Articles | Volume 18, issue 7
https://doi.org/10.5194/bg-18-2347-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/bg-18-2347-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Reviews and syntheses
| 
13 Apr 2021
Reviews and syntheses |
| 13 Apr 2021
| 13 Apr 2021
Cyanobacteria blooms in the Baltic Sea: a review of models and facts
Britta Munkes
CORRESPONDING AUTHOR
GEOMAR, Helmholtz Centre for Ocean Research Kiel, Düsternbrooker Weg 20, 24105 Kiel, Germany
Ulrike Löptien
GEOMAR, Helmholtz Centre for Ocean Research Kiel, Düsternbrooker Weg 20, 24105 Kiel, Germany
Institute of Geosciences, Christian Albrechts University of Kiel, Ludewig-Meyn-Str. 10, 24118 Kiel, Germany
Heiner Dietze
GEOMAR, Helmholtz Centre for Ocean Research Kiel, Düsternbrooker Weg 20, 24105 Kiel, Germany
Institute of Geosciences, Christian Albrechts University of Kiel, Ludewig-Meyn-Str. 10, 24118 Kiel, Germany
Related authors
No articles found.
Henrike Schmidt, Julia Getzlaff, Ulrike Löptien, and Andreas Oschlies
Ocean Sci., 17, 1303–1320, https://doi.org/10.5194/os-17-1303-2021, https://doi.org/10.5194/os-17-1303-2021, 2021
Short summary
Short summary
Oxygen-poor regions in the open ocean restrict marine habitats. Global climate simulations show large uncertainties regarding the prediction of these areas. We analyse the representation of the simulated oxygen minimum zones in the Arabian Sea using 10 climate models. We give an overview of the main deficiencies that cause the model–data misfit in oxygen concentrations. This detailed process analysis shall foster future model improvements regarding the oxygen minimum zone in the Arabian Sea.
This article is included in the Encyclopedia of Geosciences
Sabine Mathesius, Julia Getzlaff, Heiner Dietze, Andreas Oschlies, and Markus Schartau
Earth Syst. Sci. Data, 12, 1775–1787, https://doi.org/10.5194/essd-12-1775-2020, https://doi.org/10.5194/essd-12-1775-2020, 2020
Short summary
Short summary
Controlled manipulation of environmental conditions within large enclosures in the ocean, pelagic mesocosms, has become a standard method to explore responses of marine plankton communities to anthropogenic change. Among the challenges of interpreting mesocosm data is the often uncertain role of vertical mixing. This study introduces a mesocosm mixing model that is able to estimate vertical diffusivities and thus provides a tool for future mesocosm data analyses that account for mixing.
This article is included in the Encyclopedia of Geosciences
Ulrike Löptien and Heiner Dietze
Biogeosciences Discuss., https://doi.org/10.5194/bg-2020-96, https://doi.org/10.5194/bg-2020-96, 2020
Manuscript not accepted for further review
Short summary
Short summary
Nitrogen fixation, conducted by specific microorganisms, makes molecular nitrogen available for marine biota. By this means this process exerts major control on the growth of algae in the ocean. This study compares two contemporary paradigms, anticipating the ecological niche of N-fixing organisms in an Earth System Model. We illustrate respective uncertainties in climate projections and suggest specific observations to advance the reliable representation of nitrogen fixation in numerical models.
This article is included in the Encyclopedia of Geosciences
Heiner Dietze, Ulrike Löptien, and Julia Getzlaff
Geosci. Model Dev., 13, 71–97, https://doi.org/10.5194/gmd-13-71-2020, https://doi.org/10.5194/gmd-13-71-2020, 2020
Short summary
Short summary
We present a new near-global coupled biogeochemical ocean-circulation model configuration of the Southern Ocean. The configuration features both a relatively equilibrated oceanic carbon inventory and an explicit representation of mesoscale eddies. In this paper, we document the model configuration and showcase its potential to tackle research questions such as the Southern Ocean carbon uptake dynamics on decadal timescales.
This article is included in the Encyclopedia of Geosciences
Robinson Hordoir, Lars Axell, Anders Höglund, Christian Dieterich, Filippa Fransner, Matthias Gröger, Ye Liu, Per Pemberton, Semjon Schimanke, Helen Andersson, Patrik Ljungemyr, Petter Nygren, Saeed Falahat, Adam Nord, Anette Jönsson, Iréne Lake, Kristofer Döös, Magnus Hieronymus, Heiner Dietze, Ulrike Löptien, Ivan Kuznetsov, Antti Westerlund, Laura Tuomi, and Jari Haapala
Geosci. Model Dev., 12, 363–386, https://doi.org/10.5194/gmd-12-363-2019, https://doi.org/10.5194/gmd-12-363-2019, 2019
Short summary
Short summary
Nemo-Nordic is a regional ocean model based on a community code (NEMO). It covers the Baltic and the North Sea area and is used as a forecast model by the Swedish Meteorological and Hydrological Institute. It is also used as a research tool by scientists of several countries to study, for example, the effects of climate change on the Baltic and North seas. Using such a model permits us to understand key processes in this coastal ecosystem and how such processes will change in a future climate.
This article is included in the Encyclopedia of Geosciences
Volkmar Sauerland, Ulrike Löptien, Claudine Leonhard, Andreas Oschlies, and Anand Srivastav
Geosci. Model Dev., 11, 1181–1198, https://doi.org/10.5194/gmd-11-1181-2018, https://doi.org/10.5194/gmd-11-1181-2018, 2018
Short summary
Short summary
We present a concept to prove that a parametric model is well calibrated, i.e., that changes of its free parameters cannot lead to a much better model–data misfit anymore. The intention is motivated by the fact that calibrating global biogeochemical ocean models is important for assessment and inter-model comparison but computationally expensive.
This article is included in the Encyclopedia of Geosciences
Per Pemberton, Ulrike Löptien, Robinson Hordoir, Anders Höglund, Semjon Schimanke, Lars Axell, and Jari Haapala
Geosci. Model Dev., 10, 3105–3123, https://doi.org/10.5194/gmd-10-3105-2017, https://doi.org/10.5194/gmd-10-3105-2017, 2017
Short summary
Short summary
The Baltic Sea is seasonally ice covered with intense wintertime ship traffic and a sensitive ecosystem. Understanding the sea-ice pack is important for climate effect studies and forecasting. A NEMO-LIM3.6-based model setup for the North Sea/Baltic Sea is introduced, including a method for ice in the coastal zone. We evaluate different sea-ice parameters and overall find that the model agrees well with the observation though deformed ice is more challenging to capture.
This article is included in the Encyclopedia of Geosciences
Markus Schartau, Philip Wallhead, John Hemmings, Ulrike Löptien, Iris Kriest, Shubham Krishna, Ben A. Ward, Thomas Slawig, and Andreas Oschlies
Biogeosciences, 14, 1647–1701, https://doi.org/10.5194/bg-14-1647-2017, https://doi.org/10.5194/bg-14-1647-2017, 2017
Short summary
Short summary
Plankton models have become an integral part in marine ecosystem and biogeochemical research. These models differ in complexity and in their number of parameters. How values are assigned to parameters is essential. An overview of major methodologies of parameter estimation is provided. Aspects of parameter identification in the literature are diverse. Individual findings could be better synthesized if notation and expertise of the different scientific communities would be reasonably merged.
This article is included in the Encyclopedia of Geosciences
Heiner Dietze, Julia Getzlaff, and Ulrike Löptien
Biogeosciences, 14, 1561–1576, https://doi.org/10.5194/bg-14-1561-2017, https://doi.org/10.5194/bg-14-1561-2017, 2017
Short summary
Short summary
The Southern Ocean is a sink for anthropogenic carbon. Projections of how this sink will evolve in an ever-warming climate are based on coupled ocean-circulation–biogeochemical models. This study compares uncertainties of simulated oceanic carbon uptake associated to physical (eddy) parameterizations with those associated wtih (unconstrained) supply of bioavailable iron supply to the surface ocean.
This article is included in the Encyclopedia of Geosciences
Heiner Dietze and Ulrike Löptien
Ocean Sci., 12, 977–986, https://doi.org/10.5194/os-12-977-2016, https://doi.org/10.5194/os-12-977-2016, 2016
Short summary
Short summary
Winds blowing over the ocean drive ocean currents. The oceanic response to winds is, in turn, influenced by ocean currents. Theoretical considerations suggest that the latter effect is especially pronounced in the Baltic Sea. The study presented here puts theses theoretical considerations in a high-resolution ocean circulation model of the Baltic Sea to the test.
This article is included in the Encyclopedia of Geosciences
U. Löptien and H. Dietze
Ocean Sci., 11, 573–590, https://doi.org/10.5194/os-11-573-2015, https://doi.org/10.5194/os-11-573-2015, 2015
Short summary
Short summary
Marine biogeochemical ocean models are embedded into earth system models - which are, to an increasing degree, applied to project the fate of our warming world. These biogeochemical models generally depend on poorly constrained model parameters. In this study we investigate the the demands on observations for an objective estimation of such parameters. A major result is that even modest noise (10%) inherent to observations can hinder the assignment of reasonable parameters.
This article is included in the Encyclopedia of Geosciences
U. Löptien and L. Axell
The Cryosphere, 8, 2409–2418, https://doi.org/10.5194/tc-8-2409-2014, https://doi.org/10.5194/tc-8-2409-2014, 2014
Short summary
Short summary
The Baltic Sea is a seasonally ice-covered marginal sea in central northern Europe. In wintertime, on-time shipping depends crucially on sea ice forecasts. Among the forecasting tools heavily applied are numerical models, which suffer from a lack of calibration data because relevant ice properties are difficult (and costly) to monitor. We developed an innovative and inexpensive approach, by using ship speed observations obtained by the automatic identification system (AIS) to asses such models.
This article is included in the Encyclopedia of Geosciences
U. Löptien and H. Dietze
Earth Syst. Sci. Data, 6, 367–374, https://doi.org/10.5194/essd-6-367-2014, https://doi.org/10.5194/essd-6-367-2014, 2014
H. Dietze, U. Löptien, and K. Getzlaff
Geosci. Model Dev., 7, 1713–1731, https://doi.org/10.5194/gmd-7-1713-2014, https://doi.org/10.5194/gmd-7-1713-2014, 2014
Related subject area
Biogeochemistry: Modelling, Aquatic
Investigating ecosystem connections in the shelf sea environment using complex networks
Seasonal and interannual variability of the pelagic ecosystem and of the organic carbon budget in the Rhodes Gyre (eastern Mediterranean): influence of winter mixing
Validation of the coupled physical-biogeochemical ocean model NEMO-SCOBI for the North Sea-Baltic Sea system
How much do bacterial growth properties and biodegradable dissolved organic matter control water quality at low flow?
Methane emissions from Arctic landscapes during 2000–2015: an analysis with land and lake biogeochemistry models
Including filter-feeding gelatinous macrozooplankton in a global marine biogeochemical model: model–data comparison and impact on the ocean carbon cycle
Riverine impact on future projections of marine primary production and carbon uptake
Subsurface oxygen maximum in oligotrophic marine ecosystems: mapping the interaction between physical and biogeochemical processes
Quantifying biological carbon pump pathways with a data-constrained mechanistic model ensemble approach
Assessing the spatial and temporal variability of methylmercury biogeochemistry and bioaccumulation in the Mediterranean Sea with a coupled 3D model
Hydrodynamic and biochemical impacts on the development of hypoxia in the Louisiana–Texas shelf – Part 2: statistical modeling and hypoxia prediction
Modelling the effects of benthic fauna on carbon, nitrogen and phosphorus dynamics in the Baltic Sea
Improved prediction of dimethyl sulfide (DMS) distributions in the northeast subarctic Pacific using machine-learning algorithms
Nutrient transport and transformation in macrotidal estuaries of the French Atlantic coast: a modeling approach using the Carbon-Generic Estuarine Model
A modelling study of temporal and spatial pCO2 variability on the biologically active and temperature-dominated Scotian Shelf
Modeling the marine chromium cycle: new constraints on global-scale processes
New insights into large-scale trends of apparent organic matter reactivity in marine sediments and patterns of benthic carbon transformation
Evaluation of ocean dimethylsulfide concentration and emission in CMIP6 models
Zooplankton mortality effects on the plankton community of the northern Humboldt Current System: sensitivity of a regional biogeochemical model
Multi-compartment kinetic–allometric (MCKA) model of radionuclide bioaccumulation in marine fish
Impact of bottom trawling on sediment biogeochemistry: a modelling approach
Arctic Ocean acidification over the 21st century co-driven by anthropogenic carbon increases and freshening in the CMIP6 model ensemble
Modeling silicate–nitrate–ammonium co-limitation of algal growth and the importance of bacterial remineralization based on an experimental Arctic coastal spring bloom culture study
Role of jellyfish in the plankton ecosystem revealed using a global ocean biogeochemical model
Extreme event waves in marine ecosystems: an application to Mediterranean Sea surface chlorophyll
Use of optical absorption indices to assess seasonal variability of dissolved organic matter in Amazon floodplain lakes
The role of sediment-induced light attenuation on primary production during Hurricane Gustav (2008)
Quantifying spatiotemporal variability in zooplankton dynamics in the Gulf of Mexico with a physical–biogeochemical model
One size fits all? Calibrating an ocean biogeochemistry model for different circulations
Assessing the temporal scale of deep-sea mining impacts on sediment biogeochemistry
Seasonal patterns of surface inorganic carbon system variables in the Gulf of Mexico inferred from a regional high-resolution ocean biogeochemical model
Oxygen dynamics and evaluation of the single-station diel oxygen model across contrasting geologies
Oceanic CO2 outgassing and biological production hotspots induced by pre-industrial river loads of nutrients and carbon in a global modeling approach
Global trends in marine nitrate N isotopes from observations and a neural network-based climatology
Merging bio-optical data from Biogeochemical-Argo floats and models in marine biogeochemistry
Model constraints on the anthropogenic carbon budget of the Arctic Ocean
Modeling oceanic nitrate and nitrite concentrations and isotopes using a 3-D inverse N cycle model
Biogeochemical response of the Mediterranean Sea to the transient SRES-A2 climate change scenario
Modelling the biogeochemical effects of heterotrophic and autotrophic N2 fixation in the Gulf of Aqaba (Israel), Red Sea
A perturbed biogeochemistry model ensemble evaluated against in situ and satellite observations
Diazotrophy as the main driver of the oligotrophy gradient in the western tropical South Pacific Ocean: results from a one-dimensional biogeochemical–physical coupled model
Causes of simulated long-term changes in phytoplankton biomass in the Baltic proper: a wavelet analysis
Modelling N2 fixation related to Trichodesmium sp.: driving processes and impacts on primary production in the tropical Pacific Ocean
Long-term response of oceanic carbon uptake to global warming via physical and biological pumps
Seasonal patterns in phytoplankton biomass across the northern and deep Gulf of Mexico: a numerical model study
Sea-surface dimethylsulfide (DMS) concentration from satellite data at global and regional scales
A new look at the multi-G model for organic carbon degradation in surface marine sediments for coupled benthic–pelagic simulations of the global ocean
Groundwater data improve modelling of headwater stream CO2 outgassing with a stable DIC isotope approach
The influence of the ocean circulation state on ocean carbon storage and CO2 drawdown potential in an Earth system model
Modelling potential production of macroalgae farms in UK and Dutch coastal waters
Ieuan Higgs, Jozef Skákala, Ross Bannister, Alberto Carrassi, and Stefano Ciavatta
Biogeosciences, 21, 731–746, https://doi.org/10.5194/bg-21-731-2024, https://doi.org/10.5194/bg-21-731-2024, 2024
Short summary
Short summary
A complex network is a way of representing which parts of a system are connected to other parts. We have constructed a complex network based on an ecosystem–ocean model. From this, we can identify patterns in the structure and areas of similar behaviour. This can help to understand how natural, or human-made, changes will affect the shelf sea ecosystem, and it can be used in multiple future applications such as improving modelling, data assimilation, or machine learning.
