Publikationsdatum:
2010-07-07
Beschreibung:
Terrestrial gross primary production (GPP) is the largest global CO(2) flux driving several ecosystem functions. We provide an observation-based estimate of this flux at 123 +/- 8 petagrams of carbon per year (Pg C year(-1)) using eddy covariance flux data and various diagnostic models. Tropical forests and savannahs account for 60%. GPP over 40% of the vegetated land is associated with precipitation. State-of-the-art process-oriented biosphere models used for climate predictions exhibit a large between-model variation of GPP's latitudinal patterns and show higher spatial correlations between GPP and precipitation, suggesting the existence of missing processes or feedback mechanisms which attenuate the vegetation response to climate. Our estimates of spatially distributed GPP and its covariation with climate can help improve coupled climate-carbon cycle process models.〈br /〉〈span class="detail_caption"〉Notes: 〈/span〉Beer, Christian -- Reichstein, Markus -- Tomelleri, Enrico -- Ciais, Philippe -- Jung, Martin -- Carvalhais, Nuno -- Rodenbeck, Christian -- Arain, M Altaf -- Baldocchi, Dennis -- Bonan, Gordon B -- Bondeau, Alberte -- Cescatti, Alessandro -- Lasslop, Gitta -- Lindroth, Anders -- Lomas, Mark -- Luyssaert, Sebastiaan -- Margolis, Hank -- Oleson, Keith W -- Roupsard, Olivier -- Veenendaal, Elmar -- Viovy, Nicolas -- Williams, Christopher -- Woodward, F Ian -- Papale, Dario -- New York, N.Y. -- Science. 2010 Aug 13;329(5993):834-8. doi: 10.1126/science.1184984. Epub 2010 Jul 5.〈br /〉〈span class="detail_caption"〉Author address: 〈/span〉Biogeochemical Model-Data Integration Group, Max Planck Institute for Biogeochemistry, 07745 Jena, Germany. christian.beer@bgc-jena.mpg.de〈br /〉〈span class="detail_caption"〉Record origin:〈/span〉 〈a href="http://www.ncbi.nlm.nih.gov/pubmed/20603496" target="_blank"〉PubMed〈/a〉
Schlagwort(e):
Artificial Intelligence
;
Atmosphere
;
Carbon Dioxide/*metabolism
;
*Climate
;
Climatic Processes
;
*Ecosystem
;
Geography
;
Models, Biological
;
Models, Statistical
;
Neural Networks (Computer)
;
Oxygen Consumption
;
*Photosynthesis
;
Plant Leaves/*metabolism
;
Plants/*metabolism
;
Temperature
;
Trees/metabolism
;
Uncertainty
;
Water
Print ISSN:
0036-8075
Digitale ISSN:
1095-9203
Thema:
Biologie
,
Chemie und Pharmazie
,
Informatik
,
Medizin
,
Allgemeine Naturwissenschaft
,
Physik
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