Biological processes dominate seasonality of remotely sensed canopy greenness in an Amazon evergreen forest

Jin Wu, Hideki Kobayashi, Scott C. Stark, Ran Meng, Kaiyu Guan, Ngoc Nguyen Tran, Sicong Gao, Wei Yang, Natalia Restrepo-Coupe, Tomoaki Miura, Raimundo Cosme Oliviera, Alistair Rogers, Dennis G. Dye, Bruce W. Nelson, Shawn P. Serbin, Alfredo R. Huete, Scott Saleska

Research output: Contribution to journalArticle

14 Citations (Scopus)

Abstract

Satellite observations of Amazon forests show seasonal and interannual variations, but the underlying biological processes remain debated. Here we combined radiative transfer models (RTMs) with field observations of Amazon forest leaf and canopy characteristics to test three hypotheses for satellite-observed canopy reflectance seasonality: seasonal changes in leaf area index, in canopy-surface leafless crown fraction and/or in leaf demography. Canopy RTMs (PROSAIL and FLiES), driven by these three factors combined, simulated satellite-observed seasonal patterns well, explaining c. 70% of the variability in a key reflectance-based vegetation index (MAIAC EVI, which removes artifacts that would otherwise arise from clouds/aerosols and sun-sensor geometry). Leaf area index, leafless crown fraction and leaf demography independently accounted for 1, 33 and 66% of FLiES-simulated EVI seasonality, respectively. These factors also strongly influenced modeled near-infrared (NIR) reflectance, explaining why both modeled and observed EVI, which is especially sensitive to NIR, captures canopy seasonal dynamics well. Our improved analysis of canopy-scale biophysics rules out satellite artifacts as significant causes of satellite-observed seasonal patterns at this site, implying that aggregated phenology explains the larger scale remotely observed patterns. This work significantly reconciles current controversies about satellite-detected Amazon phenology, and improves our use of satellite observations to study climate-phenology relationships in the tropics.

Original languageEnglish (US)
JournalNew Phytologist
DOIs
StateAccepted/In press - Jan 1 2018

Fingerprint

Biological Phenomena
Crowns
Artifacts
Demography
canopy
Biophysics
Solar System
Aerosols
Climate
reflectance
phenology
demography
leaf area index
tree crown
seasonal variation
leaves
biophysics
aerosols
Forests
tropics

Keywords

  • Canopy phenology
  • Leaf age
  • Leaf optics
  • LiDAR canopy structure
  • MODIS EVI
  • WorldView-2

ASJC Scopus subject areas

  • Physiology
  • Plant Science

Cite this

Biological processes dominate seasonality of remotely sensed canopy greenness in an Amazon evergreen forest. / Wu, Jin; Kobayashi, Hideki; Stark, Scott C.; Meng, Ran; Guan, Kaiyu; Tran, Ngoc Nguyen; Gao, Sicong; Yang, Wei; Restrepo-Coupe, Natalia; Miura, Tomoaki; Oliviera, Raimundo Cosme; Rogers, Alistair; Dye, Dennis G.; Nelson, Bruce W.; Serbin, Shawn P.; Huete, Alfredo R.; Saleska, Scott.

In: New Phytologist, 01.01.2018.

Research output: Contribution to journalArticle

Wu, J, Kobayashi, H, Stark, SC, Meng, R, Guan, K, Tran, NN, Gao, S, Yang, W, Restrepo-Coupe, N, Miura, T, Oliviera, RC, Rogers, A, Dye, DG, Nelson, BW, Serbin, SP, Huete, AR & Saleska, S 2018, 'Biological processes dominate seasonality of remotely sensed canopy greenness in an Amazon evergreen forest', New Phytologist. https://doi.org/10.1111/nph.14939
Wu, Jin ; Kobayashi, Hideki ; Stark, Scott C. ; Meng, Ran ; Guan, Kaiyu ; Tran, Ngoc Nguyen ; Gao, Sicong ; Yang, Wei ; Restrepo-Coupe, Natalia ; Miura, Tomoaki ; Oliviera, Raimundo Cosme ; Rogers, Alistair ; Dye, Dennis G. ; Nelson, Bruce W. ; Serbin, Shawn P. ; Huete, Alfredo R. ; Saleska, Scott. / Biological processes dominate seasonality of remotely sensed canopy greenness in an Amazon evergreen forest. In: New Phytologist. 2018.
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AU - Yang, Wei

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AU - Oliviera, Raimundo Cosme

AU - Rogers, Alistair

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