Articles | Volume 10, issue 2
https://doi.org/10.5194/esd-10-287-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/esd-10-287-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Tidal impacts on primary production in the North Sea
Changjin Zhao
CORRESPONDING AUTHOR
Helmholtz Centre Geesthacht, Institute of Coastal Research,
Max-Planck-Str. 1, 21502 Geesthacht, Germany
Ute Daewel
Helmholtz Centre Geesthacht, Institute of Coastal Research,
Max-Planck-Str. 1, 21502 Geesthacht, Germany
Corinna Schrum
Helmholtz Centre Geesthacht, Institute of Coastal Research,
Max-Planck-Str. 1, 21502 Geesthacht, Germany
Related authors
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Hoa T. T. Nguyen, Ute Daewel, Neil Banas, and Corinna Schrum
EGUsphere, https://doi.org/10.5194/egusphere-2024-2710, https://doi.org/10.5194/egusphere-2024-2710, 2024
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Parameterisation is key in modeling to reproduce observations well but is often done manually. This study presents a Particle Swarm Optimizer-based toolbox for marine ecosystem models, compatible with the Framework for Aquatic Biogeochemical Models, thus enhancing its reusability. Applied to the Sylt ecosystem, the toolbox effectively (1) identified multiple parameter sets that matched observations well, thus providing different insights into ecosystem dynamics, (2) optimized model complexity.
Lucas Porz, Wenyan Zhang, Nils Christiansen, Jan Kossack, Ute Daewel, and Corinna Schrum
Biogeosciences, 21, 2547–2570, https://doi.org/10.5194/bg-21-2547-2024, https://doi.org/10.5194/bg-21-2547-2024, 2024
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Seafloor sediments store a large amount of carbon, helping to naturally regulate Earth's climate. If disturbed, some sediment particles can turn into CO2, but this effect is not well understood. Using computer simulations, we found that bottom-contacting fishing gears release about 1 million tons of CO2 per year in the North Sea, one of the most heavily fished regions globally. We show how protecting certain areas could reduce these emissions while also benefitting seafloor-living animals.
Philipp Heinrich, Stefan Hagemann, Ralf Weisse, Corinna Schrum, Ute Daewel, and Lidia Gaslikova
Nat. Hazards Earth Syst. Sci., 23, 1967–1985, https://doi.org/10.5194/nhess-23-1967-2023, https://doi.org/10.5194/nhess-23-1967-2023, 2023
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High seawater levels co-occurring with high river discharges have the potential to cause destructive flooding. For the past decades, the number of such compound events was larger than expected by pure chance for most of the west-facing coasts in Europe. Additionally rivers with smaller catchments showed higher numbers. In most cases, such events were associated with a large-scale weather pattern characterized by westerly winds and strong rainfall.
Johannes Bieser, David J. Amptmeijer, Ute Daewel, Joachim Kuss, Anne L. Soerensen, and Corinna Schrum
Geosci. Model Dev., 16, 2649–2688, https://doi.org/10.5194/gmd-16-2649-2023, https://doi.org/10.5194/gmd-16-2649-2023, 2023
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MERCY is a 3D model to study mercury (Hg) cycling in the ocean. Hg is a highly harmful pollutant regulated by the UN Minamata Convention on Mercury due to widespread human emissions. These emissions eventually reach the oceans, where Hg transforms into the even more toxic and bioaccumulative pollutant methylmercury. MERCY predicts the fate of Hg in the ocean and its buildup in the food chain. It is the first model to consider Hg accumulation in fish, a major source of Hg exposure for humans.
Veli Çağlar Yumruktepe, Annette Samuelsen, and Ute Daewel
Geosci. Model Dev., 15, 3901–3921, https://doi.org/10.5194/gmd-15-3901-2022, https://doi.org/10.5194/gmd-15-3901-2022, 2022
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We describe the coupled bio-physical model ECOSMO II(CHL), which is used for regional configurations for the North Atlantic and the Arctic hind-casting and operational purposes. The model is consistent with the large-scale climatological nutrient settings and is capable of representing regional and seasonal changes, and model primary production agrees with previous measurements. For the users of this model, this paper provides the underlying science, model evaluation and its development.
Onur Kerimoglu, Yoana G. Voynova, Fatemeh Chegini, Holger Brix, Ulrich Callies, Richard Hofmeister, Knut Klingbeil, Corinna Schrum, and Justus E. E. van Beusekom
Biogeosciences, 17, 5097–5127, https://doi.org/10.5194/bg-17-5097-2020, https://doi.org/10.5194/bg-17-5097-2020, 2020
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In this study, using extensive field observations and a numerical model, we analyzed the physical and biogeochemical structure of a coastal system following an extreme flood event. Our results suggest that a number of anomalous observations were driven by a co-occurrence of peculiar meteorological conditions and increased riverine discharges. Our results call for attention to the combined effects of hydrological and meteorological extremes that are anticipated to increase in frequency.
Laurie M. Charrieau, Karl Ljung, Frederik Schenk, Ute Daewel, Emma Kritzberg, and Helena L. Filipsson
Biogeosciences, 16, 3835–3852, https://doi.org/10.5194/bg-16-3835-2019, https://doi.org/10.5194/bg-16-3835-2019, 2019
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We reconstructed environmental changes in the Öresund during the last 200 years, using foraminifera (microfossils), sediment, and climate data. Five zones were identified, reflecting oxygen, salinity, food content, and pollution levels for each period. The largest changes occurred ~ 1950, towards stronger currents. The foraminifera responded quickly (< 10 years) to the changes. Moreover, they did not rebound when the system returned to the previous pattern, but displayed a new equilibrium state.
Johannes Pein, Annika Eisele, Richard Hofmeister, Tina Sanders, Ute Daewel, Emil V. Stanev, Justus van Beusekom, Joanna Staneva, and Corinna Schrum
Biogeosciences Discuss., https://doi.org/10.5194/bg-2019-265, https://doi.org/10.5194/bg-2019-265, 2019
Revised manuscript not accepted
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The Elbe estuary is subject to vigorous tidal forcing from the sea side and considerable biological inputs from the land side. Our 3D numerical coupled physical-biogeochemical integrates these forcing signals and provides highly realistic hindcasts of the associated dynamics. Model simulations show that the freshwater part of Elbe estuary is inhabited by plankton. According to simulations these organism play a key role in converting organic inputs into nitrate, the major inorganic nutrient.
Ute Daewel, Corinna Schrum, and Jed I. Macdonald
Geosci. Model Dev., 12, 1765–1789, https://doi.org/10.5194/gmd-12-1765-2019, https://doi.org/10.5194/gmd-12-1765-2019, 2019
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Here we propose a novel modelling approach that includes an extended food web in a functional-group-type marine ecosystem model (ECOSMO E2E) by formulating new groups for macrobenthos and fish. This enables the estimation of the dynamics of the higher-trophic-level production potential and constitutes a more consistent closure term for the lower-trophic-level ecosystem. Thus, the model allows for the study of the control mechanisms for marine ecosystems at a high spatial and temporal resolution.
Ute Daewel and Corinna Schrum
Earth Syst. Dynam., 8, 801–815, https://doi.org/10.5194/esd-8-801-2017, https://doi.org/10.5194/esd-8-801-2017, 2017
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Processes behind observed long-term variations in marine ecosystems are difficult to be deduced from in situ observations only. By statistically analysing a 61-year model simulation for the North Sea and Baltic Sea and additional model scenarios, we identified major modes of variability in the environmental variables and associated those with changes in primary production. We found that the dominant impact on changes in ecosystem productivity was introduced by modulations of the wind fields.