This article is included in the Encyclopedia of Geosciences
Joelle Habib, Caroline Ulses, Claude Estournel, Milad Fakhri, Patrick Marsaleix, Mireille Pujo-Pay, Marine Fourrier, Laurent Coppola, Alexandre Mignot, Laurent Mortier, and Pascal Conan
Biogeosciences, 20, 3203–3228, https://doi.org/10.5194/bg-20-3203-2023, https://doi.org/10.5194/bg-20-3203-2023, 2023
Short summary
Short summary
The Rhodes Gyre, eastern Mediterranean Sea, is the main Levantine Intermediate Water formation site. In this study, we use a 3D physical–biogeochemical model to investigate the seasonal and interannual variability of organic carbon dynamics in the gyre. Our results show its autotrophic nature and its high interannual variability, with enhanced primary production, downward exports, and onward exports to the surrounding regions during years marked by intense heat losses and deep mixed layers.
This article is included in the Encyclopedia of Geosciences
Itzel Ruvalcaba Baroni, Elin Almroth-Rosell, Lars Axell, Sam T. Fredriksson, Jenny Hieronymus, Magnus Hieronymus, Sandra-Esther Brunnabend, Matthias Gröger, and Lars Arneborg
Biogeosciences Discuss., https://doi.org/10.5194/bg-2023-116, https://doi.org/10.5194/bg-2023-116, 2023
Revised manuscript accepted for BG
Short summary
Short summary
The health of the Baltic Sea and the North Sea is threatened due to high anthropogenic pressure and different methods to assess its status are urgently needed. Here, we validated a novel model simulating the ocean dynamics and biogeochemistry of the Baltic Sea and the North Sea that can be used to create future climate and nutrient scenarios and can keep contributing to European initiatives on de-eutrophication, water quality advice and support on nutrient reduction loads for both seas.
This article is included in the Encyclopedia of Geosciences
Masihullah Hasanyar, Thomas Romary, Shuaitao Wang, and Nicolas Flipo
Biogeosciences, 20, 1621–1633, https://doi.org/10.5194/bg-20-1621-2023, https://doi.org/10.5194/bg-20-1621-2023, 2023
Short summary
Short summary
The results of this study indicate that biodegradable dissolved organic matter is responsible for oxygen depletion at low flow during summer seasons when heterotrophic bacterial activity is so intense. Therefore, the dissolved organic matter must be well measured in the water monitoring networks in order to have more accurate water quality models. It also advocates for high-frequency data collection for better quantification of the uncertainties related to organic matter.
This article is included in the Encyclopedia of Geosciences
Xiangyu Liu and Qianlai Zhuang
Biogeosciences, 20, 1181–1193, https://doi.org/10.5194/bg-20-1181-2023, https://doi.org/10.5194/bg-20-1181-2023, 2023
Short summary
Short summary
We are among the first to quantify methane emissions from inland water system in the pan-Arctic. The total CH4 emissions are 36.46 Tg CH4 yr−1 during 2000–2015, of which wetlands and lakes were 21.69 Tg yr−1 and 14.76 Tg yr−1, respectively. By using two non-overlap area change datasets with land and lake models, our simulation avoids small lakes being counted twice as both lake and wetland, and it narrows the gap between two different methods used to quantify regional CH4 emissions.
This article is included in the Encyclopedia of Geosciences
Corentin Clerc, Laurent Bopp, Fabio Benedetti, Meike Vogt, and Olivier Aumont
Biogeosciences, 20, 869–895, https://doi.org/10.5194/bg-20-869-2023, https://doi.org/10.5194/bg-20-869-2023, 2023
Short summary
Short summary
Gelatinous zooplankton play a key role in the ocean carbon cycle. In particular, pelagic tunicates, which feed on a wide size range of prey, produce rapidly sinking detritus. Thus, they efficiently transfer carbon from the surface to the depths. Consequently, we added these organisms to a marine biogeochemical model (PISCES-v2) and evaluated their impact on the global carbon cycle. We found that they contribute significantly to carbon export and that this contribution increases with depth.
This article is included in the Encyclopedia of Geosciences
Shuang Gao, Jörg Schwinger, Jerry Tjiputra, Ingo Bethke, Jens Hartmann, Emilio Mayorga, and Christoph Heinze
Biogeosciences, 20, 93–119, https://doi.org/10.5194/bg-20-93-2023, https://doi.org/10.5194/bg-20-93-2023, 2023
Short summary
Short summary
We assess the impact of riverine nutrients and carbon (C) on projected marine primary production (PP) and C uptake using a fully coupled Earth system model. Riverine inputs alleviate nutrient limitation and thus lessen the projected PP decline by up to 0.7 Pg C yr−1 globally. The effect of increased riverine C may be larger than the effect of nutrient inputs in the future on the projected ocean C uptake, while in the historical period increased nutrient inputs are considered the largest driver.
This article is included in the Encyclopedia of Geosciences
Valeria Di Biagio, Stefano Salon, Laura Feudale, and Gianpiero Cossarini
Biogeosciences, 19, 5553–5574, https://doi.org/10.5194/bg-19-5553-2022, https://doi.org/10.5194/bg-19-5553-2022, 2022
Short summary
Short summary
The amount of dissolved oxygen in the ocean is the result of interacting physical and biological processes. Oxygen vertical profiles show a subsurface maximum in a large part of the ocean. We used a numerical model to map this subsurface maximum in the Mediterranean Sea and to link local differences in its properties to the driving processes. This emerging feature can help the marine ecosystem functioning to be better understood, also under the impacts of climate change.
This article is included in the Encyclopedia of Geosciences
Michael R. Stukel, Moira Décima, and Michael R. Landry
Biogeosciences, 19, 3595–3624, https://doi.org/10.5194/bg-19-3595-2022, https://doi.org/10.5194/bg-19-3595-2022, 2022
Short summary
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.
This article is included in the Encyclopedia of Geosciences
Ginevra Rosati, Donata Canu, Paolo Lazzari, and Cosimo Solidoro
Biogeosciences, 19, 3663–3682, https://doi.org/10.5194/bg-19-3663-2022, https://doi.org/10.5194/bg-19-3663-2022, 2022
Short summary
Short summary
Methylmercury (MeHg) is produced and bioaccumulated in marine food webs, posing concerns for human exposure through seafood consumption. We modeled and analyzed the fate of MeHg in the lower food web of the Mediterranean Sea. The modeled spatial–temporal distribution of plankton bioaccumulation differs from the distribution of MeHg in surface water. We also show that MeHg exposure concentrations in temperate waters can be lowered by winter convection, which is declining due to climate change.
This article is included in the Encyclopedia of Geosciences
Yanda Ou, Bin Li, and Z. George Xue
Biogeosciences, 19, 3575–3593, https://doi.org/10.5194/bg-19-3575-2022, https://doi.org/10.5194/bg-19-3575-2022, 2022
Short summary
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.
This article is included in the Encyclopedia of Geosciences
Eva Ehrnsten, Oleg Pavlovitch Savchuk, and Bo Gustav Gustafsson
Biogeosciences, 19, 3337–3367, https://doi.org/10.5194/bg-19-3337-2022, https://doi.org/10.5194/bg-19-3337-2022, 2022
Short summary
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.
This article is included in the Encyclopedia of Geosciences
Brandon J. McNabb and Philippe D. Tortell
Biogeosciences, 19, 1705–1721, https://doi.org/10.5194/bg-19-1705-2022, https://doi.org/10.5194/bg-19-1705-2022, 2022
Short summary
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.
This article is included in the Encyclopedia of Geosciences
Xi Wei, Josette Garnier, Vincent Thieu, Paul Passy, Romain Le Gendre, Gilles Billen, Maia Akopian, and Goulven Gildas Laruelle
Biogeosciences, 19, 931–955, https://doi.org/10.5194/bg-19-931-2022, https://doi.org/10.5194/bg-19-931-2022, 2022
Short summary
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.
This article is included in the Encyclopedia of Geosciences
Krysten Rutherford, Katja Fennel, Dariia Atamanchuk, Douglas Wallace, and Helmuth Thomas
Biogeosciences, 18, 6271–6286, https://doi.org/10.5194/bg-18-6271-2021, https://doi.org/10.5194/bg-18-6271-2021, 2021
Short summary
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.
This article is included in the Encyclopedia of Geosciences
Frerk Pöppelmeier, David J. Janssen, Samuel L. Jaccard, and Thomas F. Stocker
Biogeosciences, 18, 5447–5463, https://doi.org/10.5194/bg-18-5447-2021, https://doi.org/10.5194/bg-18-5447-2021, 2021
Short summary
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.
This article is included in the Encyclopedia of Geosciences
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, https://doi.org/10.5194/bg-18-4651-2021, https://doi.org/10.5194/bg-18-4651-2021, 2021
Short summary
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.
This article is included in the Encyclopedia of Geosciences
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, https://doi.org/10.5194/bg-18-3823-2021, https://doi.org/10.5194/bg-18-3823-2021, 2021
Short summary
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.
This article is included in the Encyclopedia of Geosciences
Mariana Hill Cruz, Iris Kriest, Yonss Saranga José, Rainer Kiko, Helena Hauss, and Andreas Oschlies
Biogeosciences, 18, 2891–2916, https://doi.org/10.5194/bg-18-2891-2021, https://doi.org/10.5194/bg-18-2891-2021, 2021
Short summary
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.
This article is included in the Encyclopedia of Geosciences
Roman Bezhenar, Kyeong Ok Kim, Vladimir Maderich, Govert de With, and Kyung Tae Jung
Biogeosciences, 18, 2591–2607, https://doi.org/10.5194/bg-18-2591-2021, https://doi.org/10.5194/bg-18-2591-2021, 2021
Short summary
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.
This article is included in the Encyclopedia of Geosciences
Emil De Borger, Justin Tiano, Ulrike Braeckman, Adriaan D. Rijnsdorp, and Karline Soetaert
Biogeosciences, 18, 2539–2557, https://doi.org/10.5194/bg-18-2539-2021, https://doi.org/10.5194/bg-18-2539-2021, 2021
Short summary
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.
This article is included in the Encyclopedia of Geosciences
Jens Terhaar, Olivier Torres, Timothée Bourgeois, and Lester Kwiatkowski
Biogeosciences, 18, 2221–2240, https://doi.org/10.5194/bg-18-2221-2021, https://doi.org/10.5194/bg-18-2221-2021, 2021
Short summary
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.
This article is included in the Encyclopedia of Geosciences
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, https://doi.org/10.5194/bg-18-1719-2021, https://doi.org/10.5194/bg-18-1719-2021, 2021
Short summary
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.
This article is included in the Encyclopedia of Geosciences
Rebecca M. Wright, Corinne Le Quéré, Erik Buitenhuis, Sophie Pitois, and Mark J. Gibbons
Biogeosciences, 18, 1291–1320, https://doi.org/10.5194/bg-18-1291-2021, https://doi.org/10.5194/bg-18-1291-2021, 2021
Short summary
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.
This article is included in the Encyclopedia of Geosciences
Valeria Di Biagio, Gianpiero Cossarini, Stefano Salon, and Cosimo Solidoro
Biogeosciences, 17, 5967–5988, https://doi.org/10.5194/bg-17-5967-2020, https://doi.org/10.5194/bg-17-5967-2020, 2020
Short summary
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
This article is included in the Encyclopedia of Geosciences
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, https://doi.org/10.5194/bg-17-5355-2020, https://doi.org/10.5194/bg-17-5355-2020, 2020
Short summary
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.
This article is included in the Encyclopedia of Geosciences
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, https://doi.org/10.5194/bg-17-5043-2020, https://doi.org/10.5194/bg-17-5043-2020, 2020
Taylor A. Shropshire, Steven L. Morey, Eric P. Chassignet, Alexandra Bozec, Victoria J. Coles, Michael R. Landry, Rasmus Swalethorp, Glenn Zapfe, and Michael R. Stukel
Biogeosciences, 17, 3385–3407, https://doi.org/10.5194/bg-17-3385-2020, https://doi.org/10.5194/bg-17-3385-2020, 2020
Short summary
Short summary
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.
