HR: 1330h
AN: B22A-0799 [PDF]
TI: Spatial analysis of growing season length control over NEE
AU: * Churkina, G
EM: churkina@bgc-jena.mpg.de
AF: MPI for Biogeochemistry, Winzerlaerstr. 10, Jena, 07745
Germany
AU: Schimel, D
EM: schimel@ucar.edu
AF: NCAR, 1850 Table Mesa Dr., Boulder, CO 80307 United States
AU: Braswell, R
EM: braswell@zurueck.sr.unh.edu
AF: University of New Hampshire, Morse Hall, Durham, NH 03824 United States
AU: Trembath, J
EM: jtrembat@srv0.bio.ed.ac.uk
AF: University of Edinburgh, Darwin Building
Mayfield Road, Edinburgh, EH9 3JU
United Kingdom
AU: Falge, E
EM: falge@uni-bayreuth.de
AF: University of Bayreuth, Department of Plant Ecology, Bayreuth, 95440
Germany
AB:
Using data from a large number of flux measurements, analysis of the annual net ecosystem exchange and the length of the
carbon uptake period (CUP, number of days with negative flux) from observations suggest linear correlation between the two.
The change in annual carbon uptake per CUP day differs significantly between forests and non-forests. Forest stands in this
study are mostly young and regrowing. The ratio between mean daily carbon exchange rates during carbon uptake and release
periods is conservative (2.73, with st.dv.1.08) for different vegetation types. It implies that a balance between carbon
release and uptake periods exists despite different photosynthetic pathways, life forms, and leaf habits. The mean daily
carbon sequestration rate of ecosystem never exceeds the carbon emission rate by more then four times. The growing season
length derived from AVHRR NDVI data is closely related to the carbon uptake period and consequently can be used to
approximate annual carbon exchange values of the ecosystems. The suggested approach has a potential for extrapolations of NEE
over large areas from remotely sensed data, while most currently existing techniques still partially rely on modeling for
respiration. Remote detection of growing season length in arid and cloud-covered ecosystem is problematic using data from
AVHRR and requires improved, next generation remotely sensed data.
DE: 0400 Biogeosciences
DE: 1615 Biogeochemical processes (4805)
DE: 1640 Remote sensing
SC: Biogeosciences [B]
MN: 2003 Fall Meeting