Skogen, M.D., Ji, R., Akimova, A., Daewel, U., Hansen, C., Hjøllo, S.S., van Leeuwen, S.M., Maar, M., Macias, D., Mousing, E.A., Almroth-Rosell, E., Sailley, S.F., Spence, M.A., Troost, T.A., & van de Wolfshaar, K. (2021): Disclosing the truth: Are models better than observations? Mar Ecol Prog Ser :DYNMODav1, doi:10.3354/meps13574
The aphorism, ‘All models are wrong, but some models are useful’, originally referred to statistical models, but is now used for scientific models in general. When presenting results from a marine simulation model, this statement effectively stops discussions about the quality of the model, as there is always another observation to mismatch, and thereby another confirmation why the model cannot be trusted. It is common that observations are less challenged and are often viewed as a ‘gold standard’ for judging models, whereas proper interpretations and the true value of models are often overlooked. Models are not perfect, and there are many examples where models are used improperly to provide misleading answers with great confidence, but to what extent does an observation represent the truth? The precision of the observational gear may be high, but what about representativeness? The interpretation of observations is simply another model, but this time not coded in a computer language but rather formed by the individual observer. We submit that it would be more productive to initiate a process where the norm is that models and observations are joined to strengthen both. In the end, neither method is the goal, but both are useful tools for disclosing the truth. Biased views on either observational or modeling approaches would limit us from achieving this goal.
Friedland, R., Macias, D., Cossarini, G., Daewel, U., Estournel, C., Garcia-Gorriz, E., Grizzetti, B., Grégoire, M., Gustafson, B., Kalaroni, S., Kerimoglu, O., Lazzari, P., Lenhart, H., Lessin, G., Maljutenko, I., Miladinova, S., Müller-Karulis, B., Neumann, T., Parn, O., Pätsch, J., Piroddi, C., Raudsepp, U., Schrum, C., Stegert, C., Stips, A., Tsiaras, K., Ulses, C., & Vandenbulcke, L. (2021): Effects of Nutrient Management Scenarios on Marine Eutrophication Indicators: A Pan-European, Multi-Model Assessment in Support of the Marine Strategy Framework Directive. Front. Mar. Sci. 8:596126, doi:10.3389/fmars.2021.596126
A novel pan-European marine model ensemble was established, covering nearly all seas under the regulation of the Marine Strategy Framework Directive (MSFD), with the aim of providing a consistent assessment of the potential impacts of riverine nutrient reduction scenarios on marine eutrophication indicators. For each sea region, up to five coupled biogeochemical models from institutes all over Europe were brought together for the first time. All model systems followed a harmonised scenario approach and ran two simulations, which varied only in the riverine nutrient inputs. The load reductions were evaluated with the catchment model GREEN and represented the impacts due to improved management of agriculture and wastewater treatment in all European river systems. The model ensemble, comprising 15 members, was used to assess changes to the core eutrophication indicators as defined within MSFD Descriptor 5. In nearly all marine regions, riverine load reductions led to reduced nutrient concentrations in the marine environment. However, regionally the nutrient input reductions led to an increase in the non-limiting nutrient in the water, especially in the case of phosphate concentrations in the Black Sea. Further core eutrophication indicators, such as chlorophyll-a, bottom oxygen and the Trophic Index TRIX, improved nearly everywhere, but the changes were less pronounced than for the inorganic nutrients. The model ensemble displayed strong consistency and robustness, as most if not all models indicated improvements in the same areas. There were substantial differences between the individual seas in the speed of response to the reduced nutrient loads. In the North Sea ensemble, a stable plateau was reached after only three years, while the simulation period of eight years was too short to obtain steady model results in the Baltic Sea. The ensemble exercise confirmed the importance of improved management of agriculture and wastewater treatments in the river catchments to reduce marine eutrophication. Several shortcomings were identified, the outcome of different approaches to compute the mean change was estimated and potential improvements are discussed to enhance policy support. Applying a model ensemble enabled us to obtain highly robust and consistent model results, substantially decreasing uncertainties in the scenario outcome.