Seeing the Canopy for the Branches: Improved Within Canopy Scaling of Leaf Nitrogen

Ethan E. Butler, Ming Chen, Daniel Ricciuto, Habacuc Flores Moreno, Kirk R Wythers, Jens Kattge, Peter E. Thornton, Peter B. Reich

Research output: Contribution to journalArticlepeer-review

Abstract

Transitioning across biological scales is a central challenge in land surface models. Processes that operate at the scale of individual leaves must be scaled to canopies, and this is done using dedicated submodels. Here, we focus on a submodel that prescribes how light and nitrogen are distributed through plant canopies. We found a mathematical inconsistency in a submodel implemented in the Community and Energy Land Models (CLM and ELM), which incorporates twigs, branches, stems, and dead leaves in nitrogen scaling from leaf to canopy. The inconsistency leads to unrealistic (physically impossible) values of the nitrogen scaling coefficient. The mathematical inconsistency is a general mistake, that is, would occur in any model adopting this particular submodel. We resolve the inconsistency by allowing distinct profiles of stems and branches versus living leaves. We implemented the updated scheme in the ELM and find that the correction reduces global mean gross primary production (GPP) by 3.9 Pg C (3%). Further, when stems and branches are removed from the canopy in the updated model (akin to models that ignore shading from stems), global GPP increases by 4.1 Pg C (3.2%), because of reduced shading. Hence, models that entirely ignore stem shading also introduce errors in the global spatial distribution of GPP estimates, with a strong signal in the tropics, increasing GPP there by over 200 g C m−2 yr−1. Appropriately incorporating stems and other nonphotosynthesizing material into the light and nitrogen scaling routines of global land models, will improve their biological realism and accuracy.

Original languageEnglish (US)
Article numbere2020MS002237
JournalJournal of Advances in Modeling Earth Systems
Volume12
Issue number10
DOIs
StatePublished - Oct 1 2020

Bibliographical note

Funding Information:
They thank Nick Smith and an anonymous reviewer for their comments that improved the manuscript. This research was supported as part of the Energy Exascale Earth System Model (E3SM) project, funded by the U.S. Department of Energy, Office of Science, Office of Biological and Environmental Research (including Grant DE‐SC0012677 to P. B. R.) and Biological Integration Institutes Grant NSF‐DBI‐2021898 (to P. B. R.).

Funding Information:
They thank Nick Smith and an anonymous reviewer for their comments that improved the manuscript. This research was supported as part of the Energy Exascale Earth System Model (E3SM) project, funded by the U.S. Department of Energy, Office of Science, Office of Biological and Environmental Research (including Grant DE-SC0012677 to P. B. R.) and Biological Integration Institutes Grant NSF-DBI-2021898 (to P. B. R.).

Publisher Copyright:
© 2020 The Authors.

Keywords

  • climate
  • land surface
  • modeling
  • nitrogen
  • photosynthesis
  • vegetation

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