Sperm whale hotspots off western Ireland and the importance of dynamic variables as shown by a multiscale Bayesian Additive Regression Trees workflow

Abstract

Species distribution models are increasingly used to understand species' environmental preferences and habitat use as a means to inform management decisions. To identify important areas, mitigate impacts of anthropogenic activities, and forecast potential changes in habitat suitability under future climate conditions, emphasis should be placed on computing accurate and representative models from which reliable predictions can be derived, while ensuring that continued monitoring supports these predictions under increasing environmental uncertainty. In this study, we applied a Bayesian Additive Regression Trees modelling framework to data collected over the course of six seasonal passive acoustic surveys (2015-2016) along the Irish continental shelf break to assess habitat use by sperm whales, Physeter macrocephalus. Previous studies indicated that substantial numbers of sperm whales occur in Irish offshore waters, particularly along and beyond the shelf edge. It is likely that the area contains foraging habitats and that mature males also move through these waters when traveling between southern breeding grounds and northern feeding areas. However, more recent findings reported that females and immature individuals also occur in these habitats in significant numbers, indicating that the area supports a wider range of demographic groups. As a result, sperm whale presence in the region are likely to result from interactions between migrations and access to prey resources. The scale-dependent nature of those processes adds further complexities for the quantification of relationships between underlying environmental variables and species distribution. For this reason, we used a multiscale framework to investigate the influence of a set of topographic features and oceanographic processes acting as proxies for prey availability, on sperm whale occurrence. Occurrence was found to correlate with depth, slope gradient and slope orientation, as well as with distance to fronts, frontal strength, relative sea surface temperature, chlorophyll-a concentration and sea level anomaly. These variables were most informative at different scales, highlighting the value of multiscale approaches. This study shed light on the relative favourability of the region for sperm whales as well as on the complex interactions between sperm whales and their habitat, contributing towards future management and conservation efforts.