This article is included in the Encyclopedia of Geosciences
Iris Kriest, Paul Kähler, Wolfgang Koeve, Karin Kvale, Volkmar Sauerland, and Andreas Oschlies
Biogeosciences, 17, 3057–3082, https://doi.org/10.5194/bg-17-3057-2020, https://doi.org/10.5194/bg-17-3057-2020, 2020
Short summary
Short summary
Constants of global biogeochemical ocean models are often tuned
This article is included in the Encyclopedia of Geosciences
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, https://doi.org/10.5194/bg-17-2767-2020, https://doi.org/10.5194/bg-17-2767-2020, 2020
Short summary
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.
This article is included in the Encyclopedia of Geosciences
Fabian A. Gomez, Rik Wanninkhof, Leticia Barbero, Sang-Ki Lee, and Frank J. Hernandez Jr.
Biogeosciences, 17, 1685–1700, https://doi.org/10.5194/bg-17-1685-2020, https://doi.org/10.5194/bg-17-1685-2020, 2020
Short summary
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.
This article is included in the Encyclopedia of Geosciences
Simon J. Parker
Biogeosciences, 17, 305–315, https://doi.org/10.5194/bg-17-305-2020, https://doi.org/10.5194/bg-17-305-2020, 2020
Short summary
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.
This article is included in the Encyclopedia of Geosciences
Fabrice Lacroix, Tatiana Ilyina, and Jens Hartmann
Biogeosciences, 17, 55–88, https://doi.org/10.5194/bg-17-55-2020, https://doi.org/10.5194/bg-17-55-2020, 2020
Short summary
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.
This article is included in the Encyclopedia of Geosciences
Patrick A. Rafter, Aaron Bagnell, Dario Marconi, and Timothy DeVries
Biogeosciences, 16, 2617–2633, https://doi.org/10.5194/bg-16-2617-2019, https://doi.org/10.5194/bg-16-2617-2019, 2019
Short summary
Short summary
The N isotopic composition of nitrate (
This article is included in the Encyclopedia of Geosciences
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, https://doi.org/10.5194/bg-16-2527-2019, https://doi.org/10.5194/bg-16-2527-2019, 2019
Short summary
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.
This article is included in the Encyclopedia of Geosciences
Jens Terhaar, James C. Orr, Marion Gehlen, Christian Ethé, and Laurent Bopp
Biogeosciences, 16, 2343–2367, https://doi.org/10.5194/bg-16-2343-2019, https://doi.org/10.5194/bg-16-2343-2019, 2019
Short summary
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.
This article is included in the Encyclopedia of Geosciences
Taylor S. Martin, François Primeau, and Karen L. Casciotti
Biogeosciences, 16, 347–367, https://doi.org/10.5194/bg-16-347-2019, https://doi.org/10.5194/bg-16-347-2019, 2019
Short summary
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.
This article is included in the Encyclopedia of Geosciences
Camille Richon, Jean-Claude Dutay, Laurent Bopp, Briac Le Vu, James C. Orr, Samuel Somot, and François Dulac
Biogeosciences, 16, 135–165, https://doi.org/10.5194/bg-16-135-2019, https://doi.org/10.5194/bg-16-135-2019, 2019
Short summary
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.
This article is included in the Encyclopedia of Geosciences
Angela M. Kuhn, Katja Fennel, and Ilana Berman-Frank
Biogeosciences, 15, 7379–7401, https://doi.org/10.5194/bg-15-7379-2018, https://doi.org/10.5194/bg-15-7379-2018, 2018
Short summary
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.
This article is included in the Encyclopedia of Geosciences
Prima Anugerahanti, Shovonlal Roy, and Keith Haines
Biogeosciences, 15, 6685–6711, https://doi.org/10.5194/bg-15-6685-2018, https://doi.org/10.5194/bg-15-6685-2018, 2018
Short summary
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.
This article is included in the Encyclopedia of Geosciences
Audrey Gimenez, Melika Baklouti, Thibaut Wagener, and Thierry Moutin
Biogeosciences, 15, 6573–6589, https://doi.org/10.5194/bg-15-6573-2018, https://doi.org/10.5194/bg-15-6573-2018, 2018
Short summary
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.
This article is included in the Encyclopedia of Geosciences
Jenny Hieronymus, Kari Eilola, Magnus Hieronymus, H. E. Markus Meier, Sofia Saraiva, and Bengt Karlson
Biogeosciences, 15, 5113–5129, https://doi.org/10.5194/bg-15-5113-2018, https://doi.org/10.5194/bg-15-5113-2018, 2018
Short summary
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.
This article is included in the Encyclopedia of Geosciences
Cyril Dutheil, Olivier Aumont, Thomas Gorguès, Anne Lorrain, Sophie Bonnet, Martine Rodier, Cécile Dupouy, Takuhei Shiozaki, and Christophe Menkes
Biogeosciences, 15, 4333–4352, https://doi.org/10.5194/bg-15-4333-2018, https://doi.org/10.5194/bg-15-4333-2018, 2018
Short summary
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.
This article is included in the Encyclopedia of Geosciences
Akitomo Yamamoto, Ayako Abe-Ouchi, and Yasuhiro Yamanaka
Biogeosciences, 15, 4163–4180, https://doi.org/10.5194/bg-15-4163-2018, https://doi.org/10.5194/bg-15-4163-2018, 2018
Short summary
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.
This article is included in the Encyclopedia of Geosciences
Fabian A. Gomez, Sang-Ki Lee, Yanyun Liu, Frank J. Hernandez Jr., Frank E. Muller-Karger, and John T. Lamkin
Biogeosciences, 15, 3561–3576, https://doi.org/10.5194/bg-15-3561-2018, https://doi.org/10.5194/bg-15-3561-2018, 2018
Short summary
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.
This article is included in the Encyclopedia of Geosciences
Martí Galí, Maurice Levasseur, Emmanuel Devred, Rafel Simó, and Marcel Babin
Biogeosciences, 15, 3497–3519, https://doi.org/10.5194/bg-15-3497-2018, https://doi.org/10.5194/bg-15-3497-2018, 2018
Short summary
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.
This article is included in the Encyclopedia of Geosciences
Konstantin Stolpovsky, Andrew W. Dale, and Klaus Wallmann
Biogeosciences, 15, 3391–3407, https://doi.org/10.5194/bg-15-3391-2018, https://doi.org/10.5194/bg-15-3391-2018, 2018
Short summary
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.
This article is included in the Encyclopedia of Geosciences
Anne Marx, Marcus Conrad, Vadym Aizinger, Alexander Prechtel, Robert van Geldern, and Johannes A. C. Barth
Biogeosciences, 15, 3093–3106, https://doi.org/10.5194/bg-15-3093-2018, https://doi.org/10.5194/bg-15-3093-2018, 2018
Short summary
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.
This article is included in the Encyclopedia of Geosciences
Malin Ödalen, Jonas Nycander, Kevin I. C. Oliver, Laurent Brodeau, and Andy Ridgwell
Biogeosciences, 15, 1367–1393, https://doi.org/10.5194/bg-15-1367-2018, https://doi.org/10.5194/bg-15-1367-2018, 2018
Short summary
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.
This article is included in the Encyclopedia of Geosciences
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, https://doi.org/10.5194/bg-15-1123-2018, https://doi.org/10.5194/bg-15-1123-2018, 2018
Short summary
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.
This article is included in the Encyclopedia of Geosciences
Cited articles
Adam, B., Klawonn, I., Sveden, J. B., Bergkvist, J., Nahar, N., Walve, J., Littmann, S., Whitehouse, M. J., Lavik, G., Kuypers, M. M., and Ploug, H.: N2-fixation, ammonium release and N-transfer to the microbial and classical food web within a plankton community, ISME J., 10, 450–459, https://doi.org/10.1038/ismej.2015.126, 2016. a
Agrawal, S. C.: Factors affecting spore germination in algae – review,
Folia Microbiol., 54, 273–302, https://doi.org/10.1007/s12223-009-0047-0, 2009. a, b
Ahrens, R.: Untersuchungen zur Verbreitung von Phagern der Gattung Agrobacterium in der Ostsee, Institut für Meereskunde, Universität Kiel, Germany, 102–112, 1971. a
Almroth-Rosell, E., Eilola, K., Hordoir, R., Meier, H. E. M., and Hall, P. O. J.: Transport of fresh and resuspended particulate organic material in the Baltic Sea? A model study, J. Marine Syst., 87, 1–12, https://doi.org/10.1016/j.jmarsys.2011.02.005, 2011. a
Ameisen, J. C.: The Origin of Programmed Cell Death, Science, 272, 1278–1279, https://doi.org/10.1126/science.272.5266.1278, 1996. a
Andersson, A., Höglander, H., Karlsson, C., and Huseby, S.: Key role of phosphorus and nitrogen in regulating cyanobacterial community composition in the northern Baltic Sea, Estuar. Coast. Shelf S., 164, 161–171, https://doi.org/10.1016/j.ecss.2015.07.013, 2015a. a
Andersson, A., Meier, H. E. M., Ripszam, M., Rowe, O., Wikner, J., Haglund, P., Eilola, K., Legrand, C., Figueroa, D., Paczkowska, J., Lindehoff, E., Tysklind, M., and Elmgren, R.: Projected future climate change and Baltic Sea ecosystem management, AMBIO, 44, 345–356, https://doi.org/10.1007/s13280-015-0654-8, 2015b. a
Baker, S. M., Levinton, J. S., Kurdziel, J. P., and Shumway, S. E.: Selective feeding and biodeposition by Zebra mussels and their relation to changes in phytoplankton composition and seston load, J. Shellfish Res., 17, 1207–1213, 1998. a
Berman-Frank, I., Bidle, K. D., Haramaty, L., and Falkowski, P. G.: The demise of the marine cyanobacterium, Trichodesmium spp., via an autocatalyzed cell death pathway, Limnol. Oceanogr., 49, 997–1005, https://doi.org/10.4319/lo.2004.49.4.0997, 2004. a, b
Bleiwas, A. H. and Stokes, P. M.: Collection of large and small food particles by Bosmina, Limnol. Oceanogr., 30, 1090–1092, https://doi.org/10.4319/lo.1985.30.5.1090, 1985. a
Bouvy, M., Pagano, M., and Trousellier, M.: Effects of a cyanobacterial bloom (Cylindrospermopsis raciborskii) on bacteria and zooplankton communities in Ingazeira reservoir (northeast Brazil), Aquat. Microb. Ecol., 25, 215–227, https://doi.org/10.3354/ame025215, 2001. a, b
Boyer, J., Rollwagen-Bollens, G., and Bollens, S. M.: Microzooplankton grazing before, during and after a cyanobacterial bloom in Vancouver Lake, Washington, USA, Aquat. Microb. Ecol., 64, 163–174, https://doi.org/10.3354/ame01514, 2011. a
Bracher, A., Vountas, M., Dinter, T., Burrows, J. P., Röttgers, R., and Peeken, I.: Quantitative observation of cyanobacteria and diatoms from space using PhytoDOAS on SCIAMACHY data, Biogeosciences, 6, 751–764, https://doi.org/10.5194/bg-6-751-2009, 2009. a
Bratbak, G., Egge, J. K., and Heldal, M.: Viral mortality of the marine algae Emiliania huxleyi (Haptophyceae) and termination of algal blooms, Mar. Ecol. Prog. Ser., 93, 39–48, https://doi.org/10.3354/meps093039, 1993. a
Bratbak, G., Thingstad, F., and Heldal, M.: Viruses and the microbial
loop, Microbial Ecol., 28, 209–221, https://doi.org/10.1007/bf00166811, 1994. a, b, c
Breitbart, M.: Marine viruses: truth or dare, Annu. Rev. Mar. Sci., 4, 425–448, https://doi.org/10.1146/annurev-marine-120709-142805, 2012. a, b
Breitbart, M., Thompson, L. R., Suttle, C. A., and Sullivan, M. B.: Exploring the Vast Diversity of Marine Viruses, Oceanography, 20, 135–139, https://doi.org/10.5670/oceanog.2007.58, 2007. a
Breitburg, D., Levin, L. A., Oschlies, A., Gregoire, M., Chavez, F. P., Conley, D. J., Garcon, V., Gilbert, D., Gutierrez, D., Isensee, K., Jacinto, G. S., Limburg, K. E., Montes, I., Naqvi, S. W. A., Pitcher, G. C., Rabalais, N. N., Roman, M. R., Rose, K. A., Seibel, B. A., Telszewski, M., Yasuhara, M., and Zhang, J.: Declining oxygen in the global ocean and coastal waters, Science, 359, eaam7240, https://doi.org/10.1126/science.aam7240, 2018. a, b
Brookes, J. D. and Ganf, G. G.: Variations in the boyancy response of Microcystis aeruginosa to nitrogen, phosphorus and light, J. Plankton Res., 23, 1399–1411, https://doi.org/10.1093/plankt/23.12.1399, 2001. a
Brookes, J. D., Ganf, G. G., and Oliver, R. L.: Heterogeneity of cyanobacterial gas-vesicle volume and metabolic activity,
