Invasion thresholds for fungicide resistance: deterministic and stochasticanalyses

Citation
S. Gubbins et Ca. Gilligan, Invasion thresholds for fungicide resistance: deterministic and stochasticanalyses, P ROY SOC B, 266(1437), 1999, pp. 2539-2549
Citations number
39
Categorie Soggetti
Experimental Biology
Journal title
PROCEEDINGS OF THE ROYAL SOCIETY OF LONDON SERIES B-BIOLOGICAL SCIENCES
ISSN journal
09628452 → ACNP
Volume
266
Issue
1437
Year of publication
1999
Pages
2539 - 2549
Database
ISI
SICI code
0962-8452(199912)266:1437<2539:ITFFRD>2.0.ZU;2-#
Abstract
Fungicide resistance is an important practical problem, but one that is poo rly understood at the population level. Here we introduce a simple nonlinea r model for fungicide resistance in botanical epidemics which includes the dynamics of the chemical control agent and the host population, while also allowing for demographic stochasticity in the host-parasite dynamics. This provides a mathematical framework for analysing the risk of fungicide resis tance developing by including the parameters for the amount applied, longev ity and application frequency of the fungicide. The model demonstrates the existence of thresholds for the invasion of the resistant strain in the par asite population which depend on two quantities: the relative fitness of th e resistant strain and the effectiveness of control. This threshold marks a change from definite elimination of the resistant strain below the thresho ld to a finite probability of invasion which increases above the threshold. The fungicide decay rate, the amount of fungicide applied and the period b etween applications affect the effectiveness of control and, consequently, they influence whether or not resistance develops and the time taken to ach ieve a critical frequency of resistance. All three parameters are amenable to control by the grower or by coordinating the activity of a population of growers. Providing crude estimates of the effectiveness of control and rel ative fitness are available, the results can be used to predict the consequ ences of changing these parameters for the risk of invasion and the proport ion of sites at which this might be expected to occur. Although motivated f or fungicide resistance, the model has broader application to herbicide, an tibiotic and antiviral resistance. The modelling approach and results are d iscussed in the contest of resistance to chemical control in general.