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Title: Modelling the incidence and impact of 'Peridermium pini' on 'Pinus sylvestris' in north-east Scotland
Author: Moseley, Darren Glenn
Awarding Body: University of Aberdeen
Current Institution: University of Aberdeen
Date of Award: 2004
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Peridermium pini causes a stem rust of two-needled pine trees, with the greatest problems in the United Kingdom associated with Scots pine forests in north-east Scotland.  It was hypothesised that silvicultural practices are viable options for controlling the incidence of P. pini and that a combination of climatic and biophysical factors may be significant in regulating the incidence of the disease.  P. pini incidence was determined in four Scots pine plantations established in Moray, and in five native pinewoods.  P. pini incidence in the Scots pine forests of north-east Scotland has increased since the previous surveys undertaken in the 1960s.  Mean disease incidence for all plantations was 4.9%, with a range from 4.0% at Cawdor Estate to 5.7% at Darnaway Estate. Age-class, the number of years since thinning, elevation and continentality were statistically significant factors influencing disease incidence.  These factors were used as the basis for a rule-based model to describe the distribution of P. pini within the forests surveyed. A second modelling approach, using Bayesian methods to analyse a large number of datasets, supported the hypothesis that management factors had the major influence on incidence of the disease and that climatic factors added, incrementally, to explaining the spatial distribution of the disease.  Maps produced from the outputs designated the probabilities of P. pini incidence into risk classes. Estimation of timber volume losses in infected stands confirmed that the disease would have significant economic impact in most sites if no savage thinnings were undertaken.  This process would have the most significant effect at Altyre Estate. The combination of these modelling approaches with Geographic Information Systems is potentially useful as a decision-support tool for forest managers, enabling greater confidence in judging the potential local significance of the factors affecting disease incidence.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available