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Title: Regulation of a biennial host plant population by an autoecious, demicyclic rust fungus : Puccinia hysterium on Tragopogon pratensis in the Park Grass Experiment
Author: Salama, Nabeil Khairy Gad
ISNI:       0000 0004 2676 691X
Awarding Body: Imperial College London
Current Institution: Imperial College London
Date of Award: 2009
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Models developed in continuous-time have been used to study the epidemiology and population dynamics of plant hosts, usually in cultivated systems. Here discrete-time SIR–type models are developed which contain parameters representing characteristics of an uncultivated, biennial host plant – systemic, castrating pathogen system. This thesis presents 4 epidemiological model forms representing a generic SIR model, a constant pathogen-induced mortality model, a variable pathogen-induced mortality model, and a model which has an additional phase representing a seedbank. Using a range of parameter values it is possible to produce simulation outcomes with population crashes, cycles and steady-state populations. For each of the models a pathogen epidemic criterion is derived as is a term describing population steady-state values. For the pathogen-induced mortality models, the invasion criteria include a pathogenicity term indicating that the pathogen in part regulates the host population dynamics. The biennial host plant Tragopogon pratensis has been recorded in the Park Grass Experiment and has been described as an outbreak species regulated by the autoecious, demicyclic rust fungus, Puccinia hysterium (Silvertown et al., 2006). The rust is shown to castrate the host plant by reducing the numbers of seed set and the viability of seeds produced by infected individuals. Further characteristics of this host – pathogen system are identified by using the developed models. This is justified as the recurrencerelationships derived from the models fit the observed data, and that the accuracy of the fit is increased with larger values of pathogen-induced mortality. These models produce simulation outcomes that are similar to the host population dynamics. The models also show that the system is governed by density-dependent factors.
Supervisor: Jeger, Mike Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral