Articles | Volume 11, issue 11
https://doi.org/10.5194/bg-11-3015-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/bg-11-3015-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
06 Jun 2014
Research article |
| 06 Jun 2014
Using biogeochemical data assimilation to assess the relative skill of multiple ecosystem models in the Mid-Atlantic Bight: effects of increasing the complexity of the planktonic food web
Y. Xiao
Virginia Institute of Marine Science, College of William & Mary, P.O. Box 1346, Gloucester Point, VA 23062, USA
M. A. M. Friedrichs
Virginia Institute of Marine Science, College of William & Mary, P.O. Box 1346, Gloucester Point, VA 23062, USA
Viewed
Total article views: 5,051 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 08 Jan 2014)
| HTML | XML | Total | BibTeX | EndNote | |
|---|---|---|---|---|---|
| 2,289 | 2,293 | 469 | 5,051 | 470 | 419 |
- HTML: 2,289
- PDF: 2,293
- XML: 469
- Total: 5,051
- BibTeX: 470
- EndNote: 419
Total article views: 3,820 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 06 Jun 2014)
| HTML | XML | Total | BibTeX | EndNote | |
|---|---|---|---|---|---|
| 1,954 | 1,451 | 415 | 3,820 | 469 | 415 |
- HTML: 1,954
- PDF: 1,451
- XML: 415
- Total: 3,820
- BibTeX: 469
- EndNote: 415
Total article views: 1,231 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 08 Jan 2014)
| HTML | XML | Total | BibTeX | EndNote | |
|---|---|---|---|---|---|
| 335 | 842 | 54 | 1,231 | 1 | 4 |
- HTML: 335
- PDF: 842
- XML: 54
- Total: 1,231
- BibTeX: 1
- EndNote: 4
Cited
41 citations as recorded by crossref.
- Reviews and syntheses: parameter identification in marine planktonic ecosystem modelling M. Schartau et al. https://doi.org/10.5194/bg-14-1647-2017
- Quantifying biological carbon pump pathways with a data-constrained mechanistic model ensemble approach M. Stukel et al. https://doi.org/10.5194/bg-19-3595-2022
- Bridging the gap: integrating models and observations for better ecosystem understanding M. Skogen et al. https://doi.org/10.3354/meps14616
- The Assimilation of Phytoplankton Functional Types for Operational Forecasting in the Northwest European Shelf J. Skákala et al. https://doi.org/10.1029/2018JC014153
- Discussion of skill improvement in marine ecosystem dynamic models based on parameter optimization and skill assessment C. Shen et al. https://doi.org/10.1007/s00343-016-5068-3
- 75 years since Monod: It is time to increase the complexity of our predictive ecosystem models (opinion) https://doi.org/10.1016/j.ecolmodel.2016.12.001
- Decadal reanalysis of biogeochemical indicators and fluxes in the North West European shelf‐sea ecosystem S. Ciavatta et al. https://doi.org/10.1002/2015JC011496
- Observing and modelling phytoplankton community structure in the North Sea D. Ford et al. https://doi.org/10.5194/bg-14-1419-2017
- Ecosystem modeling in the Northeastern United States: a comment on Sivel et al J. Link & H. Browman https://doi.org/10.1093/icesjms/fsaf210
- Numerical models for monitoring and forecasting ocean biogeochemistry: a short description of present status G. Cossarini et al. https://doi.org/10.5194/sp-5-opsr-12-2025
- Global Assimilation of Ocean‐Color Data of Phytoplankton Functional Types: Impact of Different Data Sets H. Pradhan et al. https://doi.org/10.1029/2019JC015586
- Building the capacity for forecasting marine biogeochemistry and ecosystems: recent advances and future developments M. Gehlen et al. https://doi.org/10.1080/1755876X.2015.1022350
- Carbon Fluxes in the Coastal Ocean: Synthesis, Boundary Processes, and Future Trends M. Dai et al. https://doi.org/10.1146/annurev-earth-032320-090746
- Effects of parameter indeterminacy in pelagic biogeochemical modules of Earth System Models on projections into a warming future: The scale of the problem U. Löptien & H. Dietze https://doi.org/10.1002/2017GB005690
- Assimilation of Ocean‐Color Plankton Functional Types to Improve Marine Ecosystem Simulations S. Ciavatta et al. https://doi.org/10.1002/2017JC013490
- Capabilities of Baltic Sea models to assess environmental status for marine biodiversity L. Tedesco et al. https://doi.org/10.1016/j.marpol.2016.04.021
