Applying a spread model to identify the entry points from which the pine wood nematode, the vector of pine wilt disease, would spread most rapidly across Europe
2011
Robinet , Christelle (INRA , Ardon (France). UR 0633 Unité de Recherche Zoologie Forestière) | Van Opstal , Nico (Organisation Européenne et Méditerranéenne de Protection des Plantes, Paris(France).) | Baker , Richard (Food and Environment Research Agency, Sand Hutton(Royaume Uni).) | Roques , Alain(auteur de correspondance) (INRA , Ardon (France). UR 0633 Unité de Recherche Zoologie Forestière)
Pine wilt disease, which can rapidly kill pines, is caused by the pine wood nematode, Bursaphelenchus xylophilus. It is expanding its range in many countries in Asia and measures are being taken at the EU level to prevent its spread from Portugal. Due to the threat to European forests, it is important to prevent additional introductions and target surveillance to the points of entry that pose the greatest risk. In this study, we present a model to identify the European ports from which the nematode can spread most rapidly across Europe. This model describes: (1) the potential spread of the pine wood nematode based on short-distance spread (the active flight of the vector beetles) and long-distance spread (primarily due to human-mediated transportation), and (2) the development of pine wilt disease based on climate suitability and the potential spread of the nematode. Separate introductions at 200 European ports were simulated under various climate change scenarios. We found that the pine wood nematode could invade 19–60% of the study area (30°00 N–72°00 N, 25°00 W–40°00 E) by 2030, with the highest spread from ports located in Eastern and Northern Europe. Based on climate change scenarios, the disease could affect 8–34% of the study area by 2030, with the highest spread from ports located in South-Eastern Europe. This study illustrates how a spread model can be used to determine the critical points of entry for invasive species, so that surveillance can be targeted more accurately and control measures prioritised.
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