Microbial dormancy improves development and experimental validation of ecosystem model

Abstract

Climate feedbacks from soils can result from environmental change followed by response of plant and microbial communities, and/or associated changes in nutrient cycling. Explicit consideration of microbial life-history traits and functions may be necessary to predict climate feedbacks owing to changes in the physiology and community composition of microbes and their associated effect on carbon cycling. Here we developed the microbial enzyme-mediated decomposition (MEND) model by incorporating microbial dormancy and the ability to track multiple isotopes of carbon. We tested two versions of MEND, that is, MEND with dormancy (MEND) and MEND without dormancy (MEND_wod), against long-term (270 days) carbon decomposition data from laboratory incubations of four soils with isotopically labeled substrates. MEND_wod adequately fitted multiple observations (total C-CO 2 and 14 C-CO 2 respiration, and dissolved organic carbon), but at the cost of significantly underestimating the total microbial biomass. MEND improved estimates of microbial biomass by 20-71% over MEND_wod. We also quantified uncertainties in parameters and model simulations using the Critical Objective Function Index method, which is based on a global stochastic optimization algorithm, as well as model complexity and observational data availability. Together our model extrapolations of the incubation study show that long-term soil incubations with experimental data for multiple carbon pools are conducive to estimate both decomposition and microbial parameters. These efforts should provide essential support to future field-and globalscale simulations, and enable more confident predictions of feedbacks between environmental change and carbon cycling.

Dispersal-Based Microbial Community Assembly Decreases Biogeochemical Function

“…As ecosystem process models become more sophisticated (e.g., [44][45][46]), there is a need to improve these models by better understanding the linkages among community assembly processes and ecosystem function. Here, we used an ecological simulation model to highlight the importance of dispersal-based microbial community assembly for biogeochemical function.…”

Soil carbon cycling proxies: Understanding their critical role in predicting climate change feedbacks

“…Recently, a new cohort of soil biogeochemical models has attempted to use a more mechanistic approach to simulating SOM formation and decomposition by explicitly representing microbial dynamics and physically defined, mineral‐associated organic matter pools (Sulman et al., ; Tang & Riley, ; Wang et al., ; Wieder et al., ). A key factor in this push for increased mechanistic representation has been the explicit simulation of mineral‐associated and microaggregate organic matter pools, based on evidence suggesting that these fractions are physically protected from microbial decomposition through mineral–organic bonds and small pore spaces and correspond well with slow‐turnover SOM pools (Baldock & Skjemstad, ; Schmidt et al., ; Six et al., ; Von Lutzow et al., ).…”

Fungal Traits That Drive Ecosystem Dynamics on Land

“…These models are capable of addressing ecosystem feedbacks from shifts in microbial communities and, in doing so, improve their accuracy (32)(33)(34). However, in order to parameterize them, we need better information regarding relationships among relevant traits within fungal taxa (for the trait-based models) and how these traits vary among broad groups of fungi (for the functional group models).…”