MEPS 548:263-275 (2016)  -  DOI: https://doi.org/10.3354/meps11663

ABSTRACT: There are significant challenges associated with mapping critical habitat for large, migratory species. The humpback whales of Oceania in the South Pacific are no exception, with their winter breeding grounds spanning >4000 km of ocean basin. This subpopulation is listed as endangered, but there are few systematic spatial data with which to prioritise specific areas for additional research or conservation. A few sites in Oceania have been the focus of long-term, non-systematic population surveys. Using the maximum entropy algorithm, we developed predictive habitat models for 2 such sites: American Samoa 2003-2010 (n = 300) and Tonga 1996-2007 (n = 475), using sightings of whale groups and environmental factors hypothesised to influence their space-use patterns. At both sites, shallow water was the best predictor of the spatial distribution of mother–calf pairs. In contrast, access to deep water was important for adult groups, and sea-floor slope and rugosity influenced habitat suitability for males engaged in acoustic breeding displays. Our study illustrates the value of predictive modelling for identifying habitat partitioning for specific sub-groups of a wider population. Similarities between habitat requirements predicted in our study to those identified for other populations suggest that the slow recovery of Oceania humpback whales cannot be attributed to unusual breeding-habitat needs; instead, there may be other factors influencing the slow increase in population size. We recommend that the modelling techniques utilised here be used to identify other breeding sites within Oceania for future research and conservation efforts across the South Pacific region.

KEY WORDS: Habitat · Maximum Entropy Modelling · Humpback whale · MPA · Megaptera novaeangliae