4.7 Article

Making spatial-temporal marine ecosystem modelling better-A perspective

期刊

ENVIRONMENTAL MODELLING & SOFTWARE
卷 145, 期 -, 页码 -

出版社

ELSEVIER SCI LTD
DOI: 10.1016/j.envsoft.2021.105209

关键词

Opinion; Spatial-temporal marine ecosystem modelling; Capacity building; Systematic skill assessments; Systematic model calibration

资金

  1. EuroMarine 2018 call for Foresight Workshops and Working Groups proposals
  2. Spanish Ministry of Science and Innovation [PID2020-118097RB-I00]
  3. European Union [869300, 817578]
  4. `Severo Ochoa Centre of Excellence' accreditation [CEX2019-000928-S]
  5. German Federal Ministry of Education and Research (BMBF) [01LC1823D]
  6. NSERC [RGPIN-2019-04901]
  7. NSERC Mitacs Accelerate Fellowship [IT09266]
  8. IOF Ocean Leaders Fellowship
  9. DFO
  10. Biodiversa and Belmont Forum project SOMBEE (BiodivScen ERA-Net COFUND programme) [ANR-18-EBI4-0003-01]
  11. Pew marine fellows programme
  12. Agence Nationale de la Recherche (ANR) [ANR-18-EBI4-0003] Funding Source: Agence Nationale de la Recherche (ANR)

向作者/读者索取更多资源

Marine Ecosystem Models (MEMs) provide a deeper understanding of marine ecosystem dynamics, but are underutilized in policy arenas due to lack of formal validation and uncertainty quantifications. Addressing technical issues and proposing a simple, scalable conceptual solution is key to increasing the usefulness of MEMs.
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.

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