4.6 Article

Improving understanding of soil organic matter dynamics by triangulating theories, measurements, and models

Journal

BIOGEOCHEMISTRY
Volume 140, Issue 1, Pages 1-13

Publisher

SPRINGER
DOI: 10.1007/s10533-018-0478-2

Keywords

Biogeochemical models; Carbon stabilization; Decomposition; Global carbon cycle; Soil organic matter

Funding

  1. U.S. Geological Survey (USGS)
  2. USDA NIFA [HAW01130-H]

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Soil organic matter (SOM) turnover increasingly is conceptualized as a tension between accessibility to microorganisms and protection from decomposition via physical and chemical association with minerals in emerging soil biogeochemical theory. Yet, these components are missing from the original mathematical models of belowground carbon dynamics and remain underrepresented in more recent compartmental models that separate SOM into discrete pools with differing turnover times. Thus, a gap currently exists between the emergent understanding of SOM dynamics and our ability to improve terrestrial biogeochemical projections that rely on the existing models. In this opinion paper, we portray the SOM paradigm as a triangle composed of three nodes: conceptual theory, analytical measurement, and numerical models. In successful approaches, we contend that the nodes are connected-models capture the essential features of dominant theories while measurement tools generate data adequate to parameterize and evaluate the models-and balanced-models can inspire new theories via emergent behaviors, pushing empiricists to devise new measurements. Many exciting advances recently pushed the boundaries on one or more nodes. However, newly integrated triangles have yet to coalesce. We conclude that our ability to incorporate mechanisms of microbial decomposition and physicochemical protection into predictions of SOM change is limited by current disconnections and imbalances among theory, measurement, and modeling. Opportunities to reintegrate the three components of the SOM paradigm exist by carefully considering their linkages and feedbacks at specific scales of observation.

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