J. Plankton Res., 22, 1579–1589, https://doi.org/10.1093/plankt/22.8.1579, 2000. a
Brutemark, A., Vandelannoote, A., Engström-Öst, J., and Suikkanen, S.: A Less Saline Baltic Sea Promotes Cyanobacterial Growth, Hampers Intracellular Microcystin Production, and Leads to Strain-Specific Differences in Allelopathy, PLoS One, 10, e0128904, https://doi.org/10.1371/journal.pone.0128904, 2015. a, b, c
Bugajev, A. O. and Koreiviene, J.: Determining optimal growth conditions for the highest biomass microalgae species in Lithuaninan Part of the Curonian Lagoon for further cultivation, Int. J. Environ. Res., 9, 233–246, 2015. a
Burchard, H., Craig, P. D., Gemmrich, J. R., van Haren, H., Mathieu, P. P., Meier, H. M., Nimmo Smith, W. A. M., Prandke, H., Rippeth, T. P., Skyllingstad, E. D., Smyth, W. D., Welsh, D. J. K., and Wijesekera, W.: Observational and numerical modeling methods for quantifying coastal ocean turbulence and mixing, Prog. Oceanogr., 76, 399–442, https://doi.org/10.1016/j.pocean.2007.09.005, 2008. a
Canter, H. M., Heaney, S. I., and Lund, J. W. G.: The ecological significance of grazing on planktonic populations of cyanobacteria by the ciliate Nassula, New Phytol., 114, 247–263, https://doi.org/10.1111/j.1469-8137.1990.tb00397.x, 1990. a
Carpenter, S. R.: Temporal variance in lake communities: blue-green algae and the trophic cascade, Landscape Ecol., 3, 175–184, https://doi.org/10.1007/BF00131536, 1989. a
Chan, F., Pace, M. L., Howarth, R. W., and Marino, R. M.: Bloom formation in heterocystic nitrogen-fixing cyanobacteria: The dependence on colony size and zooplankton grazing, Limnol. Oceanogr., 49, 2171–2178, https://doi.org/10.4319/lo.2004.49.6.2171, 2004. a
Chan, F., Marino, R. M., Howarth, R. W., and Pace, M. L.: Ecological constraints on planktonic nitrogen fixation in saline estuaries, II. Grazing controls on cyanobacterial population dynamics, Mar. Ecol. Prog. Ser., 309, 41–53, https://doi.org/10.3354/meps309041, 2006. a
Cirés, S. and Ballot, A.: A review of the phylogeny, ecology and toxin production of bloom-forming Aphanizomenon spp. and related species within the Nostocales (cyanobacteria), Harmful Algae, 54, 21–43, https://doi.org/10.1016/j.hal.2015.09.007, 2016. a, b
Cirés, S., Wörmer, L., Agha, R., and Quesada, A.: Overwintering populations of Anabaena, Aphanizomenon and Microcystis as potential inocula for summer blooms, J. Plankton Res., 35, 1254–1266, https://doi.org/10.1093/plankt/fbt081, 2013. a, b
Claessen, D., Rozen, D. E., Kuipers, O. P., Søgaard-Andersen, L., and van Wezel, G. P.: Bacterial solutions to multicellularity: a tale of biofilms, filaments and fruiting bodies, Nat. Rev. Microbiol., 12, 115–124, https://doi.org/10.1038/nrmicro3178, 2014. a
Clark, L. L., Ingall, E. D., and Benner, R.: Marine phosphorus is selectively remineralized, Nature, 393, 426, https://doi.org/10.1038/30881, 1998. a
Conley, D. J., Humborg, C., Rahm, L., Svchuk, O. P., and Wulff, F.: Hypoxia in the Baltic Sea and basin-scale changes in phosphorus
biogeochemistry, Environ. Sci. Technol., 36, 5315–5320, 2002. a
Cook, W. L., Ahearn, D. G., Reinhardt, D. J., and Reiber, R. J.: Blooms of an algophorous amoeba associated with anabaena in a fresh water lake, Water, Air, and Soil Pollution, 3, 71–80, https://doi.org/10.1007/BF00282728, 1974. a
Cottingham, K. L., Ewing, H. A., Greer, M. L., Carey, C. C., and Weathers, K. C.: Cyanobacteria as biological drivers of lake nitrogen and phosphorus cycling, Ecosphere, 6, 1–19, https://doi.org/10.1890/ES14-00174.1, 2015. a, b
Daewel, U. and Schrum, C.: Simulating long-term dynamics of the coupled North Sea and Baltic Sea ecosystem with ECOSMO II: Model description and validation, J. Marine Syst., 119–120, 30–49, https://doi.org/10.1016/j.jmarsys.2013.03.008, 2013. a, b, c
Daewel, U. and Schrum, C.: Low-frequency variability in North Sea and Baltic Sea identified through simulations with the 3-D coupled physical–biogeochemical model ECOSMO, Earth Syst. Dynam., 8, 801–815, https://doi.org/10.5194/esd-8-801-2017, 2017. a
Davis, T. W., Koch, F., Marcoval, M. A., Wilhelm, S. W., and Gobler, C. J.: Mesozooplankton and microzooplankton grazing during cyanobacterial blooms in the western basin of Lake Erie, Harmful Algae, 15, 26–35, https://doi.org/10.1016/j.hal.2011.11.002, 2012. a, b
DeMott, W. R. and Moxter, F.: Foraging on cyanobacteria by copepods: responses to chemical defences and resource abundance, Ecology, 72, 1820–1834, https://doi.org/10.2307/1940981, 1991. a, b
DeNobel, W. T., Matthijs, H. C. P., Von Elert, E., and Mur, L. R.: Comparison of the light-limited growth of the nitrogen-fixing cyanobacteria Anabaena and Aphanizomenon, New Phytol., 138, 579–587, https://doi.org/10.1046/j.1469-8137.1998.00155.x, 1998. a
Deutsch, C., Sarmiento, J. L., Sigman, D. M., Gruber, N., and Dunne, J. P.: Spatial coupling of nitrogen inputs and losses in the ocean, Nature, 445, 163–167, https://doi.org/10.1038/nature05392, 2007. a
Diaz, R. J. and Rosenberg, R.: Marine benthic hypoxia: a review of its ecological effects and the behavioural responses of benthic
macrofauna, Oceanogr. Mar. Biol., 33, 245–303, 1995. a
Diaz, R. J. and Rosenberg, R.: Spreading Dead Zones and Consequences for Marine Ecosystems, Science, 321, 926–929, https://doi.org/10.1126/science.1156401, 2008. a
Dietze, H. and Löptien, U.: Effects of surface current–wind interaction in an eddy-rich general ocean circulation simulation of the Baltic Sea, Ocean Sci., 12, 977–986, https://doi.org/10.5194/os-12-977-2016, 2016. a
Dolman, A. M., Rucker, J., Pick, F. R., Fastner, J., Rohrlack, T., Mischke, U., and Wiedner, C.: Cyanobacteria and cyanotoxins: the influence of nitrogen versus phosphorus, PLoS One, 7, e38757, https://doi.org/10.1371/journal.pone.0038757, 2012. a
Dryden, R. C. and Wright, S. J. L.: Predation of cyanobacteria by protozoa, Can. J. Microbiol., 33, 471–482, https://doi.org/10.1139/m87-080, 1987. a
Dyhrman, S. T. and Ruttenberg, K. C.: Presence and regulation of alkaline phosphatase activity in eukaryotic phytoplankton from the coastal ocean: Implications for dissolved organic phosphorus remineralization, Limnol. Oceanogr., 51, 1381–1390, https://doi.org/10.4319/lo.2006.51.3.1381, 2006. a, b, c
Dzierzbicka-Głowacka, L., Janecki, M., Nowicki, A., and Jakacki, J.: Activation of the operational ecohydrodynamic model (3D CEMBS) – the ecosystem module, Oceanologia, 55, 543–572, https://doi.org/10.5697/oc.55-3.543, 2013. a, b
Eglite, E., Graeve, M., Dutz, J., Wodarg, D., Liskow, I., Schulz-Bull, D., and Loick-Wilde, N.: Metabolism and foraging strategies of mid-latitude mesozooplankton during cyanobacterial blooms as revealed by fatty acids, amino acids, and their stable carbon isotopes, Ecol. Evol., 9, 9916–9934, https://doi.org/10.1002/ece3.5533, 2019. a, b
Eigemann, F., Schwartke, M., and Schuly-Vogt, H.: Niche separation of Baltic Sea cyanobacteria during bloom events by species interactions and autecological preferences, Harmful Algae, 72, 65–73, https://doi.org/10.1016/j.hal.2018.01.001, 2018. a, b, c, d
Eilola, K., Meier, H. E. M., and Almroth, E.: On the dynamics of oxygen, phosphorus and cyanobacteria in the Baltic Sea; A model study,
J. Marine Syst., 75, 163–184, https://doi.org/10.1016/j.jmarsys.2008.08.009, 2009. a, b
Eilola, K., Gustafsson, B. G., Kuznetsov, I., Meier, H. E. M., Neumann, T., and Savchuk, O. P.: Evaluation of biogeochemical cycles in an ensemble of three state-of-the-art numerical models of the Baltic Sea, J. Marine Syst., 88, 267–284, https://doi.org/10.1016/j.jmarsys.2011.05.004, 2011. a, b
Elmgren, R.: Understanding Human Impact on the Baltic Ecosystem: Changing Views in Recent Decades, AMBIO, 30, 222–231, https://doi.org/10.1579/0044-7447-30.4.222, 2001. a
Elmgren, R. and Larsson, U.: Nitrogen and the Baltic Sea: managing nitrogen in relation to phosphorus, Sci. World J., 1, 371–377, https://doi.org/10.1100/tsw.2001.291, 2001. a
Engström, J., Koski, M., Viitasalo, M., Reinikainen, M. R., Repka, S., and Sivonen, K.: Feeding interactions of the copepods Eurytemora affinis and Acartia bifilosa with the cyanobacteria Nodularia sp., J. Plankton Res., 22, 1403–1409, https://doi.org/10.1093/plankt/22.7.1403, 2000. a
Eppley, R. W.: The growth and culture of diatoms, in: The biology of diatoms, edited by: Werner, D., Botanical Monographs, Blackwell Scientific Publications, Oxford, London, Edinburgh, Melbourne, 24–64, https://doi.org/10.4319/lo.1979.24.1.0200, 1977. a, b, c
Foy, R. H.: The influence of surface to volume ratio on the growth rates of planktonic blue-green algae, Brit. Phycol. J., 15, 279–289, https://doi.org/10.1080/00071618000650281, 1980. a, b, c, d
Foy, R. H., Gibson, C. E., and Smith, R. V.: The influence of daylength, light intensity and temperature on the growth rates of planktonic blue-green algae, Brit. Phycol. J., 11, 151–163, https://doi.org/10.1080/00071617600650181, 1976. a, b, c
Franklin, D. J.: Explaining the causes of cell death in cyanobacteria: what role for asymmetric division?, J. Plankton Res., 36, 11–17, https://doi.org/10.1093/plankt/fbt114, 2013. a, b, c, d
Fuhrman, J. A.: Marine viruses and their biogeochemical and ecological effects, Nature, 399, 541–548, https://doi.org/10.1038/21119, 1999. a
Fuhs, G. W., Demnmerle, S. D., Canelli, E., and Chen, M.: Characterization of phosphorus-limited plankton algae, in: Nutrients and eutrophication, Amer. Soc. Limnol. Oceanogr. Spec. Symp. 1., edited by: Hutchinson, G. E. and Likens, G. E., Limnol. Oceanogr., 17, 113–133, https://doi.org/10.4319/lo.1972.17.6.0965, 1972. a, b, c, d, e
Ganf, G. G. and Oliver, R. L.: Vertical separation of light and available nutrients as a factor causing replacement of green algae by blue-green algae in the plankton of a stratified lake, J. Ecol., 70, 829–844, https://doi.org/10.2307/2260107, 1982. a
Ger, K. A., Naus-Wiezer, S., De Meester, L., and Lürling, M.: Zooplankton grazing selectivity regulates herbivory and dominance of toxic phytoplankton over multiple prey generations, Limnol. Oceanogr., 64, 1214–1227, https://doi.org/10.1002/lno.11108, 2019. a, b, c
Gerphagnon, M., Macarthur, D. J., Latour, D., Gachon, C. M. M., Van Ogtrop, F., Gleason, F. H., and Sime-Ngando, T.: Microbial players involved in the decline of filamentous and colonial cyanobacterial blooms with a focus on fungal parasitism, Environ. Microbiol., 17, 2573–2587, https://doi.org/10.1111/1462-2920.12860, 2015. a, b, c
Gilbert, J. J., and Bogdan, K. G.: Rotifer Grazing: In situ studies on selectivity and rates, in: Trophic Interactions Within Aquatic Ecosystems edited by: Meyers, D. G., CRC Press, New York, 97–134, https://doi.org/10.4324/9780429269608, 2017. a
Gobler, C. J., Burkholder, J. M., Davis, T. W., Harke, M. J., Johengen, T., Stow, C. A., and Van de Waal, D. B.: The dual role of nitrogen supply in controlling the growth and toxicity of cyanobacterial blooms, Harmful Algae, 54, 87–97, https://doi.org/10.1016/j.hal.2016.01.010, 2016. a, b
Gulati, R. D., Dionisio Pires, L. M., and Van Donk, E.: Lake restoration studies: Failures, bottlenecks and prospects of new ecotechnological measures, Limnologica, 38, 233–247, https://doi.org/10.1016/j.limno.2008.05.008, 2008. a
Gustafsson, E.: Modeled long-term development of hypoxic area and nutrient pools in the Baltic Proper, J. Marine Syst., 94, 120–134, https://doi.org/10.1016/j.jmarsys.2011.11.012, 2012. a
Gustafsson, E., Savchuk, O. P., Gustafsson, B. G., and Müller-Karulis, B.: Key processes in the coupled carbon, nitrogen, and phosphorus cycling of the Baltic Sea, Biogeochemistry, 134, 301–317, https://doi.org/10.1007/s10533-017-0361-6, 2017. a, b, c
