Decomposing uncertainties in the future terrestrial carbon budget associated with emission scenarios, climate projections, and ecosystem simulations using the ISI-MIP results

摘要

We examined the changes to global net primary production (NPP), vegetationbiomass carbon (VegC), and soil organic carbon (SOC) estimated by six globalvegetation models (GVMs) obtained from the Inter-Sectoral Impact ModelIntercomparison Project. Simulation results were obtained using fiveglobal climate models (GCMs) forced with four representative concentrationpathway (RCP) scenarios. To clarify which component (i.e., emissionscenarios, climate projections, or global vegetation models) contributes themost to uncertainties in projected global terrestrial C cycling by 2100,analysis of variance (ANOVA) and wavelet clustering were applied to 70projected simulation sets. At the end of the simulation period, changes fromthe year 2000 in all three variables varied considerably from net negative topositive values. ANOVA revealed that the main sources of uncertainty aredifferent among variables and depend on the projection period. We determinedthat in the global VegC and SOC projections, GVMs are the main influence onuncertainties (60 % and 90 %, respectively) rather thanclimate-driving scenarios (RCPs and GCMs). Moreover, the divergence of changes invegetation carbon residence times is dominated by GVM uncertainty,particularly in the latter half of the 21st century. In addition, we foundthat the contribution of each uncertainty source is spatiotemporallyheterogeneous and it differs among the GVM variables. The dominant uncertaintysource for changes in NPP and VegC varies along the climatic gradient. Thecontribution of GVM to the uncertainty decreases as the climate divisionbecomes cooler (from ca. 80 % in the equatorial division to40 % in the snow division). Our results suggest that to assessclimate change impacts on global ecosystem C cycling among each RCP scenario,the long-term C dynamics within the ecosystems (i.e., vegetation turnover andsoil decomposition) are more critical factors than photosyntheticprocesses. The different trends in the contribution of uncertainty sources in eachvariable among climate divisions indicate that improvement of GVMs based onclimate division or biome type will be effective. On the other hand, in dryregions, GCMs are the dominant uncertainty source in climate impactassessments of vegetation and soil C dynamics.