Coupling spectral and resource-use complementarity in experimental grassland and forest communities

Area of Science:

• Plant ecology
• Ecosystem science
• Remote sensing

Background:

• Reflectance spectra integrate diverse plant traits (chemical, morphological, anatomical, architectural).
• Spectral variation within plant communities is linked to ecosystem productivity.
• Understanding spectral-plant trait linkages informs ecological strategy assessment.

Purpose of the Study:

• Investigate associations between plant spectral variation and individual growth.
• Examine relationships between plant community spectral space and ecosystem productivity.
• Determine if spectral complementarity explains ecosystem productivity better than individual spectral space.

Main Methods:

• Utilized reflectance spectra to define n-dimensional hypervolumes for individual plants and communities.
• Conducted experiments in forest and prairie grassland diversity settings.
• Assessed the correlation between spectral space, individual growth, and ecosystem productivity.

Main Results:

• Individual plant spectral space positively correlated with plant growth.
• Community spectral space positively correlated with ecosystem productivity.
• Inter-individual spectral complementarity was a stronger predictor of ecosystem productivity than large individual spectral space.

Conclusions:

• Spectral hypervolumes serve as indicators of plant ecological strategies influencing community dynamics and ecosystem function.
• Spectral complementarity effectively reveals underlying resource-use complementarity in plant communities.
• Reflectance spectroscopy offers a powerful tool for ecological research and ecosystem monitoring.