Systemic fungal diseases in natural plant populations

University dissertation from Umeå : Umeå Universitet

Abstract: The purpose of this thesis was to study interactions between systemic fungal diseases and perennial plants. Using the systemic rust Puccinia minussensis on the host plant Lactuca sibirica, and the rust Puccinia pulsatillae on the host plant Pulsatilla pratensis, this thesis focused on: (i) the effects of systemic diseases on their hosts (ii) host and pathogen responses to abiotic factors, (iii) the importance of life history strategies for understanding host-pathogen interactions, and (iv) the evolutionary consequences of living in close associations.Results of greenhouse experiments showed that Lactuca sibirica had a high plasticity in growth, since it produced significantly more shoots in favourable than in unfavourable growth conditions. Both the disease levels and the number of healthy shoots (i.e. escape) were significantly higher under favourable conditions. Disease spread within the rhizome was found to be incomplete, and the risk of aecidial- infection decreased with distance from the parent. Furthermore, one isolate of the fungus had highest success and reduced the host plant biomass and shoot production more on the clone it was collected on compared to four other clones .In the field, disease levels were found to fluctuate more at localities subjected to disturbance, the host and pathogen abundances were found to be in phase and the pathogen showed no delayed response to increasing host densities. The rust Puccinia pulsatillae on Pulsatilla pratensis showed no fluctuations between years, low infection rates, and disease levels were higher in ungrazed compared to grazed sites. There was no escape from the disease in this system.A comparison of characteristics of different systemic fungi and hosts with different growth patterns indicated that the life history strategies of both host plants and pathogens need to be studied if the long-term consequences of host-pathogen interactions are to be predicted.

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