Gustafsson, S., Rengefors, K., and Hansson, L.-A.: Increased consumer fitness following transfer of toxin tolerance to offspring via maternal effects, Ecology, 86, 2561–2567, https://doi.org/10.1890/04-1710, 2005. a
Håkanson, L.: A general process-based mass-balance model for phosphorus/eutrophication as a tool to estimate historical reference values for key bioindicators, as exemplified using data for the Gulf of
Riga, Ecol. Model., 220, 226–244, https://doi.org/10.1016/j.ecolmodel.2008.09.012, 2009. a
Hannerz, F. and Destouni, G.: Spatial Characterization of the Baltic Sea Drainage Basin and Its Unmonitored Catchments, AMBIO, 35, 214–219, https://doi.org/10.1579/05-a-022r.1, 2006. a
Hansson, M. and Hakansson, B.: The Baltic Algae Watch System – a remote sensing application for monitoring cyanobacterial blooms in the Baltic
Sea, J. Appl. Remote Sens., 1, 011507, https://doi.org/10.1117/1.2834769, 2007. a
Head, R. M., Jones, R. I., and Bailey-Watts A. E.: An assessment of the influence of recruitment from the sediment on the development of planktonic populations of cyanobacteria in a temperate mesotrophic lake, Freshwater Biol., 41, 759–769, https://doi.org/10.1046/j.1365-2427.1999.00421.x,1999. a
Healey, F. P: Characteristics of phosphorus deficiency in Anabaena, J. Phycol., 9, 383–394, https://doi.org/10.1111/j.1529-8817.1973.tb04111.x, 1973. a, b
Heiskanen, A.-S. and Olli, K.: Sedimentation and buoyancy of Aphanizomenon cf. flosaquae (Nostocales, Cyanophyta) in a nutrient-replete and nutrient-depleted coastal area of the Baltic Sea, Phycologia, 35, 94–101, https://doi.org/10.2216/i0031-8884-35-6S-94.1, 1996. a
HELCOM: Baltic Sea Action Plan – Eutrophication segment of the HELCOM Baltic Sea Action Plan, HELCOM Ministerial Meeting, Krakow, Poland, 1—41, 15 November 2007. a
HELCOM: Eutrophication status of the Baltic Sea 2007–2011 – A concise thematic assessment, Baltic Sea Environment Proceedings, 1–41, 143, 2014. a
HELCOM: State of the Baltic Sea – Second HELCOM holistic assessment 2011–2016, Baltic Sea Environment Proceedings, 1–155, 2018. a
Hellweger, F. L., Fredrick, N. D., McCarthy, M. J., Gardner, W. S., Wilhelm, S. W., and Paerl, H. W.: Dynamic, mechanistic, molecular-level modeling of cyanobacteria: Anabaena and nitrogen interaction, Environ. Microbiol., 18, 2721–2731, https://doi.org/10.1111/1462-2920.13299, 2016. a
Hense, I.: Regulative feedback mechanisms in cyanobacteria-driven systems: a model study, Mar. Ecol. Prog. Ser., 339, 41–47, https://doi.org/10.3354/meps339041, 2007. a, b
Hense, I. and Beckmann, A.: The representation of cyanobacteria life cycle processes in aquatic ecosystem models, Ecol. Model., 221, 2330–2338, https://doi.org/10.1016/j.ecolmodel.2010.06.014, 2010. a, b
Hense, I., Meier, H. E. M., and Sonntag, S.: Projected climate change impact on Baltic Sea cyanobacteria, Climatic Change, 119, 391–406, https://doi.org/10.1007/s10584-013-0702-y, 2013. a, b, c
Hewson, I., Govil, S. R., Capone, D. G., Carpenter, E. J., and Fuhrman, J. A.: Evidence of Trichodesmium viral lysis and potential significance for biogeochemical cyling in the oligotrophic ocean, Aquat. Microb. Ecol., 36, https://doi.org/10.3354/ame036001, 2004. a
Hofmeister, R., Beckers, J. M., and Burchard, H.: Realistic modeling of the exceptional inflows into the central Baltic Sea in 2003 using terrain-following coordinates, Ocean Model., 39, 233–247, https://doi.org/10.1016/j.ocemod.2011.04.007, 2011. a
Holm, N. P. and Armstrong, D. E.: Role of nutrient limitation and competition in controlling the populations of Asterionella formosa and Microcystis aeruginosa in semicontinuous culture, Limnol. Oceanogr., 26, 622–634, https://doi.org/10.4319/lo.1981.26.4.0622, 1981. a, b, c, d
Holmfeldt, K., Titelman, J., and Riemann, L.: Virus production and lysate recycling in different sub-basins of the northern Baltic Sea, Microbial Ecol., 60, 572–580, https://doi.org/10.1007/s00248-010-9668-8, 2010. a
Hong, Y., Burford, M. A., Ralph, P. J., Udy, J. W., and Doblin, M. A.: The cyanobacterium Cylindrospermopsis raciborskii is facilitated by copepod selective grazing, Harmful Algae, 29, 14–21, https://doi.org/10.1016/j.hal.2013.07.003, 2013. a
Huber, A. L.: Factors affecting the germination of akinetes of Nodularia spumigena (Cyanobacteriaceae), Appl. Environ. Microb., 49, 73–78, https://doi.org/0099-2240/85/010073-06,1985. a
Ibelings, B. W.: Changes in photosynthesis in response to combined irradiance and temperature stress in cyanobacterial surface
waterblooms, J. Appl. Phycol., 32, 549–557, https://doi.org/10.1111/j.0022-3646.1996.00549.x, 1996. a
Ibelings, B., Mur, L., Kinsman, R., and Walsby, A.: Microcystis changes its buoyancy in response to the average irradiance in the surface mixed
layer, Arch. Hydrobiol., 120, 385–401, 1991. a
Ismail, A. H., Mills, S., and Recknagel, F.: Feeding evaluation of microcrustacea (Cladocera): responses to variations in cell volume of green and blue-green algae, Appl. Ecol. Env. Res., 17, 7715–7725, https://doi.org/10.15666/aeer/1704_77157725, 2019. a
Janssen, F., Neumann, T., and Schmidt, M.: Inter-annual variability in cyanobacteria blooms in the Baltic Sea controlled by wintertime hydrographic conditions, Mar. Ecol. Prog. Ser., 275, 59–68, https://doi.org/10.3354/meps275059, 2004. a, b
Jodlowska, S. and Latala, A.: Photoacclimation strategies in the toxic cyanobacterium Nodularia spumigena (Nostocales, Cyanobacteria), Phycologia, 49, 203–211, https://doi.org/10.2216/PH08-14.1, 2019. a, b, c, d
Jones, G. J., Blackburn, S. I., and Parker, N. S.: A toxic bloom of Nodularia spumigena Mertens in Orielton Lagoon, Tasmania,
Aust. J. Mar. Fresh. Res., 45, 787–800, 1994. a
Jones, R. I.: Notes on the growth and sporulation of a natural population of Aphanizomenon flos-aquae, Hydrobiologia, 62, 55–58, https://doi.org/10.1007/BF00012562, 1979. a
Kahru, M., Elmgren, R., Kaiser, J., Wasmund, N., and Savchuk, O.: Cyanobacterial blooms in the Baltic Sea: Correlations with environmental factors, Harmful Algae, 92, 101739, https://doi.org/10.1016/j.hal.2019.101739, 2020. a
Kaiser, J., Wasmund, N., Kahru, M., Wittenborn, A. K., Hansen, R., Häusler, K., Moros, M., Schulz-Bull, D., and Arz, H. W.: Reconstructing N2-fixing cyanobacterial blooms in the Baltic Sea beyond observations using 6- and 7-methylheptadecane in sediments as specific biomarkers, Biogeosciences, 17, 2579–2591, https://doi.org/10.5194/bg-17-2579-2020, 2020. a
Kaitala, S., Kettunen, J., and Seppälä, J.: Introduction to Special Issue: 5th ferrybox workshop – Celebrating 20 years of the Algaline, J. Marine Syst., 140, 1–3, https://doi.org/10.1016/j.jmarsys.2014.10.001, 2014. a
Kanoshina, I., Lips, U., and Leppänen, J.-M.: The influence of weather conditions (temperature and wind) on cyanobacterial bloom development in the Gulf of Finland (Baltic Sea), Harmful Algae, 2, 29–41, https://doi.org/10.1016/s1568-9883(02)00085-9, 2003. a
Kaplan-Levy, R. N., Hadas, O., Summers, M. L., Rücker, J., and Sukenik, A.: Akinetes: Dormant Cells of Cyanobacteria, in: Dormancy and Resistance in Harsh Environments, Topics in Current Genetics, edited by: Lubzens, E., Cerda, J., and Clark, M., Springer, Berlin, Heidelberg, Germany, 5–27, https://doi.org/10.1007/978-3-642-12422-8, 2010. a, b, c, d, e
Karlberg, M. and Wulff, A.: Impact of temperature and species interaction on filamentous cyanobacteria may be more important than salinity and increased pCO2 levels, Mar. Biol., 160, 2063–2072, https://doi.org/10.1007/s00227-012-2078-3, 2013. a
Karlsson, K. M., Kankaanpää, H., Huttunen, M., and Meriluoto, J.: First observation of microcystin-LR in pelagic cyanobacterial blooms in the northern Baltic Sea, Harmful Algae, 4, 163–166, https://doi.org/10.1016/j.hal.2004.02.002, 2005. a
Karlsson-Elfgren, I., Rengefors, K., and Gustafsson, S.: Factors regulating recruitment from the sediment to the water column in the bloom-forming cyanobacterium Gloeotrichia echinulata, Freshwater Biol., 49, 265–273, https://doi.org/10.1111/j.1365-2427.2004.01182.x, 2004. a
Kerfoot, W. C. and Kirk, K. L.: Degree of taste discrimination among suspension-feeding cladocerans and copepods: Implications for detritivory and herbivory, Limnol. Oceanogr., 36, 1107–1123, https://doi.org/10.4319/lo.1991.36.6.1107, 1991. a
Klemer, A. R., Feuillade, J., and Feuillade, M.: Cyanobacterial blooms: carbon and nitrogen limitation have opposite effects on the buoyancy of Oscillatoria, Science, 215, 1629–1631, https://doi.org/10.1126/science.215.4540.1629, 1982. a
Kononen, K. and Leppänen, J.-M.: Patchiness, scales and controlling mechanisms of cyanobacterial blooms in the Baltic Sea: application of a multiscale research strategy, in: Monitoring algal blooms: new techniques for detecting large-scale environmental change, edited by: Kahru, M. and Brown, C. W., Landes Bioscience, Austin, Texas, USA, 63–84, 1997. a
Kononen, K., Kuparinen, J., and Mäkelä, K.: Initiation of cyanobacterial blooms in a frontal region at the entrance to the Gulf of Finland, Baltic Sea, Limnol. Oceanogr., 41, 98–112, https://doi.org/10.4319/lo.1996.41.1.0098, 1996. a
Konopka, A., Kromkamp, J., and Mur, L. R.: Regulation of gas vesicle content and buoyancy in light-or phosphate-limited cultures of Aphanizomenon flos-aquae (Cyanophyta), J. Phycol., 23, 70–78, https://doi.org/10.1111/j.0022-3646.1987.00070.x, 1987. a, b, c
Kozik, C., Young, E. B., Sandgren, C. D., and Berges, J. A.: Cell death in individual freshwater phytoplankton species: relationships with population dynamics and environmental factors, Eur. J. Phycol., 54, 369–379, https://doi.org/10.1080/09670262.2018.1563216, 2019. a
Kremp, C., Seifert, T., Mohrholz, V., and Fennel, W.: The oxygen dynamics during Baltic inflow events in 2001 to 2003 and the effect of different meteorological forcing? A model study, J. Marine Syst., 67, 13–30, https://doi.org/10.1016/j.jmarsys.2006.08.002, 2007. a
Kromkamp, J., Konopka, A., and Mur, L. R.: Buoyancy regulation in a strain of Aphanizomenon-flos-aquae (Cyanophyceae) – The importance of carbohydrate accumulation and gas vesicle collapse, Journal of general microbiology, 132, 2113–2121, 1986. a
Kruk, C., Huszar, V. L. M., Peeters, E. T. H. M., Bonilla, S., Costa, L., Lürling, M., Reynolds, C. S., and Scheffer, M.: A morphological classification capturing functional variation in phytoplankton, Freshwater Biol., 55, 614–627, https://doi.org/10.1111/j.1365-2427.2009.02298.x, 2010. a
Kuznetsov, I. and Neumann, T.: Simulation of carbon dynamics in the Baltic Sea with a 3D model, J. Marine Syst., 111–112, 167–174, https://doi.org/10.1016/j.jmarsys.2012.10.011, 2013. a
Kuznetsov, I., Neumann, T., and Burchard, H.: Model study on the ecosystem impact of a variable
Laamanen, M. J., Forsstrom, L., and Sivonen, K.: Diversity of Aphanizomenon flos-aquae (Cyanobacterium) Populations along a Baltic Sea Salinity Gradient, Appl. Environ. Microb., 68, 5296–5303, https://doi.org/10.1128/aem.68.11.5296-5303.2002, 2002. a, b, c
Laanemets, J., Lilover, M. J., Raudsepp, U., Autio, R., Vahtera, E., Lips, I., and Lips, U.: A Fuzzy Logic Model to Describe the Cyanobacteria Nodularia spumigena Blooms in the Gulf of Finland, Baltic Sea, Hydrobiologia, 554, 31–45, https://doi.org/10.1007/s10750-005-1004-x, 2006. a
Landolfi, A., Kähler, P., Koeve, W., and Oschlies, A.: Global Marine N2 Fixation Estimates: from Observations to
Models, Front. Microbiol., 9, 2112, https://doi.org/10.3389/fmicb.2018.02112, 2018. a
LaRoche, J. and Breitbarth, E.: Importance of the diazotrophs as a source of new nitrogen in the ocean, J. Sea Res., 53, 67–91, https://doi.org/10.1016/j.seares.2004.05.005, 2005. a
Larsson, U., Hajdu, S., Walve, J., and Elmgren, R.: Baltic Sea nitrogen fixation estimated from the summer increase in upper mixed layer total nitrogen, Limnol. Oceanogr., 46, 811–820, https://doi.org/10.4319/lo.2001.46.4.0811, 2001. a, b, c
Lee, D.-Y. and Rhee, G.-Y.: Kinetics of cell death in the cyanobacterium Anabaena flosaquae and the production of dissolved organic
carbon, J. Phycol., 33, 991–998, https://doi.org/10.1111/j.0022-3646.1997.00991.x, 1997. a, b
Lee, D.-Y. and Rhee, G.-Y.: Kinetics of growth and death in Anabaena flosaquae (Cyanobacteria) and light limitation and supersaturation, J. Phycol., 35, 700–709, https://doi.org/10.1046/j.1529-8817.1999.3540700.x, 1999. a, b, c, d
Levy, B. and Jami, E.: Exploring the Prokaryotic Community Associated with the Rumen Ciliate Protozoa Population, Front. Microbiol., 9, 1–14, https://doi.org/10.3389/fmicb.2018.02526, 2018. a
Lewis, W. M.: Surface/Volume Ratio: Implications for Phytoplankton Morphology, Science, 192, 885–887, https://doi.org/10.1126/science.192.4242.885, 1976. a
Lilover, M. J. and Laanemets, J.: A simple tool for the early prediction of the cyanobacteria Nodularia spumigena bloom biomass in the Gulf of Finland, Oceanologia, 48, 213–229, 2006. a
Lin, S., Litaker, R. W., and Sunda, W. G.: Phosphorus physiological ecology and molecular mechanisms in marine phytoplankton, J. Phycol., 52, 10–36, https://doi.org/10.1111/jpy.12365, 2016. a
Lin, X., Zhang, H., Cui, Y., and Lin, S.: High sequence variability, diverse subcellular localizations, and ecological implications of alkaline phosphatase in dinoflagellates and other eukaryotic
phytoplankton, Front. Microbiol., 3, 1–13, https://doi.org/10.3389/fmicb.2012.00235, 2012. a
Lips, I. and Lips, U.: Abiotic factors influencing cyanobacterial bloom development in the Gulf of Finland (Baltic Sea), Hydrobiologia, 614, 133–140, https://doi.org/10.1007/s10750-008-9449-2, 2008. a, b
Lips, I. and Lips, U.: The importance of Mesodinium rubrum at post-spring bloom nutrient and phytoplankton dynamics in the vertically stratified Baltic Sea, Front. Mar. Sci., 4, 407–416, https://doi.org/10.3389/fmars.2017.00407, 2017. a
Liu, L., Yang, J., Lv, H., and Yu, Z.: Synchronous dynamics and correlations between bacteria and phytoplankton in a subtropical drinking water reservoir, FEMS Microbiol. Ecol., 90, 126–138, https://doi.org/10.1111/1574-6941.12378, 2014. a
Löptien, U.: Steady states and sensitivities of commonly used pelagic ecosystem model components, Ecol. Model., 222, 1376–1386, https://doi.org/10.1016/j.ecolmodel.2011.02.005, 2011. a
Löptien, U. and Dietze, H.: Constraining parameters in marine pelagic ecosystem models – is it actually feasible with typical observations of standing stocks?, Ocean Sci., 11, 573–590, https://doi.org/10.5194/os-11-573-2015, 2015. a
Löptien, U. and Dietze, H.: Reciprocal bias compensation and ensuing uncertainties in model-based climate projections: pelagic biogeochemistry versus ocean mixing, Biogeosciences, 16, 1865–1881, https://doi.org/10.5194/bg-16-1865-2019, 2019. a
Löptien, U. and Dietze, H.: Contrasting juxtaposition of two paradigms for diazotrophy in an Earth System Model of intermediate complexity, Biogeosciences Discuss. [preprint], https://doi.org/10.5194/bg-2020-96, 2020. a, b
Lund, J. W. G.: Studies on Asterionella: I. The Origin and Nature of the Cells Producing Seasonal Maxima, J. Ecol., 37, 389–419, https://doi.org/10.2307/2256614, 1949. a, b
Łysiak-Pastuszak, E., Bartoszewicz, M., Bradtke, K., Darecki, M., Drgas, N., Kowalczuk, P., Kraśniewski, W., Krężel, A., Krzymiński, W., Lewandowski, Ł., Mazur-Marzec, H., Piliczewski, B., Sagan, S., Sutryk, K., and Witek, B.: A study of episodic events in the Baltic Sea – combined in situ and satellite observations, Oceanologia, 54, 121–141, https://doi.org/10.5697/oc.54-2.121, 2012. a
Maranger, R. and Bird, D. F.: Viral abundance in aquatic systems: a comparison between marine and fresh waters, Mar. Ecol. Prog. Ser., 16161599, https://doi.org/10.3354, 1995. a
Mazur-Marzec, H., Żeglińska, L., and Pliński, M.: The effect of salinity on the growth, toxin production, and morphology of Nodularia spumigena isolated from the Gulf of Gdańsk, southern Baltic Sea, J. Appl. Phycol., 17, 171–179, https://doi.org/10.1007/s10811-005-5767-1, 2005. a
Mazur-Marzec, H., Sutryk, K., Kobos, J., Hebel, A., Hohlfeld, N., Błaszczyk, A., Toruńska, A., Kaczkowska, M. J., Łysiak-Pastuszak, E., Kraśniewski, W., and Jasser, I.: Occurrence of cyanobacteria and cyanotoxin in the Southern Baltic Proper. Filamentous cyanobacteria versus single-celled picocyanobacteria, Hydrobiologia, 701, 235–252, https://doi.org/10.1007/s10750-012-1278-7, 2013. a, b
Meier, H. E. M. and Kauker, F.: Modeling decadal variability of the Baltic Sea: 2. Role of freshwater inflow and large-scale atmospheric circulation for salinity, J. Geophys. Res.-Oceans, 108, 3368, https://doi.org/10.1029/2003JC001799, 2003. a
Meier, H. E. M., Andersson, H. C., Eilola, K., Gustafsson, B. G., Kuznetsov, I., Müller-Karulis, B., Neumann, T., and Savchuk, O. P.: Hypoxia in future climates: A model ensemble study for the Baltic
Sea, Geophys. Res. Lett., 38, 1–6, https://doi.org/10.1029/2011gl049929, 2011a. a
Meier, H. E. M., Eilola, K., and Almroth-Rosell, E.: Climate-related changes in marine ecosystems simulated with a three-dimensional coupled physical-biogeochemical model of the Baltic Sea, Clim. Res., 48, 31–55, https://doi.org/10.3354/cr00968, 2011b. a
Meier, H. E. M., Höglund, A., Döscher, R., Andersson, H., Löptien, U., and Kjellström, E.: Quality assessment of atmospheric surface fields over the Baltic Sea from an ensemble of regional climate model simulations with respect to ocean dynamics, Oceanologia, 53, 193–227, https://doi.org/10.5697/oc.53-1-TI.193, 2011c. a
Meier, H. E. M., Müller-Karulis, B., Andersson, H. C., Dieterich, C., Eilola, K., Gustafsson, B. G., Hoglund, A., Hordoir, R., Kuznetsov, I., Neumann, T., Ranjbar, Z., Savchuk, O. P., and Schimanke, S.: Impact of climate change on ecological quality indicators and biogeochemical fluxes in the Baltic sea: a multi-model ensemble study, AMBIO, 41, 558–573, https://doi.org/10.1007/s13280-012-0320-3, 2012. a, b, c, d
Meier, H. E. M., Andersson, H. C., Arheimer, B., Donnelly, C., Eilola, K., Gustafsson, B. G., Kotwicki, L., Neset, T. S., Niiranen, S., Piwowarczyk, J., Savchuk, O. P., Schenk, F., Weslawski, J. M., and Zorita, E.: Ensemble modeling of the Baltic Sea ecosystem to provide scenarios for management, AMBIO, 43, 37–48, https://doi.org/10.1007/s13280-013-0475-6, 2014. a
Meier, H. E. M., Dieterich, C., Eilola, K., Gröger, M., Höglund, A., Radtke, H., Saraiva, S., and Wählström, I.: Future projections of record-breaking sea surface temperature and cyanobacteria bloom events in the Baltic Sea, AMBIO, 48, 1362–1376, https://doi.org/10.1007/s13280-019-01235-5, 2019. a, b
Mironova, E. I., Telesh, I. V., and Skarlato, S. O.: “Biodiversity of microzooplankton (ciliates and rotifers) in the Baltic Sea”, in: IEEE/OES US/EU-Baltic International Symposium, Tallinn, Estonia, 27–29 May 2008, 1–5, https://doi.org/10.1109/BALTIC.2008.4625505, 2008. a, b, c
Mohamed, Z. A., Hashem, M., and Alamri, S. A.: Growth inhibition of the cyanobacterium Microcystis aeruginosa and degradation of its microcystin toxins by the fungus Trichoderma citrinoviride, Toxicon, 86, 51–58, https://doi.org/10.1016/j.toxicon.2014.05.008, 2014. a
Moisander, P. H., McClinton, E., and Paerl, H. W.: Salinity effects on growth, photosynthetic parameters, and nitrogenase activity in estuarine planktonic cyanobacteria, Microb. Ecol., 43, 432–442, https://doi.org/10.1007/s00248-001-1044-2, 2002. a, b, c
Moisander, P. H., Paerl, H. W., Dyble, J., and Sivonen, K.: Phosphorus limitation and diel control of nitrogen-fixing cyanobacteria in the Baltic Sea, Mar. Ecol. Prog. Ser., 345, 41–50, https://doi.org/10.3354/meps06964, 2007. a, b
Molot, L. A., Watson, S. B., Creed, I. F., Trick, C. G., McCabe, S. K., Verschoor, M. J., Sorichetti, R. J., Powe, C., Venkiteswaran, J. J., and Schiff, S. L.: A novel model for cyanobacteria bloom formation: the critical role of anoxia and ferrous iron, Freshwater Biol., 59, 1323–1340, https://doi.org/10.1111/fwb.12334, 2014. a
Munn, C.: Ecology & Applications, in: Marine Microbiology, 2 edn., Garland Science, New York, 1–364, https://doi.org/10.1201/9781136667527, 2011. a
Nalewajko, C. and Murphy, T. P.: Effects of temperature, and availability of nitrogen and phosphorus on the abundance of Anabaena and Microcystis in Lake Biwa, Japan: an experimental approach, Limnology, 2, 45–48, https://doi.org/10.1007/s102010170015, 2001. a, b, c
Nausch, M., Nausch, G., Wasmund, N., and Nagel, K.: Phosphorus pool variations and their relation to cyanobacteria development in the Baltic Sea: A three-year study, J. Marine Syst., 71, 99–111, https://doi.org/10.1016/j.jmarsys.2007.06.004, 2008. a
Nausch, M., Nausch, G., Lass, H. U., Mohrholz, V., Nagel, K., Siegel, H., and Wasmund, N.: Phosphorus input by upwelling in the eastern Gotland Basin (Baltic Sea in summer and its effects on filamentous cyanobacteria,
Estuar. Coast. Shelf S., 83, 434–442, https://doi.org/10.1016/j.ecss.2009.04.031, 2009. a, b
Nehring, D. and Matthäus, W.: Current Trends in Hydrographic and Chemical Parameters and Eutrophication in the Baltic Sea, Int. Rev. Hydrobiol., 76, 297–316, https://doi.org/10.1002/iroh.19910760303, 1991. a
Neumann, T.: Climate-change effects on the Baltic Sea ecosystem: A model study, J. Marine Syst., 81, 213–224, https://doi.org/10.1016/j.jmarsys.2009.12.001, 2010. a, b, c
Neumann, T. and Schernewski, G.: An ecological model evaluation of two nutrient abatement strategies for the Baltic Sea, J. Marine Syst., 56, 195–206, https://doi.org/10.1016/j.jmarsys.2004.10.002, 2005. a
Neumann, T. and Schernewski, G.: Eutrophication in the Baltic Sea and shifts in nitrogen fixation analysed with a 3D ecosystem model, J. Marine Syst., 74, 592–602, https://doi.org/10.1016/j.jmarsys.2008.05.003, 2008. a
Neumann, T., Fennel, W., and Kremp, C.: Experimental simulations with an ecosystem model of the Baltic Sea: A nutrient load reduction experiment, Global Biogeochem. Cy., 16, https://doi.org/10.1029/2001gb001450, 2002. a, b, c
Neumann, T., Eilola, K., Gustafsson, B., Müller-Karulis, B., Kuznetsov, I., Meier, H. E. M., and Savchuk, O. P.: Extremes of Temperature, Oxygen and Blooms in the Baltic Sea in a Changing Climate, AMBIO, 41, 574–585, https://doi.org/10.1007/s13280-012-0321-2, 2012. a
Ning, S.-B., Guo, H.-L., Wang, L., and Song, Y.-C.: Salt stress induces programmed cell death in prokaryotic organism
Anabaena, J. Appl. Microbiol., 93, 15–28, https://doi.org/10.1046/j.1365-2672.2002.01651.x, 2002. a
Nowicki, A., Dzierzbicka-Głowacka, L., Janecki, M., and Kałas, M.: Assimilation of the satellite SST data in the 3D CEMBS model, Oceanologia, 57, 17–24, https://doi.org/10.1016/j.oceano.2014.07.001, 2015. a
Nowicki, A., Rak, D., Janecki, M., and Dzierzbicka-Głowacka, L.: Accuracy assessment of temperature and salinity computed by the 3D Coupled Ecosystem Model of the Baltic Sea (3D CEMBS) in the Southern
Baltic, J. Oper. Oceanogr., 9, 67–73, https://doi.org/10.1080/1755876x.2016.1209368, 2016. a
Nyholm, N.: Kinetics of phosphate limited algal
growth, Biotechnol. Bioeng., 19, 467–492, https://doi.org/10.1002/bit.260190404, 1977. a
O'Neil, J. M., Davis, T. W., Burford, M. A., and Gobler, C. J.: The rise of harmful cyanobacteria blooms: The potential roles of eutrophication and climate change, Harmful Algae, 14, 313–334, https://doi.org/10.1016/j.hal.2011.10.027, 2012. a, b
