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Wilt expression

New techniques to improve prediction of pine wilt disease

When the pine wood nematode B. xylophilus enters a living tree through the maturation feeding of adult beetle vectors in the genus Monochamus, the outcome for the tree is decided by a series of inter-related factors:

Tree species
Soil type
Temperature
Rainfall
Elevation
Exposure to Monochamus vectors

In extreme cases, the tree will die very rapidly due to full expression of pine wilt, leading to the aptly named syndrome of pine wilt disease (PWD).

The range of tree species susceptible to pine wilt is relatively large, as indicated in the PWN Problem Module and, with increasing knowledge from the countries where the nematode has established, their relative susceptibilities are being clarified.
Despite observations of pine wilt across the world, determining the likelihood of trees dying from PWD has, until now, been based primarily on summer temperatures in affected countries.

This is a valuable approximation but is not sufficiently accurate for local or regional wilt prediction.

Now REPHRAME has developed a new range of modelling and simulation techniques to improve prediction of wilt under current and future climates. This builds on the twin approaches developed in the previous PHRAME project which used modified tree growth models and empirical models on known distributions of PWD trees in Portugal.

The process model developed by Forest Research, UK is based on ForestETp, an existing, fully coupled, point scale and daily time step soil-vegetation-atmosphere transfer (SVAT) model, which predicts vertical and lateral water movement from soil, through the plant to the atmosphere, as well as gross primary productivity (GPP) – tree growth.

This is a complex model and simulates hydrology processes - rainfall interception, vertical and lateral soil water movement, runoff, soil and canopy evaporation, and water transpiration related to photosynthesis by the tree.

It is linked to the structure of a forest, it's local soil and climate conditions.

After analysis of the model's sensitivity to a wide range of tree and environment parameters, it has been possible to include the influence of the nematode on tree physiology, including temperature-driven growth rates for PWN.

These complex drivers have been used to provide predictions of wilt over Europe and to verify model outputs on known distribution and severity of PWD in Japan, where the nematode has been present since the beginning of the 20th century.

A different, but related, approach has been taken by University of Evora, Portugal, in which detailed information on wilt expression caused by PWN has been analysed and high resolution data on tree distribution, road networks, climate variables, has been incorporated in bioclimatic modelling to explain the incidence of PWD.
     
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