001     887972
005     20210130010716.0
024 7 _ |a 10.7717/peerj.9750
|2 doi
024 7 _ |a 2128/26236
|2 Handle
024 7 _ |a altmetric:89703359
|2 altmetric
024 7 _ |a pmid:32974092
|2 pmid
024 7 _ |a WOS:000567264100001
|2 WOS
037 _ _ |a FZJ-2020-04558
082 _ _ |a 610
100 1 _ |a Deckmyn, Gaby
|0 0000-0003-3794-7735
|b 0
|e Corresponding author
245 _ _ |a KEYLINK: towards a more integrative soil representation for inclusion in ecosystem scale models. I. review and model concept
260 _ _ |a London [u.a.]
|c 2020
|b PeerJ, Inc.
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 1605801010_4356
|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 relatively poor simulation of the below-ground processes is a severe drawback for many ecosystem models, especially when predicting responses to climate change and management. For a meaningful estimation of ecosystem production and the cycling of water, energy, nutrients and carbon, the integration of soil processes and the exchanges at the surface is crucial. It is increasingly recognized that soil biota play an important role in soil organic carbon and nutrient cycling, shaping soil structure and hydrological properties through their activity, and in water and nutrient uptake by plants through mycorrhizal processes. In this article, we review the main soil biological actors (microbiota, fauna and roots) and their effects on soil functioning. We review to what extent they have been included in soil models and propose which of them could be included in ecosystem models. We show that the model representation of the soil food web, the impact of soil ecosystem engineers on soil structure and the related effects on hydrology and soil organic matter (SOM) stabilization are key issues in improving ecosystem-scale soil representation in models. Finally, we describe a new core model concept (KEYLINK) that integrates insights from SOM models, structural models and food web models to simulate the living soil at an ecosystem scale.
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 Flores, Omar
|0 0000-0003-2760-3015
|b 1
700 1 _ |a Mayer, Mathias
|0 0000-0003-4366-9188
|b 2
700 1 _ |a Domene, Xavier
|0 P:(DE-HGF)0
|b 3
700 1 _ |a Schnepf, Andrea
|0 P:(DE-Juel1)157922
|b 4
700 1 _ |a Kuka, Katrin
|0 P:(DE-HGF)0
|b 5
700 1 _ |a Van Looy, Kris
|0 P:(DE-Juel1)171429
|b 6
700 1 _ |a Rasse, Daniel P.
|0 0000-0002-5977-3863
|b 7
700 1 _ |a Briones, Maria J. I.
|0 P:(DE-HGF)0
|b 8
700 1 _ |a Barot, Sébastien
|0 P:(DE-HGF)0
|b 9
700 1 _ |a Berg, Matty
|0 0000-0001-8442-8503
|b 10
700 1 _ |a Vanguelova, Elena
|0 P:(DE-HGF)0
|b 11
700 1 _ |a Ostonen, Ivika
|0 0000-0001-9043-6083
|b 12
700 1 _ |a Vereecken, Harry
|0 P:(DE-Juel1)129549
|b 13
700 1 _ |a Suz, Laura M.
|0 0000-0003-4742-572X
|b 14
700 1 _ |a Frey, Beat
|0 P:(DE-HGF)0
|b 15
700 1 _ |a Frossard, Aline
|0 0000-0003-1699-6220
|b 16
700 1 _ |a Tiunov, Alexei
|0 P:(DE-HGF)0
|b 17
700 1 _ |a Frouz, Jan
|0 P:(DE-HGF)0
|b 18
700 1 _ |a Grebenc, Tine
|0 0000-0003-4035-8587
|b 19
700 1 _ |a Öpik, Maarja
|0 P:(DE-HGF)0
|b 20
700 1 _ |a Javaux, Mathieu
|0 P:(DE-Juel1)129477
|b 21
|u fzj
700 1 _ |a Uvarov, Alexei
|0 P:(DE-HGF)0
|b 22
700 1 _ |a Vindušková, Olga
|0 0000-0002-7060-2459
|b 23
700 1 _ |a Henning Krogh, Paul
|0 0000-0003-2033-553X
|b 24
700 1 _ |a Franklin, Oskar
|0 P:(DE-HGF)0
|b 25
700 1 _ |a Jiménez, Juan
|0 P:(DE-HGF)0
|b 26
700 1 _ |a Curiel Yuste, Jorge
|0 0000-0002-3221-6960
|b 27
773 _ _ |a 10.7717/peerj.9750
|g Vol. 8, p. e9750 -
|0 PERI:(DE-600)2703241-3
|p e9750 -
|t PeerJ
|v 8
|y 2020
|x 2167-8359
856 4 _ |u https://juser.fz-juelich.de/record/887972/files/peerj-9750.pdf
|y OpenAccess
909 C O |o oai:juser.fz-juelich.de:887972
|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 4
|6 P:(DE-Juel1)157922
910 1 _ |a Forschungszentrum Jülich
|0 I:(DE-588b)5008462-8
|k FZJ
|b 13
|6 P:(DE-Juel1)129549
910 1 _ |a Forschungszentrum Jülich
|0 I:(DE-588b)5008462-8
|k FZJ
|b 21
|6 P:(DE-Juel1)129477
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 2020
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0200
|2 StatID
|b SCOPUS
|d 2020-09-11
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0160
|2 StatID
|b Essential Science Indicators
|d 2020-09-11
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)1050
|2 StatID
|b BIOSIS Previews
|d 2020-09-11
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)1190
|2 StatID
|b Biological Abstracts
|d 2020-09-11
915 _ _ |a Creative Commons Attribution CC BY 4.0
|0 LIC:(DE-HGF)CCBY4
|2 HGFVOC
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)1040
|2 StatID
|b Zoological Record
|d 2020-09-11
915 _ _ |a JCR
|0 StatID:(DE-HGF)0100
|2 StatID
|b PEERJ : 2018
|d 2020-09-11
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0501
|2 StatID
|b DOAJ Seal
|d 2020-09-11
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0500
|2 StatID
|b DOAJ
|d 2020-09-11
915 _ _ |a WoS
|0 StatID:(DE-HGF)0113
|2 StatID
|b Science Citation Index Expanded
|d 2020-09-11
915 _ _ |a Fees
|0 StatID:(DE-HGF)0700
|2 StatID
|d 2020-09-11
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0150
|2 StatID
|b Web of Science Core Collection
|d 2020-09-11
915 _ _ |a IF < 5
|0 StatID:(DE-HGF)9900
|2 StatID
|d 2020-09-11
915 _ _ |a OpenAccess
|0 StatID:(DE-HGF)0510
|2 StatID
915 _ _ |a Peer Review
|0 StatID:(DE-HGF)0030
|2 StatID
|b DOAJ : Blind peer review
|d 2020-09-11
915 _ _ |a Article Processing Charges
|0 StatID:(DE-HGF)0561
|2 StatID
|d 2020-09-11
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0300
|2 StatID
|b Medline
|d 2020-09-11
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0320
|2 StatID
|b PubMed Central
|d 2020-09-11
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0199
|2 StatID
|b Clarivate Analytics Master Journal List
|d 2020-09-11
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