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Leveraging energy flows to quantify microbial traits in soils

Chakrawal, Arjun and Herrmann, Anke and Manzoni, Stefano (2021). Leveraging energy flows to quantify microbial traits in soils. Soil Biology and Biochemistry. 155 , 108169
[Research article]

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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' 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.

Authors/Creators:Chakrawal, Arjun and Herrmann, Anke and Manzoni, Stefano
Title:Leveraging energy flows to quantify microbial traits in soils
Series Name/Journal:Soil Biology and Biochemistry
Year of publishing :2021
Volume:155
Article number:108169
Number of Pages:12
Publisher:PERGAMON-ELSEVIER SCIENCE LTD
ISSN:0038-0717
Language:English
Publication Type:Research article
Article category:Scientific peer reviewed
Version:Published version
Copyright:Creative Commons: Attribution 4.0
Full Text Status:Public
Subjects:(A) Swedish standard research categories 2011 > 4 Agricultural Sciences > 401 Agricultural, Forestry and Fisheries > Soil Science
Keywords:Calorimetry, Glucose metabolism, Parameter estimation, Microbial activity, Energy balance, Microbial model
URN:NBN:urn:nbn:se:slu:epsilon-p-111462
Permanent URL:
http://urn.kb.se/resolve?urn=urn:nbn:se:slu:epsilon-p-111462
Additional ID:
Type of IDID
DOI10.1016/j.soilbio.2021.108169
Web of Science (WoS)000626605700014
ID Code:23285
Faculty:NJ - Fakulteten för naturresurser och jordbruksvetenskap
Department:(NL, NJ) > Dept. of Soil and Environment
(S) > Dept. of Soil and Environment
Deposited By: SLUpub Connector
Deposited On:16 Apr 2021 13:03
Metadata Last Modified:16 Apr 2021 13:11

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