Random search with resetting as a strategy for optimal pollination

Tal Robin, Lilach Hadany, and Michael Urbakh
Phys. Rev. E 99, 052119 – Published 15 May 2019

Abstract

The problem of pollination is unique among a wide scope of search problems, since it requires optimization of benefits for both the searcher (pollinator) and its targets (plants). To address this challenge, we propose a pollination model which is based on a framework of first passage under stochastic restart. We derive equations for the search time and number of visited plants as functions of the distribution of nectar in the plant population and of the probability that a pollinator will leave the plant after examining a flower, thus effectively restarting the search. We demonstrate that nectar variation in plants serves as a driving force for pollination and establish conditions required for optimal pollination, which provides an efficient pollinator search strategy and the maximum number of plants visited by the pollinator.

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  • Received 28 November 2018

DOI:https://doi.org/10.1103/PhysRevE.99.052119

©2019 American Physical Society

Physics Subject Headings (PhySH)

  1. Research Areas
Interdisciplinary Physics

Authors & Affiliations

Tal Robin1, Lilach Hadany2, and Michael Urbakh1,*

  • 1School of Chemistry, The Raymond and Beverly Sackler Faculty of Exact Sciences and The Sackler Center for Computational Molecular and Materials Science, Tel Aviv University, Tel Aviv 6997801, Israel
  • 2School of Molecular Biology and Ecology of Plants, The George S. Wise Faculty of Life Sciences, Tel Aviv University, Tel Aviv 6997801, Israel

  • *Corresponding author: urbakh@post.tau.ac.il

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Issue

Vol. 99, Iss. 5 — May 2019

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