Forecasting Global Change Impacts On Ecosystems Using a Unified Plant Functional Spectrum

Introduction

Functional traits of organisms determine their responses to the environment, disturbances, biotic interactions, but also their effects on ecosystem processes. Therefore, trait-based approaches can potentially advance our understanding of complex ecological questions.

Challenges in Trait-Based Approaches

However, straightforward approaches for accurate predictions of community composition and ecosystem functioning from traits are not yet available. Studies have considered different traits, which hampers synthesis, and analytical tools have been limited.

Holistic Approach

Trait-based predictions need a holistic approach incorporating all aspects of the functional structure of plant communities within a unified plant functional space (UPFS) that considers the independent information provided by above- and belowground traits.

PLECTRUM Objectives

PLECTRUM takes advantage of the UPFS and provides solutions for three of the most intractable problems for trait-based ecology:

1. The dimensionality of functional variation across ecosystems.
2. Predicting functional structure from environmental variables.
3. Using this knowledge to forecast the effects of global change on functional structure, ecosystem functioning, and species extinction risk.

Methodology

I will combine the information from massive datasets of vegetation plots and plant traits with the first global standardized sampling of key above- and belowground traits. I will use this data to:

• Quantify functional dimensionality across ecosystems.
• Estimate the position of thousands of species in the UPFS.

Application of Deep Learning

Then, I will use species distributions in the UPFS analogous to images and apply deep learning methods to link the functional structure of communities to ecosystem functioning and environmental change.

Conclusion

The methodological toolbox developed in the project, combined with the synergy of aboveground and root traits, will allow us to forecast the effects of different global change scenarios on plant communities and their functioning across scales.