Error propagation and scaling for tropical forest biomass estimates

The above-ground biomass (AGB) of tropical forests is a crucial variable for ecologists, biogeochemists, foresters and policymakers. Tree inventories are an efficient way of assessing forest carbon stocks and emissions to the atmosphere during deforestation. To make correct inferences about long-term changes in biomass stocks, it is essential to know the uncertainty associated with AGB estimates, yet this uncertainty is rarely evaluated carefully. Here, we quantify four types of uncertainty that could lead to statistical error in AGB estimates: (i) error due to tree measurement; (ii) error due to the choice of an allometric model relating AGB to other tree dimensions; (iii) sampling uncertainty, related to the…

• NS
  National Science Foundation
• UD
  U.S. Department of Defense
• SI
  Smithsonian Institution
• JD
  John D. and Catherine T. MacArthur Foundation
• GR
  Geraldine R. Dodge Foundation
• EI
  Earthwatch Institute
• ST
  Smithsonian Tropical Research Institute