Soaring birds use the energy available in the environment in the form of atmospheric uplifts, to subsidize their flight. Their dependence on soaring opportunities makes them extremely sensitive to anthropogenic wind energy development. Predictive modelling is now considered instrumental to forecast the impact of wind farms on single species of concern. However, as multiple species often coexist in the same area, there is clear need to overcome the limitations of single species approaches.
We looked for converging patterns in the way two obligate soaring species use the energy available in the landscape to soar, using movement data from 57 white storks, Ciconia ciconia, and 27 griffon vultures, Gyps fulvus. We first compared the soaring efficiency of the two species. We then tested the accuracy of topographic features, important correlates of collision risk in soaring birds, in predicting their soaring behaviour. We finally tested the transferability of soaring suitability models across species.
Topography alone can predict and map the soaring opportunities available to storks across Europe, but not as efficiently in vultures. Only 20.5% of the study area was suitable to both species to soar, suggesting the existence of species-specific requirements in the use of the landscape for soaring. Storks relied on uplift occurrence while vultures on uplift quality, needing stronger uplifts to support their higher body mass and wing loading.
Our results indicate that the flight of highly specialized soaring species is more dependent on atmospheric conditions than on static features, and that more knowledge is required to accurately predict their behaviour. Despite the superficially similar soaring behaviour, the two species have different environmental requirements, suggesting that energy landscapes are species-specific. Our models provide a base to explore the effects that changes in the landscape have on the flight behaviour of different soaring species and suggest that there is no reliable and responsible way to shortcut risk assessment in areas where multiple species might be at risk by anthropogenic structures.