Satellite-based modeling of gross primary production in a seasonally moist tropical evergreen forest

Authors

Xiangming Xiao, University of New Hampshire - Main Campus
Qingyuan Zhang, University of New Hampshire - Main Campus
Scott Saleska, Harvard UniversityFollow
Lucy Hutyra, Harvard University
Plinio De Camargo, Universidade de São Paulo, Brazil
Steven C. Wofsy, Harvard University
Steve Frolking, University of New Hampshire - Main CampusFollow
Stephen Boles, University of New Hampshire - Main Campus
Michael Keller, USDA Forest ServiceFollow
B Moore, University of New Hampshire - Main CampusFollow

Abstract

A CO₂ eddy flux tower study has recently reported that an old-growth stand of seasonally moist tropical evergreen forest in Santarém, Brazil, maintained high gross primary production (GPP) during the dry seasons [Saleska, S. R., Miller, S. D., Matross, D. M., Goulden, M. L., Wofsy, S. C., da Rocha, H. R., de Camargo, P. B., Crill, P., Daube, B. C., de Freitas, H. C., Hutyra, L., Keller, M., Kirchhoff, V., Menton, M., Munger, J. W., Pyle, E. H., Rice, A. H., & Silva, H. (2003). Carbon in amazon forests: Unexpected seasonal fluxes and disturbance-induced losses. Science, 302, 1554–1557]. It was proposed that seasonally moist tropical evergreen forests have evolved two adaptive mechanisms in an environment with strong seasonal variations of light and water: deep roots system for access to water in deep soils and leaf phenology for access to light. Identifying tropical forests with these adaptive mechanisms could substantially improve our capacity of modeling the seasonal dynamics of carbon and water fluxes in the tropical zone. In this paper, we have analyzed multi-year satellite images from the VEGETATION (VGT) sensor onboard the SPOT-4 satellite (4/1998–12/2002) and the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard the Terra satellite (2000–2003). We reported temporal analyses of vegetation indices and simulations of the satellite-based vegetation photosynthesis model (VPM). The Enhanced Vegetation Index (EVI) identified subtle changes in the seasonal dynamics of leaf phenology (leaf emergence, leaf aging and leaf fall) in the forest, as suggested by the leaf litterfall data. The land surface water index (LSWI) indicated that the forest experienced no water stress in the dry seasons of 1998–2002. The VPM model, which uses EVI, LSWI and site-specific climate data (air temperature and photosynthetically active radiation, PAR) for 2001–2002, predicted high GPP in the late dry seasons, consistent with observed high evapotranspiration and estimated GPP from the CO₂ eddy flux tower.

Department

Earth Sciences, Earth Systems Research Center

Publication Date

1-15-2005

Journal Title

Remote Sensing of Environment

Publisher

Elsevier

Digital Object Identifier (DOI)

10.1016/j.rse.2004.08.015

Document Type

Article

Recommended Citation

Xiangming Xiao, Qingyuan Zhang, Scott Saleska, Lucy Hutyra, Plinio De Camargo, Steven Wofsy, Stephen Frolking, Stephen Boles, Michael Keller, Berrien Moore III, Satellite-based modeling of gross primary production in a seasonally moist tropical evergreen forest, Remote Sensing of Environment, Volume 94, Issue 1, 15 January 2005, Pages 105-122, ISSN 0034-4257, http://dx.doi.org/10.1016/j.rse.2004.08.015.

Rights

Copyright © 2004 Elsevier Inc. All rights reserved.