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Type: Journal Article
Author(s): Masahito Ueyama; Kazuhito Ichii; Hiroki Iwata; Eugénie S. Euskirchen; Donatella Zona; Adrian V. Rocha; Yoshinobu Harazono; Chie Iwama; Taro Nakai; Walter C. Oechel
Publication Date: July 2013

Carbon dioxide (CO2) fluxes from a network of 21 eddy covariance towers were upscaled to estimate the Alaskan CO2 budget from 2000 to 2011 by combining satellite remote sensing data, disturbance information, and a support vector regression model. Data were compared with the CO2 budget from an inverse model (CarbonTracker). Observed gross primary productivity (GPP), ecosystem respiration (RE), and net ecosystem exchange (NEE) were each well reproduced by the model on the site scale; root-mean-square errors (RMSEs) for GPP, RE, and NEE were 0.52, 0.23, and 0.48g C m-2 d-1, respectively. Landcover classification was the most important input for predicting GPP, whereas visible reflectance index of green ratio was the most important input for predicting RE. During the period of 2000-2011, predicted GPP and RE were 369 ± 22 and 362 ± 12 Tg C yr-1 (mean ± interannual variability) for Alaska, respectively, indicating an approximately neutral CO2 budget for the decade. CarbonTracker also showed an approximately neutral CO2 budget during 2000-2011 (growing season RMSE - 14 g C m-2 season-1; annual RMSE - 13 g C m-1 yr-1). Interannual CO2 flux variability was positively correlated with air temperature anomalies from June to August, with Alaska acting as a greater CO2 sink in warmer years. CO2 flux trends for the decade were clear in disturbed ecosystems; positive trends in GPP and CO2 sink were observed in areas where vegetation recovered for about 20 years after fire. © 2013 American Geophysical Union. All Rights Reserved.

Citation: Ueyama, M. et al. 2013. Upscaling terrestrial carbon dioxide fluxes in Alaska with satellite remote sensing and support vector Regression. Journal of Geophysical Research: Biogeosciences, v. 118, no. 3, p. 1266-1281. 10.1002/jgrg.20095.

Cataloging Information

  • boreal forests
  • carbon dioxide
  • disturbance
  • disturbance
  • eddy covariance
  • fire management
  • fire regimes
  • forest management
  • MODIS - Moderate Resolution Imaging Spectroradiometer
  • remote sensing
  • support vector regression
  • tundra
  • upscaling CO2 fluxes
  • wildfires
Tall Timbers Record Number: 29184Location Status: Not in fileCall Number: AvailableAbstract Status: Fair use, Okay, Reproduced by permission
Record Last Modified:
Record Maintained By: FRAMES Staff (
FRAMES Record Number: 52131

This bibliographic record was either created or modified by Tall Timbers and is provided without charge to promote research and education in Fire Ecology. The E.V. Komarek Fire Ecology Database is the intellectual property of Tall Timbers.