Critical classification parameters linking species to Plant Functional Type in African ecosystems

TL;DR

This paper improves the representation of African ecosystems in climate models by classifying plant species into functional types using available trait data.

Contribution

A sixfold increase in plant species mapped to PFTs in African ecosystems using TRY database traits.

Findings

Mapped 1603 plant species to PFTs, up from 265, using TRY database data.

Increased usable trait observations fivefold across 27 traits.

Created a lookup table to integrate plant trait data into land surface models.

Abstract

Accurately representing African ecosystems in land surface models (LSMs) remains challenging due to the limited availability and accessibility of ecological data like plant traits. We systematically classified African plant species represented in the TRY plant trait database into Plant Functional Types (PFTs) consistent with those in the JULES LSM, to enable improvements of PFT parameterization in these models. From the TRY database plant trait observations were obtained representing 2,082 plant species. We assigned classification parameters including growth form, leaf type, leaf phenology, photosynthetic pathway and climate zone using multiple sources. This delivered a sixfold increase in number of plant species that could be mapped to PFT classes from 265 to 1603 representing 137 families. It delivered a fivefold increase in the number of useable observations among the 27 traits evaluated. Our lookup table can be used to integrate existing plant trait data into PFT parameterisations in land surface models and similar large scale modelling exercises, to enhance the representation of African ecosystems and improve their capacity to simulate African ecosystems.

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