D.N. Huntzinger, K. Schaefer, C. Schwalm, J.B. Fisher, D. Hayes, E. Stofferahn, J. Carey, A.M. Michalak, Y. Wei, A.K. Jain, H. Kolus, J. Mao, B. Poulter, X. Shi, J. Tang and H. Tian
The Multi-scale Terrestrial Model Intercomparison Project (MsTMIP) provides simulations of carbon fluxes from an ensemble of terrestrial biosphere models that represent carbon emissions and uptake by soils and plants. In this work, simulations for the boreal region are examined to explore how models represent carbon cycling in soils. We found that the models' estimates of carbon stocks at the turn of the 20th century continue to have a strong impact on the models' estimates of current carbon stocks and flows. As a result, model estimates vary widely and are not always consistent with observational constraints. The models also differ in terms of their response to variability in temperature and moisture availability. This study provides guidance for further improvements of process-based models of boreal carbon dynamics.
Figure: Model estimates of soil carbon residence times vary substantially among themselves and relative to observational constraints. (G) MsTMIP model ensemble median soil carbon residence time (years), (H) observationally-based estimates of soil carbon residence time (years), and (I) percent bias of model estimates relative to observational constraint.
Given the magnitude of soil carbon stocks in northern ecosystems, and the vulnerability of these stocks to climate warming, land surface models must accurately represent soil carbon dynamics in these regions. We evaluate soil carbon stocks and turnover rates, and the relationship between soil carbon loss with soil temperature and moisture, from an ensemble of eleven global land surface models. We focus on the region of NASA's Arctic-Boreal vulnerability experiment (ABoVE) in North America to inform data collection and model development efforts. Models exhibit an order of magnitude difference in estimates of current total soil carbon stocks, generally under- or overestimating the size of current soil carbon stocks by greater than 50 PgC. We find that a model's soil carbon stock at steady-state in 1901 is the prime driver of its soil carbon stock a hundred years later—overwhelming the effect of environmental forcing factors like climate. The greatest divergence between modeled and observed soil carbon stocks is in regions dominated by peat and permafrost soils, suggesting that models are failing to capture the frozen soil carbon dynamics of permafrost regions. Using a set of functional benchmarks to test the simulated relationship of soil respiration to both soil temperature and moisture, we find that although models capture the observed shape of the soil moisture response of respiration, almost half of the models examined show temperature sensitivities, or Q10 values, that are half of observed. Significantly, models that perform better against observational constraints of respiration or carbon stock size do not necessarily perform well in terms of their functional response to key climatic factors like changing temperature. This suggests that models may be arriving at the right result, but for the wrong reason. The results of this work can help to bridge the gap between data and models by both pointing to the need to constrain initial carbon pool sizes, as well as highlighting the importance of incorporating functional benchmarks into ongoing, mechanistic modeling activities such as those included in ABoVE.
Huntzinger, D.N., K. Schaefer, C. Schwalm, J.B. Fisher, D. Hayes, E. Stofferahn, J. Carey, A.M. Michalak, Y. Wei, A.K. Jain, H. Kolus, J. Mao, B. Poulter, X. Shi, J. Tang, H. Tian (2020) "Evaluation of simulated soil carbon dynamics in Arctic-Borealecosystems," Environmental Research Letters, 15, 025005, doi:10.1088/1748-9326/ab6784.