Archive for July, 2016

Thoughts on Li et al. 2014, “Soil carbon sensitivity to temperature and carbon use efficiency compared across microbial-ecosystem models of varying complexity.”

Saturday, July 9th, 2016

Ha, that is a long auto-generated URL. Given what has happened in the past few days, one has to chuckle at and cherish the little harmless things.

I read Li et al. 2014 from Biogeochemistry. This paper compares the output of several Earth system models including the “conventional model,” German (German et al., 2012), AWB (Allison et al., 2010), and MEND (Wang et al., 2013). The models differ in carbon pool structure and interactions, parameter values, and complexity — German has the fewest parameters and pools, while MEND has the most. The models were simulated under three separate microbial carbon use efficiency (CUE) scenarios. CUE is an important parameter in describing microbial function, and the effect of rising temperatures on the CUE of global microbial populations will be a key determinant of changes to the soil organic carbon (SOC) pool size in the coming century.

The three CUE scenarios tested were:

  1. A constant CUE scenario in which the CUE parameter stayed at 0.31 and did not depend on temperature
  2. A varied CUE scenario in which CUE monotonically decreases with temperature increase
  3. A varied CUE with thermal acclimation

Another key parameter that CUE depends on in all of the models in Li et al. (with the exception of the conventional model) is m, the CUE temperature response coefficient. CUE is given by

CUE(T) = CUE_{ref} + m * (T – T_{ref})

where T is temperature, CUE_{ref} is a set reference CUE value, and T_{ref} is a set reference temperature, in this 298.15 Kelvin.

Models were simulated at initial temperatures until they reached equilibrium and then perturbed with a 5 degree Celsius temperature increase.

Now, I won’t go into too much detail since I need to go to bed at some point, but there are several results in this paper that piqued my interest. For one, for regions initiated at low temperatures, the German, AWB, and MEND models predicted the decrease of SOC pool sizes. Regions initially seeded at higher temperatures saw smaller SOC losses, or even modest gains. This prediction aligns with experimental results predicting SOC losses in Arctic soils (Xue et al., 2016; Natali et al., 2011). Additionally, the observation of damped oscillations matched my own observations in simulations I have run, which makes sense as interactive coupling between SOC and microbial soil (MBC) pools is reminiscent of that observed in predator-prey models, so I was glad to see that confirmed.

Since I really have to go to bed now, I’ll jump straight to questions and future research directions that this paper has evoked. First, instead of a constant 50% thermal acclimation scenario (where m is halved in comparison to the varied CUE scenario), I wonder how changing m to be a function dependent on time (representing adapting mutations) would change things up. Second, this is a question less related to this paper, but with these Earth system biogeochemistry models, the carbon dioxide flux does not feed back into the pools in any way and is entirely separate from the input. How could the atmospheric carbon pool size be fit into these models? As a person new to this sub-field of Earth system biogeochemistry, I’m wondering why atmospheric carbon is not accounted for as an interactive pool in these models.