Highlights

2016

• Predicting biomass of complex central Amazonian forests

  The hyper-diversity of tropical forests makes it difficult to predict their aboveground biomass levels based on biomass models that generalize across species. In a recent study, researchers employed a virtual forest approach using extensive field data to estimate biomass levels in the central Amazon.  Due to the highly heterogenous nature of old-growth forests in structure and species composition, this study found that generic global or pantropical biomass estimation models can lead to strong biases.

  PI Contacts
  Robinson Negron-Juarez, robinson.inj@lbl.gov
  Jeffrey Q. Chambers, jchambers@lbl.gov

  Publication
  Magnabosco Marra, D., et al. “Predicting biomass of hyperdiverse and structurally complex central Amazonian forests: A virtual approach using extensive field data.” Biogeosciences 13, 1553–70 (2016). [DOI:10.5194/bg-13-1553-2016]. (Reference link)