Constraining Carbon and Nutrient Flows in Soil With Ecological Stoichiometry

Robert W Buchkowski,Alanna N Shaw,Gabriel R Smith,Ashley D Keiser,Debjani Sihi

doi:10.3389/fevo.2019.00382

Abstract

Soil organic matter (SOM) is central to soil carbon (C) storage and terrestrial nutrient cycling. New data have upended the traditional model of stabilization, which held that stable SOM was mostly made of undecomposed plant molecules. We now know that microbial by-products and dead cells comprise unexpectedly large amounts of stable SOM because they can become attached to mineral surfaces or physically protected within soil aggregates. SOM models have been built to incorporate the microbial to mineral stabilization of organic matter, but now face a new challenge of accurately capturing microbial productivity and metabolism. Explicitly representing stoichiometry, the relative nutrient requirements for growth and maintenance of organisms, could provide a way forward. Stoichiometry limits SOM formation and turnover in nature, but important nutrients like nitrogen (N), phosphorus (P), and sulfur (S) are often missing from the new generation of SOM models. In this synthesis, we seek to facilitate the addition of these nutrients to SOM models by (1) reviewing the stoichiometric bias—the tendency to favor one element over another—of four key processes in the new framework of SOM cycling and (2) applying this knowledge to build a stoichiometrically explicit budget of C, N, P, and S flow through the major SOM pools. By quantifying the role of stoichiometry in SOM cycling, we discover that constraining the C:N:P:S ratio of microorganisms and SOM to specific values reduces uncertainty in C and nutrient flow as effectively as using microbial C use efficiency (CUE) parameters. We find that the value of additional constraints on stoichiometry vs. CUE varies across ecosystems, depending on how precise the available data is for that ecosystem and which biogeochemical pathways are present. Moreover, because CUE summarizes many different processes, stoichiometric measurements of key soil pools are likely to be more robust when extrapolated from soil incubations to plot or biome scale estimates. Our results suggest that measuring SOM stoichiometry should be a priority for future empirical work and that the inclusion of new nutrients in SOM models may be an effective way to improve precision.

Highlights

Why does some soil organic matter (SOM) persist for hundreds of years while other Soil organic matter (SOM) turns over quickly, rapidly losing its carbon (C), and nutrients? Throughout the twentieth century, most scientists believed that stable SOM was composed primarily of plant compounds that persisted in soil because their complex chemical structures resisted microbial degradation (Brady and Weil, 2007)
Following the new generation of SOM models, we focused on microbial productivity and mineral sorption as primary pathways of SOM stabilization
We discovered that adding stoichiometric information narrowed the range of possible flows, and that the inclusion of elements other than C and N substantially improved the precision of overall flow patterns

Summary

Introduction

Why does some soil organic matter (SOM) persist for hundreds of years while other SOM turns over quickly, rapidly losing its carbon (C), and nutrients? Throughout the twentieth century, most scientists believed that stable SOM was composed primarily of plant compounds that persisted in soil because their complex chemical structures resisted microbial degradation (Brady and Weil, 2007). Microbial residues and necromass can become attached to mineral surfaces or trapped within soil aggregates, rendering them inaccessible to decomposition (Prescott, 2010; Bradford et al, 2013; Cotrufo et al, 2013; Kallenbach et al, 2015; Lehmann and Kleber, 2015; Jilling et al, 2018). These new findings represent a major shift in our understanding of SOM formation, and have spurred the development of a new generation of SOM models. The stoichiometries of plant inputs, SOM, and microbial biomass are known to affect C and nutrient flows in soil (Griffiths et al, 2012; Tipping et al, 2016) but remain absent from many SOM models (Allison et al, 2010; Wieder et al, 2014)

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