4.7 Article

Observed allocations of productivity and biomass, and turnover times in tropical forests are not accurately represented in CMIP5 Earth system models

Journal

ENVIRONMENTAL RESEARCH LETTERS
Volume 10, Issue 6, Pages -

Publisher

IOP PUBLISHING LTD
DOI: 10.1088/1748-9326/10/6/064017

Keywords

tropical biomass; tropical productivity; biomass turnover time; earth system models

Funding

  1. Office of Science, Office of Biological and Environmental Research of the US Department of Energy as part of the Regional and Global Climate Modeling (RGCM) program [DE-AC02-05CH11231]
  2. Office of Science, Office of Biological and Environmental Research of the US Department of Energy as part of the Next-Generation Ecosystems Experiments (NGEE Tropics) Program [DE-AC02-05CH11231]
  3. Laboratory Directed Research and Development (LDRD) from Berkeley Lab, provided by the, Office of Science, of the US Department of Energy [DE-AC02-05CH11231]

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A significant fraction of anthropogenic CO2 emissions is assimilated by tropical forests and stored as biomass, slowing the accumulation of CO2 in the atmosphere. Because different plant tissues have different functional roles and turnover times, predictions of carbon balance of tropical forests depend on how earth system models (ESMs) represent the dynamic allocation of productivity to different tree compartments. This study shows that observed allocation of productivity, biomass, and turnover times of main tree compartments (leaves, wood, and roots) are not accurately represented in Coupled Model Intercomparison Project Phase 5 ESMs. In particular, observations indicate that biomass saturates with increasing productivity. In contrast, most models predict continuous increases in biomass with increases in productivity. This bias may lead to an over-prediction of carbon uptake in response toCO2 or climate-driven changes in productivity. Compartment-specific productivity and biomass are useful benchmarks to assess terrestrial ecosystem model performance. Improvements in the predicted allocation patterns and turnover times by ESMs will reduce uncertainties in climate predictions.

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