Mapping functional diversity from remotely sensed morphological and physiological forest traits

Area of Science:

• Ecology
• Remote Sensing
• Forestry

Background:

• Assessing forest functional diversity is crucial for predicting ecosystem productivity and stability.
• Biodiversity-ecosystem functioning relationships are key to understanding global ecological patterns.
• Remote sensing offers a scalable approach to monitor forest ecosystems.

Purpose of the Study:

• To present a novel, spatially continuous method for mapping tree functional diversity from space.
• To integrate variations in plant functional traits (morphological and physiological) between and within species.
• To demonstrate the potential of remote sensing for assessing functional diversity at various scales.

Main Methods:

• Combined airborne laser scanning (ALS) and imaging spectroscopy data.
• Developed a method independent of prior taxonomic information.
• Validated the approach using leaf-level field measurements and species-level plot inventory data.

Main Results:

• The method showed reasonable agreement with ground-based measurements.
• Functional diversity patterns correlated with topography and soil conditions.
• Functional richness increased logarithmically with area, while divergence and evenness were scale-invariant.

Conclusions:

• Remote sensing, using combined laser scanning and imaging spectroscopy, provides a powerful tool for mapping forest functional diversity.
• The methodology is robust and applicable from individual trees to entire forest communities.
• This approach offers a scalable pathway for global assessment of forest functional diversity, limited primarily by technological advancements.