Nonlinear-statistical modelling

The ascomycete H. fraxineus (an airborne fungus) has spread across most of the host range of European ash with a high level of mortality, causing important economic, cultural and environmental effects. We used a novel method combining a Monte-Carlo approach with a generalised additive (nonlinear statistical) model to confirm the importance of meteorology to the magnitude and timing of H. fraxineus spore emissions. The variability in model selection and the relative degree to which our models over- or under-fitted the data was quantified.

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