A history of research on the link between (micro)aggregates, soil biota, and soil organic matter dynamics

Since the 1900s, the link between soil biotic activity, soil organic matter (SOM) decomposition and stabilization, and soil aggregate dynamics has been recognized and intensively been studied. By 1950, many studies had, mostly qualitatively, investigated the influence of the five major factors (i.e. soil fauna, microorganisms, roots, inorganics and physical processes) on this link. After 1950, four theoretical mile-stones related to this subject were realized. The first one was when Emerson [Nature 183 (1959) 538] proposed a model of a soil crumb consisting of domains of oriented clay and quartz particles. Next, Edwards and Bremner [J. Soil Sci. 18 (1967) 64] formulated a theory in which the solid-phase reaction between clay minerals, polyvalent cations and SOM is the main process leading to microaggregate formation. Based on this concept, Tisdall and Oades [J. Soil Sci. 62 (1982) 141] coined the aggregate hierarchy concept describing a spatial scale dependence of mechanisms involved in micro- and macroaggregate formation. Oades [Plant Soil 76 (1984) 319] suggested a small, but very important, modification to the aggregate hierarchy concept by theorizing the formation of microaggregates within macroaggregates. Recent research on aggregate formation and SOM stabilization extensively corroborate this modification and use it as the base for furthering the understanding of SOM dynamics. The major outcomes of adopting this modification are: (1) microaggregates, rather than macroaggregates protect SOM in the long term; and (2) macroaggregate turnover is a crucial process influencing the stabilization of SOM. Reviewing the progress made over the last 50 years in this area of research reveals that still very few studies are quantitative and/or consider interactive effects between the five factors. The quantification of these relationships is clearly needed to improve our ability to predict changes in soil ecosystems due to management and global change. This quantification can greatly benefit from viewing aggregates as dynamic rather than static entities and relating aggregate measurements with 2D and 3D quantitative spatial information.