Global-scale plant trait-environment relationships based on sPlotOpen and TRY data

Relationships between plant functional traits and environmental variables have been intensively studied in the ecological community due to their importance for applications such as generating upscaled trait maps and predicting trait responses due to climate change. However, such relationships have been found to be relatively weak for various potential reasons.

We analyzed global-scale trait-environment relationships using plot-level trait estimates based on the sPlotOpen and TRY databases. In addition to the commonly used community weighted mean (CWM), we considered a top-of-canopy weighted mean (TWM) metric that excludes understory vegetation. For both trait metrics, we quantified the change in trait-environment relationships when considering the dominant plant functional type (PFT) of the plot. 

We found that, overall, TWM combined with PFT had the strongest correlations to environmental variables and TWM also had the strongest increase in correlation when adding PFTs. CWM, in contrast, tended to show slightly higher correlations than TWM when not adding PFTs, but the correlations for CWM combined with PFTs were also substantially higher than CWM without PFTs. Overall, we found stronger trait-environment relationships compared to the existing literature. Our findings confirm the relevance of considering PFT-specific trait-environment relationships and demonstrate the considerable impact of different plot-level trait metrics. The choice of the most suitable trait metric depends on the application and the availability of ancillary data that can be used as weighting factors in CWM.