50 citations as recorded by crossref.

1. Using Maximum Entropy Production to Describe Microbial Biogeochemistry Over Time and Space in a Meromictic Pond J. Vallino & J. Huber 10.3389/fenvs.2018.00100
2. A structure-preserving model for the dynamics of estuarine ecosystems and its application in western Patagonia fjords P. Mata Almonacid & C. Medel 10.1016/j.ecolmodel.2021.109871
3. Disentangling the effects of climate change and reoligotrophication on primary production in a large lake S. Krishna et al. 10.1007/s00027-022-00910-2
4. Resolving ecological feedbacks on the ocean carbon sink in Earth system models D. Armstrong McKay et al. 10.5194/esd-12-797-2021
5. Suspension feeders: diversity, principles of particle separation and biomimetic potential L. Hamann & A. Blanke 10.1098/rsif.2021.0741
6. Mapping manifestations of parametric uncertainty in projected pelagic oxygen concentrations back to contemporary local model fidelity U. Löptien et al. 10.1038/s41598-021-00334-2
7. From Bacteria to Zooplankton: An Integrative Approach Revealing Regional Spatial Patterns During the Spring Phytoplankton Bloom in the Southern Bight of the North Sea A. Aubert et al. 10.3389/fmars.2022.863996
8. The role of biota in the Southern Ocean carbon cycle P. Boyd et al. 10.1038/s43017-024-00531-3
9. Multiobjective Calibration of a Global Biogeochemical Ocean Model Against Nutrients, Oxygen, and Oxygen Minimum Zones V. Sauerland et al. 10.1029/2018MS001510
10. Intermediate Variable Emulation: Using Internal Processes in Simulators to Build More Informative Emulators R. Oughton et al. 10.1137/20M1370902
11. Food web structure and intraguild predation affect ecosystem functioning in an established plankton model A. Prowe et al. 10.1002/lno.12039
12. Bridging the gap: integrating models and observations for better ecosystem understanding M. Skogen et al. 10.3354/meps14616
13. Can neural networks predict steady annual cycles of marine ecosystems? T. Slawig & M. Pfeil 10.1007/s00287-022-01491-y
14. Quantifying biological carbon pump pathways with a data-constrained mechanistic model ensemble approach M. Stukel et al. 10.5194/bg-19-3595-2022
15. Investigating ecosystem connections in the shelf sea environment using complex networks I. Higgs et al. 10.5194/bg-21-731-2024
16. Exploring the role of different data types and timescales in the quality of marine biogeochemical model calibration I. Kriest et al. 10.5194/bg-20-2645-2023
17. Assimilating bio-optical glider data during a phytoplankton bloom in the southern Ross Sea D. Kaufman et al. 10.5194/bg-15-73-2018
18. Assimilating synthetic Biogeochemical-Argo and ocean colour observations into a global ocean model to inform observing system design D. Ford 10.5194/bg-18-509-2021
19. Zooplankton grazing is the largest source of uncertainty for marine carbon cycling in CMIP6 models T. Rohr et al. 10.1038/s43247-023-00871-w
20. A CMA‐ES Algorithm Allowing for Random Parameters in Model Calibration V. Sauerland et al. 10.1029/2022MS003390
21. Evolution of oxygen and stratification and their relationship in the North Pacific Ocean in CMIP6 Earth system models L. Novi et al. 10.5194/bg-21-3985-2024
22. Evaluating ecosystem model complexity for the northwest North Atlantic through surrogate-based optimization A. Kuhn & K. Fennel 10.1016/j.ocemod.2019.101437
23. Impacts of parameter uncertainties on deep chlorophyll maximum simulation revealed by the CNOP-P approach Y. Gao et al. 10.1007/s00343-020-0020-y
24. Taxon-specific phytoplankton growth, nutrient utilization and light limitation in the oligotrophic Gulf of Mexico N. Yingling et al. 10.1093/plankt/fbab028
