Recent years have seen a rapid expansion in the ability of earth system models to describe and predict the physical state of the ocean. Skilful forecasts ranging from seasonal (3 months) to decadal (5-10 years) time scales are now a reality. With the advance of these forecasts of ocean physics, the first generation of marine ecological forecasts has started to emerge. Such forecasts are potentially of great value in the management of living marine resources and for all of those who are dependent on the ocean for both nutrition and their livelihood; however, this is still a field in its infancy. We review the state of the art in this emerging field and identify the lessons that can be learnt and carried forward from these pioneering efforts. The majority of this first wave of products are forecasts of spatial distributions, possibly reflecting the inherent suitability of this response variable to the task of forecasting. Promising developments are also seen in forecasting fish-stock recruitment where, despite well-recognized challenges in understanding and predicting this response, new process knowledge and model approaches that could form a basis for forecasting are becoming available. Forecasts of phenology and coral-bleaching events are also being applied to monitoring and industry decisions. Moving marine ecological forecasting forward will require striking a balance between what is feasible and what is useful. We propose here a set of criteria to quickly identify "low-hanging fruit" that can potentially be predicted; however, ensuring the usefulness of forecast products also requires close collaboration with actively engaged end-users. Realizing the full potential of marine ecological forecasting will require bridging the gaps between marine ecology and climatology on the one-hand, and between science and end-users on the other. Nevertheless, the successes seen thus far and the potential to develop further products suggest that the field of marine ecological forecasting can be expected to flourish in the coming years.

The spawning distribution of blue whiting (Micromesistius poutassou) has varied considerably between years, but quantitative understanding of the processes driving this change is lacking. Using 55 years of larval‐observations from the wide‐ranging Continuous Plankton Recorder (CPR) survey, we show that changes in the spawning distribution of blue whiting are associated with variations in the marine environment and particularly salinity. We first corroborated previously reported associations between variations in the spawning distribution and environmental regimes in the spawning region based on space‐time interpolation models. We then applied species distribution models to quantify the linkage between the environment and the distribution of blue whiting larvae and verified these model results against independent fisheries and scientific survey data. Models incorporating salinity in the spawning region gave the best agreement with data, with observations of larvae in the CPR being limited to a window of salinities between 35.3 and 35.5. Changes in the area of suitable spawning habitat (estimated here to be up to 2.5 times) can therefore be understood as arising from the spread of saline subtropical water masses throughout the spawning region due to a weak North Atlantic subpolar gyre. We postulate that blue whiting actively select optimum oceanographic conditions to deliver their eggs to enhance their offsprings likelihood of survival and thereby their fitness. The knowledge derived here, together with the high predictability of salinity at depth in the North‐East Atlantic, can potentially form the basis for forecasting the spawning distribution of this species.

Many fish and marine organisms are responding to our planet’s changing climate by shifting their distribution. Such shifts can drive international conflicts and are highly problematic for the communities and businesses that depend on these living marine resources. Advances in climate prediction mean that in some regions the drivers of these shifts can be forecast up to a decade ahead, although forecasts of distribution shifts on this critical time-scale, while highly sought after by stakeholders, have yet to materialise. Here, we demonstrate the application of decadal-scale climate predictions to the habitat and distribution of marine fish species. We show statistically significant forecast skill of individual years that outperform baseline forecasts 3–10 years ahead; forecasts of multi-year averages perform even better, yielding correlation coefficients in excess of 0.90 in some cases. We also demonstrate that the habitat shifts underlying conflicts over Atlantic mackerel fishing rights could have been foreseen. Our results show that climate predictions can provide information of direct relevance to stakeholders on the decadal-scale. This tool will be critical in foreseeing, adapting to and coping with the challenges of a changing future climate, particularly in the most ocean-dependent nations and communities.

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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.