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Soil respiration at mean annual temperature predicts annual total across vegetation types and biomes

MPG-Autoren
http://pubman.mpdl.mpg.de/cone/persons/resource/persons62524

Reichstein,  M.
Research Group Biogeochemical Model-data Integration, Dr. M. Reichstein, Max Planck Institute for Biogeochemistry, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons62425

Jung,  M.
Research Group Biogeochemical Model-data Integration, Dr. M. Reichstein, Max Planck Institute for Biogeochemistry, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons62589

Trumbore,  S. E.
Department Biogeochemical Processes, Prof. S. E. Trumbore, Max Planck Institute for Biogeochemistry, Max Planck Society;

Externe Ressourcen
Volltexte (frei zugänglich)

BGC1385.pdf
(Verlagsversion), 384KB

BGC1385D.pdf
(Preprint), 415KB

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Zitation

Bahn, M., Reichstein, M., Davidson, E. A., Grünzweig, J., Jung, M., Carbone, M. S., et al. (2010). Soil respiration at mean annual temperature predicts annual total across vegetation types and biomes. Biogeosciences, 7(7), 2147-2157. doi:10.5194/bg-7-2147-2010.


Zitierlink: http://hdl.handle.net/11858/00-001M-0000-000E-D957-3
Zusammenfassung
Soil respiration (SR) constitutes the largest flux of CO2 from terrestrial ecosystems to the atmosphere. However, there still exist considerable uncertainties as to its actual magnitude, as well as its spatial and interannual variability. Based on a reanalysis and synthesis of 80 site-years for 57 forests, plantations, savannas, shrublands and grasslands from boreal to tropical climates we present evidence that total annual SR is closely related to SR at mean annual soil temperature (SRMAT), irrespective of the type of ecosystem and biome. This is theoretically expected for non water-limited ecosystems within most of the globally occurring range of annual temperature variability and sensitivity (Q(10)). We further show that for seasonally dry sites where annual precipitation (P) is lower than potential evapotranspiration (PET), annual SR can be predicted from wet season SRMAT corrected for a factor related to P/PET. Our finding indicates that it can be sufficient to measure SRMAT for obtaining a well constrained estimate of its annual total. This should substantially increase our capacity for assessing the spatial distribution of soil CO2 emissions across ecosystems, landscapes and regions, and thereby contribute to improving the spatial resolution of a major component of the global carbon cycle.