2014, Nishina, K., Ito, A., Beerling, D.J., Cadule, P., Ciais, P., Clark, D.B., Friend, A.D., Kahana, R., Kato, E., Keribin, R., Lucht, W., Lomas, M., Rademacher, T.T., Pavlick, R., Schaphoff, S., Vuichard, N., Warszawaski, L., Yokohata, T.

Soil organic carbon (SOC) is the largest carbon pool in terrestrial ecosystems and may play a key role in biospheric feedbacks with elevated atmospheric carbon dioxide (CO2) in a warmer future world. We examined the simulation results of seven terrestrial biome models when forced with climate projections from four representative-concentration-pathways (RCPs)-based atmospheric concentration scenarios. The goal was to specify calculated uncertainty in global SOC stock projections from global and regional perspectives and give insight to the improvement of SOC-relevant processes in biome models. SOC stocks among the biome models varied from 1090 to 2650 Pg C even in historical periods (ca. 2000). In a higher forcing scenario (i.e., RCP8.5), inconsistent estimates of impact on the total SOC (2099–2000) were obtained from different biome model simulations, ranging from a net sink of 347 Pg C to a net source of 122 Pg C. In all models, the increasing atmospheric CO2 concentration in the RCP8.5 scenario considerably contributed to carbon accumulation in SOC. However, magnitudes varied from 93 to 264 Pg C by the end of the 21st century across biome models. Using the time-series data of total global SOC simulated by each biome model, we analyzed the sensitivity of the global SOC stock to global mean temperature and global precipitation anomalies (ΔT and ΔP respectively) in each biome model using a state-space model. This analysis suggests that ΔT explained global SOC stock changes in most models with a resolution of 1–2 °C, and the magnitude of global SOC decomposition from a 2 °C rise ranged from almost 0 to 3.53 Pg C yr−1 among the biome models. However, ΔP had a negligible impact on change in the global SOC changes. Spatial heterogeneity was evident and inconsistent among the biome models, especially in boreal to arctic regions. Our study reveals considerable climate uncertainty in SOC decomposition responses to climate and CO2 change among biome models. Further research is required to improve our ability to estimate biospheric feedbacks through both SOC-relevant and vegetation-relevant processes.

2015, Nishina, K., Ito, A., Falloon, P., Friend, A.D., Beerling, D.J., Ciais, P., Clark, D.B., Kahana, R., Kato, E., Lucht, W., Lomas, M., Pavlick, R., Schaphoff, S., Warszawaski, L., Yokohata, T.

We examined the changes to global net primary production (NPP), vegetation biomass carbon (VegC), and soil organic carbon (SOC) estimated by six global vegetation models (GVMs) obtained from the Inter-Sectoral Impact Model Intercomparison Project. Simulation results were obtained using five global climate models (GCMs) forced with four representative concentration pathway (RCP) scenarios. To clarify which component (i.e., emission scenarios, climate projections, or global vegetation models) contributes the most to uncertainties in projected global terrestrial C cycling by 2100, analysis of variance (ANOVA) and wavelet clustering were applied to 70 projected simulation sets. At the end of the simulation period, changes from the year 2000 in all three variables varied considerably from net negative to positive values. ANOVA revealed that the main sources of uncertainty are different among variables and depend on the projection period. We determined that in the global VegC and SOC projections, GVMs are the main influence on uncertainties (60 % and 90 %, respectively) rather than climate-driving scenarios (RCPs and GCMs). Moreover, the divergence of changes in vegetation carbon residence times is dominated by GVM uncertainty, particularly in the latter half of the 21st century. In addition, we found that the contribution of each uncertainty source is spatiotemporally heterogeneous and it differs among the GVM variables. The dominant uncertainty source for changes in NPP and VegC varies along the climatic gradient. The contribution of GVM to the uncertainty decreases as the climate division becomes cooler (from ca. 80 % in the equatorial division to 40 % in the snow division). Our results suggest that to assess climate change impacts on global ecosystem C cycling among each RCP scenario, the long-term C dynamics within the ecosystems (i.e., vegetation turnover and soil decomposition) are more critical factors than photosynthetic processes. The different trends in the contribution of uncertainty sources in each variable among climate divisions indicate that improvement of GVMs based on climate division or biome type will be effective. On the other hand, in dry regions, GCMs are the dominant uncertainty source in climate impact assessments of vegetation and soil C dynamics.

2014, Boysen, L.R., Brovkin, V., Arora, V.K., Cadule, P., De Noblet-Ducoudré, N., Kato, E., Pongratz, J., Gayler, V.

Biogeophysical (BGP) and biogeochemical (BGC) effects of land-use and land cover change (LULCC) are separated at the global and regional scales in new interactive CO2simulations for the 21st century. Results from four earth system models (ESMs) are analyzed for the future RCP8.5 scenario from simulations with and without land-use and land cover change (LULCC), contributing to the Land-Use and Climate, IDentification of robust impacts (LUCID) project. Over the period 2006-2100, LULCC causes the atmospheric CO2concentration to increase by 12, 22, and 66 ppm in CanESM2, MIROC-ESM, and MPI-ESM-LR, respectively. Statistically significant changes in global near-surface temperature are found in three models with a BGC-induced global mean annual warming between 0.07 and 0.23 K. BGP-induced responses are simulated by three models in areas of intense LULCC of varying sign and magnitude (between g 0.47 and 0.10 K). Modifications of the land carbon pool by LULCC are disentangled in accordance with processes that can lead to increases and decreases in this carbon pool. Global land carbon losses due to LULCC are simulated by all models: 218, 57, 35 and 34 Gt C by MPI-ESM-LR, MIROC-ESM, IPSL-CM5A-LR and CanESM2, respectively. On the contrary, the CO2-fertilization effect caused by elevated atmospheric CO2concentrations due to LULCC leads to a land carbon gain of 39 Gt C in MPI-ESM-LR and is almost negligible in the other models. A substantial part of the spread in models' responses to LULCC is attributed to the differences in implementation of LULCC (e.g., whether pastures or crops are simulated explicitly) and the simulation of specific processes. Simple idealized experiments with clear protocols for implementing LULCC in ESMs are needed to increase the understanding of model responses and the statistical significance of results, especially when analyzing the regional-scale impacts of LULCC.