- Assessing the value of biogeochemical Argo profiles versus ocean color observations for biogeochemical model optimization in the Gulf of Mexico B. Wang et al. https://doi.org/10.5194/bg-17-4059-2020
- Effects of assimilating phytoplankton carbon in marine ecosystem modelling in NEMO4.0.4-MEDUSA2.0-PDAF2.0 Y. Chen et al. https://doi.org/10.5194/gmd-19-7589-2026
- Carbon Budget of Tidal Wetlands, Estuaries, and Shelf Waters of Eastern North America R. Najjar et al. https://doi.org/10.1002/2017GB005790
- Variability of plankton production during the spring bloom in NW Iberia L. García-García & M. Ruiz-Villarreal https://doi.org/10.3354/meps14236
- Taxon-specific phytoplankton growth, nutrient utilization and light limitation in the oligotrophic Gulf of Mexico N. Yingling et al. https://doi.org/10.1093/plankt/fbab028
- The Role of Zooplankton Grazing and Nutrient Recycling for Global Ocean Biogeochemistry and Phytoplankton Phenology O. Karakuş et al. https://doi.org/10.1029/2022JG006798
- Impacts of Atmospheric Nitrogen Deposition and Coastal Nitrogen Fluxes on Oxygen Concentrations in Chesapeake Bay F. Da et al. https://doi.org/10.1029/2018JC014009
- Climate change impacts on southern Ross Sea phytoplankton composition, productivity, and export D. Kaufman et al. https://doi.org/10.1002/2016JC012514
- Evaluating ecosystem model complexity for the northwest North Atlantic through surrogate-based optimization A. Kuhn & K. Fennel https://doi.org/10.1016/j.ocemod.2019.101437
- Lessons from seventy-five years of ecosystem modeling in the Northeastern US Shelf E. Sivel et al. https://doi.org/10.1093/icesjms/fsaf078
- Ocean Circulation Causes Strong Variability in the Mid‐Atlantic Bight Nitrogen Budget M. Friedrichs et al. https://doi.org/10.1029/2018JC014424
- Advancing Marine Biogeochemical and Ecosystem Reanalyses and Forecasts as Tools for Monitoring and Managing Ecosystem Health K. Fennel et al. https://doi.org/10.3389/fmars.2019.00089
- EMPOWER-1.0: an Efficient Model of Planktonic ecOsystems WrittEn in R T. Anderson et al. https://doi.org/10.5194/gmd-8-2231-2015
- Chesapeake Bay nitrogen fluxes derived from a land‐estuarine ocean biogeochemical modeling system: Model description, evaluation, and nitrogen budgets Y. Feng et al. https://doi.org/10.1002/2015JG002931
- Impacts of Atmospheric Nitrogen Deposition on Surface Waters of the Western North Atlantic Mitigated by Multiple Feedbacks P. St‐Laurent et al. https://doi.org/10.1002/2017JC013072
- Using Multiple Ecological Models to Inform Environmental Decision-Making K. Lewis et al. https://doi.org/10.3389/fmars.2021.625790
- Uncertainties in ocean biogeochemical simulations: Application of ensemble data assimilation to a one-dimensional model N. Mamnun et al. https://doi.org/10.3389/fmars.2022.984236
- Variations in the elemental ratio of organic matter in the central Baltic Sea: Part II – Sensitivities of annual mass flux estimates to model parameter variations M. Kreus & M. Schartau https://doi.org/10.1016/j.csr.2015.02.004
- Modelling primary production: multitude of theories, or multitude of languages? J. Skákala et al. https://doi.org/10.5194/os-22-1457-2026
- Evaluating Confidence in the Impact of Regulatory Nutrient Reduction on Chesapeake Bay Water Quality I. Irby & M. Friedrichs https://doi.org/10.1007/s12237-018-0440-5
- Predicting the resilience and recovery of aquatic systems: A framework for model evolution within environmental observatories M. Hipsey et al. https://doi.org/10.1002/2015WR017175
- Challenges associated with modeling low-oxygen waters in Chesapeake Bay: a multiple model comparison I. Irby et al. https://doi.org/10.5194/bg-13-2011-2016
- Biogeochemical Model Optimization by Using Satellite-Derived Phytoplankton Functional Type Data and BGC-Argo Observations in the Northern South China Sea C. Shu et al. https://doi.org/10.3390/rs14051297
- Applications of biogeochemical models in different marine environments: a review K. Ismail & M. Al-Shehhi https://doi.org/10.3389/fenvs.2023.1198856
- Assimilating bio-optical glider data during a phytoplankton bloom in the southern Ross Sea D. Kaufman et al. https://doi.org/10.5194/bg-15-73-2018
41 citations as recorded by crossref.
