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Area of Science:

  • Ecosystem modeling
  • Marine ecology
  • Ecological forecasting

Background:

  • Global ecosystem changes necessitate reliable models for management.
  • Skill assessment of complex marine ecosystem models is underdeveloped.
  • Evaluating model reliability is key to informed environmental management.

Purpose of the Study:

  • To assess the skill of the Northeast U.S. (NEUS) Atlantis marine ecosystem model.
  • To compare 10-year forecast skill with a 40-year hindcast.
  • To establish best-practice approaches for end-to-end ecosystem model skill assessment.

Main Methods:

  • Compared 10-year model forecasts with observed data for the NEUS Atlantis model.
  • Utilized multiple statistical metrics (e.g., RMSE, correlation) to measure skill.
  • Analyzed time-series data including species biomass and fisheries landings.

Main Results:

  • The NEUS Atlantis model demonstrated above-average performance for key species.
  • Forecast skill was comparable to hindcast skill, showing stable performance.
  • Model skill assessment is feasible and advisable for complex ecosystem models.

Conclusions:

  • Skill assessment of marine ecosystem models is possible and necessary for strategic management.
  • The developed methods can improve operational use and development of predictive models.
  • Findings are applicable beyond ecology to fields like economics and risk assessment.