Improving plant functional groups for dynamic models of biodiversity: at the crossroads between functional and community ecology

• Published in: Global change biology Vol. 18; no. 11; pp. 3464 - 3475
• Main Authors: Boulangeat, Isabelle, Philippe, Pauline, Abdulhak, Sylvain, Douzet, Roland, Garraud, Luc, Lavergne, Sébastien, Lavorel, Sandra, Van Es, Jérémie, Vittoz, Pascal, Thuiller, Wilfried
• Format: Journal Article
• Language: English
• Published: Oxford Blackwell Publishing Ltd 01.11.2012; Wiley-Blackwell
• Subjects: Animal and plant ecology; Animal, plant and microbial ecology; biodiversity scenarios; Biological and medical sciences; Climate change; Community ecology; Conservation biology; dynamic vegetation model; emergent groups; functional diversity; functional traits; Fundamental and applied biological sciences. Psychology; General aspects; hybrid model; Mathematical models; Plant ecology; plant functional groups; plant functional types; Plant populations; emergent groups; Functional trait; plant functional groups; plant functional types; Functional ecology; Biodiversity; biodiversity scenarios; Functional diversity; hybrid model; functional traits; Vegetation; dynamic vegetation model; Dynamic model; Community; Functional group; functional diversity
• ISSN: 1354-1013; 1365-2486
• DOI: 10.1111/j.1365-2486.2012.02783.x

The pace of on‐going climate change calls for reliable plant biodiversity scenarios. Traditional dynamic vegetation models use plant functional types that are summarized to such an extent that they become meaningless for biodiversity scenarios. Hybrid dynamic vegetation models of intermediate complexity (hybrid‐DVMs) have recently been developed to address this issue. These models, at the crossroads between phenomenological and process‐based models, are able to involve an intermediate number of well‐chosen plant functional groups (PFGs). The challenge is to build meaningful PFGs that are representative of plant biodiversity, and consistent with the parameters and processes of hybrid‐DVMs. Here, we propose and test a framework based on few selected traits to define a limited number of PFGs, which are both representative of the diversity (functional and taxonomic) of the flora in the Ecrins National Park, and adapted to hybrid‐DVMs. This new classification scheme, together with recent advances in vegetation modeling, constitutes a step forward for mechanistic biodiversity modeling.