001     862431
005     20210130001346.0
024 7 _ |a 10.1038/s41396-018-0270-2
|2 doi
024 7 _ |a 1751-7362
|2 ISSN
024 7 _ |a 1751-7370
|2 ISSN
024 7 _ |a 2128/22088
|2 Handle
024 7 _ |a pmid:30214028
|2 pmid
024 7 _ |a WOS:000455747900005
|2 WOS
024 7 _ |a altmetric:48232285
|2 altmetric
037 _ _ |a FZJ-2019-02747
082 _ _ |a 570
100 1 _ |a Meredith, Laura K.
|0 P:(DE-HGF)0
|b 0
|e Corresponding author
245 _ _ |a Soil exchange rates of COS and CO18O differ with the diversity of microbial communities and their carbonic anhydrase enzymes
260 _ _ |a Basingstoke
|c 2019
|b Nature Publishing Group
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 1555999357_22955
|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 Differentiating the contributions of photosynthesis and respiration to the global carbon cycle is critical for improving predictive climate models. Carbonic anhydrase (CA) activity in leaves is responsible for the largest biosphere-atmosphere trace gas fluxes of carbonyl sulfide (COS) and the oxygen-18 isotopologue of carbon dioxide (CO18O) that both reflect gross photosynthetic rates. However, CA activity also occurs in soils and will be a source of uncertainty in the use of COS and CO18O as carbon cycle tracers until process-based constraints are improved. In this study, we measured COS and CO18O exchange rates and estimated the corresponding CA activity in soils from a range of biomes and land use types. Soil CA activity was not uniform for COS and CO2, and patterns of divergence were related to microbial community composition and CA gene expression patterns. In some cases, the same microbial taxa and CA classes catalyzed both COS and CO2 reactions in soil, but in other cases the specificity towards the two substrates differed markedly. CA activity for COS was related to fungal taxa and β-D-CA expression, whereas CA activity for CO2 was related to algal and bacterial taxa and α-CA expression. This study integrates gas exchange measurements, enzyme activity models, and characterization of soil taxonomic and genetic diversity to build connections between CA activity and the soil microbiome. Importantly, our results identify kinetic parameters to represent soil CA activity during application of COS and CO18O as carbon cycle tracers.
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 Ogée, Jérôme
|0 0000-0002-3365-8584
|b 1
700 1 _ |a Boye, Kristin
|0 P:(DE-HGF)0
|b 2
700 1 _ |a Singer, Esther
|0 0000-0002-3126-2199
|b 3
700 1 _ |a Wingate, Lisa
|0 P:(DE-HGF)0
|b 4
700 1 _ |a von Sperber, Christian
|0 P:(DE-HGF)0
|b 5
700 1 _ |a Sengupta, Aditi
|0 P:(DE-HGF)0
|b 6
700 1 _ |a Whelan, Mary
|0 P:(DE-HGF)0
|b 7
700 1 _ |a Pang, Erin
|0 P:(DE-HGF)0
|b 8
700 1 _ |a Keiluweit, Marco
|0 P:(DE-HGF)0
|b 9
700 1 _ |a Brüggemann, Nicolas
|0 P:(DE-Juel1)142357
|b 10
700 1 _ |a Berry, Joe A.
|0 P:(DE-HGF)0
|b 11
700 1 _ |a Welander, Paula V.
|0 P:(DE-HGF)0
|b 12
773 _ _ |a 10.1038/s41396-018-0270-2
|g Vol. 13, no. 2, p. 290 - 300
|0 PERI:(DE-600)2299378-2
|n 2
|p 290 - 300
|t The ISME journal
|v 13
|y 2019
|x 1751-7370
856 4 _ |y OpenAccess
|u https://juser.fz-juelich.de/record/862431/files/s41396-018-0270-2.pdf
856 4 _ |y OpenAccess
|x pdfa
|u https://juser.fz-juelich.de/record/862431/files/s41396-018-0270-2.pdf?subformat=pdfa
909 C O |o oai:juser.fz-juelich.de:862431
|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 10
|6 P:(DE-Juel1)142357
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 2019
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0200
|2 StatID
|b SCOPUS
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)1030
|2 StatID
|b Current Contents - Life Sciences
915 _ _ |a Creative Commons Attribution CC BY 4.0
|0 LIC:(DE-HGF)CCBY4
|2 HGFVOC
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0600
|2 StatID
|b Ebsco Academic Search
915 _ _ |a JCR
|0 StatID:(DE-HGF)0100
|2 StatID
|b ISME J : 2017
915 _ _ |a IF >= 5
|0 StatID:(DE-HGF)9905
|2 StatID
|b ISME J : 2017
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 OpenAccess
|0 StatID:(DE-HGF)0510
|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)1050
|2 StatID
|b BIOSIS Previews
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0300
|2 StatID
|b Medline
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0320
|2 StatID
|b PubMed Central
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0199
|2 StatID
|b Clarivate Analytics 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