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Doligez, B., Danchin, E., & Clobert, J. (2002). Public information and breeding habitat selection in a wild bird population. Science, 297(5584), 1168–1170.
Abstract: According to the “public information” hypothesis, some animal species may monitor the current reproductive success of conspecifics to assess local habitat quality and to choose their own subsequent breeding site. To test this hypothesis experimentally, we manipulated two components of public information, the mean number of offspring raised locally (“quantity”) and their condition (“quality”), in the collared flycatcher Ficedula albicollis. Immigration rate decreased with local offspring quantity but did not depend on local offspring quality, suggesting that immigrants are deprived of information regarding local quality. Conversely, emigration rate increased both when local offspring quantity or quality decreased, suggesting that residents can use both components of public information.
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Weir, A. A. S., Chappell, J., & Kacelnik, A. (2002). Shaping of hooks in New Caledonian crows. Science, 297(5583), 981.
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Abstract: Animals process sensory information according to specific computational rules and, subsequently, form representations of their environments that form the basis for decisions and choices. The specific computational rules used by organisms will often be evolutionarily adaptive by generating higher probabilities of survival, reproduction, and resource acquisition. Experiments with enclosed colonies of bumblebees constrained to foraging on artificial flowers suggest that the bumblebee's cognitive architecture is designed to efficiently exploit floral resources from spatially structured environments given limits on memory and the neuronal processing of information. A non-linear relationship between the biomechanics of nectar extraction and rates of net energetic gain by individual bees may account for sensitivities to both the arithmetic mean and variance in reward distributions in flowers. Heuristic rules that lead to efficient resource exploitation may also lead to subjective misperception of likelihoods. Subjective probability formation may then be viewed as a problem in pattern recognition subject to specific sampling schemes and memory constraints.
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