@article{Weidenmuller2019-08Recon-46611,
  year={2019},
  doi={10.1007/s00265-019-2709-5},
  title={Reconsidering response threshold models : short-term response patterns in thermoregulating bumblebees},
  number={8},
  volume={73},
  issn={0340-5443},
  journal={Behavioral Ecology and Sociobiology},
  author={Weidenmüller, Anja and Chen, Rui and Meyer, Bernd},
  note={Article Number: 112}
}

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    <dc:creator>Meyer, Bernd</dc:creator>
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    <dc:contributor>Meyer, Bernd</dc:contributor>
    <dcterms:issued>2019-08</dcterms:issued>
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    <dc:contributor>Chen, Rui</dc:contributor>
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    <dc:creator>Chen, Rui</dc:creator>
    <dcterms:abstract xml:lang="eng">Social insect colonies distribute their workforce with amazing flexibility across a large array of diverse tasks under fluctuating external conditions and internal demands. Deciphering the individual rules of task selection and task performance is at the heart of understanding how colonies can achieve this collective feature. Models play an important role in this endeavor, as they allow us to investigate how the rules of individual behavior give rise to emergent patterns at the colony level. Modulation of individual behavior occurs at many different timescales and to successfully use a model we need to ensure that it applies on the timescale under observation. Here, we focus on short timescales and ask the question whether the most commonly used class of models (response threshold models) adequately describes behavioral modulation on this timescale. We study the fanning behavior of bumblebees on temperature-controlled brood dummies and investigate the effect of (i) stimulus intensity, (ii) repeated task performance, and (iii) task performance feedback. We analyze the timing patterns (rates of task engagement and task disengagement) using survival analysis. Our results show that stimulus intensity does not significantly influence individual task investment at these comparably short timescales. In contrast, repeated task performance and task performance feedback affect individual task investment. We propose an explicitly time-resolved individual-based model and simulate this model to study how patterns of individual task engagement influence task involvement at the group level, finding support for the hypothesis that regulation mechanisms at different timescales can improve performance at the group level in dynamic environments.</dcterms:abstract>
    <dc:creator>Weidenmüller, Anja</dc:creator>
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