Akhabue et al. (2026) Critical classification parameters linking species to Plant Functional Type in African ecosystems

Identification

• Journal: Scientific Data
• Year: 2026
• Date: 2026-02-03
• Authors: Enimhien Faith Akhabue, Andrew M. Cunliffe, Karina Bett-Williams, Anna Harper, Petra B. Holden, Tom Powell
• DOI: 10.1038/s41597-026-06728-z

Research Groups

• Department of Geography, University of Exeter, Exeter, United Kingdom
• Global Systems Institute, University of Exeter, Exeter, United Kingdom
• UK Meteorological Office, Exeter, United Kingdom
• University of Georgia, Athens, Georgia, United States of America
• African Climate & Development Initiative, University of Cape Town, Cape Town, South Africa

Short Summary

This study systematically classified African plant species from the TRY plant trait database into Plant Functional Types (PFTs) compatible with the JULES land surface model. This effort resulted in a sixfold increase in the number of species mapped to PFTs and a fivefold increase in usable trait observations, significantly enhancing the representation of African ecosystems in global models.

Objective

• To systematically classify African plant species from the TRY plant trait database into Plant Functional Types (PFTs) consistent with those used in the JULES Land Surface Model (LSM), thereby enabling improvements in PFT parameterization for these models and redressing key regional data gaps in African ecosystems.

Study Configuration

• Spatial Scale: African ecosystems, specifically plant species with geographic coordinates within Africa's extent.
• Temporal Scale: Data records from the TRY database were processed up to 27 August 2024. The resulting dataset was compiled in 2025.

Methodology and Data

• Models used: The classification is designed for the JULES (Joint UK Land Environment Simulator) PFT framework, with applicability to other PFT schemes like ORCHIDEE, LPJ-GUESS, and CLM.
• Data sources:
  • TRY plant trait database (15.4 million trait records across 2,661 traits for 305,600 plant taxa).
  • TRY - Categorical Traits Dataset (harmonized categorical trait information for 66,043 plant species).
  • World Flora Online (WFO) taxonomic backbone for taxonomic harmonization.
  • Natural Earth Admin 0 country polygons for geographic filtering.
  • Authoritative databases (e.g., African Plant Database, The Floral of Central Africa, Useful Tropical Plants, iNaturalist, Global Biodiversity Information Facility, The grass genera of the world) and peer-reviewed literature for parameter assignment.
  • R v4.1.2 statistical software, including packages sf (v1.0.19), WorldFlora (v1.14.5), rtry, and europepmc.

Main Results

• The study achieved a sixfold increase in the number of African plant species that could be linked to JULES PFT classes, from 265 to 1,603 species, representing 137 families.
• It delivered a fivefold increase in the number of usable observations among the 27 traits evaluated, from 7,373 to 35,537.
• The majority of functionally classified African species in the dataset are tropical broadleaf evergreen trees or evergreen shrubs.
• 325 species remained unclassified due to insufficient critical parameters.
• The final output is a harmonized lookup table (MappedPFTHarmonized.csv) containing original and harmonized species names, family, growth form, leaf type, phenology, photosynthetic pathway, climatic zone, and the resulting PFT classification according to the JULES taxonomy.

Contributions

• Provides a novel, harmonized dataset that systematically maps African plant species to model-relevant PFTs, directly addressing the significant underrepresentation of African ecosystems in global vegetation datasets.
• Substantially increases the availability of floral trait data for parameterizing and evaluating land surface modeling frameworks, particularly for African landscapes.
• Enables the derivation of more regionally appropriate model parameters, which is expected to improve the accuracy of model simulations for African ecosystems.
• The identified critical classification parameters offer a foundational resource for linking plant trait observations to PFT taxonomies in various land surface models beyond JULES, including ORCHIDEE, LPJ-GUESS, and CLM.

Funding

• Oppenheimer Programme in African Landscape Systems (OPALS), jointly funded by the University of Exeter, Sarah Turvill, and Oppenheimer Generations Research and Conservation.

Citation

@article{Akhabue2026Critical,
  author = {Akhabue, Enimhien Faith and Cunliffe, Andrew M. and Bett-Williams, Karina and Harper, Anna and Holden, Petra B. and Powell, Tom},
  title = {Critical classification parameters linking species to Plant Functional Type in African ecosystems},
  journal = {Scientific Data},
  year = {2026},
  doi = {10.1038/s41597-026-06728-z},
  url = {https://doi.org/10.1038/s41597-026-06728-z}
}