Modelling deep divers habitat from whale watching data: can it work?

Cuvier’s beaked whale is one of the less known species worldwide. Its elusive behaviour together with its deep diver character make collecting presence and distribution data even more difficult than for other species. As a consequence effective habitat modelling is challenging and usually based on few data. Whale watching vessels are widely recognized as a suitable platform for collecting ample dataset about cetacean distribution, but do they perform well even with elusive species? In this study we used Cuvier’s beaked whale distribution data collected during whale watching trips in the Ligurian Sea, (NW Mediterranean Sea) from 2004 to 2007. Generalized Additive Models have been used to describe species habitat preferences and in particular to inspect the role of submarine canyons in structuring its distribution. Different topographic variables have been used as environmental descriptors and a novel GIS methodologies have been applied for the identification of canyon axis and canyon basins. The model has been built using a fine resolution grid (1x1 km) in order to deal with complex topography of the study area. In order to minimize bias arising from the use of opportunistic dataset, effort data spatial and temporal coverage have first been analyzed. An ecological buffer has been applied to sighting positions in order to take into account the false absence bias due to species diving behaviour. The final model highlighted two different preferred habitat for the species: a canyon-related one as well as a pelagic one. The model was able to explain 73.8% of deviance. Model performance has been evaluated with an independent dataset and the final model accuracy resulted to be 0.63, with a sensitivity of 0.9 and a specificity of 0.62. The applied methodology allowed for an effective use of data collected from platform of opportunity in the habitat modelling of Cuvier’s beaked whale.