- Reviews and syntheses: parameter identification in marine planktonic ecosystem modelling M. Schartau et al. https://doi.org/10.5194/bg-14-1647-2017
- Quantifying biological carbon pump pathways with a data-constrained mechanistic model ensemble approach M. Stukel et al. https://doi.org/10.5194/bg-19-3595-2022
- Bridging the gap: integrating models and observations for better ecosystem understanding M. Skogen et al. https://doi.org/10.3354/meps14616
- The Assimilation of Phytoplankton Functional Types for Operational Forecasting in the Northwest European Shelf J. Skákala et al. https://doi.org/10.1029/2018JC014153
- Discussion of skill improvement in marine ecosystem dynamic models based on parameter optimization and skill assessment C. Shen et al. https://doi.org/10.1007/s00343-016-5068-3
- 75 years since Monod: It is time to increase the complexity of our predictive ecosystem models (opinion) https://doi.org/10.1016/j.ecolmodel.2016.12.001
- Decadal reanalysis of biogeochemical indicators and fluxes in the North West European shelf‐sea ecosystem S. Ciavatta et al. https://doi.org/10.1002/2015JC011496
- Observing and modelling phytoplankton community structure in the North Sea D. Ford et al. https://doi.org/10.5194/bg-14-1419-2017
- Ecosystem modeling in the Northeastern United States: a comment on Sivel et al J. Link & H. Browman https://doi.org/10.1093/icesjms/fsaf210
- Numerical models for monitoring and forecasting ocean biogeochemistry: a short description of present status G. Cossarini et al. https://doi.org/10.5194/sp-5-opsr-12-2025
- Global Assimilation of Ocean‐Color Data of Phytoplankton Functional Types: Impact of Different Data Sets H. Pradhan et al. https://doi.org/10.1029/2019JC015586
- Building the capacity for forecasting marine biogeochemistry and ecosystems: recent advances and future developments M. Gehlen et al. https://doi.org/10.1080/1755876X.2015.1022350
- Carbon Fluxes in the Coastal Ocean: Synthesis, Boundary Processes, and Future Trends M. Dai et al. https://doi.org/10.1146/annurev-earth-032320-090746
- Effects of parameter indeterminacy in pelagic biogeochemical modules of Earth System Models on projections into a warming future: The scale of the problem U. Löptien & H. Dietze https://doi.org/10.1002/2017GB005690
- Assimilation of Ocean‐Color Plankton Functional Types to Improve Marine Ecosystem Simulations S. Ciavatta et al. https://doi.org/10.1002/2017JC013490
- Capabilities of Baltic Sea models to assess environmental status for marine biodiversity L. Tedesco et al. https://doi.org/10.1016/j.marpol.2016.04.021
- Assessing the value of biogeochemical Argo profiles versus ocean color observations for biogeochemical model optimization in the Gulf of Mexico B. Wang et al. https://doi.org/10.5194/bg-17-4059-2020
- Effects of assimilating phytoplankton carbon in marine ecosystem modelling in NEMO4.0.4-MEDUSA2.0-PDAF2.0 Y. Chen et al. https://doi.org/10.5194/gmd-19-7589-2026
- Carbon Budget of Tidal Wetlands, Estuaries, and Shelf Waters of Eastern North America R. Najjar et al. https://doi.org/10.1002/2017GB005790
- Variability of plankton production during the spring bloom in NW Iberia L. García-García & M. Ruiz-Villarreal https://doi.org/10.3354/meps14236
- Taxon-specific phytoplankton growth, nutrient utilization and light limitation in the oligotrophic Gulf of Mexico N. Yingling et al. https://doi.org/10.1093/plankt/fbab028
