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Estimating CO2 Flux from Tropical Forests

  • Virginia H. Dale
  • Sandra Brown
  • Elizabeth P. Flint
  • Charles A. S. Hall
  • Richard A. Houghton
  • Louis R. Iverson
  • John F. Richards
  • James Uhlig
Part of the Ecological Studies book series (ECOLSTUD, volume 101)

Abstract

The flux of CO2 from terrestrial systems is determined by changes in biomass density, soil carbon, and land use of the major cover types. Biomass density is estimated by geographic information systems (GIS) modeling, analysis of historical records, or using country-specific volume data. Together, these approaches are improving estimates of biomass densities, and variations between the estimates can be explained by the classification of forest categories, the methods used to estimate forest degradation, and the basic assumptions on the importance of floristics and climate on species distribution. For global analysis, the GIS model is advantageous in that it can provide biomass-density estimates where historical information is absent. Land-use change can be estimated from historical records or, for the period since 1972, by remotely sensed data with in situ measures. Although the historical approach is labor and data intensive, it is the only direct way to obtain land-use changes prior to 1972. Carbon-flux estimates have been made from both historical information and bookkeeping models. The wide variation in these estimates and even in projections from different model runs suggests that more work needs to be done to understand how the components of the system affect carbon flux. This paper presents the known ranges for two major components of the carbon-flux projections: estimates of biomass density and land-use change. The analysis of the strengths and weaknesses of the methods used to obtain these estimates suggests the most fruitful directions for future research on estimating the terrestrial flux of carbon.

Keywords

Geographic Information System Tropical Forest Geographic Information System Carbon Flux Forest Biomass 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag New York, Inc. 1994

Authors and Affiliations

  • Virginia H. Dale
  • Sandra Brown
  • Elizabeth P. Flint
  • Charles A. S. Hall
  • Richard A. Houghton
  • Louis R. Iverson
  • John F. Richards
  • James Uhlig

There are no affiliations available

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