Using plant functional traits to explain diversity-productivity relationships.

Area of Science:

• Ecology
• Plant functional traits
• Biodiversity and ecosystem functioning

Background:

• Species richness-productivity relationships are explained by selection and complementarity effects.
• Plant functional characteristics are central to understanding biodiversity's role in ecosystem processes.

Purpose of the Study:

• To assess the predictive power of functional trait composition for biomass production and biodiversity effects.
• To compare the roles of community-weighted means (CWM) and functional trait diversity (FD(Q)) in experimental grasslands.

Main Methods:

• Utilized community-wide measures: CWM and FD(Q) based on Rao's quadratic diversity.
• Studied experimental grasslands with varying species richness and functional group composition.
• Analyzed biomass production and biodiversity effects four years post-establishment.

Main Results:

• Functional trait composition (40-82% variation explained) significantly outperformed species richness (<1-13%) in predicting biomass and biodiversity effects.
• CWM (80% biomass, 70% net biodiversity effects) was a stronger predictor than FD(Q) (36-38%).
• Combined CWM and FD(Q) significantly improved model predictions for all response variables.

Conclusions:

• Relevant trait identification and understanding the interplay of dominant species' functional identity and functional diversity are crucial.
• These factors are essential for a mechanistic understanding of plant diversity's impact on ecosystem processes like biomass production.