquatic microbial food webs, Antonie van Leeuwenhoek, Int. J. Gen. Mol. Microbiol., 81, 293–308, https://doi.org/10.1023/A:1020591307260, 2002.
Shropshire, T.: NEMURO-GoM model code along with configuration files to run with MITgcm, GitHub, available at: https://github.com/tashrops/NEMURO-GoM, 2019a.
Shropshire, T.: Temporally averaged three-dimensional fields for all 11 state variables used in NEMURO-GOM along with surface chlorophyll, available at: https://data.gulfresearchinitiative.org, 2019b.
Staniewski, M. A. and Short, S. M.: Methodological review and meta-analysis of dilution assays for estimates of virus- and grazer-mediated phytoplankton mortality, Limnol. Oceanogr.-Methods, 16, 649–668, https://doi.org/10.1002/lom3.10273, 2018.
Steele, J. H. and Henderson, E. W.: The role of predation in plankton models, J. Plankton Res., 14, 157–172, https://doi.org/10.1093/plankt/14.1.157, 1992.
Steinberg, D. K. and Landry, M. R.: Zooplankton and the Ocean Carbon Cycle, Annu. Rev. Mar. Sci., 9, 413–444, https://doi.org/10.1146/annurev-marine-010814-015924, 2017.
Straile, D.: and metazoan efficiencies of protozoan Gross growth on food concentration, and their dependence zooplankton group ratio, and taxonomic, Limnol. Oceanogr., 42, 1375–1385, 1997.
Strickland, J. D. H. and Parsons, T. R.: A practical handbook for seawater analysis. Second Edition, available at: http://www.dfo-mpo.gc.ca/Library/1507.pdf (last access: 29 June 2020), 1972.
Strom, S. L., Benner, R., Ziegler, S., and Dagg, M. J.: Planktonic grazers are a potentially important source of marine dissolved organic carbon, Limnol. Oceanogr., 42, 1364–1374, https://doi.org/10.4319/lo.19220.127.116.114, 1997.
Stukel, M. R., Coles, V. J., Brooks, M. T., and Hood, R. R.: Top-down, bottom-up and physical controls on diatom-diazotroph assemblage growth in the Amazon River plume, Biogeosciences, 11, 3259–3278, https://doi.org/10.5194/bg-11-3259-2014, 2014.
Stukel, M. R., Kahru, M., Benitez-Nelson, C. R., Décima, M., Goericke, R., Landry, M. R., and Ohman, M. D.: Using Lagrangian-based process studies to test satellite algorithms of vertical carbon flux in the eastern North Pacific Ocean, J. Geophys. Res.-Oceans, 120, 7208–7222, https://doi.org/10.1002/2015JC011264, 2015.
Turner, J. T.: Zooplankton fecal pellets, marine snow, phytodetritus and the ocean's biological pump, Prog. Oceanogr., 130, 205–248, https://doi.org/10.1016/j.pocean.2014.08.005, 2015.
Wainwright, T. C., Feinberg, L. R., Hooff, R. C., and Peterson, W. T.: A comparison of two lower trophic models for the California Current System, Ecol. Modell., 202, 120–131, https://doi.org/10.1016/j.ecolmodel.2006.06.019, 2007.
Werner, F. E., Ito, S. I., Megrey, B. A., and Kishi, M. J.: Synthesis of the NEMURO model studies and future directions of marine ecosystem modeling, Ecol. Model., 202, 211–223, https://doi.org/10.1016/j.ecolmodel.2006.08.019, 2007.
Wiebe, P. H.: Functional regression equations for zooplankton displacement volume wet weight, dry weight, and carbon: A correction, Fish. Bull., 86, 833–835, 1988.
Xue, Z., He, R., Fennel, K., Cai, W.-J., Lohrenz, S., and Hopkinson, C.: Modeling ocean circulation and biogeochemical variability in the Gulf of Mexico, Biogeosciences, 10, 7219–7234, https://doi.org/10.5194/bg-10-7219-2013, 2013.
Zooplankton are the smallest animals in the ocean and important food for fish. Despite their importance, zooplankton have been relatively undersampled. To better understand the zooplankton community in the Gulf of Mexico (GoM), we developed a model to simulate their dynamics. We found that heterotrophic protists are important for supporting mesozooplankton, which are the primary prey of larval fish. The model developed in this study has the potential to improve fisheries management in the GoM.
Zooplankton are the smallest animals in the ocean and important food for fish. Despite their...