Predicting current and future spatial community patterns of plant functional traits

Détails

ID Serval
serval:BIB_D16677F23476
Type
Article: article d'un périodique ou d'un magazine.
Collection
Publications
Institution
Titre
Predicting current and future spatial community patterns of plant functional traits
Périodique
Ecography
Auteur⸱e⸱s
Dubuis A., Rossier L., Pottier J., Pellissier L., Vittoz P., Guisan A.
ISSN
0906-7590
Statut éditorial
Publié
Date de publication
2013
Peer-reviewed
Oui
Volume
36
Numéro
11
Pages
1158-1168
Langue
anglais
Notes
Editor's Choice
Résumé
Community-level patterns of functional traits relate to community assembly and ecosystem functioning. By modelling the changes of different indices describing such patterns - trait means, extremes and diversity in communities - as a function of abiotic gradients, we could understand their drivers and build projections of the impact of global change on the functional components of biodiversity. We used five plant functional traits (vegetative height, specific leaf area, leaf dry matter content, leaf nitrogen content and seed mass) and non-woody vegetation plots to model several indices depicting community-level patterns of functional traits from a set of abiotic environmental variables (topographic, climatic and edaphic) over contrasting environmental conditions in a mountainous landscape. We performed a variation partitioning analysis to assess the relative importance of these variables for predicting patterns of functional traits in communities, and projected the best models under several climate change scenarios to examine future potential changes in vegetation functional properties. Not all indices of trait patterns within communities could be modelled with the same level of accuracy: the models for mean and extreme values of functional traits provided substantially better predictive accuracy than the models calibrated for diversity indices. Topographic and climatic factors were more important predictors of functional trait patterns within communities than edaphic predictors. Overall, model projections forecast an increase in mean vegetation height and in mean specific leaf area following climate warming. This trend was important at mid elevation particularly between 1000 and 2000 m asl. With this study we showed that topographic, climatic and edaphic variables can successfully model descriptors of community-level patterns of plant functional traits such as mean and extreme trait values. However, which factors determine the diversity of functional traits in plant communities remains unclear and requires more investigations.
Web of science
Création de la notice
12/03/2013 15:52
Dernière modification de la notice
20/08/2019 16:51
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