Seasonal and interannual variability of Amazon carbon and water vapour exchange in response to the environment
Bart
Kruijt, ALTERRA - WUR, bart.kruijt@wur.nl
(Presenting)
Antonio
Donato
Nobre, INPE, anobre@ltid.inpe.br
Antonio
Ocimar
Manzi, INPA, manzi@inpa.gov.br
Celso
Von
Randow, Wageningen University and Research Centre, celso.vonrandow@wur.nl
Alessandro
Carioca de
Araujo, Free University of Amsterdam, arau@geo.vu.nl
Yadvinder
Singh
Malhi, University of Oxford, ymalhi@ed.ac.uk
Paulo
Jorge
Oliveira, Universidade Fderal Rural da Amazonia, pj@ufra.edu.br
John
Grace, University of Edinburgh, jgrace@ed.ac.uk
Fernando
Cardoso, Universidade de Rondonia, cardoso@unir.br
Nicolau
Priante Filho, Universidade Federal do Mato Grosso, nicolaup@terra.com.br
George
Luiz
Vourlitis, Cal State University San Marcos, georgev@csusm.edu
Yves-Marie
Gardette, Office National de Forets - Brazil, onfbrasil@juruena.com
Leonardo
Deane de Abreu
Sá, Museu Emilio Goeldi, ldsa@museu-goeldi.br
John
H. C.
Gash, Centre for Ecology and Hydrology, jhg@ceh.ac.uk
Eddy
Moors, ALTERRA - WUR, eddy.moors@wur.nl
There are now multi-year eddy-correlation flux data sets from about ten tower sites across the Amazon, available for analysis of environmental sensitivity in carbon and water vapour exchange at various time scales. We will give an overview of these data sets, especially for those in Rondonia, Mato Grosso, Amazonas and around Belem, and, for a subset of these data, analyse which factors are dominant in causing variation over synoptic (weeks) to interannual time periods, looking at primary weather variables such as precipitation, radiation and temperature. Carbon fluxes will be decomposed into Gross Primary Productivity and Ecosystem respiration as far as possible, using filtered daily totals. Evaporative fluxes will be analysed in terms of surface conductance. Existing data suggest a dominance of rainfall as a driving factor for net carbon exchange at several, but not all sites, at monthly scales. The present analysis will show whether this relationship holds for updated data sets and for different time periods, and analyse the possible underlying explanations as well as the predictive power of such relationships. It will also show the benefits and limitations of eddy correlation data for such analysis.
Submetido por Bart Kruijt em 24-MAR-2004
Tema Científico do LBA: CD (Armazenamento e Trocas de Carbono)