Objectives

Open questions

The following questions are addressed by the SoilSystems priority programme:

  • How to identify the thermodynamic principles that link carbon and energy use efficiencies to microbial growth and activity dynamics in soil?
  • Does the microbiome, its structural and functional diversity and interacting trophic levels on the turnover and storage of SOM control the energy flux?
  • Do boundary conditions shape or even define the energy use channel in soil?
  • Does a specific substrate and its energy content always result in similar microbial community composition and similar degradation performance in terms of kinetics?
  • What causes the C-stabilization (‘entombing effect´) after conversion to microbial necromass in different soil types?

These questions are condensed to three working hypotheses of SoilSystems. The research requires coupling of experiments on detritus decomposition and SOM formation plus turnover facing two major challenges: (i) understanding the combination of soil organisms, their genetic potential, physiological status and interactions, type and access to resources, and the environmental boundaries and constraints recently termed as `soil metaphenome´ (Jansson and Hofmockel, 2018), and (ii) integrating thermodynamic concepts into soil science by linking theories of systems ecology to energy based approaches.


Hypothesis

SoilSystems developed three main hypotheses on the premises that soils are highly complex, open thermodynamic systems and that the soil ecosystem structure, function and stability are controlled by energy discharge and consumption. It may even be argued that soil microbial biomass as well as SOM can be understood as dissipative structures emerging from the energy and matter fluxes (Fig. 1).

Fig. 1: Experimental Concept for linking balnces and fluxes of heat, enthalpies (H), Gibbs energies (G) of oxidation reactions, losses, efficiencies to matter turnover mass balances of C, H, O, N (S, P). (FIg. modified from Kästner et al., 2014)

SoilSystems addresses the research questions by linking energy and matter fluxes to systems ecology (microbial ecology and diversity; connectedness to higher trophic, faunal levels) and the boundary conditions perspective focussing at first on organic matter (organic carbon) transformation in topsoils from agricultural sites, which are ideal objects for application of energy-based concepts to managed soil systems. Research will focus on the high diversity in the composition of carbon and energy sources connected to the development of microbial communities, their structures and maintenance, and finally necromass stabilisation. The energy and carbon use efficiency (EUE and CUE) as key-parameters linked to the energy use principles on all trophic levels vary with input of substrate matter and energy, whereby reports are inconsistent about the role of influencing factors such as substrates’ energy content, stoichiometry, and molecular structure, as well as nutrients (Spohn et al., 2016; Takriti et al., 2018). Process based knowledge shall be achieved, whether the microbiome of a soil or its constituents and properties, especially the mineral matrix with their nutrient resources are determining the steady state amounts of biomass and SOM in a system with a given input of energy substrates. The analysis of the energy dissipation and matter fluxes, and the microbial ecology of the system will provide the data basis for the assessment of thermodynamic principles in soil ecology and will enable integrated modelling founded on ecosystem properties and processes. The following three hypotheses (A-C) give the general research objectives of SoilSystems.

Hypothesis A

“The microbiome modulates energy dissipation and matter turnover along various energy use channels.” The microbial carbon turnover activity (‘carbon pump’) is part of the energy-use-channel and the dominant `contributor´ to SOM via carbon use and recycling and necromass stabilisation.

Research under this hypothesis will target microbes as energy, organic matter, and nutrient consumers, mass contributors, and `shapers´ of the soil system within the overall frame set by the boundary conditions (see Hypothesis C). Focus will be laid on trophic networks within the microbiome, i.e. the linkage between microorganisms and fauna that are organized by spatial and temporal arrangement within the soil microhabitat architecture thereby modulating SOM turnover. Integrating soil food webs is thus important to understand and manage the processes of SOM regulation, which has not yet been systematically analysed based on a systems ecology view. Studies under this hypothesis will link the energy content and the input and stoichiometry of plant/detritus-derived substrates to the amount and type of degrader biomass formed as well as degradation kinetics under the respective boundary conditions of a given soil, which was not in the focus of previous research.

Projects shall employ thermodynamic theories of systems ecology on the levels of molecules, organisms, and habitats, resulting in extensive interdisciplinary research. Basic thermodynamic approaches that consider the sum of heat fluxes, enthalpies, and Gibbs reaction energy changes available for work will be analysed in relation to turnover and fractions of SOM. Modern ecological methods such as metabolic footprints, combining biomass and activity of biota as functional trait (Ferris, 2010b; Mulder and Maas, 2017) will be applied. Determined parameters can be used for quantitative thermodynamic predictions of biological growth and turnover (Heijnen, 2013).

Hypothesis B

“Energy and matter input, discharge, and consumption in the soil system affect biological complexity, i.e. the structural and functional diversity, trophic networks and organization of the soil microbiome.

