4.5 Article

Evaluation of modeled global vegetation carbon dynamics: Analysis based on global carbon flux and above-ground biomass data

期刊

ECOLOGICAL MODELLING
卷 355, 期 -, 页码 84-96

出版社

ELSEVIER
DOI: 10.1016/j.ecolmodel.2017.04.012

关键词

Dynamic global vegetation model; Integrated biosphere simulator; Gross primary production; Above-ground biomass; Global carbon cycle

类别

资金

  1. National Science Foundation of China [41301020]
  2. National Key Basic Research Program of China [2013CB956604]
  3. U.S. Department of Energy, Biological and Environmental Research, Terrestrial Carbon Program [DE-FG02-04ER63917, DE-FG02-04ER63911]
  4. CFCAS
  5. NSERC
  6. BIOCAP
  7. Environment Canada
  8. NRCan
  9. CarboEuropeIP
  10. FAO-GTOS-TCO
  11. iLEAPS
  12. Max Planck Institute for Biogeochemistry
  13. National Science Foundation
  14. University of Tuscia
  15. Universite Laval
  16. US Department of Energy

向作者/读者索取更多资源

Dynamic global vegetation models are useful tools for the simulation of global carbon cycle. However, most models are hampered by the poor availability of global aboveground biomass (AGB) data, which is necessary for the model calibration process. Here, taking the integrated biosphere simulator model (IBIS) as an example, we evaluated the modeled carbon dynamics, including gross primary production (GPP) and potential AGB, at the global scale. The IBIS model was constrained by both in situ GPP and plot-level AGB data collected from the literature. Model results showed that IBIS could reproduce GPP with acceptable accuracy in monthly and annual scales. At the global scale, the IBIS-simulated total AGB was similar to those obtained in other studies. However, discrepancies were observed between the model-derived and observed AGB for pan-tropical forests. The bias in modeled AGB was mainly caused by the unchanged parameters over the global scale for a specific plant functional type. This study also showed that different meteorological inputs can introduce substantial differences in modeled AGB in the global scale, although this difference is small compared with parameter-induced differences. The conclusions of our research highlight the necessity of considering the heterogeneity of key model physiological parameters in modeling global AGB. (C) 2017 Elsevier B.V. All rights reserved.

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