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The biological basis for using optical signals to track evergreen needleleaf photosynthesis

  • Zoe Amie Pierrat
  • , Troy S. Magney
  • , Rui Cheng
  • , Andrew J. Maguire
  • , Christopher Y.S. Wong
  • , Magali F. Nehemy
  • , Mukund Rao
  • , Sara E. Nelson
  • , Anneka F. Williams
  • , Jeremy A. Hoyne Grosvenor
  • , Kenneth R. Smith
  • , Jaret S. Reblin
  • , Jochen Stutz
  • , Andrew D. Richardson
  • , Barry A. Logan
  • , David R. Bowling
  • University of California at Los Angeles
  • California Institute of Technology
  • Massachusetts Institute of Technology
  • University of California at Davis
  • Trent University
  • Centre de Recerca Ecològica i Aplicacions Forestals (CREAF)
  • Columbia University
  • Bowdoin College
  • University of Utah
  • Northern Arizona University

Research output: Contribution to journalReview articlepeer-review

17 Scopus citations

Abstract

Evergreen needleleaf forests (ENFs) play a sizable role in the global carbon cycle, but the biological and physical controls on ENF carbon cycle feedback loops are poorly understood and difficult to measure. To address this challenge, a growing appreciation for the stress physiology of photosynthesis has inspired emerging techniques designed to detect ENF photosynthetic activity with optical signals. This Overview summarizes how fundamental plant biological and biophysical processes control the fate of photons from leaf to globe, ultimately enabling remote estimates of ENF photosynthesis. We demonstrate this using data across four ENF sites spanning a broad range of environmental conditions and link leaf- and stand-scale observations of photosynthesis (i.e., needle biochemistry and flux towers) with tower- and satellite-based remote sensing. The multidisciplinary nature of this work can serve as a model for the coordination and integration of observations made at multiple scales.

Original languageEnglish
Pages (from-to)130-145
Number of pages16
JournalBioScience
Volume74
Issue number3
DOIs
StatePublished - Mar 1 2024

Keywords

  • ecophysiology
  • ecosystem fluxes
  • evergreen needleleaf forests
  • photosynthesis
  • remote sensing

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