- The Role of Zooplankton Grazing and Nutrient Recycling for Global Ocean Biogeochemistry and Phytoplankton Phenology O. Karakuş et al. https://doi.org/10.1029/2022JG006798
- Impacts of Atmospheric Nitrogen Deposition and Coastal Nitrogen Fluxes on Oxygen Concentrations in Chesapeake Bay F. Da et al. https://doi.org/10.1029/2018JC014009
- Climate change impacts on southern Ross Sea phytoplankton composition, productivity, and export D. Kaufman et al. https://doi.org/10.1002/2016JC012514
- Evaluating ecosystem model complexity for the northwest North Atlantic through surrogate-based optimization A. Kuhn & K. Fennel https://doi.org/10.1016/j.ocemod.2019.101437
- Lessons from seventy-five years of ecosystem modeling in the Northeastern US Shelf E. Sivel et al. https://doi.org/10.1093/icesjms/fsaf078
- Ocean Circulation Causes Strong Variability in the Mid‐Atlantic Bight Nitrogen Budget M. Friedrichs et al. https://doi.org/10.1029/2018JC014424
- Advancing Marine Biogeochemical and Ecosystem Reanalyses and Forecasts as Tools for Monitoring and Managing Ecosystem Health K. Fennel et al. https://doi.org/10.3389/fmars.2019.00089
- EMPOWER-1.0: an Efficient Model of Planktonic ecOsystems WrittEn in R T. Anderson et al. https://doi.org/10.5194/gmd-8-2231-2015
- Chesapeake Bay nitrogen fluxes derived from a land‐estuarine ocean biogeochemical modeling system: Model description, evaluation, and nitrogen budgets Y. Feng et al. https://doi.org/10.1002/2015JG002931
- Impacts of Atmospheric Nitrogen Deposition on Surface Waters of the Western North Atlantic Mitigated by Multiple Feedbacks P. St‐Laurent et al. https://doi.org/10.1002/2017JC013072
- Using Multiple Ecological Models to Inform Environmental Decision-Making K. Lewis et al. https://doi.org/10.3389/fmars.2021.625790
- Uncertainties in ocean biogeochemical simulations: Application of ensemble data assimilation to a one-dimensional model N. Mamnun et al. https://doi.org/10.3389/fmars.2022.984236
- Variations in the elemental ratio of organic matter in the central Baltic Sea: Part II – Sensitivities of annual mass flux estimates to model parameter variations M. Kreus & M. Schartau https://doi.org/10.1016/j.csr.2015.02.004
- Modelling primary production: multitude of theories, or multitude of languages? J. Skákala et al. https://doi.org/10.5194/os-22-1457-2026
- Evaluating Confidence in the Impact of Regulatory Nutrient Reduction on Chesapeake Bay Water Quality I. Irby & M. Friedrichs https://doi.org/10.1007/s12237-018-0440-5
- Predicting the resilience and recovery of aquatic systems: A framework for model evolution within environmental observatories M. Hipsey et al. https://doi.org/10.1002/2015WR017175
- Challenges associated with modeling low-oxygen waters in Chesapeake Bay: a multiple model comparison I. Irby et al. https://doi.org/10.5194/bg-13-2011-2016
- Biogeochemical Model Optimization by Using Satellite-Derived Phytoplankton Functional Type Data and BGC-Argo Observations in the Northern South China Sea C. Shu et al. https://doi.org/10.3390/rs14051297
- Applications of biogeochemical models in different marine environments: a review K. Ismail & M. Al-Shehhi https://doi.org/10.3389/fenvs.2023.1198856
- Assimilating bio-optical glider data during a phytoplankton bloom in the southern Ross Sea D. Kaufman et al. https://doi.org/10.5194/bg-15-73-2018
Saved (final revised paper)
Latest update: 06 Oct 2026
Altmetrics
Final-revised paper
Preprint