© 2016 John Wiley & Sons Ltd Aim: Dynamic global vegetation models (DGVMs) use a discretization of forest vegetation based on plant functional types (PFTs). The physiological and ecological parameters used to model a given PFT are usually fixed, being defined from point-based observations, while model applications are often grid-based. This rigid approach causes spatial biases in the results of DGVM-simulated productivity and biomass-related variables. We aim to overcome this limitation with a new approach that uses a hierarchical classification of forest PFT parameters from traits retrieved from the literature and from the TRY global database of plant traits. This approach is applied to temperate conifers in the ORCHIDEE-FM DGVM, which has previously been shown to produce systematic biases in the simulation of biomass and biomass increments. Location: Temperate coniferous forests in France. Methods: The five major coniferous species in France, Abies alba, Picea abies, Pinus pinaster, Pinus sylvestris and Pseudotsuga menziesii, were grouped objectively into PFTs within the ORCHIDEE-FM DGVM using a hierarchical classification based on 12 key attributes related to photosynthesis, phenology and allometric relationships. Results: We show that the single PFT covering all temperate coniferous forests used by default in ORCHIDEE-FM could be replaced by two representative subcategories defined by grouping species-level data without necessarily having to adopt a set of parameters for each species. The definition of new temperate conifer PFTs with this approach allows us to reduce the spatial heterogeneity by 40% on average in model–measurement misfit for stand volume, growth and stand density at the regional scale. Main conclusions: The proposed approach to improve the representation of PFTs in DGVMs, while keeping the number of different PFTs manageable, is promising for application to regions where a single PFT can correspond to a number of different species.
|Journal||Global Ecology and Biogeography|
|Publication status||Published - 1 Apr 2017|
- PFT classification
- forest management
- functional traits
- hierarchical classification