@article{steenbeekMakingSpatialtemporalMarine2021,

title = {Making Spatial-Temporal Marine Ecosystem Modelling Better \textendash A Perspective},

author = {Jeroen Steenbeek and Joe Buszowski and David Chagaris and Villy Christensen and Marta Coll and Elizabeth A. Fulton and Stelios Katsanevakis and Kristy A. Lewis and Antonios D. Mazaris and Diego Macias and Kim Mutsert and Greig Oldford and Maria Grazia Pennino and Chiara Piroddi and Giovanni Romagnoni and Natalia Serpetti and Yunne-Jai Shin and Michael A. Spence and Vanessa Stelzenm\"{u}ller},

doi = {10.1016/j.envsoft.2021.105209},

issn = {1364-8152},

year  = {2021},

date = {2021-11-01},

urldate = {2021-10-05},

journal = {Environmental Modelling \& Software},

volume = {145},

pages = {105209},

abstract = {Marine Ecosystem Models (MEMs) provide a deeper understanding of marine ecosystem dynamics. The United Nations Decade of Ocean Science for Sustainable Development has highlighted the need to deploy these complex mechanistic spatial-temporal models to engage policy makers and society into dialogues towards sustainably managed oceans. From our shared perspective, MEMs remain underutilized because they still lack formal validation, calibration, and uncertainty quantifications that undermines their credibility and uptake in policy arenas. We explore why these shortcomings exist and how to enable the global modelling community to increase MEMs' usefulness. We identify a clear gap between proposed solutions to assess model skills, uncertainty, and confidence and their actual systematic deployment. We attribute this gap to an underlying factor that the ecosystem modelling literature largely ignores: technical issues. We conclude by proposing a conceptual solution that is cost-effective, scalable and simple, because complex spatial-temporal marine ecosystem modelling is already complicated enough.},

keywords = {capacity building, Opinion, spatial-temporal marine ecosystem modelling, systematic model calibration, systematic skill assessments},

pubstate = {published},

tppubtype = {article}

}

@article{steenbeek_making_2021,

title = {Making spatial-temporal marine ecosystem modelling better \textendash A perspective},

author = {Jeroen Steenbeek and Joe Buszowski and David Chagaris and Villy Christensen and Marta Coll and Elizabeth A. Fulton and Stelios Katsanevakis and Kristy A. Lewis and Antonios D. Mazaris and Diego Macias and Kim Mutsert and Greig Oldford and Maria Grazia Pennino and Chiara Piroddi and Giovanni Romagnoni and Natalia Serpetti and Yunne-Jai Shin and Michael A. Spence and Vanessa Stelzenm\"{u}ller},

url = {https://www.sciencedirect.com/science/article/pii/S1364815221002516},

doi = {10.1016/j.envsoft.2021.105209},

issn = {1364-8152},

year  = {2021},

date = {2021-11-01},

urldate = {2021-10-05},

journal = {Environmental Modelling \& Software},

volume = {145},

pages = {105209},

abstract = {Marine Ecosystem Models (MEMs) provide a deeper understanding of marine ecosystem dynamics. The United Nations Decade of Ocean Science for Sustainable Development has highlighted the need to deploy these complex mechanistic spatial-temporal models to engage policy makers and society into dialogues towards sustainably managed oceans. From our shared perspective, MEMs remain underutilized because they still lack formal validation, calibration, and uncertainty quantifications that undermines their credibility and uptake in policy arenas. We explore why these shortcomings exist and how to enable the global modelling community to increase MEMs’ usefulness. We identify a clear gap between proposed solutions to assess model skills, uncertainty, and confidence and their actual systematic deployment. We attribute this gap to an underlying factor that the ecosystem modelling literature largely ignores: technical issues. We conclude by proposing a conceptual solution that is cost-effective, scalable and simple, because complex spatial-temporal marine ecosystem modelling is already complicated enough.},

keywords = {capacity building, Opinion, spatial-temporal marine ecosystem modelling, systematic model calibration, systematic skill assessments},

pubstate = {published},

tppubtype = {article}

}