Qian Song S.

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Qian
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Song S.
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  • Article
    Techniques for cetacean–habitat modeling
    (Inter-Research, 2006-04-03) Redfern, J. V. ; Ferguson, M. C. ; Becker, E. A. ; Hyrenbach, K. D. ; Good, Caroline P. ; Barlow, Jay ; Kaschner, K. ; Baumgartner, Mark F. ; Forney, K. A. ; Ballance, L. T. ; Fauchald, P. ; Halpin, Patrick N. ; Hamazaki, T. ; Pershing, Andrew J. ; Qian, Song S. ; Read, Andrew J. ; Reilly, S. B. ; Torres, Leigh ; Werner, Francisco E.
    Cetacean–habitat modeling, although still in the early stages of development, represents a potentially powerful tool for predicting cetacean distributions and understanding the ecological processes determining these distributions. Marine ecosystems vary temporally on diel to decadal scales and spatially on scales from several meters to 1000s of kilometers. Many cetacean species are wide-ranging and respond to this variability by changes in distribution patterns. Cetacean–habitat models have already been used to incorporate this variability into management applications, including improvement of abundance estimates, development of marine protected areas, and understanding cetacean–fisheries interactions. We present a review of the development of cetacean–habitat models, organized according to the primary steps involved in the modeling process. Topics covered include purposes for which cetacean–habitat models are developed, scale issues in marine ecosystems, cetacean and habitat data collection, descriptive and statistical modeling techniques, model selection, and model evaluation. To date, descriptive statistical techniques have been used to explore cetacean–habitat relationships for selected species in specific areas; the numbers of species and geographic areas examined using computationally intensive statistic modeling techniques are considerably less, and the development of models to test specific hypotheses about the ecological processes determining cetacean distributions has just begun. Future directions in cetacean–habitat modeling span a wide range of possibilities, from development of basic modeling techniques to addressing important ecological questions.
  • Article
    Whale distribution in relation to prey abundance and oceanographic processes in shelf waters of the Western Antarctic Peninsula
    (Inter-Research, 2006-07-18) Friedlaender, Ari S. ; Halpin, Patrick N. ; Qian, Song S. ; Lawson, Gareth L. ; Wiebe, Peter H. ; Thiele, Deb ; Read, Andrew J.
    The Western Antarctic Peninsula (WAP) is a biologically rich area supporting large standing stocks of krill and top predators (including whales, seals and seabirds). Physical forcing greatly affects productivity, recruitment, survival and distribution of krill in this area. In turn, such interactions are likely to affect the distribution of baleen whales. The Southern Ocean GLOBEC research program aims to explore the relationships and interactions between the environment, krill and predators around Marguerite Bay (WAP) in autumn 2001 and 2002. Bathymetric and environmental variables including acoustic backscattering as an indicator of prey abundance were used to model whale distribution patterns. We used an iterative approach employing (1) classification and regression tree (CART) models to identify oceanographic and ecological variables contributing to variability in humpback Megaptera novaeangliae and minke Balaenoptera acutorstrata whale distribution, and (2) generalized additive models (GAMs) to elucidate functional ecological relationships between these variables and whale distribution. The CART models indicated that the cetacean distribution was tightly coupled with zooplankton acoustic volume backscatter in the upper (25 to 100 m), and middle (100 to 300 m) portions of the water column. Whale distribution was also related to distance from the ice edge and bathymetric slope. The GAMs indicated a persistent, strong, positive relationship between increasing zooplankton volume and whale relative abundance. Furthermore, there was a lower limit for averaged acoustic volume backscatter of zooplankton below which the relationship between whales and prey was not significant. The GAMs also supported an annual relationship between whale distribution, distance from the ice edge and bathymetric slope, suggesting that these are important features for aggregating prey. Our results demonstrate that during the 2 yr study, whales were consistently and predictably associated with the distribution of zooplankton. Thus, humpback and minke whales may be able to locate physical features and oceanographic processes that enhance prey aggregation.