Related subject area
Earth system interactions with the biosphere: ecosystems
Opening Pandora's box: reducing global circulation model uncertainty in Australian simulations of the carbon cycle
Persistent La Niñas drive joint soybean harvest failures in North and South America
Spatiotemporal changes in the boreal forest in Siberia over the period 1985–2015 against the background of climate change
Downscaling of climate change scenarios for a high-resolution, site-specific assessment of drought stress risk for two viticultural regions with heterogeneous landscapes
Global climate change and the Baltic Sea ecosystem: direct and indirect effects on species, communities and ecosystem functioning
Widespread greening suggests increased dry-season plant water availability in the Rio Santa valley, Peruvian Andes
Spatiotemporal patterns and drivers of terrestrial dissolved organic carbon (DOC) leaching into the European river network
Impacts of compound hot–dry extremes on US soybean yields
Vulnerability of European ecosystems to two compound dry and hot summers in 2018 and 2019
Modelling forest ruin due to climate hazards
Exploring how groundwater buffers the influence of heatwaves on vegetation function during multi-year droughts
Diverging land-use projections cause large variability in their impacts on ecosystems and related indicators for ecosystem services
Impacts of land use change and elevated CO2 on the interannual variations and seasonal cycles of gross primary productivity in China
Investigating the applicability of emergent constraints
Global vegetation variability and its response to elevated CO2, global warming, and climate variability – a study using the offline SSiB4/TRIFFID model and satellite data
Steering operational synergies in terrestrial observation networks: opportunity for advancing Earth system dynamics modelling
Contrasting terrestrial carbon cycle responses to the 1997/98 and 2015/16 extreme El Niño events
Low-frequency variability in North Sea and Baltic Sea identified through simulations with the 3-D coupled physical–biogeochemical model ECOSMO
Vegetation–climate feedbacks modulate rainfall patterns in Africa under future climate change
Climate change increases riverine carbon outgassing, while export to the ocean remains uncertain
Spatial and temporal variations in plant water-use efficiency inferred from tree-ring, eddy covariance and atmospheric observations
Modelling short-term variability in carbon and water exchange in a temperate Scots pine forest
Establishment and maintenance of regulating ecosystem services in a dryland area of central Asia, illustrated using the Kökyar Protection Forest, Aksu, NW China, as an example
Do Himalayan treelines respond to recent climate change? An evaluation of sensitivity indicators
The impact of land cover generated by a dynamic vegetation model on climate over east Asia in present and possible future climate
Bimodality of woody cover and biomass across the precipitation gradient in West Africa
Critical impacts of global warming on land ecosystems
The influence of vegetation dynamics on anthropogenic climate change
Quantifying the thermodynamic entropy budget of the land surface: is this useful?
Lina Teckentrup, Martin G. De Kauwe, Gab Abramowitz, Andrew J. Pitman, Anna M. Ukkola, Sanaa Hobeichi, Bastien François, and Benjamin Smith
Earth Syst. Dynam., 14, 549–576, https://doi.org/10.5194/esd-14-549-2023, https://doi.org/10.5194/esd-14-549-2023, 2023
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Studies analyzing the impact of the future climate on ecosystems employ climate projections simulated by global circulation models. These climate projections display biases that translate into significant uncertainty in projections of the future carbon cycle. Here, we test different methods to constrain the uncertainty in simulations of the carbon cycle over Australia. We find that all methods reduce the bias in the steady-state carbon variables but that temporal properties do not improve.
Raed Hamed, Sem Vijverberg, Anne F. Van Loon, Jeroen Aerts, and Dim Coumou
Earth Syst. Dynam., 14, 255–272, https://doi.org/10.5194/esd-14-255-2023, https://doi.org/10.5194/esd-14-255-2023, 2023
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Spatially compounding soy harvest failures can have important global impacts. Using causal networks, we show that soy yields are predominately driven by summer soil moisture conditions in North and South America. Summer soil moisture is affected by antecedent soil moisture and by remote extra-tropical SST patterns in both hemispheres. Both of these soil moisture drivers are again influenced by ENSO. Our results highlight physical pathways by which ENSO can drive spatially compounding impacts.
Wenxue Fu, Lei Tian, Yu Tao, Mingyang Li, and Huadong Guo
Earth Syst. Dynam., 14, 223–239, https://doi.org/10.5194/esd-14-223-2023, https://doi.org/10.5194/esd-14-223-2023, 2023
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Climate change has been proven to be an indisputable fact and to be occurring at a faster rate in boreal forest areas. The results of this paper show that boreal forest coverage has shown an increasing trend in the past 3 decades, and the area of broad-leaved forests has increased more rapidly than that of coniferous forests. In addition, temperature rather than precipitation is the main climate factor that is driving change.
Marco Hofmann, Claudia Volosciuk, Martin Dubrovský, Douglas Maraun, and Hans R. Schultz
Earth Syst. Dynam., 13, 911–934, https://doi.org/10.5194/esd-13-911-2022, https://doi.org/10.5194/esd-13-911-2022, 2022
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We modelled water budget developments of viticultural growing regions on the spatial scale of individual vineyard plots with respect to landscape features like the available water capacity of the soils, slope, and aspect of the sites. We used an ensemble of climate simulations and focused on the occurrence of drought stress. The results show a high bandwidth of projected changes where the risk of potential drought stress becomes more apparent in steep-slope regions.
Markku Viitasalo and Erik Bonsdorff
Earth Syst. Dynam., 13, 711–747, https://doi.org/10.5194/esd-13-711-2022, https://doi.org/10.5194/esd-13-711-2022, 2022
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Climate change has multiple effects on Baltic Sea species, communities and ecosystem functioning. Effects on species distribution, eutrophication and trophic interactions are expected. We review these effects, identify knowledge gaps and draw conclusions based on recent (2010–2021) field, experimental and modelling research. An extensive summary table is compiled to highlight the multifaceted impacts of climate-change-driven processes in the Baltic Sea.
Lorenz Hänchen, Cornelia Klein, Fabien Maussion, Wolfgang Gurgiser, Pierluigi Calanca, and Georg Wohlfahrt
Earth Syst. Dynam., 13, 595–611, https://doi.org/10.5194/esd-13-595-2022, https://doi.org/10.5194/esd-13-595-2022, 2022
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To date, farmers' perceptions of hydrological changes do not match analysis of meteorological data. In contrast to rainfall data, we find greening of vegetation, indicating increased water availability in the past decades. The start of the season is highly variable, making farmers' perceptions comprehensible. We show that the El Niño–Southern Oscillation has complex effects on vegetation seasonality but does not drive the greening we observe. Improved onset forecasts could help local farmers.
Céline Gommet, Ronny Lauerwald, Philippe Ciais, Bertrand Guenet, Haicheng Zhang, and Pierre Regnier
Earth Syst. Dynam., 13, 393–418, https://doi.org/10.5194/esd-13-393-2022, https://doi.org/10.5194/esd-13-393-2022, 2022
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Dissolved organic carbon (DOC) leaching from soils into river networks is an important component of the land carbon (C) budget, but its spatiotemporal variation is not yet fully constrained. We use a land surface model to simulate the present-day land C budget at the European scale, including leaching of DOC from the soil. We found average leaching of 14.3 Tg C yr−1 (0.6 % of terrestrial net primary production) with seasonal variations. We determine runoff and temperature to be the main drivers.
Raed Hamed, Anne F. Van Loon, Jeroen Aerts, and Dim Coumou
Earth Syst. Dynam., 12, 1371–1391, https://doi.org/10.5194/esd-12-1371-2021, https://doi.org/10.5194/esd-12-1371-2021, 2021
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Soy yields in the US are affected by climate variability. We identify the main within-season climate drivers and highlight potential compound events and associated agricultural impacts. Our results show that soy yields are most negatively influenced by the combination of high temperature and low soil moisture during the summer crop reproductive period. Furthermore, we highlight the role of temperature and moisture coupling across the year in generating these hot–dry extremes and linked impacts.
Ana Bastos, René Orth, Markus Reichstein, Philippe Ciais, Nicolas Viovy, Sönke Zaehle, Peter Anthoni, Almut Arneth, Pierre Gentine, Emilie Joetzjer, Sebastian Lienert, Tammas Loughran, Patrick C. McGuire, Sungmin O, Julia Pongratz, and Stephen Sitch
Earth Syst. Dynam., 12, 1015–1035, https://doi.org/10.5194/esd-12-1015-2021, https://doi.org/10.5194/esd-12-1015-2021, 2021
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Temperate biomes in Europe are not prone to recurrent dry and hot conditions in summer. However, these conditions may become more frequent in the coming decades. Because stress conditions can leave legacies for many years, this may result in reduced ecosystem resilience under recurrent stress. We assess vegetation vulnerability to the hot and dry summers in 2018 and 2019 in Europe and find the important role of inter-annual legacy effects from 2018 in modulating the impacts of the 2019 event.