Research under this hypothesis will address microbial diversity and complexity in soils that are not random or accidental but a result of various factors. Also, the potential energy yield from substrates entering a (micro)habitat determines the functional diversity of soil biota involved in metabolic transformation. Yet, predictions on how microbial complexity and network structures are shaped by, and how this feeds-back on SOM composition and storage, are highly limited and require more systematic understanding of these factors in relation to microhabitat conditions (e.g. presence of electron acceptors, nutrients, activity of water). In line with the maximum power principle (Odum and Odum, 1981), we hypothesize that syntrophic microbial groups, entire communities or trophic networks able to exploit the highest amount of energy from a particular carbon source for growth and respiration will become dominant in comparison to less efficient competitors. The potential energetic yield from a compound presumably gives the link to functional diversity – in the sense that a function is redundantly provided by diverse communities. In case of redundancy energy yield would be apparently independent from community composition. This has implications for resilience research to be tested against disturbance and changes of boundary conditions (Ludwig et al., 2018). Integrating soil food web interactions will enable to understand and also manage processes of SOM regulation and energy cycling. This, however, still awaits systematic research (Fierer, 2017).

Projects shall address the question how the provided substrate with its energy content, the microbial community composition with their functional traits, and their faunal grazers are interlinked and whether trigger values and tipping points exist, beyond which community and/or pathways and fluxes are sustainably altered.

Hypothesis C

“The boundary conditions and mineral composition shape the channel for energy and matter use.” They constrain the non-equilibrium steady states of living and non-living organic matter in soil.

Research under this hypothesis will focus on the soil mineral composition (parent rock material, secondary minerals) and boundary conditions shaping the energy use channel in soil. Boundary conditions encompass (i) factors of soil formation, such as pedoclimate, (ii) nutrients, (iii) structures (e.g. aggregates) developed upon pedogenesis, and (iv) present physicochemical properties such as pH, redox potential and electron acceptor availability as well as water activity (Mikutta et al., 2009; Turner et al., 2017). These conditions are determinants of the energy channel that can be exploited by the microbiome. Linking functional traits of microbes to mineral composition and boundary conditions and properties of macro- and micro-aggregates (e.g. connectivity, tortuosity and heterogeneity of the 3D pore space) is needed to understand SOM turnover and energy use in the sphere of energy and matter consumption. The resulting composition and spatial arrangement of microhabitats along with the basic principle that self-organization is a feature also of soil systems need to be analysed (Addiscott, 2010; Prigogine and Stengers, 1984).

Studies will investigate the link of functional traits of microbes to SOM turnover and energy use at the scales of macro- and micro-aggregates. Research will give answers to the question in how far boundary conditions are shaping or even driving the energy use channel in soil.

References

Addiscott, T.M., 2010. Entropy, non-linearity and hierarchy in ecosystems. Geoderma 160(1), 57-63.
Ferris, H., 2010. Form and function: Metabolic footprints of nematodes in the soil food web. Europ. J. Soil Biol. 46, 97-104.
Fierer, N., 2017. Embracing the unknown: Disentangling the complexities of the soil microbiome. Nat. Rev. Microbiol. 15, 579-590.
Heijnen, J.J., 2013. A thermodynamic approach to predict black box model parameters for microbial growth. In: U. von Stockar (Ed.), Biothermodynamics – the Role of Thermodynamics in Biochemical Engineering. EFPL Press, Lausanne, Switzerland, pp. 443-460.
Kästner, M., Nowak, K.M., Miltner, A., Trapp, S., Schäffer, A., 2014. Classification and modelling of nonextractable residue (NER) formation of xenobiotics in soil – A synthesis. Crit. Rev. Environ. Sci. Technol. 44, 2107-2171.
Jansson, J.K., Hofmockel, K.S., 2018. The soil microbiome — from metagenomics to metaphenomics. Curr. Opin. Microbiol. 43, 162-168.
Ludwig, M., Wilmes, P., Schrader, S., 2018. Measuring soil sustainability via soil resilience. Sci. Tot. Environ. 626, 1484-1493.
Mikutta, R., Schaumann, G.E., Gildemeister, D., Bonneville, S., Kramer, M.G., Chorover, J., Chadwick, O.A., Guggenberger, G., 2009. Biogeochemistry of mineral-organic associations across a long-term mineralogical soil gradient (0.3-4100 kyr), Hawaiian Islands. Geochim. Cosmochim. Acta 73, 2034-2060.
Mulder, C., Maas, R., 2017. Unifying the functional diversity in natural and cultivated soils using the overall body-mass distribution of nematodes. BMC Ecology 17(1).
Odum, H.T., Odum, E.C., 1981. Energy basis for man and nature. McGraw-Hill Companies.
Prigogine, I., Stengers, I., 1984. Order out of chaos, man’s dialogue with nature. Bantam Books Toronto.
Spohn, M., Pötsch, E.M., Eichorst, S.A., Woebken, D., Wanek, W., Richter, A., 2016. Soil microbial carbon use efficiency and biomass turnover in a long-term fertilization experiment in a temperate grassland. Soil Biol. Biochem. 97, 168-175.
Takriti, M., Wild, B., Schnecker, J., Mooshammer, M., Knoltsch, A., Lashchinskiy, N., Eloy Alves, R.J., Gentsch, N., Gittel, A., Mikutta, R., Wanek, W., Richter, A., 2018. Soil organic matter quality exerts a stronger control than stoichiometry on microbial substrate use efficiency along a latitudinal transect. Soil Biol. Biochem. 121, 212-220.
Turner, S., Mikutta, R., Meyer-Stüve, S., Guggenberger, G., Schaarschmidt, F., Lazar, C.S., Dohrmann, R., Schippers, A., 2017. Microbial community dynamics in soil depth profiles over 120,000 years of ecosystem development. Front. Microbiol. 8, Article No. 874.

