4.7 Article

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

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FRONTIERS IN MARINE SCIENCE
卷 8, 期 -, 页码 -

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FRONTIERS MEDIA SA
DOI: 10.3389/fmars.2021.777427

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species distribution model; habitat preference; spawning; North Atlantic; climate variability; ecological forecast; prediction; MPI-ESM

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This study explores the use of a dynamic Earth System Model (ESM) to forecast the suitable spawning habitat of blue whiting and finds that retrospective forecasts based on predicted salinity outperform persistence forecasts. Retrospective forecasts with the ESM show a better ability to differentiate between suitable and unsuitable habitat compared to persistence forecasts.
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.

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