Schwalm Christopher R.

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Schwalm
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Christopher R.
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  • Preprint
    The terrestrial biosphere as a net source of greenhouse gases to the atmosphere
    ( 2015-12-21) Tian, Hanqin ; Lu, Chaoqun ; Ciais, Philippe ; Michalak, Anna M. ; Canadell, Josep G. ; Saikawa, Eri ; Huntzinger, Deborah N. ; Gurney, Kevin R. ; Sitch, Stephen ; Zhang, Bowen ; Yang, Jia ; Bousquet, Philippe ; Bruhwiler, Lori ; Chen, Guangsheng ; Dlugokencky, Edward J. ; Friedlingstein, Pierre ; Melillo, Jerry M. ; Pan, Shufen ; Poulter, Benjamin ; Prinn, Ronald G. ; Saunois, Marielle ; Schwalm, Christopher R. ; Wofsy, Steven C.
    The terrestrial biosphere can release or absorb the greenhouse gases, carbon dioxide (CO2), methane (CH4) and nitrous oxide (N2O) and therefore plays an important role in regulating atmospheric composition and climate1. Anthropogenic activities such as land use change, agricultural and waste management have altered terrestrial biogenic greenhouse gas fluxes and the resulting increases in methane and nitrous oxide emissions in particular can contribute to climate warming2,3. The terrestrial biogenic fluxes of individual greenhouse gases have been studied extensively4-6, but the net biogenic greenhouse gas balance as a result of anthropogenic activities and its effect on the climate system remains uncertain. Here we use bottom-up (BU: e.g., inventory, statistical extrapolation of local flux measurements, process-based modeling) and top-down (TD: atmospheric inversions) approaches to quantify the global net biogenic greenhouse gas balance between 1981-2010 as a result of anthropogenic activities and its effect on the climate system. We find that the cumulative warming capacity of concurrent biogenic CH4 and N2O emissions is about a factor of 2 larger than the cooling effect resulting from the global land CO2 uptake in the 2000s. This results in a net positive cumulative impact of the three GHGs on the planetary energy budget, with a best estimate of 3.9±3.8 Pg CO2 eq/yr (TD) and 5.4±4.8 Pg CO2 eq/yr (BU) based on the GWP 100 metric (global warming potential on a 100-year time horizon). Our findings suggest that a reduction in agricultural CH4 and N2O emissions in particular in Southern Asia may help mitigate climate change.
  • Article
    Evaluation of simulated soil carbon dynamics in Arctic-Boreal ecosystems
    (IOP Publishing, 2020-02-07) Huntzinger, Deborah N. ; Schaefer, Kevin ; Schwalm, Christopher R. ; Fisher, Joshua B. ; Hayes, Daniel ; Stofferahn, Eric ; Carey, Joanna C. ; Michalak, Anna M. ; Wei, Yaxing ; Jain, Atul K. ; Kolus, Hannah ; Mao, Jiafu ; Poulter, Benjamin ; Shi, Xiaoying ; Tang, Jianwu ; Tian, Hanqin
    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.