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Published on: May 9, 2019
Canopy functional trait variation across Earth's tropical forests
Jesús Aguirre-Gutiérrez1,2, Sami W Rifai3, Xiongjie Deng4
1Environmental Change Institute, School of Geography and the Environment, University of Oxford, Oxford, UK. jeaggu@gmail.com.
Tropical forests exhibit significant functional diversity across continents. Tropical American forests show greater richness, while African forests display higher divergence in tree traits, impacting ecosystem functions.
Area of Science:
- Ecology
- Biogeography
- Remote Sensing
Background:
- Tropical forest canopies are critical interfaces for global carbon, water, and energy cycles.
- Current Earth System Models oversimplify tropical forests, lacking representation of their functional heterogeneity.
- Geographical variation in tropical forest canopy functional properties is poorly understood.
Purpose of the Study:
- To predict and map the functional diversity of tropical forests globally.
- To understand the geographical variation in tree functional traits across tropical regions.
- To identify areas for future data collection to improve global tropical forest models.
Main Methods:
- Combined field data from over 1,800 vegetation plots and tree traits with satellite remote-sensing, terrain, climate, and soil data.
- Predicted variation in 13 morphological, structural, and chemical functional traits of trees.
- Computed and mapped the functional diversity of tropical forests.
Main Results:
- Tropical American, African, and Asian forests occupy distinct functional trait spaces.
- Tropical American forests exhibit 40% greater functional richness compared to African and Asian forests.
- African forests show the highest functional divergence, exceeding American and Asian forests by 32% and 7%, respectively.
Conclusions:
- Geographical variation in tropical forest functional traits is substantial and predictable.
- Distinct functional trait spaces highlight regional differences in tropical forest ecosystems.
- The study provides a foundation for improved Earth System Model parameterization and identifies key areas for future research.
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