Oh, H.-M., Maeng, J., and Rhee, G.-Y.: Nitrogen and carbon fixation by Anabaena sp. isolated from a rice paddy and grown under P and light limitations, J. Appl. Phycol., 3, 335–343, https://doi.org/10.1007/BF00026096, 1991. a, b
Ojaveer, H., Jaanus, A., Mackenzie, B. R., Martin, G., Olenin, S., Radziejewska, T., Telesh, I., Zettler, M. L., and Zaiko, A.: Status of biodiversity in the Baltic Sea, PloS One, 5, e12467, https://doi.org/10.1371/journal.pone.0012467, 2010. a
Oliver, R. L.: Floating and Sinking in Gas-Vacuolate Cyanobacteria1, J. Phycol., 30, 161–173, https://doi.org/10.1111/j.0022-3646.1994.00161.x, 1994. a
Olli, K., Kangro, K., and Kabel, M.: Akinete Production of Anabaena Lemmermannii and A. Cylindrica (Cyanophyceae) in Natural Populations of N- and P-Limited Coastal Mesocosms, J. Phycol., 41, 1094–1098, https://doi.org/10.1111/j.1529-8817.2005.00153.x, 2005. a
Olofsson, M., Egardt, J., Singh, A., and Ploug, H.: Inorganic phosphorus enrichments in Baltic Sea water have large effects on growth, carbon fixation, and N2 fixation by Nodularia spumigena, Aquat. Microb. Ecol., 77, 111–123, https://doi.org/10.3354/ame01795, 2016. a
Orchard, E. D., Ammerman, J. W., Lomas, M. W., and Dyhrman, S. T.: Dissolved inorganic and organic phosphorus uptake in Trichodesmium and the microbial community: The importance of phosphorus ester in the Sargasso Sea, Limnol. Oceanogr., 55, 1390–1399, https://doi.org/10.4319/lo.2010.55.3.1390, 2010. a
Orcutt, K. M., Gundersen, K., and Ammerman, J. W.: Intense ectoenzyme activities associated with Trichodesmium colonies in the Sargasso Sea, Mar. Ecol. Prog. Ser., 478, 101–113, https://doi.org/10.3354/meps10153, 2013. a
Paerl, H. W.: Nuisance Phytoplankton Blooms in Coastal, Estuarine and Inland Waters, Limnol. Oceanogr., 33, 823–847, https://doi.org/10.4319/lo.1988.33.4part2.0823, 1988. a
Paerl, H. W. and Huisman, J.: Climate change: a catalyst for global expansion of harmful cyanobacterial blooms, Env. Microbiol. Rep., 1, 27–37, https://doi.org/10.1111/j.1758-2229.2008.00004.x, 2009. a, b
Paerl, H. W. and Otten, T. G.: Duelling CyanoHABS: unravelling the environmental drivers controlling dominance and succession among diazotrophic and non-N2-fixing harmful cyanobacteria, Environ. Microbiol., 18, 316–424, https://doi.org/10.1111/1462-2920.13035, 2016. a
Paerl, H. W., Valdes, L. M., Peierls, B. L., Adolf, J. E., Harding, J., and Lawrence, W.: Anthropogenic and climatic influences on the eutrophication of large estuarine ecosystems, Limnol. Oceanogr., 51, 448–462, https://doi.org/10.4319/lo.2006.51.1_part_2.0448, 2006. a
Paerl, H. W., Hall, N. S., and Calandrino, E. S.: Controlling harmful cyanobacterial blooms in a world experiencing anthropogenic and climatic-induced change, Sci. Total Environ., 409, 1739–1745, https://doi.org/10.1016/j.scitotenv.2011.02.001, 2011. a
Pechar, L.: Photosynthesis of Natural Populations of Aphanizomenon flos-aquae: Some Ecological Implications,
Int. Rev. Ges. Hydrobio., 72, 599–606, https://doi.org/10.1002/iroh.19870720506, 1987. a
Petersen, W., Colijn, F., Gorringe, P., Kaitala, S., Karlson, B., King, A., Lips, U., Ntoumas, M., Seppälä, J., Sørensen, K., Petihakis, G., de la Villéon, L. P., and Wehde, H.: Ferryboxes within Europe: state-of-the-art and integration in the european ocean observation system (EOOS), in: Operational oceanography serving sustainable marine development, EuroGOOS, Bergen, Norway, 63–70, 2018. a
Ploug, H., Adam, B., Musat, N., Kalvelage, T., Lavik, G., Wolf-Gladrow, D., and Kuypers, M. M.: Carbon, nitrogen and O2 fluxes associated with the cyanobacterium Nodularia spumigena in the Baltic Sea, ISME J., 5, 1549–1558, https://doi.org/10.1038/ismej.2011.20, 2011. a
Preuss, R. and von Toussaint, U.: Uncertainty quantification in ion-solid interaction simulations, Nucl. Instrum. Meth. B, 393, 26–28, https://doi.org/10.1016/j.nimb.2016.10.033, 2017. a
Prussin, A. J., Garcia, E. B., and Marr, L. C.: Total Concentrations of Virus and Bacteria in Indoor and Outdoor
Air, Environ. Sci. Tech. Let., 2, 84–88, https://doi.org/10.1021/acs.estlett.5b00050, 2015. a
Raateoja, M., Kuosa, H., and Hällfors, S.: Fate of excess phosphorus in the Baltic Sea: A real driving force for cyanobacterial blooms?, J. Sea Res., 65, 315–321, https://doi.org/10.1016/j.seares.2011.01.004, 2011. a
Redfield, A. C.: The biological control of chemical factors in the environment, Am. Sci., 46 pp., 230A-221, 1958. a
Reinart, A. and Kutser, T.: Comparison of different satellite sensors in detecting cyanobacterial bloom events in the Baltic
Sea, Remote Sens. Environ., 102, 74–85, https://doi.org/10.1016/j.rse.2006.02.013, 2006. a
Reissmann, J. H., Burchard, H., Feistel, R., Hagen, E., Lass, H. U., Mohrholz, V., Nusch, G., Umlauf, L., and Wieczorek, G.: Vertical mixing in the Baltic Sea and consequences for eutrophication – A review,
Prog. Oceanogr., 82, 47–80, https://doi.org/10.1016/j.pocean.2007.10.004, 2009. a
Rengefors, K., Gustafsson, S., and Stȧhl-Delbanco, A.: Factors regulating the recruitment of cyanobacterial and eukaryotic phytoplankton from littoral and profundal sediments, Aquat. Microb. Ecol., 36, 213–226, https://doi.org/10.3354/ame036213, 2004. a
Reynolds, C. S. and Walsby, A. E.: Water-blooms, Biol. Rev., 50, 437–481, https://doi.org/10.1111/j.1469-185X.1975.tb01060.x, 1975. a
Reynolds, C. S. and Rodgers, M. W.: Cell- and colony-division in Eudorina (Chlorophyta: Volvocales) and some ecological implications, Brit. Phycol. J., 18, 111–119, https://doi.org/10.1080/00071618300650151, 1983. a
Rhee, G.-Y. and Lederman, T. C.: Effects of nitrogen sources on P-limited growth of Anabaena flosaquae, J. Phycol., 19, 179–185, https://doi.org/10.1111/j.0022-3646.1983.00179.x, 1983. a, b, c
Riemann, L., Holmfeldt, K., and Titelman, J.: Importance of viral lysis and dissolved DNA for bacterioplankton activity in a P-limited estuary, Northern Baltic Sea, Microbial Ecol., 57, 286–294, https://doi.org/10.1007/s00248-008-9429-0, 2009. a
Rivkin, R. B. and Swift, E.: Phosphate uptake by the oceanic dinoflagellate Pyrocystis noctiluca, J. Phycol., 18, 113–120, https://doi.org/10.1111/j.1529-8817.1982.tb03164.x, 1982. a
Robarts, R. D. and Zohary, T.: Temperature effects on photosynthetic capacity, respiration, and growth rates of bloom-forming cyanobacteria,
New Zeal. J. Mar. Fresh., 21, 391–399, https://doi.org/10.1080/00288330.1987.9516235, 1987. a, b, c, d
Rohwer, F. and Youle, M.: Coral Reefs in the Microbial Seas, Plaid Press, 204 pp., ISBN 0982701209, 2010. a
Roleda, M. Y., Mohlin, M., Pattanaik, B., and Wulff, A.: Photosynthetic response of Nodularia spumigenato UV and photosynthetically active radiation depends on nutrient (N and P) availability, FEMS Microbiol. Ecol., 66, 230–242, https://doi.org/10.1111/j.1574-6941.2008.00572.x, 2008. a, b
Rother, J. A. and Fay, P.: Sporulation and the development of planktonic blue-green algae in two Salopian meres, P. Roy. Soc. Lond. B Bio., 196, 317–332, https://doi.org/10.1098/rspb.1977.0043, 1977. a, b, c
Rücker, J., Tingwey, E. I., Wiedner, C., Anu, C. M., and Nixdorf, B.: Impact of the inoculum size on the population of Nostocales cyanobacteria in a temperate lake, J. Plankton Res., 31, 1151–1159, https://doi.org/10.1093/plankt/fbp067, 2009. a
Saraiva, S., Meier, H. E. M., Andersson, H., Höglund, A., Dieterich, C., Gröger, M., Hordoir, R., and Eilola, K.: Uncertainties in Projections of the Baltic Sea Ecosystem Driven by an Ensemble of Global Climate Models, Front. Earth Sci., 6, 1–18, https://doi.org/10.3389/feart.2018.00244, 2019. a, b
Sarnelle, O.: Initial conditions mediate the interaction between Daphnia and bloom-forming cyanobacteria, Limnol. Oceanogr., 52, 2120–2127, https://doi.org/10.4319/lo.2007.52.5.2120, 2007. a
Savchuk, O. P.: Nutrient biogeochemical cycles in the Gulf of Riga: scaling up field studies with a mathematical model, J. Marine Syst., 32, 253–280, https://doi.org/10.1016/S0924-7963(02)00039-8, 2002. a, b
Savchuk, O. P.: Large-Scale Nutrient Dynamics in the Baltic Sea, 1970–2016, Front. Mar. Sci., 5, 1–20, https://doi.org/10.3389/fmars.2018.00095, 2018. a
Savchuk, O. P., Gustafsson, B. G., and Müller-Karulis, B. BALTSEM: A marine model for decision support within the Baltic Sea Region,
Baltic Nest Institute Technical Report, 7, 1–55, 2012. a
Schartau, M., Wallhead, P., Hemmings, J., Löptien, U., Kriest, I., Krishna, S., Ward, B. A., Slawig, T., and Oschlies, A.: Reviews and syntheses: parameter identification in marine planktonic ecosystem modelling, Biogeosciences, 14, 1647–1701, https://doi.org/10.5194/bg-14-1647-2017, 2017. a
Schernewski, G. and Neumann, T.: The trophic state of the Baltic Sea a century ago: a model simulation study, J. Marine Syst., 53, 109–124, https://doi.org/10.1016/j.jmarsys.2004.03.007, 2005. a
Schoffelen, N. J., Mohr, W., Ferdelman, T. G., Littmann, S., Duerschlag, J., Zubkov, M. V., Ploug, H., and Kuypers, M. M. M.: Single-cell imaging of phosphorus uptake shows that key harmful algae rely on different phosphorus sources for growth, Sci. Rep.-UK, 8, 17182, https://doi.org/10.1038/s41598-018-35310-w, 2018. a, b
Schrum, C. and Backhaus, J. O.: Sensitivity of atmosphere – ocean heat exchange and heat content in the North Sea and the Baltic Sea, Tellus A, 51, 526–549, https://doi.org/10.1034/j.1600-0870.1992.00006.x, 1999. a
Sellner, K. G.: Physiology, ecology, and toxic properties of marine cyanobacteria blooms, Limnol. Oceanogr., 42, 1089–1104, https://doi.org/10.4319/lo.1997.42.5_part_2.1089, 1997. a, b, c, d
Sellner, K. G. and Olli, K.: Copepod interactions with toxic and non-toxic cyanobacteria from the Gulf of Finland, Phycologia, 35, 177–182, https://doi.org/10.2216/i0031-8884-35-6S-177.1, 1996. a
Sellner, K. G., Olson, M. M., and Kononen, K.: Copepod grazing in a summer cyanobacteria bloom in the Gulf of Finland, Hydrobiologia, 292–293, 249–254, https://doi.org/10.1007/978-94-017-1347-4_33, 1994. a
Shimoda, Y. and Arhonditsis, G. B.: Phytoplankton functional type modeling: Running before we can walk? A critical evaluation of the current state of knowledge, Ecol. Model., 320, 29–43, https://doi.org/10.1016/j.ecolmodel.2015.08.029, 2015. a
Short, F. T. and Wyllie-Echeverria, S.: Natural and human-induced disturbances of seagrasses, Environ. Conserv., 23, 17–27, https://doi.org/10.1017/S0376892900038212, 1996. a
Sigee, D. C., Selwyn, A., Gallois, P., and Dean, A. P.: Patterns of cell death in freshwater colonial cyanobacteria during the late summer bloom, Phycologia, 46, 284–292, https://doi.org/10.2216/06-69.1, 2007. a, b, c
Silveira, C. B. and Rohwer, F. L.: Piggyback-the-Winner in host-associated microbial communities, NPJ Biofilms Microbiomes, 2, 16010, https://doi.org/10.1038/npjbiofilms.2016.10, 2016. a
Simis, S. G. H., Tijdens, M., Hoogveld, H. L., and Gons, H. J.: Optical changes associated with cyanobacterial bloom termination by viral lysis, J. Plankton Res., 27, 937–949, https://doi.org/10.1093/plankt/fbi068, 2005. a
Sipiä, V. O., Kankaanpäa, H., T., Flinkman, J., Lahti, K., and Meriluoto, J. A. O.: Time-Dependent Accumulation of Cyanobacterial Hepatotoxins in Flunders (Platichthys flesus) and Mussels (Mytilus edulis) from the Northern Baltic Sea, Environ. Toxicol., 16, 330–336, https://doi.org/10.1002/tox.1040, 2001. a
Śliwińska-Wilczewska, S., Cieszyńska, A., Konik, M., Maculewicz, J., and Latala, A.: Environmental drivers of bloom-forming cyanobacteria in the Baltic Sea: Effects of salinity, temperature, and irradiance,
Estuar. Coast. Shelf S., 219, 139–150, https://doi.org/10.1016/j.ecss.2019.01.016, 2019. a, b, c
Smirnov, N. N.: Chapter 4 – Nutrition, in: Physiology of the Cladocera, 2 edn., Academic Press, 39–88, https://doi.org/10.1016/B978-0-12-805194-8.00004-0, 2017. a
