K. Kaschner, R. Watson, C. MacLeod, D. Pauly, (2003).  Paper published in proceedings of the Quantitative Seminar Series, University of Washington, Seattle, Washington, USA.

The delineation of geographic ranges for cryptic marine mammal species is often subjective and limited to roughly sketched outlines encompassing all known records. We developed a new, more quantitative approach to map the distribution of marine species based on existing knowledge about habitat preferences and demonstrate this approach on beaked whales (Ziphiidae, Cetacea), one of the least known families of mammals. We used available published information about species-specific habitat preferences with respect to depth, sea surface temperature and ice-edge association to assign species to broad-scale, quantified habitat categories. Using a raster-based GIS model, we related the quantified preferences to locally averaged oceanographic conditions. Predicted distributions closely matched published information about maximum range extents for most species, encompassing at least 90 % of all known sighting records. In addition, raster-based predictions provided more detailed information about the relative suitability of the environment for a species throughout its range. To test the validity of the approach, we developed a simulation model of ziphiid strandings using a global data set of residual ocean currents. Relative probabilities of strandings were generated based on two different input distributions: species-specific habitat suitability predictions and a uniform distribution based on published information. Simulated strandings based on habitat suitability predictions produced significant correlations with observed strandings for more than twice as many species (11 of 21 ziphiid species) as those generated based on uniform distributions (5/21). Thus, results provided support for our quantitative approach to map species distributions. The visualization of potentially important habitat areas based on this GIS approach will help to re-evaluate current assumptions and knowledge about marine mammal distribution. This in turn will help focus research efforts in the context of the impact of underwater noise pollution on ziphiids and other management issues.