001     839885
005     20210129231703.0
024 7 _ |a 10.1016/j.geoderma.2017.10.047
|2 doi
024 7 _ |a 0016-7061
|2 ISSN
024 7 _ |a 1872-6259
|2 ISSN
024 7 _ |a WOS:000424178400005
|2 WOS
024 7 _ |a 2128/18681
|2 Handle
037 _ _ |a FZJ-2017-07464
041 _ _ |a English
082 _ _ |a 550
100 1 _ |a Herbst, M.
|0 P:(DE-Juel1)129469
|b 0
|e Corresponding author
|u fzj
245 _ _ |a Correspondence of measured soil carbon fractions and RothC pools for equilibrium and non-equilibrium states
260 _ _ |a Amsterdam [u.a.]
|c 2018
|b Elsevier Science
336 7 _ |a article
|2 DRIVER
336 7 _ |a Output Types/Journal article
|2 DataCite
336 7 _ |a Journal Article
|b journal
|m journal
|0 PUB:(DE-HGF)16
|s 1527166260_22519
|2 PUB:(DE-HGF)
336 7 _ |a ARTICLE
|2 BibTeX
336 7 _ |a JOURNAL_ARTICLE
|2 ORCID
336 7 _ |a Journal Article
|0 0
|2 EndNote
520 _ _ |a The link between carbon turnover model pools and measurable carbon fractions is of key interest for initial parameterisation and subsequent validation of dynamic soil carbon models. In this study we performed the established particle-size fractionation of soils from 54 intensively monitored sites in Germany and from archived samples from 5 other long-term experiments in Germany and the United Kingdom. The Rothamsted carbon (RothC) model was then used to compare the measured soil C fractionation from the 54 intensively monitored sites against modelled pools using spin-up equilibrium runs whilst dynamic (non-equilibrium) model runs were performed when comparing data from the long-term experiments. We detected good agreement between measured soil C fractions and modelled pools, indicated by correlation coefficients of 0.73 and 0.81 for the resistant plant material pool (RPM) and 0.91 and 0.94 for the humus pool (HUM) for the intensively monitored and the long-term sites, respectively. Slightly larger errors were detected for the intensively monitored sites together with a bias in the relationship between the RPM pool and particulate organic matter fraction. This bias detected for the intensively monitored sites indicated that the equilibrium assumption for arable agricultural sites, even though under crop cover for at least 50 years, might not be entirely valid. From the relative mean absolute error of 11% for the HUM pool and 26% for the RPM pool of the combined data set we conform that the measured fractions can be used to estimate the RothC model pools in arable soils. Given the magnitude of these errors, however, we rather suggest to apply the fractionation approach instead of using an equilibrium assumption for the RothC initialisation of arable sites.
536 _ _ |a 255 - Terrestrial Systems: From Observation to Prediction (POF3-255)
|0 G:(DE-HGF)POF3-255
|c POF3-255
|f POF III
|x 0
588 _ _ |a Dataset connected to CrossRef
700 1 _ |a Welp, G.
|0 P:(DE-HGF)0
|b 1
700 1 _ |a Macdonald, A.
|0 P:(DE-HGF)0
|b 2
700 1 _ |a Jate, M.
|0 P:(DE-HGF)0
|b 3
700 1 _ |a Hädicke, A.
|0 P:(DE-HGF)0
|b 4
700 1 _ |a Scherer, H.
|0 P:(DE-HGF)0
|b 5
700 1 _ |a Gaiser, T.
|0 P:(DE-HGF)0
|b 6
700 1 _ |a Herrmann, F.
|0 P:(DE-Juel1)141774
|b 7
|u fzj
700 1 _ |a Amelung, W.
|0 P:(DE-Juel1)129427
|b 8
|u fzj
700 1 _ |a Vanderborght, J.
|0 P:(DE-Juel1)129548
|b 9
|u fzj
773 _ _ |a 10.1016/j.geoderma.2017.10.047
|g Vol. 314, p. 37 - 46
|0 PERI:(DE-600)2001729-7
|p 37 - 46
|t Geoderma
|v 314
|y 2018
|x 0016-7061
856 4 _ |u https://juser.fz-juelich.de/record/839885/files/1-s2.0-S0016706117314581-main.pdf
|y Restricted
856 4 _ |x icon
|u https://juser.fz-juelich.de/record/839885/files/1-s2.0-S0016706117314581-main.gif?subformat=icon
|y Restricted
856 4 _ |x icon-1440
|u https://juser.fz-juelich.de/record/839885/files/1-s2.0-S0016706117314581-main.jpg?subformat=icon-1440
|y Restricted
856 4 _ |x icon-180
|u https://juser.fz-juelich.de/record/839885/files/1-s2.0-S0016706117314581-main.jpg?subformat=icon-180
|y Restricted
856 4 _ |x icon-640
|u https://juser.fz-juelich.de/record/839885/files/1-s2.0-S0016706117314581-main.jpg?subformat=icon-640
|y Restricted
856 4 _ |x pdfa
|u https://juser.fz-juelich.de/record/839885/files/1-s2.0-S0016706117314581-main.pdf?subformat=pdfa
|y Restricted
856 4 _ |y Published on 2017-11-13. Available in OpenAccess from 2019-11-13.