upwards


Systems ecology and soil science

The soil system understanding is at its advent and thus needs novel perspectives. A new paradigm was opened with Systems Ecology, targeting an integrated understanding of the biological system in its abiotic environment emphasizing interconnections and organizational structures rather than individual, separated components (Aon et al., 2014; Evans et al., 2013). Changes in external factors (forcing functions) define a further aspect in soil systems research answering the resistance and resilience of the system related to disturbances (e.g. by changing temperatures, moisture status, redox potential, pH, and others) (Göransson et al., 2013; Moyano et al., 2012).

Systems ecology offers up-to-date approaches to unravel the linkages of biotic networks, organism-modulated energy and matter fluxes, related self-regulation processes in soil and abiotic ecosystem components and to identify general underlying principles. Systems ecology relies on both the individual organism and/or compound based community ecology (e.g. metabolic theory) and flux and mass-balance based ecosystem ecology (e.g. system theory) (Jørgensen et al., 2016; Loreau, 2010). Systems ecology approaches are suited to holistically assess matter and energy fluxes and balances and to predict emergent system properties such as SOM storage and turnover. Yet, such approaches were rarely applied to soils (Addiscott, 2010).

Systems ecology is based on (1) hierarchy, (2) thermodynamics, (3) networks, and (4) biogeochemistry (Jørgensen, 2012). Jørgensen et al. (2016) stated that these approaches, each with its own strengths, weaknesses, and perspectives, have often been developed in parallel and further progress arises with their continued integration. They outlined the four approaches:

  1. Hierarchy theory — the understanding of the hierarchical structure of ecosystems with its vertical hierarchies and also control hierarchies, forming an interface to the cybernetic processes of the systems (Nielsen, 2015).
  2. Thermodynamics — the understanding of the use, need, and transfer of energy by ecosystems, with irreversible, dissipative processes working along imposed gradients (Aoki, 2012). They may serve as indicators of functional state or be subjected to optimization by adaptive and selective processes (Nielsen and Jorgensen, 2013).
  3. Network theory — the understanding of the functions and advantages of ecological networks allowing for identification and quantification of interdependence along complex, indirect pathways (Borrett et al., 2014; Patten, 2016).
  4. Biogeochemistry — the understanding of the biogeochemical processes in ecosystems with focus on the cycling of matter and of particular (quantitative important) elements such as C and N, respectively (Morowitz and Smith, 2007).

Expedient thermodynamics-based modelling approaches exist, but they need to be related to soil functioning. For example, systems ecology offers up-to-date approaches to unravel the linkages of biotic networks, organism-modulated energy and matter fluxes, related self-regulation processes in soil and abiotic ecosystem components and to identify general underlying principles. Systems ecology relies on both the individual organism and/or compound based community ecology (e.g. metabolic theory) and flux and mass-balance based ecosystem ecology (e.g. system theory) (Jørgensen et al., 2016; Loreau, 2010). Systems ecology approaches are suited to holistically assess matter and energy fluxes and balances and to predict emergent system properties such as SOM storage and turnover. Yet, such approaches were rarely applied to soils (Addiscott, 2010).

  • The metabolic theory is organism-based, works bottom-up in order to quantify fluxes and stores of energy and materials within organisms and to predict structural and functional characteristics at multiple levels of organization from individual organisms to ecosystems.
  • Systems theory is ecosystem-based, works top-down and quantifies fluxes and stores of energy or materials among functional compartments in order to derive emergent whole-ecosystem properties, i.e. average residence times of carbon and other molecules (Jørgensen et al., 2016).

