Evaluating changes of biomass in global vegetation models: the role of turnover fluctuations and ENSO events. (26th June 2018)

• Record Type: Journal Article
• Authors: Cantú, Anselmo García; Frieler, Katja; Reyer, Christopher P O; Ciais, Philippe; Chang, Jinfeng; Ito, Akihiko; Nishina, Kazuya; François, Louis; Henrot, Alexandra-Jane; Hickler, Thomas; Steinkamp, Jörg; Rafique, Rashid; Zhao, Fang; Ostberg, Sebastian; Schaphoff, Sibyll; Tian, Hanqin; Pan, Shufen; Yang, Jia; Morfopoulos, Catherine; Betts, Richard
• Is Part Of: Environmental research letters. Volume 13:Number 7(2018:Jul.)
• Publication Date: 2018-06-26
• Subjects: terrestrial ecosystems -- ENSO -- interannual variability -- vegetation optical depth -- biomass -- ISIMIP2a -- global vegetation models; Environmental sciences -- Periodicals; Human ecology -- Research -- Periodicals; Environmental health -- Periodicals; 333.7
• DOI: 10.1088/1748-9326/aac63c
• Languages: English
• ISSNs: 1748-9326

Abstract

Abstract: This paper evaluates the ability of eight global vegetation models to reproduce recent trends and inter-annual variability of biomass in natural terrestrial ecosystems. For the purpose of this evaluation, the simulated trajectories of biomass are expressed in terms of the relative rate of change in biomass (RRB), defined as the deviation of the actual rate of biomass turnover from its equilibrium counterpart. Cumulative changes in RRB explain long-term changes in biomass pools. RRB simulated by the global vegetation models is compared with its observational equivalent, derived from vegetation optical depth reconstructions of above-ground biomass (AGB) over the period 1993–2010. According to the RRB analysis, the rate of global biomass growth described by the ensemble of simulations substantially exceeds the observation. The observed fluctuations of global RRB are significantly correlated with El Niño Southern Oscillation events (ENSO), but only some of the simulations reproduce this correlation. However, the ENSO sensitivity of RRB in the tropics is not significant in the observation, while it is in some of the simulations. This mismatch points to an important limitation of the observed AGB reconstruction to capture biomass variations in tropical forests. Important discrepancies in RRB were also identified at the regional scale, in the tropical forests of Amazonia and Central Africa, as well as in the boreal forests of north-western America, western and central Siberia. In each of these regions, the RRBs derived from the simulations were analyzed in connection with underlying differences in net primary productivity and biomass turnover rate ̶as a basis for exploring in how far differences in simulated changes in biomass are attributed to the response of the carbon uptake to CO2 increments, as well as to the model representation of factors affecting the rates of mortality and turnover of foliage and roots. Overall, our findings stress the usefulness of using RRB to evaluate complex vegetation models and highlight the importance of conducting further evaluations of both the actual rate of biomass turnover and its equilibrium counterpart, with special focus on their background values and sources of variation. In turn, this task would require the availability of more accurate multi-year observational data of biomass and net primary productivity for natural ecosystems, as well as detailed and updated information on land-cover classification.