Interacting microbe and litter quality controls on litter decomposition: a modeling analysis.

The decomposition of plant litter in soil is a dynamic process during which substrate chemistry and microbial controls interact. We more clearly quantify these controls with a revised version of the Guild-based Decomposition Model (GDM) in which we used a reverse Michaelis-Menten approach to simulat...

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Main Authors: Daryl Moorhead, Gwenaëlle Lashermes, Sylvie Recous, Isabelle Bertrand
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2014-01-01
Series:PLoS ONE
Online Access:http://europepmc.org/articles/PMC4181322?pdf=render
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author Daryl Moorhead
Gwenaëlle Lashermes
Sylvie Recous
Isabelle Bertrand
author_facet Daryl Moorhead
Gwenaëlle Lashermes
Sylvie Recous
Isabelle Bertrand
author_sort Daryl Moorhead
collection DOAJ
description The decomposition of plant litter in soil is a dynamic process during which substrate chemistry and microbial controls interact. We more clearly quantify these controls with a revised version of the Guild-based Decomposition Model (GDM) in which we used a reverse Michaelis-Menten approach to simulate short-term (112 days) decomposition of roots from four genotypes of Zea mays that differed primarily in lignin chemistry. A co-metabolic relationship between the degradation of lignin and holocellulose (cellulose+hemicellulose) fractions of litter showed that the reduction in decay rate with increasing lignin concentration (LCI) was related to the level of arabinan substitutions in arabinoxylan chains (i.e., arabinan to xylan or A∶X ratio) and the extent to which hemicellulose chains are cross-linked with lignin in plant cell walls. This pattern was consistent between genotypes and during progressive decomposition within each genotype. Moreover, decay rates were controlled by these cross-linkages from the start of decomposition. We also discovered it necessary to divide the Van Soest soluble (labile) fraction of litter C into two pools: one that rapidly decomposed and a second that was more persistent. Simulated microbial production was consistent with recent studies suggesting that more rapidly decomposing materials can generate greater amounts of potentially recalcitrant microbial products despite the rapid loss of litter mass. Sensitivity analyses failed to identify any model parameter that consistently explained a large proportion of model variation, suggesting that feedback controls between litter quality and microbial activity in the reverse Michaelis-Menten approach resulted in stable model behavior. Model extrapolations to an independent set of data, derived from the decomposition of 12 different genotypes of maize roots, averaged within <3% of observed respiration rates and total CO2 efflux over 112 days.
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spelling doaj.art-652b175a15634efbb294ab7c653cff9b2022-12-22T01:57:56ZengPublic Library of Science (PLoS)PLoS ONE1932-62032014-01-0199e10876910.1371/journal.pone.0108769Interacting microbe and litter quality controls on litter decomposition: a modeling analysis.Daryl MoorheadGwenaëlle LashermesSylvie RecousIsabelle BertrandThe decomposition of plant litter in soil is a dynamic process during which substrate chemistry and microbial controls interact. We more clearly quantify these controls with a revised version of the Guild-based Decomposition Model (GDM) in which we used a reverse Michaelis-Menten approach to simulate short-term (112 days) decomposition of roots from four genotypes of Zea mays that differed primarily in lignin chemistry. A co-metabolic relationship between the degradation of lignin and holocellulose (cellulose+hemicellulose) fractions of litter showed that the reduction in decay rate with increasing lignin concentration (LCI) was related to the level of arabinan substitutions in arabinoxylan chains (i.e., arabinan to xylan or A∶X ratio) and the extent to which hemicellulose chains are cross-linked with lignin in plant cell walls. This pattern was consistent between genotypes and during progressive decomposition within each genotype. Moreover, decay rates were controlled by these cross-linkages from the start of decomposition. We also discovered it necessary to divide the Van Soest soluble (labile) fraction of litter C into two pools: one that rapidly decomposed and a second that was more persistent. Simulated microbial production was consistent with recent studies suggesting that more rapidly decomposing materials can generate greater amounts of potentially recalcitrant microbial products despite the rapid loss of litter mass. Sensitivity analyses failed to identify any model parameter that consistently explained a large proportion of model variation, suggesting that feedback controls between litter quality and microbial activity in the reverse Michaelis-Menten approach resulted in stable model behavior. Model extrapolations to an independent set of data, derived from the decomposition of 12 different genotypes of maize roots, averaged within <3% of observed respiration rates and total CO2 efflux over 112 days.http://europepmc.org/articles/PMC4181322?pdf=render
spellingShingle Daryl Moorhead
Gwenaëlle Lashermes
Sylvie Recous
Isabelle Bertrand
Interacting microbe and litter quality controls on litter decomposition: a modeling analysis.
PLoS ONE
title Interacting microbe and litter quality controls on litter decomposition: a modeling analysis.
title_full Interacting microbe and litter quality controls on litter decomposition: a modeling analysis.
title_fullStr Interacting microbe and litter quality controls on litter decomposition: a modeling analysis.
title_full_unstemmed Interacting microbe and litter quality controls on litter decomposition: a modeling analysis.
title_short Interacting microbe and litter quality controls on litter decomposition: a modeling analysis.
title_sort interacting microbe and litter quality controls on litter decomposition a modeling analysis
url http://europepmc.org/articles/PMC4181322?pdf=render
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AT gwenaellelashermes interactingmicrobeandlitterqualitycontrolsonlitterdecompositionamodelinganalysis
AT sylvierecous interactingmicrobeandlitterqualitycontrolsonlitterdecompositionamodelinganalysis
AT isabellebertrand interactingmicrobeandlitterqualitycontrolsonlitterdecompositionamodelinganalysis