Snoeijs-Leijonmalm, P., Schubert, H., and Radziejewska, T.: Biological Oceanography of the Baltic Sea, Springer, Dordrecht, Netherlands, 714 pp., ISBN-109402413170, 2017. a
Sobol, I. M.: Global sensitivity indices for nonlinear mathematical models and their Monte Carlo estimates, Math. Comput. Simulat., 55, 271–280, https://doi.org/10.1016/S0378-4754(00)00270-6, 2001. a, b
Sohm, J. A. and Capone, D. G.: Phosphorus dynamics of the tropical and subtropical north Atlantic: Trichodesmium spp. versus bulk plankton, Mar. Ecol. Prog. Ser., 317, 21–28, https://doi.org/10.3354/meps317021, 2006. a
Sohm, J. A., Mahaffey, C., and Capone, D. G.: Assessment of relative phosphorus limitation of Trichodesmium spp. in the North Pacific, North Atlantic, and the north coast of Australia, Limnol. Oceanogr., 53, 2495–2502, https://doi.org/10.4319/lo.2008.53.6.2495, 2008. a
Sohm, J. A., Webb, E. A., and Capone, D. G.: Emerging patterns of marine nitrogen fixation, Nat. Rev. Microbiol., 9, 499–508, https://doi.org/10.1038/nrmicro2594, 2011. a
Solis, M., Pawlik-Skowrońska, B., Adamczuk, M., and Kalinowska, R.: Dynamics of small-sized Cladocera and their algal diet in lake with toxic cyanobacterial water blooms, Ann. Limnol.-Int. J. Lim., 54, 6, https://doi.org/10.1051/limn/2018001, 2018. a
Sommer, U.: The role of r- and K-selection in the succession of phytoplankton in Lake Constance, Acta Oecol., 2, 327–342, https://doi.org/10.1007/BF00027228, 1981. a, b, c, d
Sousa, W., Attayde, J. L., Rocha, E. D. S., and Eskinazi-Sant'Anna, E. M.: The response of zooplankton assemblages to variations in the water quality of four man-made lakes in semi-arid north-eastern Brazil, J. Plankton Res., 30, 699–708, https://doi.org/10.1093/plankt/fbn032, 2008. a
Stal, L. J., Albertano, P., Bergman, B., Bröckel, K. V., Gallon, J. R., Hayes, P. K., Sivonen, K., and Walsby, A. E.: BASIC: Baltic Sea cyanobacteria, an investigation of the structure and dynamics of water blooms of cyanobacteria in the Baltic Sea – responses to a changing
environment, Cont. Shelf Res., 23, 1695–1714, https://doi.org/10.1016/j.csr.2003.06.001, 2003. a, b
Stigebrandt, A., Rahm, L., Viktorsson, L., Ödalen, M., Hall, P. O. J., and Liljebladh, B.: A New Phosphorus Paradigm for the Baltic Proper, AMBIO, 43, 634–643, https://doi.org/10.1007/s13280-013-0441-3, 2014. a
Suikkanen, S., Kaartokallio, H., Hällfors, S., Huttunen, M., and Laamanen, M.: Life cycle strategies of bloom-forming, filamentous cyanobacteria in the Baltic Sea,
Deep Sea Research Part II: Topical Studies in Oceanography, 57, 199–209, https://doi.org/10.1016/j.dsr2.2009.09.014, 2010. a, b, c, d, e
S̆ulc̆ius, S. and Holmfeldt, K.: Viruses of microorganisms in the Baltic Sea: current state of research and
perspectives, Mar. Biol. Res., 12, 115–124, https://doi.org/10.1080/17451000.2015.1118514, 2016. a, b, c
S̆ulc̆ius, S., Simoliunas, E., Staniulis, J., Koreiviene, J., Baltrusis, P., Meskys, R., and Paskauskas, R.: Characterization of a lytic cyanophage that infects the bloom – forming cyanobacterium Aphanizomenon flos-aquae, FEMS Microbiol. Ecol., 91, 1–7, https://doi.org/10.1093/femsec/fiu012, 2015. a
S̆ulc̆ius, S., Slavuckytė, K., Janus̆kaitė, M., and Pas̆kauskas, R.: Establishment of axenic cultures from cyanobacterium Aphanizomenon flos-aquae akinetes by micromanipulation and chemical treatment, Algal Res., 23, 43–50, https://doi.org/10.1016/j.algal.2017.01.006, 2017a. a
S̆ulc̆ius, S., Slavuckytė, K., and Pas̆kauskas, R.: The predation paradox: Synergistic and antagonistic interactions between grazing by crustacean predator and infection by cyanophages promotes bloom formation in filamentous cyanobacteria, Limnol. Oceanogr., 62, 2189–2199, https://doi.org/10.1002/lno.10559, 2017b. a
Suttle, C. A.: Viruses in the sea, Nature, 437, 356–361, https://doi.org/10.1038/nature04160, 2005. a, b
Tang, E. P. Y., Tremblay, R., and Vincent, W. F.: Cyanobacterial dominance of polar freshwater ecosystems: are high-latitude mat-formers adapted to low temperature?, J. Phycol., 33, 171–181, https://doi.org/10.1111/j.0022-3646.1997.00171.x, 1997. a, b, c, d
Tang, H., Vanderploeg, H. A., Johengen, T. H., and Liebig, J. R.: Quagga musel (Dreissena rostriformis bugensis) selective feeding of phytoplankton in Saginaw Bay, J. Great Lakes Res., 40, 83–94, https://doi.org/10.1016/j.jglr.2013.11.011, 2014. a
Taranu, Z. E., Zurawell, R. W., Pick, F., and Gregory-Eaves, I.: Predicting cyanobacterial dynamics in the face of global change: the importance of scale and environmental context, Global Change Biol., 18, 3477–3490, https://doi.org/10.1111/gcb.12015, 2012. a
Thomas, R. H. and Walsby, A. E.: The Effect of Temperature on Recovery of Buoyancy by Microcystis, J. Gen. Microbiol., 132, 1665–1672, https://doi.org/10.1099/00221287-132-6-1665, 1986. a
Tucker, S. and Pollard, P.: Identification of cyanophage Ma-LBP and infection of the cyanobacterium Microcystis aeruginosa from an Australian subtropical lake by the virus, Appl. Environ. Microb., 71, 629–635, https://doi.org/10.1128/AEM.71.2.629-635.2005, 2005. a, b
Unger, J., Endres, S., Wannicke, N., Engel, A., Voss, M., Nausch, G., and Nausch, M.: Response of Nodularia spumigena to pCO2 – Part 3: Turnover of phosphorus compounds, Biogeosciences, 10, 1483–1499, https://doi.org/10.5194/bg-10-1483-2013, 2013. a, b
Urrutia-Cordero, P., Ekvall, M. K., and Hansson, L.-A.: Controlling Harmful Cyanobacteria: Taxa-Specific Responses of Cyanobacteria to Grazing by Large-Bodied Daphnia in a Biomanipulation Scenario, PloS One, 11, e0153032, https://doi.org/10.1371/journal.pone.0153032, 2016. a
Üveges, V., Tapolczai, K., Krienitz, L., and Padisák, J.: Photosynthetic characteristics and physiological plasticity of an Aphanizomenon flos-aquae (Cyanobacteria, Nostocaceae) winter bloom in a deep oligo-mesotrophic lake (Lake Stechlin, Germany), Hydrobiologia, 698, 263–272, https://doi.org/10.1007/s10750-012-1103-3, 2012. a, b, c
Vahtera, E., Laanemets, J., Pavelson, J., Huttunen, M., and Kononen, K.: Effect of upwelling on the pelagic environment and bloom-forming cyanobacteria in the western Gulf of Finland, Baltic Sea, J. Marine Syst., 58, 67–82, https://doi.org/10.1016/j.jmarsys.2005.07.001, 2005. a, b
Vahtera, E., Conley, D. J., Gustafsson, B. G., Kuosa, H., Pitkänen, H., Savchuk, O. P., Tamminen, T., Viitasalo, M., Voss, M., Wasmund, N., and Wulff, F.: Internal Ecosystem Feedbacks Enhance Nitrogen-fixing Cyanobacteria Blooms and Complicate Management in the Baltic Sea, AMBIO, 36, 186–194, https://doi.org/10.1579/0044-7447(2007)36[186:IEFENC]2.0.CO;2, 2007a. a
Vahtera, E., Laamanen, M., and Rintala, J.-M.: Use of different phosphorus sources by the bloom-forming cyanobacteria Aphanizomenon flos-aquae and Nodularia spumigena, Aquat. Microb. Ecol., 46, 225–237, https://doi.org/10.3354/ame046225, 2007b. a, b, c
Visser, P. M., Ibelings, B. W., and Mur, L. R.: Autumnal sedimentation of Microcystis spp. as result of an increase in carbohydrate ballast at reduced temperature, J. Plankton Res., 17, 919–933, https://doi.org/10.1093/plankt/17.5.919, 1995. a
Walsby, A. E. and Booker, M. J.: Changes in buoyancy of a planktonic blue-green alga in response to light intensity, Brit. Phycol. J., 15, 311–319, https://doi.org/10.1080/00071618000650321, 1980. a, b, c
Walsby, A. E., Hayes, P. K., Boje, R., and Stal, L. J.: The selective advantage of buoyancy provided by gas vesicles for planktonic cyanobacteria in the Baltic Sea, New Phytol., 136, 407–417, https://doi.org/10.1046/j.1469-8137.1997.00754.x, 1997. a
Walve, J. and Larsson, U.: Blooms of Baltic Sea Aphanizomenon sp. (Cyanobacteria) collapse after internal phosphorus depletion, Aquat. Microb. Ecol., 49, 57–69, https://doi.org/10.3354/ame01130, 2007. a, b
Walve, J. and Larsson, U.: Seasonal changes in Baltic Sea seston stoichiometry: the influence of diazotrophic cyanobacteria, Mar. Ecol. Prog. Ser., 407, 13–25, https://doi.org/10.3354/meps08551, 2010. a
Wang, Z.-H., Liang, Y., and Kang, W.: Utilization of dissolved organic phosphorus by different groups of phytoplankton taxa, Harmful Algae, 12, 113–118, https://doi.org/10.1016/j.hal.2011.09.005, 2011. a
Ward, E. J. and Shumway, S. S.: Separating the grain from the chaff: particle selection in suspension- and deposit-feeding
bivalves, J. Exp. Mar. Biol. Ecol., 300, 83–130, https://doi.org/10.1016/j.jembe.2004.03.002, 2004. a, b
Wasmund, N.: Occurrence of cyanobacterial blooms in the Baltic Sea in relation to environmental conditions, Int. Rev. Ges. Hydrobio., 82, 169–184, https://doi.org/10.1002/iroh.19970820205, 1997. a
Wasmund, N., Nausch, G., Schneider, B., Nagel, K., and Voss, M.: Comparison of nitrogen fixation rates determined with different methods: a study in the Baltic Proper, Mar. Ecol. Prog. Ser., 297, 23–31, https://doi.org/10.3354/meps297023, 2005. a, b
Wasmund, N., Dutz, J., Kremp, A., and Zettler, M. L.: Biological Assessment of the Baltic Sea 2018, Meereswissenschaftliche Berichte, Warnemuende, 112, 1–100, https://doi.org/10.12754/msr-2019-0112, 2019.
a
Weinbauer, M. G. and Rassoulzadegan, F.: Are viruses driving microbial diversification and diversity?, Environ. Microbiol., 6, 1–11, https://doi.org/10.1046/j.1462-2920.2003.00539.x, 2003. a
Weinbauer, M. G., Brettar, I., and Höfle, M. G.: Lysogeny and virus-induced mortality of bacterioplankton in surface, deep, and anoxic marine waters, Limnol. Oceanogr., 48, 1457–1465, https://doi.org/10.4319/lo.2003.48.4.1457, 2003. a
Werner, M., Michalek, M., and Solvita, S.: Abundance and distribution of the Zebra mussel (Dreissena Polymorpha), available at: https://helcom.fi/wp-content/uploads/2020/06/BSEFS-Abundance-and-distribution-of-the-Zebra-mussel.pdf (last access: 22 March 2021), 2012. a
White, J. D. and Sarnelle, O.: Size-structured vulnerability of the colonial cyanobacterium, Microcystis aeruginosa,to grazing by zebra mussels (Dreissena Polymorpha), Freshwater Biol., 59, 514–525, https://doi.org/10.1111/fwb.12282, 2014. a
Whitton, B. A., Grainger, S. L. J., Hawley, G. R. W., and Simon, J. W.: Cell-bound and extracellular phosphatase activities of cyanobacterial isolates, Microb. Ecol., 21, 85–98, https://doi.org/10.1007/bf02539146, 1991. a
Wommack, K. E., and Colwell, R. R.: Virioplankton: Viruses in aquatic Ecosystems, Mircobiology and Molecular Biology Review, 64, 69–114, https://doi.org/10.1128/MMBR.64.1.69-114.2000, 2000. a
Worden, A. Z., Follows, M. J., Giovannoni, S. J., Wilken, S., Zimmerman, A. E., and Keeling, P. J.: Environmental science. Rethinking the marine carbon cycle: factoring in the multifarious lifestyles of microbes, Science, 347, 1257594, https://doi.org/10.1126/science.1257594, 2015. a
Yamamoto, T., Suzuki, M., Kim, K., and Asaoka, S.: Growth and uptake kinetics of phosphate by benthic microalga Nitzschia sp. isolated from Hiroshima Bay, Japan, Phycol. Res., 60, 223–228, https://doi.org/10.1111/j.1440-1835.2012.00653.x, 2012. a, b, c, d
Yamamoto, Y., Kouchiwa, T., Hodoki, Y., Hotta, K., Uchida, H., and Harada, K.-I.: Distribution and identification of actinomycetes lysing cyanobacteria in a eutrophic lake, J. Appl. Phycol., 10, 391–397, https://doi.org/10.1023/A:1008077414808, 1998. a
Zeigler Allen, L., McCrow, J. P., Ininbergs, K., Dupont, C. L., Badger, J. H., Hoffman, J. M., Ekman, M., Allen, A. E., Bergman, B., and Venter, J. C.: The Baltic Sea Virome: Diversity and Transcriptional Activity of DNA and RNA Viruses, mSystems, 2, e00125-16, https://doi.org/10.1128/mSystems.00125-16, 2017. a
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.
Cyanobacteria blooms can strongly aggravate eutrophication problems of water bodies. Their...
Altmetrics
Final-revised paper
Preprint