Title

Orb-web spiders as Bayesian learners

Publication Date

4-30-2019

Document Type

Article

Department

Mathematics and Statistics

Disciplines

Animal Sciences | Science and Mathematics Education

Publication Title

The Science of Nature

Volume

106

DOI

10.1007/s00114-019-1615-z

Abstract

Orb-web spiders typically construct their webs with a vertical asymmetry: the hub, or meeting point of the radial threads, is often above the geometric center of the web. Previous explanations for this asymmetry involve differences in up/down running speed and mass, but fail to account adequately for ontogenetic changes in vertical asymmetry. The current article argues that the hub location is determined so as to maximize the expected number of prey and is updated, partially, in response to predation experience. A Bayesian model of spider learning from predation experience is presented and shown to be alone a better fit than spider mass to an existing empirical dataset. Combining this Bayesian model with the extant results on spider mass and differential running speeds ought to provide more thorough explanations for observed web asymmetry. The results of this theory-driven work positions orb-web spiders as a potentially ideal study family for animal Bayesian learning: predation experience is manifest in the spider’s orb-web geometry, which is updated frequently, and is readily quantifiable. Spider orb webs ought to facilitate further theoretical and empirical work in animal cognition and learning.

Keywords

Orb-web spiders, Bayesian learning, Spider web geometry, Animal cognition

Comments

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