Pascal Yiou and Nicolas Viovy
Earth Syst. Dynam., 12, 997–1013, https://doi.org/10.5194/esd-12-997-2021, https://doi.org/10.5194/esd-12-997-2021, 2021
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This paper presents a model of tree ruin as a response to drought hazards. This model is inspired by a standard model of ruin in the insurance industry. We illustrate how ruin can occur in present-day conditions and the sensitivity of ruin and time to ruin to hazard statistical properties. We also show how tree strategies to cope with hazards can affect their long-term reserves and the probability of ruin.
Mengyuan Mu, Martin G. De Kauwe, Anna M. Ukkola, Andy J. Pitman, Weidong Guo, Sanaa Hobeichi, and Peter R. Briggs
Earth Syst. Dynam., 12, 919–938, https://doi.org/10.5194/esd-12-919-2021, https://doi.org/10.5194/esd-12-919-2021, 2021
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Groundwater can buffer the impacts of drought and heatwaves on ecosystems, which is often neglected in model studies. Using a land surface model with groundwater, we explained how groundwater sustains transpiration and eases heat pressure on plants in heatwaves during multi-year droughts. Our results showed the groundwater’s influences diminish as drought extends and are regulated by plant physiology. We suggest neglecting groundwater in models may overstate projected future heatwave intensity.
Anita D. Bayer, Richard Fuchs, Reinhard Mey, Andreas Krause, Peter H. Verburg, Peter Anthoni, and Almut Arneth
Earth Syst. Dynam., 12, 327–351, https://doi.org/10.5194/esd-12-327-2021, https://doi.org/10.5194/esd-12-327-2021, 2021
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Many projections of future land-use/-cover exist. We evaluate a number of these and determine the variability they cause in ecosystems and their services. We found that projections differ a lot in regional patterns, with some patterns being at least questionable in a historical context. Across ecosystem service indicators, resulting variability until 2040 was highest in crop production. Results emphasize that such variability should be acknowledged in assessments of future ecosystem provisions.
Binghao Jia, Xin Luo, Ximing Cai, Atul Jain, Deborah N. Huntzinger, Zhenghui Xie, Ning Zeng, Jiafu Mao, Xiaoying Shi, Akihiko Ito, Yaxing Wei, Hanqin Tian, Benjamin Poulter, Dan Hayes, and Kevin Schaefer
Earth Syst. Dynam., 11, 235–249, https://doi.org/10.5194/esd-11-235-2020, https://doi.org/10.5194/esd-11-235-2020, 2020
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We quantitatively examined the relative contributions of climate change, land
use and land cover change, and elevated CO2 to interannual variations and seasonal cycle amplitude of gross primary productivity (GPP) in China based on multi-model ensemble simulations. The contributions of major subregions to the temporal change in China's total GPP are also presented. This work may help us better understand GPP spatiotemporal patterns and their responses to regional changes and human activities.
Alexander J. Winkler, Ranga B. Myneni, and Victor Brovkin
Earth Syst. Dynam., 10, 501–523, https://doi.org/10.5194/esd-10-501-2019, https://doi.org/10.5194/esd-10-501-2019, 2019
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The concept of
emergent constraintsis a key method to reduce uncertainty in multi-model climate projections using historical simulations and observations. Here, we present an in-depth analysis of the applicability of the method and uncover possible limitations. Key limitations are a lack of comparability (temporal, spatial, and conceptual) between models and observations and the disagreement between models on system dynamics throughout different levels of atmospheric CO2 concentration.
Ye Liu, Yongkang Xue, Glen MacDonald, Peter Cox, and Zhengqiu Zhang
Earth Syst. Dynam., 10, 9–29, https://doi.org/10.5194/esd-10-9-2019, https://doi.org/10.5194/esd-10-9-2019, 2019
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Climate regime shift during the 1980s identified by abrupt change in temperature, precipitation, etc. had a substantial impact on the ecosystem at different scales. Our paper identifies the spatial and temporal characteristics of the effects of climate variability, global warming, and eCO2 on ecosystem trends before and after the shift. We found about 15 % (20 %) of the global land area had enhanced positive trend (trend sign reversed) during the 1980s due to climate regime shift.
Roland Baatz, Pamela L. Sullivan, Li Li, Samantha R. Weintraub, Henry W. Loescher, Michael Mirtl, Peter M. Groffman, Diana H. Wall, Michael Young, Tim White, Hang Wen, Steffen Zacharias, Ingolf Kühn, Jianwu Tang, Jérôme Gaillardet, Isabelle Braud, Alejandro N. Flores, Praveen Kumar, Henry Lin, Teamrat Ghezzehei, Julia Jones, Henry L. Gholz, Harry Vereecken, and Kris Van Looy
Earth Syst. Dynam., 9, 593–609, https://doi.org/10.5194/esd-9-593-2018, https://doi.org/10.5194/esd-9-593-2018, 2018
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Focusing on the usage of integrated models and in situ Earth observatory networks, three challenges are identified to advance understanding of ESD, in particular to strengthen links between biotic and abiotic, and above- and below-ground processes. We propose developing a model platform for interdisciplinary usage, to formalize current network infrastructure based on complementarities and operational synergies, and to extend the reanalysis concept to the ecosystem and critical zone.
Jun Wang, Ning Zeng, Meirong Wang, Fei Jiang, Hengmao Wang, and Ziqiang Jiang
Earth Syst. Dynam., 9, 1–14, https://doi.org/10.5194/esd-9-1-2018, https://doi.org/10.5194/esd-9-1-2018, 2018
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Behaviors of terrestrial ecosystems differ in different El Niños. We analyze terrestrial carbon cycle responses to two extreme El Niños (2015/16 and 1997/98), and find large differences. We find that global land–atmosphere carbon flux anomaly was about 2 times smaller in 2015/16 than in 1997/98 event, without the obvious lagged response. Then we illustrate the climatic and biological mechanisms of the different terrestrial carbon cycle responses in 2015/16 and 1997/98 El Niños regionally.
Ute Daewel and Corinna Schrum
Earth Syst. Dynam., 8, 801–815, https://doi.org/10.5194/esd-8-801-2017, https://doi.org/10.5194/esd-8-801-2017, 2017
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Processes behind observed long-term variations in marine ecosystems are difficult to be deduced from in situ observations only. By statistically analysing a 61-year model simulation for the North Sea and Baltic Sea and additional model scenarios, we identified major modes of variability in the environmental variables and associated those with changes in primary production. We found that the dominant impact on changes in ecosystem productivity was introduced by modulations of the wind fields.
Minchao Wu, Guy Schurgers, Markku Rummukainen, Benjamin Smith, Patrick Samuelsson, Christer Jansson, Joe Siltberg, and Wilhelm May
Earth Syst. Dynam., 7, 627–647, https://doi.org/10.5194/esd-7-627-2016, https://doi.org/10.5194/esd-7-627-2016, 2016
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On Earth, vegetation does not merely adapt to climate but also imposes significant influences on climate with both local and remote effects. In this study we evaluated the role of vegetation in African climate with a regional Earth system model. By the comparison between the experiments with and without dynamic vegetation changes, we found that vegetation can influence climate remotely, resulting in modulating rainfall patterns over Africa.
F. Langerwisch, A. Walz, A. Rammig, B. Tietjen, K. Thonicke, and W. Cramer
Earth Syst. Dynam., 7, 559–582, https://doi.org/10.5194/esd-7-559-2016, https://doi.org/10.5194/esd-7-559-2016, 2016
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In Amazonia, carbon fluxes are considerably influenced by annual flooding. We applied the newly developed model RivCM to several climate change scenarios to estimate potential changes in riverine carbon. We find that climate change causes substantial changes in riverine organic and inorganic carbon, as well as changes in carbon exported to the atmosphere and ocean. Such changes could have local and regional impacts on the carbon budget of the whole Amazon basin and parts of the Atlantic Ocean.