|u https://juser.fz-juelich.de/record/839885/files/postprint_geoderma_2018_herbst.pdf
856 4 _ |y Published on 2017-11-13. Available in OpenAccess from 2019-11-13.
|x icon
|u https://juser.fz-juelich.de/record/839885/files/postprint_geoderma_2018_herbst.gif?subformat=icon
856 4 _ |y Published on 2017-11-13. Available in OpenAccess from 2019-11-13.
|x icon-1440
|u https://juser.fz-juelich.de/record/839885/files/postprint_geoderma_2018_herbst.jpg?subformat=icon-1440
856 4 _ |y Published on 2017-11-13. Available in OpenAccess from 2019-11-13.
|x icon-180
|u https://juser.fz-juelich.de/record/839885/files/postprint_geoderma_2018_herbst.jpg?subformat=icon-180
856 4 _ |y Published on 2017-11-13. Available in OpenAccess from 2019-11-13.
|x icon-640
|u https://juser.fz-juelich.de/record/839885/files/postprint_geoderma_2018_herbst.jpg?subformat=icon-640
909 C O |o oai:juser.fz-juelich.de:839885
|p openaire
|p open_access
|p driver
|p VDB:Earth_Environment
|p VDB
|p dnbdelivery
910 1 _ |a Forschungszentrum Jülich
|0 I:(DE-588b)5008462-8
|k FZJ
|b 0
|6 P:(DE-Juel1)129469
910 1 _ |a Forschungszentrum Jülich
|0 I:(DE-588b)5008462-8
|k FZJ
|b 7
|6 P:(DE-Juel1)141774
910 1 _ |a Forschungszentrum Jülich
|0 I:(DE-588b)5008462-8
|k FZJ
|b 8
|6 P:(DE-Juel1)129427
910 1 _ |a Forschungszentrum Jülich
|0 I:(DE-588b)5008462-8
|k FZJ
|b 9
|6 P:(DE-Juel1)129548
913 1 _ |a DE-HGF
|l Terrestrische Umwelt
|1 G:(DE-HGF)POF3-250
|0 G:(DE-HGF)POF3-255
|2 G:(DE-HGF)POF3-200
|v Terrestrial Systems: From Observation to Prediction
|x 0
|4 G:(DE-HGF)POF
|3 G:(DE-HGF)POF3
|b Erde und Umwelt
914 1 _ |y 2018
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0200
|2 StatID
|b SCOPUS
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)1050
|2 StatID
|b BIOSIS Previews
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0600
|2 StatID
|b Ebsco Academic Search
915 _ _ |a Embargoed OpenAccess
|0 StatID:(DE-HGF)0530
|2 StatID
915 _ _ |a JCR
|0 StatID:(DE-HGF)0100
|2 StatID
|b GEODERMA : 2015
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0150
|2 StatID
|b Web of Science Core Collection
915 _ _ |a WoS
|0 StatID:(DE-HGF)0110
|2 StatID
|b Science Citation Index
915 _ _ |a WoS
|0 StatID:(DE-HGF)0111
|2 StatID
|b Science Citation Index Expanded
915 _ _ |a IF < 5
|0 StatID:(DE-HGF)9900
|2 StatID
915 _ _ |a Peer Review
|0 StatID:(DE-HGF)0030
|2 StatID
|b ASC
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)1060
|2 StatID
|b Current Contents - Agriculture, Biology and Environmental Sciences
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0310
|2 StatID
|b NCBI Molecular Biology Database
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0300
|2 StatID
|b Medline
915 _ _ |a Nationallizenz
|0 StatID:(DE-HGF)0420
|2 StatID
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0199
|2 StatID
|b Thomson Reuters Master Journal List
920 1 _ |0 I:(DE-Juel1)IBG-3-20101118
|k IBG-3
|l Agrosphäre
|x 0
980 _ _ |a journal
980 _ _ |a VDB
980 _ _ |a UNRESTRICTED
980 _ _ |a I:(DE-Juel1)IBG-3-20101118
980 1 _ |a FullTexts


LibraryCollectionCLSMajorCLSMinorLanguageAuthor
Marc 21