Show simple item record

Analysis of soil carbon transit times and age distributions using network theories

dc.contributor.author Katul, Gabriel G
dc.contributor.author Manzoni, S
dc.contributor.author Porporato, A
dc.date.accessioned 2011-06-21T17:22:07Z
dc.date.issued 2009-01-01
dc.identifier.issn 0148-0227
dc.identifier.uri https://hdl.handle.net/10161/3995
dc.description.abstract The long-term soil carbon dynamics may be approximated by networks of linear compartments, permitting theoretical analysis of transit time (i.e., the total time spent by a molecule in the system) and age (the time elapsed since the molecule entered the system) distributions. We compute and compare these distributions for different network. configurations, ranging from the simple individual compartment, to series and parallel linear compartments, feedback systems, and models assuming a continuous distribution of decay constants. We also derive the transit time and age distributions of some complex, widely used soil carbon models (the compartmental models CENTURY and Rothamsted, and the continuous-quality Q-Model), and discuss them in the context of long-term carbon sequestration in soils. We show how complex models including feedback loops and slow compartments have distributions with heavier tails than simpler models. Power law tails emerge when using continuous-quality models, indicating long retention times for an important fraction of soil carbon. The responsiveness of the soil system to changes in decay constants due to altered climatic conditions or plant species composition is found to be stronger when all compartments respond equally to the environmental change, and when the slower compartments are more sensitive than the faster ones or lose more carbon through microbial respiration. Copyright 2009 by the American Geophysical Union.
dc.language.iso en_US
dc.relation.ispartof Journal of Geophysical Research: Biogeosciences
dc.relation.isversionof 10.1029/2009JG001070
dc.title Analysis of soil carbon transit times and age distributions using network theories
dc.title.alternative
dc.type Journal article
dc.description.version Version of Record
duke.date.pubdate 2009-12-30
duke.description.issue
duke.description.volume 114
dc.relation.journal Journal of Geophysical Research-Biogeosciences
pubs.begin-page G04025
pubs.issue 4
pubs.organisational-group Civil and Environmental Engineering
pubs.organisational-group Duke
pubs.organisational-group Environmental Sciences and Policy
pubs.organisational-group Nicholas School of the Environment
pubs.organisational-group Pratt School of Engineering
pubs.publication-status Published
pubs.volume 114


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record