Stefan C. Dekker, Margriet Groenendijk, Ben B. B. Booth, Chris Huntingford, and Peter M. Cox
Earth Syst. Dynam., 7, 525–533, https://doi.org/10.5194/esd-7-525-2016, https://doi.org/10.5194/esd-7-525-2016, 2016
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Our analysis allows us to infer maps of changing plant water-use efficiency (WUE) for 1901–2010, using atmospheric observations of temperature, humidity and CO2. Our estimated increase in global WUE is consistent with the tree-ring and eddy covariance data, but much larger than the historical WUE increases simulated by Earth System Models (ESMs). We therefore conclude that the effects of increasing CO2 on plant WUE are significantly underestimated in the latest climate projections.
M. H. Vermeulen, B. J. Kruijt, T. Hickler, and P. Kabat
Earth Syst. Dynam., 6, 485–503, https://doi.org/10.5194/esd-6-485-2015, https://doi.org/10.5194/esd-6-485-2015, 2015
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We compared a process-based ecosystem model (LPJ-GUESS) with EC measurements to test whether observed interannual variability (IAV) in carbon and water fluxes can be reproduced because it is important to understand the driving mechanisms of IAV. We show that the model's mechanistic process representation for photosynthesis at low temperatures and during drought could be improved, but other process representations are still lacking in order to fully reproduce the observed IAV.
S. Missall, M. Welp, N. Thevs, A. Abliz, and Ü. Halik
Earth Syst. Dynam., 6, 359–373, https://doi.org/10.5194/esd-6-359-2015, https://doi.org/10.5194/esd-6-359-2015, 2015
U. Schickhoff, M. Bobrowski, J. Böhner, B. Bürzle, R. P. Chaudhary, L. Gerlitz, H. Heyken, J. Lange, M. Müller, T. Scholten, N. Schwab, and R. Wedegärtner
Earth Syst. Dynam., 6, 245–265, https://doi.org/10.5194/esd-6-245-2015, https://doi.org/10.5194/esd-6-245-2015, 2015
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Near-natural Himalayan treelines are usually krummholz treelines, which are relatively unresponsive to climate change. Intense recruitment of treeline trees suggests a great potential for future treeline advance. Competitive abilities of tree seedlings within krummholz thickets and dwarf scrub heaths will be a major source of variation in treeline dynamics. Tree growth-climate relationships show mature treeline trees to be responsive in particular to high pre-monsoon temperature trends.
M.-H. Cho, K.-O. Boo, G. M. Martin, J. Lee, and G.-H. Lim
Earth Syst. Dynam., 6, 147–160, https://doi.org/10.5194/esd-6-147-2015, https://doi.org/10.5194/esd-6-147-2015, 2015
Z. Yin, S. C. Dekker, B. J. J. M. van den Hurk, and H. A. Dijkstra
Earth Syst. Dynam., 5, 257–270, https://doi.org/10.5194/esd-5-257-2014, https://doi.org/10.5194/esd-5-257-2014, 2014
S. Ostberg, W. Lucht, S. Schaphoff, and D. Gerten
Earth Syst. Dynam., 4, 347–357, https://doi.org/10.5194/esd-4-347-2013, https://doi.org/10.5194/esd-4-347-2013, 2013
U. Port, V. Brovkin, and M. Claussen
Earth Syst. Dynam., 3, 233–243, https://doi.org/10.5194/esd-3-233-2012, https://doi.org/10.5194/esd-3-233-2012, 2012
N. A. Brunsell, S. J. Schymanski, and A. Kleidon
Earth Syst. Dynam., 2, 87–103, https://doi.org/10.5194/esd-2-87-2011, https://doi.org/10.5194/esd-2-87-2011, 2011
Cited articles
Allen, J. I., Siddorn, J. R., Blackford, J. C., and Gilbert, F. J.:
Turbulence as a control on the microbial loop in a temperate seasonally
stratified marine systems model, J. Sea Res., 52, 1–20,
https://doi.org/10.1016/j.seares.2003.09.004, 2004.
Arheimer, B., Dahné, J., Donnelly, C., Lindström, G., and
Strömqvist, J.: Water and nutrient simulations using the HYPE model for
Sweden vs. the Baltic Sea basin – Influence of input-data quality and scale,
Hydrol. Res., 43, 315–329, https://doi.org/10.2166/nh.2012.010, 2012.
Backhaus, J. O.: A three-dimensional model for the simulation of shelf sea
dynamics, Dtsch. Hydrogr. Zeitschrift, 38, 165–187, 1985.
Backhaus, J. O. and Hainbucher, D.: A finite difference general circulation
model for shelf seas and its application to low frequency variability on the
north european shelf, Elsev. Oceanogr. Serie., 45, 221–244,
https://doi.org/10.1016/S0422-9894(08)70450-1, 1987.
Bagniewski, W., Fennel, K., Perry, M. J., and D'Asaro, E. A.: Optimizing
models of the North Atlantic spring bloom using physical, chemical and
bio-optical observations from a Lagrangian float, Biogeosciences, 8,
1291–1307, https://doi.org/10.5194/bg-8-1291-2011, 2011.
Bakun, A.: Fronts and eddies as key structures in the habitat of marine fish
larvae: opportunity, adaptive response and competitive advantage, Sci. Mar.,
70, 105–122, https://doi.org/10.3989/scimar.2006.70s2105, 2006.
Balch, W. M. K.: An apparent lunar tidal cycle of phytoplankton blooming and
community succession in the Gulf of Maine, J. Exp. Mar. Biol. Ecol., 55,
65–77, https://doi.org/10.1016/0022-0981(81)90093-9, 1981.
Barthel, K., Daewel, U., Pushpadas, D., Schrum, C., Arthun, M., and Wehde,
H.: Resolving frontal structures: On the payoff using a less diffusive but
computationally more expensive advection scheme, Ocean Dynam., 62,
1457–1470, https://doi.org/10.1007/s10236-012-0578-9, 2012.
Belkin, I. M., Cornillon, P. C., and Sherman, K.: Fronts in Large Marine
Ecosystems, Prog. Oceanogr., 81, 223–236, https://doi.org/10.1016/j.pocean.2009.04.015,
2009.
Benoit-Bird, K. J., Cowles, T. J., and Wingard, C. E.: Edge gradients provide
evidence of ecological interactions in planktonic thin layers, Limnol.
Oceanogr., 54, 1382–1392, https://doi.org/10.4319/lo.2009.54.4.1382, 2009.
Blauw, A. N., Benincà, E., Laane, R. W. P. M., Greenwood, N., and
Huisman, J.: Dancing with the Tides: Fluctuations of Coastal Phytoplankton
Orchestrated by Different Oscillatory Modes of the Tidal Cycle, PLoS One, 7,
e49319, https://doi.org/10.1371/journal.pone.0049319, 2012.
Bowden, K. F. and Hamilton, P.: Some experiments with a numerical model of
circulation and mixing in a tidal estuary, Estuar. Coast. Mar. Sci., 3,
281–301, https://doi.org/10.1016/0302-3524(75)90029-8, 1975.
Bowers, D. G., Boudjelas, S., and Harker, G. E. L.: The distribution of fine
suspended sediments in the surface waters of the irish sea and its relation
to tidal stirring, Int. J. Remote Sens., 19, 2789–2805,
https://doi.org/10.1080/014311698214514, 1998.
Brettschneider, G.: Anwendung des hydrodynamisch-numerischen Verfahrens zur
Ermittlung der M2-Mitschwingungsgezeit der Nordsee, Univ. Hamburg, Hamburg,
1967.
Capuzzo, E., Painting, S. J., Forster, R. M., Greenwood, N., Stephens, D. T.,
and Mikkelsen, O. A.: Variability in the sub-surface light climate at
ecohydrodynamically distinct sites in the North Sea, Biogeochemistry, 113,
85–103, https://doi.org/10.1007/s10533-012-9772-6, 2013.
Cloern, J. E.: Tidal Stirring and Phytoplankton Bloom Dynamics in an Estuary,
J. Mar. Res., 49, 203–221, https://doi.org/10.1357/002224091784968611, 1991.
Conkright, M. E., Locarnini, R. A., Garcia, H. E., O'Brien, T. D., Boyer, T.
