Techniques and Options for Modelling

Soilsystems will build on recent developments in methods that are ideally suited for integrated experimental work on the soil system. This asks for techniques such as:

  1. dynamic balances of enthalpy and Gibbs energy during oxidation combined with matter fluxes and modelling (e.g. nano- to megacalorimetry, DSC, thermogravimetry),
  2. biomarker analysis (e.g. proteins, aminosugars, membrane compounds and lipids), and improved quantitative stable isotope probing (SIP) techniques for the determination of compound turnover and metabolic pathways,
  3. DNA, RNA and protein based (meta‑)omics systems biology approaches for assessment of microbial communities including correlation analyses,
  4. chemical high resolution analyses for metabolome identification and transformation pathway mapping (e.g. LC-QTOF-MS, FT-ICR-MS, Py-GC-MS),
  5. high spatial resolution 3D imaging for soil structure analysis and chemical mapping for visualization of compound fluxes and spatial arrangements like XRT, NanoSIMS, XPS, and (H)SEM.

In order to assess the physiology of microorganisms and for ecological modelling, determination of energy contents and fluxes can be performed in different ways, for example by:

  1. balancing turnover of isotope (stable/radioactive) labelled C-compounds including heat and CO2 in defined batch setups (Pausch et al., 2016a, 2016b);
  2. (nano- and micro)calorimetric analysis of heat production rate from biotic activity (Barros et al., 2007) and/or megacalorimetric determination of total heat balance of micro- to mesocosms (Maskow, 2013);
  3. measuring rates of oxygen uptake that are suited to estimate heat production (‘indirect calorimetry’) and, when related to CO2 evolution, provide a real-time measure for biomass related yield coefficients (Hansen et al., 2004; Maskow, 2013);
  4. determination of enthalpies, and theoretical Gibbs energy or the nominal oxidation state of carbon (NOSC) in SOM or major constituents and selected key compounds as well as in developing biomass and remaining necromass (LaRowe and Amend, 2016; Sinsabaugh et al., 2016; Trapp et al., 2018);
  5. information from ecological stoichiometry on (multiple) resource utilization and carbon use efficiency (CUE) (Geyer et al., 2019; Manzoni et al., 2018; Sinsabaugh et al., 2016; Zechmeister-Boltenstern et al., 2015) and from audit of small molecules (Addiscott, 1995).

Besides numerous expedient SOM models, various thermodynamics and flux related modelling approaches can serve to integrate thermodynamic principles into soil systems theory. Models may be based on, e.g.

  1. throughflow analysis such as the Thermodynamics-based Metabolic Flux Analysis (TMFA; Henry et al., 2007), Thermodynamic Feasibility Analysis (TFA; Maskow and Paufler, 2015; Vojinović and Von Stockar, 2009), Flux-Force relations (Beard and Qian, 2007; Noor et al., 2013) and the Ecological Network Analysis (ENA; Matamba et al., 2009);
  2. Dynamic Energy Budget (DEB) models such as the Metabolic Theory (Aoki, 2012; Kooijman et al., 2008; Schramski et al., 2015);
  3. individual-based modelling allowing to capture emergent behaviour of microbial decomposer communities (Kaiser et al., 2015);
  4. ecological network analysis to reveal inter-connection between microbiome diversity and function (Bascompte, 2007);
  5. thermodynamic organizing principles, such as Maximum Entropy Production (MEP, e.g. Ozawa et al., 2003), Maximum Power (Odum and Pinkerton, 1955), Minimum Energy Expenditure (Rodriguez-Iturbe et al., 1992) and Minimum Dissipation (West et al., 1999);
  6. modelling the potential growth yield of microbes feeding on organic compounds (Microbial Turnover to Biomass, MTB; (Brock et al., 2017; Trapp et al., 2018).

Such approaches can be complemented and refined for their application to SOM turnover.


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