001     173296
005     20220930130036.0
024 7 _ |a 10.1016/j.agrformet.2014.10.015
|2 doi
024 7 _ |a 0168-1923
|2 ISSN
024 7 _ |a 1873-2240
|2 ISSN
024 7 _ |a WOS:000347863900013
|2 WOS
024 7 _ |a altmetric:3760559
|2 altmetric
037 _ _ |a FZJ-2014-06707
082 _ _ |a 630
100 1 _ |a Gangi, Laura
|0 P:(DE-Juel1)144570
|b 0
|e Corresponding Author
|u fzj
245 _ _ |a Effect of short-term variations of environmental conditions on atmospheric CO18O isoforcing of different plant species
260 _ _ |a Amsterdam [u.a.]
|c 2015
|b Elsevier
336 7 _ |a Journal Article
|b journal
|m journal
|0 PUB:(DE-HGF)16
|s 1418645371_10607
|2 PUB:(DE-HGF)
336 7 _ |a Output Types/Journal article
|2 DataCite
336 7 _ |a Journal Article
|0 0
|2 EndNote
336 7 _ |a ARTICLE
|2 BibTeX
336 7 _ |a JOURNAL_ARTICLE
|2 ORCID
336 7 _ |a article
|2 DRIVER
520 _ _ |a The oxygen isotope signature of atmospheric carbon dioxide (δ18O–CO2) is significantly influenced by terrestrial vegetation through 18O-exchange between CO2 and leaf water. However, the impact of short-term variations of environmental conditions on this 18O-exchange has not been sufficiently characterized yet for different plant functional types. In the present study, δ18O of CO2 and water vapor were measured online in chamber-based experiments with spruce, wheat, poplar and maize using infrared laser spectroscopy. The impact of the plants on ambient δ18O–CO2 was inferred from the chamber-based CO18O isoforcing (CO18O-Iso), i.e., the product of the net CO2 flux through the chamber and the δ18O–CO2 of this flux obtained from differential measurements at the chamber inlet and outlet. The measured CO18O-Iso was compared to the CO18O isoforcing (CO18O-Isosim) calculated as a function of the δ18O of leaf water at the evaporation site (δ18O–H2Oev) and the degree of oxygen isotope equilibration between CO2 and leaf water (θ). Plants were exposed to elevated air temperature (35 °C) and cessation of water supply. CO18O-Iso was reduced at 35 °C due to the reduction of stomatal conductance (gs) in all plant species except for maize, and at decreasing water availability in all four plant species due to a reduction of θ, assimilation rate (Ar) and gs, while leaf water became progressively 18O-enriched. The combination of θ, gs, Ar and δ18O–H2Oev accounted for up to 98% of the variations in CO18O-Iso, which were well represented by CO18O-Isosim, whereas the relationship between individual determinants and CO18O-Iso was weaker. The degree of isotopic CO2–H2O equilibration calculated from isotopic gas exchange reached maximum values of 0.51 and 0.53 in maize and spruce, and 0.67 and 0.74 in wheat and poplar, respectively. Although θ was highly sensitive to the parameterization of mesophyll conductance (gm), most of the gm literature values for each species yielded values for θ significantly lower than previously reported for the respective plant species. This finding, as well as the observed temporal variations in the oxygen isotopic exchange introduced by varying environmental conditions, should be considered for the parameterization of δ18O–CO2 models.
536 _ _ |a 255 - Terrestrial Systems: From Observation to Prediction (POF3-255)
|0 G:(DE-HGF)POF3-255
|c POF3-255
|x 0
|f POF III
536 _ _ |a 255 - Terrestrial Systems: From Observation to Prediction (POF3-255)
|0 G:(DE-HGF)POF3-255
|c POF3-255
|x 1
|f POF III
588 _ _ |a Dataset connected to CrossRef, juser.fz-juelich.de
700 1 _ |a Tappe, Wolfgang
|0 P:(DE-Juel1)129545
|b 1
|u fzj
700 1 _ |a Vereecken, Harry
|0 P:(DE-Juel1)129549
|b 2
|u fzj
700 1 _ |a Brüggemann, Nicolas
|0 P:(DE-Juel1)142357
|b 3
|u fzj
773 _ _ |a 10.1016/j.agrformet.2014.10.015
|g Vol. 201, p. 128 - 140
|0 PERI:(DE-600)2012165-9
|p 128 - 140
|t Agricultural and forest meteorology
|v 201
|y 2015
|x 0168-1923
856 4 _ |u https://juser.fz-juelich.de/record/173296/files/FZJ-2014-06707.pdf
|y Restricted
909 C O |o oai:juser.fz-juelich.de:173296
|p OpenAPC
|p VDB
|p VDB:Earth_Environment
|p openCost
910 1 _ |a Forschungszentrum Jülich GmbH
|0 I:(DE-588b)5008462-8
|k FZJ
|b 0
|6 P:(DE-Juel1)144570
910 1 _ |a Forschungszentrum Jülich GmbH
|0 I:(DE-588b)5008462-8
|k FZJ
|b 1
|6 P:(DE-Juel1)129545
910 1 _ |a Forschungszentrum Jülich GmbH
|0 I:(DE-588b)5008462-8
|k FZJ
|b 2
|6 P:(DE-Juel1)129549
910 1 _ |a Forschungszentrum Jülich GmbH
|0 I:(DE-588b)5008462-8
|k FZJ
|b 3
|6 P:(DE-Juel1)142357
913 0 _ |a DE-HGF
|b Erde und Umwelt
|l Terrestrische Umwelt
|1 G:(DE-HGF)POF2-240
|0 G:(DE-HGF)POF2-246
|2 G:(DE-HGF)POF2-200
|v Modelling and Monitoring Terrestrial Systems: Methods and Technologies
|x 0
913 0 _ |a DE-HGF
|b Marine, Küsten- und Polare Systeme
|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 1
913 1 _ |a DE-HGF
|b Marine, Küsten- und Polare Systeme
|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
914 1 _ |y 2015
915 _ _ |a JCR
|0 StatID:(DE-HGF)0100
|2 StatID
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 DBCoverage
|0 StatID:(DE-HGF)0150
|2 StatID
|b Web of Science Core Collection
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0199
|2 StatID
|b Thomson Reuters Master Journal List
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0200
|2 StatID
|b SCOPUS
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)1050
|2 StatID
|b BIOSIS Previews
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)1060
|2 StatID
|b Current Contents - Agriculture, Biology and Environmental Sciences
915 _ _ |a IF < 5
|0 StatID:(DE-HGF)9900
|2 StatID
920 1 _ |0 I:(DE-Juel1)IBG-3-20101118
|k IBG-3
|l Agrosphäre
|x 0
980 _ _ |a journal
980 _ _ |a VDB
980 _ _ |a I:(DE-Juel1)IBG-3-20101118
980 _ _ |a UNRESTRICTED
980 _ _ |a APC


LibraryCollectionCLSMajorCLSMinorLanguageAuthor
Marc 21