P., Stephens, C., and Antonov, J. I.: World Ocean Atlas 2001: Objective
Analyses, Data Statistics, and Figures, CD-ROMDocumentation, National
Oceanographic Data Center, Silver Spring, MD, 17 pp., 2002.
Cullen, J. J.: Subsurface chlorophyll maximum layers: enduring enigma or
mystery solved?, Annu. Rev. Mar. Sci., 7, 207–39,
https://doi.org/10.1146/annurev-marine-010213-135111, 2015.
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.
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.
Daewel, U., Hjøllo, S. S., Huret, M., Ji, R., Maar, M., Niiranen, S.,
Travers-Trolet, M., Peck, M. A., and Van De Wolfshaar, K. E.: Predation
control of zooplankton dynamics: A review of observations and models, ICES J.
Mar. Sci., 71, 254–271, https://doi.org/10.1093/icesjms/fst125, 2014.
Daewel, U., Schrum, C., and Macdonald, J.: Towards End-2-End modelling in a
consistent NPZD-F modelling framework (ECOSMOE2E_vs1.0): Application to
the North Sea and Baltic Sea, Geosci. Model Dev. Discuss.,
https://doi.org/10.5194/gmd-2018-239, in review, 2018.
Daly, K. L. and Smith, W. O.: Physical-Biological Interactions Influencing
Marine Plankton Production, Annu. Rev. Ecol. Syst., 24, 555–585,
https://doi.org/10.1146/annurev.es.24.110193.003011, 1993.
Davies, A. M., Sauvel, J., and Evans, J.: Computing near coastal tidal
dynamics from observations and a numerical model, Cont. Shelf Res., 4,
341–366, https://doi.org/10.1016/0278-4343(85)90047-0, 1985.
de Baar, H. J. W.: von Liebig's law of the minimum and plankton ecology
(1899–1991), Prog. Oceanogr., 33, 347–386,
https://doi.org/10.1016/0079-6611(94)90022-1, 1994.
Dekshenieks, M. M., Donaghay, P. L., Sullivan, J. M., Rines, J. E. B.,
Osborn, T. R., and Twardowski, M. S.: Temporal and spatial occurrence of thin
phytoplankton layers in relation to physical processes, Mar. Ecol.-Prog.
Ser., 223, 61–71, https://doi.org/10.3354/meps223061, 2001.
Deutsches Hydrographisches Institut: Tafeln der Astronomischen Argumente
V0+v und der Korrektionen j,v, Deutsches Hydrographisches Insititut,
Hamburg, 1967.
Dippner, J. W.: A frontal-resolving model for the German Bight, Cont. Shelf
Res., 13, 49–66, https://doi.org/10.1016/0278-4343(93)90035-V, 1993.
Dobrynin, M., Gayer, G., Pleskachevsky, A., and Günther, H.: Effect of
waves and currents on the dynamics and seasonal variations of suspended
particulate matter in the North Sea, J. Marine Syst., 82, 1–20,
https://doi.org/10.1016/j.jmarsys.2010.02.012, 2010.
Ebenhöh, W., Kohlmeier, C., Baretta, J. W., and Flöser, G.:
Shallowness may be a major factor generating nutrient gradients in the Wadden
Sea, Ecol. Model., 174, 241–252, https://doi.org/10.1016/j.ecolmodel.2003.07.011, 2004.
Eisma, D.: Supply and Deposition of Suspended Matter in the North Sea, in:
Holocene Marine Sedimentation in the North Sea Basin, 415–428, 2009.
Eliasen, S. K., Hátún, H., Larsen, K. M. H., Hansen, B., and
Rasmussen, T. A. S.: Phenologically distinct phytoplankton regions on the
Faroe Shelf – identified by satellite data, in-situ observations and model,
J. Marine Syst., 169, 99–110, https://doi.org/10.1016/j.jmarsys.2017.01.015, 2017.
Foshtomi, M. Y., Braeckman, U., Derycke, S., Sapp, M., Van Gansbeke, D.,
Sabbe, K., Willems, A., Vincx, M., and Vanaverbeke, J.: The link between
microbial diversity and nitrogen cycling in marine sediments is modulated by
macrofaunal bioturbation, PLoS One, 10, 1–20,
https://doi.org/10.1371/journal.pone.0130116, 2015.
Franks, P. J. S. and Chen, C.: Plankton production in tidal fronts: A model
of Georges Bank in summer, J. Mar. Res., 54, 631–651,
https://doi.org/10.1357/0022240963213718, 1996.
George, J. A., Lonsdale, D. J., Merlo, L. R., and Gobler, C. J.: The
interactive roles of temperature, nutrients, and zooplankton grazing in
controlling the winter-spring phytoplankton bloom in a temperate, coastal
ecosystem, Long Island Sound, Limnol. Oceanogr., 60, 110—126,
https://doi.org/10.1002/lno.10020, 2015.
Geyer, W. R. and MacCready, P.: The Estuarine Circulation, Annu. Rev. Fluid
Mech., 46, 175–197, https://doi.org/10.1146/annurev-fluid-010313-141302, 2014.
Gong, X., Shi, J., and Gao, H.: Modeling seasonal variations of subsurface
chlorophyll maximum in South China Sea, J. Ocean Univ. China, 13, 561–571,
https://doi.org/10.1007/s11802-014-2060-4, 2014.
Große, F., Greenwood, N., Kreus, M., Lenhart, H.-J., Machoczek, D.,
Pätsch, J., Salt, L., and Thomas, H.: Looking beyond stratification: a
model-based analysis of the biological drivers of oxygen deficiency in the
North Sea, Biogeosciences, 13, 2511–2535,
https://doi.org/10.5194/bg-13-2511-2016, 2016.
Heath, M. R.: Changes in the structure and function of the North Sea fish
foodweb, 1973–2000, and the impacts of fishing and climate, ICES J. Mar.
Sci., https://doi.org/10.1016/j.icesjms.2005.01.023, 2005.
Heath, M. R., Edwards, A. C., Pätsch, J., and Turrell, W. R.: Modelling
the behaviour of nutrient in the coastal waters of Scotland, Fisheries
Research Services, Aberdeen, 2002.
Heathershaw, A. D., New, A. L., and Edwards, P. D.: Internal tides and
sediment transport at the shelf break in the Celtic Sea, Cont. Shelf Res., 7,
485–517, https://doi.org/10.1016/0278-4343(87)90092-6, 1987.
Heip, C., Basford, D., Craeymeersch, J. A., Dewarumez, J. M., Dörjes, J.,
de Wilde, P., Duineveld, G., Eleftheriou, A., Herman, P. M. J., Niermann, U.,
Kingston, P., Künitzer, A., Rachor, E., Rumohr, H., Soetaert, K., and
Soltwedel, T.: Trends in biomass, density and diversity of North Sea
macrofauna, ICES Journal of Marine Science, 49, 13–22,
https://doi.org/10.1093/icesjms/49.1.13, 1992.
Henriksen, H. J., Troldborg, L., Nyegaard, P., Sonnenborg, T. O., Refsgaard,
J. C., and Madsen, B.: Methodology for construction, calibration and
validation of a national hydrological model for Denmark, J. Hydrol., 280,
52–71, https://doi.org/10.1016/S0022-1694(03)00186-0, 2003.
Hofmeister, R., Flöser, G., and Schartau, M.: Estuary-type circulation as
a factor sustaining horizontal nutrient gradients in freshwater-influenced
coastal systems, Geo-Mar. Lett., 37, 179–192, https://doi.org/10.1007/s00367-016-0469-z,
2017.
Holligan, P. M., Pingree, R. D., and Mardell, G. T.: Oceanic solitons,
nutrient pulses and phytoplankton growth, Nature, 314, 348–350,
https://doi.org/10.1038/314348a0, 1985.
Holt, J., Butenschön, M., Wakelin, S. L., Artioli, Y., and Allen, J. I.:
Oceanic controls on the primary production of the northwest European
continental shelf: model experiments under recent past conditions and a
potential future scenario, Biogeosciences, 9, 97–117,
https://doi.org/10.5194/bg-9-97-2012, 2012.
