An index for measuring functional extension and evenness in trait space

Area of Science:

• Ecology
• Biodiversity Science
• Trait-based Ecology

Background:

• Existing functional diversity indices often focus on single aspects, limiting comprehensive assessment.
• Conceptual and practical limitations exist in current methods for estimating functional diversity.

Purpose of the Study:

• Introduce a novel functional extension and evenness (FEE) index to capture multiple facets of functional diversity.
• Develop a metric that overcomes limitations of single-facet indices and allows for standardized comparisons.

Main Methods:

• Utilized the minimum spanning tree (MST) concept to analyze species trait distribution in trait space.
• Combined MST branch length (extension) and variation (evenness) into a raw metric (FEE₀).
• Employed a null model approach to derive a species richness-independent FEE index.

Main Results:

• The FEE index effectively quantifies functional diversity, considering both trait extension and evenness.
• Demonstrated that FEE allows fair comparisons across different species richness levels.
• Showcased FEE's ability to standardize comparisons by accounting for the shared species pool trait space.

Conclusions:

• The FEE index is a robust and versatile metric for assessing functional diversity.
• FEE can distinguish between different community assembly processes.
• This index holds potential for informing biodiversity conservation policy and management at large scales.