Predicting when and where cetaceans are likely to occur can inform efforts to mitigate the impacts of anthropogenic activities. Recently developed dynamical forecasting systems provide the opportunity to use forecasted environmental variables to predict distributions of cetaceans on subseasonal time scales (lead times of days to weeks). In the Northeast United States (NEUS), cetaceans are impacted by many anthropogenic activities which are typically clustered in space and time, including vessel strikes, entanglement in fishing gear, naval exercises, and offshore energy development. Cetaceans are highly mobile species, and environmental variabilities from subseasonal to seasonal (S2S) timescale can influence their distribution. Our objectives were to develop predictions of cetacean habitat use using subseasonal forecasts from climate models and to assess the utility of these predictions for identifying times and places of high risk for anthropogenic threats. We assessed the prediction skill for sea surface temperature (SST) forecasts from the SubX system, a modeling project focused on improving subseasonal predictions. We developed generalized additive models (GAMs) for fin whales (Balaenoptera physalus) and humpback whales (Megaptera novaeangliae) based on environmental covariates and used SubX SST predictions to generate probabilistic predictions of cetacean distributions.
Results/Conclusions
We present forecasts for fin and humpback whales with lead times of 5 to 30 days along with estimates of forecast skill for SubX SST predictions in the NEUS. Changes in predicted distributions of fin and humpback whales were detectable at weekly time scales, and changes were especially apparent during spring (March-May) when SST warms rapidly. SubX forecast skill in the NEUS was high for short lead times (approximately 7 days), but decreased as the lead time increased, particularly in regions influenced by Gulf Stream dynamics. This suggests that the predictive capacity for cetacean models will be highest on the shelf at short lead times. Thus, subseasonal forecasts may be most useful for identifying changes in cetacean distributions in species that undergo migrations in spring, are dependent on temperature-dependent prey migrations, or that occupy coastal and mid-shelf regions. By predicting times and places where cetaceans are likely to occur, subseasonal forecasts of cetacean distributions could provide effective tools for managers at short time scales, but the utility of these forecasts varies based on species-specific habitat use and variability. This work highlights the importance of considering both forecast skill and species-specific behaviors influencing habitat use when developing ecological forecasts.