Exploring the Potential of Forecasting Fish Distributions in the North East Atlantic With a Dynamic Earth System Model, Exemplified by the Suitable Spawning Habitat of Blue Whiting

• Published in: Frontiers in Marine Science
• Main Authors: Miesner, Anna K., Brune, Sebastian, Pieper, Patrick, Koul, Vimal, Baehr, Johanna, Schrum, Corinna
• Other Authors: Deutsche Forschungsgemeinschaft
• Format: Article in Journal/Newspaper
• Language: unknown
• Published: Frontiers Media SA 2022
• Subjects: Ocean Engineering; Water Science and Technology; Aquatic Science; Global and Planetary Change; Oceanography; Rockall Plateau; North East Atlantic
• Online Access: http://dx.doi.org/10.3389/fmars.2021.777427; https://www.frontiersin.org/articles/10.3389/fmars.2021.777427/full

Local oceanographic variability strongly influences the spawning distribution of blue whiting ( Micromesistius poutassou ). Here, we explore the potential of using a dynamic Earth System Model (ESM) to forecast the suitable spawning habitat of blue whiting to assist management. Retrospective forecasts of temperature and salinity with the Max Planck Institute ESM (MPI-ESM) show significant skill within blue whiting’s spawning region and spawning depth (250–600 m) during the peak months of spawning. While persistence forecasts perform well at shorter lead times (≤2 years), retrospective forecasts with MPI-ESM are clearly more skilful than persistence in predicting salinity at longer lead times. Our results indicate that retrospective forecasts of the suitable spawning habitat of blue whiting based on predicted salinity outperform those based on calibrated species distribution models. In particular, we find high predictive skill for the suitable spawning habitat based on salinity predictions around one year ahead in the area of Rockall-Hatton Plateau. Our approach shows that retrospective forecasts with MPI-ESM show a better ability to differentiate between the presence and absence of suitable habitat over Rockall Plateau compared to persistence. Our study highlights that physical-biological forecasts based on ESMs could be crucial for developing distributional forecasts of marine organisms in the North East Atlantic.