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| Reference : Refining vegetation simulation models: From plant functional types to bioclimatic affini... |
| Scientific journals : Article | |||
| Life sciences : Phytobiology (plant sciences, forestry, mycology...) Life sciences : Environmental sciences & ecology Life sciences : Phytobiology (plant sciences, forestry, mycology...) | |||
| http://hdl.handle.net/2268/39101 | |||
| Refining vegetation simulation models: From plant functional types to bioclimatic affinity groups of plants | |
| English | |
| Laurent, J.-M. [Université Montpellier 2 > ISEM > > >] | |
| Bar-Hen, A. [Université Aix-Marseille III > FST Saint Jerome, LATP > > >] | |
François, Louis  [Université de Liège - ULg > Département d'astrophys., géophysique et océanographie (AGO) > Modélisation du climat et des cycles biogéochimiques >] | |
| Ghislain, M. [Université de Liège > LPAP > > >] | |
| Cheddadi, R. [Université de Montpellier 2 > ISEM > > >] | |
| 2004 | |
| Journal of Vegetation Science | |
| Opulus Press | |
| 15 | |
| 6 | |
| 739-746 | |
| International | |
| 1100-9233 | |
| [en] CARAIB ; discriminant analysis ; hierarchical clusteranalysis ; moisture ; pollen ; seasonality ; temperature ; vegetation distribution | |
| [en] Question: How to refine simulations based on a global vegetation model in order to apply it to regional scale? Location: Europe from 35degrees N to 71degrees N and 25degrees W to 70degrees E. Methods: Geographical ranges of European plants were georeferenced and used with monthly mean climatic data (diurnal temperature ranges, ground frost frequencies, precipitation, relative humidity, rain frequencies, amount of sunshine hours and temperature) and growing degree days to infer climatic boundaries for 320 taxa. We performed a discriminant analysis to define their potential geographic ranges. Hierarchical clustering was computed on potential ranges. Results: Clustering provided 25 Bioclimatic Affinity Groups (BAG) of plants consisting of 13 tree, seven shrub and five herb groups. These BAGs are characterized by different geographical ranges and climatic tolerances and requirements. Conclusion: The use of monthly data instead of annual values improved the prediction of potential distribution ranges and highlighted the importance of climate seasonality for defining the plant groups with accuracy. The BAGs are detailed enough to provide finer reconstructions and simulations of the vegetation at the regional scale. | |
| Researchers | |
| http://hdl.handle.net/2268/39101 |
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