Holt, J. T. and James, I. D.: A simulation of the southern North Sea in
comparison with measurements from the North Sea Project Part 2 suspended
particulate matter, Cont. Shelf Res., 19, 1617–1642,
https://doi.org/10.1016/S0278-4343(99)00032-1, 1999.
Hu, S., Townsend, D. W., Chen, C., Cowles, G., Beardsley, R. C., Ji, R., and
Houghton, R. W.: Tidal pumping and nutrient fluxes on Georges Bank: A
process-oriented modeling study, J. Marine Syst., 74, 528–544,
https://doi.org/10.1016/j.jmarsys.2008.04.007, 2008.
Jacobs, W.: Modelling the Rhine River Plume, TU Delft, 2004.
Jago, C. F., Jones, S. E., Latter, R. J., McCandliss, R. R., Hearn, M. R.,
and Howarth, M. J.: Resuspension of benthic fluff by tidal currents in deep
stratified waters, northern North sea, J. Sea Res., 48, 259–269,
https://doi.org/10.1016/S1385-1101(02)00181-8, 2002.
Janssen, F., Schrum, C., and Backhaus, J. O.: A climatological data set of
temperature and salinity for the Baltic Sea and the North Sea, Dtsch.
Hydrogr. Zeitschrift, 51, 5, https://doi.org/10.1007/BF02933676, 1999.
Janssen, F., Schrum, C., Hübner, U., and Backhaus, J. O.: Uncertainty
analysis of a decadal simulation with a regional ocean model for the North
Sea and Baltic Sea, Clim. Res., 18, 55–62, https://doi.org/10.3354/cr018055, 2001.
Joint, I. and Pomroy, A.: Phytoplankton biomass and production in the
southern North Sea, Mar. Ecol. Ser., 99, 169–182, https://doi.org/10.3354/meps099169,
1993.
Joint, T. and Pomroy, A.: hytoplankton Biomass and Production in the North
Sea. Results from the NERC North Sea Project August 1988–October 1989,
Plymouth Marine Laboratory, Plymouth, 1992.
Jones, S. E., Jago, C. F., Bale, a J., Chapman, D., Howland, R. J. M., and
Jackson, J.: Aggregation and resuspension of suspended particulate matter at
a stratified site in the southern North Sea: physical and biological
controls, Cont. Shelf Res., 18, 1283–1309,
https://doi.org/10.1016/S0278-4343(98)00044-2, 1998.
Kalnay, E., Kanamitsu, M., Kistler, R., Collins, W., Deaven, D., Gandin, L.,
Iredell, M., Saha, S., White, G., Woollen, J., Zhu, Y., Chelliah, M.,
Ebisuzaki, W., Higgins, W., Janowiak, J., Mo, K. C., Ropelewski, C., Wang,
J., Leetmaa, A., Reynolds, R., Jenne, R., and Joseph, D.: The NCEP/NCAR
40-year reanalysis project, B. Am. Meteorol. Soc., 77, 437–471,
https://doi.org/10.1175/1520-0477(1996)077<0437:TNYRP>2.0.CO;2, 1996.
Karl, D. M. and Lukas, R.: The Hawaii Ocean Time-series (HOT) program:
Background, rationale and field implementation, Deep-Sea Res. Pt. II, 43,
129–156, https://doi.org/10.1016/0967-0645(96)00005-7, 1996.
Kerimoglu, O., Hofmeister, R., Maerz, J., Riethmüller, R., and Wirtz, K.
W.: The acclimative biogeochemical model of the southern North Sea,
Biogeosciences, 14, 4499–4531, https://doi.org/10.5194/bg-14-4499-2017, 2017.
Lindström, G., Pers, C., Rosberg, J., Strömqvist, J., and Arheimer,
B.: Development and testing of the HYPE (Hydrological Predictions for the
Environment) water quality model for different spatial scales, Hydrol. Res.,
43, 295–319, https://doi.org/10.2166/nh.2010.007, 2010.
Loder, J. W. and Greenberg, D. A.: Predicted positions of tidal fronts in the
Gulf of Maine region, Cont. Shelf Res., 6, 397–414,
https://doi.org/10.1016/0278-4343(86)90080-4, 1986.
Loder, J. W., Brickman, D., and Horne, E. P. W.: Detailed structure of
currents and hydrography on the northern side of Georges Bank, J. Geophys.
Res., 97, 14331–14351, https://doi.org/10.1029/92JC01342, 1992.
Longhurst, A. R.: Ecological Geography of the Sea, Academic Press, 2006.
Maar, M., Markager, S., Madsen, K. S., Windolf, J., Lyngsgaard, M. M.,
Andersen, H. E., and Møller, E. F.: The importance of local versus
external nutrient loads for Chl a and primary production in the Western
Baltic Sea, Ecol. Model., 320, 258–272,
https://doi.org/10.1016/j.ecolmodel.2015.09.023, 2016.
Mahadevan, A., Tandon, A., and Ferrari, R.: Rapid changes in mixed layer
stratification driven by submesoscale instabilities and winds, J. Geophys.
Res.-Ocean., 115, 1–12, https://doi.org/10.1029/2008JC005203, 2010.
Martin, J. H.: Phytoplankton-Zooplankton Relationships in Narragansett Bay,
Limnol. Oceanogr., 10, 185–191, 1965.
Matthias, V., Aulinger, A., and Quante, M.: Adapting CMAQ to investigate air
pollution in North Sea coastal regions, Environ. Modell. Softw., 23,
356–368, https://doi.org/10.1016/j.envsoft.2007.04.010, 2008.
McCandliss, R. R., Jones, S. E., Hearn, M., Latter, R., and Jago, C. F.:
Dynamics of suspended particles in coastal waters (southern North Sea) during
a spring bloom, J. Sea Res., 47, 285–302, https://doi.org/10.1016/S1385-1101(02)00123-5,
2002.
McQuatters-Gollop, A., Raitsos, D. E., Edwards, M., and Attrill, M. J.:
Spatial patterns of diatom and dinoflagellate seasonal cycles in the NE
Atlantic Ocean, Mar. Ecol.-Prog. Ser., 339, 301–306, https://doi.org/10.3354/meps339301,
2007.
Monod, J.: Recherches sur la croissance des cultures bactèriennes,
Hermann & cie, Paris, 1942.
Munk, P. and Nielsen, T. G.: Trophodynamics of the plankton community at
Dogger Bank: Predatory impact by larval fish, J. Plankton Res., 16,
1225–1245, https://doi.org/10.1093/plankt/16.9.1225, 1994.
New, A. L. and Da Silva, J. C. B.: Remote-sensing evidence for the local
generation of internal soliton packets in the central Bay of Biscay, Deep-Sea
Res. Pt. I, 49, 915–934, https://doi.org/10.1016/S0967-0637(01)00082-6, 2002.
Nissen, C.: Physical-Biogeochemical Couplings in the Land-Ocean Transition
Zone, The University of Bergen, available at:
http://hdl.handle.net/1956/18682 (last access: 21 April 2019), 2014.
Otto, L., Adams, J. A., Adam, M. Y., Becker, G. A., Dahl, F. E., Davies, A.
M., Dooley, H. D., Durance, J. A., Furness, G. K., Harding, F. D., Jefferies,
D. J., Koltermann, K. P., Mork, M., Ronday, F. C., and Svansson, A.: Flushing
times of the North Sea, International Council for the Exploration of the Sea,
Copenhagen, 1983.
Otto, L., Zimmerman, J. T. F., Furnes, G. K., Mork, M., Saetre, R., and
Becker, G.: Review of the physical oceanography of the North Sea, Neth. J.
Sea Res., 26, 161–238, https://doi.org/10.1016/0077-7579(90)90091-T, 1990.
Pätsch, J. and Lenhart, H.-J.: Daily Loads of Nutrients, Total
alkalinity, dissolved inorganic carbon and dissolved organic carbon of the
European continental rivers for the years 1977–2002, in: Berichte aus dem
Zentrum für Meeres- und Klimaforschung, Reihe B: Ozeanographie Nr. 48,
p. 159, University of Hamburg, Germany, 2004.
Pedersen, F. B.: The Oceanographic and Biological Tidal Cycle Succession in
Shallow Sea Fronts in the North Sea and the English Channel, Estuar. Coast.
