High-resolution spatiotemporal forecasting of the European crane migration

•Observations of speed and direction improve short-term bird migration forecasts.•Wind forecasts further improve the range of individual bird migration forecasts.•Altitude changes may be worthwhile to add in the models as indirect driver of speed.•Mixed flight modes may cause slower flight speeds than forecasted by our model.•Forecast errors in direction are more problematic than speed for most applications. In this paper we present three different models to forecast bird migration. They are species-specific individual-based models that operate on a high spatiotemporal resolution (kilometres, 15 min-hours), as an addition to radar-based migration forecast models that currently exist. The models vary in complexity, and use GPS-tracked location, flying direction and speed, and/or wind data to forecast migration speed and direction. Our aim is to quantitatively evaluate the forecasting performance and assess which metrics improve forecasts at different ranges. We test the models through cross-validation using GPS tracks of common cranes during spring and autumn migration. Our results show that recordings of flight speed and direction improve the accuracy of forecasts on the short range (