Mapping World-Wide Distributions of Marine Mammal Species Using a Relative Environmental Suitability (Res) Model

K. Kaschner, R. Watson, A. Trites, D. Pauly, (2006). Marine Ecology Progress Series 316, 285-310.

We developed a large-scale habitat suitability modeling approach to map global distributions of 115 species of marine mammals. Predictions were generated by first assigning each species to broad-scale categories of habitat preferences with respect to depth, sea surface temperature and ice edge association based on synopses of published qualitative and quantitative habitat preference information. Using a global grid with 0.5 degree lat/long cell dimensions, we generated an index of the relative environmental suitability (RES) of each cell for a given species by relating quantified habitat preferences to locally averaged environmental conditions in a GIS modeling framework. RES predictions closely matched published maximum range extents for most species, suggesting that our model-based approach for identifying habitat represents a useful, more objective alternative to existing sketched distributional outlines. In addition, raster-based predictions provided more detailed information about heterogeneous patterns of potentially suitable habitat for species throughout their range. We validated RES model outputs for eleven species (northern fur seal, harbor porpoise, sperm whale, killer whale, hourglass dolphin, fin whale, humpback whale, blue whale and Antarctic minke whale) from a broad taxonomic and geographic range using at-sea sightings from dedicated surveys. Observed relative encounter rates and species-specific predicted environmental suitability were significantly and positively correlated for all, but one species. In comparison, observed encounter rates were correlated with < 1 % of 1000 simulated random data sets for all but two species. Mapping of suitable habitat for marine mammals using this environmental envelope model is helpful for evaluating current assumptions and knowledge about species? occurrences, especially for data-poor species. Moreover, RES modeling may help to focus research efforts on smaller geographic scales and usefully supplement other, statistical, habitat suitability models.