ORCHIMIC (v1.0), a microbe-driven model for soil organic matter decomposition designed for large-scale applications

Abstract

Abstract. The role of soil microorganisms in regulating soil organic matter (SOM) decomposition is of primary importance in the carbon cycle, and in particular in the context of global change. Modelling soil microbial community dynamics to simulate its impact on soil gaseous carbon (C) emissions and nitrogen (N) mineralization at large spatial scales is a recent research field with the potential to improve predictions of SOM responses to global climate change. We here present a SOM 15 model called ORCHIMIC whose input data that are consistent with those of global vegetation models. The model simulates decomposition of SOM by explicitly accounting for enzyme production and distinguishing three different microbial functional groups: fresh organic matter (FOM) specialists, SOM specialists, and generalists, while implicitly also accounting for microbes that do not produce extracellular enzymes, i.e. cheaters. This ORCHIMIC model and two other organic matter decomposition models, CENTURY (based on first order kinetics and representative for the structure of most current global 20 soil carbon models) and PRIM (with FOM accelerating the decomposition rate of SOM) were calibrated to reproduce the observed respiration fluxes from FOM and SOM and their possible interactions from incubation experiments of Blagodatskaya et al. (2014). Among the three models, ORCHIMIC was the only one that captured well both the temporal dynamics of the respiratory fluxes and the magnitude of the priming effect observed during the incubation experiment.ORCHIMIC also reproduced well the temporal dynamics of microbial biomass. We then applied different idealized changes 25 to the model input data, i.e. a 5 K stepwise increase of temperature and/or a doubling of plant litter inputs. Under 5 K warming, ORCHIMIC predicted a 0.002 K -1 decrease in the C use efficiency (defined as the ratio of C allocated to microbial growth to the sum of C allocated to growth and respiration) and a 3 % loss of SOC. Under the double litter input scenario, ORCHIMIC predicted a doubling of microbial biomass, while SOC stock increased by less than 1 % due to the priming effect. This limited increase in SOC stock contrasted with the proportional increase in SOC stock as modelled by the 30 conventional SOC decomposition model (CENTURY), which cannot reproduce the priming effect. If temperature increased by 5 K and litter input is doubled, the model predicted almost the same loss of SOC as when only temperature was increased.These tests suggest that the responses of SOC stock to warming and increasing input may differ a lot from those simulated

Microbial dynamics and soil physicochemical properties explain large‐scale variations in soil organic carbon

“…Deprotection rate of the SOC protected by the mineral matrix is closely related to this saturation degree (defined as the ratio of existing SOC p to the soil maximum adsorption capacity; Kothawala, Moore, & Hendershot, ; Wang, Post, & Mayes, ). In this study, we did not calculate the maximum adsorption capacity directly, as it is determined by soil physical and chemical characteristics, and there is still no widely recognized method to calculate it (Campbell & Paustian, ; Huang et al, ; Lützow et al, ), The upper limit of SOC p was represented by assuming that the deprotection rate increases exponentially with the pool size of SOC p :where k dp is a coefficient for tuning the relationship between the deprotection rate ( D ) and the pool size of SOC p .…”

“…New theories and soil biogeochemical models have been developed to explicitly represent microbial biomass and physiology (Abramoff, Torn, Georgiou, Tang, & Riley, 2019;Abramoff et al, 2018;Allison, 2012;Campbell et al, 2016;Cotrufo, Wallenstein, Boot, Denef, & Paul, 2013;Huang et al, 2018;Robertson et al, 2019;Wieder, Grandy, Kallenbach, & Bonan, 2014). These microbial models are valuable for testing specific responses of SOC at small spatial scales, such as the effect of short-term priming observed during litter manipulation experiments or the addition of labile organic matter to the incubated soil samples in the laboratory.…”

Soil Organic Matter Temperature Sensitivity Cannot be Directly Inferred From Spatial Gradients

“…Different combinations of reasonable assumptions about microbial and mineral temperature sensitivity resulted in a wide range of SOC stock changes. Although many soil C models have considered and incorporated explicit assumptions about microbial temperature sensitivity (Abramoff et al, , ; Allison et al, ; Finzi et al, ; German et al, ; He et al, ; Lawrence et al, ; Sistla et al, ; Sulman et al, ; Wang et al, ; Wieder et al, ), there are fewer models that consider the temperature sensitivity of mineral sorption (Dwivedi et al, ; Huang et al, ; Riley et al, ; Tang & Riley, ). The wide range of SOC stock changes predicted by varying only mineral sorption assumptions implies that the temperature sensitivity of sorption may be just as important as that of microbial activity in determining total C stock changes with warming.…”

Referee comment

“…Page 1, Line 5-6: Some microbial-explicit decomposition models have included nutrient cycle coupling for example, Abramoff et al, 2017;Sulman et al, 2017;Huang et al, 2018. Page 2, Line 31-32: Likewise, there are some TBMs that have included more mechanistic SOM cycling and there are some microbial SOC models that include nutrient cycling.…”