Logo image
Combined use of empirical data and mathematical modelling to better estimate the microbial turnover of isotopically labelled carbon substrates in soil
Journal article   Open access   Peer reviewed

Combined use of empirical data and mathematical modelling to better estimate the microbial turnover of isotopically labelled carbon substrates in soil

H. C. Glanville, P. W. Hill, A. Schnepf, E. Oburger and D. L. Jones
Soil biology & biochemistry, Vol.94, pp.154-168
2016
pdf
Published1.91 MBDownloadView
CC BY V4.0 Open Access

Abstract

Agriculture Life Sciences & Biomedicine Science & Technology Soil Science
The flow of carbon (C) through soil is inherently complex due to the many thousands of different chemical transformations occurring simultaneously within the soil microbial community. The accurate modelling of this C flow therefore represents a major challenge. In response to this, isotopic tracers (e.g. C-13, C-14) are commonly used to experimentally parameterise models describing the fate and residence time of individual C compounds within soil. In this study, we critically evaluated the combined use of experimental C-14 labelling and mathematical modelling to estimate C turnover times in soil. We applied C-14-labelled alanine and glucose to an agricultural soil and simultaneously measured, their loss from soil solution alongside the rate of microbial C immobilization and mineralization. Our results revealed that chloroform fumigation-extraction (CFE) cannot be used to reliably quantify the amount of isotopically labelled C-13/C-14 immobilised by the microbial biomass. This is due to uncertainty in the extraction efficiency values (k(ec)) within the CFE methodology which are both substrate and incubation time dependent. Further, the traditional mineralization approach (i.e. measuring (CO2)-C-14/13 evolution) provided a poor estimate of substrate loss from soil solution and mainly reflected rates of internal microbial C metabolism after substrate uptake from the soil. Therefore, while isotope addition provides a simple mechanism for labelling the microbial biomass it provides limited information on the behaviour of the substrate itself. We used our experimental data to construct a new empirical model to describe the simultaneous flow of substrate-C between key C pools in soil. This model provided a superior estimate of microbial substrate use and microbial respiration flux in comparison to traditional first order kinetic modelling approaches. We also identify a range of fundamental problems associated with the modelling of isotopic-C in soil, including issues with variation in C partitioning within the community, model pool connectivity and variation in isotopic pool dilution, which make interpretation of any C isotopic flux data difficult. We conclude that while convenient, the use of isotopic data (C-13, C-14, N-15) has many potential pitfalls necessitating a critical evaluation of both past and future studies.

Details

UN Sustainable Development Goals (SDGs)

This output has contributed to the advancement of the following goals:

#2 Zero Hunger
#13 Climate Action
#14 Life Below Water
#15 Life on Land

Source: InCites

Metrics

1 File views/ downloads
28 Record Views

InCites Highlights

These are selected metrics from InCites Benchmarking & Analytics tool, related to this output

Collaboration types
Domestic collaboration
International collaboration
Citation topics
3 Agriculture, Environment & Ecology
3.45 Soil Science
3.45.112 Soil Carbon Dynamics
Web Of Science research areas
Soil Science
ESI research areas
Agricultural Sciences
Logo image