Literature DB >> 19029598

Stochastic resonance and the evolution of Daphnia foraging strategy.

Nathan D Dees1, Sonya Bahar, Frank Moss.   

Abstract

Search strategies are currently of great interest, with reports on foraging ranging from albatrosses and spider monkeys to microzooplankton. Here, we investigate the role of noise in optimizing search strategies. We focus on the zooplankton Daphnia, which move in successive sequences consisting of a hop, a pause and a turn through an angle. Recent experiments have shown that their turning angle distributions (TADs) and underlying noise intensities are similar across species and age groups, suggesting an evolutionary origin of this internal noise. We explore this hypothesis further with a digital simulation (EVO) based solely on the three central Darwinian themes: inheritability, variability and survivability. Separate simulations utilizing stochastic resonance (SR) indicate that foraging success, and hence fitness, is maximized at an optimum TAD noise intensity, which is represented by the distribution's characteristic width, sigma. In both the EVO and SR simulations, foraging success is the criterion, and the results are the predicted characteristic widths of the TADs that maximize success. Our results are twofold: (1) the evolving characteristic widths achieve stasis after many generations; (2) as a hop length parameter is changed, variations in the evolved widths generated by EVO parallel those predicted by SR. These findings provide support for the hypotheses that (1) sigma is an evolved quantity and that (2) SR plays a role in evolution.

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Year:  2008        PMID: 19029598     DOI: 10.1088/1478-3975/5/4/044001

Source DB:  PubMed          Journal:  Phys Biol        ISSN: 1478-3967            Impact factor:   2.583


  4 in total

Review 1.  The benefits of noise in neural systems: bridging theory and experiment.

Authors:  Mark D McDonnell; Lawrence M Ward
Journal:  Nat Rev Neurosci       Date:  2011-06-20       Impact factor: 34.870

2.  From Lévy to Brownian: a computational model based on biological fluctuation.

Authors:  Surya G Nurzaman; Yoshio Matsumoto; Yutaka Nakamura; Kazumichi Shirai; Satoshi Koizumi; Hiroshi Ishiguro
Journal:  PLoS One       Date:  2011-02-03       Impact factor: 3.240

3.  Stochastic resonance and 'gamma band' synchronization in the human visual system.

Authors:  Simone Carozzo; Walter G Sannita
Journal:  IBRO Neurosci Rep       Date:  2021-03-19

4.  Stochastic optimal foraging: tuning intensive and extensive dynamics in random searches.

Authors:  Frederic Bartumeus; Ernesto P Raposo; Gandhimohan M Viswanathan; Marcos G E da Luz
Journal:  PLoS One       Date:  2014-09-12       Impact factor: 3.240

  4 in total

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