Literature DB >> 22730057

Shifting focus from the population to the individual as a way forward in understanding, predicting and managing the complexities of evolution of resistance to pesticides.

Michael Renton1.   

Abstract

The evolution of resistance to pesticides is often conceptualised and modelled at a population level, but population-based approaches ignore important aspects of variability between individuals within populations that may be essential drivers of resistance. Here it is argued that individual-based modelling has the potential to generate new insights and perspectives, thus deepening our understanding of the complexities of the evolutionary dynamics of resistance to pesticides.
Copyright © 2012 Society of Chemical Industry.

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Year:  2012        PMID: 22730057     DOI: 10.1002/ps.3341

Source DB:  PubMed          Journal:  Pest Manag Sci        ISSN: 1526-498X            Impact factor:   4.845


  4 in total

Review 1.  Microbial adaptive evolution.

Authors:  Aiqin Shi; Feiyu Fan; James R Broach
Journal:  J Ind Microbiol Biotechnol       Date:  2022-04-14       Impact factor: 4.258

Review 2.  Emerging Challenges and Opportunities for Education and Research in Weed Science.

Authors:  Bhagirath S Chauhan; Amar Matloob; Gulshan Mahajan; Farhena Aslam; Singarayer K Florentine; Prashant Jha
Journal:  Front Plant Sci       Date:  2017-09-05       Impact factor: 5.753

3.  Tracking Ideal Varieties and Cropping Techniques for Agroecological Weed Management: A Simulation-Based Study on Pea.

Authors:  Nathalie Colbach; Emeline Felten; Christelle Gée; Antony Klein; Laura Lannuzel; Christophe Lecomte; Thibault Maillot; Florence Strbik; Jean Villerd; Delphine Moreau
Journal:  Front Plant Sci       Date:  2022-04-04       Impact factor: 6.627

4.  Herbicide-resistant weeds: from research and knowledge to future needs.

Authors:  Roberto Busi; Martin M Vila-Aiub; Hugh J Beckie; Todd A Gaines; Danica E Goggin; Shiv S Kaundun; Myrtille Lacoste; Paul Neve; Scott J Nissen; Jason K Norsworthy; Michael Renton; Dale L Shaner; Patrick J Tranel; Terry Wright; Qin Yu; Stephen B Powles
Journal:  Evol Appl       Date:  2013-09-10       Impact factor: 5.183

  4 in total

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