25. Top-down and bottom-up control of phytoplankton in a mid-latitude continental shelf ecosystem S. Rodríguez-Gálvez et al. 10.1016/j.pocean.2023.103083
26. Calibration of a simple and a complex model of global marine biogeochemistry I. Kriest 10.5194/bg-14-4965-2017
27. Ocean biogeochemical modelling K. Fennel et al. 10.1038/s43586-022-00154-2
28. Cyanobacteria blooms in the Baltic Sea: a review of models and facts B. Munkes et al. 10.5194/bg-18-2347-2021
29. How uncertain and observable are marine ecosystem indicators in shelf seas? J. Skákala et al. 10.1016/j.pocean.2024.103249
30. Primary production sensitivity to phytoplankton light attenuation parameter increases with transient forcing K. Kvale & K. Meissner 10.5194/bg-14-4767-2017
31. Error assessment of biogeochemical models by lower bound methods (NOMMA-1.0) V. Sauerland et al. 10.5194/gmd-11-1181-2018
32. Spatial variability in rates of net primary production (NPP) and onset of the spring bloom in Greenland shelf waters M. Vernet et al. 10.1016/j.pocean.2021.102655
33. A global sensitivity analysis approach for marine biogeochemical modeling C. Prieur et al. 10.1016/j.ocemod.2019.101402
34. Comparison of two carbon-nitrogen regulatory models calibrated with mesocosm data S. Krishna et al. 10.1016/j.ecolmodel.2019.05.016
35. Biological data assimilation for parameter estimation of a phytoplankton functional type model for the western North Pacific Y. Hoshiba et al. 10.5194/os-14-371-2018
36. Future digital twins: emulating a highly complex marine biogeochemical model with machine learning to predict hypoxia J. Skákala et al. 10.3389/fmars.2023.1058837
37. Revealing the seasonal cycles of Arctic phytoplankton: insights from year-round chlorophyll monitoring E. Ko et al. 10.1088/1748-9326/ad1e7e
38. Uncertainties in ocean biogeochemical simulations: Application of ensemble data assimilation to a one-dimensional model N. Mamnun et al. 10.3389/fmars.2022.984236
39. Optimality-based non-Redfield plankton–ecosystem model (OPEM v1.1) in UVic-ESCM 2.9 – Part 2: Sensitivity analysis and model calibration C. Chien et al. 10.5194/gmd-13-4691-2020
40. Predicting temperature impacts on aquatic productivity: Questioning the metabolic theory of ecology's “canonical” activation energies Q. Wang et al. 10.1002/lno.11105
41. Recommendations for the formulation of grazing in marine biogeochemical and ecosystem models T. Rohr et al. 10.1016/j.pocean.2022.102878
42. The role of microzooplankton trophic interactions in modelling a suite of mesocosm ecosystems B. Su et al. 10.1016/j.ecolmodel.2017.11.013
43. A data–model synthesis to explain variability in calcification observed during a CO<sub>2</sub> perturbation mesocosm experiment S. Krishna & M. Schartau 10.5194/bg-14-1857-2017
44. Advances in biorenewables-resource-waste systems and modelling M. Guo et al. 10.1016/j.ccst.2023.100142
45. Ambiguous controls on simulated diazotrophs in the world oceans U. Löptien & H. Dietze 10.1038/s41598-022-22382-y
46. Using machine learning and Biogeochemical-Argo (BGC-Argo) floats to assess biogeochemical models and optimize observing system design A. Mignot et al. 10.5194/bg-20-1405-2023
47. Nitrogen Fixation in Mesoscale Eddies of the North Pacific Subtropical Gyre: Patterns and Mechanisms M. Dugenne et al. 10.1029/2022GB007386
48. Climate change impacts on southern Ross Sea phytoplankton composition, productivity, and export D. Kaufman et al. 10.1002/2016JC012514
49. A Simple Finite Difference‐Based Approximation for Biogeochemical Tangent Linear and Adjoint Models J. Mattern & C. Edwards 10.1029/2018JC014283
50. Calibrating a global three-dimensional biogeochemical ocean model (MOPS-1.0) I. Kriest et al. 10.5194/gmd-10-127-2017