Scale dependence of canopy trait distributions along a tropical forest elevation gradient

Area of Science:

• Ecology
• Remote Sensing
• Forest Science

Background:

• Understanding forest foliar trait responses to elevation is crucial for predicting ecosystem changes.
• Limited knowledge exists on trait distributional responses across multiple ecological scales.

Purpose of the Study:

• To analyze and compare canopy foliar trait distributions at multiple scales using field and remote sensing data.
• To investigate how trait variation responds to elevation and identify traits indicative of climate change impacts.

Main Methods:

• Field sampling and airborne imaging spectroscopy along an Andes-to-Amazon elevation gradient.
• Generation of field-estimated traits using community-weighting methods.
• Estimation of remotely sensed traits at varying spatial scales (sampling grain and ecological extent).

Main Results:

• Average leaf mass per unit area (LMA), water, nonstructural carbohydrates (NSCs), and polyphenols increased with elevation.
• Foliar nutrients and photosynthetic pigments showed minimal elevation trends.
• Trait variance and distributional skew increased with elevation, particularly evident in remote sensing data.

Conclusions:

• Leaf mass per unit area (LMA), leaf water, and nonstructural carbohydrates (NSCs) exhibit multiscale invariance, making them valuable indicators for monitoring forest responses to climate change.
• Imaging spectroscopy enables enhanced multiscale trait-based ecological studies.