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. Ecoystems 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.