title: A process-based approach to predicting the effect of climate change on the distribution of an invasive allergenic plant in Europe.
abstract: Ambrosia artemisiifolia is an invasive weed in Europe with highly allergenic pollen. Populations are currently well established and cause significant health problems in the French Rhône valley, Austria, Hungary and Croatia but transient or casual introduced populations are also found in more Northern and Eastern European countries. A process-based model of weed growth, competition and population dynamics was used to predict the future potential for range expansion of A.artemisiifolia under climate change scenarios. The model predicted a northward shift in the available climatic niche for populations to establish and persist, creating a risk of increased health problems in countries including the UK and Denmark. This was accompanied by an increase in relative pollen production at the northern edge of its range. The southern European limit for A.artemisiifolia was not expected to change; populations continued to be limited by drought stress in Spain and Southern Italy. The process-based approach to modelling the impact of climate change on plant populations has the advantage over correlative species distribution models of being able to capture interactions of climate, land use and plant competition at the local scale. However, for this potential to be fully realised, additional empirical data are required on competitive dynamics of A.artemisiifolia in different crops and ruderal plant communities and its capacity to adapt to local conditions.
authors.affiliation: AgroEcology Department, Rothamsted Research, Harpenden, Hertfordshire, United Kingdom.
authors.forename: Jonathan
authors.initials: J
authors.lastname: Storkey
authors.affiliation: Computational and Systems Biology Department, Rothamsted Research, Harpenden, Hertfordshire, United Kingdom.
authors.forename: Pierre
authors.initials: P
authors.lastname: Stratonovitch
authors.affiliation: Centre for Ecology and Hydrology, Edinburgh, United Kingdom.
authors.forename: Daniel S
authors.initials: DS
authors.lastname: Chapman
authors.affiliation: University of Turin, Grugliasco, Italy.
authors.forename: Francesco
authors.initials: F
authors.lastname: Vidotto
authors.affiliation: Computational and Systems Biology Department, Rothamsted Research, Harpenden, Hertfordshire, United Kingdom.
authors.forename: Mikhail A
authors.initials: MA
authors.lastname: Semenov
mesh_terms: D000465:Algorithms; D031164:Ambrosia / Q000254:growth & development*; D057231:Climate Change; D003198:Computer Simulation; D017753:Ecosystem; D005060:Europe; D005843:Geography; D006969:Hypersensitivity, Immediate / Q000517:prevention & control; D058865:Introduced Species; D008962:Models, Theoretical; D011058:Pollen; D011157:Population Dynamics