Increasing Functional Diversity in a Global Land Surface Model Illustrates Uncertainties Related to Parameter Simplification

Ethan E. Butler, Kirk R. Wythers, Habacuc Flores-Moreno, Daniel M. Ricciuto, Abhirup Datta, Arindam Banerjee, Owen K. Atkin, Jens Kattge, Peter E. Thornton, Madhur Anand, Sabina Burrascano, Chaeho Byun, J. H.C. Cornelissen, Estelle Forey, Steven Jansen, Koen Kramer, Vanessa Minden, Peter B. Reich

Research output: Contribution to journalArticlepeer-review


Simulations of the land surface carbon cycle typically compress functional diversity into a small set of plant functional types (PFT), with parameters defined by the average value of measurements of functional traits. In most earth system models, all wild plant life is represented by between five and 14 PFTs and a typical grid cell (≈100 × 100 km) may contain a single PFT. Model logic applied to this coarse representation of ecological functional diversity provides a reasonable proxy for the carbon cycle, but does not capture the non-linear influence of functional traits on productivity. Here we show through simulations using the Energy Exascale Land Surface Model in 15 diverse terrestrial landscapes, that better accounting for functional diversity markedly alters predicted total carbon uptake. The shift in carbon uptake is as great as 30% and 10% in boreal and tropical regions, respectively, when compared to a single PFT parameterized with the trait means. The traits that best predict gross primary production vary based on vegetation phenology, which broadly determines where traits fall within the global distribution. Carbon uptake is more closely associated with specific leaf area for evergreen PFTs and the leaf carbon to nitrogen ratio in deciduous PFTs.

Original languageEnglish (US)
Article numbere2021JG006606
JournalJournal of Geophysical Research: Biogeosciences
Issue number3
StatePublished - Mar 2022


  • carbon cycle
  • diversity
  • functional traits
  • global models
  • phenology

ASJC Scopus subject areas

  • Soil Science
  • Forestry
  • Water Science and Technology
  • Palaeontology
  • Atmospheric Science
  • Aquatic Science
  • Ecology


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