Shelf S., 38, 249–269, https://doi.org/10.1006/ecss.1994.1017, 1994.
Pietrzak, J. D., de Boer, G. J., and Eleveld, M. A.: Mechanisms controlling
the intra-annual mesoscale variability of SST and SPM in the southern North
Sea, Cont. Shelf Res., 31, 594–610, https://doi.org/10.1016/j.csr.2010.12.014, 2011.
Pingree, R. D. and Griffiths, D. K.: Tidal fronts on the shelf seas around
the British Isles, J. Geophys. Res., 83, 4615, https://doi.org/10.1029/JC083iC09p04615,
1978.
Pingree, R. D., Mardell, G. T., and Cartwright, D. E.: Slope Turbulence,
Internal Waves and Phytoplankton Growth at the Celtic Sea Shelf-Break [and
Discussion], Philos. T. R. Soc. A, 302, 663–682, https://doi.org/10.1098/rsta.1981.0191,
1981.
Pleskachevsky, A., Dobrynin, M., Babanin, A. V., Günther, H., and Stanev,
E.: Turbulent Mixing due to Surface Waves Indicated by Remote Sensing of
Suspended Particulate Matter and Its Implementation into Coupled Modeling of
Waves, Turbulence, and Circulation, J. Phys. Oceanogr., 41, 708–724,
https://doi.org/10.1175/2010JPO4328.1, 2011.
Pohlmann, T.: Predicting the thermocline in a circulation model of the North
Sea – Part I: Model description, calibration and verification, Cont. Shelf
Res., 16, 131–146, https://doi.org/10.1016/0278-4343(95)90885-S, 1996.
Porter, E. T., Mason, R. P., and Sanford, L. P.: Effect of tidal resuspension
on benthic-pelagic coupling in an experimental ecosystem study, Mar.
Ecol.-Prog. Ser., 413, 33–53, https://doi.org/10.3354/meps08709, 2010.
Postma, H.: Exchange of materials between the North Sea and the Wadden Sea,
Mar. Geol., 40, 199–213, https://doi.org/10.1016/0025-3227(81)90050-5, 1981.
Prandle, D.: A modelling study of the mixing of 137Cs in the seas of the
European Continental Shelf, Philos. T. R. Soc. A, 310, 408–435,
https://doi.org/10.1098/rsta.1984.0002, 1984.
Prins, T. C., Smaal, A. C., Pouwer, A. J., and Dankers, N.: Filtration and
resuspension of particulate matter and phytoplankton onan intertidal mussel
bed in the Oosterschelde estuary (SW Netherlands), Mar. Ecol.-Prog. Ser.,
142, 121–134, https://doi.org/10.3354/meps142121, 1996.
Richardson, A. J., Pfaff, M. C., Field, J. G., Silulwane, N. F., and
Shillington, F. A.: Identifying characteristic chlorophyll a profiles in the
coastal domain using an artificial neural network, J. Plankton Res., 24,
1289–1303, https://doi.org/10.1093/plankt/24.12.1289, 2002.
Richardson, K., Visser, A. W., and Bo Pedersen, F.: Subsurface phytoplankton
blooms fuel pelagic production in the North Sea, J. Plankton Res., 22,
1663–1671, https://doi.org/10.1093/plankt/22.9.1663, 2000.
Rippeth, T. P., Wiles, P., Palmer, M. R., Sharples, J., and Tweddle, J.: The
diapcynal nutrient flux and shear-induced diapcynal mixing in the seasonally
stratified western Irish Sea, Cont. Shelf Res., 29, 1580–1587,
https://doi.org/10.1016/j.csr.2009.04.009, 2009.
Rodhe, J.: The Baltic and Northern Seas: a process-orientated review of the
physical oceanography, in: The sea, edited by: Robinson, A. R. and Brink, K.
H., 699–732, Wildy, New York, 1998.
Rodhe, J., Tett, P., and Wulf, F.: Chapter 26. The Baltic and North Seas: a
regional review of some important physical-checmial-biological interaction
processes, Sea, 14, 1029–1072, 2004.
Ruddick, K. G., Deleersnijder, E., Luyten, P. J., and Ozer, J.: Haline
stratification in the Rhine-Meuse freshwater plume: a three-dimensional model
sensitivity analysis, Cont. Shelf Res., 15, 1597–1630,
https://doi.org/10.1016/0278-4343(95)00034-X, 1995.
Sabine, C. L., Feely, R. A., Gruber, N., Key, R. M., Lee, K., Bullister, J.
L., Wanninkhof, R., Wong, C. S., Wallace, D. W. R., Tilbrook, B., Millero, F.
J., Peng, T. H., Kozyr, A., Ono, T., and Rios, A. F.: The oceanic sink for
anthropogenic CO2, Science, 305, 367–371,
https://doi.org/10.1126/science.1097403, 2004.
Schartau, M., Riethmüller, R., Flöser, G., Beusekom, J. E. E. Van,
Krasemann, H., Hofmeister, R., and Wirtz, K.: On the separation between
inorganic and organic fractions of suspended matter in a marine coastal
environment, Prog. Oceanogr., 171, 231–250,
https://doi.org/10.1016/j.pocean.2018.12.011, 2018.
Schaub, B. E. M. and Gieskes, W. W. C.: Eutrophication of the North Sea: the
relation between Rhine river discharge and chlorophyll-a concentration in
Dutch coastal waters, Fredensborg, Estuaries and Coasts: Spatial and Temporal
Intercomparisons, ECSA 19 Symposium, ECSA, 1991.
Schrum, C.: Thermohaline stratification and instabilities at tidal mixing
fronts: Results of an eddy resolving model for the German Bight, Cont. Shelf
Res., 17, 689–716, https://doi.org/10.1016/S0278-4343(96)00051-9, 1997.
Schrum, C. and Backhaus, J. O.: Sensivity 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.
Schrum, C., Siegismund, F., and John, M. S.: Decadal variations in the
stratification and circulation patterns of the North Sea. Are the 1990s
unusual?, ICES Mar. Sc., 219, 121–131, 2003.
Schrum, C., St. John, M., and Alekseeva, I.: ECOSMO, a coupled ecosystem
model of the North Sea and Baltic Sea: Part II. Spatial-seasonal
characteristics in the North Sea as revealed by EOF analysis, J. Marine
Syst., 61, 100–113, https://doi.org/10.1016/j.jmarsys.2006.01.004, 2006.
Scott, B. E., Sharples, J., Ross, O. N., Wang, J., Pierce, G. J., and
Camphuysen, C. J.: Sub-surface hotspots in shallow seas: Fine-scale limited
locations of top predator foraging habitat indicated By tidal mixing and
sub-surface chlorophyll, Mar. Ecol.-Prog. Ser., 408, 207–226,
https://doi.org/10.3354/meps08552, 2010.
Sharples, J.: Potential impacts of the spring-neap tidal cycle on shelf sea
primary production, J. Plankton Res., 30, 183–197,
https://doi.org/10.1093/plankt/fbm088, 2008.
Sharples, J. and Simpson, J. H.: Periodic Frontogenesis in a Region of
Freshwater Influence, Estuaries, 16, 74–82, https://doi.org/10.2307/1352765, 1993.
Sharples, J., Moore, M. C., Rippeth, T. P., Holligan, P. M., Hydes, D. J.,
Fisher, N. R., and Simpson, J. H.: Phytoplankton distribution and survival in
the thermocline, Limnol. Oceanogr., 46, 486–496,
https://doi.org/10.4319/lo.2001.46.3.0486, 2001.
Sharples, J., Ross, O. N., Scott, B. E., Greenstreet, S. P. R., and Fraser,
H.: Inter-annual variability in the timing of stratification and the spring
bloom in the North-western North Sea, Cont. Shelf Res., 26, 733–751,
https://doi.org/10.1016/j.csr.2006.01.011, 2006.
Sharples, J., Tweddle, J. F., Green, J. A. M., Palmer, M. R., Kim, Y.,
Hickman, A. E., Holligan, P. M., Moore, C. M., Rippeth, T. P., Simpson, J.
H., and Krivtsov, V.: Spring – neap modulation of internal tide mixing and
vertical nitrate fluxes at a shelf edge in summer, Limnol. Oceanogr., 52,
1735–1747, 2007.
