Bedoukian   RussellIPM   RussellIPM   Piezoelectric Micro-Sprayer


Home
Animal Taxa
Plant Taxa
Semiochemicals
Floral Compounds
Semiochemical Detail
Semiochemicals & Taxa
Synthesis
Control
Invasive spp.
References

Abstract

Guide

Alphascents
Pherobio
InsectScience
E-Econex
Counterpart-Semiochemicals
Print
Email to a Friend
Kindly Donate for The Pherobase

« Previous AbstractThe master regulator MAT1-1-1 of fungal mating binds to its targets via a conserved motif in the human pathogen Aspergillus fumigatus    Next AbstractDetection and identification of volatile organic compounds in blood by headspace gas chromatography as an aid to the diagnosis of solvent abuse »

J Theor Biol


Title:A mathematical model of foraging in a dynamic environment by trail-laying Argentine ants
Author(s):Ramsch K; Reid CR; Beekman M; Middendorf M;
Address:"Department of Computer Science, University of Leipzig, PF 100920, D-04009 Leipzig, Germany. kairamsch@informatik.uni-leipzig.de"
Journal Title:J Theor Biol
Year:2012
Volume:20120410
Issue:
Page Number:32 - 45
DOI: 10.1016/j.jtbi.2012.04.003
ISSN/ISBN:1095-8541 (Electronic) 0022-5193 (Linking)
Abstract:"Ants live in dynamically changing environments, where food sources become depleted and alternative sources appear. Yet most mathematical models of ant foraging assume that the ants' foraging environment is static. Here we describe a mathematical model of ant foraging in a dynamic environment. Our model attempts to explain recent empirical data on dynamic foraging in the Argentine ant Linepithema humile (Mayr). The ants are able to find the shortest path in a Towers of Hanoi maze, a complex network containing 32,768 alternative paths, even when the maze is altered dynamically. We modify existing models developed to explain ant foraging in static environments, to elucidate what possible mechanisms allow the ants to quickly adapt to changes in their foraging environment. Our results suggest that navigation of individual ants based on a combination of one pheromone deposited during foraging and directional information enables the ants to adapt their foraging trails and recreates the experimental results"
Keywords:"Adaptation, Physiological/physiology Algorithms Animals Ants/*physiology Feeding Behavior/*physiology Maze Learning/physiology *Models, Biological Pheromones/physiology;"
Notes:"MedlineRamsch, Kai Reid, Chris R Beekman, Madeleine Middendorf, Martin eng Research Support, Non-U.S. Gov't England 2012/05/12 J Theor Biol. 2012 Aug 7; 306:32-45. doi: 10.1016/j.jtbi.2012.04.003. Epub 2012 Apr 10"

 
Back to top
 
Citation: El-Sayed AM 2024. The Pherobase: Database of Pheromones and Semiochemicals. <http://www.pherobase.com>.
© 2003-2024 The Pherobase - Extensive Database of Pheromones and Semiochemicals. Ashraf M. El-Sayed.
Page created on 19-12-2024