Researching this experimentally is enabled by top-down approaches, exploiting the new options and novel techniques in life sciences for investigating the `science of the system´ by making use of meta-omics methods (metagenomics, metaproteomics, meta-metabolomics). In complementary bottom-up approaches specific fluxes of organisms, components and energy can be investigated with high spatial and temporal resolution, which approach is boosted by the novel options for low invasive high-resolution methods of visualization and analysis of microscale spatial heterogeneity and to obtain high density data.

 The relevance of the combined matter and energy fluxes is reflected in the ecosystem theory with its propositions acc. to Jørgensen (2012):

  1. Ecosystems are open systems and require an input of free energy (receiving from environment in which they are embedded).
  2. Ecosystems on one hand conserve and on the other hand recycle matter and (most of the) energy.
  3. All ecosystem processes are irreversible, produce entropy and consume free energy.
  4. If an ecosystem receives more free energy than needed to maintain its functions, the surplus will be applied to move the system further away from thermodynamic equilibrium.
  5. As a consequence, ecosystems have emergent system properties.
  6. Ecosystems apply three growth forms, i.e. growth of (i) biomass, (ii) network, (iii) information.
  7. The carbon based life on Earth, has a characteristic basic biochemistry which all organisms share.
  8. Ecosystems are hierarchically organized, forming a complex interactive, self-organizing ecological network.
  9. Ecosystems have a high diversity in all levels of the hierarchy.
  10. Ecosystems have a buffer capacity toward changes.

References

Addiscott, T.M., 2010. Entropy, non-linearity and hierarchy in ecosystems. Geoderma 160(1), 57-63.
Aon, M.A., Lloyd, D., Saks, V., 2014. From Physiology, Genomes, Systems, and Self-Organization to Systems Biology: The Historical Roots of a Twenty-First Century Approach to Complexity. In: M.A. Aon, V. Saks, U. Schlattner (Eds.), Systems Biology of Metabolic and Signaling Networks: Energy, Mass and Information Transfer. Springer Berlin Heidelberg, Berlin, Heidelberg, pp. 3-17.
Borrett, S.R., Moody, J., Edelmann, A., 2014. The rise of Network Ecology: Maps of the topic diversity and scientific collaboration. Ecol. Modell. 293, 111-127.
Evans, M.R., Bithell, M., Cornell, S.J., Dall, S.R.X., Díaz, S., Emmott, S., Ernande, B., Grimm, V., Hodgson, D.J., Lewis, S.L., Mace, G.M., Morecroft, M., Moustakas, A., Murphy, E., Newbold, T., Norris, K.J., Petchey, O., Smith, M., Travis, J.M.J., Benton, T.G., 2013. Predictive systems ecology. Proc. Royal Soc. B: Biol. Sci. 280(1771).
Göransson, H., Godbold, D.L., Jones, D.L., Rousk, J., 2013. Bacterial growth and respiration responses upon rewetting dry forest soils: Impact of drought-legacy. Soil Biol. Biochem. 57, 477-486.
Jørgensen, S.E., 2012. Introduction to Systems Ecology. CRC Press, Boca Raton, FL.
Jørgensen, S.E., Nielsen, S.N., Fath, B.D., 2016. Recent progress in systems ecology. Ecol. Modell. 319, 112-118.
Loreau, M., 2010. Linking biodiversity and ecosystems: Towards a unifying ecological theory. Phil. Transact. Royal Soc. B: Biol. Sci. 365(1537), 49-60.
Morowitz, H., Smith, E., 2007. Energy flow and the organization of life. Complexity 13(1), 51-59.
Moyano, F.E., Vasilyeva, N., Bouckaert, L., Cook, F., Craine, J., Curiel Yuste, J., Don, A., Epron, D., Formanek, P., Franzluebbers, A., Ilstedt, U., Kätterer, T., Orchard, V., Reichstein, M., Rey, A., Ruamps, L., Subke, J.A., Thomsen, I.K., Chenu, C., 2012. The moisture response of soil heterotrophic respiration: Interaction with soil properties. Biogeosci. 9(3), 1173-1182.
Nielsen, S.N., 2015. Second order cybernetics and semiotics in ecological systems-Where complexity really begins. Ecol. Modell. 319, 119-129.
Nielsen, S.N., Jorgensen, S.E., 2013. Goal functions, orientors and indicators (GoFOrIt’s) in ecology. Application and functional aspects-Strengths and weaknesses. Ecol. Indic. 28, 31-47.
Patten, B.C., 2016. The cardinal hypotheses of Holoecology. Facets for a general systems theory of the organism-environment relationship. Ecol. Modell. 319, 63-111.

upwards