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Information on animal abundance and distribution is at the cornerstone of many wildlife andconservation strategies. However, these data can be difficult and costly to obtain for cetacean species. Theexpense of sufficient ship time to conduct design-unbiased line transect surveys may be simply out of reachfor researchers in many countries, which nonetheless grapple with problems of conservation of endangeredspecies, by-catch of small cetaceans in commercial fisheries, and progression toward ecosystem-basedfisheries management. Recently developed spatial modeling techniques show promise for estimatingwildlife abundance using non-randomized surveys, but have yet to receive much field-testing in areas wheredesigned surveys have also been conducted. Effort and sightings data were collected along 9 650 km oftransects aboard ships of opportunity in the Southern Ocean during the austral summers of 2000-2001 and2001-2002. Generalized additive models with generalized cross-validation were used to expressheterogeneity of cetacean sightings as functions of spatial covariates. Models were used to map predicteddensities and to estimate abundance of humpback, minke, and fin whales in the Drake Passage and alongthe Antarctic Peninsula. All species' distribution maps showed strong density gradients, which were robustto jackknife resampling when each of 14 trips was removed sequentially with replacement. Loopedanimations of model predictions of whale density illustrate uncertainty in distribution estimates in a waythat is informative to non-scientists. The best abundance estimate for humpback whales was 1 829 (95%CI: 978-3 422). Abundance of fin whales was 4 487 (95% CI: 1 326-15 179) and minke whales was 1,544(95% CI: 1,221-1,953). These estimates agreed roughly with those reported from a designed surveyconducted in the region during the previous austral summer. These estimates assumed that all animals onthe trackline were detected, but preliminary results suggest that any negative bias due to violation of thisassumption was likely small. Similarly, current methodological limitations prohibit inclusion of all knownsources of uncertainty in the favored variance estimator. Meanwhile, our approach can be seen generallyas an inexpensive pilot study to identify areas of predicted high density that could be targeted to: informstratified designs for future line transect surveys, making them less expensive and more precise; increaseefficiency of future photo-identification or biopsy studies; identify candidate time-area fisheries closuresto minimize by-catch; or direct ecotourism activities. The techniques are likely to apply to areas wherefunding is limiting, where cetacean studies or wilderness-based tourism are just beginning, or in regionswhere even a very rough estimate of animal abundance is needed for conservation or management purposes.