A novel approach for modelling vegetation distributions and analysing vegetation sensitivity through trait-climate relationships in China.

ABSTRACT: Increasing evidence indicates that current dynamic global vegetation models (DGVMs) have suffered from insufficient realism and are difficult to improve, particularly because they are built on plant functional type (PFT) schemes. Therefore, new approaches, such as plant trait-based methods, are urgently needed to replace PFT schemes when predicting the distribution of vegetation and investigating vegetation sensitivity. As an important direction towards constructing next-generation DGVMs based on plant functional traits, we propose a novel approach for modelling vegetation distributions and analysing vegetation sensitivity through trait-climate relationships in China. The results demonstrated that a Gaussian mixture model (GMM) trained with a LMA-Nmass-LAI data combination yielded an accur

SUBMITTER: Yang Y 

PROVIDER: S-EPMC4823651 | biostudies-literature | 2016 Apr

REPOSITORIES: biostudies-literature