Soil organic matter turnover is governed by accessibility not recalcitrance

Mechanisms to mitigate global climate change by sequestering carbon (C) in different sinks' have been proposed as at least temporary measures. Of the major global C pools, terrestrial ecosystems hold the potential to capture and store substantially increased volumes of C in soil organic matter (SOM) through changes in management that are also of benefit to the multitude of ecosystem services that soils provide. This potential can only be realized by determining the amount of SOM stored in soils now, with subsequent quantification of how this is affected by management strategies intended to increase SOM concentrations, and used in soil C models for the prediction of the roles of soils in future climate change. An apparently obvious method to increase C stocks in soils is to augment the soil C pools with the longest mean residence times (MRT). Computer simulation models of soil C dynamics, e.g. RothC and Century, partition these refractory constituents into slow and passive pools with MRTs of centuries to millennia. This partitioning is assumed to reflect: (i) the average biomolecular properties of SOM in the pools with reference to their source in plant litter, (ii) the accessibility of the SOM to decomposer organisms or catalytic enzymes, or (iii) constraints imposed on decomposition by environmental conditions, including soil moisture and temperature. However, contemporary analytical approaches suggest that the chemical composition of these pools is not necessarily predictable because, despite considerable progress with understanding decomposition processes and the role of decomposer organisms, along with refinements in simulation models, little progress has been made in reconciling biochemical properties with the kinetically defined pools. In this review, we will explore how advances in quantitative analytical techniques have redefined the new understanding of SOM dynamics and how this is affecting the development and application of new modelling approaches to soil C.