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Species Distribution Models are commonly used with surface dynamic environmental variables as proxies for prey distribution to characterise marine top predator habitats. For oceanic species that spend lot of time at depth, surface variables might not be relevant to predict deep-dwelling prey distributions. We hypothesised that descriptors of deep-water layers would better predict the deep-diving cetacean distributions than surface variables. We combined static variables and dynamic variables integrated over different depth classes of the water column into Generalised Additive Models to predict the distribution of sperm whales Physeter macrocephalus and beaked whales Ziphiidae in the Bay of Biscay, eastern North Atlantic. We identified which variables best predicted their distribution. Although the highest densities of both taxa were predicted near the continental slope and canyons, the most important variables for beaked whales appeared to be static variables and surface to subsurface dynamic variables, while for sperm whales only surface and deep-water variables were selected. This could suggest differences in foraging strategies and in the prey targeted between the two taxa. Increasing the use of variables describing the deep-water layers would provide a better understanding of the oceanic species distribution and better assist in the planning of human activities in these habitats. [ABSTRACT FROM AUTHOR]

Aim: Deep‐diving cetaceans are oceanic species exposed to multiple anthropogenic pressures including high intensity underwater noise, and knowledge of their distribution is crucial to manage their conservation. Due to intrinsic low densities, wide distribution ranges and limited presence at the sea surface, these species are rarely sighted. Pooling data from multiple visual surveys sharing a common line‐transect methodology can increase sightings but requires accounting for heterogeneity in protocols and platforms. Location: North Atlantic Ocean and Mediterranean Sea. Time period: 1998 to 2015. Major taxa: Ziphiidae; Physeteriidae; Kogiidae. Methods: About 1,240,000 km of pooled effort provided 630 sightings of ziphiids, 836 of physeteriids and 106 of kogiids. For each taxon, we built a hierarchical model to estimate the effective strip width depending on observation conditions and survey types. We then modelled relative densities in a generalized additive modelling framework. Geographical predictions were limited to interpolations identified with a gap analysis of environmental space coverage. Results: Deeper areas of the North Atlantic gyre were mostly environmental extrapolation in the predictions, thereby highlighting gaps in sampling across the different surveys. For the three species groups, the highest relative densities were predicted along continental slopes, particularly in the western North Atlantic Ocean where the Gulf Stream creates dynamic frontal zones and eddies. Main conclusions: Pooling a large number of surveys provided the first basin‐wide models of distribution for deep‐diving cetaceans, including several data‐deficient taxa, across the North Atlantic Ocean and the Mediterranean Sea. These models can help the conservation of elusive and poorly known marine megafauna. [ABSTRACT FROM AUTHOR]