de.mpg.escidoc.pubman.appbase.FacesBean
Deutsch
 
Hilfe Wegweiser Datenschutzhinweis Impressum Kontakt
  DetailsucheBrowse

Datensatz

DATENSATZ AKTIONENEXPORT

Freigegeben

Zeitschriftenartikel

Models in country scale carbon accounting of forest soils

MPG-Autoren
http://pubman.mpdl.mpg.de/cone/persons/resource/persons62545

Schrumpf,  M.
Soil and Ecosystem Processes, Dr. M. Schrumpf, Department Biogeochemical Processes, Prof. E.-D. Schulze, Max Planck Institute for Biogeochemistry, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons62608

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

Externe Ressourcen
Volltexte (frei zugänglich)
Es sind keine frei zugänglichen Volltexte verfügbar
Ergänzendes Material (frei zugänglich)
Es sind keine frei zugänglichen Ergänzenden Materialien verfügbar
Zitation

Peltoniemi, M., Thürig, E., Ogle, S., Palosuo, T., Schrumpf, M., Wutzler, T., et al. (2007). Models in country scale carbon accounting of forest soils. Silva Fennica, 41(3): 290. doi:10.14214/sf.290.


Zitierlink: http://hdl.handle.net/11858/00-001M-0000-000E-D5A2-6
Zusammenfassung
Countries need to assess changes in the carbon stocks of forest soils as a part of national greenhouse gas (GHG) inventories under the United Nations Framework Convention on AM Climate Change (UNFCCC) and the Kyoto Protocol (KP). Since measuring these changes is expensive, it is likely that many countries will use alternative methods to prepare these estimates. We reviewed seven well-known soil carbon models from the point of view of preparing country-scale soil C change estimates. We first introduced the models and explained how they incorporated the most important input variables. Second, we evaluated their applicability at regional scale considering commonly available data sources. Third, we compiled references to data that exist for evaluation of model performance in forest soils. A range of process-based soil carbon models differing in input data requirements exist, allowing some flexibility to forest soil C accounting. Simple models may be the only reasonable option to estimate soil C changes if available resources are limited. More complex models may be used as integral parts of sophisticated inventories assimilating several data sources. Currently, measurement data for model evaluation are common for agricultural soils, but less data have been collected in forest soils. Definitions of model and measured soil pools often differ, ancillary model inputs require scaling of data, and soil C measurements are uncertain. These issues complicate the preparation of model estimates and their evaluation with empirical data, at large scale. Assessment of uncertainties that accounts for the effect of model choice is important part of inventories estimating large-scale soil C changes. Joint development of models and large-scale soil measurement campaigns could reduce the inconsistencies between models and empirical data, and eventually also the uncertainties of model predictions.