Siegel, H., Gerth, M., Heene, T., Ohde, T., Rüß, D., and Kraft, H.:
Hydrography, currents and distribution of suspended matter during a dumping
experiment in the western Baltic Sea at a site near Warnemünde, J. Marine
Syst., 75, 397–408, https://doi.org/10.1016/j.jmarsys.2008.04.005, 2009.
Siegismund, F.: Long-term changes in the flushing times of the ICES-boxes,
Senck. Marit., 31, 151–167, https://doi.org/10.1007/BF03043025, 2001.
Simpson, J. H. and Bowers, D.: Models of stratification and frontal movement
in shelf seas, Deep-Sea Res. Pt. A, 28, 727–738,
https://doi.org/10.1016/0198-0149(81)90132-1, 1981.
Simpson, J. H. and Hunter, J. R.: Fronts in the Irish Sea, Nature, 250,
404–406, https://doi.org/10.1038/250404a0, 1974.
Simpson, J. H. and Sharples, J.: Introduction to the Physical and Biological
Oceanography of Shelf Seas, Cambridge University Press, 2012.
Simpson, J. H. and Souza, A. J.: Semidiurnal switching of stratification in
the region of freshwater influence of the Rhine, J. Geophys. Res., 100,
7037–7044, https://doi.org/10.1029/95JC00067, 1995.
Smith, W. O. and Jones, R. M.: Vertical mixing, critical depths, and
phytoplankton growth in the Ross Sea, ICES J. Mar. Sci., 72, 1952–1960,
https://doi.org/10.1093/icesjms/fsu234, 2015.
Stedmon, C. A., Markager, S., and Kaas, H.: Optical Properties and Signatures
of Chromophoric Dissolved Organic Matter (CDOM) in Danish Coastal Waters,
Estuar. Coast. Shelf S., 51, 267–278, https://doi.org/10.1006/ecss.2000.0645, 2000.
Stoica, P., Moses, R. L., and Hall, P.: Introduction to Spectral Analysis,
Technometrics, 47, 104–105, https://doi.org/10.1198/tech.2005.s841, 2005.
Tett, P. and Walne, A.: Observations and simulations of hydrography,
nutrients and plankton in the southern north sea, Ophelia, 42, 371–416,
https://doi.org/10.1080/00785326.1995.10431514, 1995.
Thomson, R. E. and Emery, W. J.: Chapter 5 – Time Series Analysis Methods,
in: Data Analysis Methods in Physical Oceanography, 3rd Edn., 425–591,
Elsevier, Boston, 2014.
Tian, T., Merico, A., Su, J., Staneva, J., Wiltshire, K., and Wirtz, K.:
Importance of resuspended sediment dynamics for the phytoplankton spring
bloom in a coastal marine ecosystem, J. Sea Res., 62, 214–228,
https://doi.org/10.1016/j.seares.2009.04.001, 2009.
Urtizberea, A., Dupont, N., Rosland, R., and Aksnes, D. L.: Sensitivity of
euphotic zone properties to CDOM variations in marine ecosystem models, Ecol.
Model., 256, 16–22, https://doi.org/10.1016/j.ecolmodel.2013.02.010, 2013.
van Alphen, J. S. L. J.: A mud balance for Belgian-Dutch coastal waters
between 1969 and 1986, Neth. J. Sea Res., 25, 19–30,
https://doi.org/10.1016/0077-7579(90)90005-2, 1990.
Van Beusekom, J. and Diel-Christiansen, A.: Synthesis of phyto- and
zooplankton dynamics in the North Sea environment, 148 pp., WWF – World Wide
Fund For Nature, Godalming, 1994.
van der Woerd, H. J., Blauw, A., Peperzak, L., Pasterkamp, R., and Peters,
S.: Analysis of the spatial evolution of the 2003 algal bloom in the
Voordelta (North Sea), J. Sea Res., 65, 195–204,
https://doi.org/10.1016/j.seares.2010.09.007, 2011.
van Leeuwen, S. M., van der Molen, J., Ruardij, P., Fernand, L., and
Jickells, T.: Modelling the contribution of deep chlorophyll maxima to annual
primary production in the North Sea, Biogeochemistry, 113, 137–152,
https://doi.org/10.1007/s10533-012-9704-5, 2013.
Van Leeuwen, S., Tett, P., Mills, D., and Van Der Molen, J.: Stratified and
nonstratified areas in the North Sea: Long-term variability and biological
and policy implications, J. Geophys. Res.-Ocean., 120, 4670–4686,
https://doi.org/10.1002/2014JC010485, 2015.
Van Raaphorst, W., Philippart, C. J. M., Smit, J. P. C., Dijkstra, F. J., and
Malschaert, J. F. P.: Distribution of suspended particulate matter in the
North Sea as inferred from NOAA/AVHRR reflectance images and in situ
observations, J. Sea Res., 39, 197–215, https://doi.org/10.1016/S1385-1101(98)00006-9,
1998.
Wafar, M. V. M., Le Corre, P., and Birrien, J. L.: Nutrients and primary
production in permanently well-mixed temperate coastal waters, Estuar. Coast.
Shelf S., 17, 431–446, https://doi.org/10.1016/0272-7714(83)90128-2, 1983.
Waniek, J. J.: The role of physical forcing in initiation of spring blooms in
the northeast Atlantic, J. Marine Syst., 39, 57–82,
https://doi.org/10.1016/S0924-7963(02)00248-8, 2003.
Warnock, R. E., Gieskes, W. W. C., and Van Laar, S.: Regional and seasonal
differences in light absorption by yellow substance in the Southern Bight of
the North Sea, J. Sea Res., 42, 169–178, https://doi.org/10.1016/S1385-1101(99)00025-8,
1999.
Welch, P. D.: The use of fast Fourier transform for the estimation of power
spectra: A method based on time averaging over short, modified periodograms,
IEEE T. Audio Electroacoust., 15, 70–73, https://doi.org/10.1109/TAU.1967.1161901, 1967.
Windolf, J., Thodsen, H., Troldborg, L., Larsen, S. E., Bøgestrand, J.,
Ovesen, N. B., and Kronvang, B.: A distributed modelling system for
simulation of monthly runoff and nitrogen sources, loads and sinks for
ungauged catchments in Denmark, J. Environ. Monitor., 13, 2645–2658,
https://doi.org/10.1039/c1em10139k, 2011.
Windolf, J., Blicher-Mathiesen, G., Carstensen, J., and Kronvang, B.: Changes
in nitrogen loads to estuaries following implementation of governmental
action plans in Denmark: A paired catchment and estuary approach for
analysing regional responses, Environ. Sci. Policy, 24, 24–33,
https://doi.org/10.1016/j.envsci.2012.08.009, 2012.
Yee, H. C., Warming, R. F., and Harten, A.: Implicit total variation
diminishing (TVD) schemes for steady-state calculations, J. Comput. Phys.,
57, 327–360, https://doi.org/10.1016/0021-9991(85)90183-4, 1985.
Zhang, W. and Wirtz, K.: Mutual Dependence Between Sedimentary Organic Carbon
and Infaunal Macrobenthos Resolved by Mechanistic Modeling, J. Geophys.
Res.-Biogeo., 122, 2509–2526, https://doi.org/10.1002/2017JG003909, 2017.
Zhao, C., Maerz, J., Hofmeister, R., Röttgers, R., Riethmüller, R.,
Wirtz, K., and Schrum, C.: Characterizing the vertical distribution of
chlorophyll a in the German Bight, Cont. Shelf Res., 175, 127–146,
https://doi.org/10.1016/j.csr.2019.01.012, 2019.
Short summary
Our study highlights the importance of tides in controlling the spatial and temporal distributions North Sea primary production based on numerical experiments. We identified two different response chains acting in different regions of the North Sea. (i) In the southern shallow areas, strong tidal mixing dilutes phytoplankton concentrations and increases turbidity, thus decreasing NPP. (ii) In the frontal regions, tidal mixing infuses nutrients into the surface mixed layer, thus increasing NPP.
Our study highlights the importance of tides in controlling the spatial and temporal...
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