4.5 Article

Can environmental heterogeneity explain individual foraging variation in wild bottlenose dolphins (Tursiops sp.)?

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BEHAVIORAL ECOLOGY AND SOCIOBIOLOGY
卷 61, 期 5, 页码 679-688

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SPRINGER
DOI: 10.1007/s00265-006-0296-8

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foraging; bottlenose dolphins; ecological variation; social learning

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Because behavioral variation within and among populations may result from ecological, social, genetic and phenotypic differences, identifying the mechanism(s) responsible is challenging. Observational studies typically examine social learning by excluding ecological and genetic factors, but this approach is insufficient for many complex behaviors associated with substantial environmental variation. Indian Ocean bottlenose dolphins (Tursiops sp.) in Shark Bay, Western Australia show individual differences in foraging tactics, including possible tool use with marine sponges and social learning may be responsible for this diversity. However, the contributions of ecological factors to the development of these foraging tactics were not previously investigated. Here, we determined the relationship between ecological variables and foraging tactics and assessed whether differences in habitat use could explain individual differences in foraging tactics. We monitored 14 survey zones to identify how foraging tactics were spatially distributed and matched behavioral data to the ecological variables within each zone. Three of four foraging tactics were significantly correlated with ecological characteristics such as seagrass biomass, water depth, presence of marine sponges and season. Further, individual differences in habitat use were associated with some tactics. However, several tactics overlapped spatially and previous findings suggest demographic and social factors also contribute to the individual variation in this population. This study illustrates the importance of environmental heterogeneity in shaping foraging diversity and shows that investigating social learning by ruling out alternative mechanisms may often be too simplistic, highlighting the need for methods incorporating the relative contributions of multiple factors.

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