Leveraging energy flows to quantify microbial traits in soils. (April 2021)
- Record Type:
- Journal Article
- Title:
- Leveraging energy flows to quantify microbial traits in soils. (April 2021)
- Main Title:
- Leveraging energy flows to quantify microbial traits in soils
- Authors:
- Chakrawal, Arjun
Herrmann, Anke M.
Manzoni, Stefano - Abstract:
- Abstract: Heat dissipation from organic matter decomposition is a well-recognized proxy for microbial activity in soils, but only a few modeling studies have used heat signals to quantify microbial traits such as maximum substrate uptake rate, specific growth rate, mortality rate, and growth efficiency. In this contribution, a hierarchy of coupled mass-energy balance models is proposed to estimate microbial traits encoded in model parameters using heat dissipation and respiration data from glucose induced microbial activity. Moreover, the models are used to explain the observed variability in calorespirometric ratios (CR)—the ratio of heat dissipation to respiration rate. We parametrized four model variants using heat dissipation and respiration rates measured in an isothermal calorimeter during the lag-phase only or during the whole growth-phase. The four variants are referred to as: (i) complex physiological model, (ii) simplified physiological model, (iii) lag-phase model, and (iv) growth-phase model. Model parameters were determined using three combinations of data: A) only the heat dissipation rate, B) only the respiration rate, and C) both heat dissipation and respiration rates. We assumed that the 'best' parameter estimates were those obtained when using all the data (i.e., option C). All model variants were able to fit the observed heat dissipation and respiration rates. The parameters estimated using only heat dissipation data were similar to the 'best' estimatesAbstract: Heat dissipation from organic matter decomposition is a well-recognized proxy for microbial activity in soils, but only a few modeling studies have used heat signals to quantify microbial traits such as maximum substrate uptake rate, specific growth rate, mortality rate, and growth efficiency. In this contribution, a hierarchy of coupled mass-energy balance models is proposed to estimate microbial traits encoded in model parameters using heat dissipation and respiration data from glucose induced microbial activity. Moreover, the models are used to explain the observed variability in calorespirometric ratios (CR)—the ratio of heat dissipation to respiration rate. We parametrized four model variants using heat dissipation and respiration rates measured in an isothermal calorimeter during the lag-phase only or during the whole growth-phase. The four variants are referred to as: (i) complex physiological model, (ii) simplified physiological model, (iii) lag-phase model, and (iv) growth-phase model. Model parameters were determined using three combinations of data: A) only the heat dissipation rate, B) only the respiration rate, and C) both heat dissipation and respiration rates. We assumed that the 'best' parameter estimates were those obtained when using all the data (i.e., option C). All model variants were able to fit the observed heat dissipation and respiration rates. The parameters estimated using only heat dissipation data were similar to the 'best' estimates compared to using only respiration rate data, suggesting that the observed heat dissipation rate can be used to constrain microbial models and estimate microbial traits. However, the observed variability in CR was not well captured by some model variants such as the simplified physiological model, in contrast to the lag- and growth-phase model that predicted CR well. This suggests that CR can be used to scrutinize how well metabolic processes are represented in decomposition models. Graphical abstract: Image 1 Highlights: We propose a mass and energy balance model for estimating microbial traits Main traits considered: growth efficiency, specific growth rate, mortality rate Three variants capture different phases of microbial substrate-induced response The models can reproduce observed heat dissipation and CO2 production rates Heat dissipation data alone can be used to estimate soil microbial traits … (more)
- Is Part Of:
- Soil biology and biochemistry. Volume 155(2021)
- Journal:
- Soil biology and biochemistry
- Issue:
- Volume 155(2021)
- Issue Display:
- Volume 155, Issue 2021 (2021)
- Year:
- 2021
- Volume:
- 155
- Issue:
- 2021
- Issue Sort Value:
- 2021-0155-2021-0000
- Page Start:
- Page End:
- Publication Date:
- 2021-04
- Subjects:
- Calorimetry -- Glucose metabolism -- Parameter estimation -- Microbial activity -- Energy balance -- Microbial model
Soil biochemistry -- Periodicals
Soil biology -- Periodicals
Sols -- Biochimie -- Périodiques
Sols -- Biologie -- Périodiques
Sols -- Microbiologie -- Périodiques
Bodembiologie
Biochemie
631.46 - Journal URLs:
- http://www.sciencedirect.com/science/journal/00380717 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.soilbio.2021.108169 ↗
- Languages:
- English
- ISSNs:
- 0038-0717
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 8321.820100
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 16018.xml